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
This is a dataset that identifies data regarding the correlation between dimensions of school attachment and Internet addiction. The data was gained from a research population of adolescents aged 15-19 years attending secondary schools in Kosovo. The whole sample consists of 525 students, 310 (59%) of them were female, and 215 (41%) were male, respectively 214 (40.8%) were students attending the tenth grade, 189 (36%) were in the eleventh grade and 122 (23.2%) were in the twelfth grade. Data was collected via a survey with paper-pencil questionnaires from 6 different secondary schools from 4 different cities in Kosovo. Stratified and purposive sampling techniques were used. Research analyses were conducted with SPSS, using descriptive statistics and Spearman's analysis, which aimed to examine the non-parametric relationship between dimensions of school attachment and internet addiction. The research instrument was verified to have all the necessary psychometric values considered suitable for research. Several descriptive statistical analyses were performed to further clarify the data and provide the necessary platform for further analysis.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10577046 | PMC |
http://dx.doi.org/10.1016/j.dib.2023.109638 | DOI Listing |
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