Psychosocial adjustment changes and related factors in young and middle-aged patients with first-episode acute myocardial infarction: a longitudinal study.

AIMS: This study aimed to explore the change trend and group heterogeneity of psychosocial adjustment level and to determine its influencing factors among young and middle-aged patients with first-episode acute myocardial infarction (AMI). METHODS AND RESULTS: The Psychosocial Adjustment Scale of Illness was used to assess the psychosocial adjustment level of the patients at 1, 3, and 6 months after discharge, respectively. Data were analyzed using Pearson correlation analysis, generalized estimating equations, and growth mixed models. A total of 233 patients were included, and their psychosocial adjustment scores at the three-time points were 57.18 ± 15.50, 36.17 ± 15.02, and 24.22 ± 12.98, respectively. The trajectories of changes in patients' psychosocial adjustment levels were divided into three latent categories: moderate adjustment improvement group (72.5%), low adjustment improvement group (16.3%), and persistent maladjustment group (11.2%). Among them, predictors of the persistent maladjustment group included no spouse, low monthly family income per capita, normal body mass index, never smoking, never exercising, combined with hyperlipidemia, low social support, submission coping, and high perceived stress. CONCLUSIONS: The psychosocial adjustment level of young and middle-aged patients with first-episode AMI showed an upward trend within 6 months after discharge, and there was group heterogeneity in the change trajectory of psychosocial adjustment level. It is suggested that a multi-center, large-sample longitudinal study should be carried out in the future, and the time of follow-up investigation should be extended to further clarify the change trajectory and influencing factors of psychosocial adjustment of patients with different subtypes, to provide the theoretical basis for formulating targeted intervention programs.

Psychosocial adaptation profiles in young and middle-aged patients with acute myocardial infarction: a latent profile analysis.

AIMS: We sought to explore the latent classifications of psychosocial adaptation in young and middle-aged patients with acute myocardial infarction (AMI) and analyse the characteristics of different profiles of AMI patients. METHODS AND RESULTS: A cross-sectional study was performed in 438 Chinese young and middle-aged patients with AMI. The investigation time was 1 month after discharge. Three different self-report instruments were distributed to the participants, including the Psychosocial Adjustment to Illness Scale, the Perceived Stress Scale, and the Social Support Rating Scale. The seven dimensions of the Psychosocial Adjustment to Illness Scale were then used to perform a latent profile analysis. All participants signed informed consent forms in accordance with the ethical principles of the Declaration of Helsinki. Finally, a total of 411 young and middle-aged AMI patients were enrolled. Three distinct profiles were identified, including the 'well-adapted group' (44.8%), 'highlight in psychological burdens group' (25.5%), and 'poorly adapted group' (29.7%). The influencing factors included stress perception, social support, occupational type, and marital status (P < 0.05). CONCLUSION: The psychosocial adaptation of young and middle-aged AMI patients can be divided into three profiles. Clinical nurses can carry out individualized psychological interventions according to the characteristics of patients in different potential profiles to improve the psychosocial adaptation of patients and the prognosis of their disease.

Need assessment for history-taking instruction program using chatbot for nursing students: A qualitative study using focus group interviews.

Purpose: A comprehensive health history contributes to identifying the most appropriate interventions and care priorities. However, history-taking is challenging to learn and develop for most nursing students. Chatbot was suggested by students to be used in history-taking training. Still, there is a lack of clarity regarding the needs of nursing students in these programs. This study aimed to explore nursing students' needs and essential components of chatbot-based history-taking instruction program. Methods: This was a qualitative study. Four focus groups, with a total of 22 nursing students, were recruited. Colaizzi's phenomenological methodology was used to analyze the qualitative data generated from the focus group discussions. Results: Three main themes and 12 subthemes emerged. The main themes included limitations of clinical practice for history-taking, perceptions of chatbot used in history-taking instruction programs, and the need for history-taking instruction programs using chatbot. Students had limitations in clinical practice for history-taking. When developing chatbot-based history-taking instruction programs, the development should reflect students' needs, including feedback from the chatbot system, diverse clinical situations, chances to practice nontechnical skills, a form of chatbot (i.e., humanoid robots or cyborgs), the role of teachers (i.e., sharing experience and providing advice) and training before the clinical practice. Conclusion: Nursing students had limitations in clinical practice for history-taking and high expectations for chatbot-based history-taking instruction programs.

Latent profile analysis and related factors of post-traumatic growth in young and middle-aged patients with acute myocardial infarction.

BACKGROUND: AMI incidence in young and middle-aged patients is increasing year by year, and such patients are prone to negative emotions after illness, which affects health outcomes. However, post-traumatic growth can bring about positive changes in the patient, which is beneficial to their recovery. OBJECTIVES: This study aimed to understand the different types of post-traumatic growth characteristics and their related factors in young and middle-aged patients with acute myocardial infarction to help find precise intervention measures. METHODS: This was a cross-sectional study. Self-reported questionnaires were used to assess general demographic characteristics, post-traumatic growth, and rumination. The mean of the five dimensions of the Post-traumatic Growth Scale was used to perform a Latent profile analysis. RESULTS: A total of 312 participants, including 285 male and 27 female patients, with the mean age was 51.95±5.75. Latent profile analysis results showed that three-profile model was the most suitable. Three different profiles were named: the "Malgrowth group" (45.51%), the "Good growth group" (18.91%), and the "Excellent growth group" (35.58%). The related factors included rumination, age, monthly income, whether to return to work, marital status, residential address, classification of disease, and whether to perform PCI treatment (P<0.05). CONCLUSION: According to our results, the post-traumatic growth of young and middle-aged AMI patients can be divided into three profiles, and targeted intervention can be carried out for patients according to the determined patient profiles.

Experiences and perceptions of acute myocardial infarction patients with a prolonged decision-making phase of treatment seeking: A meta-synthesis.

AIMS: To describe the experiences and perceptions of acute myocardial infarction (AMI) patients with a prolonged decision-making phase of treatment-seeking. BACKGROUND: Previous attempts to reduce the treatment-seeking time of AMI have been less than optimal. Due to the coronavirus disease 2019 (COVID-19) pandemic, the situation of prehospital delay is possibly worse. Decisions to seek treatment are influenced by multiple factors and need individualised interventions. Understanding patients' external and internal experiences and psychological perceptions is essential. DESIGN: Meta-synthesis. DATA SOURCES: We searched PubMed, Embase, Cochrane Library, Web of Science, Scopus and four Chinese databases from inception to April 2022. METHODS: We screened the retrieved articles with predetermined inclusion and exclusion criteria, and reviewed articles using Thomas and Harden's (BMC Medical Research Methodology, 2008 8, 45) qualitative thematic synthesis approach. The Joanna Briggs Institute critical appraisal tool for qualitative research was used to assess the quality of studies. RESULTS: Twenty-one studies were included, identifying four themes and nine sub-themes. The four primary themes were difficulty recognising and attributing symptoms, attempt to act, unwillingness to change and self-sacrifice. CONCLUSION: Deciding to seek treatment is a complex social and psychological process, which needs comprehensive interventions considering personal and sociocultural factors and factors related to the COVID-19 pandemic. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Details of interventions for decisions to seek treatment in AMI patients need to be further designed and evaluated. IMPACT: Results would help healthcare professionals to implement individualised management of decision-making of treatment-seeking among AMI patients, and improve medical records of patients' prehospital experiences. REPORTING METHOD: The Preferred Reporting Items for Systematic Reviews 2020 checklist was used to report the findings. PATIENT OR PUBLIC CONTRIBUTION: Two AMI patients contributed to the data synthesis by giving simple feedback about the final themes.

Self-esteem and family functioning mediates the association of symptom severity and parental affiliate stigma among families with children with ASD.

PURPOSE: To investigate the level of affiliate stigma among parents of children with autism spectrum disorder and to explore the mediating role of self-esteem and family functioning. DESIGN AND METHODS: A cross-sectional study was conducted in a large regional hospital and two childhood rehabilitation centers in Guangdong, China. Data related to demographics, parental self-esteem, family functioning, and affiliate stigma were collected from 180 parents of children diagnosed with ASD. We used t-tests, analysis of variance, and correlation analysis to explore the related factors of parental affiliate stigma. Path analysis was used to determine the mediating roles of self-esteem and family functioning in the relationship between symptom severity and affiliate stigma. RESULTS: Parents of children with autism spectrum disorder in China experienced low self-esteem, family functioning, and high affiliate stigma. Symptom severity was negatively correlated with self-esteem and family functioning. Self-esteem and family functioning were significantly negatively correlated with affiliate stigma. Symptom severity was positively correlated with affiliate stigma. Self-esteem and family functioning mediated the relationship between symptom severity and affiliate stigma. CONCLUSIONS: Symptom severity affects parental affiliate stigma among families with children with ASD. Self-esteem and family functioning are the two mediators in the relationship. We should take steps to improve self-esteem and family functioning in order to alleviate parental affiliate stigma. PRACTICE IMPLICATIONS: This study emphasizes the importance of the influence of ASD severity and family functioning on affiliate stigma. In clinical practice, psychological support should be provided for parents of children with ASD to improve their mental health.

Mobilizing artificial intelligence to cardiac telerehabilitation.

Cardiac telerehabilitation is a method that uses digital technologies to deliver cardiac rehabilitation from a distance. It has been shown to have benefits to improve patients' disease outcomes and quality of life, and further reduce readmission and adverse cardiac events. The outbreak of the coronavirus pandemic has brought considerable new challenges to cardiac rehabilitation, which foster cardiac telerehabilitation to be broadly applied. This transformation is associated with some difficulties that urgently need some innovations to search for the right path. Artificial intelligence, which has a high level of data mining and interpretation, may provide a potential solution. This review evaluates the current application and limitations of artificial intelligence in cardiac telerehabilitation and offers prospects.