“Your double-blind RCT needs feminism”: an argument for engaging critical theory in quantitative rehabilitation research
Bibliographic record
Abstract
PURPOSE: Rehabilitation science has, for years, endorsed a connection between quantitative research and the philosophical assumptions of positivism. These assumptions can limit the scope of rehabilitation research, particularly in relation to matters of equity, diversity, and inclusivity. As our field moves toward a greater focus on inclusivity in research design and patient-centred care, it is imperative that we reconsider the theoretical foundations of rehabilitation research and practice. METHODS: We provide an analysis of positivism on equity, diversity, and inclusivity within quantitative rehabilitation research, using the Participant Intervention Comparison Outcome (PICO) model to provide structure for the resultant discussion and recommendations. RESULTS: Our analysis reveals that there are significant limitations and ethical concerns to engaging in positivism as the primary paradigm for quantitative rehabilitation research. We argue that decoupling of positivism and quantitative research methods may be warranted. CONCLUSIONS: Equitable and inclusive rehabilitation research requires the researcher to consider variables which are neglected in the positivist paradigm. We argue that critical theory can equip researchers with a lens to better address injustices within rehabilitation research. We provide a series of recommendations for researchers to engage critical theory at each stage of the PICO model of clinical trials.IMPLICATIONS FOR REHABILITATIONCommon assumptions in quantitative rehabilitation research (i.e., positivism) can limit the utility of research findings to rehabilitation patients.Equitable, diverse, and inclusive participant samples in research better reflect the diversity of real world rehabilitation patients, helping us better serve these populations.Critical theory can help researchers and clinicians identify and avoid interventions that may cause harm to rehabilitation patients.Research and practice that prioritize concepts of "normalcy" (i.e., "normal gait," "normal behaviours") may perpetuate negative concepts of disability and further marginalize the individuals that our interventions aim to serve.
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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 | 0.806 | 0.813 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.010 | 0.103 |
| Scholarly communication | 0.015 | 0.034 |
| Open science | 0.009 | 0.020 |
| Research integrity | 0.022 | 0.023 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".