Impact of oil recession on community mental health service utilization in an oil sands mining region in Canada
Bibliographic record
Abstract
OBJECTIVES: This retrospective clinical audit compared changes in community mental health service utilization before and during an economic recession in an oil sands region in Canada which was characterized by a doubling of unemployment rates and poor economic outlook. METHODS: Sociodemographic descriptors, psychiatric antecedents, clinical characteristics and follow-up care were compared before and during the recession for newly assessed patients in community mental health clinics located across a Northern Alberta oil mining region. Data were collected retrospectively as part of a clinical audit process and then analysed with descriptive statistics, cross-tabular univariate analyses with chi-square tests using SPSS version 20. RESULTS: A total of 1,465 patients were included. Sociodemographic factors disproportionately elevated during the recession included male sex, Caucasian ethnicity, own home ownership, higher levels of education and unemployment. More patients seeking mental health care were already taking psychotropic medications (e.g. antipsychotics, benzodiazepines and stimulants). At the same time, disproportionately fewer patients engaged in substance abuse or had a prior formal history of mental health problems. The referral reasons during recession were less likely to be associated with substance abuse or mood concerns and more likely for 'other' reasons. The patients seeking psychiatric help during a recession were disproportionately likely to be diagnosed with personality disorders and 'other' less common diagnostic categories and less likely to suffer from mood or trauma-related diagnoses. Referrals for counselling and social services were also disproportionately more common during the recession. CONCLUSION: This study provides a comprehensive description of longitudinal patterns of mental health service utilization before and during a recession. The findings provide important evidence for policy and planning decisions to encourage resource allocation to help promote accessibility of the most needed community mental health resources.
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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) | 0.001 | 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".