The Health Belief Model and smoking cessation behaviours

Received: 4 December 2017 Revised: 10 April 2018 Accepted: 14 May 2018

DOI: 10.1002/pon.4774

P A P E R

Associations between the smoking‐relatedness of a cancer type, cessation attitudes and beliefs, and future abstinence among recent quitters

Úrsula Martínez1 | Thomas H. Brandon1,2,3 | Steven K. Sutton2,3,4 | Vani N. Simmons1,2,3

1 Department of Health Outcomes and

Behavior, H. Lee Moffitt Cancer Center,

Tampa, FL, USA

2 Department of Oncologic Sciences,

University of South Florida, Tampa, FL, USA

3 Department of Psychology, University of

South Florida, Tampa, FL, USA

4 Department of Biostatistics and

Bioinformatics, H. Lee Moffitt Cancer Center,

Tampa, FL, USA

Correspondence

Úrsula Martínez, Tobacco Research and

Intervention Program, Moffitt Cancer Center,

4115 E Fowler Avenue, Tampa, FL 33617,

USA.

Email: [email protected]

Funding information

National Cancer Institute, Grant/Award Num-

ber: R01 CA154596; Biostatistics Core Facility

at the H. Lee Moffitt Cancer Center and

Research Institute, a National Cancer

Institute‐designated Comprehensive Cancer Center, Grant/Award Number: P30CA76292

2104 Copyright © 2018 John Wiley & Sons, L

Abstract

Objective: Smoking after a diagnosis of cancer can negatively impact treatment

outcomes and quality of life. It is important that patients quit smoking and remain

abstinent regardless of cancer type. Some cancer types (eg, lung) have stronger links

to smoking as a cause than do others (eg, colorectal). The aims of this study were

to (1) assess associations between smoking‐relatedness of the cancer type with

beliefs and attitudes concerning smoking abstinence (eg, confidence, self‐efficacy),

and (2) assess these variables as predictors of future abstinence.

Methods: In this secondary analysis, cancer patients (N = 357) who quit smoking

within the previous 90 days were assigned a code of 3, 2, or 1 according to the cancer

type's level of smoking‐relatedness: Very related (n = 134, thoracic and head and

neck), Somewhat related (n = 93, acute myeloid leukemia, bladder, cervix, colorectal,

esophageal, kidney, liver, pancreas, and stomach), and Unlikely related (n = 137, all

other cancer types).

Results: Smoking‐relatedness was positively associated with plan to stay smoke‐free,

maximum confidence in being smoke‐free in 6 months, higher abstinence self‐efficacy,

and lower expected difficulty in staying smoke‐free. Each of the 4 beliefs and attitude

variables predicted abstinence 2 months later. Smoking‐relatedness also predicted

abstinence in a univariate model, but not in a multivariable model with the belief and

attitude variables. Using backwards stepwise procedures, the final model included plan

to stay smoke‐free, confidence in being smoke‐free, and abstinence self‐efficacy.

Conclusion: These results are consistent with our conceptualization of cessation

motivation differing by smoking‐relatedness of the cancer type and predicting future

abstinence.

KEYWORDS

attitudes, beliefs, cancer, cessation motivation, oncology, smoking, smoking relapse

1 | BACKGROUND

It is estimated that cigarette smoking causes nearly 480 000 deaths

annually in the US.1 One of the major health consequences is cancer,

with smoking estimated to contribute causally to 30% of all cancers

deaths.2 In the most recent Surgeon General's report, smoking was

td. wileyonlinelib

associated with 12 different types of cancer including lung, head and

neck (HN), acute myeloid leukemia, bladder, cervix, colon, rectum,

esophagus, kidneys, larynx, liver, pancreas, and stomach.1 Although a

high percentage of lung cancer patients attribute their cancer to

smoking, people with cancers that are also smoking‐related (eg, colorec-

tal) are less likely to identify smoking as a primary cause of their cancer.3

Psycho‐Oncology. 2018;27:2104–2110.rary.com/journal/pon

MARTÍNEZ ET AL. 2105

Once an individual has been diagnosed with cancer, continued

smoking contributes to several adverse health consequences, regard-

less of the type of cancer. For example, smoking has been associated

with a reduction in cancer treatment efficacy, greater treatment com-

plications, higher risk of developing second primary tumors, higher

cancer recurrence rates, and increased risk of overall mortality.1,4

Despite myriad potential negative consequences, over one‐third of

patients with cancer continue to smoke after diagnosis.5 Some of the

barriers are a typically high nicotine dependence, significant stress,

and lack of knowledge of the numerous benefits of smoking cessa-

tion.6,7 Even among patients who do initially quit smoking upon receiv-

ing a cancer diagnosis, smoking relapse rates are high (up to 60%).8,9

Thus, it is important to identify variables that predict tobacco absti-

nence in cancer patients, and that may suggest targets for intervention.

Studies have found higher smoking cessation rates among

patients with cancers widely known to be smoking related compared

with those with cancers for which the smoking‐attributable risk is

unclear or less widely known to the public. For example, one review

found that smoking cessation rates varied from 46% to 96% in

smokers with lung and HN cancers, compared with 4% among

smokers with breast cancer.10 Other studies have found that lung

cancer patients are more likely than other cancer patients to quit

smoking within 5 to 6 months of diagnosis.11,12

Higher quit rates among patients with cancers widely known to be

smoking related have also been observed within the context of

smoking cessation interventions.13,14 Authors have suggested that dif-

ferences in cessation rates are a consequence of differential smoking

cessation motivation across cancer types. That is, because the public

health message that smoking causes lung cancer has been widely dis-

seminated, lung cancer patients as well as the general public associate

their cancer with smoking.15 This greater awareness may contribute to

the greater motivation to quit smoking and maintain smoking absti-

nence that is evident among lung cancer patients. Patients diagnosed

with other cancers may be less likely to change their smoking behavior

due to the lack of association with their cancer diagnosis.6 However,

the association between cancer smoking‐relatedness and smoking

cessation motivation has not been tested.

Prior studies have identified a link between cognitive motivational

variables and smoking behavior among patients with cancer types

widely known to be smoking related. For example, a series of studies

identified cessation self‐efficacy, pros and cons of quitting, risk per-

ception, and emotional distress as associated with smoking abstinence

in patients recently diagnosed with lung or HN cancer.16-18 Addition-

ally, high levels of public self‐consciousness about smoking predicted

smoking abstinence in 40 HN patients,19 and the interaction between

behavioral self‐blame and perceived control over their cancer were

significant predictors of smoking behavior in another sample of 55

HN patients.20 Overall, these studies suggest that there is an associa-

tion between cessation‐related attitudes and beliefs and smoking

behavior among cancer patients. However, these studies were

primarily focused on patients with lung or HN cancers and are limited

by their small sample sizes.

To identify possible, and potentially distinct, intervention targets

to improve smoking cessation outcomes among cancer patients with

a variety of cancer types, in the current study, we analyzed data from

a randomized controlled trial assessing a smoking relapse‐prevention

intervention.21 The primary aim of the present study was to examine

the associations between the smoking‐relatedness of a cancer type

and cessation‐related beliefs and attitudes among a diverse sample

of cancer patients who had recently quit smoking. Cancer types were

classified into 3 groups based on public's knowledge3 and cancer's

empirical link with smoking1,22: very related, somewhat related, and

unlikely related. We examined cessation‐related attitudes and beliefs

based on previous research demonstrating a relationship with future

smoking status: plan to stay smoke‐free,23 confidence in not smoking,9

commitment to abstinence,8 abstinence self‐efficacy,16,24 and

perceived risk associated with smoking after cancer diagnosis.8,16,25

We hypothesized that higher levels of smoking‐relatedness would be

associated with stronger cessation‐related beliefs and attitudes

(eg, greater self‐efficacy, plans to stay abstinent, perceived risk).

A second aim was to assess smoking‐relatedness and the

cessation‐related beliefs and attitudes variables as predictors of

smoking status 2 months later. We hypothesized that the degree of

smoking‐relatedness of the cancer type and the cessation‐related

attitudes and beliefs would predict smoking status at 2 months.

Finally, we used multivariable analyses to assess the relative contribu-

tion of individually significant predictors.

2 | METHODS

The present study is a secondary analysis using data collected for a ran-

domized controlled trial testing the efficacy of a targeted, multimodal,

empirically‐based smoking relapse prevention intervention for cancer

patients (412 enrolled). Participants in the control group received

standard of care, and those in the intervention group standard of care

+8 relapse‐prevention booklets and an educational DVD.21 The

relapse‐prevention booklets were mailed over the course of 3 months

and included information relevant for the general population of smokers

(eg, coping with urges). The DVD included smoking relapse prevention

information targeted for cancer patients (eg, cancer‐related benefits

of quitting smoking). The DVD was viewed by participants at enroll-

ment, and they were provided a copy. Follow‐up assessments occurred

2, 6, and 12 months after baseline.

This study assessed self‐report measures acquired at baseline for

the subset of participants who completed the 2‐month follow‐up

(n = 357) from which 7‐day point prevalence abstinence was derived.

2.1 | Study participants

Participants were recently diagnosed cancer patients who reported

quitting smoking within the previous 90 days. All participants were

receiving the first round of cancer treatment at a large NCI‐designated

Comprehensive Cancer Center. Inclusion criteria were as follows:

age ≥ 18 years, smoked ≥10 cigarettes per day for ≥1 year prior to

diagnosis, able to read/write English, able to give informed consent,

quit smoking after diagnosis, and abstinent ≥24 hours, but ≤3 months.

Based on the public's knowledge3 and cancer's empirical link with

smoking,1,22 participants' cancer types were classified as follows: very

related (Very, n = 133; thoracic [n = 65] and HN [n = 67]), somewhat

2106 MARTÍNEZ ET AL.

related (Somewhat, n = 93; acute myeloid leukemia [n = 14], bladder

[n = 16], cervical [n = 5], colorectal [n = 13], esophageal [n = 13], kidney

[n = 15], liver [n = 4], pancreatic [n = 11], and gastric [n = 2]), and unlikely

related (Unlikely, n = 131; all other cancer types, eg, breast [n = 46],

endometrial [n = 12], melanoma [n = 10]). Groups were, respectively,

coded 3, 2, and 1 to reflect the level of smoking‐relatedness.

2.2 | Procedure

Study procedures have been described in detail elsewhere.21 An

electronic capture and trigger system was used to identify potential

participants using the electronic medical record. Patients meeting

inclusion criteria and wishing to participate completed informed con-

sent and the baseline assessment. Participants were compensated

$25 at baseline and $25 for each follow‐up. The protocol was

approved by the Chesapeake Institutional Review Board.

2.3 | Measures

2.3.1 | Demographic, smoking history, and clinical variables

Standard survey items assessed demographic information and smoking

history. Cancer stage, treatment, and comorbidity data were extracted

from medical records. Participants also completed the FagerströmTest

forNicotineDependence,26astandardmeasureofnicotinedependence,

reworded to reflect their pre‐quitting level of nicotine dependence.27

2.3.2 | Plan to stay smoke‐free

Participants were asked about their plans to stay abstinent following

their cancer treatment: “plan to stay smoke‐free,” “planning to quit

for good, but may slip,” “plan to resume smoking less than before,”

and “plan to resume smoking as much as before.” Based on the distri-

bution, the 4 responses options were dichotomized into “plan to stay

smoke‐free” versus other.

2.3.3 | Confidence in not smoking

Participants were asked “How confident are you that you will not

smoke in the next 6 months?” Based on response distribution, the

7‐point Likert scale was dichotomized into “extremely confident”

versus all other lower levels of confidence.

2.3.4 | Commitment to abstinence

The items “I have a desire to quit smoking,” “I will successfully quit

smoking,” and “Staying smoke‐free will be difficult” were used to

assess commitment to abstinence.28 Responses ranged from 1

(strongly disagree) to 9 (strongly agree). Based on the pattern of

responding, desire to quit and expected success in quitting were

dichotomized into “maximum desire to quit” and “maximum expected

success in quitting” (score of 9) versus all other lower levels.

2.3.5 | Abstinence self‐efficacy

Total score on the situation‐specific abstinence self‐efficacy scale29

was used to assess confidence in not smoking. It is composed of 20

items ranging from 0 (not at all confident) to 5 (extremely confident).

Cronbach's alpha was .93.

2.3.6 | Perceived risks associated with smoking after cancer diagnosis

A modified version of a 5‐item risk perception tool was used to assess

the perceived risks of resuming smoking after a cancer diagnosis.16

Two items were added to include beliefs about how resuming smoking

would influence cancer outcomes.30 Response options ranged from 1

(strongly disagree) to 4 (strongly agree), and total scores were used for

the analyses. Cronbach's alpha was .90.

2.3.7 | Smoking status

Seven‐day point‐prevalence abstinence was assessed at baseline and

the 2‐month follow‐up using self‐report.

2.4 | Statistical analyses

Descriptive statistics summarized demographic, smoking history, and

clinical characteristics. Differences by smoking‐relatedness were ana-

lyzed using chi‐square and analysis of variance. Demographic and

smoking history variables that differed by smoking‐related cancer

group were included as covariates in primary analyses with a belief

or attitude as the outcome variable.

The relationship between smoking‐relatedness and each attitude

and belief variable was examined using linear or logistic regression.

The linear effect of smoking‐relatedness was evaluated in a model

controlling for demographic and/or smoking‐related variables that

differed by level of smoking‐relatedness.

Prospective predictors of smoking status at the 2‐month assess-

ment were first evaluated individually using logistic regression.

Candidates were level of smoking‐relatedness and each attitude or

belief variable that was significantly associated with level of

smoking‐relatedness. Study intervention condition was included in

these models. Significant univariate predictors were then entered into

a multivariable model, and backward stepwise procedures were used

to identify the variables making a unique contribution.

3 | RESULTS

3.1 | Sample characteristics

Of the 596 participants assessed for eligibility, 431 met inclusion

criteria and 414 completed the baseline assessment and were included

in the parent study. Data were obtained from 357 (86%) participants

at the 2‐month assessment and, therefore, used in the current analy-

sis. Participant characteristics are reported in Table 1. The Very and

Somewhat groups had a higher proportion of men and were, on aver-

age, older as compared with the Unlikely group. Participants within

the Unlikely smoking‐related group were more likely to be employed

and to self‐report a difficult or very difficult financial situation.

For smoking variables, the Very and Somewhat groups had

smoked longer than those in the Unlikely group. In addition, the Very

group had a higher smoking rate (cigarettes per day) and nicotine

dependence (Fagerström Test for Nicotine Dependence) than the

Unlikely group.

TABLE 1 Demographic, smoking, and clinical characteristics by level of smoking‐relatedness

Demographic Variables All (N = 357) Very (n = 133) Somewhat (n = 93) Unlikely (n = 131) χ2/F

Sex: Male 49.0% 57.9% 62.4% 30.5% 28.73*** a,c

Age: M (SD) 54.9 (10.7) 58.5 (9.3) 56.4 (10.0) 50.3 (10.9) 22.80*** a,c

Race: Non‐Hispanic white 86.6% 91.0% 84.9% 83.2% 3.70

Marital status: Married or has a life partner 54.9% 56.4% 57.0% 51.9% 0.76

Education: Beyond high school diploma 54.0% 48.5% 55.1% 59.1% 2.96

Employed: Yes 58.4% 50.8% 55.6% 68.0% 8.18* a

Self‐rated financial situation: Difficult or very difficult 28.0% 20.6% 33.0% 32.0% 5.69o a,b

Self‐reported annual income: ≤ $30 K 42.7% 42.1% 38.4% 46.3% 1.34

Smoking variables

Years smoking—M (SD) 34.7 (12.0) 39.3 (10.6) 36.0 (11.5) 29.0 (11.4) 28.84*** a,c

CPD average—M (SD) 20.8 (9.7) 23.4 (11.0) 20.5 (8.6) 18.4 (8.6) 8.74*** a

Fagerström dependence—M (SD) 5.2 (2.2) 5.7 (2.2) 5.1 (2.0) 4.7 (2.1) 7.89*** a

7‐day point prevalence abstinence at baseline 70.9% 70.4% 64.1% 76.1% 3.79

Clinical variables

Early stage cancer 58.7% 50.0% 62.8% 66.7% 7.28* a

One or more comorbidities 36.4% 51.1% 35.5% 21.1% 24.00*** a,b,c

Chemotherapy 21.0% 10.5% 28.0% 26.7% 14.08*** a,b

Radiation therapy 10.6% 13.5% 14.0% 5.3% 6.12* a,c

Surgery 65.8% 72.2% 62.4% 61.8% 3.81

Notes: M = mean; SD = standard deviation; CPD = cigarettes per day. o P < .10, *P < .05, **P < .01, ***P < .001 for omnibus comparison. aSignificant difference with P < .05 between Very and Unlikely. bSignificant difference with P < .05 between Very and Somewhat. cSignificant difference with P < .05 between Somewhat and Unlikely.

MARTÍNEZ ET AL. 2107

For clinical variables, participants in the Somewhat and Unlikely

groups were more likely to have a cancer in the early stage and to

have received chemotherapy. Participants in the Very group had

significantly more comorbidities.

3.2 | Beliefs and attitudes variables

Descriptive statistics of cessation belief and attitude variables are pre-

sented in Table 2, as well as results of logistic and linear regression

analyses, controlling for the demographic and smoking history vari-

ables that differed across levels of smoking‐relatedness (see Table 1).

Analyses revealed that smoking‐relatedness was positively associated

TABLE 2 Association of attitude and belief variables with smoking‐relate

Variable %

Plan to stay smoke‐free for good 67.1

Maximum confidence will not be smoking in 6 months 55.4

Maximum desire to quit smoking 78.0

Maximum expected success in quitting 72.3

M (SD)

Expected difficulty in staying smoke‐free (range 1‐9) 6.1 (3.1

Abstinence self‐efficacy (range 9‐45) 38.5 (7.4

Perceived risks associated with smoking (range 7‐28) 22.7 (4.3

Abbreviations: AOR, adjusted odd ratio; CI, confidence interval; M, mean; SD,

Prediction of attitude/belief variable by smoking‐relatedness 1–3, or was asses smoking variables that were associated with level of smoking‐relatedness (see

N's range from 353 to 357 due to missing observations for 4 predictors.

with (1) current plan to stay smoke‐free, (2) maximum confidence in

being smoke‐free in 6 months, and (3) cessation self‐efficacy; and neg-

atively associated with anticipated difficulty in staying smoke‐free. No

significant associations were found for desire to quit smoking,

expected success in quitting, and perceived risks associated with

smoking after cancer.

3.3 | Prediction of smoking status at 2 months

At the 2‐month follow‐up, 266 (74.5%) patients reported 7‐day point‐

prevalence abstinence, with no significant differences between

groups. Table 3 summarizes level of smoking‐relatedness and the four

dness

AOR [95% CI] χ2 P

1.38 [1.01, 1.89] 4.11 .043

1.67 [1.23, 2.27] 11.00 <.001

1.17 [0.84, 1.71] 0.99 .320

1.16 [0.84, 1.62] 0.81 .370

b (SE) t P

) −0.62 (0.22) −2.83 .005

) 1.23 (0.53) 2.30 .022

) 0.06 (0.31) 0.18 .854

standard deviation; SE, standard error.

sed using logistic or linear regression controlling for 4 demographic and 3 Table 1).

TABLE 3 Prediction of 7‐day point prevalence abstinence at 2 months

Predictor

Univariate Models Multivariable Model Final Model

AOR (95% CI) P AOR (95% CI) P AOR (95% CI) P

Level of smoking‐relatedness 1.34 (1.01‐1.77) .041 1.20 (0.87‐1.64) .274 ‐‐ ‐‐

Plan to stay smoke‐free for good 5.08 (3.05‐8.47) <.001 2.28 (1.23‐4.23) .009 2.42 (1.30‐4.49) .005

Maximum confidence will not be smoking in 6 months 4.92 (2.88‐8.39) <.001 1.81 (0.88‐3.72) .106 2.10 (1.04‐4.27) .039

Expected difficulty in staying smoke‐free 0.85 (0.78‐0.93) <.001 0.92 (0.84‐1.02) .118 ‐‐ ‐‐

Abstinence self‐efficacy 1.09 (1.06‐1.13) <.001 1.04 (1.00‐1.09) .051 1.04 (1.00‐1.09) .042

Abbreviations: AOR, adjusted odd ratio; CI, confidence interval.

All analyses included intervention condition as a covariate (all p's > .13).

2108 MARTÍNEZ ET AL.

attitude/belief variables as predictors of abstinence at the 2‐month

assessment using logistic regression. Individual analyses showed that

significant predictors of abstinence were smoking‐relatedness, current

plan to stay smoke‐free, maximum confidence in not smoking in

6 months, higher abstinence self‐efficacy, and lower expected

difficulty in staying smoke‐free. A multivariable model showed that

current plan to stay smoke‐free remained a significant predictor and

higher abstinence self‐efficacy was a marginally significant predictor.

Backward stepwise procedures resulted in a final model with current

plan to stay smoke‐free, maximum confidence in not smoking in

6 months, and abstinence self‐efficacy as significant predictors of

smoking abstinence. Thus, with these belief and attitude variables in

the model, level of smoking‐relatedness was not a significant predictor

of abstinence at 2 months.

4 | DISCUSSION

Although immediate smoking cessation is warranted, many cancer

patients continue to smoke and those who do quit often relapse.8,9

Previous studies have found higher cessation rates in patients with a

smoking‐related cancer, suggesting that there may be a difference in

cessation motivation across cancer types.13,14 In this study, we

advanced prior research by examining whether the smoking‐related-

ness of a patient's cancer type was associated with cessation‐related

beliefs and attitudes. Our results supported the hypothesized associa-

tion between the degree of cancer smoking‐relatedness and these

motivational variables. Specifically, level of smoking‐relatedness of

the cancer type was positively associated with plans to stay smoke‐

free, maximum confidence in not smoking in 6 months, and abstinence

self‐efficacy; and it was inversely associated with anticipated difficulty

staying smoke‐free. These variables, with the exception of the last,

were significant predictors of smoking status at the 2 months

follow‐up.

Smoking‐relatedness was positively associated with smoking

abstinence at 2 months. That is, the stronger the association between

an individual's cancer type and smoking, the more likely they were to

be smoke‐free. However, this variable was not a significant predictor

when entered in the multivariable model along with beliefs and atti-

tudes variables. These findings highlight the importance of cessation

motivation variables in smoking cessation treatments with the onco-

logic patient population. Patients with a cancer widely known to be

smoking‐related may make a connection between their cancer and

smoking and, as a result, increase their intentions and confidence to

be smoke‐free. This is supported by prior research that demonstrates

that although a high percentage of lung cancer patients attribute their

cancer to smoking, people with other cancers that are also smoking‐

related (eg, colorectal) are less likely to identify smoking as a primary

cause of their cancer.3 Consequently, they appear less likely to quit

smoking13 or seek smoking cessation treatments.31 However, the rela-

tionship between smoking‐relatedness and abstinence is complex and

could be influenced by other factors. For example, patients with lung

cancer experience stigma and blame32,33 that can increase their stress

levels leading to continued smoking.6 Thus, future studies should

explore the role of variables such as perceived stigma, blame, or shame

as potential predictors of smoking status in cancer patients.

Overall, findings of the present study suggest that patients with

cancers not widely known to be smoking related may need greater

education regarding the relationship of their cancer to smoking, as

well as the cancer treatment and prognosis implications of continue

smoking.

4.1 | Study limitations

First, participants had quit smoking and were enrolled in a smoking

relapse prevention intervention trial. They likely have specific charac-

teristics that limit generalizability to the population of smokers with

cancer. Furthermore, they likely had higher smoking cessation motiva-

tion than cancer patients who continued to smoke. Thus, even stron-

ger associations with smoking‐relatedness and smoking cessation

might have been found with a less restricted sample of cancer patients

who smoke. Second, participants were grouped based on cancers'

empirical links with smoking as well as the public's knowledge of the

links. To date, smoking has been associated with 12 different types

of cancer. However, this list may increase in the future because there

are cancer types for which the evidence is building yet is not sufficient

to infer a causal relationship (eg, breast cancer). In addition, the litera-

ture on the public knowledge or beliefs regarding the link between

smoking and cancer is limited; thus, these categorizations are likely

fluid and pose a challenge for how to best categorize the smoking‐

relatedness of cancer types. Third, those variables that were not

unimodal and symmetric (eg, confidence in not smoking) were dichot-

omized to minimize the effect of the lack of normality. Fourth, the

majority of study participants were Caucasian, which limits generaliz-

ability of the results. However, previous studies have not found signif-

icant differences in smoking status among cancer patients with

MARTÍNEZ ET AL. 2109

different races/ethnicities.9,34 Finally, to reduce burden to this

vulnerable population, smoking abstinence was self‐reported, and no

biochemical validation was conducted at the 2‐month follow‐up. Prior

studies have had mixed findings regarding concordance between

self‐report and biochemically verified abstinence among cancer

patients. Some studies found high concordance of 85% to 91%

between self‐reported tobacco abstinence and biochemical validation

in cancer patients,35-37 whereas others have indicated self‐report to

be unreliable.38,39 It is thus possible that some participants in our sam-

ple were misclassified, and future studies should include biochemical

verification of self‐reported smoking abstinence.

Our study has several strengths. Although prior studies have

found that patients with highly smoking‐related cancers tend to be

the most likely to quit, our inclusion of patients with multiple cancer

types along with categorization of cancer type by level of smoking‐

relatedness extends prior findings. There has been a call for research

on differences among patients with diverse cancer types to further

understand the observed differences in smoking rates.13,14 The

observed associations between cancer type and cessation attitudes

and beliefs, as well as the relationship between these beliefs and

future abstinence, fill a gap in the literature and suggest important

targets for intervention.

4.2 | Clinical implications

The results of the present study indicate that beliefs and attitudes

concerning smoking abstinence differ across types of cancer. Because

continued smoking after a diagnosis of cancer has adverse effects

regardless of cancer type,1,4,40 there is a need to enhance cessation

motivation and to educate patients about the risks associated with

continued smoking. This is particularly so for patients diagnosed with

a cancer type not usually perceived as smoking‐related. These findings

point to the particular need to develop and test interventions to

motivate smoking cessation among patients with a cancer type not

strongly associated with smoking.

FUNDING SOURCE

This research was supported by grant R01 CA154596 from the

National Cancer Institute and in part by the Biostatistics Core Facility

at the H. Lee Moffitt Cancer Center and Research Institute, a

National Cancer Institute‐designated Comprehensive Cancer Center

(P30CA76292). The content is solely the responsibility of the authors

and does not necessarily represent the official views of NIH.

CONFLICT OF INTEREST

Dr Thomas Brandon has received research support from Pfizer, Inc.

ORCID

Úrsula Martínez http://orcid.org/0000-0002-4212-5851

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How to cite this article: Martínez Ú, Brandon TH, Sutton SK,

Simmons VN. Associations between the smoking‐relatedness

of a cancer type, cessation attitudes and beliefs, and

future abstinence among recent quitters. Psycho‐Oncology.

2018;27:2104–2110. https://doi.org/10.1002/pon.4774