What Are the Most Distressing Aspects of Experiencing Elder Abuse? Findings From a Qualitative Study With Victims
Bibliographic record
Abstract
Abstract Adult protective services and other community-based agencies respond to hundreds of thousands of elder abuse cases annually in the United States; however, few studies include elder abuse victims’ voices. This study explored the most distressing aspects of elder abuse, as identified by victims themselves; to date, this is the first known study on this topic. Guided by a phenomenological qualitative methodology, this study conducted in-person, semi-structured interviews with a sample of elder abuse victims (n = 30) recruited from a community-based elder abuse social service program in New York City. To enhance trustworthiness, two researchers independently analyzed transcript data to identify key transcript codes/themes. Distressing aspects of elder abuse were identified across three key domains, related to feelings of loss (50% of codes), threats/negative consequences (55%), and client-needs/system incongruity (14%). Specifically, the first theme represented outcomes related to loss of relationships (19% of ‘loss’ codes), personhood (16%), credibility (19%), faith/trust in others (38%), and finances (8%). The second theme looked at threats to physical self (34% of ‘threat’ codes), psyche (39%), and others, including the perpetrator (27%). The third theme focused on mismatches in client/system goals (50% of ‘incongruity’ codes) and legal system involvement (50%). The findings in this study provide a comprehensive and conceptually organized range of aspects to serve as infrastructure for the development of meaningful interventions to address the needs of victims. This study represents one of the largest efforts to understand and integrate the perspectives and needs of victims into elder abuse intervention practice/research to date.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".