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Record W2728777716 · doi:10.14740/jocmr3081w

The Influence of Motivational Interviewing on Patients With Inflammatory Bowel Disease: A Systematic Review of the Literature

2017· review· en· W2728777716 on OpenAlexvenueno aff
Scott T. Wagoner, Jan Kavookjian

Bibliographic record

VenueJournal of Clinical Medicine Research · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMotivational interviewingEmpathyIntervention (counseling)Medical prescriptionInflammatory bowel diseasePopulationDiseaseClinical psychologyDepression (economics)Family medicinePsychiatryInternal medicineNursing

Abstract

fetched live from OpenAlex

Inflammatory bowel disease (IBD) is a condition accompanied by several physical and often psychological symptoms (e.g., depression). Treatments generally involve dietary modifications and prescription medications. Of concern, non-adherence rates with prescription medications for this population have been reported to be between 30% and 45%. In order to examine an intervention that has shown promise in improving adherence, researchers systematically reviewed the literature in order to determine the impact of a motivational interviewing (MI) intervention on outcomes for individuals diagnosed with IBD. The outcomes assessed were broad and included, among others, the target behaviors of medication adherence and advice-seeking, and also patient-perceived provider empathy. Results suggest that MI can be effective in improving outcomes for individuals with IBD since patients experienced improved adherence rates, displayed greater advice-seeking behavior, and perceived providers as having more empathy and better communication skills. Further research is required since the pool of retained studies is small, evidencing a paucity of literature focusing on this evidence-based health behavior intervention for the behaviors needed to optimally manage IBD. Further, only adults were examined in these studies, so generalizations to children and adolescents are limited.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.065
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.072
Threshold uncertainty score0.943

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.065
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.102
GPT teacher head0.480
Teacher spread0.378 · 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 teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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

Citations24
Published2017
Admission routes1
Has abstractyes

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