Abstract
Mental health after acute myocardial infarction (AMI) influences the prognosis of patients. Resilience may contribute to improving a patient’s mental health. However, no study has investigated resilience and its associated factors in young and middle-aged patients undergoing emergency percutaneous coronary intervention (PCI) after the first AMI. This study aimed to identify critical associated factors influencing resilience in these patients. This cross-sectional study recruited 161 young and middle-aged patients with first-episode AMI using a purposive sampling method. These patients were assessed 48 h after emergency PCI using the General Information Questionnaire, the Connor—Davidson Resilience Scale—10, the Perceived Social Support Scale, the General Self-Efficacy Scale, and the Post-traumatic Stress Disorder Scale Civilian Version. Stepwise and logistic regression were conducted to analyze the factors influencing resilience. Receiver operating characteristics (ROC) were used to compare the area under the curves (AUC) for each indicator. The resilience of the 161 participants was 29.50 ± 4.158. Monthly household income, self-efficacy, social support, and post-traumatic stress disorder explained 51.4% of the variance in resilience. Self-efficacy (OR 0.716, CI 0.589–0.870, P < 0.01) and social support (OR 0.772, CI 0.635–0.938, P < 0.01) were protective factors for psychological resilience, while post-traumatic stress disorder (OR 1.278, CI 1.077–1.515, P < 0.01) was a risk factor. ROC curve revealed that self-efficacy, social support, and PTSD had an AUC of 0.822, 0.855, and 0.889, respectively. Self-efficacy and social support improve, and PTSD degrades psychological resilience in young and middle-aged AMI patients undergoing emergency PCI.
Similar content being viewed by others
Introduction
Acute myocardial infarction (AMI) is the leading cause of death resulting from cardiovascular diseases worldwide, affecting approximately one million people in China annually1. Contrary to popular belief, the incidence of AMI is not limited to elderly patients; recent studies have shown a gradual increase in AMI incidence in younger individuals2. The China Cardiovascular Health Report indicated a 36% increase in AMI incidence among young individuals aged 25–44 from 1990 to 2019, with about one-third of acute AMI patients younger than 603.
Emergency percutaneous coronary intervention (PCI)4 has become increasingly popular for treating AMI patients. However, the invasive nature of the procedure and permanent stent placement can cause various psychological problems in patients, including anxiety, depression, and post-traumatic stress disorder (PTSD) associated with poor prognosis and high mortality5,6,7. These psychological responses may be more significant in emergency PCI settings, and this psychological pressure may prevent successful return reintegration into society and family life8.
Resilience is the ability of an individual to recover from or rebound from adversity9, and it is proportional to mental health and life satisfaction, mitigating the adverse effects of stress10. However, studies on resilience in AMI patients are limited. Previous research looked into the relationship between resilience, self-efficacy, and negative affect in AMI patients after PCI and have confirmed that resilience and PTSD are correlated11,12. Young and middle-aged patients are critical for social development and family life. However, Studies have shown that anxiety is significantly higher among young and middle-aged patients than among elderly patients13, they have multiple responsibilities and stressors, which cause them to suffer from impaired cardiac function after emergency PCI, such as angina pectoris and heart failure, resulting in limited physical activity14 and the ability to work and socialize. The disease has a significantly greater impact on their lives and the economy than on other age groups15. According to Kumpfer’s resilience theory, resilience can mediate the relationship between adversity and its outcomes and propel a person to grow in the face of adversity16. Most previous studies on resilience have focused on patients aged 18–80 years undergoing elective PCI. Few studies have focused on resilience and its influencing factors in young and middle-aged patients undergoing emergency PCI for their first AMI. Understanding such patients’ resilience and the impact factors may prevent and treat psychological problems and promote disease recovery and physical and mental health.
Therefore, this study aimed to assess the resilience status of young and middle-aged patients who had the first AMI after emergency PCI and investigate the relationship between sociodemographics, self-efficacy, social support, and PTSD and resilience. In addition, this study evaluated the predictive value of these factors in predicting low resilience using the receiver operating curve (ROC).
Methods
Participants
Purposive sampling was used in this cross-sectional study by recruiting 161 AMI patients between May 2020 and February 2022 from the Coronary Care Unit (CCU) Cardiology Department, Nanjing Hospital, Nanjing Medical University. The inclusion criteria of patients were:
-
(1)
18–60 years old.
-
(2)
Diagnosis meeting the Chinese Medical Association’s revised Acute ST-segment elevation myocardial infarction diagnostic criteria.
-
(3)
Symptoms of AMI on admission but never before.
-
(4)
Unaware of the presence of coronary artery disease before admission for AMI.
-
(5)
Admitted via emergency and received first emergency PCI.
Patients who were critically ill, had cognitive impairment, vital organ dysfunction, hematological diseases, and malignant tumors were excluded.
Calculation of sample size
The researchers used PASS 15.0 software to precalculate the sample size with a 95% confidence interval, 30% overall standard deviation17, and 0.15 tolerance. The computation produced 155 cases, the bare minimum sample size needed. In the end, 161 patients were included.
Data collection
This study collected data within 48 h of the patient’s mental status and condition stabilizing after emergency PCI. After all participants provided written informed consent, they received a questionnaire designed by the researcher. If patients were unable to complete the questionnaire on their own, the researcher read aloud the questions and recorded the patients’ responses on their behalf.
Ethical consideration
The Ethics Committee of Nanjing Hospital of Nanjing Medical University approved the study (Approval No., KY20200424-03.), and all methods were performed in accordance with the Declaration of Helsinki. Before the questionnaire began, participants signed informed consent forms.
Instruments
Demographic variables
After reviewing the literature, the researcher developed his own demographic questionnaire18 (Supplementary file 1), which included age, gender, presence of a spouse, education level, work status, nature of work, payment of medical expenses, residence status, place of residence, and monthly income level.
Connor–Davidson resilience scale 10 (CD-RISC-10)
The Conner–Davidson resilience scale (CD-RISC) was used to develop the CD-RISC-10 by Campbell-Sills and Stein (2007), and Zengjie Ye et al. (2018) translated the Chinese version to measure resilience among adults19. It comprises 10 items scored on a 5-point Likert scale, ranging from 0 (very non-conforming) to 4 (very conforming) with a total score of 0–40; higher scores imply higher levels of psychological resilience. The CD-RISC-10 has superior psychometric properties, reliability, and applicability to Chinese people compared to the CD-RISC scale20,21. The scale’s Cronbach’s alpha coefficient in this study was 0.922.
General self-efficacy scale (GSES)
Schwarzer22 developed the GSES to assess an individual’s ability to cope with different environments and their general self-efficacy when facing new challenges. The Chinese version was translated and corrected by Wang et al.23.
Scores are based on a Likert 4-point scale, where 1 represents completely incorrect, and 4 represents completely correct. Scores range between 10 and 40; higher scores indicate stronger self-efficacy. The Chinese version of the GSES has proven to be highly reliable and valid24. The scale’s Cronbach’s alpha coefficient in this study was 0.87.
Perceived social support scale (PSSS)
The PSSS was developed by Zimet et al.25 and translated into Chinese by Qianjin26 to measure individual sources of social support. The scale has three components: support from friends, family, and other sources, with 12 items scored on a Likert scale with seven points ranging from 1 (strongly disagree) to 7 (strongly agree). The overall score was 12–84, with higher scores indicating stronger social support for their apprehension. The scale’s Cronbach’s alpha coefficient in this study was 0.943.
The PTSD check list-civilian version (PCL-C)
The PCL-C scale was developed from the DSM-W27 to evaluate the experiences of common people following traumatic experiences in ordinary life. The 17-item scale includes three dimensions of re-experience, avoidance or numbing, and hyperarousal, scored on a 5-point scale, ranging from 1 (did not occur) to 5 (extremely severe). The total score range was 17–85. This study conducted an extensive literature review to establish a diagnostic threshold of 38 for PTSD in Chinese individuals to increase its diagnostic validity28. Patients with a total score of ≤ 37, 38–49, and ≥ 50 represented no significant PTSD symptoms, some degree of PTSD symptoms, and substantial PTSD symptoms, respectively. Item score ≥ 3 was considered a positive item. The number of positive items of re-experiencing symptoms, avoidance/numbness symptoms, and hypervigilance symptoms were ≥ 1, ≥ 3, and ≥ 2, respectively. The Cronbach’s alpha coefficient for this scale was 0.94.
Statistical analysis
The data was analyzed using IBM SPSS Statistics (version 26.0) statistical software. P < 0.05 was regarded as statistically significant. GraphPad Prism (version 9.0) software was used to plot the ROC curves. In this study, means, standard deviation, and frequency (percentage) were used to describe continuous and categorical variables, to make a statistical description of baseline characteristics and resilience scores of the study population. Normally distributed variable scores were tested using t-tests and one-way ANOVA or chi-square analysis. Pearson or Spearman correlation coefficient (r) was used to examine the relationships between resilience and sociodemographics, general self-efficacy, social support, and post-traumatic stress disorder. In addition, stepwise multiple linear regression and univariate and multivariate logistic regression analyses were used to determine the factors influencing resilience. The ROC was used to assess the predictive value of different variables on resilience and to determine the optimal value.
Results
Participants characteristics
This study included 161 participants with an age range of 33–60 years. In addition, 85.8% of participants were aged 45–60 years, and the majority (91.3%) were male (Table 1).
The association between psychological resilience, self-efficacy, social support, and PTSD
An analysis of the relationship between resilience and self-efficacy, social support, and PTSD (Table 2) showed that the high-resilience group had significantly higher self-efficacy and social support than the low-resilience group. PTSD in the high-resilience group was substantially lower. Bivariate analysis revealed that resilience was positively related to self-efficacy (r = 0.554, P < 0.01), social support and its dimensions (family support, friend support) (r = 0.432, 0.449, 0.343; P < 0.01), and PTSD and its dimensions (re-experience, avoidance/numbing, hyperarousal) (r = − 0.476, − 0.274, − 0.241, − 0.420; P < 0.01).
Influencing factors
The regression model showed that resilience was significantly correlated with five different variables (Table 3) (Adjusted R2 = 0.514, P < 0.05). Monthly household income (β = 0.167, P <0.01), general self-efficacy (β = 0.397, P < 0.01), and social support (β = 0.225, P < 0.01) were positively associated with resilience, while PTSD (β = − 0.284, P < 0.01) was negatively related to resilience. Logistic regression analysis with resilience as a categorical variable (Table 4) showed that general self-efficacy (OR 0.716, P < 0.01) and social support (OR 0.772, P < 0.01) were protective factors for psychological resilience. In contrast, PTSD (OR 1.278, P < 0.01) was a risk factor.
ROC analysis showed that the combination of the three variable scores had the most significant AUC of 0.961 (P < 0.01) (Fig. 1b), compared to GSES (AUC = 0.822), PCL-C (AUC = 0.889), and PSSS (AUC = 0.855) alone (Fig. 1a), with some predictive values for high and low levels of resilience (all P < 0.01). The optimal cut-off values, sensitivity, and specificity of the three variables are shown in Table 5.
OR odds ratio, CI confidence interval.
*P < 0.05, **P < 0.01.
Discussion
Current status of resilience in young and middle-aged patients with first myocardial infarction
This study discovered that the resilience level in young and middle-aged patients with their first AMI was 29.50 ± 4.158, with the scores of high and low resilience groups being 32.90 ± 2.19 and 26.05 ± 2.50, respectively. Self-efficacy, social support, and PTSD were significantly better in the high-resilience group than in the low-resilience group. The first symptom of AMI is generally severe chest pain, with rapid onset and progression, and the mental stimulation and psychological stress generated during the process of being rushed to the emergency room are enormous. Psychological resilience and its protective factors can assist individuals in coping with stress, improving their mental health, and maintaining patients’ physical and psychological health29. Patients with low resilience should be given more social attention because patients’ psychological adjustment disorders, such as self-perceived burden, reduced self-care ability, and a lack of social roles can lead to patients’ inability to cope with the disease. These changes weaken their active healthcare-seeking behaviors, which is detrimental to their recovery30. According to this study, monthly household income, self-efficacy, and social support all positively influence resilience, whereas PTSD was negatively associated with resilience. These factors displayed 51.4% of the variance in resiliency among first-time AMI patients (Supplementary Information).
Post-traumatic stress disorder and resilience
It has been reported that positive PTSD adversely affects cardiac events and quality of life31,32. Individuals with high psychological resilience have a low prevalence of PTSD33, and PTSD is negatively associated with resilience in a survey of burn patients34. This study also revealed a significant negative association with lower resilience scores in participants with positive PTSD symptoms (β = − 0.284, P < 0.01) and a 1.143-fold increase in the probability of PTSD in low resilience participants than high resilience participants (OR 1.278, P < 0.01). Therefore, a high level of psychological resilience improves patients’ adaptability to adversity and promotes disease regression.
Cardiovascular diseases such as acute myocardial infarction are considered “exclusive diseases” of the elderly. Therefore, accepting the diagnosis of a sudden and severe disease, such as acute myocardial infarction, is challenging for young patients psychologically, resulting in pessimistic behavior about the prognosis and increasing their stress response. Patients may develop PTSD due to the severe pain and psychological stress caused by a sudden AMI. A review showed a higher incidence of PTSD in younger acute coronary syndrome (ACS) patients35. This study found that the optimal cut-off value for predicting low resilience was 31, less than the positive cut-off value of 38, currently recommended for use in the literature36. This finding could be related to the type of disease and sample population in this study. This study highlighted the importance of nurses identifying high-risk PTSD patients as early as possible and implementing effective coping strategies for PTSD. In addition, nurses must pay special attention to the families of patients with low education levels, self-pay medical expenses, and low self-care levels and assist them in using appropriate coping strategies and social support systems to better avoid traumatic and stressful events37.
Self-efficacy and resilience
This study found self-efficacy to be significantly and positively related to resilience (β = 0.397, P < 0.01), consistent with other diseased populations, such as stroke, breast cancer, and burn injury patients38,39,40. Self-efficacy can improve the quality of life for AMI patients by boosting their self-confidence and positive attitude about dealing with the disease41. This study validated self-efficacy’s protective effect on resilience (OR 0.716, P < 0.01). An analysis of self-efficacy in elderly AMI patients showed that the mean self-efficacy score after PCI was 21.56 ± 9.6612. In contrast, the mean self-efficacy score of young and middle-aged AMI patients after emergency PCI in this study was 29.677 ± 4.765, higher than in previous studies. This difference is due to the loss of the labor force, fewer social roles, reduced confidence in treatment (due to underlying diseases), and a lower sense of self-worth in the elderly. Middle-aged and young people, on the other hand, are at a critical juncture in their careers, have higher expectations for disease recovery, and are willing to fully cooperate with treatment, influencing their feelings positively.
In addition, this study established ROC prediction thresholds for variables associated with low resilience. Therefore, a GSES score < 30 predicted low resilience with a sensitivity and specificity of 77.50% and 74.07%, respectively, indicating the need to prevent low resilience by enhancing self-efficacy. Consequently, in clinical nursing, nurses should focus on cultivating and improving patients’ self-efficacy with myocardial infarction to encourage patients to maintain a positive psychological state during disease treatment, thereby increasing their psychological resilience.
Social support and resilience
Younger AMI patients with lower levels of social support have worse mental health, quality of life, and depressive symptoms42. However, no research has explored the relationship between social support and resilience in young and middle-aged AMI survivors. Some studies in other populations have discovered a link between social support and resilience38,43. Young and middle-aged patients are generally unable to fulfill their established family and social roles following the illness and are concerned about the disease’s impact on their prognosis. After their first AMI, young and middle-aged patients showed a moderately positive relationship between resilience and social support (β = 0.225, P < 0.01), implying that positive social support can reduce negative stress-related emotions by encouraging the expression of their emotions, improving their ability to cope with the disease44, helping them overcome their fear about their condition, and boost their resilience45. Consequently, nurses should prioritize patients with low social support in their work, assist patients in changing their negative perceptions, actively seek outside consent, and encourage family members to provide more care and encouragement to patients.
Monthly household income and resilience
Furthermore, this study showed that high resilience was predicted by higher monthly household income (> 10,000 RMB), contradicting previous research. However, no statistically significant difference has been observed between economic status and resilience in patients with oral and breast cancer46,47. This study hypothesized that a higher monthly household income might indicate a greater ability and capital to deal with difficulties and adversity as an important safeguard against misfortune. Low-income patients, on the other hand, bear a heavier household burden, resulting in lower resilience.
Limitations
In this study, there were three limitations. First, an analysis was conducted on the relationship between self-efficacy, social support, PTSD, and resilience only; other potential factors that might influence resilience need further research. Second, determining the causal relationship between resilience and its influencing factors is challenging to determine using this single-center cross-sectional study; other studies should validate the conclusions of this study. Third, although the sample size met statistical needs and presented significant results, its small size may have affected the generalisability of the results. Future studies should consider larger sample sizes to strengthen the reliability of the findings.
Conclusion
Among young and middle-aged AMI patients undergoing emergency PCI, PTSD was the strongest predictor and risk factor of psychological resilience, followed by social support. Improving resilience is essential for improving individuals’ positive coping with illness after AMI. This study contributes to the development of resilience-building interventions.
Data availability
Data will be shared on request. If someone wants to request the data from this study, they can contact Jinju Wang.
Abbreviations
- AMI:
-
Acute myocardial infarction
- PCI:
-
Percutaneous coronary intervention
- PTSD:
-
Post-traumatic stress disorder
- ROC:
-
Receiver operating curve
- CCU:
-
Coronary care unit
- CD-RISC-10:
-
Connor–Davidson resilience scale 10
- GSES:
-
General self‐efficacy scale
- PSSS:
-
Perceived social support scale
- PCL-C:
-
The PTSD check list-civilian version
References
Wang, Z., Du, A., Liu, H., Wang, Z. & Hu, J. Systematic analysis of the global, regional and national burden of cardiovascular diseases from 1990 to 2017. J. Epidemiol. Glob. Health 12, 92–103 (2022).
Guo, X., Li, Z., Vittinghoff, E., Sun, Y. & Pletcher, M. J. Trends in rate of acute myocardial infarction among patients aged <30 years. Nat. Rev. Cardiol. 15, 119 (2018).
Writing Committee of the Report on Cardiovascular Health and Diseases in China. Key points of report on cardiovascular health and diseases in China 2020. Chin. J. Cardiovasc. Res. 19, 582–590 (2021).
Hu, K. et al. Intracoronary application of nicorandil regulates the inflammatory response induced by percutaneous coronary intervention. J. Cell Mol. Med. 24, 4863–4870 (2020).
Akosile, W., Young, R., Lawford, B., Voisey, J. & Colquhoun, D. PTSD symptoms associated with myocardial infarction: Practical clinical implications. Australas. Psychiatry 26, 60–64 (2018).
Lissåker, C. T., Norlund, F., Wallert, J., Held, C. & Olsson, E. M. Persistent emotional distress after a first-time myocardial infarction and its association to late cardiovascular and non-cardiovascular mortality. Eur. J. Prev. Cardiol. 26, 1510–1518 (2019).
Zhang, W. Y., Nan, N., Song, X. T., Tian, J. F. & Yang, X. Y. Impact of depression on clinical outcomes following percutaneous coronary intervention: A systematic review and meta-analysis. BMJ Open 9, e026445 (2019).
Xiao, X., Su, J. & Su, I. J. Psychosocial adjustment in young and middle-aged adults after coronary stent implantation: A mixed-method study. Heart Lung 52, 86–94 (2022).
Garcia-Dia, M. J., DiNapoli, J. M., Garcia-Ona, L., Jakubowski, R. & O’Flaherty, D. Concept analysis: Resilience. Arch. Psychiatr. Nurs. 27, 264–270 (2013).
Tamura, S., Suzuki, K., Ito, Y. & Fukawa, A. Factors related to the resilience and mental health of adult cancer patients: A systematic review. Support Care Cancer 29, 3471–3486 (2021).
Kirchner, K., Brauer, H., Van der Auwera, S. & Grabe, H. J. The impact of resilience, alexithymia and subjectively perceived helplessness of myocardial infarction on the risk of posttraumatic stress. J. Clin. Psychol. Med. Setting 29, 954–962 (2022).
Liu, N. et al. Correlations among psychological resilience, self-efficacy, and negative emotion in acute myocardial infarction patients after percutaneous coronary intervention. Front. Psychiatry 9, 1 (2018).
Liang, J. J. et al. A cross-sectional survey on the prevalence of anxiety symptoms in Chinese patients with premature ventricular contractions without structural heart disease. Chin. Med. J. (Engl.) 125, 2466–2471 (2012).
Mehrpoya, A., Jalali, R., Jalali, A. & Namdari, M. Patient experiences of living with coronary stent. J. Vasc. Nurs. 36, 181–185 (2018).
Wu, M., Wang, W., Zhang, X. & Li, J. The prevalence of acute stress disorder after acute myocardial infarction and its psychosocial risk factors among young and middle-aged patients. Sci. Rep. 12, 7675 (2022).
Kumpfer, K. L. Factors and processes contributing to resilience: The resilience framework. In Resilience Development: Positive Life Adaptations (eds Glantz, M. D. & Johnson, J. L.) 179–224 (Kluwer Academic Publishers, 2002).
Arora, S. et al. Twenty year trends and sex differences in young adults hospitalized with acute myocardial infarction. Circulation 139, 1047–1056 (2019).
Wang, Q. et al. Psychological resilience and related influencing factors in patients diagnosed with major depressive disorder in remission: A cross-sectional study. J. Psychiatr. Ment. Health Nurs. 30, 492–500 (2023).
Windle, G., Bennett, K. M. & Noyes, J. A methodological review of resilience measurement scales. Health Qual. Life Outcomes 9, 8 (2011).
Campbell-Sills, L. & Stein, M. B. Psychometric analysis and refinement of the Connor–Davidson resilience scale (CD-RISC): Validation of a 10-item measure of resilience. J. Trauma Stress 20, 1019–1028 (2007).
Wang, L., Shi, Z., Zhang, Y. & Zhang, Z. Psychometric properties of the 10-item Connor–Davidson resilience scale in Chinese earthquake victims. Psychiatry Clin. Neurosci. 64, 499–504 (2010).
Schwarzer, R., Bäßler, J., Kwiatek, P., Schröder, K. & Zhang, J. X. The assessment of optimistic self-beliefs: Comparison of the German, Spanish, and Chinese versions of the general self-efficacy scale. Appl. Psychol. 46, 69–88 (1997).
Wang, C. K., Hu, Z., F. & L, Y. Evidences for reliability and validity of the Chinese version of general self-efficacy scale. Chinese J. Appl. Psychol. 7, 37–40, In Chinese (2001).
Yang, Y. L., Liu, L., Wang, X. X., Wang, Y. & Wang, L. Prevalence and associated positive psychological variables of depression and anxiety among Chinese cervical cancer patients: A cross-sectional study. PLoS ONE 9, e94804 (2014).
Zimet, G. D., Powell, S. S., Farley, G. K., Werkman, S. & Berkoff, K. A. Psychometric characteristics of the multidimensional scale of perceived social support. J. Pers. Assess. 55, 610–617 (1990).
Jiang, Q. J. Primary exploration of comprehensive assessing of psychosocial stress. Chinese J. Behav. Med. Brain Sci. 7, 182–184, In Chinese (1998).
Foa, E. B., Cashman, L., Jaycox, L. & Perry, K. The validation of a self-report measure of posttraumatic stress disorder: The posttraumatic diagnostic scale. Psychol. Assess. 9, 445 (1997).
Lang, A. J., Laffaye, C., Satz, L. E., Dresselhaus, T. R. & Stein, M. B. Sensitivity and specificity of the PTSD checklist in detecting PTSD in female veterans in primary care. J. Traum. Stress 16, 257–264 (2003).
Nikendei, C., Greinacher, A., Berkunova, A., Junghanss, T. & Stojkovic, M. Psychological burden and resilience factors in patients with Alveolar Echinococcosis—A cross-sectional study. PLoS Negl. Trop. Dis. 13, e0007082 (2019).
Peeters, Y., Ranchor, A. V., Vliet Vlieland, T. P. & Stiggelbout, A. M. Effect of adaptive abilities on utilities, direct or mediated by mental health? Health Qual. Life Outcomes 8, 130 (2010).
Allabadi, H. et al. Posttraumatic stress disorder predicts poor health-related quality of life in cardiac patients in Palestine. PLoS ONE 16, e0255077 (2021).
Edmondson, D. et al. Posttraumatic stress due to an acute coronary syndrome increases risk of 42-month major adverse cardiac events and all-cause mortality. J. Psychiatr. Res. 45, 1621–1626 (2011).
Thompson, N. J., Fiorillo, D., Rothbaum, B. O., Ressler, K. J. & Michopoulos, V. Coping strategies as mediators in relation to resilience and posttraumatic stress disorder. J. Affect. Disord. 225, 153–159 (2018).
Bibi, A., Kalim, S. & Khalid, M. A. Post-traumatic stress disorder and resilience among adult burn patients in Pakistan: A cross-sectional study. Burns Trauma 6, 8 (2018).
Edmondson, D. & Cohen, B. E. Posttraumatic stress disorder and cardiovascular disease. Prog. Cardiovasc. Dis. 55, 548–556 (2013).
Dobie, D. J., Kivlahan, D. R., Maynard, C., Bush, K. R. & Bradley, K. A. Screening for post-traumatic stress disorder in female Veteran’s affairs patients: Validation of the PTSD checklist. Gen. Hosp. Psychiatry 24, 367–374 (2002).
Williamson, V. et al. The role of parenting behaviors in childhood post-traumatic stress disorder: A meta-analytic review. Clin. Psychol. Rev. 53, 1–13 (2017).
Huang, Y. et al. Psychological resilience of women after breast cancer surgery: A cross-sectional study of associated influencing factors. Psychol. Health Med. 24, 866–878 (2019).
Liu, Z., Zhou, X., Zhang, W. & Zhou, L. Resilience and its correlates among first ischemic stroke survivors at acute stage of hospitalization from a tertiary hospital in China: A cross-sectional study. Aging Ment. Health 24, 828–836 (2020).
Tehranineshat, B. et al. A study of the relationship among burned patients’ resilience and self-efficacy and their quality of life. Patient Prefer. Adher. 14, 1361–1369 (2020).
Náfrádi, L., Nakamoto, K. & Schulz, P. J. Is patient empowerment the key to promote adherence? A systematic review of the relationship between self-efficacy, health locus of control and medication adherence. PLoS ONE 12, e0186458 (2017).
Bucholz, E. M. et al. Effect of low perceived social support on health outcomes in young patients with acute myocardial infarction: Results from the VIRGO (variation in recovery: Role of gender on outcomes of young AMI patients) study. J. Am. Heart Assoc. 3, e001252 (2014).
Li, F. et al. Effects of sources of social support and resilience on the mental health of different age groups during the COVID-19 pandemic. BMC Psychiatry 21, 16 (2021).
Yoo, W. et al. Predictors of the change in the expression of emotional support within an online breast cancer support group: A longitudinal study. Patient Educ. Couns. 90, 88–95 (2013).
Ao, Y. et al. The impact of social support on public anxiety amidst the COVID-19 pandemic in China. Int. J. Environ. Res. Public Health 17, 9097 (2020).
Gao, Y., Yuan, L., Pan, B. & Wang, L. Resilience and associated factors among Chinese patients diagnosed with oral cancer. BMC Cancer 19, 447 (2019).
Wu, Z., Liu, Y., Li, X. & Li, X. Resilience and associated factors among mainland Chinese women newly diagnosed with breast cancer. PLoS ONE 11, e0167976 (2016).
Acknowledgements
The authors thank all the nurses who participated in the study.
Author information
Authors and Affiliations
Contributions
LS: contributed to the conception and design of the study. YW, JW: data analysis and manuscript writing. JZ: Data collection and review editing. SL: manuscript revision. All authors contributed to the article and approved the submitted version.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Wang, J., Wu, Y., Zhou, J. et al. Resilience and its influencing factors after emergency percutaneous coronary intervention in young and middle-aged patients with first acute myocardial infarction. Sci Rep 14, 9507 (2024). https://doi.org/10.1038/s41598-024-59885-9
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41598-024-59885-9
Keywords
Comments
By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.