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Record W2744876224 · doi:10.2196/mental.7985

Internet-Delivered Cognitive Behavioral Therapy for Children With Pain-Related Functional Gastrointestinal Disorders: Feasibility Study

2017· article· en· W2744876224 on OpenAlexvenueno aff
Maria Lalouni, Brjánn Ljótsson, Marianne Bonnert, Erik Hedman‐Lagerlöf, Jens Högström, Eva Serlachius, Ola Olén

Bibliographic record

VenueJMIR Mental Health · 2017
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal motility and disorders
Canadian institutionsnot available
FundersSvenska LäkaresällskapetVetenskapsrådetStockholms Läns LandstingKarolinska InstitutetKempe Foundation
KeywordsIrritable bowel syndromeMedicineAnxietyQuality of life (healthcare)Cognitive behavioral therapyPhysical therapyAbdominal painDepression (economics)Functional gastrointestinal disorderInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Pain-related functional gastrointestinal disorders (P-FGIDs; eg, irritable bowel syndrome) are highly prevalent in children and associated with low quality of life, anxiety, and school absence. Treatment options are scarce, and there is a need for effective and accessible treatments. Internet-delivered cognitive behavior therapy (Internet-CBT) based on exposure exercises is effective for adult and adolescent irritable bowel syndrome, but it has not been evaluated for younger children. OBJECTIVE: The objective of this study was to assess acceptability, feasibility, and potential clinical efficacy of Internet-CBT for children with P-FGIDs. METHODS: This was a feasibility study with a within-group design. We included 31 children aged 8-12 years and diagnosed with P-FGID, according to the ROME III criteria. Mean duration of abdominal symptoms at baseline was 3.8 years (standard deviation [SD] 2.6). The treatment was therapist-guided and consisted of 10 weekly modules of exposure-based Internet-CBT. The children were instructed to provoke abdominal symptoms in a graded manner and to engage in previously avoided activities. The parents were taught to decrease their attention to their children's pain behaviors and to reinforce and support their work with the exposures. Assessments included treatment satisfaction, subjective treatment effect, gastrointestinal symptoms, quality of life, pain intensity, anxiety, depression, and school absence. Data were collected at pretreatment, posttreatment, and 6-month follow-up. Means, standard errors (SEs), and Cohen d effect sizes were estimated based on multi-level linear mixed models. RESULTS: Most children 25/31 (81%) completed 9 or 10 of the 10 treatment modules. Almost all children, 28/31 (90%), reported that the treatment had helped them to deal more effectively with their symptoms, and 27/31 (87%) children declared that their symptoms had improved during the treatment. Assessments from the parents were in accordance with the children's reports. No child or parent reported that the symptoms had worsened. We observed a large within-group effect size on the primary outcome measure, child-rated gastrointestinal symptoms from pretreatment to posttreatment (Cohen d=1.14, P<.001, 95% CI 0.69-1.61), and this effect size was maintained at 6-month follow-up (Cohen d=1.40, P<.001, 95% CI 1.04-1.81). We also observed significant improvements from pretreatment to posttreatment on a wide range of child- and parent-rated measures including quality of life, pain intensity, anxiety, depression, and school absence. All results remained stable or were further improved at 6-month follow-up. CONCLUSIONS: This study shows that children with longstanding P-FGIDs, and their parents, perceive exposure-based Internet-CBT as a helpful and feasible treatment. The included children improved significantly despite a long duration of abdominal symptoms before the intervention. The treatment shows potential to be highly effective for P-FGIDs. The results need to be confirmed in a randomized controlled trial (RCT).

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.059
GPT teacher head0.364
Teacher spread0.305 · 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 designObservational
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

Citations39
Published2017
Admission routes1
Has abstractyes

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