A common-sense model–based nursing intervention improves exercise compliance in coronary heart disease: a randomized controlled trial and a pilot study

Abstract

Aims:

This study explored the effects of a Common-sense model of self-regulation-based nursing intervention on enhancing cardiac exercise rehabilitation compliance in coronary heart disease patients, aiming to improve cardiac function and overall health outcomes.

Design:

This study was a two-arm, parallel prospective randomized controlled trial.

Methods:

Participants were recruited from February to August 2024 at 3 Hospitals in Changsha, Hunan, China. Participants in the intervention group received a nursing intervention based on a Common-sense model of self-regulation and routine health education, while those in the control group received routine health education only. The outcome variables included exercise compliance, level of exercise fear, brief illness perception, emotional regulation self-efficacy level, blood pressure, body mass index, six-minute walking test. Statistical methods used to analyze the data include t-test, non-parametric rank sum test.

Results:

77 participants completed the study. Compared to the control group (n = 38), the intervention group (n = 39) showed statistically significant improvements in the outcomes of exercise compliance, level of exercise fear, level of brief illness perception, level of emotion regulation self-efficacy, blood pressure, body mass index, six-minute walk test.

Conclusion:

A Common-sense model-based cardiac exercise rehabilitation compliance intervention effectively improves health outcomes in coronary heart disease patients and can be integrated into nursing practice to enhance clinical care.

Clinical Trial Registration:

identifier ChiCTR2400084280.

1 Introduction

Amid societal and economic progress, cardiovascular diseases (CVDs) have become a critical global health challenge, with prevalence showing a persistent upward trend (1). The World Health Organization (WHO) estimates that CVD-related deaths will surpass 25.5 million by the mid-21st century, with coronary heart disease (CHD) accounting for the majority of cases (2). CHD, a prevalent cardiac condition primarily resulting from cardiac dysfunction and organic lesions leading to insufficient myocardial blood supply, is characterized by high mortality and disability rates. Consequently, it imposes significant psychological and economic burdens on both affected individuals and their families (3).

Contemporary medical advancements facilitate prompt coronary revascularization, effectively restoring myocardial perfusion. Nevertheless, although these interventions confer short-term survival advantages, they fail to address the underlying risk factors for CHD, resulting in substantial long-term mortality (4). Some studies have shown that lifestyle modifications and risk factor management can significantly reduce the incidence of cardiovascular events and long-term mortality (5, 6). Consequently, the therapeutic focus has increasingly transitioned from acute-phase intervention and rescue to a comprehensive approach encompassing primary prevention and post-event rehabilitation (7). Exercise training constitutes a core component of contemporary cardiac rehabilitation (CR) programs (8). Exercise-centered cardiac rehabilitation has gained established consensus as a key strategy for both CHD prevention and post-event rehabilitation. Major cardiovascular societies, including the European Society of Cardiology, the American Heart Association and the American College of Cardiology all recommending exercise rehabilitation for patients with CHD based on the highest level of scientific evidence (Level I) (9, 10). Recent systematic reviews confirm both the safety and long-term efficacy of remote cardiac rehabilitation in coronary populations, underlining the urgency to develop personalized and scalable models (11).

Nursing interventions employing the Common-sense model of self-regulation（CSM）as a theoretical framework have demonstrated efficacy in enhancing self-regulatory behaviors and relevant health outcomes among individuals with various chronic diseases (12, 13). However, there is no such intervention to improve compliance to cardiac exercise rehabilitation and health outcomes in patients with CHD.

2 Background

Research demonstrates that exercise-based cardiac rehabilitation constitutes an effective secondary prevention strategy for CHD, improving cardiac rhythm, blood flow, blood pressure, and lipid profiles (14). Cardiac exercise rehabilitation controls cardiovascular disease risk factors and improves cardiac and coronary artery function. Furthermore, compared to non-exercise control groups, this intervention significantly reduces the risk of cardiovascular mortality and hospitalization, while improving health-related quality of life (15). Additionally, it promotes mental health by providing patients with a platform to address concerns, effectively alleviating anxiety (16).

Cardiac exercise rehabilitation compliance refers to the extent to which patients follow healthcare professionals' recommendations, including participation in rehabilitation programs, exercise training, dietary guidelines, medication regimens, and other prescribed behaviors (17). Exercise rehabilitation compliance is essential for achieving optimal therapeutic outcomes in CHD patients, yet their adherence rates are generally low (18). I Factors such as age, literacy, disease awareness, coping styles, psychological status, and disease-related uncertainty negatively impact CHD exercise rehabilitation compliance (19). Evidence indicates that diminished patient perception of disease symptoms and effects corresponds to reduced treatment compliance (20). Additionally, fear of exercise, commonly observed in CHD patients, substantially reduces cardiac rehabilitation participation, stemming from fears of precipitating cardiac events (21). Negative emotions and entrenched lifestyle habits among coronary artery disease patients frequently compromise long-term exercise compliance, however, support from peers and family can enhance participation motivation (22). Therefore, altering level of illness perception, level of exercise fear, and emotion regulation in patients with coronary artery disease can promote compliance to cardiac exercise rehabilitation.

The CSM provides a theoretical framework for examining the relationship between an individual's illness perception, coping, and health outcomes in the aftermath of an illness (Figure 1) (23). The CSM posits that individuals take action to mitigate health risks based on their subjective understanding and commonsense perceptions of health threats, providing a comprehensive framework for understanding the relationships between health threats, coping responses, and disease outcomes. The model comprises four interconnected components: (1) health threats, which encompass both internal indicators (e.g., physical symptoms) and external information sources (e.g., electronic media); (2) illness representation, consisting of cognitive and emotional dimensions that characterize health threats; (3) coping procedures, representing self-regulatory strategies developed in response to illness representations; and (4) outcome assessment, involving continuous evaluation of coping effectiveness throughout disease management. Compared to other health education models, CSM offers unique intervention targets across three phases (cognition, response, and assessment), leveraging both intrinsic and extrinsic motivation to enhance health beliefs and improve exercise rehabilitation adherence (24, 25).

Figure 1

Evidence demonstrates that interventions grounded in the Common-Sense Model of Self-Regulation facilitate the development of healthy behaviors and effective self-management practices to optimize health outcomes (26, 27), thereby improving their healthcare behaviors, compliance, quality of life, and alleviating their anxiety, depression and psychological distress (26, 28).

However, CSM is rarely used in health interventions for patients with CHD. Therefore, we undertook to address this gap by developing a CSM-based nursing intervention to improve the impact of compliance to cardiac exercise rehabilitation and health outcomes in Chinese CHD.

3 Methods

3.1 Study design

A two-arm, parallel prospective randomized controlled trial design was employed.

3.2 Aims

Aims of this study are (1) to develop a nursing intervention based on CSM and (2) to explore whether the intervention could improve exercise rehabilitation compliance and health outcomes.

3.3 Participants

Participants were recruited between February and August 2024 from 3 hospitals in Changsha, Hunan, China. Based on the study objectives, ethical considerations, the voluntary nature of participation, and required physical fitness levels, we established the following inclusion and exclusion criteria.

This two-arm, parallel, prospective randomized controlled trial recruited eligible participants prior to randomization to mitigate recruitment bias. A random number sequence generated in Excel was used to allocate patients sequentially to either the intervention or control group. During the intervention, 2 participants in the intervention group were lost (1 due to disease progression, unrelated to exercise rehabilitation; 1 due to work commitments), resulting in a 5.26% attrition rate. One control group participant was lost due to changed contact information (2.63% attrition). The final analysis included 77 participants: 38 in the intervention group and 39 in the control group (Figure 2).

Figure 2

3.4 The routine health education

Routine in-hospital health education, including the provision of CHD health education, cardiac exercise rehabilitation manuals and other materials; after discharge from the hospital, the researcher conducted a telephone follow-up, once a month, a total of three times, during which compliance to cardiac rehabilitation and any existing primary issues were assessed.

3.5 The nursing intervention

The intervention group received the same routine health education plus a nursing intervention based on the Common-sense model of self-regulation.

3.5.1 Building an intervention team

A multidisciplinary team with clearly delineated responsibilities was established. A doctoral supervisor oversaw intervention implementation, quality control, and study coordination. A cardiology chief nurse (associate chief superintendent nurse) coordinated staffing for the intervention components. Two cardiologists delivered training sessions and lectures. A rehabilitation therapist (associate rehabilitation therapist) guided patients' early-stage rehabilitation exercise. A psychotherapist managed patients' negative emotion. Two cardiology nurses conducted health education and assisted with post-discharge follow-up. Two nursing postgraduate students performed data collection and statistical analysis.

3.5.2 The intervention time

The 12-week intervention protocol, structured into three distinct phases, was designed in accordance with the Chinese Expert Consensus on Cardiac Rehabilitation and Secondary Prevention for Coronary Heart Disease. This duration aligns with standard clinical practice in China, where CHD patients typically undergo follow-up assessments at the 3-month mark (approximately 12 weeks).

Phase 1 (Week 1): Corresponds to the average hospitalization period for CHD patients, during which in-hospital rehabilitation guidance will be delivered.

Phase 2 (Weeks 2–8): Implements the post-discharge exercise rehabilitation program prior to the 3-month follow-up.

Phase 3 (Week 9–12): Phase 3 was timed to coincide with the 3-month follow-up assessment.

3.5.3 The intervention site

The intervention sites were categorized as in-hospital and out-of-hospital. The in-hospital sites comprised the cardiovascular medicine wards and the cardiac rehabilitation center, while out-of-hospital intervention was delivered remotely, primarily via WeChat groups and telephone follow-up.

3.5.4 Content of the intervention

The intervention program as shown in Table 1.

3.6 Outcome measures

In accordance with the aim of our study, we collected demographic data, the Exercise Compliance Questionnaire, the Fear of Exercise Scale for Patients with Coronary Artery Disease, the Brief Illness Perception Questionnaire, the Emotion Regulation Self-Efficacy Scale.

3.6.1 Exercise compliance questionnaire

The exercise compliance questionnaire was developed by XueLi (29), comprises three dimensions: physical exercise compliance, exercise monitoring compliance, and proactive advice-seeking compliance, totaling 12 items. A 4-point Likert scale was used, ranging from “Cannot do at all” (1) to “Can do completely” (4), with total scores ranging from 12 to 48. The Cronbach's alpha coefficient was 0.818.

3.6.2 The fear of exercise scale for patients with coronary artery disease, fact-CAD

The Fear of Exercise Scale for Patients with Coronary Artery Disease (Fact-CAD) was translated into Chinese by Cuiping Tian (30). A total of 19 items were used. Likert 5-point scale was used, from “never” to “always” were assigned 0–4 points, and the total score was 0–76 points, and some of the entries were reverse scored, the higher the score, the higher the level of exercise fear of the patients. The Cronbach's alpha coefficient of this scale was 0.901.

3.6.3 Brief illness perception questionnaire, BIPQ

The Simple Illness Perception Questionnaire (BIPQ) was developed by Broadbent (31), assesses cognitive, emotional, and understanding dimensions of illness perception. It includes 8 items scored on an 11-point scale and 1 open-ended question for listing perceived causes of the illness. Items 3, 4, and 7 are reverse-scored, with total scores (sum of items 1–8) indicating stronger perceived symptom severity and disease impact. The scale demonstrated a Cronbach's alpha of 0.831 and test-retest reliability of 0.931.

3.6.4 Emotion regulation self-efficacy scale

The Emotion Regulation Self-Efficacy Scale (ERSES) was developed by Caprara (32) and later translated by Shufeng Wen (33) to measure the degree to which patients with CHD feel confident in their ability to manage their emotions. The scale consists of 12 items, including self-efficacy for expressing positive emotions (4 items), self-efficacy for regulating anger/rage (4 items), and self-efficacy for regulating frustration/pain (4 items), and is rated on a 5-point scale from “very poorly” to “very well”. The scale is rated on a 5-point scale from “very unconformable” to “very conformable”, with scores ranging from 1 to 5 and 12 to 60, with higher scores indicating higher levels of self-management of emotions. The Cronbach's coefficient of the scale was 0.85, and the factor model fit was good.

3.7 Clinical health Status indicators

① Blood pressure: Patients whose blood pressure meets the standard (<65 years old, blood pressure <140/90 mmHg; ≥65 years old, blood pressure <150/90 mmHg). Patients whose blood pressure is not up to standard (<65 years old, blood pressure ≥140/90 mmHg; ≥ 65 years old, blood pressure ≥150/90 mmHg).

② Body Mass Index (BMI): BMI = weight (kg)/height 2 (m²), normal: 20.0–23.9 kg/m²; overweight: BMI 24.0–27.9 kg/m²; obese: BMI ≥ 28.0 kg/m².

③ Six-minute walking test (6MWT): evaluate the exercise endurance through 6-minute walking distance of patients to determine the cardiac function and prognosis. The 6MWT can be divided into 4 levels, level 1 < 300 m, level 2 is 300–374.9 m, level 3 is 375–449.9 m, and level 4 is ≥450 m. The higher the level, the better the cardiac function, and level 3 or 4 indicates that the cardiac function is close to or has reached the normal level.

3.8 Procedure and data collection

Data were collected three times: at baseline (1 week before the intervention) and at follow-up (weeks 4 and 12 after the intervention).

Data were collected in participants' homes or hospital. Participants completed questionnaires by themselves or with some assistance from a researcher. It took about 30–40 min to complete the questionnaires. Data on clinical indicators were collected by hospital nurses.

3.9 Statistical analysis

SPSS 27.0 software was used for statistical description and analysis of this study. The statistical methods are as follows:

Comparison of patients “general data before intervention: the measured data obeys normal distribution with chi-square and is described by mean ± standard deviation, otherwise it is described by median and interquartile spacing; the count data in patients” general data is described by percentage.

Comparison of pre-intervention baseline data and post-intervention data at 2 time points: the data were quantitative data, and two independent samples t-test was used if the data conformed to normal distribution, and non-parametric rank-sum test was used for the quantitative data that did not obey normal distribution.

4 Results

4.1 Participants

Table 2 shows the self-reported characteristics of the 77 participants (42 males and 35 females) who completed the study. The mean age of the intervention group was 71 (67.8, 74.3) years and the mean age of the control group was 71 (65, 75) years. The largest proportion of participants for each characteristic were married (88.3%), had primary school education or less (66.2%), lived with family (88.3%), lived in urban areas (57.1%), retired (61.0%), had a household economic income >4000RMB (55.8%), had urban and rural health insurance (59.7%), had no usual exercise habits 62.3%), and stable coronary heart disease (61.0%), no experience of PCI treatment (81.8%), no experience of CABG (80.5%), duration of coronary artery disease >5 years (39.0%), 2 hospitalizations for coronary artery disease (51.9%), cardiac function class 2 (81.8%), and coronary artery disease in combination with 2 other chronic diseases (41.6%); Table 2). Differences between the two groups in all demographic and disease-related characteristics were not statistically significant (all p > 0.05).

4.2 The effect of the nursing intervention on participants' exercise compliance

At the pre-test, the difference between the total exercise compliance score and the scores of all dimensions was not statistically significant when comparing the control group and the intervention group [t = (−0.850) – (−0.375), all p > 0.05]. At posttest, the intervention group at T1 had significantly higher total exercise compliance scores and scores on all dimensions (except exercise monitoring compliance) than the control group, with total exercise compliance scores (t = 5.272, p < 0.001); physical exercise compliance (t = 4.612, p < 0.001); exercise monitoring compliance (Z = −1.396, p > 0.05); and active advice-seeking compliance (Z = −2.219, p < 0.05). The total exercise compliance score and all dimension scores (except exercise monitoring compliance) were significantly higher in the intervention group than in the control group at T2, with total exercise compliance (Z = −4,744, p < 0.001); physical exercise compliance (t = 5.597, p < 0.001); exercise monitoring compliance (t = 0.948, p > 0.05); active advice seeking compliance (Z = −2.253, p < 0.05); overall, the differences were statistically significant (p < 0.05) for all dimensions except exercise monitoring compliance at 1 month post-intervention and 3 months post-intervention (Table 3).

4.3 The effect of the nursing intervention on participants' fear of exercise

At the pre-test, the difference between the total score fear of exercise and the scores of all dimensions was not statistically significant when comparing the control group and the intervention group [t = 1.002, Z = (−1.718) −(−0.477), all p > 0.05]. At posttest, the intervention group at T1 had significantly higher total exercise compliance scores and scores on all dimensions (except exercise avoidance) than the control group, with total exercise fear scores (t = −4.262, p < 0.001); danger perception (Z = −3.039, p < 0.05); exercise fear (Z = −3.308, p < 0.05); and exercise avoidance (t = −0.358, p > 0.05); dysfunction (Z = −2.114, p < 0.05). The intervention group in T₂ had significantly higher total motor fear scores and scores on all dimensions than the control group, with total motor fear (Z = −6.464, p < 0.001); danger perception (Z = −4.761, p < 0.001); motor fear (Z = −4.56, p < 0.001); motor avoidance (Z = - 3.114, p < 0.05); and dysfunction (Z = −2.686, p < 0.05). Overall, except for the motor avoidance dimension at 1 month post-intervention, the differences were statistically significant (p < 0.05) at 1 month post-intervention and 3 months post-intervention for all other dimensions (Table 4).

4.4 The effect of the nursing intervention on participants' brief illness perception

At the pre-test, the difference in BIPQ total scores and scores of all dimensions was not statistically significant when comparing the control and intervention groups [t = 1.353, Z = (−1.891)-(−0.202), all p > 0.05]. At posttest, the intervention group at T1 had significantly higher BIPQ total scores and scores on all dimensions (except duration) than the control group, with BIPQ total scores (t = −5.095, p < 0.001); outcome (t = −6.400, p < 0.001); duration (Z = −1.208, p > 0.05); and personal control (Z = −5.579, p < 0.001); Disease control (Z = −2.679, p < 0.05); Symptoms (Z = −6.17, p < 0.001); Attention (Z = −2.928, p < 0.05); Understanding (Z = −3.267, p < 0.05); and Mood (Z = −5.497, p < 0.001). The intervention group of T2 had a significantly higher BIPQ total score and scores on all dimensions (except duration, disease control) were significantly higher than those of the control group, BIPQ total score (t = −8.065, p < 0.001); outcome (Z = −6.799, p < 0.001); duration (Z = −1.338, p > 0.05); personal control (Z = −6.35, p < 0.001); disease control (Z = −1.421, p > 0.05); symptoms (Z = −6.752, p < 0.001); attention (Z = −3.957, p < 0.001); understanding (Z = −6.469, p < 0.001); and mood (Z = −7.530, p < 0.001). Overall, the differences were statistically significant (p < 0.05) for all dimensions at 1 month post-intervention and 3 months post-intervention, with the exception of the differences at 2 post-intervention time points for duration and 3 months post-intervention for disease control, which were not statistically significant (Table 5).

4.5 The effect of the nursing intervention on participants' emotion regulation self-efficacy

At the pre-test, the difference between the control group and the intervention group in terms of total emotion regulation self-efficacy score and scores of each dimension was not statistically significant [t = −1.461, Z = (−1.74) −(−0.681), all p > 0.05]. At posttest, the intervention group at T1 had significantly higher total emotion regulation self-efficacy scores and scores on all dimensions than the control group, with total emotion regulation self-efficacy (Z = −4.889, p < 0.001); positive (Z = −5.356, p < 0.001); and frustration (Z = −3.93, p < 0.001); and anger (Z = −3.428, p < 0.05).The intervention group of T2 had significantly higher emotion regulation self-efficacy total scores and scores on all dimensions (except exercise monitoring compliance) than the control group, with the EMOTION REGULATION SELF efficacy total score (Z = −7.534, p < 0.001); positive (Z = −7.604, p < 0.001); frustration (Z = −7.304, p < 0.001); and anger (Z = −1.328, p > 0.05). Overall, except for the self-efficacy score for regulating angry emotions, for which the difference in data at 3 months post-intervention was not statistically significant, the differences in all other dimensions were statistically significant (p < 0.05) at 1 month post-intervention and 3 months post-intervention (Table 6).

4.6 The effect of the nursing intervention on participants' BP, BMI, 6MWT

The results showed that the difference in blood pressure was statistically significant when comparing the two groups at 1 month and 3 months after intervention (P < 0.05); the body indices of the two groups were analyzed at 1 month and 3 months after intervention, and the results showed that the difference was statistically significant at 3 months after intervention (P < 0.05); the 6MWT scores of the two groups of patients were analyzed at 1 month and 3 months after intervention, and the results showed that the difference was statistically significant (P < 0.05) (Table 7).

5 Discussion

This is the first study to evaluate the impact of a nursing intervention based on a common-sense model of self-regulation on compliance to cardiac exercise rehabilitation in Chinese patients with CHD. Results demonstrated that the 12-week intervention significantly improved participants' exercise compliance, emotion regulation self-efficacy, and reduced participants' fear of exercise, brief ill perception. Participants’ blood pressure, BMI, and 6MWT were significantly improved.

5.1 Improved exercise compliance

Our findings showed that the intervention significantly increased participants' exercise compliance, aligning with prior studies (34, 35). First, according to the CSM theoretical framework, we facilitated patients' development of accurate illness perceptions and recovery expectations, thereby enhancing rehabilitation engagement. A multimodal intervention protocol—incorporating bedside coaching, rehabilitation room coaching, WeChat, phone calls, text messages, and outpatient reviews—enabled continuous participant communication and progress monitoring. Tailored exercise regimens were implemented based on participants' rehabilitation settings (inpatient/outpatient), participants were encouraged to perform more aerobic and resistance exercises, flexibility exercises, etc., which helped maintain their enthusiasm for exercise. In addition, the use of exercise bracelets and WeChat campaigns to monitor exercise indicators, along with timely adjustments to the program based on the participant's exercise situation helped to promote exercise compliance among the participants (36).

5.2 Improved emotion regulation self-efficacy

Our intervention employed a participant-centered approach, focusing on patients' dynamic mood fluctuations and avoiding didactic health education methods. The results demonstrate that this intervention significantly enhanced participants' emotion regulation self-efficacy. We used various forms of emotion regulation (e.g., role modelling, self-expression) to enhance participants' awareness of the role of self-efficacy in emotion regulation, encourage active regulation of maladaptive emotions, and foster recovery motivation (37). Multiple emotion regulation techniques were employed to enhance participants' awareness of self-efficacy in emotion regulation, promote active regulation of maladaptive emotions, and foster recovery motivation. Additionally, patients who demonstrated superior outcomes in prior exercise rehabilitation programs were recruited to share experiences via online platforms, highlighting the role of peer support in bolstering patients' confidence in emotion regulation self-management (38).

5.3 Improved blood pressure, BMI, and 6MWT

Our intervention demonstrated efficacy in enhancing systemic blood pressure, body mass index, and 6MWT outcomes, consistent with previous findings (39). Although no statistically significant difference in BMI was observed between the two participant groups at baseline (T₁), a sustained intervention resulted in a statistically significant intergroup difference at T₂. Throughout the intervention, nurses disseminated diet and exercise education materials via the WeChat platform, consistently emphasizing that adopting a low-fat diet and regular exercise could improve health indicators—blood pressure, BMI, and 6MWT (40, 41). They regularly monitored and encouraged participants' health behaviors while engaging family members to provide supplementary support. Studies show women with low heart rate variability (HRV) report greater emotion regulation difficulties than men with low HRV. Conversely, women with high HRV report slightly fewer difficulties than all men. Understanding neurophysiological sex differences in emotion regulation may thus aid daily emotion management, enhancing well-being (42). Furthermore, men and women responded similarly to cardiac rehabilitation for most physiological measures. However, men showed greater improvements in maximal oxygen uptake, functional capacity, 6MWT, and handgrip strength (43). This likely results from sex differences in physiology and body composition, giving men better adaptation in some areas. These findings highlight sex differences' importance, necessitating greater attention in cardiac rehabilitation planning. However, our trial aimed to assess overall intervention effects, with analysis focused on intergroup comparisons (intervention vs. control). Future multicenter trials must prioritize this to fully understand sex differences in cardiac rehabilitation.

5.4 Reduced fear of exercise

Evidence indicates that the fear of aerobic exercise is most pronounced in cardiovascular disease patients, where perceived disease status amplifies uncertainty regarding physical sensations (44). The intervention was found effective in reducing exercise fear among participants. Patients received detailed explanations on exercise rehabilitation safety, and exercise programs were modified in real-time according to individual profiles to enhance perceived security. Additionally, the intervention reduced illness perception, ultimately decreasing exercise fear—a result aligning with prior research findings (45). Furthermore, family members provided supplementary support that potentially contributed to reducing patients' fear toward movement.

5.5 Reduced ill perception

Our intervention effectively reduced participants' illness perception. We assessed participants' level of illness perception to identify negative emotions early, assisting patients in developing positive coping styles to channel and release such emotions. In addition, we implemented measures to stimulate health beliefs (e.g., conducting lectures and distributing educational brochures) and guided positive illness reappraisal to improve illness perception. Many studies have demonstrated that reducing illness perception and motivating patients to adopt positive coping strategies can improve their health behaviors and exercise compliance (45, 46).

5.6 Development of telehealth cardiac rehabilitation

Strong evidence supports cardiac rehabilitation (CR) as a clinically effective and cost-effective intervention for most cardiovascular patients. Home-based and technology-supported CR models, increasingly evidenced as alternatives or adjuncts to traditional center-based programs, offer scalable, affordable solutions, particularly in low- and middle-income countries with limited CR access (6). Telehealth CR is a feasible and effective alternative to conventional outpatient CR (47), with demonstrated long-term efficacy in coronary artery disease patients (11). The home- (±digital/telehealth platforms) and centre-based forms of cardiac rehabilitation formally supported by healthcare staff effectively improve clinical and health-related quality of life outcomes in cardiovascular patients (48). Additionally, mobile health solutions enhance patient care and operational efficiency (49).

A Common-Sense Model (CSM)-based nursing intervention significantly improved exercise adherence in coronary heart disease (CHD) patients. This evidence-based approach can be integrated into telehealth CR platforms to overcome access barriers. Incorporating CSM's self-regulation principles—targeting illness perceptions and coping procedures—into remote programs addresses unmet rehabilitation needs in resource-limited settings. Particularly in developing countries with low traditional CR access, telehealth CR utilizing this model provides a scalable approach to expand coverage, reduce costs, and standardize care globally. The intervention's established efficacy offers a framework for enhancing remote CR systems.

6 Strengths

This pioneering study is the first globally to apply the CSM to enhance cardiac exercise rehabilitation compliance in CHD patients. Our hospital-led, home-based model bridges hospital and home care, addressing patient barriers like time constraints, distance, and costs, while overcoming hospital limitations such as space, equipment, and staff shortages. Multimodal communication—face-to-face, telephone, and online platforms—diversifies health education and improves patient engagement.

7 Limitation

Several limitations exist in our study. The sample size was small and all participants in one city. Thus, the sample were not representative of patients with CHD in other settings or in other regions of China. Should the intervention time be extended, some of the intervention effects could have been different. Moreover, future multicenter trials could explore gender differences in cardiac rehabilitation in depth to enhance the effectiveness of personalized implementation of intervention programs.

8 Conclusion

In conclusion, CSM-based nursing interventions can improve CHD cardiac exercise rehabilitation compliance and health outcomes. This pioneering study deploys a hospital-led home-based model that overcomes patient accessibility barriers and institutional resource constraints via multimodal engagement to significantly enhance CHD rehabilitation compliance. This study provides a reference for future enhancement of health education and intervention for patients with CHD. The use of larger representative samples and longer intervention periods should be considered in future studies.

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