Reconfiguring clinical communication in the electronic counselling context: The nuances of disruption
Bibliographic record
Abstract
AIM: This study expands on an earlier study about diabetes nurses' experiences of the Guided Self-Determination intervention in face-to-face consultations among people with type 2 diabetes. This current study investigates Guided Self-Determination in an electronic format with the aim to explore what can be learned about the written form for health communication from the perspectives of diabetes nurses in primary care. DESIGN: The study has an explorative, qualitative design. METHOD: Four diabetes nurses were individually interviewed after completing the electronic intervention. The analysis was guided by Interpretive Description. RESULTS: Small sample size apart, the rich empirical data and quality of dialogue point to the interviewees' earlier contact, comfort and trust with the researcher. The written electronic communication could disrupt nurses' possibilities for using basic and advanced communication skills. Findings also indicate that written electronic communication can foster thoughtful responses to patients and increase possibilities for a transparent counselling delivery process.
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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 | 0.010 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".