Distinguishing Abuse from Caregiving in Rural Nigeria: Older Adults’ Perspectives
Bibliographic record
Abstract
In Nigeria, older adults face numerous challenges that undermine their well-being and overall life satisfaction. These challenges include but are not limited to health challenges due to biological consequences of ageing, ageing stereotypes, abuse, and neglect. This study explored abuse of rural-dwelling older persons within informal caregiving settings, focusing on older adults' perspectives of some caregiving styles adopted by their caregivers. Data were obtained using semi-structured interviews with 16 older adults 60 years and above, in a rural community in Awgu Local Government Area (LGA), Enugu state. The data were analysed thematically. Findings revealed that some abusive behaviours that pass as appropriate caregiving styles include restricted movements, forcing older people to eat or take medications and collecting their money/properties. Most of the sampled older adults were found to have negative perceptions about these caregiving styles, while other participants downplayed them as a regular caregiving pattern. The study recommends that caregivers undergo training on appropriate styles for caring for their older adults in rural Nigeria.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".