Cognitive Factors Affect Treatment Response to Medical and Psychological Treatments in Functional Bowel Disorders
Bibliographic record
Abstract
OBJECTIVES: For clinical trials in functional bowel disorders (FBD), the definition of a responder, one who meets the predefined criteria for a clinical response, is needed. Factors that determine clinical response aside from treatment itself are unknown. The aim of this study was to determine what baseline and post-treatment factors affect treatment response. METHODS: Females (n=397) with FBD entering a 12-week, four-arm, randomized NIH treatment trial (desipramine (DES), CBT, pill placebo, and education) were studied at baseline and after treatment. Demographic, clinical, psychosocial, and physiological variables were considered in the analysis. A responder was defined as a patient obtaining a score>3.5 on an averaged eight-item, five-point satisfaction-with-treatment questionnaire. Baseline and post-treatment logistic regressions were performed for each treatment condition to predict the responder outcome variable. RESULTS: Similar cognitive features predisposed participants to treatment response across the treatment conditions: sense of control over the condition, positive relationship with therapist or study coordinator, confidence in treatment, improvement in maladaptive cognitions, and quality of life during treatment. Demographic and clinical variables studied were not predictive. Some treatment-specific effects predicting responder status were noted, including a reduction in stool frequency with DES treatment and lack of abuse history in the placebo group. CONCLUSIONS: For medication, psychological, and placebo treatment in FBD, satisfaction with treatment depends on cognitive factors of confidence in treatments, perceived control over illness and symptoms, and reduction in negative cognitions related to symptom experience. Addressing these issues among patients with FBD may enhance treatment response to a variety of treatments.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".