Aging, care and dependency in multimorbidity: how relationships affect elderly women’s homecare and health service use
Bibliographic record
Abstract
Relationships are multidimensional, and we know little about the facets of relationships in the way elderly patients’ with multimorbidity utilise homecare and health services. Gerontology literatures emphasize the importance of place of care, inequalities, availability of health services and affordability. However, the diversity of relationships and associated dependency in elderly care remain underassessed. A qualitative study involving a demographic survey and interviews was conducted to explore relationship experiences of elderly women with multimorbidity in homecare and health services utilization. Civil Surgeon of Sylhet District in Bangladesh was contacted to recruit participants for the study, and this resulted in 33 interviews [11 staff and 22 elderly women with multimorbidity]. Three domains of Axel Honneth’s Theory of Recognition and Misrecognition [i.e. intimate, community and legal relationships] were used to underpin the study findings. Data was analysed using critical thematic discourse method. Four themes were emerged: nature of caregiving involved; intimate affairs [marital marginalization, and parent-children-in law dynamics]; alienation in peer-relationships and neighbourhood [siblings’ overlook, neighbourhood challenges, and gender inequality in interactions]; and legal connections [ignorance of rights, and missed communication]. A marginalization in family relationships, together with poor peer supports and a misrecognition from service providers, resulted in a lack of care for elderly women with multimorbidity. Understanding the complexities of elderly women’s relationships may assist in policy making with better attention to their health and well-being support needs. Staff training on building relationships, and counselling services for family and relatives are essential to improve the quality of care for the women.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".