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Record W4413348021 · doi:10.2196/67106

ADAPTed Cognitive Behavioral Therapy for Pediatric Functional Abdominal Pain in Community-Based Pediatric Care: Mixed Methods Study

2025· article· en· W4413348021 on OpenAlexvenueno aff
Emma Ramsay Milford, Sandra Buratti, Natoshia R. Cunningham, Åsa Nilses, Ewa‐Lena Bratt, Sandra Weineland

Bibliographic record

VenueJMIR Formative Research · 2025
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsWilcoxon signed-rank testAnxietyMedicineThematic analysisPhysical therapyIntervention (counseling)Clinical psychologyCognitionCognitive behavioral therapyQualitative researchMann–Whitney U testPsychiatry

Abstract

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Background: The Aim to Decrease Anxiety and Pain Treatment (ADAPT) is a blended, digital, and live cognitive behavioral therapy program for children with functional abdominal pain disorder (FAPDs) and anxiety. Initially developed and evaluated in US pediatric gastroenterology settings, a culturally refined version was developed in Swedish, for potential use within community-based pediatric health care settings. Objective: This study aimed to evaluate a modified version of ADAPT as an early intervention for FAPD within a community-based pediatric setting in Sweden, exploring both the potential treatment effect and participants' treatment experience. Methods: Participants were aged 9-14 years, and all were diagnosed with FAPD. Using a mixed methods design, the study examined the preliminary effect through a single-arm pre-posttest and treatment experience through semistructured child interviews. Data were analyzed in three steps: nonparametric quantitative analysis of results on pre- and postintervention measures of self-rated pain-related functional disability, pain intensity, and anxiety; thematic qualitative analysis of the interviews; and conversion of qualitative data to enable both datasets to be analyzed and presented together. Results: A total of 13 children (12 girls) participated in ADAPT, all completing the program. In total, 7 of the invited 13 participating children agreed to be interviewed following intervention completion. Quantitative results were analyzed using the Wilcoxon signed rank test, and Pearson r was used to calculate the effect size. Results showed a significant reduction in pain-related functional disability, with a median decrease from 14.00 (IQR 10-20) preintervention, to 5.00 (IQR 1-9) postintervention (P=.04), a large effect size, r=-0.58, and 46% (n=6) achieving a clinically meaningful change where a Functional Disability Inventory (FDI) score decrease of ≥7.8 points denoted a clinically meaningful treatment response. Pain intensity also significantly decreased from a median of 6.5 (IQR 5.25-8) to 4.00 (IQR 2.5-6.5; P=.02), a large effect size r=-0.70, with 33% (n=4) experiencing at least a 50% reduction. Clinically meaningful change was determined to be present if at least a 50% reduction in self-rated measures of pain intensity was observed. Qualitative thematic analysis identified three themes: "Starting from scratch," "Experiencing the treatment," and "Getting on with life." In terms of treatment experience, the blended live or digital format was perceived as a good fit for youth. Most children described finding some strategy that was effective and reported positive outcomes, such as increased participation in school. Conclusions: As patient experiences were predominantly positive and quantitative results indicative of potential for increased function and reduced pain, our findings suggest that ADAPT may present as a possible early treatment option for FAPD in a Swedish community-based pediatric setting. To draw robust conclusions on effectiveness, further research is required using a larger sample size, as well as research aimed at following up treatment effects over time.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.130
GPT teacher head0.509
Teacher spread0.379 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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