Dataset Information

Development of an Item Bank to Measure Medication Adherence: Systematic Review.

ABSTRACT:

Background

Medication adherence is important in managing the progression of chronic diseases. A promising approach to reduce cognitive burden when measuring medication adherence lies in the use of computer-adaptive tests (CATs) or in the development of shorter patient-reported outcome measures (PROMs). However, the lack of an item bank currently hampers this progress.

Objective

We aim to develop an item bank to measure general medication adherence.

Methods

Using the preferred reporting items for systematic review and meta-analysis (PRISMA), articles published before October 2019 were retrieved from PubMed, Embase, CINAHL, the Cochrane Library, and Web of Science. Items from existing PROMs were classified and selected ("binned" and "winnowed") according to standards published by the Patient-Reported Outcomes Measurement Information System (PROMIS) Cooperative Group.

Results

A total of 126 unique PROMs were identified from 213 studies in 48 countries. Items from the literature review (47 PROMs with 579 items for which permission has been obtained) underwent binning and winnowing. This resulted in 421 candidate items (77 extent of adherence and 344 reasons for adherence).

Conclusions

We developed an item bank for measuring general medication adherence using items from validated PROMs. This will allow researchers to create new PROMs from selected items and provide the foundation to develop CATs.

SUBMITTER: Kwan YH

PROVIDER: S-EPMC7582150 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Publications

Development of an Item Bank to Measure Medication Adherence: Systematic Review.

Kwan Yu Heng YH Oo Livia Jia Yi LJY Loh Dionne Hui Fang DHF Phang Jie Kie JK Weng Si Dun SD Blalock Dan V DV Chew Eng Hui EH Yap Kai Zhen KZ Tan Corrinne Yong Koon CYK Yoon Sungwon S Fong Warren W Østbye Truls T Low Lian Leng LL Bosworth Hayden Barry HB Thumboo Julian J

Journal of medical Internet research 20201008 10

<h4>Background</h4>Medication adherence is important in managing the progression of chronic diseases. A promising approach to reduce cognitive burden when measuring medication adherence lies in the use of computer-adaptive tests (CATs) or in the development of shorter patient-reported outcome measures (PROMs). However, the lack of an item bank currently hampers this progress.<h4>Objective</h4>We aim to develop an item bank to measure general medication adherence.<h4>Methods</h4>Using the preferr ...[more]

PMID: 33030441

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Project description:BackgroundDiabetes is one of the leading noncommunicable chronic diseases globally. In people with diabetes, blood glucose levels need to be monitored regularly and managed adequately through healthy lifestyles and medications. However, various factors contribute to poor medication adherence. Smartphone apps can improve medication adherence in people with diabetes, but it is not clear which app features are most beneficial.ObjectiveThis study aims to systematically review and evaluate high-quality apps for diabetes medication adherence, which are freely available to the public in Android and Apple app stores and present the technical features of the apps.MethodsWe systematically searched Apple App Store and Google Play for apps that assist in diabetes medication adherence, using predefined selection criteria. We assessed apps using the Mobile App Rating Scale (MARS) and calculated the mean app-specific score (MASS) by taking the average of app-specific scores on 6 dimensions, namely, awareness, knowledge, attitudes, intention to change, help-seeking, and behavior change rated on a 5-point scale (1=strongly disagree and 5=strongly agree). We used the mean of the app's performance on these 6 dimensions to calculate the MASS. Apps that achieved a total MASS mean quality score greater than 4 out of 5 were considered to be of high quality in our study. We formulated a task-technology fit matrix to evaluate the apps for diabetes medication adherence.ResultsWe identified 8 high-quality apps (MASS score≥4) and presented the findings under 3 main categories: characteristics of the included apps, app features, and diabetes medication adherence. Our framework to evaluate smartphone apps in promoting diabetes medication adherence considered physiological factors influencing diabetes and app features. On evaluation, we observed that 25% of the apps promoted high adherence and another 25% of the apps promoted moderate adherence. Finally, we found that 50% of the apps provided low adherence to diabetes medication.ConclusionsOur findings show that almost half of the high-quality apps publicly available for free did not achieve high to moderate medication adherence. Our framework could have positive implications for the future design and development of apps for patients with diabetes. Additionally, apps need to be evaluated using a standardized framework, and only those promoting higher medication adherence should be prescribed for better health outcomes.

Project description:BackgroundPositive mindset (PM) is an important domain of health-related quality of life in Singapore, a multi-ethnic urban city state in Southeast Asia. We therefore developed and calibrated a novel item bank to measure and improve PM.MethodsWe developed an initial candidate pool of 48 items from focus groups, in-depth interviews and existing instruments locally developed and validated for use in Singapore. We administered all items in English to a multi-stage sample stratified for age and gender, of subjects with and without medical conditions recruited from the community and a hospital, and calibrated their responses using Samejima's Graded Response Model. We evaluated a final 36-item bank with respect to Item Response Theory (IRT) model assumptions, model fit, differential item functioning (DIF), concurrent and known-groups validity.ResultsAmong 493 participants (49.3% male, 41.6% above 50 years old, 33% Chinese, Malay and Indian), bifactor model analyses supported unidimensionality: explained common variance of the general factor was 0.86 and omega hierarchical was 0.97. Local independence was deemed acceptable: the average absolute residual correlations were <0.06 and 3.3% of the total item-pair residuals were flagged for local dependence. The overall model fit was adequate and provided good coverage of the PM construct (theta range: -3.6 to +2.4). Five items exhibited DIF with respect to ethnicity and gender, but were retained without modification of scores because they measured important aspects of PM. Scores correlated in the hypothesized direction with a self-reported measure of global health (Spearman's rho = -0.28, p<0.001) and discriminated between groups of participants with and without a self-reported diagnosis of a mood disorder (p = 0.007) adjusting for age, gender, ethnicity, education and marital status.ConclusionThe 36-item PM item bank demonstrated satisfactory psychometric properties for the English-speaking Singaporean population. IRT model assumptions were sufficiently met and scores showed concurrent and known-groups validity. Future studies to evaluate the validity of PM scores when items are administered adaptively are needed.

Project description:ObjectivesFunctional outcomes following cochlear implantation have traditionally been focused on word and sentence recognition, which, although important, do not capture the varied communication and other experiences of adult cochlear implant (CI) users. Although the inadequacies of speech recognition to quantify CI user benefits are widely acknowledged, rarely have adult CI user outcomes been comprehensively assessed beyond these conventional measures. An important limitation in addressing this knowledge gap is that patient-reported outcome measures have not been developed and validated in adult CI patients using rigorous scientific methods. The purpose of the present study is to build on our previous work and create an item bank that can be used to develop new patient-reported outcome measures that assess CI quality of life (QOL) in the adult CI population.DesignAn online questionnaire was made available to 500 adult CI users who represented the adult CI population and were recruited through a consortium of 20 CI centers in the United States. The questionnaire included the 101 question CIQOL item pool and additional questions related to demographics, hearing and CI history, and speech recognition scores. In accordance with the Patient-Reported Outcomes Measurement Information System, responses were psychometrically analyzed using confirmatory factor analysis and item response theory.ResultsOf the 500 questionnaires sent, 371 (74.2%) subjects completed the questionnaire. Subjects represented the full range of age, durations of CI use, speech recognition abilities, and listening modalities of the adult CI population; subjects were implanted with each of the three CI manufacturers' devices. The initial item pool consisted of the following domain constructs: communication, emotional, entertainment, environment, independence, listening effort, and social. Through psychometric analysis, after removing locally dependent and misfitting items, all of the domains were found to have sound psychometric properties, with the exception of the independence domain. This resulted in a final CIQOL item bank of 81 items in 6 domains with good psychometric properties.ConclusionsOur findings reveal that hypothesis-driven quantitative analyses result in a psychometrically sound CIQOL item bank, organized into unique domains comprised of independent items which measure the full ability range of the adult CI population. The final item bank will now be used to develop new instruments that evaluate and differentiate adult CIQOL across the patient ability spectrum.

Dataset Information

Development of an Item Bank to Measure Medication Adherence: Systematic Review.

Background

Objective

Methods

Results

Conclusions

Publications

Development of an Item Bank to Measure Medication Adherence: Systematic Review.

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