From Relational Care Quality to Digital Health Literacy: The Mediating Role of Patient Engagement and Moderating Role of Patient Satisfaction
DOI:
https://doi.org/10.61255/jeemba.v4i5.1707Keywords:
Patient Engagement, Digital Health Literacy, Relational Care Quality, Patient SatisfactionAbstract
Purpose – Indonesian regional hospitals face pressure to expand digital health services, yet whether patient engagement builds the digital literacy needed to use them, and under what conditions, remains untested. This study examined whether perceived care continuity, practitioner communication, and perceived empathic care predict patient digital literacy directly and indirectly through patient engagement, and whether patient satisfaction moderates the engagement-to-digital-literacy path.
Design/methodology/approach – This study used partial least squares structural equation modeling (PLS-SEM) on data from 400 patients across three Type B hospitals in Makassar, Indonesia.
Finding/Results – All three relational care quality constructs significantly predicted patient engagement (R² = .499), which significantly predicted digital literacy (β = .531, R² = .475). Care continuity and communication retained significant direct effects on digital literacy, while empathic care operated entirely through engagement. Patient satisfaction alone did not predict digital literacy, but its interaction with engagement was significant (β = .238), nearly tripling the effect from β = .293 among less-satisfied patients to β = .769 among more-satisfied patients. Confirmatory tetrad analysis supported the reflective measurement model, and reliability and validity criteria were met.
Originality/Value – Findings suggest patient engagement functions as a developmental pathway to digital literacy, conditional on satisfaction, offering hospital managers a sequencing rationale for pairing digital-service rollouts with service-quality improvement.
Abstract views: 10
,
PDF downloads: 5
Downloads
References
Alharbi, K., Almutairi, H. A., & Albagami, N. S. (2026). Exploring the patient engagement in the healthcare decision-making process and its association with patients' satisfaction. Nursing Open, 13(4), e70501. https://doi.org/10.1002/nop2.70501
Bonifanti, L., Ko, C., & Ownby, R. L. (2025). The role of electronic health (eHealth) literacy in patient activation: A sequential block regression analysis controlling for sociodemographic factors. Cureus, 17(11), e97646. https://doi.org/10.7759/cureus.97646
Cha, Y.-J. (2025). Key factors influencing outpatient satisfaction in chronic disease care: Insights from the 2023 Korea HSES. Healthcare, 13(6), 655. https://doi.org/10.3390/healthcare13060655
Chen, C.-C., & Cheng, S.-H. (2023). Does continuity of care improve patient satisfaction? An instrumental variable approach. Health Policy, 130, 104754. https://doi.org/10.1016/j.healthpol.2023.104754
Deshpande, N., Arora, V. M., Vollbrecht, H., Meltzer, D. O., & Press, V. (2023). eHealth literacy and patient portal use and attitudes: Cross-sectional observational study. JMIR Human Factors, 10, e40105. https://doi.org/10.2196/40105
Dul, J. (2016). Necessary condition analysis (NCA): Logic and methodology of 'necessary but not sufficient' causality. Organizational Research Methods, 19(1), 10-52. https://doi.org/10.1177/1094428115584005
Dul, J., Van der Laan, E., & Kuik, R. (2020). A statistical significance test for necessary condition analysis. Organizational Research Methods, 23(2), 385-395. https://doi.org/10.1177/1094428118795272
Gudergan, S. P., Ringle, C. M., Wende, S., & Will, A. (2008). Confirmatory tetrad analysis in PLS path modeling. Journal of Business Research, 61(12), 1238-1249. https://doi.org/10.1016/j.jbusres.2008.01.012
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). Sage Publications.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2016). Testing measurement invariance of composites using partial least squares. International Marketing Review, 33(3), 405-431. https://doi.org/10.1108/IMR-09-2014-0304
Hibbard, J. H., Mahoney, E. R., Stockard, J., & Tusler, M. (2005). Development and testing of a short form of the Patient Activation Measure. Health Services Research, 40(6 Pt 1), 1918-1930. https://doi.org/10.1111/j.1475-6773.2005.00438.x
Keelson, S. A., Addo, J. O., & Amoah, J. (2024). The impact of patient engagement on service quality and customer well-being: An introspective analysis from the healthcare providers' perspective. Cogent Public Health, 11(1), 2340157. https://doi.org/10.1080/27707571.2024.2340157
Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration, 11(4), 1-10. https://doi.org/10.4018/ijec.2015100101
Liengaard, B. D., Sharma, P. N., Hult, G. T. M., Jensen, M. B., Sarstedt, M., Hair, J. F., & Ringle, C. M. (2021). Prediction: Coveted, yet forsaken? Introducing a cross-validated predictive ability test in partial least squares path modeling. Decision Sciences, 52(2), 362-392. https://doi.org/10.1111/deci.12445
Makoul, G., Krupat, E., & Chang, C. H. (2007). Measuring patient views of physician communication skills: Development and testing of the Communication Assessment Tool. Patient Education and Counseling, 67(3), 333-342. https://doi.org/10.1016/j.pec.2007.05.005
Marshall, G. N., & Hays, R. D. (1994). The Patient Satisfaction Questionnaire Short-Form (PSQ-18). RAND Corporation, P-7865. https://www.rand.org/pubs/papers/P7865.html
Marzban, S., Najafi, M., Agolli, A., & Ashrafi, E. (2022). Impact of patient engagement on healthcare quality: A scoping review. Journal of Patient Experience, 9, 23743735221125439. https://doi.org/10.1177/23743735221125439
Mei, Y., Xu, X., & Li, X. (2020). Encouraging patient engagement behaviors from the perspective of functional quality. International Journal of Environmental Research and Public Health, 17(22), 8613. https://doi.org/10.3390/ijerph17228613
Mercer, S. W., Maxwell, M., Heaney, D., & Watt, G. C. M. (2004). The consultation and relational empathy (CARE) measure: Development and preliminary validation and reliability of an empathy-based consultation process measure. Family Practice, 21(6), 699-705. https://doi.org/10.1093/fampra/cmh621
Norman, C. D., & Skinner, H. A. (2006). eHEALS: The eHealth Literacy Scale. Journal of Medical Internet Research, 8(4), e27. https://doi.org/10.2196/jmir.8.4.e27
Peimani, M., Stewart, A. L., Ghodssi-Ghassemabadi, R., Nasli-Esfahani, E., & Ostovar, A. (2024). The moderating role of e-health literacy and patient-physician communication in the relationship between online diabetes information-seeking behavior and self-care practices among individuals with type 2 diabetes. BMC Primary Care, 25(1), 442. https://doi.org/10.1186/s12875-024-02695-9
Ringle, C. M., & Sarstedt, M. (2016). Gain more insight from your PLS-SEM results: The importance-performance map analysis. Industrial Management & Data Systems, 116(9), 1865-1886. https://doi.org/10.1108/IMDS-10-2015-0449
Sharma, P. N., Liengaard, B. D., Hair, J. F., Sarstedt, M., & Ringle, C. M. (2023). Predictive model assessment and selection in composite-based modeling using PLS-SEM: Extensions and guidelines for using CVPAT. European Journal of Marketing, 57(6), 1662-1677. https://doi.org/10.1108/EJM-08-2020-0636
Shmueli, G., Sarstedt, M., & Hair, J. F. (2019). Predictive model assessment in PLS-SEM: Guidelines for using PLSpredict. European Journal of Marketing, 53(11), 2322-2347. https://doi.org/10.1108/EJM-02-2019-0189
Shiu, L.-S., Huang, Y.-S., Liu, C. Y., Cheng, Y.-S., & Chen, Y.-C. (2025). eHealth literacy mediating social support and technology acceptance among patients with chronic illnesses: A cross-sectional study. Journal of Advanced Nursing, 82(5), 5049-5059. https://doi.org/10.1111/jan.70207
Uijen, A. A., Schellevis, F. G., van den Bosch, W. J. H. M., Mokkink, H. G. A., van Weel, C., & Schers, H. J. (2011). Nijmegen Continuity Questionnaire: Development and testing of a questionnaire that measures continuity of care. Journal of Clinical Epidemiology, 64(12), 1391-1399. https://doi.org/10.1016/j.jclinepi.2011.03.006
Zhao, X., Lynch, J. G., & Chen, Q. (2010). Reconsidering Baron and Kenny: Myths and truths about mediation analysis. Journal of Consumer Research, 37(2), 197-206. https://doi.org/10.1086/651257
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Made Santika, Thomas Stefanus Kaihatu, Timotius Febry Christian

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
















Email: fadhila.della@gmail.com, andika.isma@unm.ac.id