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Record W4323351043 · doi:10.1093/jcag/gwac036.213

A213 UNDERSTANDING PATIENT AND PHYSICIAN ATTITUDES AND EXPECTATIONS REGARDING IDENTIFYING AND MANAGING ANXIETY AND DEPRESSION IN IBD

2023· article· en· W4323351043 on OpenAlexaffabout
Aamir Patel, L Targownik, S Zelinsky, K Daley, L Jeffs, L Zeng, Sahar Tabatabavakili

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2023
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFocus groupMental healthThematic analysisMedicineAnxietyMoodQualitative researchHealth carePsychologyFamily medicinePsychiatry

Abstract

fetched live from OpenAlex

Abstract Background Patients living with Inflammatory Bowel Disease (IBD) commonly experience a number of mental health-related challenges, specifically anxiety and mood disorders (AMDs). Although there has been an awareness of the relationship between IBD and AMD within the GI research and clinical space; detection, treatment, and management amongst care providers is limited. Therefore, we are seeking to explore the overall experiences of patients living with Inflammatory Bowel Disease to identify and evaluate their experiences in interactions with GI clinicians around mental health in diverse care settings in order to determine how to best support mental health care amongst IBD patients. Purpose We aimed to explore perspectives, experiences and barriers to engaging with mental health-related challenges amongst IBD patients when interacting with gastroenterologists over the course of their health journey. Method We conducted 5 semi-structured online focus groups co-facilitated by patient researchers in early 2020 through Zoom which spanned for a total of 2.5 hours each. Participants were recruited through social media channels, GI clinics, the IMAGINE-SPOR unit, and Crohn’s and Colitis Canada. A semi-structured interview guide was developed for patient researchers to follow during the focus groups which provided guided questions that would allow patient participants to explore and reflect on: their experiences living with IBD, their expectations around mental health support, their perception of the engagement of GIs in mental health discussions, and their expectations for mental health support and services moving forward. Audio recordings from the semi-structured focus groups were then transcribed and thematic analysis was used to identify emerging themes and patient expectations. Result(s) We identified the following key themes: 1) experiences with IBD: difficulties related to reintegrating into social settings, feelings of loneliness; 2) expectations around mental health support: the need to develop their own resiliency strategies due to the lack of structural resources regarding mental health and IBD in the clinical space; 3) GI engagement: HCPs were dismissive of mental health symptoms, often gaslighting patients when mentioning mental health concerns during clinical encounters; and 4) expectations: a need to standardize mental health care across IBD care practice with a focus on potentially integrating healthcare providers of diverse care settings to help address the need for mental health support in such a vast patient population. Conclusion(s) Our study suggests that effective detection, management and awareness, along with the integration of feedback from patient lived experiences can help inform the development of mental health support and services which cater to the needs of people living with IBD. Results from this study will be interpreted in line with insight gathered from upcoming interviews of gastroenterologists and HCPs. Please acknowledge all funding agencies by checking the applicable boxes below CIHR, Other Please indicate your source of funding; IMAGINE SPOR INCUBATOR Grant Disclosure of Interest None Declared

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)0.006
metaresearch head score (Gemma)0.018
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.002
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.049
GPT teacher head0.343
Teacher spread0.294 · 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
Published2023
Admission routes2
Has abstractyes

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