Advancing rehabilitation research: An interactionist perspective to guide question and design
Bibliographic record
Abstract
The purpose of this position statement is to propose an interactionist framework to bring together the existing literature and provide a unifying direction for rehabilitation research. The framework comprises three components: the conceptual model, the research question, and the research design. The interactionist conceptual model has been adapted from the World Health Organization International Classification of Functioning, Disability, and Health. The model forms the starting point that guides the specification of the research question, which, in turn, guides the selection of research design. This approach demands that the question takes precedence and that there be an extensive repertoire of research designs, each of which is valued for its 'goodness-of-fit' with the question, rather than an a priori, single hierarchical ordering of designs. Research designs must be appropriate for questions that examine the disability experience, development over the lifespan, multifaceted interventions, low incidence conditions, and development of new interventions. Analytical challenges include dealing with confounding, mediating, and moderating variables. Rehabilitation researchers--and those who fund their work--should consider and value the use of diverse research methods to best answer the questions posed from the interactionist perspective.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.454 | 0.285 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.010 | 0.043 |
| Scholarly communication | 0.024 | 0.034 |
| Open science | 0.014 | 0.017 |
| Research integrity | 0.018 | 0.030 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".