Medication use in community-dwelling older people: pharmacoepidemiology of psychotropic utilisation
Bibliographic record
Abstract
INTRODUCTION: Psychotropic medications have a significant adverse drug event profile, particularly in older adults, and appropriate use is paramount. Patterns of prescribing in community-dwelling older adults in New Zealand remain unknown. AIM: This study aimed to determine the prevalence and the pattern of psychotropic use amongst community-dwelling older people in New Zealand and to identify any association between depressive symptomatology and psychotropic medication use. METHODS: Data were collected on the demographics, medication use and mood status of community-dwelling older adults from two New Zealand studies: the BRIGHT trial, which recruited potentially disabled participants (N=141) and the DeLLITE trial, which recruited potentially depressed participants (N=193). The prevalence and the pattern of psychotropic use were established and the gender, age and level of depression assessed using regression analysis. RESULTS: The use of any psychotropic medication was 28.9% in the BRIGHT trial and 43.5% in the DeLLITE trial. Antidepressants were the most commonly used psychotropic medication in the two studies, followed by hypnotics and sedatives. Psychotropic use was highly correlated with the presence of depressive symptoms in the BRIGHT trial and with female gender in the DeLLITE trial. Age was not associated with psychotropic medication use. In both studies, there is possible underdiagnosed, undertreated and inappropriately treated depression. DISCUSSION: The prevalence of psychotropic medication use is high in community-dwelling older people with disability and very high in community-dwelling older people with depressive symptoms, but varies by gender and level of depression.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".