Inter-individual relationships within a Canadian SPOR research network: a social network study
Bibliographic record
Abstract
BACKGROUND: Efforts have been made by health research granting agencies to bring research closer to patients' concerns. In Canada, such efforts were formalized in 2011 with the funding of the Strategy for Patient-Oriented Research (SPOR)'s research networks to address research priorities identified by patients and accelerate the translation of research findings into patient care and health care policy. Among these networks, SPOR Diabetes Action Canada (DAC) has created patient-partner circles to facilitate their integration within the network. The nature of the relationships within this atypical patient-oriented research network is systematically explored in this paper. METHODS: A cross-sectional social network study was conducted among the SPOR DAC's network members to examine inter-individual interactions, and the topics discussed the most between members. Descriptive data analyses were conducted to explore which discussion topics were discussed most among members whose primary roles were research, administration, governance, and patient representation. RESULTS: The response rate was 51.9%, providing data on 76.5% of the maximum number of connections in the network. The survey captured 2763 inter-individual relationships. Responses to a sub-question inserted in the survey show that 482 of these relationships (17,4%) existed before joining the network in collaboration on a research project. Most ties captured in the survey were yearly or quarterly, while few relationships were monthly, weekly, or daily. In measured relationships, members discussed several topics, the most frequent being scientific research, patient engagement, network coordination and governance, and operations and management. The topics associated with the most significant proportion of relationships captured in the survey were scientific research (45.4%) and patient engagement (40.7%). Management & operations and governance & coordination follow, corresponding to 24.3 and 23.9% of the captured relationships. All discussion topic subnetworks were either somewhat or highly centralized, meaning that relationships were not equally distributed among members involved in these discussions. Of the 1256 relationships involving exchanges about scientific research, 647 (51.5%) involved a researcher, 419 (33.3%) an administrator, 182 (14.5%) a patient partner, and 82 (6.5%) a member whose primary role is network governance. CONCLUSIONS: Scientific research and patient engagement were the most common topics discussed, consistent with the patient-centered research at the heart of the SPOR Diabetes Action Canada network. The study identified several relationships where a patient partner has discussed scientific research with a researcher. However, relationships involving research discussions were three times more common between a researcher and an administrator than between a researcher and a patient partner, although twice as many patient partners as administrators participated in the survey. The institutionalization of patient-partner involvement in large research networks is an evolving practice for which optimal engagement methods are still being explored.
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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 | 0.007 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.016 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".