A Prospective Proof-of-Concept Study Evaluating the Influence of Patient Education on Knowledge, Attitudes, and Cardiac Rehabilitation Attendance among Patients with Coronary Artery DiseaseGraduate Studies The Vault: Electronic Theses and Dissertations
2019-08-23
Attitudes, and Cardiac Rehabilitation Attendance
among Patients with Coronary Artery Disease
Williamson, Tamara Marie
Williamson, T. M. (2019). A Prospective Proof-of-Concept Study Evaluating the Influence of
Patient Education on Knowledge, Attitudes, and Cardiac Rehabilitation Attendance among
Patients with Coronary Artery Disease (Unpublished master's thesis). University of Calgary,
Calgary, AB.
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Coronary Artery Disease
IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE
DEGREE OF MASTER OF SCIENCE
GRADUATE PROGRAM IN CLINICAL PSYCHOLOGY
CALGARY, ALBERTA
AUGUST, 2019
Patient education (PE), delivered during cardiac rehabilitation (CR), aims to promote CR
exercise attendance by imparting knowledge about coronary artery disease (CAD; medication,
risk factors, etc.) and enhancing CR-related attitudes. This study evaluated the impact of PE on
motivational treatment targets (CAD knowledge, CR attitudes), and CR exercise attendance.
Adults (18+) with CAD referred to CR were recruited prior to attending PE. CAD knowledge
and CR attitudes (perceived necessity/suitability, exercise concerns, barriers) were assessed
pre/post-PE, and at 12-week follow-up. CR exercise attendance was obtained by chart review.
Seventy-one patients (87% male) participated. CAD knowledge and perceived CR necessity
improved pre- to post-PE; gains persisted at 12-weeks. Greater knowledge gains did not predict
larger improvements in CR attitudes or increased exercise attendance. Whereas CR-based PE
may be useful for improving CAD-related knowledge and perceived need for CR, more
formative work is needed to determine whether PE can promote CR exercise attendance.
Keywords: cardiac rehabilitation, patient education, coronary artery disease, knowledge, attitudes
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Acknowledgments
First, thank you to my family, whose support was instrumental in completing this work.
Second, this project would not have been possible without the consistent mentorship and support
of my thesis advisors and supervisory committee. My primary and co-supervisor, Dr. Tavis
Campbell and Dr. Codie Rouleau, have guided and counselled me over the past four years
through my BA and MSc degrees. Thank you for being so generous with your time, and ensuring
I received the best training experience possible. Third, thank you to Dr. Kathryn King-Shier and
Dr. Kristin von Ranson for their valuable advice and suggestions regarding this work. Fourth,
thank you to my colleagues in the Behavioural Medicine Lab, Dr. Joshua Rash, Kirsti Toivonen,
Michelle Flynn, and Chelsea Moran, for your friendship and informal advice regarding this
study. In addition, thank you to our wonderful research assistants, Ashley Felske, Sydney Seidel,
and Mahrukh Kaimkhani for assisting with data entry, questionnaire preparation, and other
important administrative work. A special thank you to Dr. Lauren Drogos for assisting me with
the statistical analyses for the present study. Fifth, I would like to acknowledge the
TotalCardiology® Research Network (TCRN), including Trina Hauer, Leslie Austford, Jim
Stone, Sandeep Aggarwal, Stephen Wilton, and Ross Arena. The TCRN has provided me with
research experiences that have enhanced my professional development and ignited my passion
for cardiovascular rehabilitation and disease prevention research. Thank you to the entire staff at
TotalCardiology® Rehabilitation, who assisted with patient recruitment and are always willing to
help with our research projects. Finally, this study would not have been possible without the
generous participation of the patients at TotalCardiology®. A sincere thank you to all of the
patients who participated in the present study.
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Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Characterizing the Impact of CR Educational Interventions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Mechanisms-of-Action in Patient Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
Knowledge about CAD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
The Present Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
Leisure-time exercise . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Baseline characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Health literacy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
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Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Secondary Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Association between TCHH and CR attitudes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Association between changes in knowledge and changes in CR attitudes . . . . . . . . . . . . . . . 23
Association between changes in knowledge and CR exercise attendance . . . . . . . . . . . . . . . 23
Post-Hoc and Exploratory Outcomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
Influence of TCHH among patients with low vs. high initial knowledge . . . . . . . . . . . . . . . 23
Influence of TCHH on behavioural intentions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
Additional exploratory outcomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
Appendix A
Figure A1. The ORBIT Model for Behavioural Treatment Development . . . . . . . . . . . . . . . . . 54
Figure A2. Model of pathway by which a behavioural treatment is hypothesized to improve a
clinical outcome . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Appendix C: Detailed Recruitment and Patient Follow-Up Procedures . . . . . . . . . . . . . . . . . . . . 56
Appendix D: Exploratory and Post-Hoc Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
Table D1. Post-hoc Two-Way Mixed Design ANCOVA examining the effects of Time (T1, T2,
T3) and baseline CAD Knowledge (High, Low) on CADE-Q II total scores. . . . . . . . . . . . . . . . 58
Table D2. Correlations between changes in CAD knowledge and changes in cardiac risk
factors from pre-TCHH to 12-weeks post-TCHH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
Table D3. Multiple regression model examining the role of pre-TCHH values of potential
treatment targets in predicting CR exercise attendance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
Figure D1. CADE-Q II knowledge domain scores pre-TCHH, post-TCHH, and at 12-week
follow-up. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
Figure D2. CADE-Q II total knowledge scores pre- and post-TCHH, and at 12-week follow-
up, for patients with low vs. high initial CAD knowledge.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
Appendix E: APA Copyright and Permissions Policy 64
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Table 1. Sample characteristics by group (study completers vs. non-completers)
and statistical tests of group differences at baseline . . . . . . . . . . . . . . . . . . . . . . . . . 34
Table 2. CAD Knowledge total Scores, domain scores, and CR Attitudes pre-
TCHH, post-TCHH and at 12-week follow-up . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
Table 3. Linear regression models estimating associations between changes in CAD knowledge
and changes in BACR subscales (T2 – T1) from pre- to post-TCHH . . . . . . . . . . . . 38
Table 4. Linear regression model estimating associations between changes in CAD
knowledge and CR exercise attendance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
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viii
Symbol Definition
Δ Difference score calculated as T2-T1 or T3-T1, as indicated
ACS Acute Coronary Syndrome
BACR Beliefs about Cardiac Rehabilitation Scales (Cooper et al. 2007)
BMI Body Mass Index (i.e., weight in kilograms divided by height in meters squared)
CAD Coronary Artery Disease
CADE-Q II Coronary Artery Disease Education Questionnaire – Version II (de Melo Ghisi
et al., 2015b)
CR Cardiac Rehabilitation
CVD Cardiovascular disease
DV Dependent Variable
HAPA Health Action Process Approach (Schwarzer et al., 2011)
HBI Health Behaviour Intentions (Renner & Schwarzer, 2005)
IV Independent Variable
MI Myocardial infarction
PE Patient Education
ANOVA Analysis of variance
TCHH Taking Charge of your Heart Health patient education curriculum
TCR TotalCardiology™ Rehabilitation
1
Introduction
Cardiovascular disease (CVD) is a leading cause of death in Canada and worldwide
(PHAC, 2017; WHO, 2017). Coronary artery disease (CAD), the most common form of CVD, is
a chronic condition characterized by an impedance or blockage of the coronary arteries that is
typically a consequence of atherosclerosis (Stone, 2009). CAD risk factors include a cluster of
poor health behaviors including smoking, obesity, and lack of exercise. CAD requires ongoing
tertiary prevention to prevent serious health consequences including angina, myocardial
infarction (MI), and cardiac arrest (Stone, 2009). Cardiac rehabilitation (CR) is the gold-standard
in tertiary prevention of CAD (Anderson et al., 2016; Balady et al., 2011; National Institute for
Health and Care Excellence, 2013), and comprises education, supervised cardiovascular exercise,
and individualized support with risk factor modification (e.g., medication, smoking cessation,
nutrition counselling; Grace, Bennett, Ardern, & Clark, 2014; Sandesara et al., 2015; Stone,
2009). Systematic reviews of randomized-controlled trials (RCTs) demonstrate that CR
participation improves health-related quality of life, reduces healthcare costs (e.g., hospital
admissions, medication consumption, and ED visits), improves cardiovascular risk factors (blood
pressure, lipid profile, depressive symptoms) and reduces cardiac-related mortality by 26% on
average (Alter, Yu, Bajaj, & Oh, 2017; Anderson et al., 2016; Lawler, Filion, & Eisenberg, 2011;
Rutledge, Redwine, Linke, & Mills, 2013). Although CR is a multi-component intervention, its
primary focus is on exercise training, and it is well-established that benefits of CR participation
are partially attributable to effects of aerobic exercise on vascular biology (Anderson et al.,
2016). Thus, attendance at supervised CR exercise sessions is a crucial indicator of whether
patients will achieve clinically relevant improvements in their cardiovascular health status.
Despite the benefits of CR participation, program uptake and adherence to exercise
sessions is suboptimal. According to systematic reviews, patients fail to attend approximately
2
relationship between higher exercise attendance and better health outcomes at two-to-four year
follow up (e.g., lower likelihood of repeat MI, hospitalization, and mortality; improved
cardiorespiratory fitness and medication adherence)(Alter et al., 2015; Hammill, Curtis,
Schulman, & Whellan, 2010; Martin et al., 2012). A recent, retrospective cohort study (N =
17,000) reported that each 10% increase in CR exercise attendance corresponded to a 4%
decreased risk of death or hospitalization within two years (Alter et al., 2015).
Given the critical role of CR participation, and exercise attendance in particular, on CAD
outcomes, providing effective behavioural interventions to improve program adherence is
essential to helping patients live longer, healthier lives (Santiago de Araújo Pio, Chaves, Davies,
Taylor, & Grace, 2019). A recent Cochrane review suggests that, while interventions to improve
CR exercise attendance are effective overall, substantial heterogeneity precludes
recommendations regarding “specific, implementable intervention materials and protocols”
(Santiago de Araújo Pio et al., 2019, p. 15). Best-practice guidelines (e.g. ORBIT [Czajkowski et
al., 2015]; MRC [Michie et al., 2013]) recommend using a phased methodology for
development, testing, and optimization of behaviour change interventions for patients with
chronic disease. For example, the ORBIT model emphasizes a need for early-phase research
demonstrating ‘proof-of-concept’, defined as “the ability of a fixed treatment package to produce
a clinically significant improvement on a behavioural risk factor” (Czajkowski et al., 2015, p.
977). This serves as a critical step prior to investing time and resources toward large-scale
efficacy trials (Czajkowski et al., 2015). Few existing interventions for enhancing CR exercise
attendance have followed this approach, and formative research is needed to characterize the
3
(Czajkowski et al. 2015, Appendix A).
Patient Education in CR
Patient education is one strategy that is widely used as part of CR programming to help
promote CAD self-management and CR exercise attendance. Patient education is defined as “the
process by which health professionals and others impart information to patients that will alter
their health behaviours or improve their health status” (Koongstvedt, 2001, p. 788). Whereas
providing education alone does not translate to improvements in cardiac-related mortality,
subsequent MI, or hospital admissions (Anderson et al., 2017), patient education is fundamental
to ensuring patients have adequate disease-related knowledge (e.g., information regarding cardiac
risk factors, nutrition recommendations, proper medication adherence) to implement and
maintain a complex health behaviour regimen (de Melo Ghisi, Abdallah, Grace, Thomas, & Oh,
2014; Friedman, Cosby, Boyko, Hatton-Bauer, & Turnbull, 2011; Kayaniyil et al., 2009; Michie,
van Stralen, & West, 2011). Patient education is thus considered a quality indicator and core
component of CR programs according to Canadian and international clinical guidelines (Buckley
et al., 2013; Canadian Cardiovascular Society, 2013; Stone, 2009).
Characterizing the Impact of CR Educational Interventions
Despite the importance of patient education to CAD self-management, there is a paucity
of high-quality research examining the impact and mechanisms of educational programs
delivered in the context of outpatient CR. Patient education for CAD patients has been
investigated in various healthcare settings using modalities such as bedside hospital
consultations, individual or group-based counselling programs, and telephone-based follow-ups.
Such educational programs have been demonstrated to enhance knowledge and improve
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adherence to a variety of recommended health practices such as engaging in regular physical
activity, healthy dietary patterns, and smoking cessation (Aldcroft, Taylor, Blackstock, &
OHalloran, 2011; de Melo Ghisi et al., 2014; Dusseldorp, van Elderen, Maes, Meulman, &
Kraaij, 1999). Programs vary widely, however, in terms of educational providers (e.g., nurses,
physicians, trained educators, researchers, coordinators), delivery mode (e.g., lectures, group
classes, e-learning, tele-health, home visits), intensity (e.g., one 40-minute session to 11-months
duration), and educational content delivered (Anderson et al., 2017; de Melo Ghisi et al., 2014;
Liu, Shi, Willis, Wu, & Johnson, 2017). Further, a systematic review of studies assessing the
impact of CAD patient education reports that just 11 of 42 studies reviewed examined patient
education in the context of outpatient CR, and none of these CR-based studies assessed the
impact of education on patients’ CAD-related knowledge.
An additional challenge in estimating the impact of CR-based patient education is the
absence of formal, evidence-based guidance regarding the optimal nature of educational
curricula for patients with CAD. For example, current Canadian CR guidelines indicate that
patient education in CR should: (1) be delivered by professional staff, (2) consist of face-to-face
contact with patients, (3) facilitate goal-setting, (4) aim to enhance patients’ self-efficacy, beliefs
and attitudes about CR, and (5) be delivered either individually or in group settings (Stone,
2009). Recommendations on the optimal setting, duration, intensity, content, and format of CR-
based patient education are absent. Given the large variability in existing educational
interventions, it is impossible to estimate the true impact of these programs on knowledge and
behaviour change. Most CR-based patient education programs are therefore operating in “good
faith” in assuming their educational interventions actually translate to improved disease-related
knowledge and increased CR exercise attendance among patients with CAD.
5
Quantifying a link between patient education interventions and target motivational
variables is critical to establishing ‘proof-of-concept’ and ultimately to impacting important
behavioural and biomedical outcomes (Czajkowski et al., 2015). Formative intervention research
of this nature is also necessary to clarify relative importance of hypothesized treatment targets
and characterize the magnitude of treatment impact on important behavioural risk factor(s) (see
Figures A1 & A2, Appendix A; Czajkowski et al., 2015). Two plausible mechanisms underlying
the potential effectiveness of CR-based patient education are improved knowledge about CAD
and enhanced positive attitudes towards CR. Theory by Michie and colleagues (2011) posits that
improvements in these constructs may favourably impact patients’ psychological capability (i.e.,
knowledge, understanding, skills) and reflective motivation (i.e., the conscious “brain processes
that energize and direct behaviour”; Michie et al., 2011, p. 4) for exercise, leading to
improvements in CR exercise attendance. Further, improvements in one target motivational
variable have the potential to promote positive changes in another (Michie et al., 2011). For
example, cross-sectional research (N = 1,308) among inpatients with CAD suggests that greater
CAD knowledge correlates with attitudes and beliefs that are important for CAD self-
management behaviour (e.g., greater perceptions of CAD as a serious, chronic condition; an
improved sense of personal control over one’s illness; Kayaniyil et al., 2009). Accordingly, CAD
knowledge and CR attitudes are frequently included as treatment targets in cardiac patient
education interventions (e.g., de Melo Ghisi, Grace, Thomas, Vieira, et al., 2015; McKinley et
al., 2009; Meng et al., 2014). Each of these factors is discussed in turn below.
Knowledge about CAD. Definitions of cardiac-related knowledge vary depending on the
patient population and the context/timing of knowledge assessment (e.g., Buckley et al., 2006; de
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Melo Ghisi et al., 2014; Lidell & Fridlund, 1996; Marshall, Penckofer, & Llewellyn, 1986).
Knowledge domains included in prior cardiac education interventions include cardiovascular
physiology, psychosocial health, risk factors, health behaviours (nutrition, exercise,
medications), symptoms, misconceptions about heart disease, and post-operative recovery
(Buckley et al., 2006; Cordasco et al., 2009; de Melo Ghisi, Grace, Thomas, Evans, & Oh, 2015;
Lidell & Fridlund, 1996; Marshall, Penckofer, & Llewellyn, 1986; McKinley et al., 2009;
Tawalbeh & Ahmad, 2014). Several tools have been developed to assess cardiac knowledge,
using True/False or multiple-choice scales (de Melo Ghisi et al., 2015b; McKinley et al., 2009).
For example, de Melo Ghisi and colleagues (2010, 2013, 2015b) developed the CAD Education
Questionnaire, Version 2 (CADE-Q-II) to assess CAD-related knowledge among CR patients
specifically. The CADE-Q II has good reliability and validity evidence supporting its use to
determine what CR patients are learning about CAD in terms of the five core components of CR
(physiology, risk factors, nutrition, exercise, and stress management; see “Measures” section
below; de Melo Ghisi et al., 2015b).
Two recent studies highlight the potential impact of CR-based patient education on
CAD-related knowledge. A German sequential-cohort study reports that participation in an
inpatient CR education curriculum (i.e., interactive, group-based classes focused on risk factors,
physiology, medication, diet, and exercise), was associated with increased knowledge at hospital
discharge and 12-months later among adult patients with CAD (Meng et al., 2014). Similarly, in
a non-randomized, quasi-experimental study by de Melo Ghisi and colleagues (2015a, 2015c),
CR patients with CAD or multiple cardiac risk factors were assigned to either a traditional CR
educational curriculum, or a curriculum based on motivational theory (i.e., The Health Action
Process Approach; HAPA, Schwarzer, Lippke, & Luszczynska, 2011) according to personal
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preference. Patients in both groups demonstrated increases in CAD knowledge post-CR and at 6-
month follow-up.
CR Attitudes. Changing health behaviours requires more than knowing “what” to do, but
also having favourable attitudes, including perceived importance and self-efficacy regarding the
demands involved in behaviour change (Ajzen, 1991; Bandura, 2010; Schwarzer et al., 2011) .
Systematic reviews of observational studies and RCTs (Murray, Craigs, Hill, Honey, & House,
2012; Ruano-Ravina et. al., 2016), and qualitative research (Clark et al., 2012; Neubeck et al.,
2012) consistently report that less-favourable attitudes, including perceptions that CR is not
personally beneficial, concerns about exercise, and low perceived control over one’s illness,
correspond to relatively poorer attendance at CR exercise sessions. A recent RCT of 96 patients
with CAD referred to outpatient CR suggests positive CR-related attitudes—namely, increased
perceived necessity of CR, fewer exercise concerns, and fewer practical CR barriers at program
outset—correlate with increased CR exercise session attendance (Rouleau et al., 2018). By
imparting detailed knowledge about CAD, patients who doubt their ability to complete CR may
feel more confident to engage in heart-healthy behaviours (e.g., CR exercise, nutritional change,
smoking cessation) and more optimistic about CR outcomes (Michie et al., 2013; Michie,
Abraham, Whittington, McAteer, & Gupta, 2009; Michie et al., 2011). Enhancing CR-related
attitudes and beliefs is therefore considered a key objective of patient education delivery in CR
(Grace et al., 2016; Stone, 2009).
To date, only one CR-based patient education program has been empirically evaluated in
terms of its impact on patients’ CAD knowledge and attitudes toward CR (i.e., Toronto-based
Cardiac College [Cardiac College, 2018; de Melo Ghisi et al., 2015a; 2015c]). The Cardiac
College curriculum consists of 24, 30-minute weekly educational classes delivered by CR
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experts, “strategically mapped and sequenced to support the program learning outcomes” (de
Melo Ghisi et al., 2015b, p.10). Research at this site indicates that, among a sample of (primarily
male, educated) CR patients with CAD, Cardiac College patient education improves CAD-
related knowledge and CR attitudes in terms of HAPA-based motivational constructs (risk
awareness, CR outcome expectancies, self-efficacy, and action planning)(de Melo Ghisi et al.,
2015a). de Melo Ghisi et al. (2015a, 2015c) also report that completion of the Cardiac College
education program corresponds to increased minutes of weekly exercise 6-months post-CR.
Curricula such as Cardiac College are resource-intensive, however, therefore this education
model may not translate well to CR programs of shorter duration. Completing a 6-month
educational program may be challenging for CR patients with various barriers to attending
clinic-based education sessions (e.g., transportation, distance from CR, work constraints)(Grace
et al., 2009; Shanmugasegaram et al., 2012). As such, existing CR educational interventions that
are more feasible to implement in the course of usual care/resource-constrained CR programs
should be evaluated (Grace et al., 2016).
Gaps in the Literature
Whereas previous work indicates patient education has the potential to enhance CAD
knowledge and CR attitudes (e.g., de Melo Ghisi et al., 2015a, 2015c), treatment pathways need
further clarification. For example, no studies have empirically evaluated whether CAD
knowledge gains actually translate to improved motivation (i.e., enhanced CR attitudes) and CR
exercise attendance. The extant literature reports equivocal associations between health-related
knowledge and initiation of target behaviours across health domains (Ajzen et al., 2011; Rimal,
2000, 2001; Kelly & Barker, 2016). For instance, de Melo Ghisi et al. (2015c) report that greater
CAD knowledge assessed using the CADE-Q II 6-months post-Cardiac College patient
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education was not associated with greater weekly exercise at 6-month follow-up. Further,
whereas de Melo Ghisi (2015c) and others (e.g., Meng et al., 2014) describe associations
between educational curricula and increased exercise minutes assessed post-CR, program impact
on CR-based exercise is less clear. One recent RCT of 825 patients with CAD or heart failure
participating in a CR program reports that an eight-week patient education intervention
incorporating numerous motivational strategies (e.g., one-on-one interviews with program
nurses; “goal setting, action planning, coping strategies, stress management, and peer modelling”
[p. 68]) increased patients’ likelihood of attending at least three-quarters of prescribed CR
exercise sessions by 48% relative to controls (95% CI of the OR = 1.07-2.05)(Lynggaard,
Nielsen, Zwisler, Taylor, & May, 2017). Given the dose-response relationship between higher
CR exercise session attendance and improved CAD outcomes (Alter et al., 2015), more research
is needed to understand and quantify the potential impact of patient education on CR-based
exercise specifically.
The Present Study
This prospective observational cohort study investigated the impact of a brief (four, 2.5-
hour, group-based classes delivered within one week), manualized patient education program
(i.e., Taking Charge of your Heart Health; TCHH) delivered through TotalCardiology™
Rehabilitation (TCR), a large outpatient CR program in Calgary, Alberta. Specifically, this Phase
IIa Proof-of-Concept study (see Figure A1, Appendix A) aimed to explore the influence of
TCHH on treatment targets known to promote health behaviour change in CR and elucidate
mechanisms-of-change whereby education impacts health behaviours. Given that Phase I work
(i.e., define/refine treatment components; Appendix A) was not previously performed during
TCHH development, the present study also sought to characterize the influence of potential
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TCHH treatment targets (CAD knowledge, CR attitudes, and behavioural intentions) on CR
exercise attendance directly. This study was approved by the Conjoint Health Research Ethics
Board at the University of Calgary (REB17-2481).
Primary Aim
The primary study aim was to evaluate the impact of the TCR TCHH curriculum on CAD
knowledge from pre-(T1) to post-(T2) TCHH, and at 12-week follow-up (T3). It was predicted
that knowledge about CAD would increase from T1 to T2, and knowledge gains would be
maintained at T3.
The secondary aims were to: (1) investigate whether TCHH participation influences CR
attitudes (i.e., perceived necessity/suitability for CR, self-efficacy for CR exercise); (2) examine
whether increases in CAD knowledge from T1 to T2 translate to improvements in CR attitudes;
and (3) determine whether CAD knowledge gains from T1 to T2 were associated with increased
CR exercise attendance. It was predicted that: (1) CR attitudes would improve from T1 to T2,
with improvements maintained at 12-week follow-up; (2) knowledge gains from T1 to T2 would
be positively associated with improvements in CR attitudes at T2, and (3) knowledge gains from
T1 to T2 would correspond to greater CR exercise attendance at 12-week follow-up.
In terms of exploratory aims, this study examined whether TCHH participation
corresponded to improved intentions to attend CR exercise sessions (T1 to T2), and intentions to
change health behaviours (e.g., smoking cessation, medication adherence, and healthy diet; T1 to
T3). Intention to engage in various health behaviours explains, on average, 28% of variance in
subsequent action (Sheeran, 2002). Previous research at TCR demonstrates that each one-point
increase in intention to attend CR exercise sessions (assessed on a 7-point scale) corresponds to
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approximately 2.5 additional CR sessions attended (Rouleau et al., 2018; Williamson, Rouleau,
Aggarwal, Arena, & Campbell, 2018). Finally, this study aimed to examine whether larger CAD
knowledge gains would translate to improvements in cardiovascular risk factors (e.g., blood
pressure, blood lipids, BMI, MET), and increased leisure-time exercise from T1 to T3.
Methods
Patients
English-speaking adults (18+ years) with CAD following an acute coronary syndrome
(ACS) event (i.e., myocardial infarction, unstable angina, ischemic heart disease) automatically
referred to attend outpatient CR at TCR in Calgary, AB participated in the study.
Inclusion criteria. Patients were eligible to participate if they: 1) were able to speak
English (assessed through conversation during recruitment and by affirmative response to a
single item on baseline questionnaire reading: “Are you able to read and write in English well
enough to fill out questionnaires and surveys without assistance?”); 2) were referred to and
eligible for the TCR CR program following diagnosis and non-surgical treatment of ACS; 3)
were registered for, but had not yet attended, TCHH patient education; 4) did not previously
complete the TCR program within the past 10 years; and 5) provided consent to be contacted
about research. Patients with ACS were targeted because they represent the most common
patient group referred to TCR (~70% of referrals according to TCR internal data; C. Rouleau,
personal communication, August 1, 2019). In addition, this group was targeted to ensure all
participants followed the same program schedule; all ACS patients follow a standard Early
Cardiac Access Clinic stream that involves a different schedule of exercise and education
appointments than other patient groups (e.g., post-surgical patients).
12
(Czajkowski et al., 2015; Kraemer, Mintz, Noda, Tinklenberg, & Yesavage, 2006), the study was
powered to detect an effect size of Cohen’s f = .20, representing a minimally practically
significant effect (Ferguson, 2009) for the primary outcome of CAD knowledge. With power =
.80 and two-tailed hypothesis testing at the α = .05 level, full data from 42 patients was needed to
detect significant results. Accounting for potential attrition, a conservative recruitment target of
100 was chosen.
CR Program Description
Exercise program. All non-surgical ACS patients admitted to cardiology wards or
coronary care units in Calgary, AB receive an automatic referral to the TCR program upon
hospital discharge. Patients are typically scheduled for an orientation appointment at the CR
centre within seven days post-discharge. The orientation appointment consists of an exercise
stress test, risk factor and medication review, and if deemed medically appropriate, an invitation
to attend the CR program. Information from the exercise stress test is used to establish
appropriate exercise intensity and establish exercise safety for individual patients. The CR
program consists of the TCHH patient education classes followed by 12-weeks of medically
supervised exercise training. Exercise sessions consist of twice-weekly hour-long cardiovascular
aerobic exercise (e.g., stationary bicycle, walking on a treadmill) held at one-of-two Calgary
locations.
specialists and registered nurses who provide tailored, weekly follow-ups to support patients in
reaching their behavioural goals (e.g., exercise targets, medication adherence, nutrition). Patients
also have access to multidisciplinary support from a psychologist, dietitian, and optional
13
education classes (e.g. strength and balance training, nutrition label-reading). Optimization of the
medical management of risk factors is supported by program physicians and/or primary care
providers. Patients who have difficulty attending centre-based CR have the option to participate
in a home-based program consisting of exercise training at home or in the community with
follow-up support by telephone. There is a one-time $500 fee for the program, however fee
waivers, payment plans, and sliding-scale payment options are available for patients with
financial constraints. Previous studies conducted at TCR demonstrate that program completion is
associated with decreased hospitalizations, improvements in physical and mental health
outcomes, and increased survival (Campbell et al., 2012; Martin et al., 2012).
Patient education. TCHH is comprised of four, 2.5-hour group-based sessions delivered
by a multi-disciplinary team of health providers. Course content covers cardiac physiology, risk
factors (e.g., smoking, hypertension, stress, obesity), medications, nutrition, exercise, stress
management, goal-setting, and general CR program information. The four TCHH classes are
delivered in two full-afternoon educational sessions, typically within the same week. All sessions
follow a manualized format including standardized PowerPoint presentations and speaker notes.
Classes are interactive, and patients are provided with a comprehensive resource manual
containing all information covered in-class. Unpublished program statistics show average
attendance at TCHH classes is 20-30 ACS patients per week; approximately 80-85% of patients
who attend the CR orientation visit come to TCHH.
TCHH instructors undergo internal training to facilitate classes including workshops on
patient-provider communication delivered by a registered health psychologist (C.R.). Facilitators
receive five hours of direct supervision on communication skills (e.g., active listening,
reflections, asking effective questions, and collaboratively delivering information) and are
14
required to observe a senior staff member facilitate at least two TCHH classes before being
qualified to teach the class. Once qualified to teach independently, facilitators undergo
observation by another trained facilitator. All facilitators have at minimum a four-year
Bachelor’s degree and include registered nurses, certified exercise specialists, registered
dieticians, and a registered psychologist.
Measures
The assessment schedule across study time-points is presented in Appendix B.
Primary outcome. CAD knowledge was measured using the Coronary Artery Disease
Education Questionnaire-2nd Version (CADE-Q II; de Melo Ghisi et al., 2015b). The CADE-Q II
contains 31 multiple choice items inquiring about CAD-related knowledge across five subscales
representing the core domains of patient education in CR: medical condition (7 items), risk
factors (5 items), exercise (7 items), nutrition (7 items), and psychosocial risk (5 items).
Respondents select from four options per question (e.g., “Coronary artery disease is:”)
representing complete knowledge (e.g., “A disease of the arteries of the heard that starts silently
at a young age. It is influenced by poor lifestyle habits, genetics, and involves inflammation in
the arteries”; 3 points), incomplete but correct knowledge (e.g., “A disease of the arteries of the
heart which occurs in older age in people with high cholesterol or who smoke”; 1 point),
incorrect knowledge (e.g., “A disease of the heart’s arteries that occurs only in older age and is
mainly caused by deposits of calcium in the arteries”; 0 points) and “I don’t know” (0 points).
The maximum total score is 93 points.
Development of the CADE-Q II was informed by results from a literature search and CR
guidelines review, as well as findings from a previous study assessing patients’ information
needs in CR (de Melo Ghisi, Grace, Thomas, Evans, & Oh, 2013). Content analysis was
15
performed by 15 CR experts (clinicians and researchers) from CR programs in Ontario, Canada
and test items refined as needed. Results from a psychometric validation study conducted with
patients with CAD referred to CR, who either had not yet initiated CR or were in their first week
of the program (N = 307), provide good evidence for the CADE-Q II’s reliability and validity (de
Melo Ghisi et al., 2015b). In this validation work, approximately half of participants
demonstrated initial CAD knowledge ≥ 75% (≥ 70/93 points). Greater scores on the CADE Q-II
are significantly associated with higher previous educational attainment across samples,
providing evidence for the questionnaire’s criterion validity, p’s < .001 (de Melo Ghisi et al.,
2015b; Chen et al., 2018; Ranjbar et al., 2018; Santos et al., 2018). Further, patients with CAD
(N = 306) achieved significant increases in CADE-Q II total scores from pre- to post-CR (de
Melo Ghisi et al., 2015a; 2015c), suggesting the measure effectively captures educational content
delivered during CR. The CADE Q-II has good internal consistency overall (Cronbach’s alpha =
0.91) and acceptable α’s for each of the five subscales (0.65-0.77). Exploratory factor analysis
revealed four factors (Medical Condition, Risk Factors/Exercise, Nutrition, and Psychosocial
Risk) explaining 62.2% of variance (loadings = 0.40 - 0.64; de Melo Ghisi et al., 2015b).
Secondary outcomes.
CR Attitudes. Attitudes regarding CR were assessed using the Beliefs About Cardiac
Rehabilitation (BACR) Scales, a 13-item self-report questionnaire assessing perceived necessity
of CR, perceived suitability, concerns about exercise, and practical barriers to CR (Cooper,
Weinman, Hankins, Jackson, & Horne, 2007). Patients rate agreement with statements on a 5-
point Likert-scale where 1 = Strongly Disagree and 5 = Strongly Agree. The perceived necessity
subscale is positively coded (potential score range = 5-25) where high scores correspond to more
favourable perceptions of personal need for a CR program. Lower scores on the perceived
16
suitability (range = 2-10), exercise concerns (range = 3-15), and practical barriers (range = 3-15)
subscales correspond to more favourable attitudes in each respective domain. BACR subscales
have demonstrated good internal consistency (alpha = .70 to .79) and have established predictive
validity for CR exercise attendance (i.e., 65% of variance in CR attendance explained)(Cooper et
al., 2007).
Exercise Attendance. CR exercise attendance is defined as the total number of supervised
exercise sessions attended (of a possible 24) and was determined by chart review upon program
completion approximately 12-weeks post-TCHH. As part of standard care, attendance at each
exercise session is recorded in patients’ electronic medical charts by TCR staff in real-time upon
patients’ arrival and check-in. Home program participants were excluded from these secondary
analyses because they are not required to attend supervised exercise sessions.
Exploratory outcomes.
Intentions to attend CR. Patients’ self-reported intention to attend CR exercise was
evaluated using the average of two items adapted from Blanchard et al. (2002). Patients respond
to the questions: (1) “My goal is to attend ___ exercise classes at cardiac rehabilitation” with
responses ranging from 1 (some exercise classes) to 7 (all exercise classes), and (2) “I intend to
attend my scheduled exercise classes during my rehabilitation program” with responses ranging
from 1 (Strongly Disagree) to 7 (Strongly Agree). Higher intention strength measured using
these items is associated with better CR attendance in prior research (Blanchard et al., 2003;
Blanchard, Courneya, Rodgers, Daub, & Knapik, 2002; Rouleau et al., 2018; Williamson et al.,
2018).
Heath behaviour intentions (HBI). Patients’ intentions to change health behaviours that are
addressed as part of CR (e.g., reduce saturated fat/sodium intake, drink less alcohol, quit
17
smoking) were assessed using a questionnaire adapted from Renner and Schwarzer (2005).
Patients rate the strength of their intentions to engage in heart-healthy behaviours (1= do not
intend, 7 = strongly intend). A “Not Applicable” option is also available. Intention strength is
averaged across items (excluding N/A responses) to provide a total score ranging from 1 to 7,
with higher scores representing a greater overall intention to engage in heart-healthy behaviours.
Prominent theories of health behaviour change (e.g., the Theory of Planned Behaviour, HAPA)
posit intention as a proximal determinant of future health behaviours, including smoking
cessation, exercise, and adhering to a healthy diet (Ajzen, 1991; Schwarzer et al., 2011).
Leisure-Time Exercise. Minutes of exercise (outside of scheduled CR sessions) was
measured with the Godin-Shepard Leisure-Time Exercise questionnaire (GSLTEQ; Godin,
2011). Patients rate how many times/week they engage in strenuous, moderate, and mild physical
activity for a time-period of 15 minutes or more to provide an estimate of total minutes of
physical activity per week. The GSLTEQ has been used extensively to asses physical activity in
various populations, and has good evidence for its convergent validity (e.g., associations with
cardiorespiratory fitness, body fat percentage, and fitness center attendance) and test-retest
reliability (e.g., Cohen’s kappa = 0.65 and 1.45 for 15- and 30-day re-tests, respectively;
Amireault & Godin, 2015).
(pre-TCHH) to ascertain sex, marital status, employment status, education, ethnic background,
current medications, travel time to CR, physician recommendation strength, and health literacy.
Strength of physician recommendation. One item was administered asking patients to rate
how strongly their physician recommended they attend CR on a 5-Point Likert-scale with the
stem “My Doctor…” (1 = did not recommend I participate in CR, 3 = gave a moderate
18
recommendation I participate in CR, 5 = gave a strong recommendation I participate in CR).
Prior research demonstrates that physician recommendation strength is associated with CR
enrollment and attendance (Grace et al., 2014).
Health literacy. The Medical Term Recognition Test (METER) is a brief (two-minute) self-
report instrument where patients are asked to distinguish real medical terms and words from
distractors (non-words)(Rawson et al., 2010). Correct word identifications are summed and
incorrect items subtracted from the total correct to provide the patient’s overall score out of 40
(Rawson et al., 2010). Health literacy assessed using the METER correlates significantly to
cardiac-related knowledge assessed pre- and post-CR in prior research (Mattson, Rawson,
Hughes, Waechter, & Rosneck, 2015).
Cardiovascular risk factors. TCR staff assess and record cardiac risk factors
(cardiorespiratory fitness [peak metabolic equivalents; METS], smoking status, blood pressure,
lipid profile, body mass index, symptoms of anxiety/depression) in patients’ electronic medical
records at intake (pre-TCHH) and during the 12-week follow-up appointment. Changes in risk
factors were assessed by comparing risk factors at baseline to 12-weeks through chart review.
Procedures
After attending their initial CR orientation appointment, patients were invited by a TCR
administrative staff member to enroll in the CR program and register for TCHH. Patients who
registered for TCHH and met study inclusion criteria were invited to participate in the study (see
Appendix C for detailed recruitment procedures). Patients were instructed on how to complete
the baseline study questionnaire battery prior to attending their first TCHH class, either on-paper
or electronically via Qualtrics XM Survey software (Qualtrics, 2019). The patient assessment
schedule is presented in Appendix B. Within three days of their final TCHH class, patients were
19
instructed to complete repeated measures of CAD knowledge, CR attitudes, intentions, and
leisure-time exercise (T2). Post-TCHH measures were completed for a third and final time 12-
weeks following TCHH (T3). Patients may or may not have completed all 24 CR exercise
sessions when completing the T3 questionnaires. CR exercise attendance (# of sessions out of
24) and changes in cardiovascular risk factors were determined by chart-review following
completion of the CR program.
Data Analysis
Primary and secondary analyses. All analyses were conducted using SPSS statistical
software version 25 (IBM Corp., 2016). Independent t-tests and Chi-square differences tests
were performed to assess differences in baseline characteristics of patients who completed the
study vs. those who were lost to follow up. To evaluate the primary hypothesis that TCHH would
be associated with an increase in CAD knowledge, a repeated-measures analysis of covariance
(RM ANCOVA) was performed with Time as the independent variable (IV; T1, T2, T3), and
CADE-Q II scores as the dependent variable (DV). Years of education was included as a
covariate. Within-subject contrasts were performed and statistical significance was evaluated at a
Bonferroni-corrected alpha = .05/2 = .025.
Secondary hypotheses were tested as follows. To evaluate the prediction that TCHH
would be associated with an increase in favourable CR attitudes, a series of RM ANOVAs were
performed with Time as the IV and BACR subscale scores as the DVs. Statistical significance
was evaluated at a Bonferroni-corrected alpha = .05/4 =.013. To evaluate the association
between CAD knowledge gains and improvements in CR attitudes, difference scores (T2 – T1)
were calculated for CADE-Q II and BACR subscale scores. Linear regression models were
estimated with Δ CADE-Q II as the IV, and Δ BACR subscale scores as the DV; baseline (T1)
20
CADE-Q II and BACR subscale scores were entered as covariates to adjust for potential
regression to the mean. Significance was evaluated at Bonferroni-corrected alpha = .05/4 = .013.
Finally, to evaluate the association between knowledge gains and CR exercise attendance, a
linear regression model was estimated with Δ CADE-Q II as the IV, and number of CR exercise
sessions attended as the DV; baseline CADE-Q II scores, years of education, and sex were
entered as covariates in Step 1.
Post-hoc and exploratory analyses. To examine the impact of TCHH on CAD
knowledge among patients with high- vs. low disease-related knowledge at program entry, the
sample was dichotomized into low (≤ 75%, ≤ 70/93; N = 33) vs. high (>75%, > 70/93; N = 38)
initial knowledge. This cut-point represented the median CADE-Q II score for the full sample
and was consistent with cut-points distinguishing high vs. low CAD knowledge used in previous
research (de Melo Ghisi et al., 2015c; Ranjbar et al., 2018). A mixed ANCOVA was performed
with initial knowledge (Low, High) as the between-subjects factor, and time as the within-
subjects factor; CADE-Q II scores were entered as DV and years of education was included as a
covariate.
Differences among individual knowledge domains at baseline were examined by
converting T1 raw CADE-Q II subscale scores to a mean percentage (out of 100). A one-way
within-subjects ANOVA was performed to examine differences in CADE-Q II domain scores at
baseline. Improvements in individual knowledge domains pre- to post-TCHH were explored by
performing a series of RM ANCOVAs (Time × CADE-Q II domain score); statistical
significance was evaluated at a Bonferroni-adjusted alpha = .05/5 = .010). The impact of TCHH
on HBI and intention to attend CR was evaluated using RM ANOVAs.
21
Residualized change scores were computed for T1 to T3 changes in CAD knowledge and
cardiac risk factors and bivariate correlations performed to examine whether larger knowledge
gains correlated with greater improvements in risk factors. Finally, to explore relative importance
of all potential TCHH treatment targets to predicting CR exercise attendance, a multiple
regression model was estimated with baseline values of total CAD knowledge, behavioural
intentions, and BACR subscales as simultaneous predictors, and exercise attendance as the DV.
Bivariate correlations were examined among CADE-Q II individual subscales at baseline, and
CR exercise attendance. The latter three analyses were performed using the full sample (i.e.,
completers and non-completers).
A visual examination of GSLTEQ questionnaire responses suggested that a large
proportion of the respondents misinterpreted questionnaire instructions for reporting leisure-time
exercise. Therefore, results on this measure were considered unreliable and excluded from
analyses. All data were checked for normality, outliers, and statistical assumptions according to
the analyses performed. Extreme values which represented true variability in the sample were
retained in analyses. Missing data on the primary and secondary outcomes (CADE-Q II and
BACR scale scores; < 5%) were imputed using scale/subscale mean scores.
Results
A patient flow diagram is presented in Figure 1. A total of 103 patients were recruited
(i.e., signed the consent form). The participant retention rate was 69%. Primary and secondary
analyses were conducted with patients who completed the study (N = 71).
Sample Characteristics
exploratory variables, including statistical difference tests comparing study completers vs. non-
22
completers, are presented in Table 1. The final sample was predominantly male (87.3%),
educated (75% with post-secondary education), White (82%), and co-habiting in a partner
relationship (68%). Relative to previous work in similar CR populations (e.g., de Melo Ghisi et
al., 2015b; Cooper et al., 2007), baseline CAD knowledge was average (M = 69.40/93.00, SD =
13.28; approximately 75% knowledge) and CR attitudes were more favourable (e.g., mean
perceived necessity for CR = 20.24/25.00 [SD = 2.88], vs. 17.69 [SD = 2.82] reported in
validation work by Cooper et al., 2007). Relative to non-completers, patients who completed the
study tended to be older (61.11 years [SD = 10.03] vs. 56.34 years [SD = 10.57] years,
respectively), reported stronger initial intention to attend CR exercise sessions (M [SD] =
6.66/7.00 [0.79] vs. 5.90/7.00 [1.40]), reported fewer practical barriers to CR participation
(5.17/15.00 [2.73] vs. 6.82/15.00 [3.46]), and attended more CR exercise sessions (20.31/24.00
[4.97] vs. 9.15/24.00 [9.24]).
Association between TCHH and CAD knowledge. RM ANCOVA analyses performed
to evaluate the primary study aims revealed an effect of Time on overall CAD knowledge,
F(1.56, 107.69) = 4.27, p = .025, p 2 = .06, refer to Table 2. Within-subjects contrasts showed an
increase in CAD knowledge from pre-TCHH (M = 69.41/93.00, SD = 13.48) to post-TCHH (M =
77.87/93.00, SD = 8.01), F(1,69) = 5.45, p = .022, p 2 = .07, representing a small-to-medium
effect size (Cohen, 1988; Lakens, 2013). CAD knowledge gains were maintained 12 weeks later
as indicated by a non-significant T2 vs. T3 contrast (MT3 = 78.49, SD = 8.37; F(1, 69) = .07, p =
.788, p 2 < .01).
Post-hoc RM ANCOVAs of CADE-Q II subscale scores indicated no change in
individual knowledge domains over time, while adjusting for years of education (p’s > .05); refer
23
to Table 2 and Figure D1 (Appendix D). Within-subjects ANOVA of baseline domain scores
indicated that at least one knowledge domain differed significantly from the others, F(4, 280) =
9.20, p < .001, p 2 = .12. This was followed up with a series of nine paired t-tests, with a
Bonferroni-adjusted alpha value = .05/9 = .006. Initial knowledge was greatest in the Exercise,
Medical Condition, and Psychosocial Risk domains, which did not differ from each other, p’s >
.05. The lowest initial knowledge scores were observed in the Nutrition and Risk Factors
domains (means did not differ, p = .592), refer to Figure D1 (Appendix D).
Secondary Objectives
Association between TCHH and CR attitudes. Results of the RM ANOVAs evaluating
the impact of TCHH on BACR subscales are presented in Table 2. On average, patients
perceived CR as more necessary after attending TCHH, and these improved attitudes were
maintained at 12-week follow up, F(2,140) = 15.94, p < .001, p 2 = .19. Improvements in other
CR attitudes were not statistically significant, p’s > .013.
Association between changes in knowledge and changes in CR attitudes. Linear
regression models showed that improvements in CAD knowledge were not associated with
improvements in CR attitudes while statistically adjusting for baseline CAD knowledge, baseline
CR attitudes, and years of education, p’s > .05, refer to Table 3.
Association between changes in knowledge and CR exercise attendance. A linear
regression indicated that improvements in CAD knowledge were not associated with CR exercise
attendance while statistically adjusting for baseline (T1) knowledge, years of education, and sex,
F(1,46) = .16, p = .695, R2 = .003, refer to Table 4.
Post-Hoc and Exploratory Outcomes
Influence of TCHH among patients with low vs. high initial knowledge. Results of a
24
post-hoc mixed ANCOVA showed a Time × Baseline Knowledge interaction, F (1.78, 120.95) =
26.23, p < .001, p2 = .28, refer to Table D1 and Figure D2, Appendix D. Within-subjects
contrasts indicated a greater increase in CAD knowledge scores (T1 to T3) among patients with
low initial knowledge, (i.e., MT1 = 58.15, SD = 11.55 vs. MT3 = 73.91, SD = 8.93), relative to
those with high baseline knowledge (MT1 = 79.18, SD = 4.16 vs. MT3 = 82.47, SD = 5.37),
F(1,68) = 36.24, p < .001, p2 = .34.
Influence of TCHH on behavioural intentions. Overall intentions to engage in health
practices increased from pre- (M = 6.48/7.00, SD = .62) to post- (M = 6.64, SD = .45) TCHH, F
(1, 70) = 7.47, p2 = .10, p = .008; however, at 12-week follow-up, HBI returned to pre-TCHH
levels (M = 6.45, SD = .54), F (1, 70) = 13.49, p < .001. No difference was observed in intention
to attend CR sessions from pre- (M = 6.66/7.00, SD = .79) to post- (M = 6.43/7.00, SD = 1.15)
TCHH, F (1, 70) = 3.58, p2 = .05, p = .063. Further, linear regression indicated that changes in
CAD knowledge were not associated with greater improvements in in HBI or intention to attend
CR from T1 to T2 (b’s < .01, p’s > .05).
Additional exploratory outcomes. Bivariate correlations among changes in CAD
knowledge and cardiac risk factors are presented in Table D2 (Appendix D). A multiple
regression model with baseline values of treatment targets entered as simultaneous IVs predicted
greater CR exercise attendance, F(7, 65) = 3.30, adjusted R2 = .18, p = .005, refer to Table D3
(Appendix D). This result was driven by the unique influence of stronger initial intentions to
attend CR. Namely, each one-point increase in intention to attend CR corresponded to nearly
four additional exercise sessions attended (SE = .98, p < .001). No correlations were observed
between initial scores on CADE-Q II knowledge domain subscales and CR exercise attendance.
25
Discussion
Participation in CR is considered the standard of care for most patients with CAD, yet
little is known about the effect of patient education on program exercise attendance. This study
helped address this important topic by providing early-phase data regarding the influence of a
CR-based patient education curriculum on knowledge about CAD, attitudes toward CR,
behavioural intentions, and CR exercise attendance among patients following an ACS event. As
hypothesized, patients who participated in the four-part TCHH curriculum prior to starting a CR
program showed improvements in their general disease-related knowledge, with gains
maintained at 12-weeks. This finding is consistent with systematic reviews indicating that patient
education improves knowledge among patients with CAD (de Melo Ghisi et al., 2014). CAD
knowledge scores increased by approximately 13 percent, representing a small-to-medium-sized
effect according to published conventions (Cohen, 1988; Hunter & Schmidt, 1990). Diversity in
methodology and statistical reporting in previous studies of educational interventions for CAD
knowledge makes it challenging to compare treatment effects across studies. For example,
randomized designs comparing education to usual care (e.g., unstructured CAD education,
handouts/verbal instruction) have reported small treatment effects (Buckley et al., 2006; Elderen,
Maes, Seegers, Kragten, & Wely, 1994; McKinley et al., 2009; Meng et al., 2014), whereas some
observational studies report larger effects (e.g., de Melo Ghisi et al., 2015a). Results of the
present research suggest TCHH patient education can produce small-to-moderate changes in
knowledge that are relatively consistent with those observed in similar programs for patients
with CAD.
Whereas patients reported an overall increase in their disease-related knowledge after
attending TCHH, no improvements were observed in individual CAD knowledge domains. This
26
suggests that the additive result of modest gains across subscales led to overall improvement on
total CADE-Q II scores. A positive implication of this finding is that knowledge delivery in
TCHH appears consistent across core content areas, rather than overall knowledge improvements
being driven by large gains in one or two discrete domains. Further, the observation that CAD
knowledge gains were greater among patients who entered the program with lower initial
disease-related knowledge relative to those with high baseline knowledge has implications for
education delivery in CR. Whereas a multi-session, classroom-based intervention delivered by
health professionals (similar to TCHH) may benefit individuals with lower knowledge upon CR
referral, this resource-intensive approach may be excessive for patients who already understand
their disease and how to manage it. There may be advantages to assessing information needs and
knowledge gaps at program outset to tailor education programs to individual requirements.
Providing less-intensive resources such as written or e-learning materials may be sufficient to
support patients with high baseline knowledge as they navigate their cardiovascular recovery.
The prediction that TCHH would be associated with improvements in CR attitudes was
partially supported. Patients’ perceived necessity of CR improved post-TCHH, consistent with
prior research demonstrating that psychoeducational interventions have potential to enhance
beliefs and attitudes about behaviour change (de Melo Ghisi et al., 2015a). For example, a
single-session, nurse-delivered educational intervention improved attitudes, beliefs, and self-
efficacy regarding seeking treatment for an ACS event among 3,522 patients with CAD, relative
to usual-care controls (McKinley et al., 2009).
No improvements were observed in terms of patients’ exercise concerns, practical barriers,
or perceived suitability for CR. In the present sample, initial concerns in these domains were low
(e.g., perceived suitability average score = 3/10, range = 2-10), therefore floor effects may have
27
prevented the detection of improvements associated with the intervention. Alternatively, whereas
TCHH may be effective at improving perceptions of CR necessity by, for example, conveying
information about benefits of exercise attendance on modifiable risk factors, TCHH may be less
helpful for troubleshooting practical barriers to attendance (e.g., work constraints, transportation,
cost) and allaying concerns about exercise (e.g., worries that exercise may be harmful).
Addressing barriers and concerns of this nature within CR education programs may be more
important to enhancing CR attitudes, and ultimately, promoting CR exercise attendance than
simply conveying information about CAD and its management. For example, observational
research among patients with CAD demonstrates that greater perceived obstacles to CR
participation in terms of work/time constraints, logistical problems, and comorbidities are
associated with lower CR program enrolment and poorer exercise session attendance
(Shanmugasegaram et al., 2012; Williamson et al., 2018). Introducing TCHH content to help
patients identify and mitigate potential CR barriers may be important to enhancing this
intervention’s effect in future work. For example, providing more comprehensive information
about how to exercise safely from home, and e-learning alternatives to centre-based TCHH
programming may help alleviate CR barriers and promote health behaviour uptake.
Consistent with best practices for intervention design (Czajkowski et al., 2015), this study
sought to characterize clinically-relevant treatment targets and examine potential mechanisms
through which improvements in motivational variables may impact on CR exercise behaviour.
The secondary hypotheses that CAD knowledge gains would be positively associated with (a)
improvements in CR attitudes, and (b) better CR exercise attendance, were not supported. There
are several potential explanations, methodological and theoretical, for this finding. For example,
the utilization of difference scores (T2 minus T1) as IVs and DVs in linear regression models
28
may have increased measurement error, reducing power to detect significant effects (Castro-
Schilo & Grimm, 2018). Further, previous research suggests that greater knowledge may
influence health behaviour indirectly via key motivational variables (e.g., positive beliefs, self-
efficacy). For example, cross-sectional and longitudinal studies in adult, community samples
indicate that associations between diet- and exercise-related knowledge and target health
behaviour (healthy eating, exercise) are greater among individuals with higher self-efficacy (i.e.,
confidence in one’s ability to exercise personal control over exercise/eating habits)(Rimal, 2000,
2001). Evaluating a potential mediating role of CR attitudes and/or self-efficacy on the CAD
knowledge-CR exercise relationship may have helped to clarify mechanisms-of-change in
TCHH. Finally, mean CAD knowledge gains were modest (i.e, 8.46/93 points, translating to ‘full
knowledge’ on an additional three test items), and initial intentions to attend CR (i.e., M =
6.70/7.00) and CR attendance (i.e., 85% adherence) were high. These ceiling effects may have
further limited power to detect a significant association between knowledge gains and improved
intention/attitudes/exercise attendance.
knowledge alone is insufficient to influencing CR exercise attendance. Imparting knowledge
about chronic disease management is typically considered an important first-step to supporting
patients in implementing heart-healthy behaviours (Michie et al., 2011; de Melo Ghisi et al.,
2014). Yet, research exploring associations between improved health-related knowledge and
concurrent and/or subsequent health behaviour across domains is equivocal, with most studies
reporting weak or no relationships (Ajzen, Joyce, Sheikh, & Cote, 2011; Kelly & Barker, 2016;
Rimal, 2001; Ross & Melzer, 2016). For example, a longitudinal study in a large (N = 1,410)
community sample reports that, while baseline knowledge about exercise (e.g., influence of
29
initial exercise behaviour, improvements in knowledge over a 2-year follow-up period were not
associated with increased exercise (Rimal, 2001). One potential explanation for the weak
empirical associations between knowledge and behaviour is that the type of knowledge assessed
on conventional health information tests (e.g., the CADE-Q II; assesses awareness of cardiac risk
factors, managing stress, taking medications correctly, etc.) may not clearly relate to target
behavioural outcomes (e.g., attendance at CR exercise sessions)(Ajzen et al., 2011). Other
unmeasured, active components of TCHH, such as facilitating social support from fellow
patients (Cooper, Jackson, Weinman, & Horne, 2002; Michie et al., 2013) or imparting practical
knowledge that assists in reducing barriers to CR attendance (e.g., learning about fee
subsidization and the TCR home program)(Grace et al., 2008), may be more beneficial for
enhancing CR-related attitudes/beliefs and, ultimately, promoting exercise attendance.
The exploratory findings regarding the relative importance of target motivational variables
in predicting CR exercise attendance further highlight the inconsistent role of knowledge in
predicting exercise behaviour, and contribute to a growing literature demonstrating the
importance of behavioural intentions in predicting actual CR exercise attendance. In this sample,
intention to attend CR exercise at program outset explained 17% of variance in exercise
attendance. This aligns with prior observational research indicating that behavioural intentions
are strong, proximal determinants of subsequent exercise behaviour among CR patients
(Blanchard et al., 2002; Sniehotta et al., 2005a, 2005b; Williamson et al., 2018). Conversely,
neither CAD knowledge nor CR attitudes assessed at baseline predicted increased exercise
attendance. Ceiling/floor effects may have contributed to this result in terms of the BACR
subscales. CAD knowledge, however, may be a less relevant treatment target for educational
30
interventions relative to behavioural intentions and CR attitudes. Of note, whereas CAD patients
typically report “strong” intentions to participate in CR exercise at program outset (i.e., 80-88%
intention strength; Sniehotta et al., 2005a; Blanchard et al., 2002; Williamson et al., 2018),
favourable beliefs and self-efficacy are necessary to supporting the translation of intentions into
actual health behaviour change (Schwarzer et al., 2011; Schwarzer et al., 2008). Thus, ensuring
that both patients’ intentions to attend CR, and attitudes and beliefs about the program, are
targeted in educational interventions may be important to producing clinically-relevant
improvements in CR exercise.
Implications for Intervention Development
Current TCHH programming is consistent with several recommendations for optimal
cardiac patient education delivery described in systematic reviews (e.g., core content areas
covered by TCHH, facilitation by a multidisciplinary team)(Friedman et al., 2011; Liu et al.,
2017). A recent umbrella review of systematic reviews of education for patients post-ACS event,
however, indicates that interventions designed using behaviour change theory (e.g., social
cognitive theory [Bandura, 2010]; HAPA [Schwarzer et al., 2008, 2011]) and incorporating at
least three evidence-based behaviour change techniques (e.g., goal setting, self-monitoring,
feedback; see Michie et al., 2009, 2013) achieve the greatest improvements in behavioural
outcomes such as exercise and smoking cessation (Liu et al., 2017). Whereas TCHH provides
basic information about goal-setting (e.g., setting ‘SMART’ goals) and recommends self-
monitoring via the use of an exercise log-book, the program may lack sufficient instruction,
follow-up, and feedback on patients’ use of these strategies to produce optimal results.
Further, the present findings suggest that patients’ attitudes and intentions regarding CR
may be more relevant motivational targets in patient education, relative to CAD knowledge.
31
Patients could feasibly attend all of their prescribed CR exercise sessions regardless of their level
of accurate CAD-related knowledge (Ajzen et al., 2011), whereas they are less likely to engage
in CR exercise if they: (a) do not actually intend to do so, and/or (b) do not believe exercise
would be suitable or helpful to their cardiovascular recovery. Incorporating motivational
communication strategies to resolve patients’ ambivalence about behaviour change (e.g.,
motivational interviewing; Miller & Rollnick, 1991) is one potential way TCHH may help target
intentions to attend CR and CR-related attitudes. For example, a brief (one, hour-long session)
motivational interviewing intervention (i.e., patient-centered, collaborative counselling to resolve
ambivalence regarding behaviour change) delivered following TCR referral was demonstrated to
enhance patients’ intentions to attend CR, promote more favourable CR attitudes, and increase
CR exercise attendance, relative to usual-care controls (Rouleau et al., 2018). Whereas TCHH
facilitators currently receive some communication skills training from the program psychologist
(C.R.), more comprehensive and/or individualized motivational counselling approaches may be
warranted to optimize TCHH outcomes.
Finally, in terms of treatment dose and format, Liu et al. (2017) recommend providing > 30
minutes/week of education, for at least 6 months, with 12-months of patient follow-up, using a
multi-modal delivery format (i.e., a combination of online/web-based, face-to-face, and phone-
based learning). TCHH may be further improved by spacing education delivery over a longer
period, introducing web-based and/or telephone follow-up components, and incorporating more
comprehensive motivational strategies into the curriculum over an increased follow-up period.
Limitations
The results should be interpreted in the context of the following limitations. First, owing to
the observational study design, it is impossible to determine whether changes in knowledge and
32
CR attitudes were caused by the TCHH intervention. TCHH concepts are actively reinforced
throughout the CR program through health coaching with TCR staff, and informally through
medical appointments. These unstructured educational experiences may have promoted
knowledge acquisition and/or retention in this sample. Second, only a small proportion of
potentially eligible patients were screened for eligibility, and one-third of the sample was
excluded from analyses for non-completion. The final sample predominantly consisted of
educated, White men, with high initial knowledge about CAD and strong intention to attend CR
exercise. Findings regarding the role of patient education in CR may therefore not translate to
underrepresented patient groups (women, ethnic minorities, patients of low socio-economic
status). Third, it was not possible to analyse whether number of TCHH classes attended
influenced results because class participation was not reliably documented by clinical staff
during the study. Whereas the full two-day TCHH curriculum is typically completed within a
single week, patients may leave mid-class or fail to present for the second day. Finally, the utility
of the CADE-Q II to accurately estimate patients’ CAD knowledge and predict CR outcomes
(exercise attendance, risk factor changes) may be limited. For example, it was likely possible for
patients to make ‘educated guesses’ on the CADE-Q II, given that full-point responses were
typically the most comprehensive choice available. This may have led to an overestimation of
some patients’ knowledge, contributing to observed ceiling effects. Further, the predictive
validity of CADE-Q II has not been established in prior validation work (e.g., de Melo Ghisi et
al., 2015b). More studies may be needed to develop and refine CAD knowledge tests with good
predictive ability for CR outcomes, and with sensitivity and specificity to distinguish patients
with greater information needs from those with good baseline knowledge at program entry.
Conclusions and Future Directions
33
Improving CAD outcomes following an ACS event requires patients to implement and
maintain a complex behavioural change regimen, including taking their medications correctly,
proper nutrition, stress management, and critically, regular attendance at CR exercise sessions.
Patient education interventions are therefore essential to (1) provide adequate, correct disease-
related information, including how to properly engage in CAD self-management behaviours, and
(2) enhance patients’ intentions and attitudes (beliefs, self-efficacy) about participating in CAD
tertiary prevention programs such as CR. Evidence supporting a link from a behavioural
treatment to a behavioural risk factor (e.g., lack of exercise participation) suggests an
intervention effect is large enough to induce a clinically-relevant change on the risk factor,
thereby justifying time and resources required to proceed to pilot testing (Czajkowski et al.,
2015). This study indicates the TCHH curriculum favourably influences three treatment targets
(knowledge, attitudes, and intention), however improvements in these constructs alone were not
powerful enough to impact CR exercise attendance.
Future work to refine the intervention and study methodology is required to sufficiently
demonstrate proof of concept prior to pilot testing TCHH in randomized designs. For example,
TCHH programming could be modified to include greater emphasis on evidence-based
behaviour change strategies such as goal-setting and self-monitoring, with appropriate follow-up
and feedback, to enhance the size of the treatment effect (Czajkowski et al., 2015; Liu et al.,
2017; Michie et al., 2013). Additional potential treatment targets (e.g., reducing CR barriers,
increasing social support) should be measured and explored as candidate mechanisms-of-change
that may influence CR exercise attendance. Finally, efforts are needed to recruit more
representative populations of patients with CAD referred to CR, including women, ethnic
minorities, and patients of lower socio-economic status, in future patient education studies.
34
group differences at baseline (pre-TCHH).
Variable (Baseline, pre-TCHH)
Group Differences Test
t or χ2 (df) p
Age (Years), M (SD) 61.11 (10.03) 56.34 (10.57) t(101) = 2.20 .030
Sex, N (%) χ2 (1) = .001 .980
Male 62 (87.3) 28 (87.5)
Female 9 (12.7) 4 (12.5)
Years of Education, M (SD) 14.56 (3.20) 13.77 (2.73), N = 26 t(95) = 1.12 .264
Travel Time to CR (minutes), M (SD) 40.08 (18.28) 49.21 (31.05), N =
26
t(31.57) = -
1.41
.168
4.47 (.98) 4.11 (1.25), N = 27 t(96) = 1.53 .129
Health Literacy (METER), M (SD) 35.52 (3.56) 33.42 (4.09), N = 26 t(34.47) =
1.93
.061
(SD)
2.61 .014
CAD Knowledge (CADEQ-II), M
26
BACR Scales, M (SD)
Perceived Necessity 20.24 (2.88) 20.30 (2.64), N = 26 t (95) = -.10 .924
Exercise Concerns 5.42 (2.81) 5.72 (2.41), N = 26 t (95) = -.47 .921
Practical Barriers 5.17 (2.73) 6.82 (3.46), N = 26 t (95) = -2.42 .018
Perceived Suitability 3.10 (1.73) 3.72 (2.07), N = 26 t (95) = -1.47 .145
CR Exercise Attendance (of 24; HP
excluded), M (SD)
20.31 (4.97) N
5.77 <
.001
High (> 75%) 38 (53.5) 16 (50)
Low (≤ 75 %) 33 (46.5) 16 (50)
(Continued)
35
Marital Status, N (%)
χ2 (3) = 4.31
Co-habitating 48 (67.6) 14 (43.8)
Separated/Divorced 11 (15.5) 7 (21.9)
Widowed 6 (8.5) 1 (3.1)
Missing 0 5 (15.6)
Full-Time 31 (43.7) 16 (50)
Part-Time 6 (8.5) 0
Missing 0 5 (15.6)
Highschool 14 (19.7) 7 (21.9)
Trade 12 (16.9) 7 (21.9)
Community College 12 (16.9) 2 (6.3)
Bachelors Degree 15 (21.1) 4 (12.5)
Graduate Degree 4 (5.6) 2 (6.3)
Other 7 (9.9) 2 (6.3)
Missing 2 (2.8) 5 (15.6)
Annual Household Income, N (%) χ2(7) = 4.55 .714
< 20,000 5 (7) 2 (6.3)
20-40,000 7 (9.8) 6 (18.7)
40-60,000 11 (15.5) 5 (15.6)
60-80,000 10 (14.1) 3 (9.4)
80-100,000 5 (7) 1 (3.1)
>100,000 26 (36.6) 8 (25)
Prefer not to say 7 (9.9) 2 (6.3)
Missing 0 5 (15.6)
Asian 9 (12.7) 4 (12.5)
Black 2 (2.8) 0
Multiple Ethnicities/Other 2 (2.8) 3 (9.4)
Missing
t or χ2 (df) p
Born in Canada, N (%) 53 (74.6) 18 (56.3) χ2 (1) = .624 .429
Missing 0 5 (15.6)
STEMI 25 (35.2) 21 (65.6)
NSTEMI 17 (23.9) 5 (15.6)
Unstable Angina 7 (9.9) 0 (0)
Ischemic Heart Disease 16 (22.5) 5 (15.6)
Other 6 (8.4) 1 (3.1)
Smoking Status χ2 (3) = 6.15 .105
Never Smoked 38 (53.5) 12 (37.5)
Quit > 6 months ago 27 (38) 9 (28.1)
Quit < 6 months ago 3 (4.2) 5 (15.6)
Still Smoking 2 (2.8) 2 (6.3)
Missing 1 (1.4) 4 (12.5)
Cardiac Risk Factors, M (SD)
Total Cholesterol (N’s = 65, 27) 4.31 (1.26) 4.81 (1.12) t (90) = -1.81 .074
HDL 1.10 (.27) 1.10 (.26) t (90) = .002 .998
LDL 2.44 (1.10) 2.98 (.95) t (89) = -2.20 .030
EST Results (N’s = 70, 28)
Resting systolic blood pressure 113.20 (14.91) 109.21 (12.26) t (96) = 1.25 .213
Resting diastolic blood pressure 70.37 (9.15) 70.29 (7.79) t (96) = .04 .965
Resting heart rate 72.03 (13.17) 69.64 (12.97) t (96) = .81 .418
Peak EST heart rate 131.44 (22.76) 124.68 (15.45) t (72.75) =
1.70
.094
Peak METS 7.59 (2.13) 7.75 (1.86) t (96) = -.34 .736
BMI (kg/m2) 29.28 (5.09) 30.31 (7.40) t (96) = -.80 .429
Waist circumference 103.55 (14.41) 104.93 (15.31) t (96) = -.42 .676
HADS scores (N’s = 60, 23)
Anxiety 5.67 (3.03) 5.39 (3.24) t (81) = .36 .717
Depression 3.27 (2.89) 2.70 (2.69) t (81) = .82 .414
Note. aStudy non-completers signed the consent form but did not complete one or more of the
assessments (T1, T2, and/or T3). BACR = Beliefs about Cardiac Rehabilitation Scales (Cooper
et al.. 2007); BMI = body mass index; CAD = coronary artery disease; CADE-Q II = Coronary
Artery Disease Education Questionnaire, Version II (de Melo Ghisi et al., 2015); CR = cardiac
rehabilitation; EST = Exercise Stress Test; HADS = Hospital Anxiety and Depression Scales
(Zigmond & Snaith, 1983); HDL = high-density lipoprotein; HP = TotalCardiology Home
Program; LDL = low-density lipoprotein; METS = metabolic equivalents; NSTEMI = Non-ST-
elevation myocardial infarction; STEMI = ST-Elevation Myocardial Infarction; TCHH = Taking
Charge of your Hearth Health patient education intervention.
37
Table 2.
CAD Knowledge Total Scores, Domain Scores, and CR Attitudes Pre-TCHH, Post-TCHH and at 12-week follow-up (N = 71)
Outcome Measure, M (SD)
Pre-TCHH Post-TCHH 12-weeks
aCADE-Q II Total Score (of 93) 69.41 (13.48) 77.87 (8.01) 78.49 (8.38) 1.56, 107.69 4.27 .025 .06
aMedical Condition (of 21) 16.15 (3.00) 18.20 (2.87) 18.15 (3.11) 1.83, 126.21 .71 .478 .01
aRisk Factors (of 15) 10.48 (3.23) 11.80 (1.64) 11.76 (1.80) 1.63, 112.34 3.20 .055 .04
aExercise (of 21) 16.99 (4.57) 18.77 (2.39) 19.32 (2.05) 1.42, 98.03 1.59 .214 .02
aNutrition (of 21) 14.37 (3.84) 16.58 (3.14) 16.70 (2.84) 1.81, 124.62 2.27 .113 .03
aPsychosocial (of 15) 11.42 (3.05) 12.52 (2.20) 12.55 (2.35) 1.77, 122.21 2.05 .133 .03
BACR Subscales
greater perceived necessity)
20.24 (2.88) 21.69 (2.70) 21.99 (2.60) 2, 140 15.94 < .001 .19
Concerns about Exercise (range = 3-15;
lower scores = fewer concerns)
5.42 (2.81) 4.93 (2.60) 4.70 (2.08) 2,140 2.71 .070 .04
Practical Barriers (range = 3-15; lower
scores = fewer barriers)
5.17 (2.73) 4.97 (2.78) 5.63 (2.97) 2, 140 2.99 .053 .04
Perceived Suitability (range = 2-10;
suitability)
3.10 (1.73) 2.97 (1.52) 2.66 (1.23) 1.83, 128.11 2.67 .078 .04
Note. aYears of education was included as a covariate in repeated-measures ANCOVA analyses. bGreenhouse-Geiser adjusted degrees
of freedom were used to evaluate statistical significance where the assumption of sphericity was violated. BACR = Beliefs about
Cardiac Rehabilitation scales (Cooper et al., 2007); CAD = Coronary Artery Disease; CADE-Q II = Coronary Artery Disease
Education Questionnaire, Version II (de Melo Ghisi et al., 2015); CR = cardiac rehabilitation; TCHH = Taking Charge of your Heart
Health patient education;.
pre- to post-TCHH (N = 71).
Model
Dependent Variable
Δ Perceived Necessity Δ Exercise Concerns Δ Practical Barriers Δ Perceived Suitability
B
SE Δ R2 b SE Δ R2 b SE Δ R2 b SE Δ R2
Step 1 .30*** .33*** .17** .44***
Constant 12.51*** 2.51 1.73 2.18 2.46 1.90 3.41 1.07**
CADE-Q II (T1) -.02 .02 -.02 .02 -.01 .02 -.03 .01
BACR Subscale
Score (T1)
Years of
Step 2 .03 .02 < .01 <.01
Δ CADE-Q II
.08 .05 -.05 .04 -.02 .04 -.01 .03
Note. CAD = coronary artery disease; CR = cardiac rehabilitation; BACR = Beliefs about Cardiac Rehabilitation scales (Cooper et al.,
2007); CADE-Q II = Coronary Artery Disease Education Questionnaire, Version II; TCHH = Taking Charge of your Heart Health
patient education. **p < .01, ***p < .001
39
Linear regression model estimating associations between changes in CAD knowledge and CR
exercise attendance (N = 54)a.
Step 1 .10
Sex 3.07 2.03
Step 2
Δ CADE-Q II (T2 – T1) -.13 .11
Note. aPatients enrolled in the CR home program were excluded from analyses as it was
impossible to reliably measure exercise attendance. CAD = coronary artery disease; CR =
cardiac rehabilitation; CADE-Q II = Coronary Artery Disease Education Questionnaire, Version
II (de Melo Ghisi et al., 2015). ***p < .001
40
Figure 1. Patient flow chart. CR = cardiac rehabilitation; ECAC = Early Cardiac Access
Stream CR program; SPS = CR surgical stream; F/U = follow-up TCHH = Taking Charge
of your Heart Health patient education; T1 = Pre-TCHH; T2 = Post-TCHH; T3 = 12-week
follow-up.
41
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