Rural suicidology: Towards a unified and developmental systems approach.
Bibliographic record
Abstract
Over 700,000 documented suicides occur annually, with millions more making attempts or thinking of suicide. One subset of individuals believed to be at increased risk for suicide are individuals from rural regions. Indeed, reviews have highlighted an abundance of factors linked to increased suicide risk in rural areas. However, there are major concerns regarding this literature, namely the consistency in how the construct ‘rural’ is defined in the context of suicide and the lack of approaches that account for contexts within which an individual develops. The current program of research sought to apply a developmental systems perspective to rural suicidology. Specifically, the first study is a comprehensive review of 142 studies that investigated rural suicide. We explored how rural has been operationalized and measured in rural suicidology. This review highlighted potential factors, across all levels of influence in an individual’s developmental system, that may be responsible for increased suicide risk in rural regions. The results indicate a lack of clarity concerning how rurality has been defined and what constitutes suicide risk in rural areas. Accordingly, we provide recommendations for moving the field of rural suicidology forward. The second study investigated the perspectives of 12 health care providers for rural residents in Newfoundland and Labrador (NL); this unique population is linked to various levels of influence for rural residents (e.g., direct care with residents; interactions with managers). Given the unique experiences of health care providers that are embedded in a broader system, the second study investigated how providers conceptualized rural and what they perceived as the factors that increase suicide risk in the rural regions that they serve. The results of the second study illuminate multiple key avenues to reduce suicide risk in rural NL. Ultimately, the findings from this program of research suggests that rural suicidology is an important field with much room for improvement. As such, we provide tangible recommendations for researchers, policy influencers, and individuals directly involved in the suicide-related care of rural residents. We hope the result of these recommendations can unify, guide, and support those invested in supporting rural residents and help people choose to live.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| 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".