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Record W2418193024 · doi:10.2196/resprot.4219

Development of the Lupus Interactive Navigator as an Empowering Web-Based eHealth Tool to Facilitate Lupus Management: Users Perspectives on Usability and Acceptability

2016· article· en· W2418193024 on OpenAlexaffvenueabout
Carolyn Neville, Deborah Da Costa, Murray Rochon, Christine Peschken, Christian A. Pineau, Sasha Bernatsky, Stephanie Keeling, A. Aviña-Zubieta, Elizabeth Lye, Davy Eng, Paul R. Fortin

Bibliographic record

VenueJMIR Research Protocols · 2016
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsUniversity of British ColumbiaUniversity of ManitobaArthritis Research Centre of CanadaUniversité LavalUniversity of AlbertaMcGill University Health Centre
Fundersnot available
KeywordsUsabilityeHealthSystemic lupus erythematosusComputer scienceWorld Wide WebHuman–computer interactionMedicineHealth care

Abstract

fetched live from OpenAlex

BACKGROUND: Systemic Lupus Erythematosus (SLE) is a serious, complex, and chronic illness. Similar to most other chronic illness states, there is great interest in helping persons with SLE engage in their disease management. OBJECTIVE: The objectives of this study were to (1) develop the Lupus Interactive Navigator (LIN), a web-based self-management program for persons with SLE, and (2) test the LIN for usability and acceptability. METHODS: The LIN development platform was based on the results of preliminary comprehensive needs assessments and adapted from the Oncology Interactive Navigator, a web-based tool developed for persons with cancer. Medical researchers, writers, designers, and programmers worked with clinical experts and persons with SLE to develop content for the LIN. Usability and acceptability of the LIN was tested on individuals with SLE meeting American College of Rheumatology criteria, who were recruited from five Canadian SLE clinics. Participants were provided with access to the LIN and were asked to use it over a two-week period. Following the testing period, participants were contacted for a 30-minute telephone interview to assess usability and acceptability. RESULTS: The content for the LIN was subdivided into six primary information topics with interview videos featuring rheumatologists, allied health professionals, and persons with SLE. Usability and acceptability of the LIN was tested on 43 females with SLE. Of these, 37 (86%) completed telephone interviews. The average age was 43.6 (SD 15.9) years and disease duration averaged 14.1 (SD 10.8) years. Median time spent on LIN was 16.3 (interquartile range [IQR]:13.7, 53.5) minutes and median number of sessions was 2 (IQR: 1, 3). Overall, Likert ratings (0=strongly disagree; 7=strongly agree) of website usability and content were very high, with 75% scoring >6 out of 7 on all items. All participants agreed that LIN was easy to use, would recommend it to others with SLE, and would refer to it for future questions about SLE. Very high ratings were also given to relevancy, credibility, and usefulness of the information provided. Overall, 73% of the participants rated all topics helpful to very helpful. Participants who reported more prior knowledge about SLE rated items regarding improvement in knowledge and helpfulness relatively lower than persons with less prior knowledge. Most participants commented that the LIN would be very useful to those newly diagnosed with SLE. Minor revisions were recommended. CONCLUSIONS: This study furthers the understanding of the needs in the SLE community and delivers a unique eHealth tool to promote self-management in persons with SLE. The LIN was found to be highly acceptable in content and usability. The information provided on LIN may be most helpful for individuals with less experience with the disease, such as those newly diagnosed, indicating the need to tailor the content for persons with more SLE experience.

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.386
Threshold uncertainty score0.722

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.139
GPT teacher head0.496
Teacher spread0.357 · 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.

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

Citations21
Published2016
Admission routes3
Has abstractyes

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