Systems of care: transition from the bio‐psycho‐social perspective of the International Classification of Functioning, Disability and Health
Bibliographic record
Abstract
BACKGROUND: The transition process of vulnerable adolescents, including those with complex health conditions, occurs in all domains of their life. Systems of care are usually designed but also restricted within certain aspects of life, as addressed by health, education and social welfare. The need for a co-ordinated approach to support the transition process has been voiced before, but usually publications focus on one system of care, usually the healthcare system or the education system. Recent moves, especially in the UK, are trying to integrate these different systems allowing for a more integrated transition process. This article illustrates how these developments are represented within the framework of the International Classification of Functioning, Disability and Health (ICF) and provides arguments that favour a greater integration of systems of care. METHODS: Examples of systems of care from North America and the EU (Germany and the UK) are described. They were selected from a literature search using the terms 'systems of care', 'transition' and 'transitional care' in different combinations. Further supportive information derives from personal experience working in some of these systems in different countries. The systems were analysed according to the components of health they address within the ICF. RESULTS: In order to assist adolescents in transition of services, there is a consensus that the approach should be individualized. The overall goal of any intervention or service should be to achieve optimal functioning of the patients. In the framework of the ICF, this means that biomedical and contextual (psychosocial) issues need to be taken into consideration. This requires an exchange of information between the different systems or the integration of those systems involved with the patient. CONCLUSION: To facilitate transition, it has been shown that close collaboration between agencies, a transdisciplinary approach of the professionals involved and the use of key workers are helpful.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| 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".