Systemic model of chronic benzodiazepine use among mature adults
Bibliographic record
Abstract
OBJECTIVES: Our goal was to build a systemic model of chronic use among community-dwelling mature benzodiazepine (BZD) users. BZDs are commonly prescribed for symptoms of anxiety and/or insomnia despite their documented side effects over time. METHOD: We conducted in-depth interviews with 23 mature (50 years and over) users, 14 women and 9 men, as well as 9 general practitioners and 11 pharmacists. We chose the grounded theory approach for our analysis. RESULTS: Results yielded a systemic model of chronic BZD use, illustrating onset and maintenance of use, and taking into account individual life context, intervening conditions (e.g. family and doctor--patient interactions) and structural factors (medicalization, ageism, influence of the media and pharmaceutical industry, etc.). Based on our findings, we suggest that intervention should go beyond medical issues and extend to the individual's perception of aging in the modern society, as well as attitudes of families and health professionals regarding long-term BZD use. Family members should be involved in the weaning process and adoption of new life habits. General practitioners should be better trained regarding geriatric psychosocial issues and offer alternatives to prescribe psychotropic drugs such as cognitive behavior therapy for insomnia. Also, as a society, we should reconsider the highly medicalized stance we take to compensate for age-related losses. The influential role of the pharmaceutical industry in the process is discussed. CONCLUSION: We conclude that a predominantly biomedical perspective on human development diminishes patient-centered care within a socially contextualized, individual perspective.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".