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Record W3013376123 · doi:10.2196/16137

A Patient Safety Educational Tool for Patients With Chronic Kidney Disease: Development and Usability Study

2020· article· en· W3013376123 on OpenAlexvenueno aff
Cassandra Bowman, Joseph Lunyera, Aviel Alkon, L. Ebony Boulware, Jennifer St. Clair Russell, Jennie Riley, Jeffrey C. Fink, Clarissa J. Diamantidis

Bibliographic record

VenueJMIR Formative Research · 2020
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
FundersNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsPreprintUsabilityKidney diseaseMedicineComputer scienceHuman–computer interactionInternal medicineWorld Wide Web

Abstract

fetched live from OpenAlex

BACKGROUND: Chronic kidney disease (CKD) is a health condition that threatens patient safety; however, few interventions provide patient-centered education about kidney-specific safety hazards. OBJECTIVE: We sought to develop and test the usability of a mobile tablet-based educational tool designed to promote patient awareness of relevant safety topics in CKD. METHODS: We used plain language principles to develop content for the educational tool, targeting four patient-actionable safety objectives that are relevant for individuals with CKD. These four objectives included avoidance of nonsteroidal anti-inflammatory drugs (NSAIDs); hypoglycemia awareness (among individuals with diabetes); temporary cessation of certain medications during acute volume depletion to prevent acute kidney injury (ie, "sick day protocol"); and contrast dye risk awareness. Our teaching strategies optimized human-computer interaction and content retention using audio, animation, and clinical vignettes to reinforce themes. For example, using a vignette of a patient with CKD with pain and pictures of common NSAIDs, participants were asked "Which of the following pain medicines are safe for Mr. Smith to take for his belly pain?" Assessment methods consisted of preknowledge and postknowledge surveys, with provision of correct responses and explanations. Usability testing of the tablet-based tool was performed among 12 patients with any stage of CKD, and program tasks were rated upon completion as no error, noncritical error (self-corrected), or critical error (needing assistance). RESULTS: The 12 participants in this usability study were predominantly 65 years of age or older (n=7, 58%) and female (n=7, 58%); all participants owned a mobile device and used it daily. Among the 725 total tasks that the participants completed, there were 31 noncritical errors (4.3%) and 15 critical errors (2.1%); 1 participant accounted for 30 of the total errors. Of the 12 participants, 10 (83%) easily completed 90% or more of their tasks. Most participants rated the use of the tablet as very easy (n=7, 58%), the activity length as "just right" (rather than too long or too short) (n=10, 83%), and the use of clinical vignettes as helpful (n=10, 83%); all participants stated that they would recommend this activity to others. The median rating of the activity was 8 on a scale of 1 to 10 (where 10 is best). We incorporated all participant recommendations into the final version of the educational tool. CONCLUSIONS: A tablet-based patient safety educational tool is acceptable and usable by individuals with CKD. Future studies leveraging iterations of this educational tool will explore its impact on health outcomes in this high-risk population.

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)0.014
metaresearch head score (Gemma)0.029
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 score0.014
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.029
Meta-epidemiology (narrow)0.0010.000
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)0.0010.000

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 head0.070
GPT teacher head0.482
Teacher spread0.412 · 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

Citations11
Published2020
Admission routes1
Has abstractyes

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