Social needs of individuals with multimorbidity: A meta-synthesis
Bibliographic record
Abstract
Social needs refer to the needs associated with the downstream influence of sociocultural and economic determinants affecting the availability of basic amenities, services, and health and social care programs and policies. Social needs are instrumental in shaping the lives and health behaviours of individuals with multimorbidity. Previous reviews explored the care needs, treatment, and support in individuals with multimorbidity. However, the social needs of this population are poorly understood. This review aimed to develop a comprehensive understanding social needs of individuals living with multimorbidity. A meta-synthesis was conducted. Literature was searched within eight databases including grey literature databases. In total, 31 studies published from January 2010 to May 2023 were included in the synthesis. Thematic synthesis approach was used for to develop analytical themes and the themes were then mapped to Bradshaw (1972) taxonomy of social needs. The felt needs included: Requiring strong social network to combat disease-associated challenges and combat social isolation & Need for readily available health and social care assistance. The expressed and comparative needs included: Need for improved health insurance to compensate for disease related expenses and need for social action to address unfair societal behaviors. Individuals with multimorbidity sought improved social connectedness and access to readily available health and social care resources. Social stigma associated with disease, race, disability, and physical appearance affects the meeting of individuals general and health care related social needs.
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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 | 0.024 | 0.059 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.017 |
| Bibliometrics | 0.015 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| 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".