Evidence map›Paper›PMID 33759796›Full record

ArticleJournal of medical Internet research2021

Key Variables for Effective eHealth Designs for Individuals With and Without Mental Health Disorders: 2^12-4 Fractional Factorial Experiment.

Armando J Rotondi, Jonathan Grady, Barbara H Hanusa, Gretchen L Haas, Michael R Spring, Kaleab Z Abebe, James Luther, John Gurklis

Erratum issuedAbstract read
In one paragraph

Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Trial
  2. Guidelines to Establish an Equitable Mobile Health Ecosystem.Psychiatric services (Washington, D.C.) · 2023
    Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Armando J RotondiMental Illness Research, Education and Clinical Center (MIRECC), VA Pittsburgh Health Care System, Department of Veterans Affairs, Pittsburgh, PA, United States.ORCID 0000-0002-7529-6753
Jonathan GradyComputer Science, Thomas College, Waterville, ME, United States.ORCID 0000-0002-6921-9065
Barbara H HanusaMental Illness Research, Education and Clinical Center (MIRECC), VA Pittsburgh Health Care System, Department of Veterans Affairs, Pittsburgh, PA, United States.ORCID 0000-0002-2347-217X
Gretchen L HaasMental Illness Research, Education and Clinical Center (MIRECC), VA Pittsburgh Health Care System, Department of Veterans Affairs, Pittsburgh, PA, United States.ORCID 0000-0002-3413-9196
Michael R SpringDepartment of Information Sciences and Technology, School of Information Sciences, University of Pittsburgh, Pittsburgh, PA, United States.ORCID 0000-0003-2288-6757
Kaleab Z AbebeCenter for Research on Health Care Data Center, School of Medicine, University of Pittsburgh, Pittsburgh, PA, United States.ORCID 0000-0002-3644-8419
James LutherMental Illness Research, Education and Clinical Center (MIRECC), VA Pittsburgh Health Care System, Department of Veterans Affairs, Pittsburgh, PA, United States.ORCID 0000-0001-6118-5318
John GurklisBehavioral Health, VA Pittsburgh Health Care System, Department of Veterans Affairs, Pittsburgh, PA, United States.ORCID 0000-0002-5427-001X

Funding

Comparison of E-Health vs. In-Person Delivered Family Psychoeducation TreatmentI01HX001443 · VA · VETERANS HEALTH ADMINISTRATION · PI ROTONDI, ARMANDO JAMES · 2015 to 2021
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HSRD VA I01 HX001443
6 · The paper itself

Abstract

backgroundeHealth applications not only offer the potential to increase service convenience and responsiveness but also expand the ability to tailor services to improve relevance, engagement, and use. To achieve these goals, it is critical that the designs are intuitive. Limited research exists on designs that work for those with a severe mental illness (SMI), many of whom have difficulty traveling for treatments, reject or infrequently seek treatment, and tend to discontinue treatments for significant periods.

objectiveThis study aims to evaluate the influence of 12 design variables (eg, navigational depth, reading level, and use of navigational lists) on the usability of eHealth application websites for those with and without SMI.

methodsA 2

resultsThe best and worst designs were identified for each of these 4 groups. The depth of a website's navigation, that is, the number of screens users needed to navigate to find the desired content, had the greatest influence on usability (ability to find information) and efficiency (time to find information). The worst performing designs for those with SSD had a 9% success rate, and the best had a 51% success rate: the navigational designs made a 42% difference in usability. For the group with other mental illnesses, the design made a 50% difference, and for those with no mental illness, a 55% difference was observed. The designs with the highest usability had several key design similarities, as did those with the poorest usability.

conclusionsIt is possible to identify evidence-based strategies for designing eHealth applications that result in significantly better performance. These improvements in design benefit all users. For those with SSD or other SMIs, there are designs that are highly effective. Both the best and worst designs have key similarities but vary in some characteristics.

Indexed as

Mental DisordersTelemedicineFemaleHumansMaleMental HealthSchizophreniaeHealtheHealth designfractional factorial designschizophreniasevere mental illnessusabilitywebsitewebsite designwebsite usability

Identifiers

PMID33759796
PMCPMC8262839

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.