Assessing patients’ involvement in decision making during the nutritional consultation with a dietitian
Bibliographic record
Abstract
BACKGROUND: Shared decision making (SDM) represents an interesting approach to optimize the impact of dietary treatment, but there is no evidence that SDM is commonly integrated into diet-related health care. OBJECTIVE: To assess the extent to which dietitians involve patients in decisions about dietary treatment. METHODS: We audiotaped dietitians conducting nutritional consultations with their patients, and we transcribed the tapes verbatim. Three trained raters independently evaluated the content of the nutritional consultations using a coding frame based on the 12 items of the French-language version of the OPTION scale, a validated and reliable third-observer instrument designed to assess patients' involvement by examining specific health professionals' behaviours. Coding was facilitated by the qualitative research software NVivo 8. We assessed internal consistency with Cronbach's alpha and inter-rater reliability with the intraclass correlation coefficient (ICC). RESULTS: Of the 40 dietitians eligible to participate in the study, 19 took part. We recruited one patient per participating dietitian. The overall mean OPTION score was 29 ± 8% [range, 0% (no patient involvement in the decision] to 100% [high patient involvement)]. The mean duration of consultations was 50 ± 26 min. The OPTION score was positively correlated with the duration of the consultation (r = 0.65, P < 0.01). Internal consistency and inter-rater reliability were both good (Cronbach's alpha = 0.72; ICC = 0.65). CONCLUSION: This study is the first to use a framework based on the OPTION scale to report on dietitians' involvement of patients in decisions about patients' dietary treatment. The results suggest that involvement is suboptimal. Interventions to increase patients' involvement in diet-related decision making are indicated.
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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 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".