Supporting a person-centred approach in clinical guidelines. A position paper of the Allied Health Community – Guidelines International Network (G-I-N)
Bibliographic record
Abstract
Background A person-centred approach in the context of health services delivery implies a biopsychosocial model focusing on all factors that influence the person’s health and functioning. Those wishing to monitor change should consider this perspective when they develop and use guidelines to stimulate active consideration of the person’s needs, preferences and participation in goal setting, intervention selection and the use of appropriate outcome measures. Objective To develop a position paper that promotes a personcentred approach in guideline development and implementation. Design, setting and participants We used three narrative discussion formats to collect data for achieving consensus: a nominal group technique for the Allied Health Steering Group, an Internet discussion board and a workshop at the annual G-I-N conference. We analysed the data for relevant themes to draft recommendations. Results We built the position paper on the values of the biopsychosocial model. Four key themes for enhancing a person-centred approach in clinical guidelines emerged: (i) use a joint definition of health-related quality of life as an essential component of intervention goals, (ii) incorporate the International Classification of Functioning, Disability and Health (ICF) as a framework for considering all domains related to health, (iii) adopt a shared decision-making method, and (iv) incorporate patient-reported health outcome measures. The position statement includes 14 recommendations for guideline developers, implementers and users.
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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 | 0.298 | 0.322 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.010 | 0.017 |
| Scholarly communication | 0.018 | 0.019 |
| Open science | 0.008 | 0.024 |
| Research integrity | 0.030 | 0.031 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".