The Application and Evaluation of eHealth Literacy (eHL) Concept (eHL)

Improving Patients With Chronic Disease to Engage in the eHealth Care Environment: the Application and Evaluation of eHealth Literacy Concept

This study aims to explore the effectiveness of experience learning program of eHealth care to improve the chronic patients' eHL in engaging with the eHealth care system on the indicators on eHealth literacy, patient health engagement, e-Health usage status among Chronic disease patients included type 2 diabetes patients, Chronic kidney disease, and Cardiovascular Diseases.

Study Overview

• Status: Completed
• Conditions: Cardiovascular Diseases; Chronic Kidney Diseases; Type 2 Diabetes Mellitus
• Intervention / Treatment: Behavioral: experience learning programs of eHealth care

Detailed Description

Chronic diseases are irreversible that incurs considerable medical and economic costs. Even if the government and medical health care system make an effort to improve care and recommend e-health care, the incidence and prevalence rates of chronic diseases have not decreased but increased, and participants have even become the main cause of kidney disease. Technology and daily life has become more inseparable, which also led to the change of the traditional face to face health care model. The chronic disease care is gradually transitioning into the smart eHealth care era, patients are in need of learning how to face innovative ways of using care and resources. eHealth literacy (eHL)is the essential element that determines if patient can adapt to the rapidly changing health care system.

Due to the disciplinary integration of medical and technology, eHealth care provides continuous care for patients. But, it is still necessary to return to patient-centered care thinking and improving patients' knowledge and ability to use eHealth care technology. This can be applied to disease care, and implemented for daily self-health management. Therefore, this study explores the effects of intervention and the learning process and experience of patients through an experience learning program of eHealth care.

• Study Type: Interventional
• Enrollment (Actual): 92
• Phase: Not Applicable

Contacts and Locations

Study Locations

• Taiwan
  • Taipei City, Taiwan
    • National Yang Ming University

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 20 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

Description

Inclusion Criteria:

• Diagnosed as a type 2 diabetes patients, Chronic kidney disease, and Cardiovascular Diseases more than three months.
• At least 20 years old, with clear consciousness and able to communicate in Mandarin or Taiwanese.
• Possess a mobile phone or tablet with internet capabilities.
• Consent to participate in this research and be willing to sign a consent form.

Exclusion Criteria:

• Suffering from serious diseases, such as: general paralysis, mental disorders, cognitive function abnormalities, etc.
• Those who cannot communicate in Mandarin or Taiwanese.
• Those who refuse to participate in this research.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Health Services Research
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Single

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: experience learning programs of eHealth care; Patients in the experimental group received 6 sections of activities.	Behavioral: experience learning programs of eHealth care; The experience learning programs of eHealth care was included six sections of activities. Six activities were conducted based on eHealth literacy framework and experience learning theory to improve patients' abilities to engage in eHealth care service. The outcome indicators were eHealth literacy, patient health engagement, the acceptance of eHealth care, eHealth usage status, and their learning experience
No Intervention: Usual care; Patients in control group received usual care

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Baseline of eHealth Literacy Questionnaire scores	Evaluate the patient's eHL level, including 7 dimensions (1) Using technology to process health information, (2) Understanding of health concepts and languages, (3)Ability to actively engage with digital service, (4)Feel safe and in control, (5) Motivated to engage with digital service, (6) Access to digital services that work (7)Digital services that suit individual. The higher the score, the better the eHL.	The pretest is completed when the patients agrees to join the intervention.
The eHealth Literacy Questionnaire scores at the end of intervention	Evaluate the patient's eHL level, including 7 dimensions (1) Using technology to process health information, (2) Understanding of health concepts and languages, (3)Ability to actively engage with digital service, (4)Feel safe and in control, (5) Motivated to engage with digital service, (6) Access to digital services that work (7)Digital services that suit individual. The higher the score, the better the eHL.	The post-test 1 is completed at the end of the 6 weeks intervention
The eHealth Literacy Questionnaire scores after intervention at 3 months	Evaluate the patient's eHL level, including 7 dimensions (1) Using technology to process health information, (2) Understanding of health concepts and languages, (3)Ability to actively engage with digital service, (4)Feel safe and in control, (5) Motivated to engage with digital service, (6) Access to digital services that work (7)Digital services that suit individual. The higher the score, the better the eHL.	The post-test 2 is completed after intervention at 3 months
The eHealth Literacy Questionnaire scores after intervention at 6 months	Evaluate the patient's eHL level, including 7 dimensions (1) Using technology to process health information, (2) Understanding of health concepts and languages, (3)Ability to actively engage with digital service, (4)Feel safe and in control, (5) Motivated to engage with digital service, (6) Access to digital services that work (7)Digital services that suit individual. The higher the score, the better the eHL.	The post-test 3 is completed after intervention at 6 months
Baseline of The acceptance of eHealth care scores	The scale was developed base on Technology Acceptance Model to assess patients' behaviors intention of using the eHealth device	The pretest is completed when the patients agrees to join the intervention.
The acceptance of eHealth care scores at the end of intervention	The scale was developed base on Technology Acceptance Model to assess patients' behaviors intention of using the eHealth device	The post-test 1 is completed at the end of the 6 weeks intervention
The acceptance of eHealth care scores after intervention at 3 months	The scale was developed base on Technology Acceptance Model to assess patients' behaviors intention of using the eHealth device	The post-test 2 is completed after intervention at 3 months
The acceptance of eHealth care scores after intervention at 6 months	The scale was developed base on Technology Acceptance Model to assess patients' behaviors intention of using the eHealth device	The post-test 3 is completed after intervention at 6 months
Baseline of Health Technology Usage Sore	Use self-developed structured questionnaires to investigate the types of health technology use and monitoring items. Use types include computer or network systems, mobile apps, health monitoring systems or wearable devices (such as pedometers, smart bracelets, heart rate monitors, blood pressure monitors, Blood glucose meter, blood pressure meter, blood glucose meter or weight scale, etc.) or other, monitoring items include blood pressure, blood sugar, weight, diet, sleep, heart rate, steps or other health data. The higher the number, the more items are monitored, the total score The higher the level, the better the use of health technology.	The pretest is completed when the patients agrees to join the intervention.
The Health Technology Usage Sore at the end of intervention	Use self-developed structured questionnaires to investigate the types of health technology use and monitoring items. Use types include computer or network systems, mobile apps, health monitoring systems or wearable devices (such as pedometers, smart bracelets, heart rate monitors, blood pressure monitors, Blood glucose meter, blood pressure meter, blood glucose meter or weight scale, etc.) or other, monitoring items include blood pressure, blood sugar, weight, diet, sleep, heart rate, steps or other health data. The higher the number, the more items are monitored, the total score The higher the level, the better the use of health technology.	The post-test 1 is completed at the end of the 6 weeks intervention
The Health Technology Usage Sore after intervention at 3 months	Use self-developed structured questionnaires to investigate the types of health technology use and monitoring items. Use types include computer or network systems, mobile apps, health monitoring systems or wearable devices (such as pedometers, smart bracelets, heart rate monitors, blood pressure monitors, Blood glucose meter, blood pressure meter, blood glucose meter or weight scale, etc.) or other, monitoring items include blood pressure, blood sugar, weight, diet, sleep, heart rate, steps or other health data. The higher the number, the more items are monitored, the total score The higher the level, the better the use of health technology.	The post-test 2 is completed after intervention at 3 months
The Health Technology Usage Sore after intervention at 6 months	Use self-developed structured questionnaires to investigate the types of health technology use and monitoring items. Use types include computer or network systems, mobile apps, health monitoring systems or wearable devices (such as pedometers, smart bracelets, heart rate monitors, blood pressure monitors, Blood glucose meter, blood pressure meter, blood glucose meter or weight scale, etc.) or other, monitoring items include blood pressure, blood sugar, weight, diet, sleep, heart rate, steps or other health data. The higher the number, the more items are monitored, the total score The higher the level, the better the use of health technology.	The post-test 3 is completed after intervention at 6 months
Baseline of Patient Health Engagement score	The scale is thought of as a self-administering tool by the patient in order to diagnose his/ her This scale has a total of 5 questions. The higher the number, the higher the patient engagement it is.	The pretest is completed when the patients agrees to join the intervention.
The Patient Health Engagement score at the end of the intervention	The scale is thought of as a self-administering tool by the patient in order to diagnose his/ her This scale has a total of 5 questions. The higher the number, the higher the patient engagement it is.	The post-test 1 is completed at the end of the 6 weeks intervention
The Patient Health Engagement score after intervention at 3 months	The scale is thought of as a self-administering tool by the patient in order to diagnose his/ her This scale has a total of 5 questions. The higher the number, the higher the patient engagement it is.	The post-test 2 is completed after intervention at 3 months
The Patient Health Engagement score after intervention at 6 months	The scale is thought of as a self-administering tool by the patient in order to diagnose his/ her This scale has a total of 5 questions. The higher the number, the higher the patient engagement it is.	The post-test 3 is completed after intervention at 6 months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
The change in renal function level at the end of the intervention	The health outcome indicator of management of renal disease by using the estimated Glomerular filtration rate(eGRF) .	To collect two-time point data by chart review. Those were before the intervention and the end of the the 6 weeks intervention
The change Trajectory of renal function level from baseline to after intervention at 6 months and 1 year	The health outcome indicator of management of renal disease by using the estimated Glomerular filtration rate(eGRF) .	To collect three-time point data by chart review. Those were before the intervention, the end of the 6 weeks intervention, and after intervention at six months and 1 year
The change in HbA1C level at the end of the intervention	The health outcome indicator of management of diabetes	To collect two-time point data by chart review. Those were before the intervention and the end of the the 6 weeks intervention
The change Trajectory of HbA1C level from baseline to after the intervention at 3, 6, and 12 months	The health outcome indicator of management of diabetes	To collect four-time point data by chart review. Those were before the intervention, the end of the 6 weeks intervention, after the intervention at three months, after the intervention at six months, and after the intervention at twelve months
The change in Triglycerides level at the end of the intervention	The health outcome indicator of management of lipid	To collect two-time point data by chart review. Those were before the intervention and the end of the six weeks intervention
The change Trajectory of Triglycerides level from baseline to after the intervention at 3 , 6 and 12 months	The health outcome indicator of management of lipid	To collect four-time point data by chart review. Those were before the intervention, the end of the 6 weeks intervention, after the intervention at three months, after the intervention at six months, and after the intervention at twelve months.
The change in Cholesterol level at the end of the intervention	The health outcome indicator of management of lipid	To collect two-time point data by chart review. Those were before the intervention and the end of the 6 weeks intervention
The change Trajectory of Cholesterol level from baseline to after the intervention at 3, 6 and 12 months	The health outcome indicator of management of lipid	To collect two-time point data by chart review. Those were before the intervention, the end of the 6 weeks intervention, after the intervention at three months, after the intervention at six months, and after the intervention at twelve months.

Collaborators and Investigators

• Sponsor: National Yang Ming University
• Investigators: Study Chair: Yu-Chi Chen, Ph.D., National Yang Ming University

Publications and helpful links

General Publications

• Kayser L, Karnoe A, Furstrand D, Batterham R, Christensen KB, Elsworth G, Osborne RH. A Multidimensional Tool Based on the eHealth Literacy Framework: Development and Initial Validity Testing of the eHealth Literacy Questionnaire (eHLQ). J Med Internet Res. 2018 Feb 12;20(2):e36. doi: 10.2196/jmir.8371.
• Graffigna G, Barello S, Bonanomi A, Lozza E. Measuring patient engagement: development and psychometric properties of the Patient Health Engagement (PHE) Scale. Front Psychol. 2015 Mar 27;6:274. doi: 10.3389/fpsyg.2015.00274. eCollection 2015.
• Kayser L, Kushniruk A, Osborne RH, Norgaard O, Turner P. Enhancing the Effectiveness of Consumer-Focused Health Information Technology Systems Through eHealth Literacy: A Framework for Understanding Users' Needs. JMIR Hum Factors. 2015 May 20;2(1):e9. doi: 10.2196/humanfactors.3696.
• Richtering SS, Morris R, Soh SE, Barker A, Bampi F, Neubeck L, Coorey G, Mulley J, Chalmers J, Usherwood T, Peiris D, Chow CK, Redfern J. Examination of an eHealth literacy scale and a health literacy scale in a population with moderate to high cardiovascular risk: Rasch analyses. PLoS One. 2017 Apr 27;12(4):e0175372. doi: 10.1371/journal.pone.0175372. eCollection 2017.
• Schillinger D. The Intersections Between Social Determinants of Health, Health Literacy, and Health Disparities. Stud Health Technol Inform. 2020 Jun 25;269:22-41. doi: 10.3233/SHTI200020.
• Alpay L, van der Boog P, Dumaij A. An empowerment-based approach to developing innovative e-health tools for self-management. Health Informatics J. 2011 Dec;17(4):247-55. doi: 10.1177/1460458211420089.
• Knight E, Stuckey MI, Petrella RJ. Health promotion through primary care: enhancing self-management with activity prescription and mHealth. Phys Sportsmed. 2014 Sep;42(3):90-9. doi: 10.3810/psm.2014.09.2080.
• Kreps GL, Neuhauser L. New directions in eHealth communication: opportunities and challenges. Patient Educ Couns. 2010 Mar;78(3):329-36. doi: 10.1016/j.pec.2010.01.013. Epub 2010 Mar 3.

Helpful Links

• A Multidimensional Tool Based on the eHealth Literacy Framework: Development and Initial Validity Testing of the eHealth Literacy Questionnaire (eHLQ)
• Measuring patient engagement: development and psychometric properties of the Patient Health Engagement (PHE) Scale.

Study record dates

Study Major Dates

• Study Start (Actual): August 1, 2019
• Primary Completion (Actual): July 31, 2021
• Study Completion (Actual): November 15, 2021

Study Registration Dates

• First Submitted: November 15, 2021
• First Submitted That Met QC Criteria: December 17, 2021
• First Posted (Actual): January 6, 2022

Study Record Updates

• Last Update Posted (Actual): January 6, 2022
• Last Update Submitted That Met QC Criteria: December 17, 2021
• Last Verified: December 1, 2021

More Information

Terms related to this study

• Keywords: Self-management; empowerment; Chronic disease; eHealth literacy; patient engagement; experience learning theory; eHealth care
• Additional Relevant MeSH Terms: Glucose Metabolism Disorders; Metabolic Diseases; Urologic Diseases; Endocrine System Diseases; Diabetes Mellitus; Renal Insufficiency; Cardiovascular Diseases; Diabetes Mellitus, Type 2; Kidney Diseases; Renal Insufficiency, Chronic
• Other Study ID Numbers: MOST-107-2314-B-010-014-MY3

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: No

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No