Aging, care and dependency in multimorbidity: how do relationships affect older Bangladeshi women’s use of homecare and health services?
Bibliographic record
Abstract
Gender issues can create major barriers to healthcare utilization for older women with multimorbidity, especially in developing countries like Bangladesh. Elderly rural women in Bangladesh, are the poorest of the poor, and the women with multimorbidity live in a regulated family atmosphere. This study explored the relationship dimensions of older women with multimorbidity in homecare and their utilization of health services. To gain a deeper understanding of these complex issues, a qualitative case study was conducted. Semi-structured, in-depth interviews were conducted with 11 health staff and 22 older women with multimorbidity, living in three residential communities of the Sylhet District, Bangladesh. Our analysis used critical thematic discourse, a technique developed from Axel Honneth's recognition-and-misrecognition theory. Seven relationship dimensions have been identified, and grouped under three major themes: intimate affairs [marital marginalization and parent-children-in law dynamics]; alienation in community relationships [patriarchal sibling relationships, neighborhood challenges, and gender inequality in interactions]; and legal disconnections [ignorance of rights and missed communication]. Our findings revealed a lack of understanding of the women's multimorbid care needs and patriarchal marginalization in family. This lack of understanding together with poor peer-supports in healthcare is perpetuated by misrecognition of needs from service providers, resulting in a lack of quality and poor utilization of homecare and health services. Understanding the high needs of multimorbidity and complexities of older women's relationships can assist in policy decisions. This study deepens our understanding of the ways gender inequality intersects with cultural devaluation to reduce the well-being of older women in developing countries.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".