Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Background: Self-efficacy, a critical psychological construct representing an individual's belief in their ability to control their motivation, behavior, and social environment. In adolescents, self-efficacy plays a crucial role in mental health, particularly concerning depressive symptoms. Despite substantial research, the complex interplay between self-efficacy and depressive symptoms in adolescents remains incompletely understood.
Aims: The aim of this study is to investigate the complex interrelationships between self-efficacy and depressive symptoms in adolescents using psychological network analysis.
Methods: The cross-sectional study involved 3,654 adolescents. Self-efficacy was assessed using the General Self-Efficacy Scale (GSES), and depressive symptoms were measured with the Patient Health Questionnaire-9 (PHQ-9). Network analysis, incorporating the least absolute shrinkage and selection operator (LASSO) technique and centrality analysis, constructed and compared self-efficacy networks between depressive symptoms and healthy control groups.
Results: Of the 3,654 participants, 560 (15.32%) met criteria for moderate to severe depressive symptoms (PHQ-9 scores ≥10). Among those with depressive symptoms, 373 (66.61%) had moderate, 126 (22.50%) had moderate-severe, and 61 (10.89%) had severe symptoms. Bivariate correlation analyses revealed a significant negative correlation between depressive symptoms and self-efficacy ( = -0.41, < 0.001). The results of the network analysis showed significant differences in self-efficacy networks between adolescents with and without depressive symptoms (global strength: = 0.25, < 0.05). Depressed participants showed a network with reduced global strength, suggesting diminished interconnectedness among self-efficacy items. Specific connections within the self-efficacy network were altered in the presence of depressive symptoms. Bridge analysis revealed that effort-based problem-solving (bridge strengths = 0.13) and suicidal ideation (bridge strengths = 0.09) were the key bridge nodes.
Conclusion: Adolescent depressive symptoms significantly impacts the self-efficacy network, resulting in diminished integration of self-efficacy and highlighting the complex interplay between self-efficacy and depressive symptoms. These findings challenge the traditional unidimensional view of self-efficacy and emphasize the need for tailored interventions focusing on unique self-efficacy profiles in adolescents with depressive symptoms.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11393584 | PMC |
http://dx.doi.org/10.3389/fpsyg.2024.1419920 | DOI Listing |
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