RETRACTED ARTICLE: Quality of life and its correlated factors among patients with substance use disorders: a systematic review and meta-analysis
Post-publication record
OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.
Bibliographic record
Abstract
BACKGROUND: Patients with substance use disorder (SUD) usually report lower quality of life (QoL) than other patients and as much as patients with other mental disorders. The present study investigated variables associated with QoL domains among patients with SUD. METHODS: 2021, were searched for on PubMed, Scopus, Cochrane, and Web of Science to identify primary studies on factors associated with QoL domains among patients with SUD. After reviewing for study duplicates, the full-texts of selected papers were assessed for eligibility using PECO (Participants, Exposures, Comparison and Outcome) criteria: (a) participants: patients with SUD; (b) exposures: sociodemographic factors, clinical, and service use variables; (c) comparison: patient groups without SUD; and (d) outcomes: four domains of QoL (physical, mental, social, and environmental domains). Three researchers recorded the data independently using predefined Excel spreadsheets. The Newcastle-Ottawa Scale (NOS) was used for assessing risk of bias and rated each study in terms of exposure, outcome, and comparability. Pooled odds ratios (ORs) and β coefficient were utilized at a 95% confidence level, and because sampling methods differed between studies' pooled estimates, a random effects model was utilized. RESULTS: After the assessment of over 10,230 papers, a total of 17 studies met the eligibility criteria. Five studies (1260 participants) found that patients with SUD who were older were less likely to have a good physical Qol (OR = 0.86, 95% CI = 0.78, 0.95). Two studies (1171 participants) indicated that patients with SUD who were homeless were less likely to have a good environmental Qol (β = -0.47, p = 0.003). However, a better mental QoL was observed in four studies (1126 participants) among those receiving support from their family or friends (social networks) (OR = 1.05, 95% CI = 1.04, 1.07). Two studies (588 participants) showed that those using cocaine were less likely to have a good mental QoL (OR = 0.83, 95% CI = 0.75, 0.93). Two studies (22,534 participants) showed that those using alcohol were less likely to have a good physical QoL (β = -2.21, p = 0.001). Two studies (956 participants) showed that those having severe substance use disorders were less likely to have a good mental (β = -5.44, p = 0.002) and environmental (β = -0.59, p = 0.006) QoL respectively. Four studies (3515 participants) showed that those having mental disorders were less likely to have a good physical QoL (β = -1.05, p = 0.001), and another three studies (1211 participants) that those having mental disorders were less likely to have a good mental QoL (β = -0.33, p = 0.001). Finally, two studies (609 and 682 participants) showed that individuals who experienced trauma symptoms or mental disorders were less likely to have good social and environmental QoL, respectively (OR = 0.78, 95% CI = 0.61, 1.00) and (OR = 0.92, 95% CI = 0.9, 0.94). CONCLUSIONS: The findings suggest the need for mental health services to improve the QOL among patients with SUD but further study is needed. Cocaine may cause behavioral changes which can increase the possibility of reckless and suicidal behaviors. Therefore, identifying cocaine user access, adherence, and satisfaction with treatment is recommended as an important component of adaptive functioning. Interventions that help patients with SUD get support from people within their social networks who support their recovery are also essential to their QoL.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.026 | 0.097 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.023 | 0.002 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".