Resilience and coping: a qualitative analysis of cognitive and behavioral factors in adults with osteogenesis Imperfecta
Bibliographic record
Abstract
PURPOSE: The aim of this qualitative study was to investigate resilience among adults with Osteogenesis Imperfecta (OI). MATERIALS AND METHODS: Semi-structured interviews were conducted with 15 adults with OI. Transcripts were coded and subsequently abstracted, yielding themes specific to resilience and coping. Interview guides covered broad topics including pain challenges specific to OI, mental health issues related to OI, and priorities for future interventions for individuals with OI. RESULTS: Participants described resilience in the context of OI as the ability to grow from adversity, adapt to challenges resulting from OI-related injuries, and find identities apart from their condition. Psychological coping strategies included acceptance, self-efficacy, cognitive reframing, perspective-taking, and positivity. Behavioral factors that helped participants develop resilience included developing new skills, pursuing meaningful goals, practicing spirituality, and seeking external resources such as psychotherapy, education, and connection with community. CONCLUSION: Having identified how adults with OI define resilience and the strategies they use to cope, we can now develop interventions and guide healthcare providers in improving psychological wellbeing in this population.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".