A systematic review of evidence-based aftercare for older adults following self-harm
Bibliographic record
Abstract
OBJECTIVE: Self-harm is closely associated with suicide in older adults and may provide opportunity to intervene to prevent suicide. This study aimed to systematically review recent evidence for three components of aftercare for older adults: (1) referral pathways, (2) assessment tools and safety planning approaches and (3) engagement and intervention strategies. METHODS: Databases PubMed, Medline, PsychINFO, Embase and CINAHL were searched from January 2010 to 10 July 2021 by two reviewers. Empirical studies reporting aftercare interventions for older adults (aged 60+) following self-harm (including with suicidal intent) were included. Full text of articles with abstracts meeting inclusion criteria were obtained and independently reviewed by three authors to determine final studies for review. Two reviewers extracted data and assessed level of evidence (Oxford) and quality ratings (Alberta Heritage Foundation for Medical Research Standard Quality Assessment Criteria for quantitative and Attree and Milton checklist for qualitative studies), working independently. RESULTS: Twenty studies were reviewed (15 quantitative; 5 qualitative). Levels of evidence were low (3, 4), and quality ratings of quantitative studies variable, although qualitative studies rated highly. Most studies of referral pathways were observational and demonstrated marked variation with no clear guidelines or imperatives for community psychiatric follow-up. Of four screening tools evaluated, three were suicide-specific and one screened for depression. An evidence-informed approach to safety planning was described using cases. Strategies for aftercare engagement and intervention included two multifaceted approaches, psychotherapy and qualitative insights from older people who self-harmed, carers and clinicians. The qualitative studies identified targets for improved aftercare engagement, focused on individual context, experiences and needs. CONCLUSION: Dedicated older-adult aftercare interventions with a multifaceted, assertive follow-up approach accompanied by systemic change show promise but require further evaluation. Research is needed to explore the utility of needs assessment compared to screening and evaluate efficacy of safety planning and psychotherapeutic approaches.
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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 | 0.015 | 0.063 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".