Assignement introduction Advocating Ideal Type Policy for Police Officer Wellness

Chapter 1: Introduction to the Study

The exposure of police officers to excessive amounts of accumulated

stress due to the rigors of police work itself is the focus of my project. The

response, practice, and policy for police officers is incongruent with the degree of

the problem. Occupational stress in law enforcement is inherent, and the officer or

the organization can scarcely control most work-related anxieties. Compounding

officer stress are other variables, such as ample body weight, which may impact

anxiety in some manner. Excessive body weight is one variable which can be

controlled and distresses roughly 80% of America’s police force (Bonauto, Lu, &

Fan, 2014; Hostetter, 2007; Loux, 2015; Shell, 2005). Stress and an overweight

condition comprise a significant health problem for America’s law enforcement

(Arter, 2008; Berset, Semmer, Elfering, Jacobshagen, & Meier, 2011) further

amplified by a lack of policy or incentives to regulate either body weight or stress.

The potential for positive change in governing excess officer body weight via

policy is far-reaching as the officer will be healthier, police agencies, in general,

can reduce various costs, and the public will receive better police services. This

chapter will discuss the benefits further.

This chapter addresses the problem and purpose in greater detail. It

introduces the research questions, similar theoretical frameworks, and the nature

of this study as it impacts human resources and policy analysis. Finally, this

chapter defines the terms as well as assumptions, scope, and limitations of this

study, concluding with an examination of the significance of this research project.

Background

A policy for stress management and regulation of body weight may be

considered part of an ideal scenario for an improved and healthier public safety

workforce (Boyden, 2010). The ability to cope better with vocational daily hassle

stressors has far-reaching outcomes. For police officers, those outcomes are better

health and improved police performance (Boyce, Willett, Mullins, Jones, &

Cottrell, 2014; Can & Hendy, 2014; Chen, 2009; Chikwem, 2017; Neely &

Cleveland, 2013). Moreover, improved police performance translates to a more

tempered officer regarding performance, decision making, and trust building for

the public (Alert et al., 2013; Chen, 2009). Serving the public, carrying a firearm,

and having the responsibility to detain and arrest a citizen contributes to vast daily

stress for police officers (Corrales, 2013; Hansen, 2016).

It is widely accepted that having an unhealthy body weight or being

overweight negatively impacts a person’s health (Azagba & Sharaf, 2012; Milsom

et al., 2014; Van Nuys, 2014). Unhealthy body weight further effects stress

responses in an unknown manner (Gu et al., 2013a; MacDonald, 2007; Proper,

Koppes, Van Zwieten, & Bemelmans, 2013b); stress was found to lead to weight

gain, further compounding the overweight condition (Berset et al., 2011). Without

a public policy directive to manage excessive officer weight and stress, police

officers endure a dual hardship. My research is intended to provide police leaders,

human resource managers, and public policy makers evidence regarding the

consequences and necessity of a policy for weight management and officer stress

to maximize health and welfare. I looked at stress through the lens of the

transactional stress-coping theory. In addition to the stress-coping theory, I

applied Max Weber’s ideal type theory guided the policy proposal purpose and

direction for the study.

Only police officers executing their duties at top efficiency should wield

police authority (Can & Hendy, 2014; Chen, 2009; Envick, 2011). Simply put, the

public can expect police officers who consistently carry out tasks at peak levels of

proficiency to have increased job performance to the society they serve (Hostetter,

2007). Stress and weight management problems of officers are not private

troubles; they are public problems facing public law enforcement organizations

that interact with citizens daily (Dean, 2014; Envick, 2011). Therefore,

complementary policy or incentives should be in place to manage stress and

weight using BMI values as a guideline.

Police work is known to be one of the most stressful occupations (see

Arter, 2008; Can & Hendy, 2014; Chen, 2009; Finney et al., 2013; Gilbert, 2010;

Kyle, 2008; Liberman et al., 2002; McCarty, Zhoa, & Garland, 2007; McCreary

& Thompson, 2006; Neely, 2011; Neely & Cleveland, 2013; Selokar et al., 2011;

Smith, 2013; Stoughton, 2015; Watery & Ussery, 2007; Wang et al., 2014; Yoo,

2007). Police officers are also active representatives of their local government.

Civically disenchanted citizens may project adverse government outlooks onto

officers, which may, in turn, create additional conflict and stress for officers

(Wang et al., 2014). As agents of the local government, officers should benefit

from protections against undue stress and unhealthy activities through the

development of public policy. My research first briefly addressed the effects of

stress on police officers.

Stressors on Law Enforcement Officers

The life expectancy of police officers is years shorter than that of the

average American (Hostetter, 2007; Loux, 2015; Violanti et al., 2013). I discuss

the shorter lifespan of officers in more detail in Chapter 2. For example, retired

police officers in Florida have an average life expectancy of 62 years old

compared to the general population of retired Floridians who live on average to

74 years old (Brevard County Sheriff’s Office, 2011). Factors contributing to this

reduced life expectancy include: (a) stressors of all types, (b) shift work and

overtime work, (c) obesity, and (d) exposure to other professional hazards. A

discussion of stressors for police officers must include being overweight because

people with an average weight tend to respond differently to stressors versus

people who are overweight or obese (Berset et al., 2011; MacDonald, 2007;

Proper et al., 2013b).

Body Mass Index (BMI)

The stress-coping theory postulates decreasing human anxiety through a

problem-oriented coping strategy with any stressor, including overall health and

body weight as stressors (Lazarus & Folkman, 1984). According to Proper et al.

(2013b), people with an overweight condition have increased stress levels

compared to those with appropriate body weight. The BMI formula translates a

person’s height and weight into a whole number value which indicates under,

average, over, and obese weight groups (Centers for Disease Control [CDC],

2017). There are challenges to the accuracy of BMI based on muscle mass, but

BMI is logistically reasonable to use and considered an accurate overall measure

of body fat (Phan et al., 2012). Having a value below 25 indicates an average

weight. A BMI value of 25 or over is considered overweight and dramatically

increases a person’s chances of injury on the job. Proper body weight is important

due to cost effectiveness as fewer injuries can save government agencies money

in health costs.

My project was grounded in the assertion that poor health, and specifically

obesity, is a growing public health concern. MacDonald (2007) described obesity

as America’s new epidemic when the obesity rate was 33.7%. The CDC (2017)

reported the United States obesity rate has increased in America to 36.5% since

then. Even reductions in body weight as small as 5% can decrease an individual’s

chances significantly of experiencing heart disease, diabetes, and other health

issues, even if the subject remains obese (Alert et al., 2013; Jackson, Steptoe,

Beeken, Kivimaki, & Wardle, 2014; Lasikiewicz, Myrissa, Hoyland, & Lawton,

2014; Milsom et al., 2014). I could not locate research that specifically

investigated any relationship between police officers’ stress and BMI. My

research aimed to address this significant gap in the existing academic literature

determine if being overweight or obese predicted stress.

In modern American society, overweight people may be stigmatized and

viewed negatively for merely being overweight. An overweight individual may be

subject to forms of discrimination at work because of high body weight (see

Arnold & Staffelbach, 2012; Bartels & Nordstrom, 2013; Lasikiewicz et al., 2014;

Randle, Mathis, & Cates, 2012). There is a definite link between weight loss and

improved confidence and other physiological benefits (CDC, 2017; Jackson et al.,

2014). Researchers recommended further investigation into the possible

consequences of weight loss. There is a known and understood body of research

regarding stressors for police officers and, separately, the benefits of weight loss.

My research focused on the predictive relationship between different BMI ranges

and police officer stressors.

Weight loss is an extensively researched area. Milsom et al. (2014)

conducted a project in which participants underwent a 12-week weight loss plan.

This experimental weight loss study measured outcome health variables such as

cholesterol and blood pressure. It was discovered that with a mere weight loss of

approximately 4% of their baseline weight, participants reduced several negative

health factors such as high cholesterol and high blood pressure (Milsom et al.,

2014). In the reviewed literature, however, no previous research could be

explicitly found addressing the manner, if any, in which weight reductions might

relate to or predict stress levels of police officers. My project intended to fill this

gap in the literature where the predictive relationship of stress was explicitly

investigated with BMI values of officers.

Reducing Stressors

Kyle (2008) conducted an experiment in which police volunteers watched

a short and humorous movie. After the film, volunteer officers took a self-

reporting stress survey. Kyle also had a control group of officers who observed a

show that was not humorous. All the police officers in the study completed the

same post-stress survey: The State-Trait Anxiety Inventory (STAI). Kyle (2008)

found that exposing officers to the short humorous movie did reduce their stress

levels as measured by the STAI mean score of 4.8. However, the follow-up

survey with the same officers just 30 days later revealed the effects of stress

reduction had dissipated with a mean score on the STAI of 1.0.

Decreasing and managing one’s stress level can increase the quality of life

and work (Barringer & Orbuch, 2013; Lazarus & Folkman, 1984). Human

resource managers and law enforcement policymakers involved with officer

safety and public health standards can use the results of my research to maximize

human capital in law enforcement. On the level of public policy advocacy, my

research could contribute towards the achievement of two goals: (a) forming

policy to assist police officers in lowering their stress levels, and (b) monitoring

and controlling officers’ body weight without discrimination. Since some

association between weight and stress exists (Berset et al., 2011), the dual policy

focus of this study becomes an essential issue for police agencies.

My study assumed that stress is a viable threat to all police officers, which

Dean (2014) validated in his study. Additionally, my study assumed any ability or

knowledge gained in reducing weight and reducing anxiety would benefit police

officers, their families, and the public. Lastly, my study assumed officer

improvements in health and stress would likewise positively influence

performance and execution of the police officers’ duties, in general, thus

benefiting all society. Chikwem (2017) and Hostetter (2007) validated this

assumption as well. People can control body weight, whereas governing stressors

within the profession of law enforcement are predominantly limited (Gerber,

Kellmann, Hartmann, & Puhse, 2010). America in general, and specifically south

Florida, can benefit from officers who do not suffer from high stress (Gerber et

al., 2013; Stoughton, 2015). Articulating the effects of high stress on officers may

encourage and teach officers to manage that stress more effectively. It is

considered a miscarriage of government policy-making for police administrators

to ignore the need for policy in managing police stress (Bardach, 2012).

Problem Statement

Being overweight is widely accepted as producing adverse health effects.

It is well documented to have an unknown impact on stress (Gerber et al., 2013;

Gu et al., 2013a; Proper, 2013b). Perry (2012) found that obesity was prevalent in

America and 68% of the population is overweight. These statistics are steadily

rising on an annual basis and currently are estimated at 75% (CDC, 2017;

Thompson, 2004a). American police officer populations exceed this figure at 80%

(Bonauto et al., 2014; Hostetter, 2007; Loux, 2015; Shell, 2005). Despite the

known damaging effects of being overweight, numerous Florida Sheriff’s Office’s

do not have a mandatory BMI regulation policy in place for employees. The state

of Florida does not have a mandatory fitness standard for officers either (Florida

Department of Law Enforcement [FDLE], 2017).

Further, only a medical physical is required for employment to be a police

officer in Florida. During the police recruit stage, the Florida police candidate

must complete a short physical ability test (PAT) in under 6 minutes and 4

seconds. Bardach (2012) suggested protective policy construction by defining a

public policy problem of excess. For overall health, police officer stress and an

overweight physique are problems of excess. Furthermore, this problem directly

relates to the “failure of the government to function well in an area which it is

traditionally expected to act effectively” (Bardach, 2012, p. 3).

The specific problem is the lack of BMI policy standards for police

officers. Stress and high BMI values are linked in some manner (Berset et al.,

2011; Proper et al., 2013b). This lapse in BMI policy negatively impacts officers’

health, job performance, and even stress (Can & Hendy, 2014; Chikwem, 2017).

Not managing officer BMI leads to a reduction in the overall efficiency of the

police department (Boyden, 2010), and it may arguably signal a grave health

problem among police officers. The performance of the police officer’s duties

calls for managing alternating periods of sedentary work, interspersed with

exceptional, albeit often short, extreme stressful work episodes (Burchfiel,

Anderson, & Straka, 2011; Corrales, 2013; Stoughton, 2015).

Law enforcement leaders, administrators, county managers, and scholars

have neglected to address the problem of overweight police officers by

formulating policy. The unintended consequences of this may have implications

for all law enforcement agencies. Understanding that high BMI is detrimental to

health, it is only a logical response for leaders to develop an ideal type of policy

encouraging programs and treatments that can effectively govern healthy BMI

among police officers without discrimination of the employee.

The ability to systematically reduce BMI among police officers, leading to

improved health and lower stress, which then leads to enhanced work

performance, is a goal of this study. Further to this goal, the primary purpose is to

direct action policy formation to minimize and regulate BMI, and thereby

theoretically reduce the stress levels of police officers. The implications of

healthy weight coupled with decreased stress for officers might even impact their

diminutive life expectancy (Violanti et al., 2013). Enforcing standards or setting

specific goals must be job task-specific and avoid employee discrimination.

Neglected areas of research include experiments, treatments, and programs to

systematically lower police officer BMI as well as address the relationship stress

plays with BMI.

Purpose of the Study

The part that weight plays in relation to stress in law enforcement is barely

known. With wellness and officer safety issues at stake, the primary purpose of

my quantitative survey project is to propose a sound and informed policy option

for controlling body weight and possibly stress management, grounded on the

ideal type theory. Research evidence can advise policymakers further based on the

relationship between stress and BMI of police officers. My research discussed

both the deep-rooted problems stress causes as well as the harmful outcomes of

being overweight. My research intended to explore a predictive correlation

between BMI and stress, which could initiate policy formation in officer stress

reduction.

According to the transactional coping theory, also known as the stress-

coping theory, applying a problem-oriented coping solution to a stressful

condition will relieve that stressor (Lazarus & Folkman, 1984). Applying this

theory as an example, if a low-calorie diet is adopted to solve the overweight

problem, then the participant will lose weight, and the stress related to that

problem will decrease. What is unknown is if the opposite effect may occur; such

as that a weight loss regimen may increase stress. My research addressed the

transactional stress-coping theory further and filled a gap in the current literature

by analyzing the relationship between BMI and stress for officers. My study used

a Likert scale police stress survey, which displayed police officers’ stress as the

dependent variable (continuous, interval level) that is being affected by the

independent variable (continuous, interval level) of BMI.

Certified police officers from a midsized agency in South Florida

compromise this cross-sectional quantitative survey design study. The police

stress questionnaire is the survey tool used to examine and collect officer stress

data, and it is a previously designed, reliable, and valid questionnaire. This police

stress questionnaire is the survey tool and is a two-part Likert scaled self-

administered police stress-specific examination. I used a multiple linear

regression to measure the strength and direction of this relationship and predict

the effect between BMI and stress. I discuss the covariates in more detail in the

next chapter. I gathered several additional independent control variables such as

rank, seniority, shift work, gender, age, and marital status as well.

My project also expanded the existing body of knowledge regarding

officer stress, weight, and manners of coping with anxiety. Berset et al. (2011)

said stress influences weight gain, which begins the harmful cycle policymakers

must address. Research on stress and weight in law enforcement may affect public

policy formation processes and help begin an education initiative to resolve this

threat. My research was vital due to the real hazards stress and high BMI pose to

police. Finally, my research tested the transactional coping theory, via the police

stress questionnaire survey, and applied the ideal type theory, encapsulated by the

research questions.

Research Questions and Hypothesis

There is no research to compare stress between officers of varying body

weight. I have deductively tested the transactional stress-coping theory based on

BMI and officer stress to provide insight regarding stress coping solutions to

officer stress. The ideal type theory was the framework employed to distinguish

how well the concept of healthy body weight compared to actual body weights

within police departments today.

Most people understand police officers should have some degree of fitness

and well-being to be successful in their jobs and maintaining a healthy body

weight helps cope with stress (Berset et al., 2011; MacDonald, 2007). If police

departments are to successfully drive down health-related issues and stress within

their organizations to improve performance and decrease adverse events, it makes

sense to try to start improving health through policy from the top down. Weber’s

theory is hierarchical from the highest ranking administrators of an agency

downward, as he knew the best way to implement policy change was through the

organization and how leaders influenced behavior (Kiser & Schneider, 1994).

This study has two research questions, which are as follows:

RQ1: Will BMI significantly contribute to the percent change of R

variance accounted for in the predictive effect of self-reported organizational

stress in the past 6 months among south Florida police officers, after controlling

for age, gender, rank, marital status, shift work, and seniority?

1: BMI, when combined with stress, will not significantly contribute to

the percent change of R

variance accounted for in the predictive effect of self-

reported organizational stress in the past 6 months among south Florida police

officers, after controlling for age, gender, rank, marital status, shift work, and

seniority.

1: BMI, when combined with stress, will significantly contribute to the

percent change of R

variance accounted for in the predictive effect of self-

reported organizational stress in the past 6 months among south Florida police

officers, after controlling for age, gender, rank, marital status, shift work, and

seniority.RQ2: Will BMI significantly contribute to the percent change of R

variance accounted for in the predictive effect of self-reported operational stress

in the past 6 months among south Florida police officers, after controlling for age,

gender, rank, marital status, shift work, and seniority?

2: BMI, when combined with stress, will not significantly contribute to

the percent change of R

variance accounted for in the predictive effect of self-

reported operational stress in the past 6 months among south Florida police

officers, after controlling for age, gender, rank, marital status, shift work, and

seniority.

2: BMI, when combined with stress, will significantly contribute to the

percent change of R

variance accounted for in the predictive effect of self-

reported operational stress in the past 6 months among south Florida police

officers, after controlling for age, gender, rank, marital status, shift work, and

seniority.

The dependent variable was self-reported levels of stress (management

and life satisfaction among police officers) measured via a Likert-type two-part

police stress specific survey. The independent variable was BMI measured using

the participants’ height divided by weight. The time in police service has been

found to be positively associated with stress and coping ability (Wang et al.,

2014). Smith (2013) said marriage in law enforcement was a positive factor in

coping with stress. Shift work also adds to stress (Gerber et al., 2013; Wirtz &

Nachreiner, 2012). Job rank is an organizational factor also increased anxiety

(Johnson, 2012; Zachar, 2004). Age and gender demographic information was

collected as well from subjects as these variables also increase or decrease stress

in some manner. These variables are discussed further in Chapter 2.

The officers for my project were volunteers in a single-stage cross-

sectional stratified sampling design. The police stress questionnaire survey is a

research tool instrument specifically predesigned and tested to measure levels of

stress among police officers. The device comprised one scaled survey (see

Appendix A) with two parts, organizational and operational stressors, which

query police subjects on 20 questions relating to either organizational or

occupational stressors (McCreary & Thompson, 2006). A standard effect size of

103 police officers was the minimum output recommended via preliminary

G*Power analysis. I solicited more participants, as oversampling will occur and

the more participants that are in my study, the higher the statistical power will be.

I selected a multiple linear regression analysis to evaluate the relationships

between my variables and covariates.

Connotations of stress management, stress-coping experiences, and

reactions to solving stressors are all grounded in the stress-coping process theory

(Lazarus & Folkman, 1984). This psychological theory applied to reduce officer

stress can direct public policy in this area. Understanding that a healthy weight

and a certain amount of fitness is needed in a perfect state but is not present in the

real world is grounded in the ideal type theory.

Theoretical Framework

The research questions and stress are associated. The stress-coping process

theory, also known as the transactional stress and coping theory, is one of the

theoretical frameworks of my study. This theory explains how people can

successfully cope with stressors. The stress-coping theory is a principle which

applies to any situation or profession where the person experiences stress,

including law enforcement. Lazarus and Folkman (1984) focused on how

processing and appraising stressors impacted stress management. The stress-

coping theory presented a framework for understanding how humans may react

when exposed to a psychological stressor (Lazarus & Folkman, 1984). A more

detailed explanation of this theory is in Chapter 2 of my project.

Once identifying a threat stressor, even if it is merely a daily hassle form

of stress, people must assess and reassess the threat and solution. It is through an

interpretive process that stress management leads to resolution, which leads to

active coping. Coping is a practice in which the subject under stress attempts to

relieve or resolve the source of tension and its impacts. Reassessment of the

stressor may include a cognitive resolution of changing one’s view of the stressor

event (Randle et al., 2012). If a problem-oriented response to stress can reduce

anxiety, policymakers could use this evidence to guide policy formation.

My project sought to contribute to the literature by improving a better

understanding of the relation between BMI and stress among police officers and

advocate policy based on evidence provided by testing this theory.

Conceptual Framework

The research questions rely on advocating an ideal policy for officer

health. The ideal type refers to a perfect model or universe, and it represents

multiple subjective viewpoints of a problem. An ideal policy might exist in a

logical sense; however, the ideal type theory directs policy implementation from

an ought to exist perspective (Wagner & Harpfer, 2014) Bartels (2009) said

Weber’s ideal type could inform policy on modern issues, such as stress and high

BMI values. This framework of producing and using ideal type models for public

administration theory has significant usefulness in forming policy. My research

included best practices from several South Florida police agencies’ fitness

standards to propose a variety of conceptual policies and incentive programs.

Weber believed in an institutional position, where public agencies and the

press held much responsibility in how society functioned (Hardt & Heyer, 2003;

Norkus, 2004). High levels of stress lead to more problems than just health issues

for police officers (Arter, 2008); it possibly makes it tougher to hire police

officers, as people will not want a job that causes them significant stress and

health concerns without impressive compensation and benefits packages. Even

then, the most qualified of police officers may not be interested in the profession

(Jarmillo, Nixon, & Sams, 2005). Comparing other agency best practices in

wellness policies fulfill the ideal type theory requisite of comparing reality in

Chapter 2.

Using an agency-oriented approach is vital to implement wide-scale

changes throughout a police department or other public organization (Cockerham,

2005). Research and resulting initiatives to improve officer health and BMI

should not be targeted directly at overweight or obese police officers. Instead,

changes should influence and inform the top administrators at the policy level.

Ideal type theory reasons it is most useful to turn ideas into practice through what

would be ideal and what is possible (see Baehr, 2011; Cahnman, 1965; Dickens &

Murphy, 2005; Harrington, 2008; Kemple, 2013; Redding, 2005). In basic terms,

applying the ideal type theory is so that policies can be developed to address

policy problems such as stress. In the case of police officers and their weight, I

researched which policies and habits yielded the ideal body weight and stress

levels to develop a program that encourages more police officers to operate at this

fitness level. Chapter 2 will explain the ideal type theory in greater detail. The

research questions and relationship between BMI and stress was grounded in this

framework.

Nature of the Study

My quantitative survey research tested the stress-coping theory and

applied the ideal type theory to policy construction by gleaning police stress

survey data from South Florida police officers. Determining the power and

direction of the relationship between body weight and stress of officers via survey

data comprised the analysis. I administered a survey to volunteers solicited

through bulletin board postings and professional department emails. A multiple

linear regression analysis assessed how officer body weight is related to officer

stress.

Measurement and Materials

My research determined the interplay between BMI and officer stress if

any. A comparison of the officers’ survey data fulfilled this goal. This project

required controls for accuracy; I calculated BMI uniformly for all volunteers.

Stress was the dependent variable. BMI was the independent variable. The

literature review discussed additional covariates, such as rank, shift work,

seniority, gender, sex, and marital status in more detail. The following protocols

comprised the investigative survey procedure:

I reliably measured body weight and height of each volunteer. Participants

completed the Likert scaled police stress survey, measuring psychological self-

reported stress.

Data was collected from subjects using these stress surveys, and I

entered it directly into the statistical package for social sciences (SPSS). This

software package analyzes statistical data. A multiple linear regression analysis

was the primary statistical analysis used to determine the relationships between

these variables.

Definitions

I identify variables and other terms used in my study here. I employed the

following definitions for this research:

Body Mass Index: A calculation derived from a person’s weight in pounds

divided by the square of height in feet. This value index determines if a person is

at a healthy weight, overweight, or obese. The body mass index value for a

healthy weight is below 25 (< 24.9; CDC, 2017). This assessment is used to group

people into classes, but it is not exhaustive regarding the total health of a subject.

BMI is the independent variable in this study.

Burnout: The body’s inability to adequately cope with continued stress

(Wang et al., 2014). Stressors without a problem-reconciling response or

successful coping in some form result in prolonged stress. Burnout is synonymous

with anxiety (Lazarus & Folkman, 1984). Everyday stress is not to be confused

with post-traumatic stress syndrome (PTSD), which is a prolonged condition of

residual anxiety usually due to a single large-scale stressor event.

Certified Police Officer: A person who holds a state certification for law

enforcement. This person is authorized to enforce laws, typically carries a firearm

as part of their duties, and protects citizens as well as upholds the constitution. In

my research, certified officers include correction, patrol, probation, and federal

personnel.

Obese or Obesity: A condition where the body weight of an individual is

significantly above the healthy weight recommended by the BMI formula. The

BMI value for obese individuals in the United States is 30 and over (BMI +30;

CDC, 2017).

Occupational and Organizational Police Stress Questionnaire: A two-

part survey tool specially created to measure the stress of police officers

(McCreary & Thompson, 2006). It features 20 questions, rating police officer

occupation and organization-specific stressors as an ordinal variable based on a

Likert scale.

Overweight: A condition where the body weight of an individual is over

the healthy weight recommended by the BMI. The BMI value for overweight

individuals in the United States is over 25 and under 30 (BMI = 25.0 - 29.9; CDC,

2017).

Rank: An organizational hierarchy where the participant identifies as an

employee, line supervisor, middle manager, or administrator for the agency.

Zachar (2004) said rank might decrease stress. Rank was a control variable for

this study.

Seniority: Also referred to as time in the current career, in the context of

this study, this is how long a participant has been working as a certified police

officer. Wang et al. (2014) found time in police service to impact stress

negatively. Seniority was a covariate for this study.

Shift Work: A schedule of labor where the employee does not work

standard Monday through Friday daytime hours. Shift work usually encompasses

working weekends, holidays, and night shifts, and also includes any on-call status.

On-call status is where the employee is subject to work recall during their off-

duty time (Gerber et al., 2013; Wirtz & Nachreiner, 2012). Shift work was a

covariate for this study.

Stress: Any common or uncommon stimulus, physiological or physical,

that causes a mental change or response in a human. The most dangerous change

is usually adverse and can include the most common daily hassles which deplete

the ability to function correctly (Lazarus & Folkman, 1984). Stress is virtually

synonymous with the term burnout in this study. Stress was the dependent

variable in this study.

Assumptions

Certain assumptions are necessary for my research. This project assumed a

law enforcement agency would undergo whatever steps are necessary to safeguard

its officers from all threats, external and internal. Additionally, I assumed that

investigating the relationship between BMI and stress may create an ideal state to

construct public policy to protect officers. Furthermore, my research assumed a

level of trust between police officers and the law enforcement agency. The

transactional model of stress and coping may be applied uniformly to law

enforcement officers as well as other populations to cope with stress. The police

stress questionnaire survey for this project has external and internal validity for

measuring police occupational stress and operational stress. Based on the internal

validity of the project, I assumed officers who participated in my research project

will be thorough in their assessment of present stress and will answer the

operational and occupational stress surveys honestly. I assumed those officers

who participated in my research project were truthful with their answers assessing

stress and disclosing demographic information. Based on external validity, I

assumed the sample population of police officers who volunteered for this study

are representative of the greater population of police officers from South Florida.

These assumptions were necessary for this research to ensure validity and

reliability and attain generalization of my research findings.

Scope and Delimitations

Excessive body weight in law enforcement is a validated problem

affecting 80% of officers (Bonauto, Lu, & Fan, 2014; Hostetter, 2007; Loux,

2015; Shell, 2005). Controlling body weight is feasible. My research focuses on

body weight, mainly because it can be controlled and may influence stress;

although conversely, stress may also influence body weight (Berset et al., 2011).

Officer stress is virtually uncontrollable by the nature of the occupation but might

increase or decrease body weight. This research addressed these delimitations.

For internal validity, the population of police officer survey participants may not

be representative of the universe of police officers in the United States. External

validity limitations addressed specific research techniques, and assumptions were

employed in my research design to maximize generalizability. However, foregone

conclusions cannot be guaranteed when extending my results to other similar

populations. In construct validity, the delimitations are that the variables are

adequately defined, and the measuring tool for stress is as accurate and validated

as I researched it. Delimitations regarding covariate variables are that numerous

variables were identified in the literature review and considered for this project. It

is unknown how many more variables might have impacted these main study

variables.

Research Population

Male and female officers comprised the survey population from a

midsized police agency in southern Florida with roughly 1,000 certified officers

employed total. A volunteer sample made the participants in this research of

certified police officers. The participants were solicited through their agency via

bulletin board postings and professional email, providing a valid cross-section of

the agency. One-hundred and three officers fulfilled the preliminary G*Power

requirements for a multinomial two-tailed linear regression analysis. I will discuss

the analysis further in Chapter 3.

I reviewed the coping resources inventory for stress developed in 1993 for

use in this study. However, the Police Stress Questionnaires are more thorough in

stress ratings and better suited due to their specificity towards police officers, and

their rigorous and more recent development than the coping resources inventory. I

also considered the Overall Satisfaction Scale, the Malasch Burnout Inventory,

and the Depression Anxiety Stress Scale tools; however, I dismissed them due to

their lack of specificity towards police officer stress.

Limitations of the Study

By the nature of the cross-sectional design, there were some inherent

limitations. Regarding the research methodology, my research project had the

following limitations. Differences in culture exist, and I did not measure them in

this investigation. Responses to the Police Stress Questionnaire will be self-

reported and may contain prevarication bias. The environment may also play a

part in this investigation; however, I did not consider in this project. This project

was limited to officers in a medium sized police agency in South Florida.

Participants may not fully understand their stress and how to measure it on the

Likert scale. No one can know how much the subject’s behavior was

compromised or affected by the researcher’s participant-observer presence. The

behavior of police officer participants in South Florida may differ significantly

from any other police officers in the universe of police officers. No one can know

how many other variables may impact stress.

Sampling Process

I used a single stage cross-sectional stratified sample to create logical

inferences about the behavior of this population. I collected subject information

via the stress survey questionnaires. Subjects completed self-evaluations of their

conditions, rating their levels of stress on the appropriate Likert scales. The

anonymous nature of the study controlled for external factors that could influence

respondents’ answers, such as fear of how the agency or I would perceive them. I

conducted sampling by soliciting volunteers and stratifying the sampling to match

police agency BMI group proportions.

Data Collection Management

I managed the data collection regarding subject BMI and stress levels and

was the sole administrator to keep confidentiality. No one else had access to the

data or summary. The data collection and storage were under my sole control. A

standard informed consent form, specific for my project was part of this research,

compliant with all relevant human subjects’ ethics and requirements.

A Likert-type scale is a standard tool for investigation. This form of

survey is simple; using it to survey officer stress is straightforward and logical.

The Likert scale queries participants to decide on questions with answers that

range from Strongly Agree to Strongly Disagree (Oddgeir, Martinussen, &

Rosenvinge, 2006; “The Likert Scale,” 2014). Since I used a pool of at least 100

police officer subjects who volunteered for this study, this favored a stratified

sample. This sample included BMI grouping stratification to represent actual

body weight groups of the population.

Significance of the Study

Law enforcement is a stressful career (Liberman et al., 2002; McCarty et

al., 2007; McCreary & Thompson, 2006). Overall, police officers are subject to

higher levels of stress than other types of employees, which can further negatively

affect BMI levels (Berset et al., 2011). Leaders can improve officer performance

by developing public policies for recommended BMI restrictions; my research can

inform such public policy formation using concrete data. Jaramillo et al. (2005)

researched police officer stress and discovered how internal stress negatively

affects police officers at the organizational level in regard to reduced

performance. Officers’ intention to stay with the agency or seek employment

elsewhere is based on stress as well. Experienced officers of high tenure are the

victims of even higher levels of stress. Zachar (2004) recommended stress

management programs and other creative interventions to provide relief to

officers. As stress increases, officer performance will decrease (Chikwem, 2017;

Shane, 2008). Over 50% of officers believe agencies should sponsor a fitness

program, and more than 50% of police rate fitness for officers as very important

(Haberman, 2012; Lee, 2003).

Significance to Theory

The application of the transactional stress-coping theory to law

enforcement may further advance best practices regarding coping with stress for

police. The theory purports a problem-oriented response to stress will resolve the

strain. As a weight loss program is a problem-oriented response to being

overweight, according to this theory, weight loss is predicted to reduce stress. My

research intended to test the theory deductively to further impact an ideal state of

public policy for law enforcement. When police administrators accept police

officers are susceptible to the troubles and stress of police work, this may

motivate law enforcement agencies to search further to establish policies to

increase health and combat those stressors of the profession.

Testing the transactional coping theory sufficed in correlating high BMI

values with the effects of stress. Recommending policy solutions without research

and evidence on the detrimental effects of stress and high BMI values will have

little influence on police policymakers. Deleterious effects of stress and coping

among police officers include alcoholism, domestic violence, sex addiction,

suicide, divorce, and even simple stress avoidance (Arter, 2008; Violanti et al.,

2011). Public policymakers must make informed decisions to design and guide

public agencies, and the results of my research based on these theories will aid in

public policy creation in that capacity. The utility of both theories is

complimentary and increases social change opportunities from wellness and

policy perspectives.

My research served to elucidate the unhealthy strategies that police

officers may exploit in their dealings with weight and stress. The significance of

my research was to fill a gap, from policy absence and the need to incorporate

wellness programs. Law enforcement officers alternate uncertainly between

moments of high anxiety and trauma to prolonged stationary phases with little or

no activity (Stoughton, 2015), which magnifies their need for public health policy.

Roughly 80% of officers are overweight (Bonauto, Lu, & Fan, 2014; Hostetter,

2007; Loux, 2015; Shell, 2005), and developing a policy to encourage officers to

maintain healthy BMI may have various positive ramifications. The relevant

results of my research study will be made available to program makers to explore

policy implications further based on an ideal type of theoretical strategy.

Significance to Practice

Police officers and agencies, as well as the entire public, have a vested

interested in reducing stress and BMI for law enforcement. In 21

Century law

enforcement, technology has advanced the way officers perform their duties, but

the stress remains. My research proposed policy advocacy for healthier officers.

To ignore the effects of stress and its adverse impacts on law enforcement culture

indicate misuse of human capital (Neely & Cleveland, 2013). The paradigm of

law enforcement administration must shift to discuss, openly treat, and address

this problem of excess weight and stress in officers. My study informed law

enforcement administrators and public policy makers as to how they can propose

programs and guidelines to safeguard police officers from harmful outcomes of

being overweight and not managing stress. Law enforcement must grow and

change as scientific research into existing factors of stress directs new options for

best practices, especially regarding the relationship between stress and obesity.

Significance to Social Change

My investigation into officer body weight and stress had many potential

implications. Decreased stress increases officer health and productivity (Boyce et

al., 2014; Can & Hendy, 2014; Chen, 2009; Neely & Cleveland, 2013). Lower

stress may further offset the adverse impacts, which would provide twofold health

benefits of increased job performance and improved officer health. Overweight

employees increase individual health insurance claims, have lower productivity,

and burden the entire agency with increases in health care costs (Ackerman, 2013;

Bartels & Nordstrom, 2013; Blair et al., 1996; CDC, 2017; Van Nuys et al.,

2014). Controlling BMI could lead to improved mental and physical health among

police officers, yielding improved productivity, fewer officer injuries, reduced use

of sick time, and a more disciplined self-image among police officers (Chikwem,

2017; Satterwhite, 2000; Thomas, 2003).

The positive social change resulting from my project could have far-

reaching implications for police officers and American society. With numerous

documented and well-researched advantages of losing weight, police officers

stand to benefit from this research. Stress has long been well documented as a

harbinger of depraved health, burnout, and poor work decisions or judgment (Can

& Hendy, 2014; Chen, 2009; Finney et al., 2013; Gilbert, 2010; Kyle, 2008). It is

likely that stress is one obstacle that impedes many worthwhile law enforcement

goals. Thus, best practices for ensuring a standard BMI value among police

officers could lead to positive social change impacting not only the police officers

of South Florida but nationwide, as well as the entire public they serve. Building

trust between the American communities and police officers may begin with

problem-oriented stress solving responses with law enforcement officers.

Summary

This chapter identified the background, problem, and purpose of this

research project, proposing a relationship between being overweight and officer

stress. My research questions are grounded in the transactional stress-coping

theory and the ideal type theory and are explicitly aimed at investigating the

relationship between BMI and stress to develop, inform, and suggest policy. The

Police Stress Questionnaire is a valid and reliable survey that was the selected

instrument for this research, which has been tested and used in numerous other

scholarly studies

As police officers continuously train to ward off outside threats, they

silently allow stress to negatively impact them internally in many ways, both

known and unknown (Can & Hendy, 2014; Chen, 2009; Finney et al., 2013;

Gilbert, 2010; Kyle, 2008). Though the general public understands the basic

principals of law enforcement, the best practices regarding the relationship

between being overweight and officer stress levels are not so well understood.

The transactional stress-coping theory can be applied to law enforcement as much

as any other population or occupation to resolve stress and direct policy. This

theory tested on police personnel can influence public policy based on an ideal

type of policy.

Chapter 2 presents an overview of current research on the detrimental

effects of stress. This chapter details scholarly studies of stress in general while

maintaining a focus on police officer weight and stress. High values of BMI and

their effects are the subjects in the literature review. I will also discuss research

experiments and studies conducted to reduce weight or increase stress

management. High BMI values lead to high blood pressure, increased chance of

heart attack, and can lessen the human lifespan (Bartels & Nordstrom, 2013;

Brevard County Sheriff’s Office, 2011; Lasikiewicz et al., 2014; Randle et al.,

2012). I investigated both stress and the overweight human condition to add to

this body of research.

Chapter 3 addresses the methodology and research design of this project.

It further explains the survey tool chosen to measure stress in detail. The

participants, settings, sample, and sample size are each described in Chapter 3.

Chapter 4 includes the results of my research. Chapter 4 describes the analytical

processes used to explain the results of my study. Chapter 5 provides an in-depth

discussion of research findings, application of results, and policy changes

including conclusions and considerations for social change.

Chapter 2: Literature Review

Introduction

With wellness and officer safety issues at stake, the main purpose of my

quantitative project was to cultivate sound informed policy options for controlling

body weight and possibly stress management, grounded in the stress-coping and

ideal type theory. This research sought primarily to encourage policy creation by

examining the predictive relationship between BMI and self-reported

organizational and operational stress among police officers. Occupational type

stresses differ according to the nature of the labor involved in each profession.

Law enforcement is considered one of the most stressful occupations (see Arter,

2008; Can & Hendy, 2014; Chen, 2009; Dean, 2014; Finney et al., 2013; Gilbert,

2010; Kyle, 2008; Liberman et al., 2002; McCarty et al., 2007; McCreary &

Thompson, 2006; Neely, 2011; Neely & Cleveland, 2013; Selokar et al., 2011;

Smith, 2013; Watery & Ussery, 2007; Wang et al., 2014; Yoo, 2007).

As a result, occupational stress is thought to put law enforcement officers

at very high risk for mental and physical health problems including multiple

cardiovascular type diseases (Corrales, 2013; Mark & Smith, 2012). The problem

is that no policy is in place to mandate stress, wellness, or body weight standards

for officers in Florida and this void can contribute to officers’ overall stress load.

Thus, it is essential to identify the various and associated factors contributing to

their stress, how it affects health, and to theorize correlations with BMI. This

literature review introduces the theoretical backgrounds and empirical evidence

regarding occupational stress and its effects on health and wellbeing in the context

of policy application. Importantly, there was a focus on the relationship between

occupational stress and BMI as the driver of poor health outcomes.

I present an overview of the literature search strategy in this chapter. The

review has three major sections. The first component is a background on modern

police training, policies, and its deficiencies addressing occupational stress and

wellness strategies, as well as relevant research related to officer lifespan. The

second portion elaborates on the framework of ideal type policy implementation

using a second complimentary theoretical foundation of stress-coping and the

application of coping strategies to my project. The final component reviews BMI,

its relationship to stress and well-being if any, and the impact of wellness

interventions on stress levels and BMI, including best practices of some other

agencies in Florida.

Literature Search Strategy

The focus of the literature search was on law enforcement fitness policy

and associated occupational stress, the ideal type framework, stress coping theory,

stress relief strategies, and the effects of stress, especially on physiological

functions like body weight regulation. Google Scholar, PubMed, academic

dissertations and theses relating to the topic, ProQuest, Legal Trac, EBSCO Host,

SAGE Journals, LexisNexis, Business Source Complete, ERIC, CINAHL and

MEDLINE, Nursing and Allied Health, and PUBMED were all databases used

with the following keys terms: stress, police stress, obese stress, officer stress,

anxiety, officer anxiety, police weight standards, work stress, police stress coping,

police stress overweight, overweight stress, employee stress, employee weight

loss, BMI stress, stress absenteeism, occupational stress, police, health standards,

overweight police, stress and coping, stress and BMI, police and anxiety, weight

loss and police, occupational stress, police stress management, stress reduction

and police, weight reduction and police, obese effects, police wellness programs,

stress coping theory, reduce police stress, wellness and police, police and sick,

copying and police, police intervention, ideal type theory, police policy stress,

McCreary stress theory, employee obesity, workplace stress, obese

discrimination, officer life expectancy, Lazarus stress coping, ideal state theory,

wellness policy, police fitness standards, and weight program.

An exhaustive search of scholarly peer-reviewed articles was conducted

through the Walden University library using multidisciplinary databases. The

literature search focused on peer-reviewed publications dated between 2012 and

the present. However, for some topics, earlier publications were used due to their

substantial academic or historical value. Less academically rigorous online

resources such as news articles were used sparingly to punctuate examples and

discussions. I also used several unpublished papers at the masters and doctoral

level authored by scholars and veteran police officers where few if any, articles

existed on particular topics. Several databases returned only a few articles related

to the study topic. Combining Boolean operators and the appropriate keywords

with Google Scholar proved to be a valuable and powerful technique.

Background

Professional law enforcement in the United States had significantly

evolved from the informal and voluntary watch system initially used in

burgeoning American cities up until the mid-18th century when city populations

increased. Paid police forces became organized in cities during the 1850s as

America populations grew (Grant & Terry, 2012). However, depending on

geographical location, police services, and governing laws varied considerably.

Policing struggled with corruption and decentralization and lacked standardization

until the mid-1900s. The maturing profession of law enforcement in America

transformed throughout the 1960s with civil rights rulings favoring citizens’

rights, and the majority of departments began to require prospective officers to

have at least a high school diploma (Grant & Terry, 2012).

Law enforcement since the 1970s had become codified with a consistent

set of policy guidelines, general rules, a code of ethics, and professional

accreditation standards. Health and fitness standard for officers became

incorporated in the 1980’s only to be minimized or eliminated in the 21

Century.

The profession of policing is currently a widely accepted and practical career

occupation in the United States (Grant & Terry, 2012). Despite such advances,

modern law enforcement faces the formidable problem of mitigating the

”incredible stress police officers face based on their decisions and the tragic

outcome of not dealing with such stress” (Grant & Terry, 2012, p. 98). The

Florida Department of Law Enforcement (FDLE) enforces the standards for all

police officers in Florida set by Florida State Statue 934.13. According to FDLE

(2017), there are no physical fitness standards for police officers in Florida. A

short obstacle course, called (PAT) is the only physical requirement a perspective

officer need accomplish when in the academy, without any subsequent testing

after the academy. Therefore, research was needed which investigates

occupational stressors among law enforcement personnel. This research suggested

policy advocacy for police training regarding health and wellness to deal with

stress in hopes of minimized related psychological and health problems.

Training Prospective Officers

Law enforcement organizations and academies have neglected training

recruits in health and wellness as well as how to manage stress. Agencies train for

job-related skills but “…less concern has been directed to mental health and

resiliency, proven tools for survival” (Water & Ussery, 2007, p. 173). Applicants

are trained in rigorous and standardized curriculums nationwide which focus on

skills such as emergency driving, firearms, defensive tactics, and procedural

conduct in criminal law (Grant & Terry, 2012). Officer safety training is also

emphasized heavily in training (Stoughton, 2015), but that training only

incorporates very modest amounts of information on coping skills for

occupational stress specific to police work (Hostetter, 2007; Shell, 2005). Where

police academies in Florida have physical ability tests, agencies have minimal

fitness values, if any.

Additionally, Patterson et al. (2014) noted that police recruits begin to

suffer stress in just their first year. Because stress is a common and pervasive

factor in the day to day activities of law enforcement, the importance of training

and policy for stress-related mental health concerns would be beneficial to both

officers and recruits alike. A more thorough policy and awareness of the

contributing factors for stress may alleviate the psychological impacts of

persistent stress. Organizational and systematic stressors accumulate and cause

more anxiety than single massive traumatic events in policing (Corrales, 2013).

Candidates who study police training at a formal college, as well as the

police academy, are often unaware of the harmful effects of poor health

compounding occupational stress and are not prepared to deal with their health or

stress. Schmalleger (2013) ranked police work in the top ten most stressful

occupations but only addressed the subject of stress in two pages of the 600-page

text. Conser, Paynich, and Gingerich (2013) published an introductory criminal

justice textbook of over 400 pages long, in which less than six pages cover police

stress. These authors only superficially elaborate on the consequences of

increased stress in policing. Stress can culminate in poor officer decision-making,

low job effectiveness, and negative health outcomes (Chikwem, 2017). Poor

decisions related to increased stress can destroy public trust as well as open the

agency to costly civil litigation. Conser et al. (2013) recommended officers sought

stress reduction techniques but provided no specific strategies to accomplish this.

As a public entity, policy needs to be developed to protect officers from stress.

Police Officer Life Span

The health effects of stress and obesity led to a dramatic increase in

mortality in law enforcement populations (Brevard County Sheriff’s Office,

2011). In Florida, law enforcement officers were found to have a significantly

shorter average lifespan compared to the general population (see Figure 1).

Figure 1. Graph Comparing Florida's (FRS) Law Enforcement and Corrections Officers with

Florida's General Population regarding the age of death. Adapted from “Florida Mortality Study:

Florida Law Enforcement and Corrections Officers compared to Florida General Population” by

Brevard’s Sheriff’s Office 2011, Sheriff Jack Parker.

Ramey, Downing, and Franke (2009) agreed; they found that even once retired,

officers (n = 165) are 11% more likely to be overweight or obese and have a 9%

greater prevalence of cardiovascular disease than the public.

According to FRS data, retired officers in Florida have a life expectancy

of 62.47 years old, while other Floridian retirees were found to have a life

expectancy of 74.21 years. The report describing this 19% disparity cites a variety

of occupational stressors in law enforcement as significant contributors to the

reduction in life expectancy as well as other health factors. The Florida

Retirement System supplied the data quantifying this report from 2000-2009

(Brevard County Sheriff’s Office, 2011). An older study analyzing data from

1950-1990 similarly showed that retired male police officers had a life expectancy

of only 66 years old (Shell, 2005). When leaders first began to address police

stress in the 1970s, even 50 years ago, administrators acknowledged that police

officers died younger than people in other occupations (Dean, 2014; Water &

Ussery, 2007). Violanti et al. (2013), studied life expectancy of male police

officers versus men in the general population of Buffalo. Officers had a 21.9-year

decreased life expectancy compared to men in the general population. The study

authors cited stress, shift work, obesity, and personal safety risks at work as

causes for this lifespan disparity (Violanti et al., 2013).

The prevalence of stress and health problems, like obesity and physical

disability, has increased steadily together in law enforcement (Corrales, 2013;

Patterson, 2009). Studies have also shown that officers have increasingly poorer

health and fitness metrics the more years of shift work performed (Wirtz &

Nachreiner, 2012). These findings suggest that causes of decreased life

expectancy in police officers cited by Violanti et al. (2013) may be inter-related

and inter-dependent.

Lack of fitness and a sedentary career negatively impact the lifespan of

officers without a protective mandate (Haberman, 2012). In one study by

Richmond, Wodak, Kehoe, and Nick (1998), 83% of nearly 1000 police officers

surveyed had at least one unhealthy lifestyle habit, which also negatively affect

police mortality rates. Those unhealthy habits were categorized as alcohol usage,

tobacco usage, low physical activity, being overweight, and reduced stress

management (Richmond et al., 1998). Overuse of alcohol is one such unhealthy

habit. Richmond et al. (1998) suggested that police officers in general, have low

overall health ratings and tend to overindulge in alcohol, which has significant

professional and health repercussions. Richmond et al. (1998), as well as police

veteran Haberman (2012), recommended law enforcement agencies encourage

more robust health standards for officers and provide interventions and policies

that will reduce even one of these five unhealthy habits, if not address them all.

Stress Coping Theoretical Foundation

The coping process theory, also known as the transactional model of stress

and coping theory was introduced in 1984 by Lazarus and Folkman, who built the

theoretical foundation in their book, Stress, Appraisal, and Coping. This theory

has been researched and used extensively in various fields of scholarly studies

since its origin and is widely accepted (Goh, Sawang & Oei, 2010). Although

many theories on stress exist, Lazarus and Folkman (1984) considered the gamut

of varying reactions to stress and offered elucidation based on two factors.

According to this theory, the causal coping factors are human and situational,

which have an interplay with the individual, possibly resulting in stress. Human

factors such as self-confidence, commitment, social structure, and perceived

control of the stressor play a part in assessing the stressor event. Situational

factors influencing coping in this theory are the events, resources, and limitations.

When these variables are combined, they offer some clarity in differences

between individuals and their ability to cope with stress, which is lacking in other

stress theories (Lazarus & Folkman, 1984; Shirley, 2013).

The stress-coping theory provides insight into managing stress, which

applied in law enforcement, is pertinent to understanding their actions and

responses. The severity of how dissimilar officers may cope with stressor events

relates the theory to policy formation for my weight comparison and stress study.

The theoretical framework is such that it accounts for human and situational

factors that influence threat assessment as well as covariates such as rank and age,

which also impact coping success ability (McDonald, 2013). The theory describes

and is the most suitable coping theory to understand the processing and appraisal

of psychological stressors based on stress management abilities, which vary from

person to person. Stress appraisal and response mechanisms typically involve

reviewing the problem, devising solutions, choosing a solution, and taking action

(Chan & Ward, 1993; Kakar, 2013; Shirley, 2013). This complete appraisal cycle

is termed “coping” and varies by personality and personal resources and continues

until the person resolves the stressor. If not resolved, anxiety difficulties arise.

Coping is the evaluation process between the event and reaction to it (Lazarus &

Folkman, 1984).

Lazarus and Folkman (1984) recognized several negative responses to

unresolved stressors, including depression, blame, and anger. Using the example

of responding to an audible fire alarm, the authors noted that people react

differently according to how directly they assess the threat. Appraisal of the threat

involves deciding whether it is “irrelevant (no value), benign-positive (enhances

well-being), or stressful (threat or challenge)” (p. 32). If the stressor is irrelevant

or positive, it requires no further re-assessment; the person disregards the stressor

as a negative threat. An example of an irrelevant stressor is one in which the actor

has no vested interested in the outcome, and ultimately the results will not affect

them. Positive stress appraisal is when the stressful event is “punctuated by joy

and happiness” (Lazarus & Folkman, 1984, p. 33), such as a job promotion or

birth of a child.

When recognizing this alarm as a negative stressor, the person perceives

it as a threat or a challenge. Once identified as a stressor threat or a challenge, a

secondary appraisal occurs to evaluate what can be done to resolve or eliminate

the source of stress. A challenge is an experience which the individual believes

can be overcome and controlled with coping; however, such a method cannot

overcome the stress. The outcome of a threat is stress. Responses usually arise in

the form of emotional or cognitive problem-solving responses. The secondary

appraisal is involved, and if the candidate is unable to formulate a cognitively

adequate solution, an overly negative emotional response occurs. Not dealing with

the stressor leads to eventual emotional exhaustion. Stress has deleterious

physiological effects and can lead to a runaway emotional, and not necessarily

rational, response. A problem-solving approach, with minimal emotional

influence, is one more likely to reduce the perceived threat or stressor (Lazarus &

Folkman, 1984). This theory applies to various vocations and disciplines. For

example, if being overweight predicts stress in police officers, then losing weight

is a prospective problem-oriented solution in coping with an overweight condition

and therefore will relieve stress. The results from testing this theory can inform

policymakers for the importance of a wellness policy.

The lingering outcome of unresolved stress also includes anxiety, which

constitutes a negative psychological and physical burden. A threat is recognized

solely as a negative stressor and usually requires a full commitment of mental and

physical resources to cope with it. Multiple or repeated significant environmental

stressors increase an individual’s anxiety load (Lazarus & Folkman, 1984), while

ineffective coping strategies can compound stressors and lead to chronic anxiety

(McCarty, Zhao & Garland, 2007). Previously comparable studies regarding

stress research have applied this theory as well.

Literature on Stress Coping Theory

Previous researchers have used the transactional stress-coping theory.

Researchers applied this theory to stress and coping research in their respective

fields, including law enforcement (MacDonald, 2007) and public administration

(McDonald, 2013). For example, Kakar (2013) used the framework of stress

coping theory to describe the relationship between gossip in the workplace and

occupational stress among actors. Milen (2005) used the stress-coping theory to

study how firefighters cope with stress, recommending that agencies incorporate a

psychological and physiological program to assist employees in stress

management. Edge and Ivey (2012) found that actors will attempt to resolve a

stressor if it is a safety threat by formulating a primary and secondary assessment,

which is a continuous process, until such time the stress is rendered inert. They

found that first appraisal of stressors is individualistic and vital to each person’s

strong coping ability.

In a medical research project studying stress management, Chan and Ward

(1993) summarized the theory succinctly: people encounter stressors, they are

then appraised as a potentially viable threat. Once a person interprets a stressor as

a potential threat, actors will attempt to resolve the perceived stressor event with

either a problem or emotion-oriented solution. The coping process necessitates

identifying the stressor as a problem, formulating coping strategies, selecting a

resolution, and acting (Chan & Ward, 1993; Shirley, 2013).

If the resolution of the problem fails, the lingering result is continuing

stress or anxiety. Elevated BMI of officers is a stressor which can be solved by a

problem-oriented approach or an emotional oriented one. An emotional approach

does not resolve the stressor whereas the problem-oriented approach is a rational

solution to the problem and will solve with the stressor. The process of appraisal,

stress, and subsequent coping continues over time for each stressor (Goh, Sawang,

& Oei, 2010; Lazarus & Folkman, 1984). I tested this theory deductively as my

project assumed that BMI levels are related to stress in some manner in officers.

The problem-oriented solution of having a healthy weight should have resolved

the “body weight” stressor, based on this theory. An association between BMI and

stress implied that if BMI goes down, then stress is lowered, and stress

management will be improved. The converse may also occur, as a person loses

weight, it could create increased stress.

Therefore, I assumed the higher the level of BMI, the higher stress levels

were, and conversely, reduced BMI correlated with improved stress management

and lower stress levels. In this theory of stress and coping, if a stressor was not

dealt with successfully, the result is the manifestation of increased and continuing

stress (Lazarus & Folkman, 1984). The theory places importance on the dynamic

nature of stress management. The challenge of stress and coping is ever-present,

especially in the work lives of police officers. As such, police officers must be

continually involved in a cognitive exercise to analyze potential stressor events

and arrive at a resolution that will allow them to experience a positive effect and

successful coping decision. If a problem-oriented response of lower BMI revealed

lower stress, then developing a stress policy could regulate an officer’s behavior

based on the testing of this theory.

Thus, this was an interpretive approach to the psychological experience of

stress that places great emphasis on the individual’s ability to engage in stress

management for accessing improved levels of coping. As such, it is understood

the process of stress and coping may be alive, interactive, and continually in a

problem-solving mode (Lazarus & Folkman, 1984). This individual sphere that

must always be committed to stress management is never absent or unaccounted –

it is an intrinsic and inherent aptitude of the human mind that has allowed humans

to become the most adaptive creatures on the planet.

This theory of stress and coping was germane to law enforcement and

public policy as officer’s deal with a variety of stressors in their daily duties.

Learning a positive problem-oriented response will solve a stressor, officers could

apply this approach in their lives and duties as well. In this way, it could be

understood the stress and coping mechanisms of people as dynamic, self-

regulating systems that are continually challenged to resolve potential threats

from stressor events in the individual’s life circumstance. Public policymakers

and leaders can immediately begin to comprehend the value of learning and

educating the individual as to the best practices that might be associated with

active stress and coping.

In other words, this is not a passive system in the human experience. The

stress and coping system, and the ability to invoke successful stress management

in the face of deleterious stressor events is a critical component in the successful

indices of a person’s life satisfaction, quality of life, and work proficiency

(Lazarus & Folkman, 1984). All of this is another way of saying that science can

assist people to learn more about stress and coping, and that is arguably

something that could benefit all individuals, law enforcement, and society.

Officers stand at the forefront of problem-solving in their profession and their

own daily lives. Increasing officer’s ability to handle stress has far-reaching

positive implications.

Coping Strategies

Perception of threats and challenges vary in every individual and group.

That is, subtle differences in exposure to stressors and coping abilities impact an

individual and group’s overall stress management. How individuals cope with a

stressor largely determines the negative or positive impact of that stimulus

(Lazarus & Folkman, 1984). Categorizing stressors and group response is

imperative; a means of assessing individual stress accurately, with relevant coping

strategies, can help to minimize its negative consequences. In the past, scholarly

research has minimized coping skills as much of the focus has been on stressors

themselves and not so much on how individuals cope with them (Haarr &

Morash, 1999). However, the understanding of coping mechanisms is just as

critical as understanding stressors, as it is possible to develop resilient coping

strategies but nearly impossible to eliminate workplace stress.

Regarding coping strategies, scholars have found that a problem-solving

strategy resolves stressors more permanently and successfully (Haarr & Morash,

1999; Lazarus & Folkman, 1984; Ortega et al., 2007). For example, when being

overweight is recognized as a stressor, a problem-solving resolution would be to

diet and lose weight. Alternately, an emotional response would be to construct

emotional justifications for being overweight or emotionally deny the existence of

a problem. In the latter case, the stressor will remain, and the temporary resolution

will require emotional upkeep to maintain, which risks emotional exhaustion and

create additional anxiety.

Police work is often emotionally draining (Arter, 2008), but requires

officers to restrain these emotions while handling the problems of the public. On

the one hand, suppressing anger has been shown to lead to mental exhaustion,

which further inhibits stress management coping skills and is damaging to a

person’s psychological health (Van Gelderen, Bakker, Konijn & Demerouti,

2011). Conversely, when officers employ more positive coping methods, they are

less prone to antisocial or abnormal behavior (Arter, 2008). Officers possess

different coping methods and capacities based on several factors, including

gender, race, rank, and number of years in service. For example, Caucasian

officers tend to communicate extensively and befriend others to cope with

occupational stress, while African American officers rely on strong bonds with

other minorities. Female officers, on the other hand, tend to have slightly higher

stress levels due to coping avoidance mechanisms and personalizing events by

writing down their experiences (McCarty et al., 2007).

Problem-oriented coping. This class of coping mechanisms involves an

appraisal of stressors as a source of adverse emotional or physical outcomes and

taking active strategies to resolve the “problem” and improve outcomes.

Successful problem-oriented coping mechanisms for officers include increased

communication with family, exercise, and spiritual support of religion. Another

form of successful proactive problem-oriented coping is post-traumatic stress

growth (Chae & Boyle, 2013). This growth is a result of meeting with mental

health professionals to repeatedly discuss and relive the events that caused stress

and anxiety. This method builds confidence and has been shown to expand the

officer’s ability to cope with past and future stressors as they “grow” from the

trauma. Officers in this form of program subsequently profess empowerment and

masterful control over their stressful occurrences (Chae & Boyle, 2013).

Emotion-oriented coping. In contrast to problem-oriented solutions to

stress, emotional responses to stress are often instinctual or reflexive and usually

fail to offer a long-term resolution to stressors. Police officers have been found to

have several inefficient and unhealthy emotion-oriented methods of coping with

stress. These include self-blame, wishful thinking, and abuse of alcohol and drugs

to distract from negative emotions, and avoidance of existence of stressors

(Larned, 2010; Ortega et al., 2007; Patterson, Chung, & Swan, 2014; Water &

Ussery, 2007). Suppressed emotions or avoidance can perpetuate the stress cycle

(Water & Ussery, 2007) and many officers also turn to exceedingly complex or

dark humor to cope with stress; whereas, humor is effective successfully only in

the short-term reduction of stress (Kyle, 2008; Shirley 2013).

The outcomes of poor stress responses can range from relatively benign to

exceedingly harmful. For example, emotional responses to stress can lead to

“stress eating” which involves excessive consumption of high-calorie food

(Thompson, 2004b; Zala, 2013). However, at the other extreme, emotionally

maladaptive coping methods can lead to unethical and even unlawful behavior

(Ater, 2008; Ortega et al., 2007).

One such coping pitfall in research that police officers can succumb to is a

form of sex addiction because of occupational stress. Territo and Sewell (2012)

define sex addiction as having risky sexual relations on a constant and escalating

basis. Sex addiction entails having unprotected or “unsafe” sex with little or no

attempt to conceal the inappropriate activity from partners or spouses. They argue

that sex addicts focus less on the sexual act itself and instead seek risky sexual

encounters to display control and choice in hazardous behavior and personal

jeopardy. This faulty coping technique often results in divorce, unwanted

pregnancy, or unlawful activity (Territo & Sewell, 2012). Sex addiction is a

plausible statistic when officers have close to twice the divorce rate of average

Americans (Liberman et al., 2002).

These behaviors are more common in the law enforcement community

than previously suspected. A news headline reads “A South Florida police chief

was arrested for soliciting a prostitute.” The 53-year-old police chief, who

attempted to hire a prostitute from an online forum which listed escorts for men,

met the prostitute at a hotel during off-duty hours only to discover that she was an

undercover officer from another jurisdiction. When released from the jail, the

former police chief spoke to the media and reasoned, “The stress overwhelmed

me, and I made a very bad decision” (Flechas & Dixon, 2015). This police chief

offered stress as the responsible element which led him to several poor decisions

and risky behaviors, which violated both professional ethical standards and even

Florida state law.

Deliberate indifference to stress is a continuing prevalent detrimental

social behavior flaw and a violation where agencies fail to engage policy to

correct this known conduct (Batterton, 2016). Several theories exist in modern

public administration which could influence the formation of policy to address the

health and wellness of officers. The public opinion theory, the job controls

demands theory, and the public service motivation theory each have their merits

in proposing policy directives. It is the Ideal Type Theory, however which best

suits to resolve the problem and purpose of this project.

Ideal Type Theoretical Framework

Initially developed by German sociologist Max Weber (2009), ideal type

theory refers to how organizations construct and implement policies that shape

professional reality. However, the term “ideal” reportedly has a negative

relationship with performance evaluations of individual employees. For Weber

(1958/2003, 2009), an ideal type suggests that individuals have a calling to enter

their respective profession. For law enforcement officers, ideal types have a

unique placement within both historical and sociological reality as capable of

generating results from empirical observations. Law enforcement officers may act

on the belief that protecting and serving their communities takes priority over

everything else when performing work-related duties (Weber, 1958/2003).

Specifically, ideal types lead researchers to draw valid comparisons between the

results of studies published within a single disciplinary field (Weber, 2009).

Generating empirical results from ideal type theory, thus, requires that researchers

compare factors between treatment and control groups over time.

Secondly, Weber understood ideal types as having an analytical tool for

upholding organizational policies. Rather than consider ideal types as belonging

strictly to empirical reality, Weber suggested that organizational policies construct

an exact purpose for regulating individual behavior (Whimster, 2004). Ideal types,

in other words, do not suggest that employees achieve perfection regarding their

general health and well-being. Here, ideal type theory applies to managerial

decision-making processes that force some employees into taking immediate

corrective action towards enhancing individual performance (Whimster, 2004).

Ideal type theory, accordingly, allows law enforcement officers to compare

current and past performance results as an empirical basis for understanding why

organizational policies exist.

Weber (1949/2015, 1968/1978), furthermore, distinguished between

"individual" and "general" ideal types. Where individual ideal types provide a

historical reference for law enforcement officers to compare current and past

performance, general ideal types pertain to how concerted efforts by law

enforcement officers improve performance over time based on the decision-

making processes involved with implementing organizational policies. Here,

Weber (1949/2015, 1968/1978) applied the term "ideal type" as a methodology to

contrast one empirical reality against another. As individuals evolve during their

membership in a professional organization, ideal types operate as a strategy for

providing a historical overview of the relationship between performance

assessments and compliance with organizational policies. More specific to public

administration, ideal type theory applies as researchers develop an empirical view

of how policymaking affects organizational dynamics (Weber, 1949/2015,

1968/1978). Ideal type theory, therefore, spurs researchers into conducting

historical investigations concerning how policy shifts affect changes in

performance assessment criteria and the behaviors of individual employees within

a professional organization.

Lastly, ideal type theory applies to policymaking as criteria for

performance assessment aligned with organizational norms and objectives. For

Weber (1949/2015), ideal types have methodological significance for researchers

in public administration to the extent that the results of one study produce valid

comparisons for use in future investigations. However, as already mentioned,

ideal types may not always reflect empirical reality. Instead, policymaking in law

enforcement entails that officers must place importance on their physical and

mental health to achieve positive results on performance assessments. In the

following literature review applying ideal type theory to the performance of law

enforcement, I draw a meaningful inference that organizational policy

development should focus more closely on physical and mental health.

Literature on Ideal Type Theory

Priel (in press) presented the Weberian ideal type as a philosophical

construct representing how organizational policies take on “pure” forms. In

policymaking terms, ideal types bear similarity to the common law as

organizational policies themselves have different empirical effects on behavior.

As ideal types, organizational policies manifest into a natural state of affairs by

drawing from basic concepts of logic and reason (Priel, in press). Ideal types,

however, have mostly top-down functions as adherents to organizational policies

find simple answers to fundamental questions about, for instance, consequences

for violating codes of conduct (Sguera et al., 2016). Ideal types place structural

demands on organizational functions as employees, including law enforcement

officers, defining their professional role as aligned with codes of conduct. Despite

having structural demands, organizations such as law enforcement agencies

provide resources for professionals to collaborate and work towards correcting

unacceptable workplace behaviors (Sguera et al., 2016). Here, ideal type theory

applies to law enforcement, as well as to public administration, as organizations

assume political neutrality.

Rothstein applied ideal type theory to explain how cadre organizations in

public administration follow either a “clan or missionary" model (2014, p. 10).

Clan or missionary models imply that law enforcement agencies should have clear

policies that all officers must follow. Accordingly, cadre organizations do not

assume political neutrality as management requires strict adherence to formal

policies (Rothstein, 2014; Van der Wal & Yang, 2015). However, ideal type

theory applies differently to civil servants in countries like China and the

Netherlands.

From their application of ideal type theory to compare the validity of

normative claims in East Asian and Western European organizational contexts,

Van der Wal and Yang (2015) found that Chinese civil servants perceived

structural factors of an organization as causing failures in compliance with

policies regulating codes of conduct. Dutch civil servants, on the other hand,

placed considerable emphasis on the need for organizational reforms in public

administration. Here, the application of ideal type theory suggests that value

preferences differ culturally as Western European cultures emulate an

individualist philosophy whereas East Asian cultures emphasize collective values.

Ideal type theory suggests, in other words, that personal preferences often conflict

with professional norms prescribed in formal organizational policies.

Along similar lines, ideal type theory applies to how professional

organizations apply concepts of New Public Management (NPM) that developed

during the 1980s. New Public Management emphasizes that professional

organizations should consolidate policies as part of a “global public management

revolution” that involves collaboration between employees (Van der Wal & Yang,

2015, p. 412). Burau (2016) noted, moreover, that while NPM allows professional

organizations to reform codes of conduct by drawing from a consolidated policy

template, individual and cultural differences must provide some leverage for

overcoming resistance to taking immediate corrective action that has significant

long-term consequences.

Related to this study concerning how law enforcement officers may take

corrective action towards reducing stress and lowering their BMI (Lacey et al.,

2016), ideal type theory contributes to research in public administration by

offering macro, mezzo-, and micro-level approaches (Burau, 2016; Kuehl et al.,

2016; Summers-Effler & Kwak, 2015). Ideal type theory contributes further to

research in public administration by suggesting that the criteria used for assessing

individual performance levels in law enforcement must coincide with dietary

habits, physical activity, and weight loss maintenance over time. Very few studies

to date explicitly applied ideal type theory to compare the results of programs

designed to reduce occupational stress or lower BMI numbers among law

enforcement officers.

Ideal type theory contributes to research in public administration by

advancing the goal of verstehen, or understanding, as an incentive for taking

corrective action and improving health outcomes among law enforcement

officers. Summers-Effler and Kwak (2016) suggested, however, that applications

of ideal type theory in public administration fail to provide any substantive results

if researchers do not offer valid comparisons of results for use in future studies.

Instead, researchers in public administration should apply ideal type theory to

develop an understanding of how, for example, law enforcement officers attribute

meaning to their role in a professional organization. Regarding their health, the

experiences of individual law enforcement officers provide empirical support for

understanding why formal organizational policies regulating conduct have

considerably more substantial effects on some more than others (Sguera et al.,

2016; Summers-Effler & Kwak, 2015). Formal policies regulating the dietary

habits of law enforcement officers, thus, have broader implications for

understanding macro, mezzo-, and micro-level differences within an

organizational culture.

Importantly, ideal type theory contributes to research in public

administration by offering analytical insights that link medicine and management

across various organizational contexts. Law enforcement officers in less-than-

ideal health perform their professional duties less efficiently and effectively

(Chikwem, 2017). Burau (2016) suggested that research in ideal type theory

should move beyond macro-level comparisons of health-related organizational

policies to provide more contextualized and process-oriented approach for

monitoring the behaviors of individual law enforcement officers. Concurrently,

Van der Wal and Yang (2015) suggested that research in ideal type theory should

provide more detailed comparisons of organizational dynamics within the context

of formal policies regulating dietary habits and other health-related behaviors of

law enforcement officers. Overall, ideal type theory can provide researchers with

a solid understanding of how management in law enforcement agencies develops

policies that monitor performance levels through programs designed to regulate

health behaviors.

The Consequences of Occupational Stress

Stress is a negative health determinant (Burchfiel et al., 2011).

“[Occupational stress] has been recognized as a global challenge” by some

experts (Kakar, 2013, p. 4), and is more important for individuals than it is for the

organizations, since stress impacts employee health and productivity, decreasing

the ability to contribute to the organization (Chikwem, 2017; McCarty et al.,

2007). Stinchcomb (2004) wrote, “Illnesses related to stress have now replaced

infectious disease as the leading cause of death” (p. 259). Stress also places

increased demands on the cardiovascular system and inhibits the body’s immune

system, rendering it more susceptible to illness (Huang & Acevedo, 2011). Stress

is also responsible for comfort eating of high-calorie foods, which can further lead

to weight management difficulties (Berset et al., 2011; Zala, 2013). Therefore,

identifying and resolving the stressors that lead to exhaustion, comfort eating, and

reduced weight control can improve workplace performance and prevent further

cycles of mental exhaustion and poor eating habits.

Both the perception of stressors as well as their acuity can lead to

behavioral and psychological changes (Arter, 2008; Liberman et al., 2002;

Stinchcomb, 2004; Water & Ussery, 2007). Mental illness and relationship

difficulties can result from stress and sometimes manifest as sleep difficulties,

alcohol abuse, and even increased violence (Chen, 2009). Chronic exposure to

occupational stress may also lead to emotional or physical exhaustion, often

culminating as excessive fatigue and demoralization (Boyden, 2010; Ortega et al.,

2007; Wang et al., 2014). Stress can result in excessive absenteeism, low morale,

and over-aggressiveness. Mental exhaustion decreases happiness, enjoyment of

significant life events, and productivity in the workplace (Larned, 2010; McCarty

et al., 2007; Patterson, 2009; Selokar et al., 2011). Additionally, stress-related

fatigue promotes an inactive lifestyle and compounds further de-conditioning,

cardiovascular disease, and other metabolic derangements (Azagba & Sharaf,

2012). These maladaptive states can become self-perpetuating and require specific

health interventions for their resolution (Larned, 2010; Selokar et al., 2011).

Stress in the Context of Law Enforcement

By and large, any job stress poses a significant social problem, yet there is

even more stress for law enforcement officers than other occupations (Chen,

2009). Policing is widely considered to be one of the most stressful occupations

(Corrales, 2013; Dean, 2014; Gu et al., 2013a; Julseth, Ruiz & Hummer, 2011;

McCreary & Thompson, 2006; Ramey, Perkhounkova, Downing & Culp, 2011;

Yoo & Franke, 2011). Occupational stressors specific to law enforcement include

the need to achieve objectives, the pressure to carry out duties in an economically

efficient manner, uncertainty in police work routine as well as outcomes of work,

variability in shift duration and timing, and the necessity for rapid response time

(Arter, 2008; Boyden, 2010; Neely & Cleveland, 2013; Ortega et al., 2007; Water

& Ussery, 2007). Police officers face scrutiny from internal and external

supervisory figures, the media, the courts, and the public, which adds to

occupational stress (Johnson, 2012). Police work also inherently carries a high

rate of unpredictable contacts with probable violence. Repeated exposure to

traumatic incidents and lack of control in these situations produces a constant

state of vigilance and stress for each officer (Gerber et al., 2013; Stinchcomb,

2004; Stoughton, 2015).

Nevertheless, the obvious physical dangers and hazards of the profession

are not the primary source of stressors for officers (Neely & Cleveland, 2013;

Stinchcomb, 2004). The outwardly nominal factors mentioned above of routine

bureaucracy, regulations, restrictions, and the hassles of daily policing cause the

bulk of stress and can lead to burnout (Chen 2009; Corrales, 2013). Problems

arising from police organizations can also increase stress in the day to day routine

of their employees. Public demands on the police force, pressure from regulatory

and supervisory bodies, and budget cuts which may result in the reduction of

police forces all potentially translate into stressors for officers (Ortega et al.,

2007). Finally, an additional stressor is unfairness in the police workplace. Stress

can result when professional rewards are thought to be incongruent with work

efforts, or excessive criticism from superiors occurs (Azagba & Sharaf, 2012;

Selokar et al., 2011).

Demographic stressors. Occupational stress levels among law

enforcement personnel are influenced not only by these inciting stressors but also

by demographic traits of the officers. Chen (2009) correlated the subject’s age,

seniority, rank, and education with stress levels. Specifically, officers between 31-

40 years old, with 11-20 years of police service, and possessing a college degree

comprised the central demographic average of officers who reported the highest

levels of stress. Smith (2013) studied female police officers and found that they

also suffer significant amounts of stress in law enforcement’s male-dominated

culture. Yoo and Franke (2011) supported this finding as well, reporting that

female officers endure more job stress than their male officer counterparts.

Stress and suicide rate. Unaddressed stress among officers leads to an

excess of problematic consequences. Police officers have 2 to 6 times a higher

rate of suicide than the national average (Larned, 2010; Liberman et al.,

2002). According to Huang and Acevedo (2011), more officers commit suicide

than die in the line of duty; for officers, “there is a significant correlation between

stress, depression, and suicide” (Larned, 2010, p. 64). In addition to these

findings, Chae and Boyle (2013) identified five predictors of suicide among

police personnel: traumatic incidents, shift work, alcoholism, relationship

problems, and organizational stress. Stress also has been shown to dramatically

reduce the life expectancy of officers (Schmalleger, 2013; Water & Ussery,

2007).

Social effects. Police officers also have nearly double the divorce rate of

average Americans (Larned, 2010; Liberman et al., 2002), estimated between 50-

80% (Water & Ussery, 2007). This high divorce rate supports the research of

Kyle (2008), who found that stress had a significant impact on personal

relationships and family life. These findings are attributed to insufficient

management of the extreme stressors of life or death situations within law

enforcement (Larned, 2010; Liberman et al., 2002).

Alcohol abuse and health issues. Other psychosocial consequences of

stress include sleep disorders, domestic and relationship violence, alcoholism, and

posttraumatic stress disorder (PSTD). Irregular work activities and unpredictable

shift work prove to be significant stressors and contribute to sleep disorders and a

high rate of alcohol consumption (Gerber et al., 2013; Larned, 2010; Neely &

Cleveland, 2013; Violanti et al., 2011; Wang et al., 2014; Water & Ussery, 2007).

Officers are three times more likely to abuse or become dependent on alcohol

than average Americans (Gaines & Miller, 2012).

Officers also have higher rates of physical health problems than other

Americans. Gaines and Miller (2012) argued that stress effects heart disease and

high blood pressure among police officers. Officers are also at increased risk for

cancer and obesity (Larned, 2010). Occupational stress and dissatisfaction,

including working in high demand situations with low latitude for decision-

making and having a poor reward for efforts, are among the leading risk factors

for higher BMI among police officers (Jarali & Radhakrishnan, 2013).

Occupational stress causes employees to use more sick days among emergency

responders in the law enforcement profession.

Job performance. The high prevalence of occupational stress in law

enforcement also causes chronic work anxiety and decreased efficiency among

officers (Johnson, 2012; Neely & Cleveland, 2013). Stinchcomb (2004, p. 262)

remarked that “ongoing stressors drain energy and enthusiasm,” which results in

less efficient job performance among officers. Stress impacts job satisfaction as

well as the quality of police work (Chikwem, 2017; Julseth et al., 2011). Quality

is partially dependent on personal traits; however, Tang and Hammontree (1992)

studied police officers (n = 600) for stress levels as correlated with hardiness.

Hardiness, as described in their study, is defined as possessing coping qualities

such as “commitment, control, and challenge” (Tang & Hammontree, 1992, p.

494). They also examined how these factors impacted illness and absenteeism.

Officers with hardiness were found to experience less stress; yet, the findings still

supported a correlation between more stress and higher rates of illness and

absenteeism for officers.

Deviant behavior. Arter (2008) linked stress in police work to deviant

behavior by officers. On a professional level, deviance is those behaviors which

are discouraged by police culture but are not necessarily prohibited. However,

these behaviors may go as far as violating professional policies and even

disobeying legal standards. Examples of the former include rude behavior,

fearfulness while on duty, selective or non-enforcement of laws, and

sympathizing with criminals. Associated with high levels of workplace stress is

more severe deviant behavior including excessive use of force by officers (Neely,

2011). This type of action reflects not only a degradation of work quality but also

a violation of ethical and professional standards. Fortunately, Arter (2008) also

found that officers under substantial stress resisted deviant behavior if their

coping approach involved positive adaptive techniques.

Organizational stressors. Organizational stressors include public

demand, bureaucratic pressure, supervisors, and budget cuts which may result in

the reduction of officers due to financial constraints (Ortega et al., 2007). Work

imbalance can occur due to this chronic anxiety and results in a change of

attitude, behavior, and risks factors related to lifestyle (Corrales, 2013). It is the

everyday hassles and slow, yet continual, daily aspects of policing which cause

the main bulk of stress in this occupation leading to burnout (Chen 2009;

Corrales, 2013).

To address lower productivity, Finney, Stergiopoulos, Hensel, Bonato, and

Dewa (2013) studied stress and burnout in correction officers. They determined

that organizational issues were the primary source of stress for correction officers

and recommended interventions to improve this problem. Haarr and Morash

(1999) also recommended interventional programs to reduce officer stress. Milen

(2005) recommended designing health and wellness programs for public service

employees to cope with stress after a study of stress in firefighters. Interestingly,

most officers do not utilize voluntary services for stress management provided by

their employers, even if they are free of charge.

Boyden (2010), Dean (2014), and Gilbert (2010) utilized the Operational

Police Stress Questionnaire to measure stress among police officers. Smith (2013)

used both the Operational and Occupational Police Stress Questionnaires to

measure stress among police officers, and the influence gender may have on stress

management. This two-survey apparatus was created by McCreary and Thompson

(2006) precisely to calculate the stress in law enforcement personnel. Dean (2014)

and Smith (2013) concluded reducing stress is critical for officer wellbeing and

recommend further studies on the topic. I will discuss these survey tools in greater

detail in Chapter 3.

The Role of Body Mass Index

Body mass index is designed as a ratio of body weight to height and is a

standardized measure to assess weight-related conditions in medicine and

research. Body mass index is considered a continuous variable and it is also useful

for classifying study subjects into underweight, normal, overweight, and obese

participants. Body mass index is logistically reasonable to utilize and considered

an accurate overall measure of body fat (Phan et al., 2012). Having a BMI of less

than 18 is considered underweight; between 18 and 25 is considered normal and

healthy; overweight is considered 25 to 30, and a BMI over 30 is branded obese.

Medical experts consider a BMI above 35 to be morbidly obese. According to the

Center for Disease Control (CDC), BMI can indicate unhealthy weight and risk of

developing diseases linked to being overweight and obese like heart disease

(CDC, 2015).

In a study of 41 occupations, law enforcement had the second highest

obesity rate (Gu et al., 2012). Increased BMI is strongly associated with

cardiovascular diseases (Ramey et al., 2011). Police officers are also 1.7 times

more likely to develop obesity-related diseases as compared to civilians (Ramey

et al., 2011; Shell, 2005). For example, obesity is associated with obstructive

sleep apnea in police officers (Charles et al., 2007). Disordered breathing in sleep

leads to poor sleep quality, interrupted sleep, and insufficient sleep duration,

which can affect mental health, lead to physical and emotional exhaustion and

predict further weight gain (Kyle, 2008; O’Connor, 2013). Over 15% of obese

workers reported emotional exhaustion, which is significantly higher than workers

of a healthy weight (Proper, Koppes, Van Zwieten, & Bemelmans, 2013a).

Emotional exhaustion is likely related to the fact that obesity and workplace stress

have a cyclical and symbiotic relationship, with one promoting the other (Ramey

et al., 2011).

Hostetter (2007) argued that “obesity is about to overtake smoking as the

number one cause of preventable deaths in the United States” (p. 14). Moran

(2013) identified obesity as an epidemic associated with unhealthy lifestyles.

O’Connor (2013) claimed the American obesity epidemic affects military and

civilian emergency services substantially; i.e., 67% to 75% of Americans in the

age group of 18-24 years old are unfit for duty as first responders due to being

overweight or obese. Likewise, approximately 40% of police officers are

considered obese (Can & Hendy, 2014; Gu et al., 2012; Gu et al., 2013a). The

prevalence of obesity in police officers is dramatically higher than other segments

of the American workforce (Bonauto & Fan, 2014; Hostetter, 2007; Yoo, 2007).

Over two-thirds of Americans are overweight or obese (Cawley & Price, 2013;

Chalupka, 2011; Hostetter, 2007; O’Connor, 2013; Proper et al., 2013a; Randle et

al., 2012; Thompson, 2004a; Wee, Davis, & Phillips, 2005; Yoo, 2007) with that

number rising to 80% among police officers (Huang & Acevedo, 2011; Shell,

2005).

In the workplace, obesity also impacts an employee’s productivity;

associated with obesity, workplace injuries, absenteeism, increased health

insurance costs, and usage impacts employers (Lim & Herrmann, 2012). Obese

employees also fear they may lose their job more than employees of a healthy

weight; they suffer from higher job insecurity and lower job confidence

(Muenster, Rueger, Ochsmann, Letzel, & Toschke, 2011). Hutton (2012) found

that obese employees displayed higher stress levels than their healthy

counterparts. Proper et al. (2013b) argued that people of a healthy weight cope

with anxiety better than overweight people do. Furthermore, emotional

consumption of food under acute psychological stress is associated with the

behavior, sensitivity, and coping strategies of chronic anxiety problems (Alert et

al., 2013; Zala, 2013).

Jarali and Radhakrishnan (2013) measured BMI and used the Professional

Life Stress Scale to survey stress levels of 300 professionals, including nurses,

bankers, pharmacists, and teachers. Approximately 70% of the participants had

normal BMI, and over 75% of participants were found to suffer from mild stress.

However, heightened stress levels correlated with increased BMI in this

population (Jarali & Radhakrishnan, 2013). In that regard, occupational stress in

law enforcement may contribute to the development of obesity and this may in

turn increase stress in the workplace (Gu et al., 2013a). Berset et al. (2011) found

occupational stress was a significant predictor for gaining weight. The unique

stressors of law enforcement often drive unhealthy patterns of eating,

consumptions of high-calorie foods, and limit leisure time and physical activities,

which can all contribute to weight gain. Working long hours or night shifts are

associated with higher BMI in law enforcement (Berset et al., 2011; Gu et al.,

2012). High BMI values are particularly harmful because of police work has long

sedentary periods punctuated by short sessions of high-intensity activities in the

field (Stoughton, 2015).

Proper et al. (2013a) posited that obesity and mental health issues are

often interlinked and recommended wellness interventions to assist employees

with both. Symptoms of depression are highly prevalent and closely linked to

metabolic syndrome among police officers (Violanti et al., 2011). Linnan et al.

(2012) summarized the plight of overweight employees well; “Overweight and

obesity are associated with diminished health, productivity, and increased costs

for employers” (p. 215).

Obesity increases mortality rates 50-100% for all causes (Poirier &

Despres, 2001). Given this finding and all the other negative consequences of

obesity among law enforcement personnel and the rest of the American

workforce, experts recommend wellness interventions to encourage activity and

reduce body weight. Shell (2005) recommended that “organizations should

implement plans to redirect money to lifelong wellness initiatives” (p. 29).

Significant weight loss may have psychological benefits; however, Lasikiewicz et

al., (2014) reported little is known about the effects of diminutive amounts of

weight loss, which can be the first step for many individuals seeking to improve

their health; they recommend more research on this topic.

Weight Discrimination

In addition to a wide variety of medical and professional difficulties,

overweight and obese individuals also face several social problems, including

rejection or discrimination (Magallares, Morales & Rubio, 2011). Obesity is

perceived as a weakness and has a negative stigma; therefore, weight

discrimination can significantly damage self-esteem and self-value, and itself

create stress (Lasikiewicz et al., 2014; Magallares et al., 2011; Randle et al.,

2012). Negative stereotypes of overweight and obese people in the workplace are

widespread. Overweight individuals are often wrongly characterized as lazy,

incompetent, sloppy, and emotionally unstable. Furthermore, overweight

candidates suffer discrimination in hiring, promotion, compensation, evaluations,

discipline, and even termination (Bartels & Nordstrom, 2013). Obese members of

the workforce have a higher rate of unemployment, and overweight employees

earn 6% - 12% less than normal-weight employees. Overweight and obese

employees work more hours, have more conflict with co-workers, and suffer from

stereotypes of having poor work habits (Magallares et al., 2011).

Ackerman (2013) had similar findings on weight discrimination and

revealed that only Michigan has laws protecting employees from such specific

bias. The Americans with Disabilities Act does not yet recognize overweight and

obese individuals as a generally protected class of people, but some obese

employees are to be considered disabled depending on their circumstances

(Ackerman, 2013).

Discrimination in the workplace further creates psychological and

physiological stress, which requires significant coping responses by victimized

employees (Randle et al., 2012). Rejection and discrimination can ultimately

create significant psychological burdens for the overweight and obese, and it is

not surprising that increasing BMI is positively associated with increased

incidences of depression.

Fitness Standards and Sedentary Work in Law Enforcement

Despite perception, law enforcement is mostly a sedentary occupation.

Extended hours are spent patrolling in a vehicle or at a desk filling out a multitude

of paperwork (Gu et al., 2013a; Kyle, 2008; Larned, 2010). Extended sedentary

periods are a risk factor for morbidity and mortality. Powell and Blair (1994)

declared that a sedentary lifestyle leads to poor health outcomes in the general

population, which Yoo (2007) concurred. They said that one-third of the United

States mortality rate is sedentary and because of the downstream conditions that

arise out of a sedentary lifestyle. Florida requires a physical assessment for

applicants as a police officer. Cadets in the academy must complete a short

physical ability test (PAT) obstacle course in under six minutes and four seconds

to pass the Florida physical standards (Florida Department of Law Enforcement

[FDLE], 2017). Once recruits graduate from the academy, the agency who hires

them determines any further fitness requirement to maintain employment. There

is no set Florida standard or mandatory requirement post-academy for officers.

Policy best practices. About half (32 out of 67) of the sheriff’s offices in

Florida include continuing physical fitness standards for officers in some manner

(FDLE, 2017). Only seven counties’ policies are mandatory. Due to changes in

the law, FDLE reformed their stance of a fitness standard to a physical abilities

test in the mid-1990’s (FDLE, 2017; Wilson, 2014). The PAT conforms to the

criteria of job task-specific abilities on an obstacle course with a pass/fail score.

The test incorporates eight skills to simulate necessary police job functions. The

PAT replaced the previously used Cooper standards test which police agencies

widely utilized. The Cooper standards are a set of gradient and gender-specific

scores for a 1.5-mile run, pushups, and sit-ups (Cooper Institute, 2017). Several

agencies in Florida use the PAT, Cooper’s standards, or some modification of

them to maintain employment as an officer, but each agency has different

standards.

One Sheriff’s Office in South Florida has over 400 sworn officers

including patrol, corrections and court operations (CCSO, 2017). This county

tests their officers every year with the PAT. Employees receive several chances to

meet the minimum time, and the agency boasts over a 95% success rate each year

(CCSO, 2017; Wilson, 2014). Another Sheriff’s Office in the near geographical

area the first county in south Florida has a mandatory fitness policy in place. This

second county necessitates physical exams every two years and has body weight

standards for officers as well as the PAT; however, the agency postponed the

standards since 2012 due to budget anxieties as fitness testing can be costly

(CCSO, 2017).

I examined a small municipal police agency within this same geographical

area also in south Florida. This city agency has about 225 officers (CCPD, 2017)

and has a fitness policy in place for their officers however this policy is not

mandatory. The standard is different for gender and prorated based on age. The

fitness test consists of a timed distance run, sit-ups, and a bench press standard

comparable to the Cooper standards (CCPD, 2017). I explored a second city

police agency in South Florida. This department has over 100 law enforcement

officers. They have a mandatory fitness policy and use the Cooper standard for

testing. This second agency has not yet terminated anyone for failure to complete

these standards (ASPD, 2017; Wilson, 2014).

Lastly, the Sheriff’s Office where I am conducting the survey does not

have any fitness standards or a policy that addresses fitness. The only physical

appearance policy is under the neglect of duty section in the operations chapter of

the policy manual, which states the body weight of officers will be proportional to

their height (LCSO, 2017). The policy does not incorporate any fitness or weight

standards.

Fitness. Fitness has been shown to inoculate officers against adverse

health outcomes, even in those who smoke (Gerber et al., 2013; Huang &

Acevedo, 2011). Lack of fitness remains directly linked to untimely death (Blair

et al., 1996).

Wei et al. (1999) verified these findings on low fitness and added

obesity as a specific risk factor for cardiovascular disease associated mortality.

Yoo (2007) also found that associated with fitness was a reduced incidence of

metabolic syndrome and stress for police officers. The interplay between stress

and fitness are bi-directional, as individuals suffering from anxiety exercise less

(Azagba & Sharaf, 2012; Berset et al., 2011). Stress can also lead to weight

control problems and impair fitness in police officers (Berset et al., 2011). Azagba

and Sharaf (2012) had similar findings, noting that occupational stressors have a

significant contribution to unhealthy BMI changes.

Huang and Acevedo (2011) recommended occupation-specific fitness

programs for officers to buffer against the negative consequences of weight and

stress. Ironically, many police organizations have removed mandatory officer

fitness standards, which compound the risks of poor physical conditioning with

those of increased stress. This trend has arisen primarily because of successful

litigation of employees in law enforcement against their employers (Shell, 2005).

In Bauer v. Holder (2014), the court ruled against gender-specific standardized

fitness testing requirements for law enforcement officers, citing gender

inequalities on general fitness requirements that could not be directly justified by

specific occupational tasks (Gilbert, 2010). Police organizations can only enforce

fitness standards which are task-specific (Gilbert, 2010; Haberman 2012).

Examples of task-specific standards for law enforcement are jumping fences,

sprinting for short distances, and dragging an injured person to safety. Other

physical standards like a distance run may be incorporated if a correlation exists

from the standard to the job-specific objective, such as sustained aerobic capacity.

The Costs of Chronic Stress and Elevated BMI

The cost of obesity to employers is significant. One study showed that an

employer incurs an additional $5,000 per month in expenses to hire an employee

with a BMI of 40 or higher compared to an employee with a BMI of 25 (Van

Nuys et al., 2014). Tsai, Williamson, and Glick (2011) said that hiring an

overweight employee versus an average weight employee costs the company 42%

more.

Obese employees reported more injuries than employees with lower BMI

(Kouvonen et al., 2013; Thomas, 2003). Associated with obesity is the

degenerative disease of weight-bearing joints, which can impact mobility and the

ability to function in an active workplace (O’Connor, 2013). Obesity also

increases health care utilization for reasons beyond the realm of workplace injury

and can increase health insurance costs for employers overall (Peake et al., 2012).

Thus, obesity increases the burden on employers and organizations through

increased expenditures to maintain a healthy workforce as well as loss of

productivity through employee absenteeism (Chalupka, 2011; Chikwem, 2017;

Satterwhite, 2000). Monitoring and encouraging healthy BMI policy among

employees may be prudent for employers simply from a financial standpoint.

From a macroeconomic standpoint, health care utilization related to

obesity cost the United States an estimated $147 billion in 2011 and is projected

to rise to $344 billion annually by 2018 (Chalupka, 2011). Health insurance

premiums have doubled in the last ten years due to an increasing prevalence of

preventable chronic diseases driven in part by rising rates of obesity (Churchill,

Gillespie, & Herbold, 2014).

Since 1990, employees have increased worker’s compensation claims by

700%, with occupational stress cited as a significant cause of loss of ability to

work (Brock & Buckley, 2012). The majority (70%) of all absenteeism is linked

to stress-related issues and costs the United States economy roughly $100 billion

each year (Tang & Hammontree, 1992). Thus, employers bear the cost of

employee stress levels, obesity, resilience, and stress coping ability of employees.

In the specific context of law enforcement, the academic literature

uniformly recommends wellness program for officers to relieve stress and reduce

weight. However, only a few recommended interventions are empirically

validated. A need for testing and implementation of wellness interventions for

stressed and overweight law enforcement personnel is necessary (Envick, 2012).

Additional scholarly studies on weight loss interventions bear further mention

here.

Wellness Intervention Studies

Milsom et al. (2014) conducted a 12-week team weight loss experiment.

Their goal was to assess changes in health predictor variables with weight loss.

These researchers found that even with modest weight loss (5-10%), predictors of

health improved such as high blood pressure. Boyce et al. (2014) also conducted a

12-week weight loss intervention at a mid-size police organization of about 1,700

employees. The team competition intervention had three to four participants on a

team. Measurement of participant weight was taken at the beginning and again at

the end of the 12 weeks. The teams competed against each other within and

between departments. There were significant weight loss results between

overweight and obese participants, despite showing little difference in weight loss

between genders. The wellness initiatives employed for weight loss in Boyce et

al. (2014) and Milsom et al. (2014) advocate ideal type policy in my study as best

practices.

Johannessen and Berntsen (2013) showed that weight loss could modulate

post-traumatic stress disorder (PTSD) symptoms. In their study, participants (n =

30) had PTSD and participated in a 16-week weight loss and exercise program. At

the end of that study, weight loss and decreased PTSD symptoms were associated.

Though the majority of law enforcement stress comes from everyday daily

stressors rather than singular traumatic events, the study serves as proof of

concept of the inter-related nature of stress and weight.

Barringer and Orbuch (2013), Kullgren et al. (2013), and Leahey et al.

(2012) recommended wellness initiatives that group participants into teams; this

encourages teamwork on the job and perpetuates stronger engagement with the

intervention itself. Leahey et al. (2012) conducted a 12-week weight loss

intervention where participants were on teams. The intervention boasted a 67%

completion rate of mostly older, white, and modestly overweight participants.

Thirty-three percent of those who finished the program reached a significant

weight loss goal of 5% percent, which was pre-determined for the study. The

more members on a team, the more substantial the amount of weight was lost per

person. The results from Leahey’s et al. (2012) study suggest that having

teammates positively influenced their participation and success.

Kullgren et al. (2013) conducted a 24-week weight loss experiment (n =

35) where subjects were on teams and others assigned to be solo participants. The

team participants lost more weight and kept the weight off longer than the solo

participants. Diana et al. (2010) conducted a substantial weight loss intervention

on almost 3,000 employees in the workplace with the goal of linking weight loss

to improvement in workplace stress. After controlling for potential confounding

variables like age, gender, race, income, education, and tobacco use, they found

that weight loss correlated with improvement in stress. Their recommendation

was for employers to establish workplace wellness initiatives to reduce employee

weight and occupational stress (Diana et al., 2010).

Alert et al. (2013) conducted a workplace weight loss intervention (n =

31) to research the results of a similar endeavor. Their study comprised of a 20-

week program and after attrition, the average weight loss of each participant was

only 9.5 pounds (n = 23). Some of the participation results were increases in self-

esteem and improved physical function. More remarkably, they found that stress

management skills also modestly increased as weight decreased.

The Affordable Care Act (ACA) and the Health Insurance Portability and

Accountability Act (HIPAA) of 1996 govern employee wellness programs.

Employee discrimination based on a health factor is unlawful and being

overweight has been determined to be a health factor, in some cases (Bardach,

2012). Specific wellness programs which are allowable under the law, HIPAA

defines. All employees must be eligible for wellness programs regardless of

health or concluding health standards. All participants of wellness programs must

be eligible for the rewards or absence of punishment void of any health standard

outcome.

For example, a program advocating a one-mile run must be made available

to all employees, and if several employees have knee injuries that prohibit

participation, employers must make an equivalent substitute. Additionally, all

participants must receive the same benefit from the program, irrespective of their

ability to achieve a physical or time requirement. Wellness plans must also meet a

reasonableness standard in any trade-off between increased wellness versus

burden to employees (Moran, 2013).

The ACA also supports wellness interventions in the workplace. However,

these interventions must be voluntary, the health information must remain

confidential, and the health information cannot be used to impact work benefits.

For an intervention to be mandatory in a public employee arena, employers must

justify a particular need of the intrusion, and it must apply to the entire work

population (Bardach, 2012; Stone, 2012). Mandatory wellness standards also must

be job specific.

Preventative Wellness Resources in Law Enforcement

As previously claimed, policing is a very stressful profession and

increases the risk of developing mental and physical health problems. High levels

of obesity contribute to professional and psychosocial difficulties as well as

increased rates of morbidity and mortality among police forces. The most

effective preventative program for officers revolves around health-promoting and

stress reduction activities, awareness, and education; however, officers do not

willingly seek out this assistance due to significant cultural stigma regarding the

utilization of mental health resources and assistance (Corrales, 2013). Often, the

concern is that preventative resource utilization comes too late; “without some

form of intervention, transient stress responses can develop into symptoms of

suicidal ideation requiring treatment” (Water & Ussery, 2007, p. 176).

Employing solutions in police departments as part of mandatory officer

training per policy could be required for personal safety. While multiple factors

impact stress levels and obesity; only some are modifiable. Implementing

employee interventions is needed for health problems, family problems, unhealthy

work hours, stress, and lack of support in the law enforcement workplace (Can &

Hendy, 2014). Since the success of interventions is dependent on several factors,

it is imperative that the upper management of the police organizations support

them (Churchill et al., 2014; Haberman, 2012; Lankford, Lang, Bowden, & Baun,

2013). For instance, employers can offer incentives, including gifts and even

monetary compensation (Cawley & Price, 2013; Churchill et al., 2014), as

financial incentives. Incentives have been shown to be successful in promoting

participation in organized workplace health interventions (Linnen et al., 2012).

Increasing the frequency of incentive disbursement also helps to decrease attrition

(Cawley & Price, 2013).

Hostetter (2007) recommended many customized wellness interventions to

help different populations within law enforcement to address the health issues

associated with being overweight and stressed. The tailoring of programs to

specific populations is thought to be more successful than a standardized

intervention. Among the most successful wellness interventions were membership

offers for off-site gym usage followed by healthier food choices in on-site

vending machines. Weight loss programs were moderately successful regarding

participation. Smoking cessation programs and back pain prevention programs

had the lowest levels of participation (Churchill et al., 2014). Water and Ussery

(2007) also recommend some form of stress management training for officers.

Fitness requirements may also benefit police organizations and personnel.

Though some evidence refutes a link between fitness and stress levels

(MacDonald, 2007), others have found that fitness improves stress levels (Gerber

et al., 2010). Shell (2005) argued that the annual physical testing of police officers

is essential in maintaining officers’ health and safety. However, these standards

may be problematic due to previous court rulings against broad fitness

requirements found to be unfair towards genders in law enforcement.

Less well-studied approaches to intervention included the showing of a

funny short movie to reduce police officer stress (Kyle, 2008). Shirley (2013)

replicated this study with teachers as participants. Both projects had a control and

an experimental group and tracked pre- and post-intervention stress levels. They

revealed small reductions in participant stress following laughter, but these gains

were not enduring (Kyle, 2008; Shirley, 2013). I have found a few other stress

reduction interventions published.

Patterson et al. (2014) conducted a comprehensive review of published

interventions aimed at reducing police stress. Between 1984 and 2008, Patterson

found only 12 interventions published. Methods in those stress reduction

programs included the use of emotion-regulation training, exercise programs, and

writing interventions. Most of these interventions only lasted hours and

“evaluation methods seldom utilized randomized controlled trials, which are the

best method for demonstrating program effectiveness” (Patterson et al., 2014, p.

20). The authors recommended increased funding and future study to improve

specific occupational stress management techniques. Barriers to wellness

programs continue to be lack of employee interest, low participation, and lack of

funding (Churchill et al., 2014).

Milsom et al. (2014) conducted a 12-week team weight loss experiment.

Their goal was to assess changes in health predictor variables with weight loss.

These researchers found that even with modest weight loss (5-10%), predictors of

health such as high blood pressure improved. Milsom’s et al. (2014) study seems

to corroborate the finding that a 5% to 7% loss in body weight can be protective

against the development of Type II diabetes mellitus (Chalupka, 2011). However,

Milsom et al. (2014) acknowledged little is known about the sustainability of

benefits derived from short-term weight loss programs and recommended further

investigation.

Boyce et al. (2014) also conducted a 12-week weight loss intervention at a

mid-size police organization of about 1700 employees. The intervention was a

team competition, with three to four participants on a team. Measurement of

participant weight was taken at the beginning and again at the end of the 12

weeks. The teams competed against other teams within and between departments.

There were significant weight loss results although there was little difference in

weight loss between genders, but significant weight loss differences between

overweight and obese participants.

Summary and Conclusions

The adverse health effects of being overweight and occupational stress are

well documented and inter-related. There has been researching on weight and

stress, but not conjointly specific to the field of law enforcement. Overweight

officers subjected to high levels of stress endure dual hazards of poor health and

poor job performance. These factors are often synergistic and symbiotic, with one

driving the other and both leading to poor psychological, physical, and social

health outcomes. Law enforcement leaders, administrators, county managers, and

scholars have neglected to address both problems to the cost of their employees as

well as their organizations. Police officers are subject to a variety of esoteric

stressors that also negatively affect their BMI. As a result, overweight and

stressed officers increase health care costs and decrease productivity for their

organizations without a policy to control them. What is not known is how BMI

may impact officer stress levels.

There is well documented research on overweight people and stress

independent of each other. There is also a documented bi-directional relationship

between these variables. What is not known is how stress is related to a police

officer’s bodyweight. Therefore, improving the healthy weight and lowering

stress of officers can have numerous personal and organizational benefits. The

high prevalence of stress and obesity in police forces highlight the need for

interventions and policy advocacy to govern this field. Various methods have

been proposed in the literature to help officers lose weight, increase fitness, and

manage stress. However, widespread implementation on a professional level is

still lacking.

Researchers have not studied the relationship between BMI predicting

officer stress. My project filled that gap. I will discuss the specific methods used

in this study further in the next chapter.

Chapter 3: Research Methods

Introduction

The primary purpose of my quantitative survey project was to advocate

informed wellness policy options for controlling officer body weight and possibly

stress management grounded on the ideal type theory. I have gleaned stress data

from participants and analyzed the relationship between self-reported stressors of

certified police officers and their BMI. This project has expanded the existing

body of knowledge regarding officer wellness and problem-oriented coping

methods for managing anxiety by testing the stress-coping theory as it related to

policy formation. Evaluating best practices for weight control in law enforcement

can further influence public policy and resolve this silent threat. This project was

vital due to the real threat stress poses for police and in turn the public they serve.

In this chapter, I will introduce each of the variables and covariates. The

methodology will be summarized in this chapter to allow other researchers to

replicate this study. I will also disclose the target population, size, recruitment

strategy, and sampling procedures. I gave the participants for this study informed

consent forms and ethical briefings upon agreeing to be part of the project. The

Police Stress Questionnaires are the survey instruments for this project, and I will

discuss them as well as their reliability and validity. I will discuss the SPSS

software used to analyze the data, data cleaning procedures, and screening for the

study in this chapter. Lastly, I will divulge threats to validity along with the

ethical procedures this project followed to ensure total conformity with scholarly

standards.

Research Design and Approach

A cross-sectional survey design project addressed a predictive relationship

between officer BMI and stress. Based on my ability to relate several variables to

determine the degree of a relationship, this was a proper design choice for this

project based on the research questions. The study participants include police

officers broken into a logistically manageable group. I selected participants from a

volunteer pool of certified officers. The survey design best conformed to multiple

linear regression analysis to determine the predictive nature of the variables.

In this project, I collected stress data via the Police Stress Questionnaire

surveys from volunteer police officers in South Florida. The research informed

the method of data collection; the purpose was to advocate policy based on the

predictive relationship between varying BMI levels and the occupational stress

experienced by police officers. Participants took a two-part stress Likert-style

questionnaire which takes less than 5 minutes to complete. I measured the BMI of

each participant via height and weight calculations. A survey design was

logistically suited to answer the research questions in this study, relate officer

weight and officer stress, and control for all other covariates. With over 100

participants, the survey was also a logistically sound choice to measure stressors.

In this project, the independent variable was the BMI of the participating

officers. BMI was anticipated to influence the dependent variable, which was self-

reported police officer stress. Officer stress levels were the effect or the measured

outcome of this project. Other variables which might influence this outcome are

known as covariates, such as family life, health, culture, and officer willingness to

participate. The covariates used for my study were seniority, rank, shift work,

marital status, gender, and age. An investigative survey design with a multiple

regression analysis determined the predictive relationship of each covariate.

Methodology

The survey design chosen for this project bears further discussion with

regards to the population, sampling, recruitment, and the survey itself. The

required participants for this project were certified police officers.

Population

I included the possibility of recruiting all certified police officers at the

agency in South Florida in this experiment. This population by their nature was

not a protected class as officers need to be at least 18 years old to be officers in

Florida. The focus of my project was on officers in South Florida. This project

was generalized to a larger group, such as the total officers in Florida, since the

sample size was representative of the population.

I estimated 1,000 state certified officers in the officer population of my

survey target county agency in South Florida. Conducting a study on the entire

population was not feasible. However, a positive sampling strategy rectified this

inadequacy. All certified officers in the agency were available for inclusion in this

population.

Sampling and Sampling Procedures

For successful research, I partitioned the entire populace of officers into a

subset, which is more efficient (Frankfort-Nachmias, & Nachmias, 2008). I

cannot address the entire population of police officers for this project. I

accomplished obtaining a sample that is representative of the using stratified

sampling. Eliminated from other types of sampling, this was a most successful

method due to the configuration of the populace. The design is probability

controlled and conducted by splitting groups further into strata. This stratagem

possessed accuracy and equality for the population it represented. This design is

also very cost effective based on the number of participants and time required

(Frankfort-Nachmias & Nachmias, 2008).

Over two-thirds of Americans are overweight or obese (Cawley & Price,

2013; Chalupka, 2011; Hostetter, 2007; O’Connor, 2013; Proper et al., 2013a;

Randle et al., 2012; Thompson, 2004a; Wee et al., 2005; Yoo, 2007) but that

number rises to 80% among police officers (Huang & Acevedo, 2011; Shell,

2005). I divided the participant population for my study according to these values,

20% average weight, 40% overweight, and 40% obese BMI. I located these

values from the convention of police officer’s average weight distribution in

research. Based on the research questions, the chosen population cluster was

representative of the populace (Frankfort-Nachmias, & Nachmias, 2008). The

participants were coded based on their measured BMI values and stratified into

three weight distribution groups. Stratification was a derivative of the original

populace to ensure accuracy, qualified, reasonable expenditures, overall unhealthy

weight, and accessibility to interact with the populace for this project (Dantzker &

Hunter, 2012). Maintaining the correct proportions of the three groups ensured the

accuracy of the survey results. From these inclusion criteria, a power analysis was

further utilized to calculate the proper size of the sample (Creswell, 2009).

Power analysis and size. A power analysis method “consists of

determining alpha, power, and effect size” (Creswell, 2009, p. 157). Essentially,

this analysis calculates how large a sample must be to validate a difference in the

populace if any difference exists. The effective sample size was calculated using

this analysis precisely since “the greater size of a sample has no influence on its

accuracy” (Frankfort-Nachmias, & Nachmias, 2008, p. 177). There are specific

standards for this formula; whereas, they depend on the alpha level, power level,

and effect size (Creswell, 2009).

The alpha is referred to as the statistical significance. Simply, it is

customarily .05. This .05 implies a 95% probability of the contentions of the

project will be accurate (Burkholder, 2012), which was sufficient for this project.

The next measure is the power level. The power level is generally signified as

80% and displayed as .80 in this power analysis formula. The .80 means that 80%

of the time the effect would be the cause of the variable. The effect size is how

much effect the variable has on the sample populace; a significant impact requires

fewer participants. These values are standard, but with oversampling the power is

increased.

The power analysis calculation values for this study were for alpha = .05,

power = .80, and effect size= .50. Utilizing these parameters in preliminary

G*Power, the necessary sample size to achieve this power for a two-tailed

multiple linear regression analysis of these variables is (n = 103) participants

(Burkholder, 2012; Faul, Erdfelder, Buchner, & Lang, 2009). As recommended

due to attrition, increasing the size of the sample by 15% countered sample

erosion (Dantzker & Hunter, 2012).

Recruitment, Participation, and Data Collection

The participants recruited for this study were volunteers from a mid-sized

South Florida County. Each volunteer met specific inclusion selection criteria to

verify membership in the required group of this study. Recruiting volunteers was

accomplished via professional department electronic mail notifications, bulletin

board postings, and attending roll calls requesting participation by any officers

who wished to complete this stress survey. This recruitment strategy ensured the

study was conducted with current, serving Florida certified police officers.

Volunteering for this survey was anonymous as well as any interest expressed in

this project was privileged conversation between the volunteer and me. I worked

solely with the volunteers on this project and controlled their data exclusively.

Police department administration permitted me to solicit volunteers for my study

throughout the agency via signed agreement.

Individually, the selection of participants was certified police officers.

There were no special needs populations recruited for this study. I recruited

participants through bulletin board postings and department emails explaining the

project; comparable to the fashion I had recruited participants for previous weight

loss programs I had coordinated from 2005-2017 for that agency as part of my

additional duties when I was employed there. Having open permission, I had

direct access to over 1,000 police officers via email and bulletin board postings. I

assigned respondents a BMI group by stratification for law enforcement. My

years of previous wellness program coordination, participation, and confidentially

codified trust and respect between volunteers and me. I met personally with all

volunteers.

When I recruited the volunteers, they were provided full written informed

consent. That is, I gave the participants acknowledgments that their participation

was voluntary, they could drop out at any time, they would not suffer any

negative treatment regardless if they participated or not. Also, I assured them that

all their data (height/weight measurements and survey answers) remained

anonymous and secured. No collected data had names on it to further protect

recruits. I met with volunteers at roll calls and various locations to obtain their

data.

I recorded the initial weight and height data collection, unassisted. I

collected important demographic covariates from each participant as self-reported

information. Each participant took both sections of the police stress

questionnaires (see Appendix A) at the onset of the project. There was no

additional follow-up with participants after the survey. Participants exited the

study after the survey, and I reassured them of the anonymity of their data; that

concluded their involvement. I collected specific demographic information from

participants at the onset which had an interplay with the primary variables at the

conclusion. Such information gathered was gender, age, rank, seniority, marital

status, and shift work (see Appendix C); this will be discussed further in this

chapter. This demographic information was also used to confirm that I obtained a

representative sample of the population.

Survey. Volunteer officers comprised the experiment and took the survey.

Additionally, they were provided a waiver, full informed consent, a personal

health information waiver, and purpose at the beginning of the experiment by me.

The survey responses remained anonymous even to me and did not contain names

or other identifiers.

I have conducted weight loss programs yearly for this sheriff’s office from

2005-2017. Since inception, that program averaged 149 participants every year

for the wellness initiative. Also, 47.6% of total participants completed my

wellness weight loss program each year, and 27.7% completed the program with

more than 5% body weight lost. That program built a trusting relationship with

the agency, me, and with previous participants. I stratified the groups of

participants to meet the proper ratios of, 20% normal body weight, 40%

overweight, and 40% obese. Previous wellness initiatives I have implemented at

the sheriff’s office deemed the previous G*Power participant numbers of 103

participants feasibly enough for my project. All weight/height measurements and

surveys were conducted and administered by me, personally.

I weighed the participant and measured their height before the volunteers

took the survey. I weighed them on a digital scale which I calibrated before

weighing each participant. That scale weighed objects to the nearest one-fifth of a

pound (.2lb). The participants were instructed to take off their shoes and empty

their bladders before being weighed to maintain consistency. They each weighed

in wearing undergarments, socks, pants, and a shirt with empty pockets. I made

adjustments to participants that wore less than this based on the average weight of

socks or pants for each BMI value stratification group. Participant height was

measured on a hard surface floor against a wall with their back straight and no

shoes. Those that requested privacy were measured and weighed in solitary. The

completed police stress survey had no names, labels, or identifiers on them. Each

participant completed the survey after being measured. Participants were

measured one at a time and took the survey one at a time. I collected the paper

surveys immediately after completion. There is no virtual or digital copy of the

completed surveys; I entered the data from the surveys directly into SPSS, and the

paper surveys were shredded. The SPSS survey data was secured virtually via a

password. After the survey, there was no follow up or contact with the researcher

or participants. I will keep the data from my research for five years and then

delete from its electronic source.

The tool best suited to measure police stress is the Organizational and

Operational Police Stress Questionnaires. This tool has two parts and surveys

officers about topics such as (a) shift work, (b) fatigue, (c) social life, (d) family,

(e) co-worker relations, (f) police administration, (g) resources, and (h) the justice

system. This tool was specifically designed to operationalize police stress into a

composite measurable variable number. I gleaned the data from the survey

answers and transferred them into SPSS v. 24.via spreadsheet. I separated these

survey results into groups (based on their BMI stratification). I calculated the data

subsequently, and a multiple linear regression analysis was performed to

determine the relationship between these variables and covariates.

Instrumentation, Operationalization, and Measurement Analysis

The Police Stress Questionnaires have been widely used for research since

their inception. Boyden (2010), Dean (2014), and Gilbert (2010) used the

Operational Police Stress Questionnaire to measure stress among police officers.

Smith (2013) used both sections of the Police Stress Questionnaires to measure

stress among police officers and further purported the influence gender may have

on stress management. This two-part survey apparatus was explicitly created to

calculate the stress in law enforcement personnel. Dean (2014) and Smith (2013)

ultimately concluded that reducing stress is critical for officer well-being and

recommend further studies on the topic; as such, these tools were best suited for

this study. As this research intended to measure police stress, I found these

surveys fundamentally designed for such a study on the target population. Freely

consented for use, I used these surveys for academic research exploring police

stress, and the surveys are available freely on the Internet. I also received

permission to use these surveys via email from Dr. McCreary, who developed

these tools (see Appendix B).

This proposed study advocated policy via predicting a relationship

between body weight and officer stress. The research questions addressed which

variables required evaluation and how I might conduct this evaluation. The

variables that required evaluation are police stress and BMI. When measuring

police stress; however, a survey tool specially designed to assess perception of

that specific variable was utilized (Frankfort-Nachmias & Nachmias, 2008). This

tool withstood reliability and validity tests as well. Previous literature guided me

on whether I should construct a new scale or employ a tool previously tested. In

this case, the literature review validated occupational stressors as a principal cause

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of conflict for officers (Boyden, 2010; Kaur, Chodagiri, & Reddi, 2013; Violanti

et al., 2011). Many of the scholarly reviews of police stressors measure and

recommend reducing stress; yet, a negligible amount of the projects conducted

experiments to accomplish this recommendation. One such tool used to measure

police stress in numerous other scholarly studies was the Occupational and

Operational Police Stress surveys.

This tool was a pre-designed Likert-scaled survey of two sections, and

they were explicitly intended to quantify the impact of stressors in police work

(McCreary & Thompson, 2006). I used these scales for my project. There are two

sections of this survey of twenty questions each. McCreary and Thompson (2006)

designed this reliable and valid tool to measure stress exclusively for police

participants. The conception of the police stress surveys integrated officers into

the study to categorize stressors. An original law enforcement focus group birthed

the survey (n = 55). Additionally, the foremost stressors were subsequently

provided to the second group of officers who assessed the reliability of these

topics. This survey has strong internal consistency, reliability, as well as validity.

Applying the results of the survey to other external aspects is predictive validity.

To assess reliability and validity, McCreary and Thompson (2006)

obtained a second and different population of officers (n = 47) to capture stress on

their survey. These officers also participated in completing numerous other

previously validated stress surveys. McCreary and Thompson’s survey validated

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an excellent positive correlation to other existing stress surveys. Using the re-test

method with yet a third cluster of police (n = 197), McCreary and Thompson

achieved high reliability with a (.92) positive Cronbach’s alpha (2006). The fourth

cluster of officers (n = 188) took the survey along with two job satisfaction

surveys. This further test of reliability again validated strong internal consistency

with a (.93) positive Cronbach’s alpha. This tool has been used liberally in

scholarly studies since their advent. To cite several, Boyden (2010), Dean (2014),

Gilbert (2010), and Smith (2013), conducted projects on police stressors and

employed both sections of the Operational and Occupational Police Stress

Questionnaires as a measuring device in their respective projects. My project

utilized both original and unmodified sections of the survey tool to measure police

stress. Participants rated their stress on varying topics on the Likert scale and

averaged all answers into a continuous interval level variable (McCreary &

Thompson, 2006)

Operationalization of constructs. The survey design also required

stratified sampling and assignment to the participant groups. Multiple linear

regression analysis is a test designed to determine the percent of the variance

between variables and a predictive relationship between two variables, in this

case, BMI of police officers and stress of police officers. In my project, the

independent variable was BMI, determined via a formula of height and weight.

Body mass index may have influenced the dependent variable, which is self-

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reported officer stress, measured with a validated survey tool. As BMI and stress

have a spurious relationship, several covariates were included to reduce the

impact on stress (Frankfort-Nachmias & Nachmias, 2008). As identified in the

literature review, these variables co-varied and had a pre-existing relationship to

stress as covariates; they were collected and included in the analysis.

Controlling for these other variables, the unique association between

stressors and BMI was identified. Stronger confidence in the results is provided

with more covariates in a study (Frankfort-Nachmias & Nachmias, 2008).

Including the covariates in a study ensured reducing spurious chance relationships

between BMI and stress. The time in police service or seniority (SEN) has been

found to be positively associated with stress and coping ability as Wang et al.

(2014) researched stress, burnout, and job satisfaction. I measured seniority in 5-

year intervals.

Smith (2013) conducted a law enforcement study signifying marriage

(MAR) was a factor in stress. I measured marriage status in three categories. Shift

work (SW) also plays a negative role in strain (Gerber et al., 2013; Wirtz &

Nachreiner, 2012). I measured shift work in two categories, day shift and every

other type of shift. Job description, or rank (RAK), was an organizational factor

also found to negatively impact anxiety (Johnson, 2012; Zachar, 2004). I

measured rank by each job title up to captain. Age (AGE) and gender (GEN)

demographic information were collected as well from subjects as these variables

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also impact stress in some manner. For example, my study differentiated a

divorced male captain with 17 years of experience from a married female sergeant

with 27 years of experience, based on these variables.

Data Analysis Plan

My reported data was analyzed by SPSS v. 24 using multiple linear

regression analysis. The purpose of this analysis was to determine the percent of

change in variance and predict conditions of the variables (Field, 2009). The

SPSS software also assisted in the data cleaning, as needed. The police stress

survey is a Likert scale rating system (1-7), and I screened data for incorrect

codes, errors, and wild codes. Once participants answered all questions, the scores

are designed to be combined and averaged; authors validated the survey in this

manner.

The posed research questions and constructed hypotheses were:

RQ1: Will BMI significantly contribute to the percent change of R

variance accounted for in the predictive effect of self-reported organizational

stress in the past 6 months among south Florida police officers, after controlling

for age, gender, rank, marital status, shift work, and seniority?

1: BMI, when combined with stress, will not significantly contribute to

the percent change of R

variance accounted for in the predictive effect of self-

reported organizational stress in the past 6 months among south Florida police

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officers, after controlling for age, gender, rank, marital status, shift work, and

seniority.

1: BMI, when combined with stress, will significantly contribute to the

percent change of R

variance accounted for in the predictive effect of self-

reported organizational stress in the past 6 months among south Florida police

officers, after controlling for age, gender, rank, marital status, shift work, and

seniority.

RQ2: Will BMI significantly contribute to the percent change of R

variance accounted for in the predictive effect of self-reported operational stress

in the past 6 months among south Florida police officers, after controlling for age,

gender, rank, marital status, shift work, and seniority?

2: BMI, when combined with stress, will not significantly contribute to

the percent change of R

variance accounted for in the predictive effect of self-

reported operational stress in the past 6 months among south Florida police

officers, after controlling for age, gender, rank, marital status, shift work, and

seniority.

2: BMI, when combined with stress, will significantly contribute to the

percent change of R

variance accounted for in the predictive effect of self-

reported operational stress in the past 6 months among south Florida police

officers, after controlling for age, gender, rank, marital status, shift work, and

seniority.

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Multiple regressions are a statistical analysis designed to find a

relationship between one dependent variable and an independent variable and one

or more covariates. The multiple regression analysis should is used when

predicting an outcome based on multiple variables (Field, 2009; Marrow, 2013),

as in my study. The sensitivity in identifying relationships between variables

made it an ideal analysis choice for this study (Can & Hendy, 2014). In this case,

there was the likelihood that the officers could face additional stressors once the

study begins that potentially affected the results; a t-test could not distinguish

such testing partiality (Shirley, 2013).

The purpose of multiple regression is to examine the relationship between

several predictor variables and one outcome variable (Marrow, 2013b; Statsoft,

2013). This analysis will determine a relationship between these variables;

however, it does not explain why the relationship exists or imply any causation on

the dependent variable. Multiple regression analysis is best suited for a study

which has more than one independent variable and predicting one variable from

another. It also identifies the importance of each independent variable (Field,

2009; Marrow, 2013b).

Assumptions

There were assumptions for a multiple regression which affect the strength

of the results. These variable assumptions are that they are normally distributed

variables within the groups, the independent variables should not be too closely

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correlated, and accounting for outliers before analysis (Marrow, 2013b; Field,

2009). Independent variables must be quantitative or categorical and dependent

variables must be quantitative, continuous, and unbounded.

Variables

The independent variable in my study was BMI, which was continuous

and measured at an interval level. I identified the dependent variable as stress,

measured via a survey on a Likert scale. The subjective nature of a survey

participants’ answers defined this variable as categorical; however, the authors of

the Police Stress Questionnaire utilized the final stress score as a continuous

interval leveled variable (McCreary & Thompson, 2006). This study met the

criteria for standard multiple regression analysis (Marrow, 2013c; Field, 2009, p.

209). When covariates are gleaned from previous research, the forced entry

method is acceptable. The forced method is where the researcher determined

which variable to test and in which order (Field, 2009). Research has identified

other variables impacting stress, but it is unknown which influences stress the

most. Dealing with the outlier’s assumption is a choice in the statistics options

SPSS box under residuals. SPSS output measures other assumptions.

There are additional variables identified from extant research, which

impacted officer stress. Wang et al. (2014) found the time in police service or

seniority (SEN) positively associated with stress and coping ability. Seniority was

a continuous variable measured at the ratio level. Smith (2013) conducted a law

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enforcement study which indicated marriage was a significant factor in managing

levels of stress for law enforcement officers. Marital status (MAR) of the officer

was, therefore, another covariate; being married and having a family impacted

officer stress positively. Marriage was a categorical nominal measured variable.

Working anomalous hours was yet another covariate which potentially negatively

influenced stress; shift work (SW) also played an adverse role in stress (Gerber et

al., 2013; Wirtz & Nachreiner, 2012). Shift work was a categorical nominal

measured variable. Smith (2013) measured stress among police officers, and

further purported the definite influence gender (GEN) had on stress management.

Chen (2009) agreed gender plays a part in stress coping and gender was a

categorical nominal measured variable. Chen (2009) also posited age as a factor

harmfully influencing stress. Age (AG) was a continuous interval measured

variable.

Different job requirements or duties were also a covariate conveyed as

rank (RAK) for this study. Rank was an organizational factor also found to reduce

stress (Johnson, 2012; Zachar, 2004) and it was an ordinal categorical variable.

Each of these variables had some impact on stress, according to the literature.

The first step involved organizing and preparing the data for analysis. That

included coding responses to the survey for each participant, along with

aggregating data on the covariates and selected demographics. The data was

analyzed using SPSS v. 24 IBM statistical software. These data allowed the

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researcher to measure levels of stress against varying officer weight. The data

revealed if the police officer’s stress was related to body weight in some manner

and direction.

The analysis included the evaluation of those covariates and the impact

they might have on the dependent variable. An analysis of the data needed to

include those survey questions which indicated other factors including an officer’s

relationship status and their rank as an officer. Addressing these variables enabled

proper interpretation of the results. The covariates conveyed support that the

relationship between the independent and dependent variable is possible. A

regression analysis verified whether varying body weight loss would predict

officer stress levels.

Threats to Validity

A study will lack focus without containing the confidence that the research

has been able to measure the specific variables and outcomes they intended to

measure (Frankfort-Nachmias, & Nachmias, 2008). Validity is when the

measuring tool indeed assessed the proper information from the variable. The

essential element of any scientific study, whether it is survey or intervention-

based, is maintaining validity and reliability. That is, the outcomes of the research

should withstand against credible threats to its soundness. To ensure reliability, a

concept which is indivisible from validity, police officers participated in the

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surveys. The forms of validity concerned in survey design projects are external,

internal, and construct.

External Validity

Selection threats existed due to the esoteric qualities of the participants.

This form of validity threat disallows the researcher from generalizing the

findings to populations who do not share similar qualities or culture. Police

culture is unique, and the results of this study have not been generalized to

populations outside of the law enforcement genre. To further solidify the

generalization to other law enforcement populations; however, officers from

several different law enforcement agencies could have been included in the

project, although logistically exhaustive. Selection and treatment validity was

addressed by generalizing results only to law enforcement officers and could be

further diffused with a multi-agency officer participant inclusion (Creswell, 2009)

if it were logistically feasible.

Setting validity threats were present and required addressing to strengthen

the generalization of results to participants in other settings. I used several settings

in this study and additional police agencies could be utilized to ensure

generalization better. To additionally bolster the ability to project the results on a

broader representation of the population, history validity threats were analyzed as

well. This threat is the inability to project the results to past or future

circumstances due to the timing of the event. Replicating the experiment later and

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comparing the results could eliminate this threat. Logistically for this project, it

was not feasible to replicate the project. Creswell (2009) recommends future

studies with new participants for history validity.

Specificity of variables was not an issue in this particular research study as

the variables were specific, narrowly operationalized, and defined. Specificity

made it that much easier to identify the settings into which the results were

generalized. Even further, the reactive effects of the survey were a threat to the

validity of the study because the police officers knew they were engaged in a

study voluntarily. When participants know they are involved in a study, it can

result in altered or distorted perceptions of their stress levels or inaccurate

responses to survey measures. I planned to combat this threat by providing only

the information necessary for the volunteers to make an informed decision.

Limiting information, but not misleading them means I told participants this was a

stress survey and did not inform them the final data was going to be used as

evidence to develop a wellness program or policy. Also, maintaining

confidentiality between volunteers ensured no information was shared that will

bias or skew the results.

Internal Validity

To guard against history as a validity threat, I gave the survey in a single

stage, cross-sectional sample of volunteers from the agency. Involving the human

element, however, is unpredictable by design. For instance, not all participants

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suffered the loss of a loved one during this project, yet some may have. The loss

of a loved one was a factor that cannot be controlled or predicted and will impact

the effect of stress on an officer. Additionally, officers who have sustained a

massive event stressor did not participate in the study upon questioning (Creswell,

2009).

Maturation was addressed with the inclusion of the control variable of age.

With a robust analysis, this threat was removed as maturity was likely to affect

both weight and stress in some manner. Those with unrepresentative one-sided

scores on the surveys were considered outliers and were removed from the study

at the onset to address regression threats. Equal distribution of participant

qualities referred to selection validity and was a hazard for this project.

Stratification selection of participants overcame this problem by representing a

viable cross-section of the participants. Recruiting a participant sample group

larger than G*Power recommended via power analysis addresses the mortality

threat.

Diffusion is a minor validity threat matter due to participants taking the

survey in a single stage. There was no reward or financial compensation for any

officer in this study; therefore, negating compensatory demoralization and rivalry.

Experimental mortality also affected the study. No one can know how many

participants may drop out of the study due to unforeseen circumstances like death,

relocation, and lack of continued interest. This threat was mitigated by

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oversampling and including more participants in the study than necessary to have

a representative sample, ensuring via probability that enough volunteers remain at

the end of the study to perform analysis of any statistically significant results.

Construct Validity

Construct validity encompasses weak descriptions and inept appraisals of

the variables (Creswell, 2009). I bolstered construct validity when the survey

instrument was interrelated to the concepts of the research theory (Frankfort-

Nachmias, & Nachmias, 2008). The survey measured police stress and the coping

theory directly related to how people cope with stress. The stress-coping theory

was the stress foundation for this project, and the research questions were

grounded in this theory. Essentially, this theory postulates a problem-oriented

response to an identified stressor will resolve the problem and alleviate the stress.

I tested this theory deductively; I assumed that being overweight was a stressor,

especially in law enforcement, for various rationales identified in the literature

review.

Lazarus and Folkman (1984) said a problem-oriented response would

reduce the stress linked to that problem. To deductively test this theory, I assumed

being an overweight police officer increased stress. I based the research questions

on theoretical reasoning. Secondly, I corroborated the construct validity by using

a known-groups technique as suggested by Frankfort-Nachmias and Nachmias

(2008). I could have furthered construct validity by providing the stress surveys to

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a group of officers previously identified as suffering from stress, via another

validated survey tool, and compared the results. McCreary and Thompson (2006)

performed this function while designing their tool as discussed earlier in this

chapter.

Ethical Protections

This research followed all previously established ethical controls for

human experiments. Access to participants was by agency permission at roll calls,

bulletin board postings, and via professional department emails. I had open access

and written department permission to recruit employee participants. The

participants were not misled or deceived in any form before, during, or after this

experiment. From the onset, I provided them with an IRB approved informed

consent form which they acknowledged if they chose to participate (Frankfort-

Nachmias, & Nachmias, 2008).

I obtained informed consent and data collection approval from the

Internal Review Board of Walden University (IRB# 1215170333535). The

informed consent explained all risks, rights, benefits, and dangers for this project.

Participation was free and voluntary. The risk of taking the survey was minimal.

Any exposure to discomfort or pain was minimal or non-existent. In cases of an

adverse reaction to the survey, medical or physiological, the officer was referred

to voluntary employee assistance, which is free of cost through the department.

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Assuring their privacy, anonymity, and confidentiality in the recruitment

material was disclosed at the onset of the experiment. Continuing and open

permission from the agency allowed me to recruit volunteers from the department

freely. The recruitment materials were sent out department-wide and posted

conspicuously throughout the agency to allow any police officer to participate.

Each participant decided to take the survey and I did not share their data with

other members, volunteers, participants, or employees. All volunteers were

informed and allowed to drop out of the survey at any time without penalty or

discrimination of any kind. By privacy and confidentiality regulations, I did not

provide raw data to anyone in the agency.

Once I collected the survey data, it was stored in electronic form in a

secured location. These data were entered in a spreadsheet in Excel for cleaning

then imported in data fields in SPSS. I stored the data on two separate data storage

drives secured with password protection for five years. I will destroy all data after

that time. This survey was conducted in my previous work environment, as I was

a supervisor in the police agency. I reassured all employees there was no

discrimination or maltreatment if they chose not to participate in this project.

There were no incentives provided for this study other than participating in a

stress survey for employees, which some participants may have deemed a benefit

in and of itself.

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Summary

This project predicted officer stress outcomes by use of a single stage

cross-sectional survey design. The strengths of this design were numerous. This

design is broadly accepted in research and permits inclusion of covariates

allowing a stronger inference of the effect of the tested variable. It is the superior

design choice to illustrate the predictive relationship between the variables. I

chose a stratified sampling of the participants from volunteers after full ethical

procedures and informed consent for this study. Participants took the surveys in

paper form. I entered the data in SPSS for analysis using multiple regression.

In Chapter 4, there will be a description of the results obtained from this

experiment. Chapter 4 will include data collection, respondent demographic

results, and full descriptive statistic results. How these results impact the

hypothesis for this study will also be discussed. In Chapter 5, I will explore study

weaknesses and opportunities for future research as well.

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Chapter 4: Results

Introduction

With wellness and officer safety issues at stake, the primary goal of my

quantitative survey project was to propose sound and informed policy options for

controlling body weight and possibly stress management, grounded on the ideal

type theory, via a hypothesis that there is a relationship between BMI and police

officer stress. I examined the predictive relationships between officer stress and

BMI, age, gender, rank, marital status, shift work, and seniority to guide policy in

this area. To achieve this, I asked these research questions:

RQ1: Will BMI significantly contribute to the percent change of R

variance accounted for in the predictive effect of self-reported organizational

stress in the past 6 months among south Florida police officers, after controlling

for age, gender, rank, marital status, shift work, and seniority?

RQ2: Will BMI significantly contribute to the percent change of R

variance accounted for in the predictive effect of self-reported operational stress

in the past 6 months among south Florida police officers, after controlling for age,

gender, rank, marital status, shift work, and seniority?

To answer these research questions, I used a multiple linear regression

analysis. Linear regression analysis is used to determine the percent of change in

variance and predict an outcome based on multiple variables (Field, 2009;

Marrow, 2013). Multiple regression is a statistical analysis designed to find a

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relationship between one dependent variable and several covariates. My research

analysis had multiple covariates influencing stress as identified from previous

research. Further, into this chapter, I will present the purpose and the research

questions and will additionally discuss data collection methods, results, and the

data table analysis. I will conclude the chapter with a summary of the results.

Data Collection Procedures

After I obtained informed consent and data collection approval from the

Internal Review Board of Walden University (IRB #1215170333535), I solicited

police volunteers for my survey study. I recruited volunteers via bulletin board

and email postings at a midsized police agency in South Florida. The agency

provided written permission for me to conduct the study with their employees.

The bulletin board recruitment postings were not deceptive in any way. For

uniformity, I conducted and calculated the height and weight of the volunteers

without any actual physical touching participants to accomplish this. I set a single

week period at the beginning of January 2018 where I attended department roll

calls, set up measuring sessions, and performed the data collection.

During my survey week, participation was open to any certified police

officer in the agency. I collected the survey and measurement data. I provided

each volunteer with the informed consent form, which had information about the

project, the procedures, the voluntary nature of the study, the risks, and the right

to withdraw at any time. Additionally, I provided my contact information for

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questions as well as contact information for the IRB at Walden University. I gave

each volunteer a personal health information form regarding the collection of

mental health data concerning the survey. I provided the volunteers with these

forms; however, for the protection of their privacy, they did not sign them. I did

not link biometric measurements, or survey responses to actual persons as officer

participation were entirely confidential. The biometrics of each participant as well

as collected covariate data were attached to their corresponding survey. Matching

the biometrics to surveys aided in rejecting the covariates of a participant if the

survey was incorrect or incomplete.

Data collection transpired for approximately seven days. All participants

who provided consent forms completed the entire research process, and no

participant requested to stop the research procedure. I sent recruitment literature

to all agency certified officers via emails; there were approximately 1,000

prospective participants. After the survey collection week, I recruited, weighed,

and surveyed (n = 132) participants from the agency, with a total response rate of

11.7%; all but four of the surveys were usable and completed copiously. The four

incomplete surveys were discovered and excluded. There was no deviance from

the previously reported data collection methods outlined in Chapter 3.

There were no other missing data and the number of usable recruited

volunteers, n = 128, exceeded the minimum sample size of 103, calculated by my

preliminary G*Power analysis for the desired .80 power of this analysis. The

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ample number of participants was proportional to the larger population of law

enforcement officers as well. After collecting all the surveys, I calculated and

entered the Police Stress Questionnaires data into an Excel file. Entering data

included the additional coded covariates of marriage, age, gender, rank, shift

work, and seniority. I subsequently uploaded these data into IBM SPSS v. 24.0

software for analysis. Each variable was coded numerically; I represented marital

status in this manner: married = 1, single = 2, and co-habituating = 3, for instance

(see Appendix D).

Data Testing and Outputs

I first ran data frequency distributions to evaluate for missing or erroneous

values. I assessed these data for central tendency, mean, median, and mode. I

evaluated responses for skew (width of distribution) and kurtosis (peak of

distribution) to estimate the output fit under a normal curve. This evaluation was

completed to verify I could use these data in a parametric format rather than

requiring nonparametric procedures. The distribution of the continuous level data

was found to fit under a normal curve.

Demographic Results

Nonprobability sampling is common in measuring a relationship between

variables, as in my study. I further stratified this sample by BMI grouping

representing three BMI clusters found in previous research. These groups were

normal BMI (n = 26), overweight BMI (n = 50), and obese BMI (n = 52). These

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strata were representative of the 80% overweight and obese proportional BMI

groups in law enforcement according to prior research. Each participant

completed the survey, and I calculated their BMI to the nearest tenth. The sample

also consisted of more males (n = 90) than females (n = 38). The mean BMI of all

participants closely approached the obese body weight rating (m = 28.9%)

although all three BMI stratified groups were represented correspondingly

according to prior research.

Frequency Distributions

Demographic data were collected to define characteristics but also as

covariates since prior research showed each impacted the dependent variable in

some manner. Table 1 represents the BMI makeup of volunteers for my project.

Most (78.9%) of the participants were married as displayed in Table 2. The most

represented age group was 40-49 years old (45.3%) represented in Table 3. The

gender of participants in Table 4 were mostly men (70.3% males; 29.7% females).

Displayed in Table 5, many of the volunteers were low ranking officers (61.7%),

and 64.1% were on varying shifts or on-call hours represented in Table 6.

Regarding time on the job, the largest group represented in Table 7 were those

officers employed 6-10 years (34.4 %).

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Table 1

Statistics for BMI, Organizational Stress, and Operational Stress

BMI

Organizational Stress

Ope

rational Stress

N 128 128 128

Mean 28.904 2.7680 2.8430

Std. Deviation 3.7081 1.10894 1.19495

Skewness -.351 .447 .753

Std. Error of Skewness .214 .214 .214

Kurtosis -.533 -.204 .159

Std. Error of Kurtosis .425 .425 .425

Range 16.0 5.30 5.30

Table 2

Statistics for Marital Status

Frequency Percent

Valid Married 101 78.9

Single 26 20.3

Cohabitating 1 .8

Total 128 100.0

Table 3

Statistics for Age

Frequency Percent

Valid <29 3 2.3

30 to 39 14 10.9

40 to 49 58 44.6

50 to 59 42 32.8

>60 11 8.6

Total 128 100.0

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Table 4

Statistics for Gender

Frequency Percent

Valid Male 90 70.3

Female 38 29.7

Total 128 100.0

Table 5

Statistics for Rank

Frequency Percent

Valid Deputy/Officer

79 61.7

Detective 21 16.4

Sergeant 20 15.6

Lieutenant 5 3.8

Captain or Above 3 2.3

Total 128 100.0

Table 6

Statistics for Shift Work

Frequency Percent

Valid Yes 82 64.1

No 46 35.9

Total 128 100.0

Table 7

Statistics for Seniority Years of Service

Frequency Percent

Valid <5 years 14 10.9

6 to 10 years 44 34.4

11 to 15 years 32 25.0

16 to 20 years 21 16.4

21 to 25 years 9 7.0

>26 years or more

8 6.3

Total 128 100.0

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Correlation Coefficients

Evaluating the correlation coefficients of the three primary independent

variables in this study (BMI, organizational stress, and operational stress) was

critical to determine their independent operation in the regression model.

Variables with strong correlation, or multicollinearity, influence the percent of

change in the R

output in a fashion which makes it problematic to ascertain

which variable is influencing the R

output. The correlations table below (Table 8)

showed the value of Pearson’s r for the correlation between organizational stress,

operational stress, and BMI. There was a relationship between organizational

stress and BMI (r = -.204; p = < .005, 2-tailed). Organizational stress also had a

significant relationship with operational stress (r = .744; p = < .001, 2-tailed).

This significance between organizational stress and operational stress illustrated

multicollinearity, which may have had a bearing in regression output computation

and interpretation.

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Table 8

Correlations for Organizational Stress, Operational Stress, and BMI

BMI Organizational

Stress

Operational

Stress

Body Mass

Index Pearson Correlation 1

Sig. (2-tailed)

N 128

Organizational

Stress Pearson Correlation -.204

Sig. (2-tailed) .021

N 128 128

Operational

Stress Pearson Correlation -.164 .744

Sig. (2-tailed) .064 .000

N 128 128 128

Note.

Correlation is significant at the 0.05 level (2-tailed).

Correlation is significant at the 0.01 level (2-tailed).

Hypothesis Testing Results

Survey data addressed two research questions with linear regression

analyses to evaluate both hypotheses. Operational stress (m = 2.843) had an

overall higher mean score than organizational stress (m = 2.768) in this

population. Given the close approximation of these values, a t-test was conducted

to determine the significance, if any, between mean values of these independent

but related stress scales. No statistically significant differences between

operational stress and organizational stress were observed (p = 0.479).

McCreary and Thompson (2006), authors of the Police Stress

Questionnaires, determined these scales to be independent measurements of some

form of stress in police officers. For my participants, no statistically significant

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difference between operational and organizational stress scale scores was

observed. Additionally, McCreary, Fong, and Groll (2017) developed normative

baseline values for these questionnaires. They found mean normative scores for

organizational stress range values to be m = 3.49-3.57 and operational stress mean

scores to fall in the m = 3.22-3.30 range. These implications will be discussed

further in Chapter 5.

Table 9

One-Sample T-test Test Value = 2.7680*

95% Confidence Interval of the Difference

t df

Sig. (2-

tailed)

Mean

Difference Lower Upper

Operational

Stress .710 127 .479 .07497 -.1340 .2840

*participant mean scale score for Organizational Stress

Regression Data Entry

I used the forced entry for the data in SPSS for this regression model for

the first block and forced entry for the second block. An analysis was completed

for organizational stress (RQ1) in the first block with covariates of marriage, age,

gender, rank, shift work, and seniority as combined predictors. Organizational

stress was the dependent variable, and BMI was the independent variable of

interest tested in the second block. A second analysis was completed for

operational stress (RQ2) in the first block with covariates of marriage, age,

gender, rank, shift work, and seniority as combined predictors. Operational stress

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was the dependent variable, and BMI was the independent variable of interest

tested in the second block.

Organizational Stress

RQ1: Will BMI significantly contribute to the percent change of R

variance accounted for in the predictive effect of self-reported organizational

stress in the past 6 months among south Florida police officers, after controlling

for age, gender, rank, marital status, shift work, and seniority?

1: BMI, when combined with stress, will not significantly contribute to

the percent change of R

variance accounted for in the predictive effect of self-

reported organizational stress in the past 6 months among south Florida police

officers, after controlling for age, gender, rank, marital status, shift work, and

seniority.

1: BMI, when combined with stress, will significantly contribute to the

percent change of R

variance accounted for in the predictive effect of self-

reported organizational stress in the past 6 months among south Florida police

officers, after controlling for age, gender, rank, marital status, shift work, and

seniority.

Table 10 illustrated two models for organizational stress tested via

multiple linear regression. Model 1 illustrated the covariates alone in this study

and model 2 illustrated the covariates with BMI as an isolated predictor variable.

For model 1 the R

change value and effect size was .113, indicating the grouped

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covariates in model 1 accounted for 11.3% of the variation in organizational stress

(F (6, 127) = 2.564, p = .023; Table 11) and illustrated that one or more covariates

was a significant predictor of organizational stress (F

change

= .023 < .05). For

model 2, the R

change value and effect size was .025, indicating the grouped

covariates and BMI accounted for 2.5% of the variation in organizational stress (F

(7, 127) = 3.485, p = .064; Table 11) and illustrated that when BMI was added to

the regression model no independent variable combinations significantly

contributed to organizational stress (F

change

= .064 > .05).

Table 10

Multiple Regression for Organizational Stress Regressed on Covariate Predictors

Std.

Error of

the

estimate

Change statistics

Model

R R

Adjusted

change

change df1 df2

Sig. F

change

1 .336

.113 .069 1.07011 .113 2.564 6 121 .023

2 .371

.138 .088 1.05929 .025 3.485 1 120 .064

Note.

a. Model 1 predictors = (constant), seniority, shift work, gender, marital status, rank, age;

b. Model 2 predictors = (constant), seniority, shift work, gender, marital status, rank, age,

body mass index;

c. Dependent Variable: Organization Stress.

Table 11 illustrated the ANOVA table for models 1 and 2 for

organizational stress. Model 1 had a significant F-ratio of 2.564 for variables

excluding body mass index (Sig. = .023 < .05). Model 2 illustrated a significant

F-ratio of 2.741 for all variables. In the organizational stress model, all covariates

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were significant when grouped together (Sig. = .011 < .05). The model for

organizational stress was a significant fit for all data overall.

Table 11

ANOVA for Organizational Stress Regressed on Covariate Predictors

ANOVA

Model Sum of Squares df Mean

square F Sig.

1 Regression 17.616 6 2.936 2.564 .023

Residual 138.563 121 1.1145

Total 156.179 127

2 Regression 21.526 7 3.075 2.741 .011

Residual 134.652 120 1.122

Total 156.179 127

Note.

a. Dependent variable: Organizational Stress.

b. Model 1 predictors = (constant), seniority, shift work, gender, marital status, rank, age;

c. Model 2 predictors = (constant), seniority, shift work, marital status, rank, age, body

mass index;

The scatter plot (see Appendix E) illustrated a random array and even

dispersal of dots in the data reiterating the assumptions had been met in the model

(Field, 2009). These validated normal distribution of the residuals. The

coefficients table (Table 12) displayed the B-value or weight, and this indicated

the relationship between stress and each predictor and illustrated the predictive

relationship’s strength. The coefficients table also showed the beta value which

provides relationship direction as well as standard deviation changes. For

organizational stress in model 2, the covariate of shift work was statistically

significant (.008 < .05). Model 2 additionally illustrated a statistical significance

of two covariates on organizational stress: (a) seniority (.019 < .05); and (b) shift

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work (.08 < .05). Between these two significant covariates shift work posed the

most statistically significant predictive relationship with a B = .537 value. For

each one increment value higher on the shift work scale, it was predicted an

officer’s organizational stress score would increase by .537 units. While these two

covariates demonstrated significance in the model, they were not the primary

predictor variable of interest. When considering the primary variable of BMI, and

controlling for my covariates, the null hypothesis was retained with BMI having

no predictive significance for officer-reported organizational stress greater than

chance.

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Table 12

Multiple Regression Coefficients for Organizational Stress Regressed on

Independent Predictors

Model

Unstandardized

Coefficients

Standardized

coefficients

B Std. Error Βeta t Sig.

1 (Constant) 2.460 .649 3.791 .000

Marriage -.187 .235 -.073 -.795 .428

Age .219 .136 .173 -1.612 .110

Gender -.086 .222 .036 -.389 .698

Rank .070 .102 .064 .685 .495

Shift Work .567 .199 .246 2.849 .005

Seniority .168 .091 .203 1.842 .068

2 (Constant) 3.991 1.042 3.832 .000

Marriage -.159 .233 -.062 -.680 .498

Age .226 .135 -.178 -1.676 .096

Gender -.107 .220 -.044 -.487 .627

Rank .064 .101 .059 .637 .525

Shift Work .537 .198 .233 2.719 .008

Seniority .147 .091 .178 1.614 .019

Body Mass

Index -.049 .026 -.163 1.867 .064

Dependent Variable: Organizational Stress

Operational Stress

RQ1: Will BMI significantly contribute to the percent change of R

variance accounted for in the predictive effect of self-reported operational stress

in the past 6 months among south Florida police officers, after controlling for age,

gender, rank, marital status, shift work, and seniority?

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RQ2: Will BMI significantly contribute to the percent change of R

variance accounted for in the predictive effect of self-reported operational stress

in the past 6 months among south Florida police officers, after controlling for age,

gender, rank, marital status, shift work, and seniority?

Two models illustrated in Table 13 for operational stress were tested via

multiple linear regression. Model 1 illustrated the covariates alone in this study

and Model 2 illustrated the covariates with BMI as an isolated predictor variable.

For Model 1, the R

change value and effect size was .064, indicating all the

covariates in Model 1 accounted for 6.4% of the variation in operational stress (F

(6, 127) = 1.388, p = .225; see Table 14). For Model 2, the R

change value and

effect size was .025, indicating the covariates and BMI accounted for 2.5% of the

variation in operational stress (F (7, 127) = 3.339, p = .070; see Table 14). Model

1 illustrated a trend towards significance, but the regression output remains non-

significant (F

change

= .225 > .05). In Model 2, with BMI added to the regression

model, no independent variable combinations significantly contributed to

operational stress (F

change

= .070 > .05).

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Table 13

Multiple Regression for Operational Stress Regressed on Covariate Predictors

Std.

Error of

the

estimate

Change statistics

Model

R R

Adjusted

change

change df1 df2

Sig. F

change

1 .254

.064 .018 1.18413 .064 1.388 6 121 .225

2 .300

.090 .037 1.17285 .025 3.339 1 120 .070

Note.

a. Model 1 predictors = (constant), seniority, shift work, gender, marital status, rank, age;

b. Model 2 predictors = (constant), seniority, shift work, gender, marital status, rank, age,

body mass index;

c. Dependent variable: Operational Stress.

Table 14 illustrated the ANOVA table for models 1 and 2 for operational

stress. Model 1 did not have a significant F-ratio of 1.388 for variables excluding

BMI (Sig. = .225 > .05). A non-significant F-ratio of 1.690 was illustrated in

model 2 for all variables. In the operational stress model, all covariates were not

significant when combined (Sig. = .118 > .05). The model for operational stress

was a significant fit for all data overall. Table 15 further illustrated when

controlling for covariates marital status, age, gender, rank, shift work, and

seniority, BMI was not a significant predictor of R

percent change in variance for

operational stress.

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Table 14

ANOVA for Operational Stress Regressed on Covariate Predictors

ANOVA

Model Sum of Squares df Mean

square F Sig.

1 Regression 11.681 6 1.947 1.388 .225

Residual 169.663 121 1.402

Total 181.344 127

2 Regression 16.274 7 2.325 1.690 .118

Residual 165.069 120 1.376

Total 181.344 127

Note.

a. Dependent variable: Operational Stress.

b. Model 1 predictors = (constant), seniority, shift work, gender, marital status, rank, age;

c. Model 2 predictors = (constant), seniority, shift work, marital status, rank, age, body

mass index;

The scatter plot (see Appendix F) illustrated a random array and even

dispersal of dots in the data reiterating the assumptions had been met in the model

(Field, 2009). These validated normal distributions of the residuals. The

coefficients table (Table 15) displayed the B-value or weight, and this indicated

the relationship between stress and each predictor and illustrated the predictive

relationship’s strength. The coefficients table also showed the beta value which

provided relationship direction as well as standard deviation changes. For

operational stress in model 1, the covariate of age was statistically significant

(.050 = .05). Model 2, none of the covariates combined with BMI were

significant. Age posed the most statistically significant predictive relationship

with a B = -.298 value. For each one increment value higher on the age scale, it

was predicted an officer’s organizational stress would decrease by .298 units.

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While this covariate demonstrated significance in the model, it was not the

primary predictor variable of interest. When considering the primary variable of

BMI, and controlling for my covariates, I retained the null hypothesis with BMI

having no predictive significance for officer-reported operational stress greater

than chance.

Table 15

Multiple Regression Coefficients for Operational Stress Regressed on

Independent Predictors

Model

Unstandardized

Coefficients

Standardized

coefficients

B Std. Error Beta t Sig.

1 (Constant) 2.559 .718 3.564 .000

Marriage .059 .260 .021 .227 .821

Age -.298 .151 -.218 -1.981 .050

Gender .137 245 .053 .559 .577

Rank .133 .112 .114 1.181 .240

Shift Work .392 .220 .158 1.780 .078

Seniority .094 .101 .105 .928 .356

2 (Constant) 4.218 1.153 3.657 .000

Marriage .090 .258 .033 .348 .728

Age .149 -.223 -2.047 .043 .096

Gender .115 .243 .044 .471 .639

Rank .127 .111 .109 1.139 .257

Shift Work .360 .219 .145 1.645 .103

Seniority .071 .101 .079 .701 .458

Body Mass

Index .053 .029 -.163 -1.827 .070

Dependent Variable: Operational Stress

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Post Hoc Analysis

In each regression model, I identified covariates that were significant and

warranted further individual investigation. For organizational stress, shift work

and seniority were significant predictors and in the operational stress model age

was a significant predictor with BMI trending towards significance. I examined

these variables further.

In the organizational stress model, I looked at shift work and seniority

independently in a correlation matrix analysis. The correlation revealed seniority

was not significantly related with organizational stress; however, shift work

remained significant (r = .248, p = 0.01, 0.01 level 2-tailed). Therefore, I

conducted an organizational stress regression model (Table 16) including shift

work, independent of my covariates and BMI and verified a significant

relationship (p = .005 < .05) accounting for 6.1% of the predictive model.

Table 16

Multiple Regression Coefficients

Model

Unstandardized

Coefficients

Standardized

coefficients

B Std. Error Βeta t Sig.

1 (Constant) 1.992 .286 6.955 .000

Shift Work .571 .199 .248 2.873 .005

Dependent Variable: Organizational Stress

Summary

I found BMI, after controlling for age, gender, rank, marital status, shift

work, and seniority was not a significant predictor of the organizational or

136

operational stress of the officer (F = 3.485, p = .064; F = 3.339, p = .070)

respectively. While an officer’s BMI was not significant to predicting

organizational or operational stress in the full regression models, shift work (R =

.371; p = .008 < .05) and seniority (R = .300; .019 < .05) illustrated weak but

significant predictive relationships. Additionally, in the full regression models,

age illustrated a predictive significance to operational stress (R = .300; p = .050 =

.05). In a post hoc analysis, these three covariates were examined individually

with shift work and organizational stress (R = .248; p = .005 < .05) emerging as

the only significant findings. When considering the primary variable of BMI, and

controlling for my covariates, the null hypotheses were retained for both research

questions with BMI having no predictive significance for officer-reported

organizational or operational stress greater than chance.

I will discuss the implications for social change based on these results in

Chapter 5. I will also describe my conclusions as well as policy recommendations

based on this body of research using ideal type theory as an exploratory lens. I

will also deliberate social change, study limitations, and endorsements for

possible future research in this area.

137

Chapter 5: Discussion, Conclusions, and Recommendations

Introduction

The purpose of this study was to examine the problem of officer stress in

relation to BMI to gain insight into stress outcomes. These outcomes were

hypothesized to serve as a basis for policy construction in law enforcement

agencies to counteract BMI and stress costs. Despite the known damaging effects

of being overweight, Florida does not have a mandatory BMI regulation policy in

place for police officers. The specific problem is the deficiency of such BMI

policy standards for police officers. BMI can also be linked to stress in some

manner (Berset et al., 2011; Proper et al., 2013b). Officer job performance related

to organizational and operational stress is an issue that influences the lifespan,

work quality, and physical and mental wellbeing of police officers (Chikwem,

2017; Violanti et al., 2013).

Officer Stress and BMI

I intended to explore a predictive relationship between BMI and officer

stress. A conceivable relationship could augment and inform policy formation for

better health outcomes regarding stress in officers. I examined multiple covariates

from previous research to strengthen the analysis results. This cross-sectional

quantitative survey study comprised of certified police officers from a midsized

agency in South Florida theorized possible relationships between BMI and officer

stress specifically related to organizational and operational stress factors. I used

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multiple linear regression to measure the strength and direction of these

relationships and predict the relationship between BMI and stress. The lack of

collective studies regarding the relationship between officer BMI and stress

combined has left a gap in scholarly research. This chapter will further provide

explanations of findings, implications for positive social change,

recommendations for future studies, and possible endorsements for further action.

After elaborating on study limitations, I will conclude the chapter with my final

research implications.

Interpretation of Findings

My foremost objective was to explore whether the BMI values of police

officers would predict or moderate the harmful influences of job stress. I collected

the covariates of rank, seniority, shift work, gender, age, and marital status for

evaluation in my regression models. Shift work was the only covariate found to be

significantly related to officer stress in my study.

Research Questions

RQ1: Will BMI significantly contribute to the percent change of R

variance accounted for in the predictive effect of self-reported organizational

stress in the past 6 months among south Florida police officers, after controlling

for age, gender, rank, marital status, shift work, and seniority?

Officer BMI values were not found to be significant in predicting any

relationship with the organizational stress of the officer. Officer BMI values also

139

did not predict their operational stress; therefore, I retained the null hypotheses for

both research questions. As this was the first research project to attempt to

examine officer BMI values directly in comparison with police organizational and

operational stress, my literature focused on previously researched stress and BMI

outcomes.

My literature review verified agencies must address these adverse impacts

of officer stress. My literature review also identified other variables relative to

stress. Stronger confidence in the results is achieved with covariates in a study

(Frankfort-Nachmias & Nachmias, 2008). Including covariates in my study

ensured reducing spurious relationships between BMI values and officer stress

levels. A brief review of the results of these covariates is warranted here.

Age and Gender

I collected gender demographic information from subjects. Smith (2013)

measured stress among police officers and said gender might increase stress

management. Yoo and Franke (2011) said that female officers endure more job

stress than their male officer counterparts. Chen (2009) said gender plays a part in

stress coping as male and females’ process stress differently. I could not confirm

Chen’s (2009) findings in my participants. Equal gender stress indicates both

male and female officers suffer stress at equivalent levels in this policing

organization and these findings offer an argument for the impartiality of treatment

of both sexes of officers.

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In my study, I measured age at 10-year intervals. I could not confirm

previous findings relating age to officer stress as a significant predictor in my

population. Stable stress scores regardless of age mean that no matter the age of

an officer, officers consistently suffer stress during the tenure of their career. An

officer can expect his or her stress levels to remain unchanged throughout their

profession. The officer will be subjected to stress their entire life, and this

expands the constant harmful effects that stress can have over time.

Rank and Marital Status

I measured rank in several different categories from deputy through

captain. The previous findings relating rank to officer stress could not be

confirmed as a significant predictor in my sample according to my results. Similar

to seniority, this nonsignificant variable in my study indicates even with

promotion or upward assignment, participants did not report increased officer

stress. Conversely, no matter the rank of the officer, there was no indication of

rank being a significant predictor of stress. Again, the officer will be subjected to

stress their entire career, regardless of the rank they attain.

Smith (2013) said marriage was a factor in managing stress. I measured

marital status in three categories: (a) married, (b) divorced, or (c) co-habituating.

Smith (2013) studied married female police officers and found that they also

suffer significant amounts of stress in law enforcement’s male-dominated culture.

Yoo and Franke (2011) supported this finding as well, reporting that single female

141

officers endure more job stress than their male officer counterparts. I could not

confirm these previous findings relating marriage to officer stress as a significant

predictor in my sample. Being married or having a significant person in their life

did not impact stress any more than being single in my participants. Marriage

might also increase stress if the relationship is not resilient. Having a significant

person for support additionally does not reduce stress if the officer is on shift

work and cannot logically spend time with the spouse.

Shift Work

Shift work drives anxiety and stress (Gerber et al., 2013; Wirtz &

Nachreiner, 2012). I measured shift work in two categories: (a) day shift and (b)

every other type of shift. This shift work variable included being on call, which is

a status where the officer is off duty but must be available to be recalled by the

agency to work at any time. In a post hoc analysis, shift work and organizational

stress (R = .248; p = .005 < .05) emerged as the only significant predictive

relationships confirming Gerber et al. and Wirtz and Nachreiner’ findings that

shift work predicts stress. Working fluctuating hours, including being on call, can

be very stressful not only for the officer but to the officer’s family.

Not having access to the family can compound stress as the family is an

active link in the support system against stress (McCarty et al., 2007). Officers

who cannot spend time with family during the holidays, weekends, or even in the

evenings suffer the loss of a vital support system for tolerating stress. McCarty et

142

al. (2007) found some officers are inclined to communicate extensively and

befriend others to cope with occupational stress where other officers rely on

strong bonds with family.

Seniority

Wang et al. (2014) researched stress, burnout, and job seniority as

positively associated with stress and coping ability. Chen (2009) found age,

seniority, rank, and education to be positively correlated with stress levels. Chen

(2009) purported officers between 31-40 years old, with 11-20 years of police

service, and possessing a college degree comprised the central demographic

average of officers who reported the highest levels of stress. The value of

seniority was significant in other previous studies; however, in my participant

sample, it was not a significant predictor.

The interpretation of this outcome may be inferred to mean that time as a

police officer does not increase these officer’s stress levels. It also stands to

reason subsequently that seniority does not decrease or diminish the volume of

stress in officers. The value of seniority was significant in other studies; however,

in my participant population, it was not significant. As an officer reaches more

time on the job, the officer may very well adapt to the stress of that position.

When seniority dictates a promotion or reassignment, again, the officer remains

subject to the stress of being a law enforcement officer.

143

Organizational Stress and Operational Stress

McCreary et al. (2017) established normative baseline values for officers

utilizing the police stress questionnaires they developed. They found mean

normative scores for organizational stress values to be m = 3.49-3.57 and

operational stress mean scores to fall within m = 3.22-3.30. I found operational

stress (m = 2.843) had an overall higher mean score than organizational stress (m

= 2.768) in my sample. My participant’s mean organizational and operational

stress scores are not consistent with McCreary et al. (2017) normative findings in

the context of higher operational stress mean scores compared to organizational

mean scores.

The mean scores in my sample were below the normative mean scores

established for the survey instruments, and this could demonstrate a lower amount

of stress overall in my participants. My participant’s baseline mean scores also

illustrate that in my sample, officers reported higher stress scores for operational

police techniques and less stress for organizational police procedures,

mathematically. Given the close approximation of these mean stress values, I

conducted a t-test to determine the significance, if any, between mean values of

these independent, but related stress scales. No statistically significant differences

between operational stress and organizational stress were observed (p = 0.479).

144

Body Mass Index

As the principal variable of interest, my research had a specific focus on

BMI and its outcomes. The negatives attributes related to higher BMI values are

well researched and reported in the literature. Berset et al. (2011), MacDonald

(2007), and Proper et al. (2013b) found overweight people did not cope as well as

those of appropriate body weight. In the agency surveyed, there are no established

BMI standards and the overweight appearance policy is not enforced for

employees. When overweight officers are not corrected, disciplined, or terminated

due to high BMI, a logical conclusion is that high BMI may not have a

relationship with reported stress levels. Without a policy to guide BMI levels, it

would appear officers do not consider being overweight at as threat stressor.

Although my study results did not illustrate any relationship between BMI and

stress, the body of existing research presented concerning the harmful effects of

BMI remains compelling in many aspects, and further relationship analyses are

encouraged.

Theory

The stress-coping theory detailed in Chapter 2 is applied in this study and

is the most suitable to understand the processing and appraisal of psychological

stressors based on stress management abilities, which vary from person to person.

Human factors such as self-confidence, commitment, social structure, and

perceived control of the stressor play a part in assessing the stressor event.

145

Situational factors influencing coping are the events, resources, and limitations.

When examined together, these variables offer some clarity in the differences

between individuals and their ability to cope with stress (Lazarus & Folkman,

1984; Shirley, 2013).

Stress appraisal and response mechanisms typically involve reviewing the

problem, devising solutions, choosing a solution, and acting (Chan & Ward, 1993;

Kakar, 2013; Shirley, 2013). This complete appraisal cycle is termed “coping”

and varies by personality and personal resources and continues until the stressor is

resolved, with anxiety difficulties arising if the stressor cannot be resolved.

Coping is the evaluation process between the event and reaction to it (Lazarus &

Folkman, 1984).

Applying coping theory to my study, there is an assumption that an

overweight condition was an unresolved stressor; however, this did not accurately

account for the coping abilities of different officers. My study did not support this

application of the stress-coping theory. From the conclusions of my analysis, BMI

does not predict officer stress. Perhaps the officers in the study population do not

have stress about their body weight. When no weight standards are set or enforced

and without policy standards, high BMI values would not place their employment

in jeopardy.

Only when a stressor is identified as a negative or a threat, does it cause

stress (Lazarus & Folkman, 1984). If the stressor is irrelevant or positive, it

146

requires no further re-assessment; it is disregarded as a threat. An example of an

irrelevant stressor is one in which the actor has no vested interested in the

outcome, and ultimately the results will not affect them (Lazarus & Folkman,

1984). Also, reasoning higher BMI values not being related to officer stress could

be in the timing of the surveys. Conducting the study in January could have

played a part in the officer coping processes as will be further discussed.

Max Weber’s ideal type theory encourages policy formation based on

what is ideal for a specific culture (Wagner & Harpfer, 2014). Ideal type theory

refers to how systems of government implement policies which shape

professional reality. Ideal types lead researchers to draw valid comparisons

between the results of studies published within a single disciplinary field (Weber,

2009). Applying ideal type theory to the performance of law enforcement, a

significant inference to draw is that organizational policy development should

focus more closely on physical and mental health.

Policy recommendations from my study in light of an ideal policy state are

many. Shift work impacted officer stress and in an ideal state, policy should be

initiated in this arena. An ideal type policy to lessen the stress of shift work

possibly is a pay increase shift differential. Those employees on shift work would

have an increased salary to offset and tolerate the additional stress. Numerous

police agencies do have a shift pay differential. My participant’s agency does not

have a pay differential for shift work, and the implementation of the same may

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help mitigate stress scores related to this shift work. Not every agency has the

budget to logistically pay a differential though it is an ideal policy change to assist

officers. Secondarily, officers can be rotated off shift work, so every officer

shares the shift workload. Lastly, only volunteers could be scheduled on shift

work as some employees do volunteer for that schedule, however, a mechanism

would be needed to ensure shifts are safely and adequately staffed when

insufficient volunteers are recruited, especially during holidays.

Limitations of Study

Many of the limitations of my study were inherent of the quantitative

design contingent of survey data. The first limitation surrounds the testing of

officers from a single agency. With roughly 765,000 full-time officers nationwide

(Reaves, 2016), testing officers from a single agency limit generalizability.

Although utilizing officers from one agency does provide insight to stress

dynamics related to the covariates and BMI in that specific agency, it does not

adequately represent officers across the region or nation. My sample (n = 128) did

exceed the computed G*Power minimum sample size and increasing the sample

size and diversity of police forces in future research could strengthen a future

study’s power, thus broaden generalizability.

A second limitation of my study was in timing bias; the testing occurred in

the first week of January. Traditionally the beginning of a new year is a time for

making “New Year’s resolutions” about life habits which people hope to change.

Assignement introduction Advocating Ideal Type Policy for Police Officer Wellness

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