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Record W2794253569 · doi:10.1093/jcag/gwy008.238

A237 DEVELOPMENT AND EVALUATION OF A WEB-BASED EDUCATIONAL TOOL FOR THE HEPATOPULMONARY SYNDROME

2018· article· en· W2794253569 on OpenAlexaffabout
Justina Marianayagam, Katherine Griffin, Jenna Sykes, Samir Gupta

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2018
Typearticle
Languageen
FieldMedicine
TopicLiver Disease and Transplantation
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsHepatopulmonary syndromeWeb applicationMedicinePsychologyComputer scienceInternal medicineWorld Wide WebLiver transplantation

Abstract

fetched live from OpenAlex

Hepatopulmonary syndrome (HPS) is a rare shunting lung disease that is caused by liver disease. This complex disease entails high informational needs for patients and their caregivers. We sought to analyze existing web resources for HPS patients, to assess patients’ and caregivers’ informational needs, and to develop and evaluate a tailored web-based educational resource for this population. We performed a GoogleTM search for existing web-based resources for HPS. We then administered an electronic needs assessment survey to patients with HPS [liver disease, intrapulmonary vascular dilatation (IPVD) and hypoxemia)/pre-HPS (liver disease, IPVD and normal oxygenation) in the Toronto HPS Clinic Database, and their caregivers. In response to these needs, we developed an HPS website, applying best practices in health website design. We administered electronic questionnaires to assess changes in self-efficacy (Likert-scale questions) and knowledge (standardized knowledge test) after website use, website quality (DISCERN score) and usability [System Usability Score (SUS)]. We identified 21 unique HPS websites, with a mean DISCERN score of 19.9 ± 5.2 (out of 45) and Flesch-Kincaid reading grade of 16.8 ± 4.2. We recruited 35 (15 HPS, 5 pre-HPS, 15 caregivers) of 59 (59.3%) eligible participants for the needs assessment. Of these, 27 (77.1%) had searched online for HPS information; 5/27 (18.5%) had found the information they sought and 8/27 (29.6%) had found the information easy to understand. Participant-reported self-efficacy (see Figure) improved after interaction with the website, as did knowledge scores [64.9% ± 16.8 to 72.7% ± 18.5 (n=30; p=0.015)]. A higher SUS score (p=0.048) and lower level of comfort browsing the Internet (p=0.020) predicted improvement in knowledge score in both univariate and multivariable models. The mean DISCERN score for our website was 38.5 ± 4.3 (out of 45); SUS score was 76.6 ± 16.2 (out of 100); and reading grade was 8.3. HPS patients often seek information on the internet, yet existing web resources were few, scored poorly on a validated test of health information quality, and had a reading level far above the 8th grade recommended threshold. A website designed through evidence-based criteria for health educational website design was able to improve self-efficacy and knowledge among patients and caregivers with HPS. The importance of user-centered design is demonstrated by the fact that users with a lower comfort level browsing the Internet were even more likely to experience knowledge gains. All patients/caregivers affected by HPS should be made aware of the availability of this beneficial resource. Figure. Participant Self-Efficacy Pre- and Post-Website Interaction. Responses were entered on a 5-point Likert scale labeled 1 (disagree); 3 (neutral); and 5 (agree). For the purposes of this figure, scores of 1 and 2 were considered “disagree,” and 4 and 5 were considered “agree.” Each bar demonstrates the proportion of participants with each response, for each statement. This includes 30 participants for the pre- and post- assessment (19 patients with hepatopulmonary syndrome and 11 caregivers). None

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)0.005
metaresearch head score (Gemma)0.010
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 score0.005
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.016
GPT teacher head0.263
Teacher spread0.247 · 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

Citations0
Published2018
Admission routes2
Has abstractyes

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