Health needs of older people and age-inclusive health care in humanitarian emergencies in low-income and middle-income countries: a systematic review
Bibliographic record
Abstract
Health needs of older people in humanitarian settings are poorly documented, negatively affecting the appropriateness of health services they receive. This Review identified the major health needs of older people across humanitarian contexts, including non-communicable diseases and mental health conditions (eg, psychological distress and depression). Barriers to health care of older people included inaccessibility of health-care services; shortage of appropriate health care; insufficient availability of medications and medical equipment; poor geriatric expertise of health-care staff, health policy makers, and health authorities; and age discrimination by health-care personnel. Individual factors included low mobility, poor health literacy, dependence on others for access to care, and self-directed ageism. The participation of older people in shaping health-care services was highlighted as a facilitator of age-inclusive care. Several understudied areas related to the health needs of older people in humanitarian emergencies in low-income and middle-income countries were exposed. We urge governments, academic institutions, humanitarian organisations, and other health-care providers to focus their response and research efforts on the health needs of older people in conflict settings; the health needs of older people in humanitarian emergencies in understudied regions; and on neglected issues such as communicable diseases, cancer, neurocognitive disorders, sexual and reproductive health, genitourinary conditions, and nutrition. The participation of older people in the design, implementation, and evaluation of health-care services is essential to ensure accessibility, appropriateness, and acceptability of care.
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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".