This study employed a cross-sectional design and utilized moderation analysis. A convenience sampling method was used to recruit young and middle-aged patients with acute myocardial infarction (AMI) who underwent their first percutaneous coronary intervention (PCI) at the Department of Cardiology, Heyuan People’s Hospital between August 2022 and April 2024.

The inclusion criteria were as follows:

The exclusion criteria were as follows:

These specific criteria were implemented to homogenize the sample and focus the investigation on a typical working-age population experiencing their first major cardiac event, thereby allowing for a clearer examination of the relationships between coping modes, social support, and social disability in this distinct subgroup.

Initial data screening revealed that 19 questionnaires had significant missing data. After excluding these cases, a final sample of 129 participants was included in the analysis (response rate = 93.5%).

Data analysis was performed using SPSS Statistics 23.0 and the PROCESS 3.6 macro for SPSS developed by Hayes (Hayes, 2013), p < 0.05 was considered statistically significant for all analyses. The specific analytical steps were as follows:

This study was approved by the Ethics Committee of Heyuan People’s Hospital (Approval No. YXLL-2021 K53). The trial was also registered with the Chinese Clinical Trial Registry (Registration No. ChiCTR2500098631). All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Written informed consent was obtained from all individual participants included in the study. All participants were assured of data confidentiality and anonymity.

A total of 129 post-PCI patients were included in this study. As shown in Table 1, the sample had a mean age of 51.2 ± 7.1 years and was predominantly male (93.0%). No significant differences in social disability scores were found across most demographic and clinical variables (all p > 0.05).

The scores for the main study variables are presented in Table 2. Given the non-normal distribution of MCMQ and SDSS, their scores are reported as median and interquartile range (IQR): the median MCMQ score was 38.00 (IQR = 34.00–47.00), and the median SDSS score was 1.00 (IQR = 0.00–3.50). The SSRS score, which was normally distributed, is reported as mean ± standard deviation (39.76 ± 6.66).

As shown in Table 2, MCMQ showed a significant positive correlation with SSRS (p = 0.571, p < 0.001), and a significant negative correlation with SDSS (p = −0.526, p < 0.001). Similarly, SSRS was negatively correlated with SDSS (p = −0.631, p < 0.001).

Latent profile analysis (LPA) was employed to identify heterogeneous patterns in medical coping modes among PCI patients. Fit indices for the competing models are presented in Table 3. The 2-class solution was selected as the optimal model based on the lower AIC, BIC, and aBIC values compared to other models. Additionally, this model demonstrated a high entropy value, and both the LMRT (p < 0.001) and BLRT (p < 0.001) reached statistical significance. According to the characteristics of the model (Figure 1), the subgroups were named as adaptive copers (Class 1, 55.1%), and maladaptive copers (Class 2, 44.9%).

Independent samples t-test was conducted to examine the differences in social disability scores between the two identified medical coping modes profiles. As shown in Table 4, a statistically significant difference was found between Adaptive Copers and Maladaptive Copers (t = 8.894, p < 0.001). Specifically, patients in the Maladaptive Copers group reported significantly lower levels of social disability (M = 0.24, SD = 0.844) compared to those in the Adaptive Copers group (M = 3.23, SD = 2.668).

The Johnson-Neyman technique was employed to precisely delineate the regions of significance for the moderating effect of perceived social support on the relationship between medical coping modes and social disability. As illustrated in Figure 2, perceived social support significantly moderated this relationship.

The analysis revealed two critical thresholds for perceived social support scores: 39.884 and 52.924. The moderating effect of social support was statistically significant (p < 0.05) when its score was below 39.884 or above 52.924.

First, consistent with our hypothesis and previous research on coping heterogeneity in chronic illness populations (Condon et al., 2020; Guiry et al., 1987), medical coping modes were not uniform among PCI patients. LPA successfully identified two distinct subgroups: Adaptive Copers (characterized by higher confrontation and lower avoidance/resignation) and Maladaptive Copers (characterized by the opposite pattern). This finding aligns with studies suggesting that patients exhibit heterogeneous coping strategies following acute cardiac events (Alanazi et al., 2025; Yamaguchi et al., 2025). The nearly equal distribution between adaptive and maladaptive copers (55.1% vs. 44.9%) highlights a significant proportion of patients who may benefit from targeted psychological interventions to improve their coping strategies post-PCI.

Second, a significant difference in perceived social support scores was observed between the two coping profiles. Contrary to some prior research which typically links avoidance and resignation to poorer outcomes (Shimode et al., 2025; Liang et al., 2022), our study yielded a counterintuitive finding: the Maladaptive Copers group reported significantly lower levels of social disability. This phenomenon can be interpreted through the lens of the cognitive-transactional model of stress. In the short-term, post-discharge context of PCI recovery, avoiding illness-related stressors and resigning to the situation might serve as an immediate, emotion-focused regulatory strategy. By disengaging from socially demanding roles and activities, these patients may temporarily reduce performance pressure and perceived failure, thereby lowering their self-reported social disability scores (Abrams, 1984). However, this apparent ‘advantage’ is likely illusory and context-dependent. While avoidance may offer a protective buffer in the acute phase, substantial evidence indicates that it is associated with poorer long-term psychological adjustment, lower treatment adherence, and worse functional recovery in cardiac patients (Blikman et al., 2014). Thus, the lower social disability score in this group may not signify healthier adaptation but rather a maladaptive disengagement from social roles that is detrimental to holistic recovery over time.

Third, and most importantly, perceived social support played a significant moderating role in the relationship between medical coping modes and perceived social support, but its effect was not linear. The Johnson-Neyman analysis revealed that social support significantly moderated this relationship only at very low (<39.884) and very high (>52.924) levels. This U-shaped moderating effect represents a novel contribution to the literature. It suggests that for patients with moderate levels of perceived social support, their coping style may be the primary driver of social disability. However, for those with exceptionally high social support, the protective effect was so strong that it significantly weakened the negative impact of maladaptive coping on social functioning, consistent with the stress-buffering hypothesis of social support (Bekiros et al., 2022; Maffei et al., 2025). Conversely, for those with very low perceived social support, the sheer lack of external resources created a vulnerable context where the individual’s coping style became paramount. In this resource-scarce environment, relying on avoidance and resignation—strategies that inherently lack proactive problem-solving—exacerbated their risk of social disability, consistent with research on the compounding effects of low perceived social support (Kazukauskiene et al., 2021; Blikman et al., 2014). Notably, the non-significant moderating effect within the moderate range of perceived social support implies that for most patients, their intrinsic coping style may be the primary driver of social disability outcomes when environmental support is neither absent nor overwhelmingly present.

Our findings offer several implications for clinical nursing practice and patient support. Firstly, the identification of two distinct coping profiles suggests that healthcare providers, especially cardiac nurses, should routinely assess the coping strategies of PCI patients (Sumin and Shcheglova, 2023). Early identification of Maladaptive Copers is crucial, Clinicians should be aware that these patients may experience relatively mild disabilities after PCI, which may mask their need for psychological support. This approach is in line with the recent call for personalized medical care in cardiac rehabilitation (Claes et al., 2024). Building on this, we propose that a comprehensive assessment should not be limited to coping styles but also encompass the patient‘s perceived social support level. This dual-assessment approach forms the foundation for personalized intervention.

Secondly, and more specifically, interventions should be tailored based on the combined insights into the patient‘s coping profile and support system, moving beyond a one-size-fits-all model. For patients with very low perceived social support, interventions must be intensive and multifaceted, focusing not only on building adaptive coping skills but also on actively connecting them with community resources, peer support groups, or counseling services to enhance their perceived support (Czajkowski et al., 2022; Purcell et al., 2021). For patients with already high perceived social support, the clinical focus should shift toward optimizing support quality. This involves educating family members and friends on how to provide effective, autonomy-supportive encouragement rather than fostering dependency or overprotective behaviors that might inadvertently reinforce avoidance (Uchino, 2006). In essence, the moderating effect revealed in our study translates into a stratified clinical strategy: for the vulnerable group with scant resources, the priority is to build support; for the well-supported group, the goal is to optimize its quality to maximize its buffering potential against maladaptive coping.

This study has several limitations. First, the cross-sectional design prohibits any causal inferences regarding the relationships between coping styles, social support, and psychological distress. Although significant correlations were found, the direction of influence remains undetermined. Future longitudinal research is needed to track the dynamic evolution throughout the recovery trajectory. Second, the generalizability of our findings is limited by the sampling strategy and our specific inclusion criteria. Although recruiting a homogeneous sample of young and middle-aged patients undergoing their first PCI from a single center enhanced the internal validity of our study, it remains unclear whether these results can be generalized to older patients, those with repeated PCI procedures, or those receiving care in other healthcare settings. Future multi-center studies with broader eligibility criteria are needed to validate our findings across the wider PCI population. Third, the generalizability of the findings is constrained by the sample characteristics. The relatively small sample size (n = 129) may limit statistical power, and the pronounced gender imbalance (over 90% male participants) means the results may not be representative of female populations. Finally, all measures relied on self-reported data. Incorporating objective indicators of functional outcomes and observational assessments of perceived social support in future studies would provide a more comprehensive data perspective.