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: 3122
Function: getPubMedXML
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: Many people who face adversity, such as disasters, demonstrate resilience. However, less is known about reactions to large scale disasters with longer recovery periods. The concern is that protracted disasters may result in more chronic or accumulated stressors with an uncertain or unknown end point and can exhaust the natural coping methods and ability to rebound. Thus, understanding patterns of longer-term disaster recovery, inclusive of resilience, is needed. Further resilience is not individual specific rather social determinants, such as support networks and available resources, are contributing factors.
Methods: The purpose of this study is to improve understanding of mental health and resilience during increased stress, we aim to identify profiles of adaptation and psychological and social determinants that predict membership within predominant symptom groupings. We conducted an exploratory cross-section study ( = 334) with two phases of multivariate analysis. Latent profile models were estimated to identify groups based on depression, anxiety, and resilience scores. The second phase included a step-wise multinomial logistic regression to predict class membership.
Results: We identified four distinct groups: 33% of participants were categorized as anxious, 18% depressed, 9% comorbid, and 40% with above average levels of resilience. Psychosocial factors such as demographics, trauma history, information access, loneliness, and lack of financial resources predicted poorer mental health outcomes and lower resilience.
Conclusion: This study identified factors that contribute to overall wellbeing despite chronic stressors. Social determinants of adaptation, found in this study population, include loneliness, finances, and information access. The findings from this study support the need for both psychological and social adaption supports, inclusive of mental health treatment, to strengthen resilience activation.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10925763 | PMC |
http://dx.doi.org/10.3389/fpsyg.2024.1245765 | DOI Listing |
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