Impact of benzodiazepine use on quality of life, mental health and cognitive function in the elderly population
Bibliographic record
Abstract
Background: Benzodiazepines (BZD) are among the most prescribed psychotropic drugs in clinical practice, commonly used to treat mood disorders, anxiety, depression, epilepsy, and insomnia. However, their use is increasingly prevalent among the elderly, often without appropriate therapeutic indications, leading to misuse. This misuse is associated with chemical dependence, worsening of delusional conditions, increased risk of falls, and cognitive changes. Objective: To compare the aging process of elderly individuals using benzodiazepines with those who do not. Methods: This cross-sectional, descriptive study was conducted in Anápolis, Goiás, including individuals over 60 years old. Data were collected after ethical approval using nine questionnaires: sociodemographic, WHOQOL-bref (World Health Organization Quality of Life Instrument), Katz Index, Lawton Scale, GDS-15 (Geriatric Depression Scale), HAM-D (Hamilton Depression Rating Scale), GAD-7 (Generalized Anxiety Disorder 7-item scale), MoCA (Montreal Cognitive Assessment), and Morse Fall Scale. Data were analyzed using IBM SPSS Statistics 29.0.1.0 with Fisher-Freeman-Halton exact test. Results: A total of 37 interviews were conducted, with one excluded due to withdrawal, leaving 36 participants (30.6% men). Most were aged 60-69 (50%), married or in a stable union (61.1%), mixed race (69.4%), and had only primary education (63.9%). BZD use was reported by 13 (36.1%) participants, primarily for insomnia (53.8%). Quality of life, measured by WHOQOL-bref, showed that BZD users had lower physical domain scores (mean 56.74%, p=0.058). Depression, assessed by GDS-15, indicated that 75% of those with scores suggesting depression were BZD users (p=0.059). The HAM-D scale also showed a significant association between BZD use and depression (p<0.001). Anxiety levels, measured by GAD-7, showed no significant difference related to BZD use (p=0.610). Cognitive function, assessed by MoCA, revealed that 92.3% of BZD users scored below the cutoff of 26 points, although this was not statistically significant (p=0.114). Fall risk, assessed by the Morse Fall Scale, indicated that 46.1% of BZD users had a low fall risk, and only 15.4% had a high fall risk, compared to 4.3% of non-users (p=0.214). Conclusion: The findings suggest that benzodiazepine use in the elderly is associated with poorer physical health, higher rates of depression, and lower cognitive function, although the latter was not statistically significant. These results highlight the need for careful prescription practices to avoid the negative impacts of these drugs on healthy aging.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".