Effect of a Self‐Regulation Skills Training Program on Cognitive Flexibility in Patients With Heart Failure: A Randomized Controlled Trial

ABSTRACT

Background

Psychological well‐being is a critical component of disease management and recovery in patients with cardiovascular disorders. Cognitive flexibility, as a key psychological determinant, significantly influences adaptive functioning and health‐related outcomes. Self‐regulation skills training has recently gained attention as an effective approach to enhancing mental health in individuals with chronic illnesses. This study aimed to assess the effect of a self‐regulation skills training program on improving cognitive flexibility among patients with heart failure.

Materials and Methods

This randomized controlled trial included 69 hospitalized patients with heart failure who were randomly assigned to an intervention group (n = 35) or a control group (n = 34). Cognitive flexibility was assessed at baseline, immediately after the intervention, and 1 month later using the Cognitive Flexibility Inventory. The intervention group received six sessions of self‐regulation skills training over 3 weeks. The data were analyzed using SPSS software with independent t‐tests, chi‐square tests, Mann–Whitney tests, and repeated‐measures ANOVA. This trial was registered in the Iranian Registry of Clinical Trials (IRCT20160927030002N4).

Results

The findings demonstrated a significant time × group interaction for total cognitive flexibility scores (F [2,66] = 16.66, p < 0.001, partial η² = 0.34). Immediately afterward, the intervention group showed significantly higher cognitive flexibility compared with those of the control group (mean difference = 8.78 points; 95% CI: 3.64–13.92; Cohen's d = 0.80). At 1‐month follow‐up, the cognitive flexibility scores in the intervention group showed a slight decline compared with post‐intervention levels but remained modestly higher than baseline, whereas no meaningful change was observed in the control group.

Conclusions

The findings suggest that self‐regulation skills training may serve as an effective intervention for enhancing cognitive flexibility and supporting the psychological well‐being of patients with heart failure.

1. Introduction

In recent decades, chronic conditions have surpassed acute and infectious diseases as the leading causes of morbidity and mortality [1]. Cardiovascular diseases, including heart failure, remain the foremost global health challenge, accounting for nearly 20 million deaths worldwide annually [2]. Among cardiovascular disorders, heart failure is particularly prevalent, affecting over 64 million people globally and representing a major public health concern [3]. Beyond the direct health burdens, cardiovascular diseases impose substantial social, economic, and psychological impacts on patients, caregivers, and healthcare systems, with the indirect costs estimated at over $200 billion annually [4, 5].

Heart failure is accompanied by physical limitations, functional impairments, and psychological distress [6]. Frequent hospitalizations, high healthcare costs, and reduced social and occupational functioning exacerbate mental strain, affecting physical health outcomes [7]. Effective management therefore requires a comprehensive biopsychosocial approach, though clinical practice often emphasizes biological aspects [8]. Research evidence indicates that addressing psychosocial health in cardiovascular patients can reduce depression, mortality, and cardiac complications, ultimately improving overall disease management [9, 10].

Cognitive flexibility has emerged as a critical psychological construct and refers to the ability of adapting thoughts and behaviors in response to changing environmental demands, particularly psychological stress and challenges [11]. Evidence indicates that approximately 30%–80% of individuals with heart failure experience varying degrees of cognitive dysfunction, suggesting that heart failure may adversely affect cognitive processes, including cognitive flexibility, and underscoring the need for targeted psychological attention in patient care [12].

In recent years, self‐regulation has emerged as a key intervention skill for managing life events and adaptation, particularly among individuals with chronic illnesses [13]. Grounded in social‐cognitive theory, self‐regulatory skills facilitate behavioral change through structured processes of self‐monitoring, evaluation, and adaptive response, supporting goal attainment and self‐efficacy [14]. Miller et al. [15] demonstrated the efficacy of self‐regulation interventions in alleviating disease‐related distress among individuals with diabetes. Likewise, Tao et al. [16] provided evidence that a self‐regulation theory‐based intervention effectively enhanced self‐management in patients undergoing hemodialysis. Furthermore, NikManesh et al. [17] investigated the role of self‐regulation in improving quality of life and illness perception among patients with breast cancer.

Despite the recognized significance of self‐regulation as a psychological construct, few studies have investigated the effects of self‐regulation programs on psychological outcomes in patients with cardiovascular disease. While some research has examined outcomes such as self‐care [18], emotional well‐being, self‐efficacy [19], depression, anxiety [20], and self‐confidence [14], other critical psychological variables, particularly cognitive flexibility, have received little attention. To the best of our knowledge, no randomized controlled trials have specifically examined the impact of self‐regulation skills training on cognitive flexibility in patients with heart failure. Given the important role of cognitive flexibility in chronic illness [21], this study evaluated the effectiveness of a structured self‐regulation skills enhancement program in patients with heart failure. We hypothesized that the intervention group would show greater improvements in cognitive flexibility than the control group.

2. Materials and Methods

This study was a randomized controlled trial (IRCT20160927030002N4) with a pretest–post‐test design and a 1‐month follow‐up conducted from January to July 2025. The participants were hospitalized male and female patients with heart failure at three teaching hospitals affiliated with Isfahan University of Medical Sciences, Iran. They were Shahid Chamran Educational‐Therapeutic Center, Ali Asghar Educational‐Therapeutic Complex, and Al‐Zahra Educational‐Therapeutic Center.

The inclusion criteria were a cardiologist‐confirmed diagnosis of heart failure, age between 35 and 70 years [22], and classification as class II–IV heart failure. Participants were required to reside in Isfahan and provide informed consent. They also had to communicate verbally in Persian and complete the questionnaires. Participants with prior participation in similar educational or research programs were excluded. Those with intellectual disability or cognitive impairment that could interfere with learning were also excluded. The exclusion criteria were unwillingness to continue participation, death, absence from two or more intervention sessions, or inability to attend any sessions, and incomplete completion of 20% or more of the questionnaires data.

Participants were selected based on a convenience sampling method and subsequently randomly assigned to the intervention and control groups. Random allocation was performed using a computer‐generated random sequence in SPSS software by an independent researcher who was not involved in participant recruitment or intervention delivery. Allocation concealment was ensured using sealed, opaque, sequentially numbered envelopes to prevent guessing of group assignment. Due to the nature of the educational intervention, blinding of participants and intervention providers was not feasible. However, outcome assessment and statistical analysis were performed by a researcher who was blinded to group allocation to minimize assessment and analysis bias.

The sample size was calculated based on a comparison of mean cognitive flexibility scores between the two independent groups, using data from a previous similar study [23]. A two‐sided significance level of 0.05 (Z₁ = 1.96) and a statistical power of 80% (Z₂ = 0.84) were assumed. The required sample size was estimated using the following formula: n = [(Z₁ + Z₂)² × (S₁ ² + S₂ ²)]/d². In this formula, S₁ and S₂ represent the estimated standard deviations of cognitive flexibility scores in the intervention and control groups (9.72 and 14.19, respectively). The minimum clinically meaningful difference between the group means (d) was set at 8.5. The minimum required sample size was 32 participants per group. To account for an anticipated attrition rate of approximately 10%, 35 participants were recruited for each group. During the study, one participant in the control group died, leaving 34 participants for the final data analysis (Figure 1).

Figure 1.

CONSORT flow diagram.

The first part of the questionnaire assessed demographic and clinical characteristics, including age, gender, marital status, disease duration, hospitalization history, angiography, pacemaker implantation, comorbidities, and surgical history. The second part consisted of the Cognitive Flexibility Inventory (CFI), a 20‐item measure developed by Dennis and Vander Wal in 2010. It consisted of three scales: perceived controllability, behavioral justification, and perception of alternative options [24]. Items were rated on a 7‐point Likert scale, with higher scores indicating greater cognitive flexibility. The Persian version validated by Shareh et al. [25] demonstrated strong psychometric properties (Cronbach's α = 0.90; test–retest reliability = 0.71) and satisfactory factorial, convergent (r = 0.67), and concurrent validity (r = –0.50). The self‐regulation skills program was developed based on relevant literature and the self‐regulation chapter of the Psychology Handbook [26] under the supervision of the principal investigator and approved by five faculty members of Isfahan University of Medical Sciences (Table 1). After recruitment, each participant received the study information and provided a written informed consent. The baseline demographic and CFI forms were completed, and 70 eligible patients were randomly assigned to intervention (n = 35) or control (n = 35) groups. The intervention group attended six 45‐min in‐person sessions over 3 weeks, delivered in groups of 5–10 participants using lectures, discussions, and assignments, while the control group received routine care. Post‐test and follow‐up assessments were conducted for both groups, and the intervention materials were provided to the control group later.

Table 1.

Summary of the self‐regulation skills enhancement program sessions.

Session	Content
Session 1	Introduction to the study and its objectives, familiarization with the researcher, group members, and group rules. Introduction to the concept of self‐regulation and its importance in managing heart failure. Completion of baseline questionnaires, Q&A, and expression of participants’ goals and expectations.
Session 2	Training in time management and planning skills. Homework: Identify one maladaptive behavior and plan strategies to address it.
Session 3	Education on stress as a risk factor for cardiovascular disease and management through muscle relaxation and deep breathing techniques. Homework: Study the muscle relaxation guideline sheet.
Session 4	Problem‐solving skills training. Homework: Practice the cost‐benefit table.
Session 5	Application of behavioral principles: reinforcement and self‐reward to maintain adherence to the training program. Training in small steps approach to achieve larger goals. Homework: Write down and assign rewards for personal achievements.
Session 6	Summary of all sessions, Q&A, review of participants’ suggestions and feedback. Completion of post‐intervention questionnaires and recognition of participants.

The study data were analyzed using IBM SPSS Statistics for Windows, version 22 (IBM Corp., Armonk, NY, USA). Descriptive statistics were used to summarize demographic and clinical characteristics. The baseline differences between the intervention and control groups were examined using independent t‐tests, chi‐square tests, or Mann–Whitney U tests, as appropriate. Changes in cognitive flexibility scores over time were analyzed using repeated‐measures analysis of variance (RM‐ANOVA), with time being the within‐subject factor and group being the between‐subject factor. The assumptions of normality and sphericity were assessed prior to conducting RM‐ANOVA using the Shapiro–Wilk test and Mauchly's test, respectively. Greenhouse–Geisser corrections were applied when the assumption of sphericity was violated. Effect sizes for the main and interaction effects were reported using partial eta squared (η²). Statistical significance was set at p < 0.05.

2.1. Ethical Considerations

This study was approved by the Ethics Committee of Isfahan University of Medical Sciences (approval ID: IR. MUI. NUREMA. REC.1403.16). Written informed consent was obtained from all participants, and data confidentiality was strictly maintained. Following study completion, the control group received the educational materials.

3. Results

A total of 69 patients with heart failure (35 in the intervention and 34 in the control groups) completed the study tasks. One participant from the control group died during the intervention period. The mean age of participants in the intervention group was 48.77 ± 11.27 years, while the mean age in the control group was 52.68 ± 12.18 years. There were no statistically significant differences between the two groups in terms of demographic or clinical characteristics, including age, gender, disease duration, marital status, economic status, history of surgery, angiography, comorbidities, hospitalization, or pacemaker implantation (Chi‐square, Mann‐Whitney, and independent t‐tests, p > 0.05) (Table 2).

Table 2.

Comparison of demographic characteristics between the intervention and control groups.

Variable	Control group	Experimental group	p‐value
Age (years); Mean (SD)	52.68 (12.18)	48.77 (11.27)	0.17
Disease duration (months)	42.38 (10.99)	40.23 (6.29)	0.86
Gender; n (%)			0.44
Male	27 (79.4%)	25 (71.4%)
Female	7 (20.6%)	10 (28.6%)
Marital status; n (%)			0.99
Single	3 (8.8%)	3 (8.6%)
Married	31 (91.2%)	32 (91.4%)
History of hospitalization; n (%)	27 (79.4%)	33 (94.3%)	0.08
History of surgery; n (%)	16 (47.1%)	23 (65.7%)	0.12
History of angiography; n (%)	21 (61.8%)	24 (68.6%)	0.55
Pacemaker implantation; n (%)	6 (17.6%)	2 (5.7%)	0.15
History of other diseases; n (%)	19 (55.9%)	17 (48.6%)	0.54
Economic status; n (%)			0.58
Poor	5 (14.7%)	3 (8.6%)
Moderate	26 (76.5%)	29 (82.9%)
Good	3 (8.8%)	3 (8.6%)

RM‐ANOVA revealed a statistically significant time × group interaction effect on total cognitive flexibility scores (F [2,66] = 16.66, p < 0.001, partial η² = 0.34), indicating differential changes over time between the intervention and control groups. The results indicated that the mean scores of total cognitive flexibility and its subscales showed statistically significant, albeit modest, changes over time, and the magnitude of these changes was greater in the intervention group compared to the control group. Furthermore, the post‐intervention mean scores were significantly higher than baseline, with a slight decline at 1‐month follow‐up, though still being above the pretest level (Table 3).

Table 3.

Comparison of cognitive flexibility scores and its domains before, immediately after, and 1 month after intervention between experimental and control groups.

Variable	Time	Control group mean (SD)	Experimental group mean (SD)	Time effect F (df)	p	Time × group interaction F (df)	p
Total cognitive flexibility score	Before intervention	94.23 (22.79)	95.14 (17.84)	17.63 (2.66)	< 0.001	16.66 (2.66)	< 0.001
	Immediately after intervention	94.26 (21.88)	111.80 (17.06)
	One month after intervention	94.09 (18.95)	99.80 (19.51)
Perceived controllability	Before intervention	32.85 (12.20)	33.14 (9.42)	22.64 (2.66)	< 0.001	17.94 (2.66)	< 0.001
	Immediately after intervention	33.79 (11.87)	42.57 (10.00)
	One month after intervention	33.91 (10.09)	34.74 (9.69)
Perceived behavioral justification	Before intervention	8.68 (3.28)	8.40 (2.85)	4.18 (2.66)	0.02	6.01 (2.66)	0.004
	Immediately after intervention	8.18 (3.19)	10.14 (2.98)
	One month after intervention	8.06 (3.39)	8.89 (2.60)
Perceived options	Before intervention	52.50 (11.21)	53.60 (11.56)	3.29 (2.66)	0.04	3.77 (2.66)	0.03
	Immediately after intervention	52.29 (10.40)	59.09 (8.23)
	One month after intervention	52.12 (9.21)	56.17 (12.68)

4. Discussion

The present study investigated the impact of a self‐regulation skills enhancement program on cognitive flexibility in patients with heart failure. The results indicated that implementing such a program can significantly improve cognitive flexibility in this patient population. Although research on the effects of self‐regulation‐based interventions on cognitive flexibility among heart failure patients remains limited, available studies in other populations, notably among students, support the efficacy of these interventions on enhancing various mental health indicators. For instance, Rahmati et al. [27] demonstrated that teaching self‐regulation strategies improved cognitive flexibility and reflective thinking in students. Similarly, Shikhan and Nouri [28] reported that self‐regulation‐based interventions enhanced cognitive flexibility in students addicted to social media. Additionally, Abbasi et al. [29] showed that metacognitive empowerment effectively improved cognitive flexibility, information processing speed, cognitive inhibition, and selective attention in students. However, a limited number of studies have reported no significant effects of educational interventions on cognitive flexibility. For instance, Biotenweg et al. [30] and Castro et al. [31] found that psychological educational interventions did not significantly impact cognitive flexibility, which contrasts with the findings of the present study. The primary reason for this discrepancy appears to be that these interventions focused on specific skills rather than general executive processes, combined with their relatively short duration and low intensity. Consequently, such interventions tend to improve the targeted skills without leading to a broader enhancement of overall cognitive flexibility.

Our study findings suggest that teaching self‐regulation skills—a cognitive‐behavioral intervention—enhances patients’ capacity to manage psychological stress and disease‐related challenges. Self‐regulation involves monitoring and adjusting thoughts, emotions, and behaviors to meet therapeutic goals [32]. In cardiac patients, who often experience anxiety, helplessness, and emotional instability [33], reinforcing these skills allows a cognitive pause between stressors and emotional responses, facilitating adaptive coping through cognitive reappraisal [34]. Mechanistically, self‐regulation training engages executive functions such as working memory, selective attention, planning, and problem‐solving, while promoting effective emotional regulation and reducing maladaptive reactions. Cognitive reappraisal further enables patients to evaluate situations from multiple perspectives, integrating physical, emotional, and behavioral information to select adaptive responses. Neurobiologically, these effects likely reflect enhanced activation and connectivity in prefrontal and executive control networks, supporting cognitive flexibility, response inhibition, and decision‐making. Together, these cognitive and neural mechanisms provide a theoretical framework for the observed improvements in adaptive coping and decision‐making following self‐regulation training [35].

The study results further indicate that enhancing self‐regulation skills positively influences deeper aspects of cognitive functioning, notably improving multiple dimensions of cognitive flexibility. In particular, training increased patients’ awareness of alternative options, broadening their perspective on behavioral and cognitive choices amid the physical and psychological constraints of heart failure. During sessions, patients learned to apply multiple coping strategies—such as cognitive reappraisal, relaxation techniques, and problem‐solving—when facing physical symptoms or negative thoughts. These findings align with those of Holzer et al. [36], who demonstrated that interventions targeting cognitive flexibility enable participants to utilize a wider range of adaptive coping strategies through cognitive restructuring. In the second dimension, perceived controllability, the intervention enhanced patients’ sense of agency and empowerment in managing disease‐related challenges. Through exercises such as realistic goal setting, time management, and evaluating behavioral consequences, self‐regulation training strengthened patients’ mastery and perceived control over difficult situations. These findings are consistent with Hsu et al. [14], who reported that self‐regulation exercises improve self‐care skills, supporting enhanced capability, situational control, and goal management. In the third dimension, perceived justification of behavior, the intervention helped patients recognize multiple explanations for life events and their own actions. Cognitive‐behavioral exercises facilitated multidimensional appraisal and reinterpretation, encouraging patients to consider not only physical symptoms but also cognitive and behavioral factors. These results are in line with Edwin et al. [37], who reported that therapeutic interventions broaden patients’ understanding of pain by integrating physical, behavioral, and cognitive perspectives.

This study addresses an important gap regarding the effects of self‐regulation skill enhancement on cognitive flexibility in patients with heart failure, a group experiencing significant psychological and physiological burden. Although interest in self‐regulation interventions has grown, evidence on their influence on cognitive flexibility in clinical populations remains limited. Given its central role in adaptive coping, decision‐making, and psychological resilience, evaluating structured self‐regulation training is both timely and essential. The findings deepen the theoretical understanding of cognitive and behavioral adaptation in chronic illness and offer practical guidance for developing targeted psychotherapeutic strategies to improve mental health and quality of life in cardiac patients. Future research should adopt rigorous longitudinal and randomized designs, include multimodal cognitive and neuropsychological assessments, and examine mediators such as emotional regulation, resilience, and executive functioning. Such approaches can strengthen the evidence base and clarify the mechanisms through which self‐regulation enhances cognitive flexibility and adaptive coping.

Despite the encouraging findings, several limitations can be noted in this study design. First, the short follow‐up period (1 month) precluded assessment of long‐term effects, highlighting the need for extended longitudinal studies. Second, reliance on self‐report measures may have introduced response biases or been influenced by patients’ psychological states, potentially affecting accuracy. Finally, the sample size, while sufficient for preliminary evaluation, may limit generalizability to broader clinical populations. Future studies should employ larger samples, multimodal assessments, and objective behavioral or neurocognitive measures to strengthen the evidence base.

5. Conclusion

This study demonstrated that a self‐regulation skills enhancement program significantly improved cognitive flexibility in patients with heart failure. These findings suggest that self‐regulation–based interventions may support psychological functioning in this population, warranting further investigation into their long‐term effects.

Author Contributions

Erfan Mohammadzadeh: conceptualization, investigation, writing – original draft, methodology, writing – review and editing, validation, project administration, data curation, supervision, resources, software, formal analysis. Mousa Alavi: conceptualization, investigation, writing – original draft, writing – review and editing, methodology, validation, formal analysis, software, project administration, data curation, supervision. Mohammad Akbari: conceptualization, writing – original draft, writing – review and editing, methodology, formal analysis, project administration, supervision, data curation. Fatemeh Lohrasbi: conceptualization, investigation, writing – original draft, data curation, supervision, resources, formal analysis, project administration, writing – review and editing, validation, methodology.

Conflicts of Interest

The authors declare no conflicts of interest.

Transparency Statement

The lead/Corresponding author (Mousa Alavi) affirms that this manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.

Data Availability Statement

The datasets during the current study are not publicly available due to confidentiality of the participants’ data, but they will be available upon reasonable request.