The concept of e-health readiness sits at the intersection of technology acceptance and health psychology. It captures the degree to which a person possesses the psychological preparedness, confidence, and willingness to adopt electronic health services such as telemedicine platforms, personal health record systems, and online appointment tools. Readiness is not simply a matter of owning a smartphone or having an internet connection. Drawing on theoretical foundations from Bandura’s work on self-efficacy and Ajzen’s theory of planned behavior, researchers have long argued that perceived usefulness, perceived ease of use, and confidence in one’s own abilities shape whether people actually embrace digital health tools. A scale that measures this latent construct reliably allows health systems to identify populations that need support before rolling out expensive digital infrastructure.

Adapting a measurement instrument from one language and culture to another is far more involved than translation. Guidelines from cross-cultural psychometrics, including the widely cited work of van de Vijver and Hambleton, warn that literal translations can distort item meaning, shift response patterns, and ultimately invalidate scores. The researchers followed standard adaptation procedures to ensure that the Turkish version preserved the conceptual content of the original scale while reading naturally for Turkish respondents. This process matters because constructs like readiness are embedded in cultural context: attitudes toward technology, trust in health institutions, and familiarity with digital services differ substantially between countries, and a poorly adapted scale could systematically overstate or understate a population’s preparedness.

A distinctive strength of the study lies in its statistical treatment of the data. Because responses on Likert-type scales are ordinal rather than continuous, treating them as interval data can bias factor analytic results. The researchers therefore used polychoric correlations combined with minimal residual extraction in their exploratory factor analysis, an approach recommended for ordinal variables. To determine how many factors underlie the scale, they did not rely on the often-criticized Kaiser criterion alone but also applied Horn’s parallel analysis and Velicer’s minimum average partial procedure, two of the most defensible factor retention methods available. Both exploratory and confirmatory approaches were used, giving the findings a level of robustness that exceeds typical scale adaptation studies.

The results were strikingly clear. Exploratory factor analysis revealed a single-factor structure, with that one factor accounting for 58.453 percent of the total variance, a substantial proportion for a unidimensional attitude scale. Confirmatory factor analysis, conducted with weighted least squares mean and variance adjusted estimation and theta parameterization, verified that the single-factor structure of the original version held in the Turkish sample. In other words, the scale measures one coherent construct, e-health readiness, and it does so in Turkish respondents just as it was designed to do in its original context. The consistency between the exploratory and confirmatory results, and their agreement with the parallel analysis and MAP procedures, strengthens confidence that the one-factor solution is not a statistical artifact.

Reliability, the degree to which a scale produces consistent scores, was assessed from multiple angles. Internal consistency was excellent: Cronbach’s alpha reached 0.938, and McDonald’s omega, an increasingly preferred coefficient because it relaxes the assumption of equal item loadings, matched it at 0.938. Reporting both coefficients is considered best practice in contemporary psychometrics, since alpha can underestimate reliability when items load unequally on the factor. Stability over time was examined with a test-retest design, yielding a correlation coefficient of 0.907, which indicates that the scale captures a stable attribute rather than a fleeting mood. Together, these figures place the Turkish adaptation among the most reliable instruments in the e-health measurement literature.

The study also tackled a question that many adaptation efforts neglect: does the scale function equivalently for men and women? Using multi-group confirmatory factor analysis, the researchers compared configural, metric, scalar, and strict invariance models, testing whether the scale measures the same construct with the same precision across gender groups. The changes in fit indices met established thresholds, with changes in the comparative fit index at or below 0.010 and changes in root mean square error of approximation at or below 0.015, criteria drawn from the influential work of Cheung and Rensvold. Achieving measurement invariance up to the strict level means that observed score differences between men and women, if they appear in future studies, can be interpreted as genuine differences in readiness rather than artifacts of the measurement instrument itself.

To establish criterion-related validity, the researchers examined correlations between the adapted scale and established e-health literacy measurement tools, including instruments in the tradition of Norman and Skinner’s eHEALS. Positive associations with e-health literacy measures are exactly what theory predicts, since individuals who feel capable of finding and using health information online should also report greater readiness to adopt electronic health services. This convergent evidence ties the new Turkish instrument into a broader international research ecosystem, allowing findings from Turkish samples to be compared meaningfully with studies conducted elsewhere using related measures of digital health preparedness.

The timing of this work is significant for Türkiye specifically. National statistics from the Turkish Statistical Institute document rapidly rising household internet access and information and communication technology use, and the country’s e-Nabız personal health system has brought digital health records to millions of citizens. Demirci’s broader doctoral research, from which this study emerges, examines factors associated with the use of that very system, including e-health readiness, engagement, communication competence, and impact. A validated readiness scale gives Turkish health administrators an evidence-based instrument for segmenting populations, identifying groups that may need training or alternative service channels, and evaluating whether interventions designed to boost digital adoption are actually working.

The implications extend well beyond one country. Studies from Ethiopia, Iraq, Poland, and other settings have shown that e-health readiness assessment is a cornerstone of sustainable digital health implementation, particularly in developing health systems where resources are limited and failed rollouts are costly. Research on older adults has repeatedly found that psychological factors, not just access, determine whether digital health services are embraced, and randomized trials of e-health interventions increasingly measure readiness as a moderator of outcomes. By providing a rigorously validated Turkish instrument, the study fills a gap in a large and growing literature. The authors recommend that future research test the scale in more diverse population groups, a sensible next step given that psychometric properties can shift across age bands, educational levels, and clinical populations. For now, the Turkish adaptation stands as a model of careful cross-cultural measurement: ordinal-appropriate statistics, dual reliability coefficients, invariance testing, and criterion validation, all converging on a single, trustworthy measure of how ready people are to bring their health into the digital age.

Subject of Research: Turkish cultural adaptation and psychometric validation of the E-Health Readiness Scale

Article Title: Adaptatıon of the E-Health Readıness Scale to Turkısh culture

Article References: Demirci, H. F., & Yardan, E. D. (2026). Adaptatıon of the E-Health Readıness Scale to Turkısh culture. SN Social Sciences, 6(10), Article 520. https://doi.org/10.1007/s43545-026-01837-3

Image Credits: AI Generated

DOI: 10.1007/s43545-026-01837-3

Keywords: e-health readiness, scale adaptation, psychometrics, validity, reliability, confirmatory factor analysis, exploratory factor analysis, measurement invariance, digital health, Turkey, e-health literacy, SN Social Sciences