Accessing health services through the back door: a qualitative interview study investigating reasons why people participate in health research in Canada
Bibliographic record
Abstract
BACKGROUND: Although there is extensive information about why people participate in clinical trials, studies are largely based on quantitative evidence and typically focus on single conditions. Over the last decade investigations into why people volunteer for health research have become increasingly prominent across diverse research settings, offering variable based explanations of participation patterns driven primarily by recruitment concerns. Therapeutic misconception and altruism have emerged as predominant themes in this literature on motivations to participate in health research. This paper contributes to more recent qualitative approaches to understanding how and why people come to participate in various types of health research. We focus on the experience of participating and the meanings research participation has for people within the context of their lives and their health and illness biographies. METHODS: This is a qualitative exploratory study informed by grounded theory strategies. Thirty-nine participants recruited in British Columbia and Manitoba, Canada, who had taken part in a diverse range of health research studies participated in semi-structured interviews. Participants described their experiences of health research participation including motivations for volunteering. Interviews were recorded, transcribed, and analyzed using constant comparisons. Coding and data management was supported by Nvivo-7. RESULTS: A predominant theme to emerge was 'participation in health research to access health services.' Participants described research as ways of accessing: (1) Medications that offered (hope of) relief; (2) better care; (3) technologies for monitoring health or illness. Participants perceived standard medical care to be a "trial and error" process akin to research, which further blurred the boundaries between research and treatment. CONCLUSIONS: Our findings have implications for recruitment, informed consent, and the dichotomizing of medical/health procedures as either research or treatment. Those with low health status may be more vulnerable to potential coercion, suggesting the need for a more cautious approach to obtaining consent. Our findings also indicate the need for boundary work in order to better differentiate treatment and research. It is important however to acknowledge a categorical ambiguity; it is not always the case that people are misinformed about the possible benefits of research procedures (i.e., therapeutic misconception); our participants were aware that the primary purpose of research is to gain new knowledge yet they also identified a range of actual health benefits arising from their participation.
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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 | 0.020 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.039 | 0.019 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".