Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
98%
921
2 minutes
20
Problematic mobile phone use (PMPU) has become increasingly prevalent among young adults, raising concerns about its psychological underpinnings. While shyness has been linked to PMPU, few studies have explored the symptom-level mechanisms that differentiate problematic from non-problematic users. This study employed psychological network analysis to examine the structure and central symptoms of PMPU in two groups: problematic and non-problematic mobile phone users. A total of 3227 young adults (19.21 ± 3.71 years) completed standardized measures of PMPU and shyness. Results showed that loneliness and time spent on mobile phone use formed the strongest edge in both groups. Withdrawal and mood modification were highly central in the PMPU network. Cross-symptom analysis indicated that social embarrassment and technology-mediated compensation form a self-reinforcing feedback loop in high-risk individuals. Key interactions were identified between mobile phone overuse and reduced offline social competence, inefficiency in real-world interactions, and avoidance of face-to-face communication. These findings suggest that interventions targeting emotional regulation symptoms may be particularly effective in reducing PMPU. The study also highlights the utility of psychological network analysis for identifying differential mechanisms in digital behavior patterns.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.addbeh.2025.108481 | DOI Listing |