Conditions organisationnelles et systémiques à l’implication des citoyens-patients dans le développement de la télésanté au Québec
Bibliographic record
Abstract
OBJECTIVES: Involving citizens-patients in decisions regarding telehealth services could allow a better match between the services offered and the needs and contexts of individuals and communities. This study aims to explore the organizational and systemic conditions that can influence citizen-patient involvement in the development of telehealth in Quebec. METHODS: A qualitative study based on semi-structured interviews with 29 key informants was conducted. A deductive-inductive thematic analysis was performed based on an integrative framework derived from diffusion of innovation theories. RESULTS: Citizen-patient involvement in the development of telehealth remains dependent on many organizational and systemic conditions. At the organizational level, it could affect the dynamics, process, cultures, rules and operations in organizations; hence the needs for adequate human and material resources as well as the availability of support for change. At the systemic level, the ideology, the sociopolitical context and the decisions in favor (or not) of a citizen appropriation of the decision-making are central. Concerns about scientific evidence, training, as well as the roles of professional federations, and citizen-patient groups have also emerged. Organizational and systemic levels are interdependent. CONCLUSION: The organizational and systemic contexts may explain part of the contrast between the discourse in favor of citizen-patient involvement in telehealth decision-making and the reality observed in Quebec. This study provides a basis for analyzing citizen-patient involvement in services development from the perspective of organizational and systemic changes.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".