The chronic disease helplessness survey: developing and validating a better measure of helplessness for chronic conditions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction: Learned helplessness develops with prolonged exposure to uncontrollable stressors and is therefore germane to individuals living with pain or other poorly controlled chronic diseases. This study has developed a helplessness scale for chronic conditions distinct from previous scales that blur the conceptualization of control constructs. Extant measures commonly examine controllability, not the three pillars of helplessness identified by Maier and Seligman (1976): cognitive, emotional, and motivational/motor deficits. Methods: Individuals who self-report a chronic pain condition (N = 350) responded to a Chronic Disease Helplessness Survey (CDHS) constructed to capture cognitive, motivational/motor, and emotion deficits. Exploratory factor analysis (EFA; N = 200) and confirmatory factor analysis (CFA; N = 150) were performed. The CDHS was assessed for convergent and discriminant validity. Results: A three-factor solution corresponding to cognitive, emotional, and motivational/motor factors was identified by EFA. The solution exhibited sufficient model fit and each factor had a high degree of internal consistency. The CDHS was significantly associated with greater pain intensity and interference, PCS helplessness, lower perceived pain control, and lower general self-efficacy. Individuals with diabetes generally experience greater control strategies over daily symptoms (e.g., diet, oral medications, and insulin) than patients with chronic pain and in this study displayed significantly lower CDHS scores compared to individuals with chronic pain, demonstrating discriminant validity. Conclusions: This study provides preliminary evidence that the three-factor CDHS is a psychometrically sound measure of helplessness in individuals with chronic pain.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it