Assessing Competencies Needed to Engage With Digital Health Services: Development of the eHealth Literacy Assessment Toolkit

Research output: Contribution to journalJournal articleResearchpeer-review

Standard

Assessing Competencies Needed to Engage With Digital Health Services : Development of the eHealth Literacy Assessment Toolkit. / Karnoe, Astrid; Furstrand, Dorthe; Christensen, Karl Bang; Nørgaard, Ole; Kayser, Lars.

In: Journal of Medical Internet Research, Vol. 20, No. 5, e178, 2018.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Karnoe, A, Furstrand, D, Christensen, KB, Nørgaard, O & Kayser, L 2018, 'Assessing Competencies Needed to Engage With Digital Health Services: Development of the eHealth Literacy Assessment Toolkit', Journal of Medical Internet Research, vol. 20, no. 5, e178. https://doi.org/10.2196/jmir.8347

APA

Karnoe, A., Furstrand, D., Christensen, K. B., Nørgaard, O., & Kayser, L. (2018). Assessing Competencies Needed to Engage With Digital Health Services: Development of the eHealth Literacy Assessment Toolkit. Journal of Medical Internet Research, 20(5), [e178]. https://doi.org/10.2196/jmir.8347

Vancouver

Karnoe A, Furstrand D, Christensen KB, Nørgaard O, Kayser L. Assessing Competencies Needed to Engage With Digital Health Services: Development of the eHealth Literacy Assessment Toolkit. Journal of Medical Internet Research. 2018;20(5). e178. https://doi.org/10.2196/jmir.8347

Author

Karnoe, Astrid ; Furstrand, Dorthe ; Christensen, Karl Bang ; Nørgaard, Ole ; Kayser, Lars. / Assessing Competencies Needed to Engage With Digital Health Services : Development of the eHealth Literacy Assessment Toolkit. In: Journal of Medical Internet Research. 2018 ; Vol. 20, No. 5.

Bibtex

@article{706beadc9e36413880c7be1d0f60990b,
title = "Assessing Competencies Needed to Engage With Digital Health Services: Development of the eHealth Literacy Assessment Toolkit",
abstract = "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.",
author = "Astrid Karnoe and Dorthe Furstrand and Christensen, {Karl Bang} and Ole N{\o}rgaard and Lars Kayser",
note = "{\circledC}Astrid Karnoe, Dorthe Furstrand, Karl Bang Christensen, Ole Norgaard, Lars Kayser. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 10.05.2018.",
year = "2018",
doi = "10.2196/jmir.8347",
language = "English",
volume = "20",
journal = "Journal of Medical Internet Research",
issn = "1439-4456",
publisher = "JMIR Publications",
number = "5",

}

RIS

TY - JOUR

T1 - Assessing Competencies Needed to Engage With Digital Health Services

T2 - Development of the eHealth Literacy Assessment Toolkit

AU - Karnoe, Astrid

AU - Furstrand, Dorthe

AU - Christensen, Karl Bang

AU - Nørgaard, Ole

AU - Kayser, Lars

N1 - ©Astrid Karnoe, Dorthe Furstrand, Karl Bang Christensen, Ole Norgaard, Lars Kayser. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 10.05.2018.

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

U2 - 10.2196/jmir.8347

DO - 10.2196/jmir.8347

M3 - Journal article

C2 - 29748163

VL - 20

JO - Journal of Medical Internet Research

JF - Journal of Medical Internet Research

SN - 1439-4456

IS - 5

M1 - e178

ER -

ID: 199062282