Editorial: Social inequality and equity in community actions for health
Bibliographic record
Abstract
Consequently, we launched this research topic on the 21 st of September 2021 with the aim of cataloguing articles that document health inequality and inequity globally as well as articles that address both through community action.Of the manuscripts that were submitted, we eventually accepted and published 10 which fall into four research areas: (1) relationship between social inequality and health outcomes, (2) community actions among socially vulnerable groups, (3) role of health professionals in addressing health inequity in communities and (4) new concepts in defining health disparities.There is a gradient between socioeconomic status and health with each level in the hierarchy generally having less morbidity and mortality. For some health conditions, however, there has been no change in health or worsening health status over time for economically disadvantaged populations. 6 Holder-Pearson and Chase in their opinion article describe how certain marginalized ethnic and socioeconomic groups in New Zealand bear a disproportionately high burden of Type 2 diabetes mellitus, suffer higher financial costs of care and have lower access to life-saving treatment. Contrarily, two studies in our topic did not elicit negative health outcomes among populations with social disadvantages. First, Chan et al. in their review article show that individuals experiencing homelessness and traumatic brain injuries in studies from United States of America and Canada had rehabilitation services available to them. They recommend that existing rehabilitation for these individuals should be tailored to include screening for TBI, conducting cognitive and functional assessments and involve multidisciplinary teams. Second, Hamilton et al. in their single-center retrospective study of 73 children with medical complexities presenting with sepsis, did not find any association between social determinants of health and length of stay in the pediatric intensive care unit.Community actions play a vital role in promoting health equity, as they occur at a level closer to individuals and can be better targeted at high-risk individuals. Each community is unique in the nature and degree of health inequities as well the required community-based efforts. These articles underscore the central role health care professionals have in addressing health inequity. Indeed, a previous study includes provider distribution according to population need and practice patterns oriented to addressing root causes of disparities as some of the critical domains to advancing health equity. 8 Two new concepts feature in the fourth area of research. The first by Dierx and Kasper details the development of a new grouping to measure socio-economic status, providing new insights into health inequalities. This is critical since advancement of health equity requires a proper assessment of differences in health and its determinants. 9 Development of structured formats of measurements for different societies is deemed necessary. 10 The second by Ju et al. proposes a new model for the process of rumor diffusion about COVID-19 and they recommend announcing true information publicly to instantly contain the COVID-19 rumor diffusion.In conclusion, our research topic brought together multiple scientific disciplines to catalogue social inequality, health inequity, community and health care professionals' actions and innovation to advance health equity. The COVID-19 pandemic has highlighted the relevance of communitybased efforts to advance health equity. Most of our studies were cross-sectional; further studies that use randomized control trials and/or longitudinal data are recommended to establish causal relationships.
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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 | 0.010 | 0.041 |
| Meta-epidemiology (narrow) | 0.006 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.020 | 0.023 |
| Insufficient payload (model declined to judge) | 0.021 | 0.010 |
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".