Evidence map›Paper›PMID 29712620›Full record

ArticleJMIR human factors2018

A Web-Based Treatment Decision Support Tool for Patients With Advanced Knee Arthritis: Evaluation of User Interface and Content Design.

Hua Zheng, Milagros C Rosal, Wenjun Li, Amy Borg, Wenyun Yang, David C Ayers, Patricia D Franklin

Registry-linked trialAbstract read
In one paragraph

Article in JMIR human factors, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT00566826 (Perioperative Intervention to Improve Post-TKR Support and Function), which is not on this map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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.

NCT00566826 phase2completednot on this map

Perioperative Intervention to Improve Post-TKR Support and Function

TypeinterventionalSponsorUniversity of Massachusetts, WorcesterRan2008 to 2012Enrolled196ConditionsOsteoarthritis, Arthroplasty, Replacement, KneeArmsPatient support sessions, Treatment as usual
3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Hua ZhengDepartment of Orthopedics and Physical Rehabilitation, University of Massachusetts Medical School, Worcester, MA, United States.ORCID http://orcid.org/0000-0002-0632-161X
Milagros C RosalDepartment of Orthopedics and Physical Rehabilitation, University of Massachusetts Medical School, Worcester, MA, United States.ORCID http://orcid.org/0000-0001-8497-5558
Wenjun LiDepartment of Orthopedics and Physical Rehabilitation, University of Massachusetts Medical School, Worcester, MA, United States.ORCID http://orcid.org/0000-0001-5335-7386
Amy BorgDepartment of Orthopedics and Physical Rehabilitation, University of Massachusetts Medical School, Worcester, MA, United States.ORCID http://orcid.org/0000-0002-6407-8945
Wenyun YangDepartment of Orthopedics and Physical Rehabilitation, University of Massachusetts Medical School, Worcester, MA, United States.ORCID http://orcid.org/0000-0002-9649-4265
David C AyersDepartment of Orthopedics and Physical Rehabilitation, University of Massachusetts Medical School, Worcester, MA, United States.ORCID http://orcid.org/0000-0001-5458-7052
Patricia D FranklinDepartment of Orthopedics and Physical Rehabilitation, University of Massachusetts Medical School, Worcester, MA, United States.ORCID http://orcid.org/0000-0002-4441-0533

Funding

Improving Orthopedic Outcomes Through a National TJR RegistryP50HS018910 · AHRQ · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI FRANKLIN, PATRICIA D · 2010 to 2013
$11.9M
Perioperative intervention to improve post-TKR support and functionR01AR054479 · NIAMS · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI FRANKLIN, PATRICIA D · 2007 to 2010
$1.7M
AHRQ HHS P50 HS018910AHRQ HHS R21 HS024003NIAMS NIH HHS R01 AR054479
6 · The paper itself

Abstract

backgroundData-driven surgical decisions will ensure proper use and timing of surgical care. We developed a Web-based patient-centered treatment decision and assessment tool to guide treatment decisions among patients with advanced knee osteoarthritis who are considering total knee replacement surgery.

objectiveThe aim of this study was to examine user experience and acceptance of the Web-based treatment decision support tool among older adults.

methodsUser-centered formative and summative evaluations were conducted for the tool. A sample of 28 patients who were considering total knee replacement participated in the study. Participants' responses to the user interface design, the clarity of information, as well as usefulness, satisfaction, and acceptance of the tool were collected through qualitative (ie, individual patient interviews) and quantitative (ie, standardized Computer System Usability Questionnaire) methods.

resultsParticipants were older adults with a mean age of 63 (SD 11) years. Three-quarters of them had no technical questions using the tool. User interface design recommendations included larger fonts, bigger buttons, less colors, simpler navigation without extra "next page" click, less mouse movement, and clearer illustrations with simple graphs. Color-coded bar charts and outcome-specific graphs with positive action were easiest for them to understand the outcomes data. Questionnaire data revealed high satisfaction with the tool usefulness and interface quality, and also showed ease of use of the tool, regardless of age or educational status.

conclusionsWe evaluated the usability of a patient-centered decision support tool designed for advanced knee arthritis patients to facilitate their knee osteoarthritis treatment decision making. The lessons learned can inform other decision support tools to improve interface and content design for older patients' use.

Indexed as

knee osteoarthritisoutcome predictionpatient decision supporttotal knee replacementusability evaluation

Identifiers

PMID29712620
PMCPMC5952113

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Registered trials

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.