UNCONVENTIONAL INDICATORS OF DRUG DEPENDENCE AMONG ELDERLY LONG-TERM USERS OF BENZODIAZEPINES
Bibliographic record
Abstract
A quarter of the elderly population is prescribed benzodiazepines (BZD). This has led to growing concerns about drug dependence and the validity of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) criteria for dependence to a substance. This study aimed to understand how dependence was experienced by long-term BZD users. Interviews were conducted with 45 elderly persons who had been using BZDs for an average of nine years. These users' comments suggest six indicators of dependence: self-identifying as a dependent user, invoking multiple stressors to justify BZD use, using BZD to cope with anticipated stressors, trivializing the dangers of BZDs, keeping a supply in reserve, having previously tried and failed to stop, and reducing the dosage. Our results stress the need to take a more elaborate, person-centered view of dependence.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; 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".