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: The increasing prevalence of depressive symptoms has emerged as a critical public health issue globally, highlighting the need for analyses of the factors contributing to depressive symptoms within the Chinese population and the development of targeted recommendations for improving mental well-being. We aimed to explore the correlation between internet use and depressive symptoms and the role of socioeconomic inequalities in this association.
Methods: We included data on 8019 residents aged 18 years and above, which we retrieved from the 2018 and 2020 waves of the China Family Panel Studies. We used latent profile analysis to categorise individuals' internet usage patterns and multiple linear regression to determine their association with depressive symptoms.
Results: Higher socioeconomic status (SES) was associated with fewer depressive symptoms (τ = -0.08; 95% confidence interval (CI) = -0.36, -0.18). Individuals in the high-dependence group presented a greater likelihood of developing depressive symptoms (τ = 0.04; 95% CI = 0.007, 0.66). We observed no significant difference in the interaction effect between individual-level SES and the four patterns of internet usage. However, compared with urban-dwelling respondents, those in rural areas had a stronger association between internet usage patterns and depressive symptoms, especially those in the high-dependence group (τ = -0.07; 95% CI = -1.47, -0.20).
Conclusions: Our findings indicate a significant association between depressive symptoms and internet usage patterns, indicating a need for interventions related to internet use, especially those targeted at reducing the risk of depressive symptoms in individuals of lower SES.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11327895 | PMC |
http://dx.doi.org/10.7189/jogh.14.04127 | DOI Listing |
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