Reaching Out for Help: Recommendations for Practice Based on an In-Depth Analysis of an Elder Abuse Intervention Programme
Bibliographic record
Abstract
Elder abuse is a growing public health concern with serious and sometimes fatal consequences. Intervention research is lacking despite its potential value to victim protection. This study investigates the first and longest-running social work intervention programme for elder abuse in Canada. The aim of this study is to provide a better understanding of the scope of the problem and needs of the population to inform programme development through the recommendations made. One hundred and sixty-four cases of elder abuse reported from January 2012 to April 2014 were examined. Case characteristics and related recommendations are reported. Third parties reported most abuse, which was typically emotional and financial; polyvictimisation was present in most cases. Intake practices that may have facilitated reporting are described and recommendations to improve victim reporting and confidentiality are made. Victim health problems and dependency were common and many victims lacked support. Perpetrators often resided with victims and had mental health and social-functioning problems. Case management varied in length and several barriers were identified. Multi-agency work is recommended to better manage the needs of the victim, risk factors related to the perpetrator and victim–perpetrator cohabitation. Recommendations to improve the safety of the victim and that of professionals are also made.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.061 | 0.124 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.009 | 0.009 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".