Nursing writing assignment

A Brief Value-based Randomized Intervention to Promote Physical Activity in Patients Attending Cardiac Rehabilitation Emily Van Wasshenovaa, Debra Boardleyb, Andrew Geersb, Matthew Tullb, and Victoria Steinerb

aOakland University; bUniversity of Toledo

ABSTRACT Background: Affective associations have been shown to predict physical activity, but interventions designed to manipulate affective associations are limited. Purpose: To increase physical activity through manipulation of affective associations toward physical activity using the values component from Acceptance and Commitment Therapy (ACT) in cardiac rehabilitation patients. Methods: Cardiac rehabilitation patients (N = 58) from two cardiac rehabilitation sites were randomly assigned to an intervention group or control group receiving standard Health Education. Three weeks after participants ended cardiac rehabilitation, follow-up data were collected. Results: Positive affective associations were not a significant predictor of physical activity inten- tions and showed no evidence of mediation of physical activity intention and physical activity. Intentions were not a significant mediator between the intervention and physical activity. Discussion: The results indicate that the intervention did not change positive affective associations or increase physical activity behavior. Future research should consider including additional aspects of ACT in the intervention with a longer intervention period. Translation to Health Education Practice: ACT is a low-cost way to promote physical activity shown to be effective in other populations. This study informs future research to design an effective framework for ACT implementation in cardiac rehabilitation centers.

ARTICLE HISTORY Received 21 March 2022 Accepted 29 August 2022

Background

Each year, approximately 790,000 adults have a heart attack with 26% being recurrent heart attacks.1 Patients recovering from heart attack and some other heart con- ditions are often referred to outpatient cardiac rehabili- tation. Cardiac rehabilitation is a medically supervised treatment that aims to reduce heart disease risk factors and help patients adopt a healthy lifestyle through exer- cise training and education and tools for adopting a heart-healthy lifestyle.2

Cardiac rehabilitation has many benefits for patients who participate in the program. A recent systematic review and meta-analysis showed that cardiac rehabili- tation, when compared with usual care, reduced the incidence of premature death from all causes, especially cardiovascular disease.3 Patients participating in cardiac rehabilitation programs who continue being physically active after cardiac rehabilitation maintain gains in car- diovascular health acquired during rehabilitation.4

Although the literature reports benefit of cardiac reha- bilitation, post-rehabilitation physical activity compli- ance is often poor. Estimates of attrition rates are 25%

in the first 3 months to 50% in the first 6 months.5 Given the large number of adults with heart disease developing effective behavioral interventions that could be used in cardiac rehabilitation programs to maintain physical activity after cardiac rehabilitation, physical activity would improve patient health and reduce mortality.

Previous research aimed at promoting physical activ- ity frequently used cognitively based techniques, such as educating about physical activity benefits and how to reduce barriers to physical activity.6 These approaches are often grounded in theories such as theory of planned behavior,7 social cognitive theory,8 and the transtheore- tical model of behavior change.9 Meta-analyses of phy- sical activity interventions using these techniques demonstrate a small but meaningful change10 and there- fore present opportunities for additional techniques to promote physical activity behavior.

A growing body of research has explored the contri- bution of affective components to physical activity intentions and behavior.10 Variables with affective com- ponents have been shown to explain variation in physi- cal activity intention or predict physical activity

CONTACT Emily Van Wasshenova [email protected] Department of Interdisciplinary Health Sciences, Oakland University, 433 Meadow Brook Road, Rochester, MI 48309, USA

AMERICAN JOURNAL OF HEALTH EDUCATION 2023, VOL. 54, NO. 1, 10–19 https://doi.org/10.1080/19325037.2022.2142334

© 2022 SHAPE America

behavior better than cognitive components.11–13

Affective determinants of health behavior are categor- ized into four categories based on their association to the health behavior.14 Within this framework, affective asso- ciations are automatic associations between the target behavior and previously experienced responses to the behavior.11 An affective association can be positive or negative. For example, a sedentary individual may auto- matically associate the idea of being physically active with a feeling of disgust. Alternatively, a regularly phy- sically active person could associate the idea of being physically active with a feeling of pride. Affective asso- ciations have shown significant positive association with physical activity behavior, even when demographic vari- ables and/or cognitive variables are controlled.11,15

One potential way to increase positive affective asso- ciations is through Acceptance and Commitment Therapy (ACT).16 ACT uses both behavioral and cogni- tive therapy to increase psychological flexibility, which is the ability to be present in each moment and to align behavior with personal values. ACT has six core pro- cesses, which lead to psychological flexibility: accep- tance, cognitive defusion, being present, self as context, committed action, and values. Acceptance is allowing unpleasant experiences to exist, while cognitive defusion refers to changing reactions to thoughts and feelings. Being present is the practice of being in the present moment. Self as context is the awareness that an indivi- dual’s self is unchanged by their surroundings. Values and committed action can be used to help individuals identify core values then to commitment to engage in behaviors consistent with personal values. Theoretically, by aligning physical activity with an individual’s perso- nal values, such as independence, individuals may increase their positive affective associations toward phy- sical activity and maintain physical activity behavior.

There is evidence that ACT is a promising approach to promote health behavior change.17 For example, using components of ACT (value clarification, acting according to own values, mindfulness skills, the obser- ving self and acceptance skills) delivered in group ses- sions or by mobile app has had beneficial effects on reported eating behavior among adults with psychologi- cal distress and overweight or obesity.18 Similarly, Levin et al. found an online, self-guided ACT intervention improved healthy eating behavior in adults who were overweight or obese.19

ACT may be also useful in physical activity promo- tion. A systematic review of ACT physical activity inter- ventions found that an increase in physical activity in the 21 studies analyzed with statistically significant changes reported in 15 of the studies.20 Increases in physical activity after ACT interventions have been observed at

1 month21, 3 months22–24, 6 months,25–28 and a year.29

Of the studies reviewed, one study was conducted with patients in cardiac rehabilitation. The pilot study deliv- ered 4 sessions of an ACT intervention, including the components of mindfulness, distress tolerance, and committed action and values (n = 16) with moderate increases in physical activity (d = 0.54).30 It is of note that the study did not include a control group. Although ACT-based interventions have proven effective in increasing physical activity, there are several limitations of this research including small sample sizes and sam- ples that are predominately or completely female.20

ACT has been used with success in physical activity interventions,20 but the theoretical framework within which ACT influences physical activity is relatively unknown. There is evidence to suggest affective associa- tions may mediate the relationship between ACT and physical activity. Theoretically, by aligning physical activity with an individual’s personal values through psychological flexibility, positive affective associations toward physical activity may increase and therefore lead to increased physical activity behaviors. Therefore, an evidence base for the effectiveness of an ACT physical activity intervention and mechanisms is needed, espe- cially in populations in which physical activity is espe- cially beneficial.

Purpose

The aim of the present study was to determine if positive affective associations toward physical activity can be manipulated using the values component from ACT. Additional aims included determining if increasing positive affective associations impacted intention to be physically active and physical activity behavior and to explore how the value-based intervention impacted phy- sical activity behavior.

Methods

Participants

Between 2017 and 2018, participants were recruited from two cardiac rehabilitation facilities in Adrian, Michigan and Sylvania, Ohio (ProMedica Bixby Hospital and ProMedica Flower Hospital) within the same health-care system. Participants were recruited through flyers and face-to-face recruitment. The inclu- sion criteria included being a participant of cardiac rehabilitation who was at least 50 years of age. Exclusion criteria included being 49 years of age or younger, enrollment in other experimental studies, refu- sal, and inability to speak English. Since the goal of the

VALUE-BASED PHYSICAL ACTIVITY INTERVENTION 11

study was to assess physical activity after participants were discharged from cardiac rehabilitation, subjects needed to be near the end of their time in cardiac rehabilitation. Therefore, subjects were also excluded if they had more than 4 weeks remaining in the cardiac rehabilitation program. Informed consent was obtained before subjects participated in the study. Subjects were offered a $10 grocery store gift card for their participa- tion in the study. Ethical approval was obtained from by ProMedica’s Institutional Review Board and the University of Toledo’s Institutional Review Board.

Study design

A randomized single blind control trial was used to compare the effectiveness of a 60-minute intervention focusing on values within ACT with a control group that received standard-of-care education in cardiac rehabilitation patients. Participants were assigned to the intervention group or control group based on the cardiac rehabilitation site. After enrollment of 30 par- ticipants from a cardiac rehabilitation site, the site switched from the control site to the intervention site and vice versa. This method was used to decrease the chances that participants could determine if they were assigned to the intervention or control group since all participants at a site during a specific time frame would be in the same group and receiving the same treatment. Therefore, participants were blinded to their group assignment. Given limited personnel resources avail- able for this study, it was not possible to blind the authors.

Procedure

The study included a baseline assessment (time 1), a 30- minute intervention or standard-of-care education ses- sion, a second assessment a week after the intervention (time 2), and a follow-up after the participant completed cardiac rehabilitation (time 3). To obtain physical activ- ity behavior data not influenced by the requirement of physical activity during cardiac rehabilitation sessions, the final data collection occurred 3 weeks after the patients’ last cardiac rehabilitation session. The follow- up survey was administered over the phone, and parti- cipants were reminded to mail their physical activity log. Participants were instructed to record any physical activity rated at a rating of perceived exertion (RPE) 10 or higher. Cardiac rehabilitation encouraged partici- pants to engage in physical activities at RPE of at least 10 and therefore an RPE of 10 was the minimum RPE for physical activities.

Control group The control group was encouraged to attend the stan- dard Health Education sessions common to cardiac rehabilitation programs. These classes, delivered by car- diac rehabilitation staff, last about 60 minutes and include topics such as healthy eating and reducing risk factors of heart disease.

Intervention group The intervention group attended a 60-minute one-on- one session. Overall, the goal of the intervention was to increase positive affective associations with physical activity. The intervention used a semi-structured guided interview based on one component of ACT, values, and a self-help workbook based on this therapy.16 The researcher led each participant through using a semi-structured guided session explaining the concept of values, asking the participant to define the top five domains of their life (e.g. family relations, parenting, career), and define values within these domains. The researcher prompted the participant to brainstorm and identify the linkages between how their values may relate to physical activity. The participant took home a visual representation of identified values and notes on how they perceive their values relate to physical activity. The participant was instructed to review their sheet prior to the next data collection point (time 2).

Measures

Positive affective associations with physical activity, physical activity intention, and physical activity behavior were primary outcomes for the study. Data were col- lected at baseline (time 1), a week after the intervention (time 2) and 3 weeks after the patients’ last cardiac rehabilitation session (time 3).

Affective association with physical activity Participants’ affective associations with physical activity were assessed using a previously validated and reliable scale.31,32 Participants were asked the question, “When you think about being physically active, how do you feel?.” This prompt was followed by five positive affective words (happy, delighted, joy, excited, and proud) and five negative affective words (disgusted, annoyed, sad, irri- tated, and bored). Participants responded to each affective word on a separate Likert-type scale, anchored from 1 (not at all), 2 (a little), 3 (unsure), 4 (somewhat), and 5 (extremely). Responses to these 10 items were averaged separately to create a positive affective association scale for time 1, time 2, and time 3 (α = .844, .857, .839) and

12 E. VAN WASSHENOVA ET AL.

negative affective association scale for time 1, time 2, and time 3 (α = .623, .723, .853) for physical activity.

Physical activity intention Physical activity intention was assessed using Bryan and Rocheleau's scale33 by three items, 1) “I intend to be physically active as much as I can in the next month,” 2) “How likely is it that you will regularly be physically active in the next month?,” and 3) “How likely is it that you will engage in physical activity at least 5 times per week in the next month?.” Responses were on a 5-point scale ranging from not at all likely (1), a little likely (2), unsure (3), somewhat likely (4), and very likely (5). A mean score was calculated and higher scores indicated greater intentions to be physically active in the next month (α = .776).

Physical activity behavior Participants completed a 7-day physical activity log reporting description of physical activity, duration in minutes, and RPE (6–20). Participants were instructed to record any physical activity rated at a rating of per- ceived exertion (RPE) 10 or higher. Previous research supports the validity and reliability of RPE for exercise intensity.34 Cardiac rehabilitation encouraged partici- pants to engage in physical activities at RPE of at least 10 and therefore an RPE of 10 was the minimum RPE for physical activities. Physical activity rated below an RPE of 10 indicates “very light or very, very light” physical activity and are described as, “how you feel when lying in bed or sitting in a chair relaxed or little or no effort” and therefore are not indicative of mean- ingful physical activity.

Demographics and clinical measures Participant demographics, clinical measures, and var- ious psychometric assessments (e.g. stage of change for exercise) were obtained through patient medical charts.

Data analysis

The primary outcome was positive affective associations with physical activity. The secondary outcomes included intention to be physically active and physical activity behavior. Statistical analyses were performed using IBM SPSS Statistics for Windows. A repeated measures Analysis of Variance (ANOVA) determined differences in positive affective associations between the interven- tion and control group across three time points. A linear regression assessed the predictive power of positive affective associations at time 1, 2, and 3 to predict intention at time 3. Paired t-tests assessed differences in physical activity intention and physical activity

behavior between the intervention and control group. A path-analysis was performed to determine the vari- ables that may mediate the effect of the intervention on physical activity behavior. Intentions and positive affec- tive associations were considered as potential mediators between the intervention and physical activity behavior. To determine whether these mediators fully mediated the relationship between the intervention and physical activity behavior, an accelerated-biased-corrected boot- strapping procedure was employed.35,36 The interven- tion was entered as the independent variable, physical activity at time 3 was the dependent variable, and phy- sical activity intentions and positive affective associa- tions at time 2 were tested as mediators in the SPPS macro created by Hayes for bootstrap analyses with multiple proposed mediators.35,36

Results

Figure 1 shows the recruitment procedure. Of the 74 participants approached to participate in the study, seven participants declined. Nine participants did not complete all three data collection points and therefore were excluded from the final results. These participants were not statistically different from participants included in the final results based on race, cardiac reha- bilitation site, gender, diagnosis, initial risk, BMI, or age (p > .05).

Participants (N = 58) were male (n = 35) and female (n = 23) patients participating in cardiac rehabilitation (M age = 67.5; SD = 8.3; range 50–86). The majority of participants identified themselves as Caucasian (86.2%), with 6.9% identifying as African American and 6.9% as other (Table 1). There were no baseline differences between the control group and the intervention group on key factors related to physical activity (i.e., ejection fraction, BMI, age, race, stage of change for exercise) (p > .05). The dropout rate for the intervention group was 3%, while the control group had a dropout rate of 22%. Table 2 provides the means, standard deviations, and correlations for group, physical activity behavior, and the psychosocial variables.

The raw data of positive affective associations at time 3 violated the assumption of normality, based on the skewness statistic. Therefore, data were transformed using logarithmic transformation and normality was confirmed using the skewness statistic (≥-1 or 1). A repeated measures ANOVA with sphericity assumed determined that the mean positive affective associations were statistically significant between time points, the main effect of condition, F (2, 112) = 4.082, p = .019 (Table 3). It should be noted that there was no statisti- cally significant effect of interaction between time and

VALUE-BASED PHYSICAL ACTIVITY INTERVENTION 13

group (F (2, 112) = .515, p = .598). Therefore, although the difference between positive affective associations was different by condition, this difference was present at the beginning of the study (time 1) and continued in a similar fashion throughout time 2 and time 3. When all participants were included in the intent to treat analyses, similar results were found for the main effect (F (2, 130) = .561, p = .005) and the interaction between time and group (F (2, 130) = 0.605, p = .561).

A linear regression was run to assess the predictive power of positive affective associations at time 1, 2, and 3

to predict intention at time 3 (Table 4). Although the model predicted 15.5% of the variance in intentions at time 3 (p < .05), positive affective associations at time 1, 2, or 3 were not a significant predictor of intentions at time 3 (p > .05). When the analysis was run with all participants intended to treat the model predicted 14.7% of the variance of intentions (p < .05), and again positive affective associations at time 1, 2, or 3 were not signifi- cant predictors of intentions at time 3 (p > .05). Therefore, the addition of participants that dropped out did not significantly alter the analysis results.

To assess differences in physical activity behavior between the intervention group and control group, an independent t-test was conducted (Table 5). Given the results of previous analyses, a non-significant result was not surprising (t = −1.09, p = .999).

To determine whether the relationship between the intervention and physical activity behavior was mediated by positive affective associations and/or inten- tions toward physical activity, a mediation analysis was

Recruited (n=74)

Randomized (n=67)

Excluded (n=7) Declined to par!cipate (n=7)

Allocated to interven!on group (n=32) Allocated to control group (n=35)

Time 2

Time 1

Time 3

Did not complete data collec!on (n=0) Did not complete data collec!on (n=2)

Loss to follow-up (n=1) Loss to follow-up (n=6)

AnalysisAnalyzed= 31 Analyzed= 27

Figure 1. Recruitment procedure.

Table 1. Characteristics for the sample of participants in cardiac rehabilitation program.

Variable Mean SD

Age 67.51 8.06 Initial CVD Risk 2.82 .39 BMI 31.81 7.43 Ejection Fraction Percentage 48.03 13.34

N’s range from 56 to 67 due to missing data in medical records. CVD = cardiovascular disease. BMI = body mass index.

Table 2. Means, standard deviations, and correlations among group, physical activity behavior, and psychosocial variables.

Variable M (SD) PA Behavior Pos AA

(T1) Pos AA

(T2) Pos AA

(T3) Intention

(T1) Intention

(T2)

Group 3.84 (.94) .14 −.27* −.35** −.44** .25* .15 PA Behavior 130.36 (108.83) −.25 −.33* −.37** .22 .44** Pos AA (T1) .33 (.17) .657** .576** −.366** −.340** Pos AA (T2) .28 (.18) .69** −.26* −.26 Pos AA (T3) .27 (.16) −.24 −.35** Intention (T2) 4.49 (.57) .56** Intention (T3) 4.32 (.66)

N’s range from 58 to 67 due to participant drop out. Abbreviations: Pos AA, positive affective association with physical activity; PA Behavior, physical activity behavior; T1, Time 1; T2, Time 2; T3, Time 3 ** p < .01, * p < .05

14 E. VAN WASSHENOVA ET AL.

performed36 using the Process bootstrapping macro for SPSS.35 The multiple mediator model simultaneously analyzed positive affective associations and intention to be physically active as mediators between the interven- tion and physical activity behavior. The first step of the analysis tested whether the manipulation altered min- utes of physical activity. The independent variable did not significantly change minutes of physical activity (t = −0.15, p = .88). Second, the model also tested whether the manipulation influenced the hypothesized mediators, positive affective associations, and intentions. The independent variable, group, had a significant asso- ciation with positive affective associations (t = −3.1, p = .003). The manipulation did not have a significant relationship with intentions (t = 1.98, p = .053). Third, the analysis tested whether positive affective associations and intentions predicted minutes of physical activity. This analysis showed that positive affective associations (t = −2.22, p = .03) were associated with a greater level of physical activity, but intentions did not (t = 1.12,

p = .27). Finally, a fourth step assessed whether the relationship between the intervention and physical activity was statistically mediated by positive affective associations, intentions, or if positive affective associa- tions and intentions were both mediators. These indirect effects are displayed in Figure 2. Following Preacher and Hayes,36 an accelerated-biased-corrected bootstrap ana- lysis was conducted using 5,000 resamples. This boot- strap analysis showed that the mediation, or indirect, path via positive affective associations was not statisti- cally significant (95% CI: −.2662, 63.22). When inten- tions were considered as a mediator between the intervention and physical activity behavior, it was also not a significant mediator (95% CI: −8.30, 25.45). Similarly, positive affective associations were not a mediator for intentions and physical activity behavior (95% CI: −1.21, 12.66). The analysis does not provide evidence of mediation.

Discussion

Approximately one in three heart attack survivors report attending cardiac rehabilitation after suffering a heart attack.37 Cardiac rehabilitation offers patients with heart disease the opportunity to learn how to increase physical activity with the aim of improving the patient’s health and reducing risk for additional cardiac events. Cost- effective and novel ways to encourage physical activity adherence after cardiac rehabilitation would improve patient health outcomes. The goal of the study was to manipulate positive affective associations toward cardiac rehabilitation exercise sessions using one behavioral component from ACT, values. A secondary goal was to determine if increasing positive affective associations impacted intention to be physically active and physical activity behavior and to explore how the intervention impacted physical activity behavior.

While positive affective associations were statistically different between time 1, time 2, and time 3, this was not the result of the manipulation. Perhaps, this is due to the short duration of the intervention. Differences between the control group and intervention group were not statistically significant, so it is unlikely the lack of effect of the inter- vention was due to participants having different severities

Table 3. Repeated measures ANOVA summary.

Effect Mean

Square df F

Positive Affective Association .04 2 4.08* Positive Affective Association*Group .01 2 .52 Error .01 112

*p < 0.05

Table 4. Predictive power of positive affective association with physical activity (T1, T2, T3).

Intentions (T3)

Variable B SE B β R2 F for R2 change

Pos. AA (T1) −.97 .68 −.24 .16 3.30* Pos. AA (T2) .31 .71 .09 Pos. AA (T3) −1.11 .72 −.27

Pos AA, positive affective association with physical activity *p < .05

Table 5. T-test results comparing intervention and control group on physical activity behavior.

95% CI

Outcome F t df Lower Bound Upper Bound

Physical Activity Behavior .000 −1.09 56 −88.53 26.06

* p < 0.05

Indirect Effect 1: Intervention Positive Affecitve Assocations Physical Activity Behavior

Indirect Effect 2: Intervention Physical Activity Intentions Physical Activity Behavior

Indirect Effect 3: Intervention Positive Affective Assocations Physical Activity Intentions Physical

Activity Behavior

Figure 2. Indirect effects of intervention on physical activity.

VALUE-BASED PHYSICAL ACTIVITY INTERVENTION 15

of heart disease. External factors that impede physical activity may have diminished the predictive power of posi- tive affective associations. Geers et al. found that positive affective associations are not as predictive for high school- ers for at-home physical activity vs. in-school activity.15 In the current study, physical activity behavior was collected after participants had left cardiac rehabilitation (time 3), while other measures were collected while in cardiac reha- bilitation with less factors impeding physical activity. Other factors not recorded which may have impeded physical activity behavior after participants left cardiac rehabilita- tion include if the subject returned to work, accessibility to exercise facilities or equipment, and medical issues pre- venting engagement in exercise.

Contrary to expectations based on previous research, when put together in a regression equation, neither positive affective associations nor intentions significantly predicted physical activity behavior (p > .05). Although the interven- tion was statistically significant in predicting intentions with 10.5% of the variance in physical activity intentions explained by group (intervention or control), there were no statistically significant differences in physical activity beha- vior between the control and intervention group (p > .05). Other researchers have found different results in ACT interventions to increase physical activity. For example, a pilot study found an increase in physical activity in cardiac rehabilitation patients after 6 hours of manipulation with licensed clinical psychologists. Additionally, Lillis, Schumacher, and Bond did a 1-day (4-hour) ACT inter- vention in insufficiently active adults with overweight or obesity with weekly e-mails and monthly phone calls for 3 months.38 In comparison, the current study used a 60- minute therapy manipulation with a Health Educator not trained in clinical psychology. The time difference and lack of continued follow-up could account for the lack of effec- tiveness in the current study. It should also be noted that both studies referenced did not have a control group; there- fore, the intervention may not have been effective and physical activity behavior could have increased naturally or due to factors outside of the interventions. A strength of the current study is the inclusion of a control group that received standard-of-care education for comparison.

The current study has limitations, including no objec- tive measurement of physical activity. While self- reporting of physical activity has limitations, the parti- cipants were familiar with reporting minutes of physical activity and RPE for activities completed during cardiac rehabilitation sessions and outside of the sessions. The current study did not measure overall survey instrument reliability and validity, but this concern is lessened slightly, due to earlier research demonstrating reliability and validity of each individual measure used. Another limitation may be the short intervention (1 session,

60 minutes) introducing the potential for a type III error – that is, correctly rejecting the null hypothesis, but rejecting for the wrong reason.39 For example, in the current study, based on the result, it might be concluded that a value-based intervention is not effective in pro- moting physical activity, when in fact the issue was with implementation (i.e. a 60-minute intervention may not lead to meaningful behavioral results). Although evi- dence suggests that one ACT session is enough to pro- mote physical activity20 and brief ACT interventions have been successful in other populations,38 a longer intervention is recommended for future studies. The current study only used one component of ACT, values, while other studies addressing all ACT core elements have obtained adequate results.20 These data could indi- cate the effectiveness of ACT and the need to apply all the processes pertaining to the model to obtain success- ful results. Although the sample size of 58 participants may have impacted results, it is larger than the previous study in cardiac rehabilitation patients (n = 19) and included more subjects than 19 of the 21 ACT physical activity interventions reported in a recent systematic review (n’s ranged from 6 to 103).20

The study has several strengths, including the inclu- sion of a control group with standard-of-care education. Additionally, the research was conducted in cardiac rehabilitation patients, an important population for physical activity promotion. Most ACT interventions to promote physical activity have been conducted exclu- sively or primarily in women, while the current sample included 60% men.20The current study showed feasibil- ity to conduct an ACT intervention in cardiac rehabili- tation patients with an overall dropout rate of 13%, which is within the range of reported adherence for randomized controlled trials with physical activity in cardiovascular disease patients (0% to 28.1%).40

Translation to Health Education Practice

This study guides future research by considering ways to promote physical activity in priority populations, such as patients in cardiac rehabilitation. This study addressed several Health Education practice competen- cies by the National Commission for Health Education Credentialing, Inc.41 The study aimed to determine if positive affective associations toward physical activity can be manipulated using the values component from ACT and explore if increases in positive affective asso- ciations impacted physical activity intention or physical activity behavior. These aims meet competencies in Area IV: Evaluation and Research (4.2.1 determine purpose, hypotheses, and questions, 4.2.2 comply with institu- tional and/or IRB requirements for research, 4.2.5 select

16 E. VAN WASSHENOVA ET AL.

a research design model and the types of data to be collected, 4.2.6 develop a sampling plan and procedures for data collection, management, and security, 4.2.7 select quantitative and qualitative tools consistent with assumptions and data requirements, 4.2.8 adopt, adapt, and/or develop instruments for collecting data, 4.3.2 implement data collection procedures, 4.3.6 analyze data, 4.4.1 explain how findings address the questions and/or hypotheses, 4.4.2 compare findings to other eva- luations or studies, 4.4.3 identify limitations and delimi- tations of findings, 4.4.4 draw conclusions based on findings).41

No significant difference was detected in positive affec- tive associations in the intervention and control groups and neither positive affective associations nor intentions signif- icantly predicted physical activity behavior. Based on this study, we have the following recommendations for future studies:

● Incorporate additional principles of ACT. This intervention was rooted in one principle of ACT, values. By identifying values, participants could focus on how physical activity was connected to their current values. We believe that values is an important concept for long-term change, allowing participants to connect physical activity to deeply held values. Future interventions should include values while including other ACT principles and components informed by the literature. Health Educators who implement additional aspects of ACT would be showing competency in Area I Assessment of Needs and Capacity (1.2.3 conduct a literature review, 1.2.6 identify data gaps).41

● Dose higher than 60-minute intervention. Future research should explore if a slightly longer inter- vention period, for example 2 sessions at 2 hours each, leads to increased physical activity behavior. This might be effectively done through pilot testing before study implementation demonstrating Area II Planning (2.3.6 conduct a pilot test of intervention(s) and 2.3.7 revise intervention(s) based on pilot feedback).41

● Use methods appropriate for the population. The intervention design incorporated health behaviors and delivery methods highly accessible to this population. However, these components can be adapted for additional populations and health behaviors demonstrating competency in Area I Assessment of Needs and Capacity (1.1.2 identify priority population(s)) and Area II Planning (2.3.4 adopt, adapt, and/or develop tailored intervention- (s) for priority population(s) to achieve desired outcomes).41

Health Educators who participate in data collection and interpretation demonstrate competency in Area IV: Evaluation and Research (4.3.2 implement data collec- tion procedures, 4.4.4 draw conclusions based on find- ings, 4.4.5 identify implications for practice).41 These considerations need to be balanced with feasibility of implementing the intervention in cardiac rehabilitation programs and consider cost and time. Health Educators could be particularly helpful in determining the feasi- bility of implementing interventions in their respective populations and settings – this would show competency in sub competency 4.4.8 evaluate feasibility of imple- menting recommendations.41

Disclosure statement

No potential conflict of interest was reported by the author(s).

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