Alcohol use among Older Adults in Inpatient Psychiatry in Ontario: Individual and Community Factors Related to Problematic Use
Bibliographic record
Abstract
Background: Alcohol use among older adults is usually not identifiable and could be mistaken for other medical or psychiatric conditions. As sometimes an underlying cause, problematic alcohol use (PAU) continues to impact older adults with mental health issues who are admitted to inpatient psychiatry care. About 60% of older adults with undiagnosed alcohol related problems are found to have depression, repeated falls, delirium, heart failure, or chest infections when admitted to acute care (2). The associations between PAU and poor health outcomes is concerning as it could exacerbate the health conditions of older adults. Current predictions indicate an increase in the older adult population in Canada. Therefore, using the Andersen behavioural model of health care use, this study sought to investigate the prevalence of PAU among older adults, the characteristics of older adults who use alcohol, and the types of community support systems available. \nMethods: Two data sources were used for this study. First, data from the Ontario Mental Health Reporting System (OMHRS) with inpatient information on mental and physical health, social support and service use, based on the Resident Assessment Instrument-Mental Health (RAI-MH) was used to conduct a multiple logistic regression analysis. OMHRS sample data included all older adults discharged from an inpatient mental health hospital between January 1, 2011, and December 31, 2016. Second, data from ConnexOntario was used to conduct a geographic analysis of psychiatric admission rates in relation to health service locations and PAU in the Waterloo-Wellington region of Ontario. \nResults: Study results from the OMHRS data indicated that of the total number of older adults admitted to inpatient psychiatric care (n = 21,577), about 10% (n = 2,107) had PAU. Older adult men were twice as likely to have PAU compared to women. Older adults had an increased the odds of having PAU if they were educated (1.4), employed (1.5), or living in their own residence (1.3). However, living with someone (0.8) and being 65 years or older (0.6) decreased the odds of an older adult having PAU. Contextual results for the Waterloo-Wellington region of Ontario showed that the clustering of psychiatry admissions for older adults were higher in areas with a cluster of services such as Guelph and Cambridge. However, in areas such as rural Wellington, there were high psychiatry admission rates for older adults but fewer mental health and addictions services. The study findings indicate that more seniors programs were needed to support older adults with mental health and addiction problems. In addition, older adults with PAU were likely to face the challenge of traveling further to utilize current available mental health and addictions support services in other cities. \nConclusion: This study identified the prevalence and characteristics of PAU among older adults admitted to psychiatric inpatient treatment; and highlighted some of the individual and contextual factors that are associated with the increased odds of PAU among this population. On an individual level, understanding the associated mental health and addictions service needs of older adults could contribute to providing better support before, during, and after psychiatry admissions. Contextually, factors such as the availability and accessibility of these mental health support services for older adults need to be further investigated to identify its role in service utilization.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".