Drug-Substance Abuse, Age at Onset and Contributing Factors to Stoppage of Drug Use among Students in Aluu Community
Bibliographic record
Abstract
Background: Most drug-substance abusers do have withdrawal symptoms considering the type of drug. Some of the symptoms include: changes in appetite, changes in mood, congestion, seizure, fatigue etc. These symptoms make it difficult for someone to effectively withdraw. It therefore means that for someone to effectively withdraw from drug abuse, there are other factors that must come into play to enhance success. Hence, this study was done to determine the contributing factors to stoppage of drug use among students in university of Port Harcourt’s host communities as an attempt to curb the menace and its effect on students and the entire society at large.
 Materials and Methods: The study was a descriptive cross-sectional study carried out in ALUU Community in Ikwerre Local Government Area of Rivers State between August 2019 and December 2019. The study involved 150 volunteers recruited randomly through a multi-staged sampling technique which included secondary school students, undergraduates who are 13yrs and above residing in ALUU community while those who did not give consent were excluded. The data was collected using self-structured close-ended self-administered questionnaires and data analysis done using SPSS version 25. 
 Results and Discussions: The results of the study showed that the proportion of students that have stopped drug/substance abuse was 7.34%, the most prevalent age group at onset of drug use was 16-18yrs, and 26.42% of students used drugs/substance daily. The most prevalent reason for stopping drug use was personal decision 54.55%, while the least proportion was other reason 9.09%; Family and religious leaders had equal influence (45.45%) in the stoppage of drug/substance use by students.
 Conclusion: The results of the study showed that the most prevalent reason for stopping drug use was personal decision 54.55%, Family and religious leaders (45.45%) were the major contributing factors and had equal influence in the stoppage of drug/substance use by students.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.033 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".