Integrative review of the social determinants of health in older adults with multimorbidity
Bibliographic record
Abstract
AIM: To examine how the social determinants of health have been considered in conceptualizations of multimorbidity in older adults in the literature and to identify implications for nursing practice, research and healthcare planning and policy. BACKGROUND: The common conceptualization of multimorbidity is the presence of multiple chronic conditions where one is not more central than others. DESIGN: The integrative review methodology of Whittemore and Knafl was employed. The World Health Organization Social Determinants of Health framework was used to determine how the social determinants of health have been considered in conceptualizations of multimorbidity. DATA SOURCES: A search of electronic databases (2000-2015) generated 22 relevant articles, including quantitative and qualitative studies and grey literature reports. REVIEW METHODS: A systematic process was used to appraise the quality of the documents, conduct qualitative data analysis procedures of data extraction, coding and theme development, and synthesize conclusions. RESULTS: Current conceptualizations of multimorbidity provide limited consideration of the complex interplay of multimorbidity with the broader social determinants of health. Gender, education, behaviours and the health system were the most commonly cited determinants. Ethnicity, socioeconomic status/social class and material circumstances received little attention. Most of the dimensions of socioeconomic political context were not discussed. CONCLUSION: The predominant conceptualization of multimorbidity focuses on the biomedical dimensions of multimorbidity. Consequently, nursing practice, research and policy informed by this literature could inadvertently sustain the mismatch between the needs of older adults with multimorbidity and the services they receive. Future research to inform a new conceptualization is necessary.
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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 | 0.008 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| 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".