Person-Centred Integrative Diagnosis: Conceptual Bases and Structural Model
Bibliographic record
Abstract
OBJECTIVES: To review the conceptual bases of Person-centred Integrative Diagnosis (PID) as a component and contributor to person-centred psychiatry and medicine and to outline its design and development. METHOD: An analysis was conducted of the historical roots of person-centred psychiatry and medicine, tracing them back to ancient Eastern and Western civilizations, to the vicissitudes of modern medicine, to recent clinical and conceptual developments, and to emerging efforts to reprioritize medicine from disease to patient to person in collaboration with the World Medical Association, the World Health Organization, the World Organization of Family Doctors, the World Federation for Mental Health, and numerous other global health entities, and with the coordinating support of the International Network for Person-centered Medicine. RESULTS: One of the prominent endeavours within the broad paradigmatic health development outlined above is the design of PID. This diagnostic model articulates science and humanism to obtain a diagnosis of the person (of the totality of the person's health, both ill and positive aspects), by the person (with clinicians extending themselves as full human beings), for the person (assisting the fulfillment of the person's health aspirations and life project), and with the person (in respectful and empowering relationship with the person who consults). This broader and deeper notion of diagnosis goes beyond the more restricted concepts of nosological and differential diagnoses. The proposed PID model is defined by 3 keys: broad informational domains, covering both ill health and positive health along 3 levels: health status, experience of health, and contributors to health; pluralistic descriptive procedures (categories, dimensions and narratives); and evaluative partnerships among clinicians, patients, and families. An unfolding research program is focused on the construction of a practical guide and its evaluation, followed by efforts to facilitate clinical implementation and training. CONCLUSIONS: PID is aimed at appraising overall health through pluralistic descriptions and evaluative partnerships, and leading through a research program to more effective, integrative, and person-centred health care.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.002 | 0.024 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".