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Development and Validation of Digital Health Technology Literacy Assessment Questionnaire.

ABSTRACT: In clinical practice, assessing digital health literacy is important to identify patients who may encounter difficulties adapting to digital health using digital technology and service. We developed the Digital Health Technology Literacy Assessment Questionnaire (DHTL-AQ) to assess the ability to use digital health technology, services, and data. The DHTL-AQ was developed in three phases. In the first phase, the conceptual framework and domains and items were generated from a systematic literature review using relevant theory and surveys. In the second phase, a cross-sectional survey with 590 adults age ≥ 18 years was conducted at an academic hospital in Seoul, Korea in January and February 2020 to test face validity of the items. Then, psychometric validation was conducted to determine the final items and cut-off scores of the DHTL-AQ. The eHealth literacy scale, the Newest Vital Sign, and 10 mobile app task ability assessments were examined to test validity. The final DHTL-AQ includes 34 items in two domains (digital functional and digital critical literacy) and 4 categories (Information and Communications Technology terms, Information and Communications Technology icons, use of an app, evaluating reliability and relevance of health information). The DHTL-AQ had excellent internal consistency (overall Cronbach's α = 0.95; 0.87-0.94 for subtotals) and acceptable model fit (CFI = 0.821, TLI = 0.807, SRMR = 0.065, RMSEA = 0.090). The DHTL-AQ was highly correlated with task ability assessment (r = 0.7591), and moderately correlated with the eHealth literacy scale (r = 0.5265) and the Newest Vital Sign (r = 0.5929). The DHTL-AQ is a reliable and valid instrument to measure digital health technology literacy.

SUBMITTER: Yoon J

PROVIDER: S-EPMC8784987 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe increasing amount of health information available on the internet makes it more important than ever to ensure that people can judge the accuracy of this information to prevent them from harm. It may be possible for platforms to set up protective mechanisms depending on the level of digital health literacy and thereby to decrease the possibility of harm by the misuse of health information.ObjectiveThis study aimed to create an instrument for digital health literacy assessment (DHLA) based on the eHealth Literacy Scale (eHEALS) to categorize participants by level of risk of misinterpreting health information into high-, medium-, and low-risk groups.MethodsThis study developed a DHLA and constructed an online health information bank with correct and incorrect answers. Receiver operating characteristic curve analysis was used to detect the cutoff value of DHLA, using 5 items randomly selected from the online health information bank, to classify users as being at low, medium, or high risk of misjudging health information. This provided information about the relationship between risk group for digital health literacy and accurate judgement of online health information. The study participants were Taiwanese residents aged 20 years and older. Snowball sampling was used, and internet questionnaires were anonymously completed by the participants. The reliability and validity of DHLA were examined. Logistic regression was used to analyze factors associated with risk groups from the DHLA.ResultsThis study collected 1588 valid questionnaires. The online health information bank included 310 items of health information, which were classified as easy (147 items), moderate (122 items), or difficult (41 items) based on the difficulty of judging their accuracy. The internal consistency of DHLA was satisfactory (α=.87), and factor analysis of construct validity found three factors, accounting for 76.6% of the variance. The receiver operating characteristic curve analysis found 106 people at high risk, 1368 at medium risk, and 114 at low risk of misinterpreting health information. Of the original grouped cases, 89.6% were correctly classified after discriminate analysis. Logistic regression analysis showed that participants with a high risk of misjudging health information had a lower education level, lower income, and poorer health. They also rarely or never browsed the internet. These differences were statistically significant.ConclusionsThe DHLA score could distinguish those at low, medium, and high risk of misjudging health information on the internet. Health information platforms on the internet could consider incorporating DHLA to set up a mechanism to protect users from misusing health information and avoid harming their health.

Project description:BackgroundMost health literacy measures require in-person administration or rely upon self-report.ObjectiveWe sought to develop and test the feasibility of a brief, objective health literacy measure that could be deployed via text messaging or online survey.DesignParticipants were recruited from ongoing NIH studies to complete a phone interview and online survey to test candidate items. Psychometric analyses included parallel analysis for dimensionality and item response theory. After 9 months, participants were randomized to receive the final instrument via text messaging or online survey.ParticipantsThree hundred six English and Spanish-speaking adults with ≥ 1 chronic condition MAIN MEASURES: Thirty-three candidate items for the new measure and patient-reported physical function, anxiety, depression, and medication adherence. All participants previously completed the Newest Vital Sign (NVS) in parent NIH studies.Key resultsParticipants were older (average 67 years), 69.6% were female, 44.3% were low income, and 22.0% had a high school level of education or less. Candidate items loaded onto a single factor (RMSEA: 0.04, CFI: 0.99, TLI: 0.98, all loadings >.59). Six items were chosen for the final measure, named the HL6. Items demonstrated acceptable internal consistency (α=0.73) and did not display differential item functioning by language. Higher HL6 scores were significantly associated with greater educational attainment (r=0.41), higher NVS scores (r=0.55), greater physical functioning (r=0.26), fewer depressive symptoms (r=-0.20), fewer anxiety symptoms (r=-0.15), and fewer barriers to medication adherence (r=-0.30; all p<.01). In feasibility testing, 75.2% of participants in the text messaging arm completed the HL6 versus 66.2% in the online survey arm (p=0.09). Socioeconomic disparities in completion were more common in the online survey arm.ConclusionsThe HL6 demonstrates adequate reliability and validity in both English and Spanish. This performance-based assessment can be administered remotely using commonly available technologies with fewer logistical challenges than assessments requiring in-person administration.

Project description:BackgroundAtrial fibrillation (AF) is a highly prevalent heart rhythm condition that has significant associated morbidity and requires chronic treatment. Mobile health (mHealth) technologies have the potential to enhance multiple aspects of AF care, including education, monitoring of symptoms, and encouraging and tracking medication adherence. We have previously implemented and tested relational agents to improve outcomes in chronic disease and sought to develop a smartphone-based relational agent for improving patient-centered outcomes in AF.ObjectiveThe objective of this study was to pilot a smartphone-based relational agent as preparation for a randomized clinical trial, the Atrial Fibrillation Health Literacy Information Technology Trial (AF-LITT).MethodsWe developed the relational agent for use by a smartphone consistent with our prior approaches. We programmed the relational agent as a computer-animated agent to simulate a face-to-face conversation and to serve as a health counselor or coach specific to AF. Relational agent's dialogue content, informed by a review of literature, focused on patient-centered domains and qualitative interviews with patients with AF, encompassed AF education, common symptoms, adherence challenges, and patient activation. We established that the content was accessible to individuals with limited health or computer literacy. Relational agent content coordinated with use of the smartphone AliveCor Kardia heart rate and rhythm monitor. Participants (N=31) were recruited as a convenience cohort from ambulatory clinical sites and instructed to use the relational agent and Kardia for 30 days. We collected demographic, social, and clinical characteristics and conducted baseline and 30-day assessments of health-related quality of life (HRQoL) with the Atrial Fibrillation Effect on Quality of life (AFEQT) measure; self-reported medication adherence with the Morisky 8-item Medication Adherence Scale (MMAS-8); and patient activation with the Patient Activation Measure (PAM).ResultsParticipants (mean age 68 [SD 11]; 39% [12/31] women) used the relational agent for an average 17.8 (SD 10.0) days. The mean number of independent log-ins was 19.6 (SD 10.7), with a median of 20 times over 30 days. The mean number of Kardia uses was 26.5 (SD 5.9), and participants using Kardia were in AF for 14.3 (SD 11.0) days. AFEQT scores improved significantly from 64.5 (SD 22.9) at baseline to 76.3 (SD 19.4) units at 30 days (P<.01). We observed marginal but statistically significant improvement in self-reported medication adherence (baseline: 7.3 [SD 0.9], 30 days: 7.7 [SD 0.5]; P=.01). Assessments of acceptability identified that most of the participants found the relational agent useful, informative, and trustworthy.ConclusionsWe piloted a 30-day smartphone-based intervention that combined a relational agent with dedicated content for AF alongside Kardia heart rate and rhythm monitoring. Pilot participants had favorable improvements in HRQoL and self-reported medication adherence, as well as positive responses to the intervention. These data will guide a larger, enhanced randomized trial implementing the smartphone relational agent and the Kardia monitor system.

Project description:BACKGROUND:To achieve full potential in user-oriented eHealth projects, we need to ensure a match between the eHealth technology and the user's eHealth literacy, described as knowledge and skills. However, there is a lack of multifaceted eHealth literacy assessment tools suitable for screening purposes. OBJECTIVE:The objective of our study was to develop and validate an eHealth literacy assessment toolkit (eHLA) that assesses individuals' health literacy and digital literacy using a mix of existing and newly developed scales. METHODS:From 2011 to 2015, scales were continuously tested and developed in an iterative process, which led to 7 tools being included in the validation study. The eHLA validation version consisted of 4 health-related tools (tool 1: "functional health literacy," tool 2: "health literacy self-assessment," tool 3: "familiarity with health and health care," and tool 4: "knowledge of health and disease") and 3 digitally-related tools (tool 5: "technology familiarity," tool 6: "technology confidence," and tool 7: "incentives for engaging with technology") that were tested in 475 respondents from a general population sample and an outpatient clinic. Statistical analyses examined floor and ceiling effects, interitem correlations, item-total correlations, and Cronbach coefficient alpha (CCA). Rasch models (RM) examined the fit of data. Tools were reduced in items to secure robust tools fit for screening purposes. Reductions were made based on psychometrics, face validity, and content validity. RESULTS:Tool 1 was not reduced in items; it consequently consists of 10 items. The overall fit to the RM was acceptable (Anderson conditional likelihood ratio, CLR=10.8; df=9; P=.29), and CCA was .67. Tool 2 was reduced from 20 to 9 items. The overall fit to a log-linear RM was acceptable (Anderson CLR=78.4, df=45, P=.002), and CCA was .85. Tool 3 was reduced from 23 to 5 items. The final version showed excellent fit to a log-linear RM (Anderson CLR=47.7, df=40, P=.19), and CCA was .90. Tool 4 was reduced from 12 to 6 items. The fit to a log-linear RM was acceptable (Anderson CLR=42.1, df=18, P=.001), and CCA was .59. Tool 5 was reduced from 20 to 6 items. The fit to the RM was acceptable (Anderson CLR=30.3, df=17, P=.02), and CCA was .94. Tool 6 was reduced from 5 to 4 items. The fit to a log-linear RM taking local dependency (LD) into account was acceptable (Anderson CLR=26.1, df=21, P=.20), and CCA was .91. Tool 7 was reduced from 6 to 4 items. The fit to a log-linear RM taking LD and differential item functioning into account was acceptable (Anderson CLR=23.0, df=29, P=.78), and CCA was .90. CONCLUSIONS:The eHLA consists of 7 short, robust scales that assess individual's knowledge and skills related to digital literacy and health literacy.

Project description:PurposeThis pilot study developed and evaluated the feasibility, usability, and perceived satisfaction with an end-user mobile medical application and provider web portal. The two interfaces allowed for remote monitoring, provided daily guidance in the management of hypertension and diarrhea, and allowed for rapid management of adverse events during a clinical trial of olaparib and cediranib.Patients and methodseCO (eCediranib/Olaparib) was designed for patient self-reported, real-time management of hypertension and diarrhea using remote monitoring. eCO links to a Bluetooth-enabled blood pressure (BP) monitor and transmits data to a secure provider web portal. eCO use was assessed for suitability, usability, and satisfaction after 4 weeks using a 17-item questionnaire. Metrics regarding patient-reported BP and diarrhea events were analyzed.ResultsSixteen patients enrolled in the pilot. A total of 98.2% of expected BP values were reported: 94.2% via Bluetooth and 5.8% entered manually. Twelve patients experienced 21 BP events (systolic BP > 140 and/or diastolic BP > 90 mmHg on two consecutive readings); data from cycle 1 were comparable to the study database. Thirteen patients reported diarrhea (more than one stool per 24 hours over baseline) categorized as grade 1 or 2, which was comparable to the study database. Survey analysis showed that patients had statistically significant, positive responses to the use of the eCO application. Patients indicated eCO use made them feel more involved in their care and better connected to their health care team. The only aspect of the application that did not show a statistically significant positive response was the process of reporting diarrhea.ConclusionThe eCO application was designed to assist in managing acute treatment-related events most often associated with treatment discontinuation, need for drug holidays, or dose interruption. Hypertension and diarrhea events reported via eCO allowed rapid provider response and a positive overall patient experience.

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Development and Validation of Digital Health Technology Literacy Assessment Questionnaire.

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