The concept of resilience in childhood disability: Does the International Classification of Functioning, Disability and Health help us?
Bibliographic record
Abstract
BACKGROUND: The concept of resilience is popular in both the mainstream media and in health and human services research. Over the last 40 years, the term has been moulded and transformed from the idea of a trait that can be fostered within the individual towards a transactional concept with an emphasis on environmental factors. Although many current definitions are used to describe and talk about resilience, the dynamism of the concept is a common element across most current discussions and research applications. This paper provides an opportunity to place the concept of resilience within a framework for future application at the clinical frontlines. METHODS: An extensive scoping review on the existing literature was undertaken to explore recurring themes associated with resilience in families and children, particularly in the context of childhood disability. This literature was mapped and categorized in the context of World Health Organization's International Classification of Functioning, Disability and Health (ICF) framework to create recommendations for practical application by health professionals. FINDINGS: Three major themes emerged: (a) the idea of resilience as a state of an individual at a specific point in time rather than a built-in trait; (b) the idea of resilience as dynamic rather than static; and (c) the value of a framework into which to place the components of "resilience." CONCLUSIONS: The relative ease with which resilience concepts is situated within the ICF is an indication that the ICF framework provides a useful way to incorporate concepts of resilience for clinical application.
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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 | 0.017 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.005 | 0.011 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".