Background: The internet is now a major source of health information. With the growth of internet users, eHealth literacy has emerged as a new concept for digital health care. Therefore, health professionals need to consider the eHealth literacy of consumers when providing care utilizing digital health technologies. Objective: This study aimed to identify currently available eHealth literacy instruments and evaluate their measurement properties to provide robust evidence to researchers and clinicians who are selecting an eHealth literacy instrument. Methods: We conducted a systematic review and meta-analysis of self-reported eHealth literacy instruments by applying the updated COSMIN (COnsensus-based Standards for the selection of health Measurement INstruments) methodology. Results: This study included 7 instruments from 41 articles describing 57 psychometric studies, as identified in 4 databases (PubMed, CINAHL, Embase, and PsycInfo). No eHealth literacy instrument provided evidence for all measurement properties. The eHealth literacy scale (eHEALS) was originally developed with a single-factor structure under the definition of eHealth literacy before the rise of social media and the mobile web. That instrument was evaluated in 18 different languages and 26 countries, involving diverse populations. However, various other factor structures were exhibited: 7 types of two-factor structures, 3 types of three-factor structures, and 1 bifactor structure. The transactional eHealth literacy instrument (TeHLI) was developed to reflect the broader concept of eHealth literacy and was demonstrated to have a sufficient low-quality and very low-quality evidence for content validity (relevance, comprehensiveness, and comprehensibility) and sufficient high-quality evidence for structural validity and internal consistency; however, that instrument has rarely been evaluated. Conclusions: The eHealth literacy scale was the most frequently investigated instrument. However, it is strongly recommended that the instrument's content be updated to reflect recent advancements in digital health technologies. In addition, the transactional eHealth literacy instrument needs improvements in content validity and further psychometric studies to increase the credibility of its synthesized evidence.

Chae DH, et al. J Korean Acad Nurs Adm. 2012 Mar;18(1):76-86. http://dx.doi.org/10.11111/jkana.2012.18.1.76

This review aimed to evaluate the internal structure (structural validity, internal consistency, and measurement invariance) of the Patient Health Questionnire-9 (PHQ-9), which is one of the most widely used self-administered instruments for assessing and screening depression. The updated COnsensus-based Standards for the selection of health Measurement Instruments (COSMIN) methodology for a systematic review of self-reported instruments was used. PubMed, Embase, CINAHL, PsycINFO, and Cochrane Library databases were searched from their inception up to February 28, 2023. This study reviewed 98 psychometric studies reported on in 90 reports conducted in 40 countries. Various versions of the PHQ-9 were identified: one-factor structures (8 types), two-factor structures (10 types), bifactor structures (4 types), three-factor structure (1 type), and second-order three-factor structure (1 type). There was sufficient high-quality evidence for structural validity of the one-factor structure with nine items scored using a four-point Likert scale based on confirmatory factor analysis, for internal consistency with a quantitatively pooled Cronbach's alpha of .85, and for measurement invariance across sex, age, education level, marital status, and income groups. There was sufficient high-quality evidence for structural validity, internal consistency (Cronbach's alpha = .76 - .92, = .83 - .92), and measurement invariance across sex for the PHQ-8 (which excluded item 9: "suicidality or self-harm thoughts"). The one-factor PHQ-9 and PHQ-8 (excluding item 9) scored using a four-point Likert scale have the best internal structure based on the current evidence. The one-factor PHQ-9 and PHQ-8 justify the use of aggregated total scores in both practice and research. The total score of the PHQ-9 using a four-point Likert scale can be used to compare depression levels across sex, age, education level, marital status, and income groups due to the availability of sufficient evidence for measurement invariance across these demographic groups.

This study aims to identify predictors of turnover intention within 2 years of employment among 3rd and 4th grade Generation Z nursing students. Turnover intention is a multi-stage process ranging from mere desire, to serious thoughts, decision-making, and actual planning. Previous studies have focused on identifying the factors affecting turnover intention among practicing nurses. However, undergraduate nursing students also contemplate their decision to stay or leave the nursing profession after graduation. This cross-sectional descriptive study recruited 210 nursing students from 3 colleges in South Korea. A self-administered survey was conducted using the Career Preparation Behavior Scale, the Calling and Vocational Questionnaire, the Social Responsibility Scale, and the Revised Self-Leadership Questionnaire. Four questions were used to explore participants’ turnover intention, their motivation for studying nursing, their major satisfaction, and their clinical experience satisfaction. Descriptive and multiple logistic regression statistics were obtained using SPSS. Of the participants, 17.6% had turnover intention within 2 years of employment. Multiple logistic regression analysis indicates that clinical experience satisfaction is the only significant predictor. In the univariate analysis, nursing students who had turnover intentions were less likely to practice career preparation behaviors and had lower levels of vocational consciousness and social responsibility. To keep a proficient nursing workforce in the profession, professional commitments from universities and hospital institutions are needed to provide quality clinical learning experiences for nursing students. Further prospective study is needed to observe how Generation Z undergraduate students’ turnover intentions change and what factors influence this process.