European Journal of Investigation in Health Psychology and Education最新文献

Background: Psychosocial and metacognitive factors play a critical role in cardiovascular health, influencing clinical outcomes and adherence to treatment after Cardiac Rehabilitation (CR). This study investigated the effects of an outpatient CR program on anxiety, depression, and Health-Related Quality of Life (HRQoL) in patients with established Cardiovascular Disease (CVD). Furthermore, it examined the contribution of depressive symptoms, anxiety, and dysfunctional metacognitions to patients' perceived HRQoL.

Methods: Data on demographic, psychological, and biomedical variables were obtained from 89 patients with CVD at baseline and upon completion of the CR program.

Results: Participation in CR was associated with significant reductions in depressive symptoms and improvements in perceived HRQoL. Importantly, reductions in dysfunctional metacognitive beliefs emerged as the strongest predictor of post-intervention HRQoL, outweighing the predictive contribution of changes in depression and anxiety.

Discussion: The results highlight the close interrelationship between psychological distress and maladaptive metacognitions, both of which are strongly associated with patients' perceived HRQoL during CR.

Conclusions: Addressing maladaptive metacognitive processes may represent a promising therapeutic target to optimize psychological adjustment and improve HRQoL in individuals undergoing CR.

In recent years, network psychometrics has emerged as an alternative to the reflective latent variable model. This model conceptualizes traits as complex systems of behaviors mutually interacting with each other. Although this model offers important advantages compared to the reflective model, questions remain regarding the necessary sample size and the influence of factors such as the number of nodes and edges. This study aims to evaluate the psychometric network model performance under different conditions of sample size, number of nodes, and number of edges. The methodology involved a simulation with 1000 replicates for each combination of sample size, number of nodes, and the value of gamma parameter, which is used to determine the magnitude of the edges considered significant. The effect of these conditions on the accuracy of edge estimations and centrality indices (strength and expected influence) was assessed using sensitivity, specificity, and bias indicators. Results suggest that sample size and network complexity have a more significant impact than γ, methodological guidelines being proposed to support decision-making in applied research. In summary, this study provides empirically grounded recommendations that can guide applied researchers in designing robust psychometric network analyses and ensuring reliable estimation of model parameters.

This study applied relational turbulence theory to examine how relationship characteristics in the form of relational uncertainty and partner interdependence during the transition to parenthood are associated with more severe appraisals of irritations, features of communication during couple conflict, and perceptions of increased turbulence in the relationship. We conducted a longitudinal study of 78 couples who were surveyed three times during the transition to parenthood from pregnancy to six months after birth. Data were analyzed using multilevel modeling and examined both actor and partner effects. Results point to between-person and within-person actor effects, with actors' relational uncertainty and facets of interdependence predicting perceived severity of irritations and features of conflict episodes. In addition, actors' severity of irritations predicted conflict features and perceived relational turbulence. Partner effects emerged for relational uncertainty predicting communicative openness, conflict management, and relational turbulence, and facets of interdependence predicting most outcomes. The results are discussed in terms of their theoretical contributions and practical implications for first-time parents.

Teaching has always been recognized as one of the professions with the highest risk of burnout, thus highlighting the need to take into account how organizations could promote a "healthier" work life. Accordingly, literature has gone beyond the conceptualization of well-being as merely the "absence of illness" to concluding that it must be regarded as a state of complete health. The current study adopts this theoretical approach to address the limited literature on factors affecting the well-being of Italian primary school teachers. Specifically, responses to a self-report questionnaire completed by 142 Italian primary school teachers showed that work self-efficacy was positively associated with job satisfaction, which in turn was positively related to well-being. Consequently, job satisfaction fully mediated the relationship between self-efficacy and well-being. Furthermore, both work overload and work autonomy were found to be negatively associated with teacher well-being. These findings can inform the design of targeted interventions aimed at enhancing the performance and psychological health of primary school teachers by managing demands and fostering effective resources.

The escalating exposure of young children to digital gaming necessitates a critical examination of its behavioral impacts. However, evidence regarding its influence on aggressive behavior remains limited. This study investigated the relationship between digital play addiction tendency and our dimensions of aggression: physical aggression, relational aggression, self-directed aggression, and aggression against objects. This study employed a cross-sectional design, gathering data through parent assessments. The sample consisted of 744 children aged 4 to 6 years. The average age of the participants was 33.5, with 82% of the sample being female. The participants came from a lower (27%), middle (37%), and high (36%) socioeconomic background. The data were analyzed using a Structural Equation Modeling (SEM) approach to test the hypothesized relationships. The main findings from the SEM analysis indicated that a higher digital play addiction tendency was a significant positive predictor of all four dimensions of aggression. These results highlight the potential adverse effects of digital play addiction tendency on the development of maladaptive behaviors in early childhood. This study underscores the urgent need to develop strategies that foster healthier digital media consumption and mitigate the adverse effects of digital gaming on children's developmental outcomes.

Anxiety disorders affect over 280 million people globally and are associated with cognitive impairment. University students show a particularly high susceptibility, with studies reporting prevalent daily anxiety in this population. Physical activity (PA) has demonstrated efficacy in reducing stress and anxiety, potentially enhancing cognitive function. This scoping review examines existing evidence on the relationship between PA, anxiety symptoms, and academic performance in university students while identifying research gaps. Following PRISMA-ScR guidelines and Arksey and O'Malley's framework, we analyzed observational and experimental studies from PubMed, Cochrane, Web of Science, and Scopus. A descriptive-analytical approach assessed the effects of exercise on anxiety and academic outcomes. Out of 362 records screened, 27 met the inclusion criteria. Evidence suggests PA interventions across intensity levels may alleviate anxiety symptoms and improve academic performance. However, experimental studies specifically targeting this population remain scarce. Current findings indicate PA interventions may reduce anxiety and potentially enhance academic performance in university students. Further experimental research is required to establish causality and elucidate underlying mechanisms.

Objective: This study aimed to identify psychological characteristics associated with suicidal ideation among Palestinian university students in the West Bank during a period of escalating regional violence (October 2023), with data collected prior to the end of the war, a period marked by intensified political violence and collective trauma. The goal was to identify empirically derived psychological profiles of distress and coping using Latent Profile Analysis. Method: A cross-sectional survey of 900 students assessed depression, anxiety, self-efficacy, resilience, help-seeking attitudes, and suicidal ideation during the past 12 months. Latent Profile Analysis (LPA), logistic regression, and moderated mediation analysis were employed to investigate the relationships between distress, self-efficacy, resilience, and suicidal ideation. Results: Results indicate that depression and anxiety are associated with increased 12-month suicidal ideation, but greater self-efficacy appears to reduce this risk. The mediation analysis revealed that self-efficacy partially explains the relationship between distress and suicidal ideation; however, resilience did not have a significant moderating effect. The LPA identified three distinct psychological profiles, with the highest-risk group exhibiting significant distress and low self-efficacy. Conclusions: These results highlight the significant mental health burden faced by Palestinian youth and underscore the importance of internal psychological resources, particularly self-efficacy, that are associated with lower levels of suicidal ideation. Enhancing self-efficacy may offer a culturally relevant approach for prevention efforts in politically unstable environments.

Background: Social media addiction is a growing concern among undergraduates, with nursing students particularly vulnerable as their stressful academic and clinical context may promote excessive use, impaired sleep, and higher depression risk. Therefore, we aimed to evaluate whether sleep disturbance mediates the association between problematic social media use and symptoms of depression among nursing students in Mexico.

Methods: We conducted a multicenter, cross-sectional, analytical study using a random sample of 638 nursing students from three Mexican public universities. Between August and December 2024, participants completed validated scales for social media addiction, sleep quality, and depression. Counterfactual causal mediation analysis was performed using logistic regression with robust errors.

Results: Sleep disturbance affected 51.7% of students, and 27.5% reported depression. Social media addiction showed a dose-response association with both outcomes. Mediation analysis revealed a total effect on depression (OR = 2.19; 95% CI = 1.45-3.30) and an indirect effect via sleep disturbance (OR = 1.22; 95% CI = 1.01-1.38), explaining 31.4% of the effect.

Conclusions: Sleep disturbance partially mediates this association. Interventions addressing digital behavior and sleep hygiene may improve mental health in nursing students.

Artificial intelligence (AI) is generating a profound and quick transformation in several areas of knowledge, as well as in industry and society on a global scale, and is considered one of the most significant technological advances of the present era. Understanding citizens' attitudes toward AI is essential forguiding its development and implementation. To achieve this, valid and reliable instruments are needed to assess attitudesin different sociocultural contexts. With this objective, the General Attitudes towards Artificial Intelligence Scale (GAAIS) was adapted to Spanish. The sample comprised 644 participants: 327 men and 316 women, aged between 18 and 78 years (M = 33.06, SD = 14.91). The original two-factor structure (Positive GAAIS and Negative GAAIS) was validated using Confirmatory Factor Analysis (CFA). Both the fit indices and the internal consistency of the scale were adequate. Furthermore, the validity of the measure (i.e., convergent and discriminant) and the invariance of the model were confirmed. The analyses performed support the adequacy of the model and, therefore, the usefulness of the instrument, considering the ambivalence that people often experience regarding AI. The limitations of the study and the implications for the design of public policies and intervention strategies that promote the ethical, equitable, and socially responsible use of AI are discussed in this study.

(1) Background: With the continuous expansion of graduate education, the mental health of postgraduates has become a growing concern for both academia and society. Understanding how family and institutional resources influence psychological outcomes is critical for developing effective support strategies; (2) Methods: A cross-sectional survey was conducted among 3998 postgraduate students across China, including 3393 master's students (51.78% female, M = 24.21, SD = 1.521) and 605 doctoral students (37.19% female, M = 27.77, SD = 2.841). Multi-group structural equation modeling was employed to examine how family functioning and supervisor-postgraduate relationships influenced mental health, research self-efficacy, and suicidal tendencies; (3) Results: The findings showed that although most structural relationships were consistent across groups, two critical pathways were nonsignificant at the doctoral stage, providing evidence of partial structural invariance; (4) Conclusions: The study suggests that while family and school support generally play a protective role, their influence varies across educational stages. Tailoring psychological interventions to the distinct needs of master's and doctoral students is essential, offering both theoretical insights into the dual role of contextual resources and practical guidance for targeted mental health support in graduate education.