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: The study examined whether adolescents receiving a universal, school based, drug prevention program in Grade 7 varied, by student profile, in substance use behaviors post program implementation. Profiles were a function of recall of program receipt and substance use at baseline.
Methods: A secondary analysis was conducted on data from the Adolescent Substance Abuse Prevention Study, a large, geographically diverse, longitudinal school-based cluster-randomized controlled trial of the Take Charge of Your Life drug prevention program. Profiles were created using self-reported substance use (preintervention) and program recall (postintervention) at Grade 7. First, characteristics of each of the 4 profiles of treatment students who varied by program recall and baseline substance use were explored. Then, multilevel logistic regression analyses were used to examine differences in the odds of substance use (alcohol, tobacco, and marijuana) among student profiles at the 6 additional study waves (Time 2 [Grade 7] through Time 7 [Grade 11]).
Results: Pearson's chi-square tests showed sample characteristics varied by student profile. Multilevel logistic regression results were consistent across all examined substance use behaviors at all time points. Namely, as compared with students who had no baseline substance use and had program recall (No Use, Recall), each of the remaining 3 profiles (No Use, No Recall; Use, Recall; Use, No Recall) were more likely to engage in substance use. Post hoc analyses showed that for the 2 subprofiles of baseline substance users, there were only 2 observed, and inconsistent, differences in the odds of subsequent substance use by recall status.
Conclusions: Findings suggest that for students who were not baseline substance users, program recall significantly decreased the likelihood of subsequent substance use. For students who were baseline substance users, program recall did not generally influence subsequent substance use. Implications for school-based drug prevention programs are discussed.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4336848 | PMC |
http://dx.doi.org/10.1080/08897077.2014.952364 | DOI Listing |
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