Can intolerance of uncertainty & anxiety impact the lives we lead? Understanding lived experiences of people with chronic physical health and pain conditions
Bibliographic record
Abstract
Purpose: Intolerance of uncertainty (IU) is associated with poorer emotional wellbeing and worse prognosis of chronic physical health and pain conditions (CHPCs). Our current understanding of IU in CHPCs is siloed within the literatures on specific CHPCs. However, IU is consistently identified as a risk factor for anxiety and depressive disorders. In this exploratory study, we used a mixed methods design to better understand the role of IU and anxiety in people’s (n = 139) lived experiences of their CHPCs and how they respond to uncertainty across health and everyday contexts. Primary Results: Higher acceptance of illness and perceived social support were related to lower IU and anxiety among people with CHPCs. Higher IU and anxiety were also related to lower scores on many domains of quality of life. Our reflexive thematic analysis resulted in four primary themes: 1) distressing ambiguous contexts are not limited to health scenarios and require management in diverse ways; 2) interference of CHPCs affects multiple domains of life beyond physical health; 3) navigating uncertainty for a chronic period changes coping abilities and identity development; and 4) responsivity to uncertainty is a multifaceted cognitive-behavioural and emotionalphysiological response that hinders or promotes coping. Conclusions: IU significantly impacts the lives of those with CHPCs and holds potential as a transdiagnostic target for early prevention and intervention. By tailoring therapeutic approaches to acknowledge the importance of health-related cues while increasing tolerance of uncertainty, people with CHPCs will likely experience improved prognosis, wellbeing, and fulfillment. Keywords: intolerance of uncertainty, anxiety, chronic health, chronic pain, transdiagnostic, context, mixed-methods
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| 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".