Addressing racism in respiratory therapy educational programs: An integrative literature review
Bibliographic record
Abstract
Introduction/background: The impacts of racism on the experiences of under-represented minorities in health education programs such as respiratory therapy can impede the ability of these students to succeed in these programs and in the healthcare workplace. This can exacerbate the discrepancy between the racial diversity of the healthcare workforce and that of the population that they intend to serve. Methods: An integrative literature review was conducted to examine and integrate the published literature that describes how racism is expressed and addressed in health education programs and in healthcare workplaces. Results: Thirty-one studies were reviewed that included a variety of allied health professions. Racial discrimination in these programs is characterized as racial stereotyping, micro-aggressions, significant cognitive and emotional burdens, socio-economic challenges, and organizational impediments. Individual coping strategies such as confronting racism directly or minimizing its existence and seeking and offering social and cultural supports are reported. At an institutional level, policies to address racism, foster an inclusive culture, and develop programs that enable and support diversity and career progression have been described. Discussion: A conceptual model that frames the factors that enable racism (both extrinsic/societal and intrinsic/individual) against strategies that mitigate the effects of racism (both institutional and individual) is proposed and applied to respiratory therapy programming. Conclusion: Respiratory therapy programs must acknowledge, prioritize, and address racism consistently and systemically. Targeted research is required to explore the specific experiences of this profession, and to validate the effectiveness of the strategies described to redress the inequities unmasked by racism.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| 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".