The use of e-health can lead to several positive outcomes. However, the potential for e-health to improve healthcare is partially dependent on its ease of use. In order to determine the usability for any technology, rigorously developed and appropriate measures must be chosen.
To identify psychometrically tested questionnaires that measure usability of e-health tools, and to appraise their generalizability, attributes coverage, and quality.
We conducted a systematic review of studies that measured usability of e-health tools using four databases (Scopus, PubMed, CINAHL, and HAPI). Non-primary research, studies that did not report measures, studies with children or people with cognitive limitations, and studies about assistive devices or medical equipment were systematically excluded. Two authors independently extracted information including: questionnaire name, number of questions, scoring method, item generation, and psychometrics using a data extraction tool with pre-established categories and a quality appraisal scoring table.
Using a broad search strategy, 5,558 potentially relevant papers were identified. After removing duplicates and applying exclusion criteria, 35 articles remained that used 15 unique questionnaires. From the 15 questionnaires, only 5 were general enough to be used across studies. Usability attributes covered by the questionnaires were: learnability (15), efficiency (12), and satisfaction (11). Memorability (1) was the least covered attribute. Quality appraisal showed that face/content (14) and construct (7) validity were the most frequent types of validity assessed. All questionnaires reported reliability measurement. Some questionnaires scored low in the quality appraisal for the following reasons: limited validity testing (7), small sample size (3), no reporting of user centeredness (9) or feasibility estimates of time, effort, and expense (7).
Existing questionnaires provide a foundation for research on e-health usability. However, future research is needed to broaden the coverage of the usability attributes and psychometric properties of the available questionnaires.
This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 August 2021.
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#9,963,976
of 29,615,412 outputs
Outputs from Applied Clinical Informatics
#405
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Outputs of similar age
#161,491
of 461,666 outputs
Outputs of similar age from Applied Clinical Informatics
#118
of 359 outputs
Altmetric has tracked 29,615,412 research outputs across all sources so far. This one has received more attention than most of these and is in the 65th percentile.
So far Altmetric has tracked 1,278 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one has gotten more attention than average, scoring higher than 67% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 461,666 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.
We're also able to compare this research output to 359 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
