Building blocks of resiliency: a transactional framework to guide research, service design, and practice in pediatric rehabilitation
Bibliographic record
Abstract
Purpose: Children’s resiliency is seen as important in pediatric rehabilitation, but is seldom the focus of research or intervention. This article presents a resiliency framework to inform pediatric rehabilitation research, service design, and practice.Methods: The development of the framework was guided by a transactional, life course perspective, and a review of self-constructs in the resiliency literature.Results: The framework comprises health-related adversities, self-capacities, self-regulatory processes, and adaptive benefits. Four adaptive self-capacities are highlighted (activity self-efficacy, capacity to marshal resources and supports to achieve goals, capacity to adapt to changing life situations, and capacity to envision a positive future). These self-capacities are linked to common adversities experienced by children with disabilities, namely activity limitations, functioning and participation restrictions, transition issues, and anticipated future life challenges. The self-capacities are also associated with empowered, optimistic, adaptive, and hopeful mindsets, which influence accommodative and assimilative self-regulatory strategies affecting children’s adaptive benefits.Conclusions: The framework can inform resiliency-related research exploring self-capacities and resiliency processes. The framework points to what is modifiable through intervention targeting the person-in-context, namely self-capacities, mindsets, and situated experiences. Implications for service design and delivery include providing opportunities and interacting with clients in ways that support the development of these self-capacities.Implications for rehabilitationFostering resiliency means preparing children with disabilities to negotiate and navigate the adversities and challenges they will encounter over their lives.Important resiliency-related self-capacities include activity self-efficacy, capacity to marshal resources and supports to achieve goals, capacity to adapt to changing life situations, and capacity to envision a positive future.The resiliency framework suggests the importance of enhancing children’s views of themselves as empowered, optimistic, adaptive, and hopeful.Practice will be enriched by acknowledging that a range of health concerns are relevant to practice, including issues of impairment, functioning, participation, and adaptation.
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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 | 0.061 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.012 | 0.046 |
| Scholarly communication | 0.018 | 0.020 |
| Open science | 0.007 | 0.014 |
| Research integrity | 0.006 | 0.013 |
| Insufficient payload (model declined to judge) | 0.007 | 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".