The motivation for physical activity is a predictor of VO2peak and is a useful parameter when determining the need for cardiac rehabilitation in an elderly cardiac population.

BACKGROUND: Exercise-based cardiac rehabilitation (CR) is an essential contributor to a successful recovery for elderly cardiac patients. The motivation for physical activity is a psychological parameter seldom described in secondary prevention, and it is plausible that motivation contributes to the differential effect of CR.
PURPOSE: To investigate if motivation, measured using the behavioural regulation in an exercise questionnaire (BREQ-2), predicts VO2peak in elderly cardiac patients before and after CR.
METHODS: A prospective cohort study of elderly ischemic cardiac patients and patients with valvular disease participating in cardiac rehabilitation was used. Motivation was measured using BREQ-2, which measures five constructs of motivation and a summed score-the relative autonomy index (RAI). VO2peak was measured before and after CR using a cardiopulmonary exercise test (CPET).
RESULTS: Two hundred and three patients performed the baseline tests and initiated CR. One hundred and eighty-two completed CR and comprised the follow-up group. The mean VO2peak was 18 ml/kg/min (SD±5.1). VO2peak increased significantly with increasing motivation, 1.02 (.41-1.62) ml/kg/min pr. SD. Mean improvement from CR was 2.3 ml/kg/min (SD±4.3), the equivalent of a 12% increase. A change in VO2peak after CR was likewise positively associated with increased motivation, .74 (.31-1.17) pr. SD.
CONCLUSION: The level of motivation predicts VO2peak before CR, and is also able to predict changes in VO2peak following CR. Motivation measured with the BREQ-2 questionnaire can be applied as a screening tool for elderly cardiac patients before they initiate CR to identify patients with need of specific attention.

Introduction

Cardiac rehabilitation (CR) is an essential contributor to a successful recovery for cardiac patients. CR improves life expectancy, physical function, and quality of life and patients experience less relapse of the disease compared to non-participants of CR [1-3] Although the benefits of exercise-based rehabilitation are well studied, compliance and adherence in CR remain low [4]. This is especially the case in elderly cardiac patients [5]. Poor compliance and adherence have previously been linked to psychological distress, especially anxiety and depression [6-8]. As psychological distress is more prevalent in the younger segment of the cardiac population [9, 10], other psychological factors may determine success in CR in the elderly cardiac patients.

Physical exercise is a primary component in CR. The ‘gold standard’ of measuring effect of the exercise component of CR is VO2peak from a symptom-limited cardiopulmonary exercise test (CPET). VO2peak is a precise measure and a reliable individual predictor of future health outcomes such as CVD and mortality [11-14]. The motivation for physical activity is a parameter seldom described in secondary prevention, and it is plausible that the lack of motivation to be physically active can explain the difference in success rates, assessed as improvement of VO2peak, when participating in CR.

The motivation for physical activity can be measured using the validated “behavioral regulation in exercise questionnaire” (BREQ-2). BREQ-2 is based on the Self Determination Theory, which is used to understand exercise and physical activity patterns [15, 16] and why people adopt and/or maintain a behavior change [17, 18]. The BREQ-2 questionnaire measures different constructs of motivation. A summed score of the level of motivation can be derived by combining the constructs of motivation. The summed score is named the Relative Autonomy Index (RAI).

This study aimed to investigate if the constructs of motivation and/or the RAI was associated with the effect of CR, measured as VO2peak, in elderly cardiac patients.

Methods

The study population

This is a prospective cohort study of elderly cardiac patients entering a CR program at a Danish cardiac rehabilitation unit at a hospital in Copenhagen from December 2015 to February 2018 [19]. Patients were asked to join the study if they were more than 64 years of age and met one of the following criteria within three months of entering the CR program: 1) had acute coronary syndrome, including myocardial infarction 2) underwent percutaneous coronary intervention, 3) received coronary artery bypass grafting or 4) received a heart valve replacement. Exclusion criteria: Patients with a contraindication to CR, mental impairment leading to an inability to cooperate, a severely impaired ability to exercise, signs of severe cardiac ischemia and/or a positive exercise testing on severe cardiac ischemia, insufficient knowledge of the native language and an implanted cardiac device (CRT-P, ICD). For the majority of the patients this was their first enrolment in CR because patients attending a second CR would be referred to municipal CR.

Ethical approval for the study was obtained from the Regional Scientific Ethical Committee for Copenhagen, Denmark (Ref.: H-15011913) and the study was conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained.

The study cohort is part of a multi-center/national cohort study, European Cardiac Rehabilitation in the Elderly (EU-CaRE, [20]).

Rehabilitation program

The CR program consisted of a supervised eight-week outpatient exercise intervention at a hospital with two weekly sessions (16 sessions in total) of 1.5 hours with a high-intensity interval (80% of VO2peak) and resistance training. Patients were instructed in self-monitoring of training intensity using the Borg Scale and the sessions were supervised by an instructor. The training sessions were not routinely monitored with heart rate sensors. The program was complemented with a weekly 1.5 hour session of group-based patient education on cardiovascular disease, psychological issues, and diet counseling. Additionally, patients had one or more individual sessions with a cardiologist, a dietician, a physiotherapist, and a nurse.

Primary exposure—The motivation for physical activity

The level and type of motivation were measured using BREQ-2 (see S1 Appendix). The BREQ-2 is the second version of the questionnaire and is a validated and useful tool to measure a patient’s motivation for exercise [21].

The BREQ-2 inventory comprises 19 items. Each item has five possible answers scored on a scale of 0–4 (0 = Not true for me; 4 = Very true for me). The questionnaire assesses five constructs: amotivation –e.g., “I think that exercising is a waste of time”; external regulation –e.g., “I exercise because other people tell me I should”; introjected regulation –e.g., “I feel guilty when I do not exercise”; identified regulation –e.g., “I value the benefits/advantages of exercising”; and intrinsic motivation –e.g., “I enjoy my exercise sessions”.

BREQ-2 was measured as a multidimensional scale, measuring each of the five types of motivation. Additionally, a summed score was derived from the five subscales, the Relative Autonomy Index (RAI). The RAI gives an index of the degree to which respondents are motivated. The RAI is obtained by weighting each subscale and then summing these weighted scores. Each subscale score is multiplied by its weighting, and then the weighted scores are summed. Higher, positive scores indicate greater relative autonomy; lower, negative scores indicate more controlled regulation.

In the descriptive analyses (Table 1) the RAI was categorized into low, medium and high degree of motivation. Since there is no recommended categorization of RAI, we arbitrarily created cut-points that yielded a reasonable distribution of the population.

Table 1

Patient characteristics by level of motivation at the baseline.

	Total population	Motivation for physical activity			p value
		Low (RAI<0)	Medium (RAI 0–9)	High (RAI 10–20)
N	203	46 (23%)	94 (46%)	63 (31%)
Age (years)	72.3±5	71.3±5	72.2±5	72.8±5	0.360
Sex (male)	149 (73%)	34 (74%)	69 (73%)	46 (73%)	0.995
Body mass index (kg/m 2 )	27.3 (4.6)	29.3 (4.7)	26.8 (4.0)	26.3 (4.4)	<0.001
Living status (alone)	66 (33%)	21 (46%)	27 (29%)	18 (29%)	0.096
Ethnicity (Non- Western European)	12 (6%)	2 (4%)	4 (4%)	6 (9%)	0.342
Educational attainment
Short-term education	107 (54%)	26 (57%)	43 (46%)	38 (60%)	0.169
Long-term education	96 (46%)	20 (43%)	51 (54%)	25 (40%)
Index event
ACS	101 (50%)	17 (37%)	48 (52%)	36 (57%)	0.200
Stable CAD	73 (36%)	22 (48%)	34 (36%)	17 (27%)
Heart valve replacement	28 (14%)	7 (15%)	11 (12%)	10 (16%)
Smoking status
Never smoked (>1year)	99 (49%)	27 (59%)	58 (62%)	14 (63%)	0.094
Former smoker (<1year)	60 (30%)	14 (30%)	29 (31%)	17 (27%)
Smoker	18 (21%)	5 (11%)	7 (7%)	6 (10%)
Hypertension (yes)	83 (67%)	14 (70%)	32 (66%)	37 (59%)	0.468
Hypercholesterolemia (yes)		35 (76%)	66 (71%)	35 (55%)	0.047
Ejection fraction (%)	51% (9.7)	50% (9.6)	52% (9.5)	53% (10.0)	0.031
Diabetes (yes)	39 (20%)	16 (35%)	15 (16%)	8 (13%)	0.009
Peripheral artery disease (yes)	19 (9%)	4 (9%)	11 (12%)	4 (6%)	0.485
COPD (Yes)	15 (7%)	2 (4%)	8 (9%)	5 (8%)	0.666
Kidney disease (yes)	24 (12%)	5 (11%)	11 (12%)	8 (13%)	0.978
Beta blockers (yes)	142 (70%)	34 (74%)	64 (68%)	44 (70%)	0.779
Statins (yes)	178 (87%)	40 (87%)	83 (88%)	55 (87%)	0.969
Vital exhaustion (0–17 score)	4.4 (4.0)	5.6 (4.1)	4.2 (4.1)	3.6(3.4)	0.027
PHQ-9 (0–27 score)	5.2 (4.5)	5.8 (4.6)	5.2 (4.8)	4.4 (4.3)	0.641
GAD-7 (0–21 score)	3.3 (4.2)	4.1 (4.4)	3.4 (4.5)	2.6 (3.4)	0.607
VO2peak (mL/kg/min) before CR	18.0 (5.2)	16.1 (3.9)	17.5 (4.7)	20.3 (6.0)	<0.001
RER	1.09 (0.1)	1.09 (0.1)	1.07 (0.1)	1.1 (0.1)	0.398
Borg score (0–20)	15.5 (3.7)	14.3 (5.1)	16.0 (2.6)	15.1 (3.7)	0.702
Predicted VO2peak before CR*	15.7 (7.0)	12.6 (5.6)	15.8 (5.9)	18.1 (8.3)	<0.001

Abbreviations: RAI, relative autonomy index; ACS, acute coronary syndrome; CAD; coronary artery disease; COPD; chronic obstructive pulmonary disease; PHQ-9; patient health questionnaire; GAD-7; generalized anxiety disorder; RER; respiratory exchange ratio; CR; cardiac rehabilitation. Data are reported as mean ± SD or number (%).

*Predicted VO2peak is derived from the validated prediction model by Myers et al [

Study outcome

The primary study outcome was VO2peak. VO2peak was assessed before and after CR using a cardiopulmonary exercise test (CPET) using a maximal symptom-limited bicycle ergometer test (Via Sprint 150P, Ergoline). Breathing gases were collected and analyzed (Jaeger, Master Screen, vers.5.21, Cardinal Health). Each test aimed at a respiratory exchange ratio greater than 1.1 to ensure the validity of the CPET tests [23]. VO2peak was defined as the highest value of oxygen consumption reached, despite progressive increase of the load applied, with the development of a plateau in the VO2 curve during the CPET. When a plateau was not identified, the highest value obtained at the end of test was characterized as VO2peak.

Patients that either withdrew their consent or did not attend the CPET after CR were considered as prematurely ending the program. Compliance was defined according to proportion of planned training- sessions attended (<50%, 50–75% or >75% attendance).

Confounding variables

Other variables of interest included age, sex, revascularization (PCI or CABG), educational attainment (Short or higher education), working status (working or retired), smoking status (never a smoker, former smoker, current smoker), physical activity level during leisure time (>30 minutes, 0–7 days per week) before cardiac event, the use of beta blockers (yes/no), use of statins (yes/no), left ventricular ejection fraction (%), comorbidities. Psychological distress was accounted for with three questionnaires measuring vital exhaustion, depression, and anxiety. Vital exhaustion was assessed using a 17-item questionnaire [24]. Depression and anxiety were assessed the validated Patient Health Questionnaire (PHQ-9) [25] and General Anxiety Disorder questionnaire (GAD-7) [26], respectively. Information on history of hypertension, hypercholesterolemia and co-morbidities were based on hospital records.

Follow-up analyses were also investigated for the influence of VO2peak at baseline, the premature end of rehabilitation and compliance to the CR program

Statistical analysis

The summed motivation score, RAI, is a continuous variable. For the descriptive statistics, the RAI was categorized into low (RAI<0, medium (RAI 0–9) and high (RAI>10–20) levels of motivation. For the inferential statistics, the RAI was used as a continuous variable.

Normally distributed variables were compared across the different levels of motivation using one-way ANOVA. Non-normally distributed variables were tested using Mann-Whitney and Kruskal-Wallis tests, while a Chi 2 test tested categorical data. Statistically significant differences between the groups were tested with pairwise comparisons using t test and Chi 2 tests.

Correlation between the constructs of motivation and VO2peak were assessed by scatterplots and tested using Pearson’s Correlation.

The influence of motivation on VO2peak was tested using multiple adjusted linear regression analyses. Confounders for both baseline and follow-up analyses were identified according to previous literature [27, 28] and whether they were associated with CRF and motivation. Follow-up analyses were additionally adjusted for VO2peak at baseline and compliance to the CR program. Identified confounders were tested sequentially against a simple regression model and adjusted for sex and age to assess the impact on CRF. Confounders that influenced a change in the estimate for motivation by more than 15% were included in the final model [29]. Due to the different continuous scales of the covariates, a standardized regression model was conducted to compare the strength of the association of different continuous predictors with the outcome within the same model.

A 2-tailed p value <0.05 was considered to be statistically significant. All statistical analyses were carried out using STATA IC 13.1 (StataCorp LP).

Results

Two hundred and thirty-seven patients were initially included in the study. Two hundred and three performed the baseline CPET and completed the BREQ-2 questionnaire. These patients comprised the baseline analyses. One hundred and eighty-two patients performed the second CPET and comprised the follow-up analyses. For a detailed overview of patient exclusion, see S1 Flowchart of the patient population with the number of patients excluded and the reason for exclusion.

Baseline characteristics

Baseline characteristics, according to the categorized RAI score (low, medium and high motivation), are presented in Table 1.

The mean age of the population was 72 (±5) years old, and 73% was male. The majority were Western European and living with a spouse. Almost half of the population had a higher educational attainment. Only 9% were current smokers. Half of the population had a PCI, 30% CABG, 14% heart valve replacement and 5% no revascularization. The mean VO2peak before CR was 18.2 (±5.0). The mean motivation RAI score was 5 (±7) ranging from -14 to 19.

Twenty-three percent of the population had low levels of motivation, while 31% were highly motivated. Patients with a low level of motivation had an overall higher burden of risk factors: higher body mass index, higher prevalence of both diabetes and hypertension, and lower LVEF. Patients with a low level of motivation also tend to live alone more and score higher on vital exhaustion than patients with both medium and high levels of motivation.

Differences between high and medium motivation levels were minor: Patients with a high level of motivation had a lower prevalence of hypercholesteremia, less hypertension, and lower vital exhaustion score.

There was a definite increase in VO2peak with an increasing level of motivation (p<0.001).

Constructs of motivation

A correlation between the five constructs of motivation and VO2peak was tested using pairwise correlations and scatterplots with a linear, see Fig 1.

Fig 1

Correlation between different constructs of motivation and VO2peak with Spearman coefficient (r).

(A) Amotivation: relationship between amotivation score and VO2peak. r = -0.21*; (B) External regulation: relationship between external regulation and VO2peak. r = 0.23*; (C) Introjected regulation: relationship between introjected regulation and VO2peak. r = 0.08; (D) Identified regulation: relationship between identified regulation and VO2peak. r = 0.17*; (E) Intrinsic regulation: relationship between intrinsic regulation and VO2peak. r = 0.27*; (F) Relative autonomy index: relationship between relative autonomy index and VO2peak. r = 0.30*. Significance: *P<0.05.

Except for introjected regulation, all constructs of motivation were significantly correlated with VO2peak at baseline. VO2peak correlated most with RAI (r = 0.30, p< 0.01). RAI also correlated with the other constructs of motivation. The highest correlation was observed between RAI and VO2peak. Amotivation and external regulation were especially right-skewed, whereas intrinsic regulation had a bimodal distribution.

To avoid multicollinearity between the different constructs of motivation, the RAI was chosen as the primary exposure variable for the baseline analyses.

VO2peak before CR

VO2peak was associated with sex, activity level, revascularization procedure, comorbidity, and vital exhaustion, but not with age, ejection fraction, or use of beta-blockers. RAI and VO2peak were significantly correlated (Fig 1, plot (F)). When adjusting for age and sex, the RAI remained significantly associated with VO2peak (1.70 per SD) (Table 2). After multiple adjustments, motivation remained associated with VO2peak (1.05 per SD), even after an adjustment for depression. Being male was also positively associated (3.23ml/kg/min) as was being physically active 5–7 days per week (2.64 ml/kg/min) compared to 0 days per week. Chronic kidney disease was associated with a lower baseline VO2peak (-3.34 ml/kg/min) as were diabetes and COPD (-2.22 and -2.09 ml/kg/min, respectively).

Table 2

Standardized coefficients of predictors of VO2peak before cardiac rehabilitation (A) and a change in VO2peak following cardiac rehabilitation (B).

Values indicate the difference in ml/kg/min.

A	Age and sex adjusted		Multiple adjusted model
Motivation (RAI pr. SD)	1.70	(1.04–2.37) ***	1.05	(.43–1.69) **
Age (pr. SD)	-1.47	(-3.09 - .15)	-1.02	(-2.47 - .42)
Sex (male)	2.65	(1.06–4.24) ***	3.23	(1.85–4.60) ***
Activity level (>30 min.)	0 days		0 days
2–4 days	1.71	(-.04–3.45)	1.01	(-.52–2.56)
5–7 days	3.54	(1.93–5.15) ***	2.64	(1.18–4.10) ***
Index diagnosis	ACS		ACS
Stable CAD	-1.76	(-3.29 - -.23) *	-.90	(-2.25 - .45)
Heart valve replacement	-2.47	(-4.62 - -.32) *	-1.80	(-3.69 - .09)
Ejection fraction (pr. SD)	1.28	(.46–2.09) *	1.24	(.54–1.94) **
COPD (yes)	-2.34	(-5.03 - -.35)	-2.09	(-4.35 - .17)
Diabetes (yes)	-4.01	(-5.71 - -2.30) ***	-2.22	(-3.81 - -.64) *
Kidney disease (yes)	-3.98	(-6.14 - -1.82) ***	-3.24	(-5.13 - -1.35) **
PHQ-9 (pr. SD)	-1.28	(-1.99 - -.58) ***	-.89	(-1.51 - -.28) *
B	Age and sex adjusted		Multiple adjusted model
Motivation (RAI pr. SD)	.57	(.12–1.01) *	.78	(.33–1.24) **
Baseline VO2peak (pr. SD)	-.56	(-1.16 - .21)	-1.30	(-1.94 - -.66) ***
Age (pr. SD)	-.84	(-1.85 - .18)	-1.00	(-2.01 - -0.01) *
Sex (male)	-.18	(-1.21 - .85)	.74	(-.28–1.76)
Smoking status	Never smoker		Never smoker
Previous smoker	-.23	(-1.22 - .77)	-.37	(-1.34 - .59)
Current smoker	-1.43	(-3.00 - .14)	-1.89	(-3.36 - -.40) *
Diabetes (yes)	-1.37	(-2.50 - -.24) *	-1.62	(-2.78 - -.48) **
Kidney disease (yes)	-0.98	(-2.37–0.42)	-1.45	(-2.84 - -0.06) *
PHQ-9 (pr. SD)	.22	(-.24 - .69)	.21	(-.24 - .66)

Significance levels

*p<0.05

**p<0.01

***p<0.001.

Abbreviations: RAI, relative autonomy index; ACS, acute coronary syndrome; CAD; coronary artery disease; COPD; chronic obstructive pulmonary disease; PHQ-9; patient health questionnaire.

Motivation, depression, age and ejection fraction were standardized in the multiple models to compare the importance of the individual covariates on the same scale. After standardization, motivation had a just as high association with VO2peak as depression. Comorbidity also had a high impact on VO2peak.

Change in VO2peak following CR

The mean improvement from CR was 2.27 ml/kg/min (SD±4.3), the equivalent of a 12% increase. In age and sex adjusted analyses, change in VO2peak was positively associated with motivation score (0.57 ml/kg/min per SD), and negatively associated with diabetes.

In the multiple-adjusted model, motivation continued to be statistically associated with VO2peak (0.78 ml/kg/min per SD), whereas depression was not associated. Current smokers and patients with chronic kidney disease or diabetes also improved less. Higher age, higher baseline VO2peak and having diabetes or kidney disease was negatively associated with change in VO2peak.

Adherence

16 patients (7%) ended the CR program prematurely. This was not significantly associated with level of motivation, but statistical power was limited.

Discussion

We aimed to investigate whether motivation, measured using BREQ-2, was a predictor of VO2peak before and after CR in an elderly cardiac population. This is the first study to apply BREQ-2 to cardiac patients to predict the success of CR. Using the computed RAI score, we found a significant association between motivation and VO2peak, both before and after CR. This was persistent in both simple and multiple-adjusted regression analyses.

Motivation as a predictor of VO2peak before and after CR

Applying the BREQ-2 to measure motivation seems to be a valid tool to predict physical capacity in the elderly cardiac population and may be a useful assessment tool to target patients with lower motivation who could need special attention during exercise-based rehabilitation.

Psychological distress, measured using depression, anxiety, and vital exhaustion, does not appear to affect the inverse relationship between motivation and VO2peak.

In current CR programs, it is recommended that the patients are screened for psychological distress with, for example, the PHQ9 score or the Hospital Anxiety and Depression Scale (HADS) [30]. These results showed that depression is associated with r VO2peak before CR. However, the presence of depression did not significantly affect the impact of motivation on VO2peak. Vital exhaustion and anxiety did not have an impact on VO2peak before CR.

Motivation was the only psychological factor that had an impact on change in VO2peak following CR. Neither depression, anxiety, nor vital exhaustion had an impact on change in VO2peak. This could suggest that it is more relevant to screen older cardiac patients for motivation rather than other psychological factors, at least if the purpose is to screen for barriers to CR. Our results suggest that the application of BREQ-2 before CR could help the health care professionals in capturing unmotivated patients and help them frame a rehabilitation that supports the patients in building motivation.

BREQ-2 measured five constructs of motivation. In addition, we calculated the summed score, RAI. Some literature suggests that applying a simple score, e.g., the RAI, is a step backward and a simplification of the SDT.

We tested all possible constructs of motivation against VO2peak in this paper and found that the constructed score was the only score that was normally distributed, and that this score also had the highest correlation with VO2peak (Fig 1).

The skewness of amotivation, external regulation and intrinsic regulation, in particular, might be explained by the selection of patients. The patients participated voluntarily in the CR program, and this suggests that the patients had at least some motivation for exercise. Patients with a high level of amotivation may be prone to reject participation in CR and participation in the study, introducing an increased risk of selection bias. This suggests that not all constructs of motivation fit equally well for patients engaging in exercise-based CR.

For future research, the model fit for amotivation specifically may be better if the BREQ-2 questionnaire is collected while the patients are still hospitalized. Many cardiac patients never initiate CR, and these patients, in particular, could prove to have higher levels of amotivation.

Strengths and weaknesses

The focus on adapting a simple screening tool for motivation is a new approach in cardiac rehabilitation. Motivational interviews can be time-consuming, and demand extra resources in a CR unit. Using the BREQ-2 could prove a relevant tool to guide therapists in targeting patients with low levels of motivation before they initiate rehabilitation.

The prospective study design provided the high quality of the data, both with regards to exposures, confounders, and endpoints. Also, given the nature of the prospective design, we could address the issue of causality between exposure and outcome.

Less than 50% of cardiac patients participate in CR [31], a lower proportion of women participated and patients with insufficient understanding of the Danish language were also excluded. While this does not affect internal validity, it may affect generalizability of the results. It is also uncertain whether findings can be transferred to younger cardiac patients (<65 years).

As we investigated an elderly population age-related comorbidities could have an impact on both motivation and outcome. In this study no geriatric assessment was performed on the patients. However, the patients referred to rehabilitation did have an examination with a cardiologist who assessed mental capability to complete the CR program before referral and patients with physical disabilities rendering exercise training impossible were not included.

Conclusion

Motivation predicted VO2peak, both before and after participating in CR. Motivation measured with the BREQ-2 questionnaire may be of value as a screening tool for elderly cardiac patients to identify patients in need of specific attention for successful CR. Future studies should address whether interventions targeting motivation may improve outcomes of CR.

Patient population with exclusion and reason for exclusion.

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Behavioral regulation in exercise Questionnaire-2 with 19 questions.

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18 Mar 2021

PONE-D-21-02329

The motivation for physical activity is a predictor of VO2peak and is a useful parameter when determining the need for cardiac rehabilitation in an elderly cardiac population

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Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors aimed to investigate the association between motivation, as measured by means of BREQ-2 questionnaire, and (changes in) exercise capacity in older patients participating in an ambulatory phase II cardiac rehabilitation program. A cohort of 203 patients was enrolled of which 182 participants completed the rehabilitation program and follow-up exercise testing. In general, the manuscript is well-written and reads fluently. The following suggestions/remarks are aimed at further improving the clarity of the manuscript.

In the introduction, authors focus mainly on the fact that uptake and adherence to CR is low and that some physiological factors have been identified (e.g. anxiety, depression) that party explain this poor adherence/compliance. Then authors suggest that another, tough less investigated, parameter could be motivation. In the introduction, i miss a bit the rationale why you then opt to investigate the association between motivation and change in VO2/baseline VO2 and why for instance not focusing on the association between motivation and adherence/compliance to CR. Could authors elaborate a bit more on why they opted (rationale) for exercise capacity.

Methods:

Study population. One of the biggest challenges with regard to CR remains uptake of CR in which motivation most likely plays a crucial role. Could authors add how many of the hospitalized patients following ACS,PCT, CABG or valve replacement were in fact eligible for participation in a CR program. It would be particularly interesting to know whether motivation played a crucial role in the uptake of CR. Could it be be that patients already deciding to go to CR are already the more motivated patients. Could there be some selection bias?

Was this the first enrollment in CR program for all patients? If not, please add to table 1 number of patients that participated for the first time and number of patients for whom this was 2nd or 3rd enrollment.

Rehabilitation program. Please add the number of sessions that make up a full rehabilitation program

Primary exposure. Motivation is categorized into three categories: low, medium, high. Was this an arbitrary categorization or according to previous reference. In case of the latter, please add reference.

Please provide a definition for premature ending of the rehab program and a definition for compliance (i.e. how was it calculated). Did you observe a difference in number of patients that prematurely ended the rehab program and with regard to compliance across the three categories of motivation?

Table 1: please add a column with the overall data of the study population. Further, please add a definition for hypertension / hypercholesterolemia. Is there a rationale for only reporting data on statins and beta-blockers but not insulin / other BP lowering medication/... Add SD to ejection fraction. Please also add to this table VO2 peak expressed as percentage of predicted, RER and BORG score.

Study outcome: As peak VO2 is your primary outcome somewhat more detailed information could be provided. E.g each test aimed at RER> 1.1. Was this achieved in all patients? Which protocol did you apply? Next to RER, did you use other parameters to decide on the maximal character of the test? How did you define peakVO2?

Confounding variables. Authors report that physical activity was assessed during leisure time. How was this assessed? Further, was PA in leisure time different across the three categories of motivation? Provide also summary data for PA. Please also add where you retrieved data on demographics, EF etc.

Questionnaires. How where questionnaires completed (online survey, interview, paper,...). Especially in case of paper and pencil - was there any missing data?

Rehabilitation program. Did you monitor your patients during the training session? If so, please provide details on what was monitored during training and whether patients were adherent to the prescribed intensity/duration/...of the exercise program

Please add the statistical tests used to evaluate normality of your data. Which data were not normally distributed?

It seems that Figure 1 is missing?

Though i agree and understand that you should not repeating what is in the tables, yet somewhat more statistics and numerical data in the results section could improve the reading without having to go back to the table all the time.

In the discussion section, the different subsections of of motivation are discussed - though this is missing in the results section. please provide the results first before discussing it.

Reviewer #2: This paper by Mikkelsen et al prospectively investigated the correlation of individual motivation for physical activity, determined as the summed RAI score by BREQ-2 questionnaire, and the cardio-pulmonary fitness, measured as VO2peak in a symptom-limited CPET, in 203 patients participating in an ambulatory cardiac rehabilitation (CR) program. They found that in contrast to other psychological determinants such as depression and anxiety, motivation was and independent predictor of VO2peak at baseline and predicted delta VO2peak from baseline to the end of CR. The authors conclude that motivation measured with the BREQ-2 questionnaire can be useful as a screening tool for

elderly cardiac patients undergoing CR to detect patients with lower potential to increase VO2peak.

The study addresses an important topic and provides interesting and clinically useful new data to the field of CR. The prospective study design is solid. The study, however, includes a very selected patient population (e.g. > 64 years, only 9 % current smokers, high level of education) that might not be representative for most CR cohorts.

Major points

The main limitation of the study is its low patient number and its selective recruitment. Considering the study duration of 26 months, the inclusion of 203 patients seems rather low (average of < 8 patients/months). What is the size of the local CR program? Where patients recruited consecutively every day or dependent on the availability of the study staff?

A better motivation could result in the achievement of a higher respiratory exchange ratio (RER) in CPET. Did RAI correlate with RER. This relation should be presented in the data.

Please specify the “multiple adjustment” made in the multiple adjusted model. Was the model also adjusted for diabetes, body mass index and activity level? If not, this should be done.

Was there a signal of lower RAI in the 16 drop outs?

Did the CR program had an impact on the RAI score? Providing data on RAI scores at baseline and after CR would be interesting

Minor points

Why were patients < 64 years excluded? What is the percentage of patients < 64 years in the CR program

Appendix is missing

Figure 1 should be presented as a flow chart

The low numbers of female participants should be stated as a limitation

**********

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Reviewer #1: No

Reviewer #2: No

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19 Aug 2021

Response to reviewers

Reviewer #1:

The authors aimed to investigate the association between motivation, as measured by means of BREQ-2 questionnaire, and (changes in) exercise capacity in older patients participating in an ambulatory phase II cardiac rehabilitation program. A cohort of 203 patients was enrolled of which 182 participants completed the rehabilitation program and follow-up exercise testing. In general, the manuscript is well-written and reads fluently. The following suggestions/remarks are aimed at further improving the clarity of the manuscript.

• Comment 1: In the introduction, authors focus mainly on the fact that uptake and adherence to CR is low and that some physiological factors have been identified (e.g. anxiety, depression) that party explain this poor adherence/compliance. Then authors suggest that another, tough less investigated, parameter could be motivation. In the introduction, i miss a bit the rationale why you then opt to investigate the association between motivation and change in VO2/baseline VO2 and why for instance not focusing on the association between motivation and adherence/compliance to CR. Could authors elaborate a bit more on why they opted (rationale) for exercise capacity.

• Response: Thank you for this relevant comment. We have addressed this in the introduction now with the rationale that VO2peak/change in VO2peak is a great measure for the effect of a CR program and the fact that VO2peak is an important predictor of future morbidity and mortality.

• Comment 2: Study population. One of the biggest challenges with regard to CR remains uptake of CR in which motivation most likely plays a crucial role. Could authors add how many of the hospitalized patients following ACS,PCT, CABG or valve replacement were in fact eligible for participation in a CR program. It would be particularly interesting to know whether motivation played a crucial role in the uptake of CR. Could it be be that patients already deciding to go to CR are already the more motivated patients. Could there be some selection bias?

• Response: Unfortunately, this cannot be addressed in this paper. We very much agree that there can be selection bias on attendance in CR because we capture the most motivated.

We only had the opportunity to address motivation among patients that attended CR. If possible, it would be very interesting to interview patients with the BREQ-2 questionnaire just after surgery or even before if possible, to see if there was a correlation between motivation for exercise and attendance in CR. This could be an opportunity to capture patients with a lack of motivation and perform some kind of intervention to increase motivation.

• Comment 3: Was this the first enrolment in CR program for all patients? If not, please add to table 1 number of patients that participated for the first time and number of patients for whom this was 2nd or 3rd enrolment.

• Response: We do not have this information available. However, the normal clinical practice at this hospital is that if patients are referred for the second or third time, they will be referred for municipal rehabilitation and not at the hospital. Thus, for the majority of the patients this will be their first CR. We have added this information to the methods section: Study population

• Comment 4: Rehabilitation program. Please add the number of sessions that make up a full rehabilitation program

• Response: Thank you for your comment as this is indeed relevant. In the description of the rehabilitation program we do state that the program consists of an 8-week intervention with 2 weekly sessions of 1.5 hours. We have added the total of 16 sessions to the text as well. I hope this is what you alluded to.

• Comment 5: Primary exposure. Motivation is categorized into three categories: low, medium, high. Was this an arbitrary categorization or according to previous reference. In case of the latter, please add reference.

• Response: The BREQ-2 questionnaire has not previously been divided into groups. The three groups were created by the authors in order to provide a descriptive overview of the population. This should of course be stated in the article and we have now done this in the methods section: Primary exposure – the motivation for physical activity

• Question 6: Please provide a definition for premature ending of the rehab program and a definition for compliance (i.e. how was it calculated). Did you observe a difference in number of patients that prematurely ended the rehab program and with regard to compliance across the three categories of motivation?

• Response: Compliance is described in confounding variables and was measured as attendance (<50%, 50-75% or >75% attendance). We have added information on subjects that prematurely ended the program to the methods section: Rehabilitation program. The categories of motivation were not significantly associated with compliance.

• Comment 7: Table 1: please add a column with the overall data of the study population. Further, please add a definition for hypertension / hypercholesterolemia. Is there a rationale for only reporting data on statins and beta-blockers but not insulin / other BP lowering medication/... Add SD to ejection fraction. Please also add to this table VO2 peak expressed as percentage of predicted, RER and BORG score.

• Response: We have added a total study population column and added information on hypertension / hypercholesterolemia and predicted VO2peak, RER and BORG score. We reported data on statins and beta-blockers because these are guidelines recommended medications for (almost) all patients with CVD and frequently used as indicators.

• Comment 8: Study outcome: As peak VO2 is your primary outcome somewhat more detailed information could be provided. E.g each test aimed at RER> 1.1. Was this achieved in all patients? Which protocol did you apply? Next to RER, did you use other parameters to decide on the maximal character of the test? How did you define peakVO2?

• Response: We have added this information in the methods section: Study outcome

• Comment 9: Confounding variables. Authors report that physical activity was assessed during leisure time. How was this assessed? Further, was PA in leisure time different across the three categories of motivation? Provide also summary data for PA. Please also add where you retrieved data on demographics, EF etc.

• Response: This valid point has been addressed in table 1. There was indeed a positive trend correlating difference between motivation for physical activity and self-reported physical activity, although this was not significant.

• Comment 10: Questionnaires. How where questionnaires completed (online survey, interview, paper,...). Especially in case of paper and pencil - was there any missing data?

• Response: The questionnaires were primarily filled out online. One a few subjects filled out the questionnaire in a paper format as they did not have access to a computer. We have described the missing data in figure 1 as exclusions from the analyses. This comprised of 13 patients that did not answer.

• Comment 11: Rehabilitation program. Did you monitor your patients during the training session? If so, please provide details on what was monitored during training and whether patients were adherent to the prescribed intensity/duration/...of the exercise program

• Response: The patients were not monitored during the training sessions. The therapists supervised all training sessions and guided the patients based on the BORG scale. We have added this information to the methods section: rehabilitation program

• Comment 12: Please add the statistical tests used to evaluate normality of your data. Which data were not normally distributed?

• Response: I believe we have described this in under: Statistical analyses “Normally distributed variables were compared across the different levels of motivation using one-way ANOVA. Non-normally distributed variables were tested using Mann-Whitney and Kruskal-Wallis tests, while a Chi 2 test tested categorical data. Statistically significant differences between the groups were tested with pairwise comparisons using t test and Chi 2 tests.”

• Comment 13: It seems that Figure 1 is missing?

• Response: We apologize if this was not visible to you. It was in the compiled sheet approved before uploading. We will contact the editor to ensure that all figures are visible in the revised paper.

• Comment 14: Though I agree and understand that you should not repeating what is in the tables, yet somewhat more statistics and numerical data in the results section could improve the reading without having to go back to the table all the time.

• Response: We have tried to accommodate this by adding more numbers to the results section.

• Comment 15: In the discussion section, the different subsections of of motivation are discussed - though this is missing in the results section. please provide the results first before discussing it.

• Response: I do believe that we have described this in the results section: Constructs of motivation. Unless I am misunderstanding your comment

Reviewer #2:

This paper by Mikkelsen et al prospectively investigated the correlation of individual motivation for physical activity, determined as the summed RAI score by BREQ-2 questionnaire, and the cardio-pulmonary fitness, measured as VO2peak in a symptom-limited CPET, in 203 patients participating in an ambulatory cardiac rehabilitation (CR) program. They found that in contrast to other psychological determinants such as depression and anxiety, motivation was and independent predictor of VO2peak at baseline and predicted delta VO2peak from baseline to the end of CR. The authors conclude that motivation measured with the BREQ-2 questionnaire can be useful as a screening tool for

elderly cardiac patients undergoing CR to detect patients with lower potential to increase VO2peak.

The study addresses an important topic and provides interesting and clinically useful new data to the field of CR. The prospective study design is solid. The study, however, includes a very selected patient population (e.g. > 64 years, only 9 % current smokers, high level of education) that might not be representative for most CR cohorts.

Major points

• Comment 1: The main limitation of the study is its low patient number and its selective recruitment. Considering the study duration of 26 months, the inclusion of 203 patients seems rather low (average of < 8 patients/months). What is the size of the local CR program? Where patients recruited consecutively every day or dependent on the availability of the study staff?

• Response: This was a selective recruitment because this is a sub-study of the EU-CaRE trial that aimed for including patients >64 years which only is a little more than half of the patients being offered CR (. 40 % of the population is <64 years). Patients were recruited consecutively by the cardiologist and if the patient was eligible and wished to participate in CR they were asked to participate. Almost all CR patients agreed to participate. We did also publish this in an article with baseline data from the EU-CaRE cohort:

Prescott E, Mikkelsen N, Holdgaard A, Eser P, Marcin T, Wilhelm M, Gil CP, González-Juanatey JR, Moatemri F, Iliou MC, Schneider S, Schromm E, Zeymer U, Meindersma EP, Ardissino D, Kolkman EK, Prins LF, van der Velde AE, Van 't Hof AW, de Kluiver EP. Cardiac rehabilitation in the elderly patient in eight rehabilitation units in Western Europe: Baseline data from the EU-CaRE multicentre observational study. Eur J Prev Cardiol. 2019 Jul;26(10):1052-1063. doi: 10.1177/2047487319839819. Epub 2019 Mar 29. PMID: 30924688.

• Comment 2: A better motivation could result in the achievement of a higher respiratory exchange ratio (RER) in CPET. Did RAI correlate with RER. This relation should be presented in the data.

• Response: This was added to table 1. There was no significant difference between groups.

• Comment 3: Please specify the “multiple adjustment” made in the multiple adjusted model. Was the model also adjusted for diabetes, body mass index and activity level? If not, this should be done.

• Response: All relevant confounding variables describes in table 1 were tested in the multiple models to see if it made any significant change to the effect motivation had on peak VO2. We have added the confounding variables of interest in the statistical analyses section. The first model for baseline VO2peak was both adjusted for diabetes and self-reported physical activity at these had significant confounding impact. BMI was also tested, but not included as it did not impact the result. The first model for baseline VO2peak was both adjusted for diabetes and self-reported physical activity at these had significant confounding impact. BMI was also tested, but not included as it did not impact the result.

• Comment 4: Was there a signal of lower RAI in the 16 dropouts?

• Response: Thank you for this comment. There was an approximately even distribution among dropouts irrespectively of level of motivation. COPD and diabetes were associated with ending prematurely. This was not significant, probably due to low power of this analyses. We have added this to our results section

• Comment 5: Did the CR program had an impact on the RAI score? Providing data on RAI scores at baseline and after CR would be interesting

• Response: This is a very interesting comment. We only have data on the baseline motivation. But this bring a new interesting aspect to rehabilitation and motivation since motivation also can change over time when exposed to changes in life.

Minor points

• Comment 6: Why were patients < 64 years excluded? What is the percentage of patients < 64 years in the CR program

• Response: This is because this a Danish sub-study based on the EU-CaRE study which is a multi-country study on elderly cardiac patient >64 years of age. In this hospital rehabilitation app. 40 % of the population is <64 years.

• Comment 7: Appendix is missing

• Response: I am sorry for that. This must have been missed in the upload process. I will make sure it becomes available to you.

• Comment 8: Figure 1 should be presented as a flow chart

• Response: Valid point and this has been corrected.

• Comment 9: The low numbers of female participants should be stated as a limitation

• Response: Yes. This is a general limitation for rehabilitation, and we have added this to limitations.

21 Dec 2021

PONE-D-21-02329R1

The motivation for physical activity is a predictor of VO2peak and is a useful parameter when determining the need for cardiac rehabilitation in an elderly cardiac population

PLOS ONE

Dear Dr.Mikkelsen

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we have decided that your manuscript does not meet our criteria for publication and must therefore be rejected.

Specifically:

I am sorry that we cannot be more positive on this occasion, but hope that you appreciate the reasons for this decision.

Yours sincerely,

Xianwu Cheng, M.D., Ph.D., FAHA

Academic Editor

PLOS ONE

Additional Editor Comments (if provided):

Both original reviewers have been declined to review this revised manuscript. The main serious problems are that the authors changed key data without acceptable explanation (especially, in Table).

[Note: HTML markup is below. Please do not edit.]

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

- - - - -

For journal use only: PONEDEC3

21 Feb 2022

Response to reviewers

Reviewer #1:

The authors aimed to investigate the association between motivation, as measured by means of BREQ-2 questionnaire, and (changes in) exercise capacity in older patients participating in an ambulatory phase II cardiac rehabilitation program. A cohort of 203 patients was enrolled of which 182 participants completed the rehabilitation program and follow-up exercise testing. In general, the manuscript is well-written and reads fluently. The following suggestions/remarks are aimed at further improving the clarity of the manuscript.

• Comment 1: In the introduction, authors focus mainly on the fact that uptake and adherence to CR is low and that some physiological factors have been identified (e.g. anxiety, depression) that party explain this poor adherence/compliance. Then authors suggest that another, tough less investigated, parameter could be motivation. In the introduction, i miss a bit the rationale why you then opt to investigate the association between motivation and change in VO2/baseline VO2 and why for instance not focusing on the association between motivation and adherence/compliance to CR. Could authors elaborate a bit more on why they opted (rationale) for exercise capacity.

• Response: Thank you for this relevant comment. We have addressed this in the introduction now with the rationale that VO2peak/change in VO2peak is a great measure for the effect of a CR program and the fact that VO2peak is an important predictor of future morbidity and mortality.

• Comment 2: Study population. One of the biggest challenges with regard to CR remains uptake of CR in which motivation most likely plays a crucial role. Could authors add how many of the hospitalized patients following ACS,PCT, CABG or valve replacement were in fact eligible for participation in a CR program. It would be particularly interesting to know whether motivation played a crucial role in the uptake of CR. Could it be be that patients already deciding to go to CR are already the more motivated patients. Could there be some selection bias?

• Response: Unfortunately, this cannot be addressed in this paper. We very much agree that there can be selection bias on attendance in CR because we capture the most motivated.

We only had the opportunity to address motivation among patients that attended CR. If possible, it would be very interesting to interview patients with the BREQ-2 questionnaire just after surgery or even before if possible, to see if there was a correlation between motivation for exercise and attendance in CR. This could be an opportunity to capture patients with a lack of motivation and perform some kind of intervention to increase motivation.

• Comment 3: Was this the first enrolment in CR program for all patients? If not, please add to table 1 number of patients that participated for the first time and number of patients for whom this was 2nd or 3rd enrolment.

• Response: We do not have this information available. However, the normal clinical practice at this hospital is that if patients are referred for the second or third time, they will be referred for municipal rehabilitation and not at the hospital. Thus, for the majority of the patients this will be their first CR. We have added this information to the methods section: Study population

• Comment 4: Rehabilitation program. Please add the number of sessions that make up a full rehabilitation program

• Response: Thank you for your comment as this is indeed relevant. In the description of the rehabilitation program we do state that the program consists of an 8-week intervention with 2 weekly sessions of 1.5 hours. We have added the total of 16 sessions to the text as well. I hope this is what you alluded to.

• Comment 5: Primary exposure. Motivation is categorized into three categories: low, medium, high. Was this an arbitrary categorization or according to previous reference. In case of the latter, please add reference.

• Response: The BREQ-2 questionnaire has not previously been divided into groups. The three groups were created by the authors in order to provide a descriptive overview of the population. This should of course be stated in the article and we have now done this in the methods section: Primary exposure – the motivation for physical activity

• Question 6: Please provide a definition for premature ending of the rehab program and a definition for compliance (i.e. how was it calculated). Did you observe a difference in number of patients that prematurely ended the rehab program and with regard to compliance across the three categories of motivation?

• Response: Compliance is described in confounding variables and was measured as attendance (<50%, 50-75% or >75% attendance). We have added information on subjects that prematurely ended the program to the methods section: Rehabilitation program. The categories of motivation were not significantly associated with compliance.

• Comment 7: Table 1: please add a column with the overall data of the study population. Further, please add a definition for hypertension / hypercholesterolemia. Is there a rationale for only reporting data on statins and beta-blockers but not insulin / other BP lowering medication/... Add SD to ejection fraction. Please also add to this table VO2 peak expressed as percentage of predicted, RER and BORG score.

• Response: We have added a total study population column and added information on hypertension / hypercholesterolemia and predicted VO2peak, RER and BORG score. We reported data on statins and beta-blockers because these are guidelines recommended medications for (almost) all patients with CVD and frequently used as indicators.

• Comment 8: Study outcome: As peak VO2 is your primary outcome somewhat more detailed information could be provided. E.g each test aimed at RER> 1.1. Was this achieved in all patients? Which protocol did you apply? Next to RER, did you use other parameters to decide on the maximal character of the test? How did you define peakVO2?

• Response: We have added this information in the methods section: Study outcome

• Comment 9: Confounding variables. Authors report that physical activity was assessed during leisure time. How was this assessed? Further, was PA in leisure time different across the three categories of motivation? Provide also summary data for PA. Please also add where you retrieved data on demographics, EF etc.

• Response: This valid point has been addressed in table 1. There was indeed a positive trend correlating difference between motivation for physical activity and self-reported physical activity, although this was not significant.

• Comment 10: Questionnaires. How where questionnaires completed (online survey, interview, paper,...). Especially in case of paper and pencil - was there any missing data?

• Response: The questionnaires were primarily filled out online. One a few subjects filled out the questionnaire in a paper format as they did not have access to a computer. We have described the missing data in figure 1 as exclusions from the analyses. This comprised of 13 patients that did not answer.

• Comment 11: Rehabilitation program. Did you monitor your patients during the training session? If so, please provide details on what was monitored during training and whether patients were adherent to the prescribed intensity/duration/...of the exercise program

• Response: The patients were not monitored during the training sessions. The therapists supervised all training sessions and guided the patients based on the BORG scale. We have added this information to the methods section: rehabilitation program

• Comment 12: Please add the statistical tests used to evaluate normality of your data. Which data were not normally distributed?

• Response: I believe we have described this in under: Statistical analyses “Normally distributed variables were compared across the different levels of motivation using one-way ANOVA. Non-normally distributed variables were tested using Mann-Whitney and Kruskal-Wallis tests, while a Chi 2 test tested categorical data. Statistically significant differences between the groups were tested with pairwise comparisons using t test and Chi 2 tests.”

• Comment 13: It seems that Figure 1 is missing?

• Response: We apologize if this was not visible to you. It was in the compiled sheet approved before uploading. We will contact the editor to ensure that all figures are visible in the revised paper.

• Comment 14: Though I agree and understand that you should not repeating what is in the tables, yet somewhat more statistics and numerical data in the results section could improve the reading without having to go back to the table all the time.

• Response: We have tried to accommodate this by adding more numbers to the results section.

• Comment 15: In the discussion section, the different subsections of of motivation are discussed - though this is missing in the results section. please provide the results first before discussing it.

• Response: I do believe that we have described this in the results section: Constructs of motivation. Unless I am misunderstanding your comment

Reviewer #2:

This paper by Mikkelsen et al prospectively investigated the correlation of individual motivation for physical activity, determined as the summed RAI score by BREQ-2 questionnaire, and the cardio-pulmonary fitness, measured as VO2peak in a symptom-limited CPET, in 203 patients participating in an ambulatory cardiac rehabilitation (CR) program. They found that in contrast to other psychological determinants such as depression and anxiety, motivation was and independent predictor of VO2peak at baseline and predicted delta VO2peak from baseline to the end of CR. The authors conclude that motivation measured with the BREQ-2 questionnaire can be useful as a screening tool for

elderly cardiac patients undergoing CR to detect patients with lower potential to increase VO2peak.

The study addresses an important topic and provides interesting and clinically useful new data to the field of CR. The prospective study design is solid. The study, however, includes a very selected patient population (e.g. > 64 years, only 9 % current smokers, high level of education) that might not be representative for most CR cohorts.

Major points

• Comment 1: The main limitation of the study is its low patient number and its selective recruitment. Considering the study duration of 26 months, the inclusion of 203 patients seems rather low (average of < 8 patients/months). What is the size of the local CR program? Where patients recruited consecutively every day or dependent on the availability of the study staff?

• Response: This was a selective recruitment because this is a sub-study of the EU-CaRE trial that aimed for including patients >64 years which only is a little more than half of the patients being offered CR (. 40 % of the population is <64 years). Patients were recruited consecutively by the cardiologist and if the patient was eligible and wished to participate in CR they were asked to participate. Almost all CR patients agreed to participate. We did also publish this in an article with baseline data from the EU-CaRE cohort:

Prescott E, Mikkelsen N, Holdgaard A, Eser P, Marcin T, Wilhelm M, Gil CP, González-Juanatey JR, Moatemri F, Iliou MC, Schneider S, Schromm E, Zeymer U, Meindersma EP, Ardissino D, Kolkman EK, Prins LF, van der Velde AE, Van 't Hof AW, de Kluiver EP. Cardiac rehabilitation in the elderly patient in eight rehabilitation units in Western Europe: Baseline data from the EU-CaRE multicentre observational study. Eur J Prev Cardiol. 2019 Jul;26(10):1052-1063. doi: 10.1177/2047487319839819. Epub 2019 Mar 29. PMID: 30924688.

• Comment 2: A better motivation could result in the achievement of a higher respiratory exchange ratio (RER) in CPET. Did RAI correlate with RER. This relation should be presented in the data.

• Response: This was added to table 1. There was no significant difference between groups.

• Comment 3: Please specify the “multiple adjustment” made in the multiple adjusted model. Was the model also adjusted for diabetes, body mass index and activity level? If not, this should be done.

• Response: All relevant confounding variables describes in table 1 were tested in the multiple models to see if it made any significant change to the effect motivation had on peak VO2. We have added the confounding variables of interest in the statistical analyses section. The first model for baseline VO2peak was both adjusted for diabetes and self-reported physical activity at these had significant confounding impact. BMI was also tested, but not included as it did not impact the result. The first model for baseline VO2peak was both adjusted for diabetes and self-reported physical activity at these had significant confounding impact. BMI was also tested, but not included as it did not impact the result.

• Comment 4: Was there a signal of lower RAI in the 16 dropouts?

• Response: Thank you for this comment. There was an approximately even distribution among dropouts irrespectively of level of motivation. COPD and diabetes were associated with ending prematurely. This was not significant, probably due to low power of this analyses. We have added this to our results section

• Comment 5: Did the CR program had an impact on the RAI score? Providing data on RAI scores at baseline and after CR would be interesting

• Response: This is a very interesting comment. We only have data on the baseline motivation. But this bring a new interesting aspect to rehabilitation and motivation since motivation also can change over time when exposed to changes in life.

Minor points

• Comment 6: Why were patients < 64 years excluded? What is the percentage of patients < 64 years in the CR program

• Response: This is because this a Danish sub-study based on the EU-CaRE study which is a multi-country study on elderly cardiac patient >64 years of age. In this hospital rehabilitation app. 40 % of the population is <64 years.

• Comment 7: Appendix is missing

• Response: I am sorry for that. This must have been missed in the upload process. I will make sure it becomes available to you.

• Comment 8: Figure 1 should be presented as a flow chart

• Response: Valid point and this has been corrected.

• Comment 9: The low numbers of female participants should be stated as a limitation

• Response: Yes. This is a general limitation for rehabilitation, and we have added this to limitations.

25 Jul 2022

8 Sep 2022

Comment

Reviewer #4: Interesting study about a clinically elevant topic. Impaired adherence of CR programs is one of the major issues when planning this kind of health resources. Describing predictors of success is very important. We know that CR adherence is low, even in randomized trials. I suggest to cite

Sanchis J, Sastre C, Ruescas A, Ruiz V, Valero E, Bonanad C, García-Blas S, Fernández-Cisnal A, González J, Miñana G, Núñez J. Randomized Comparison of Exercise Intervention Versus Usual Care in Older Adult Patients with Frailty After Acute Myocardial Infarction. Am J Med. 2021 Mar;134(3):383-390.e2. doi: 10.1016/j.amjmed.2020.09.019.

Answer:

Thank you for providing this interesting reference. It is indeed what we see as well in our clinic and we have sited Sanchis et al in the “Introduction” section on page 3.

I have some minor comments to the authors

Comment:

-Please explain the cutt-of of age. In this sense, 64 years is a very young cut off to be designated as elderly

Answer:

Thank you for raising this question. We agree that in many patients a cut-off of 65 is relatively low, however, there is considerable biological variation. Age 65 is the age of retirement in many European countries. Most importantly, however, is that the cut-of age of more than 64 years was decided in the EU-CaRE study group, which this paper derived data from. As EU-CaRE was a multi-country program, the 8 different countries had to agree of an acceptable cut-of age that all countries could accept. The definition of elderly is subject to discussion and we appreciate your relevant comment.

Comment:

-When talking about patients at older ages, frailty, comorbidity and other geriatric syndromes are closely related to prognosis, to the need for CR and probably to the motivation for CR. I understand the authors do not have information about geriatric assessment. In this case, this should be included as a limitation of this study

Answer: Thank you for this comment. We have added this to our limitations as we did not have a direct geriatric assessment. However, all patients did consult a cardiologist before CR who assessed if the patient were capable, also mentally, to complete a CR program.

Comment:

-Finally the authos should clearly discuss the clinical implications of their findings. Which is the recommendation for patients with low motivation values?. Probably these are the patients which higher need for CR...

Answer:

This is an interesting point and we have elaborated on the implications on page 9 under discussion and “Motivation as a predictor of VO2peak before and after CR”

Submitted filename: Response to reviewers.docx

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11 Sep 2022

The motivation for physical activity is a predictor of VO2peak and is a useful parameter when determining the need for cardiac rehabilitation in an elderly cardiac population

PONE-D-21-02329R3

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19 Sep 2022

PONE-D-21-02329R3

The motivation for physical activity is a predictor of VO2peak and is a useful parameter when determining the need for cardiac rehabilitation in an elderly cardiac population

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