The Effect of Remote Digital Services on Health Care Inequalities Among People Under Long-Term Dermatology Follow-Up: Cross-Sectional Questionnaire Study

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Background

Given the expansion of remote digital dermatology services from the National Health Service, particularly during the COVID-19 pandemic, there is a need for methods that identify patients at risk of digital exclusion to guide equitable representation in service co-design processes and tailor remote services to the needs of their patient population.

Objective

This quality improvement project aims to inform the redesign of remote services to optimally support the ongoing needs of patients with chronic skin diseases, ensuring that the services are tailored to patients’ digital health literacy requirements.

Methods

We profiled the digital health literacy of 123 people with chronic skin conditions who require long-term surveillance in 2 specialist clinics (London, United Kingdom) using the Multidimensional Readiness and Enablement Index for Health Technology (READHY) questionnaire alongside the Optimizing Health Literacy and Access (Ophelia) process for hierarchical cluster analysis.

Results

The cluster analysis of READHY dimensions in responding participants (n=116) revealed 7 groups with distinct digital and health literacy characteristics. High READHY scores in groups 1 (n=22, 19%) and 2 (n=20, 17.2%) represent those who are confident with managing their health and using technology, whereas the lower-scoring groups, 6 (n=4, 3.4%) and 7 (n=12, 10.3%), depended on traditional services. Groups 3 (n=27, 23.3%), 4 (n=23, 19.8%), and 5 (n=8, 6.9%) had varying digital skills, access, and engagement, highlighting a population that may benefit from a co-designed dermatology service.

Conclusions

By identifying patient groups with distinguishable patterns of digital access and health literacy, our method demonstrates that 63.8% (n=74) of people attending specialist clinics in our center require support in order to optimize remote follow-up or need an alternative approach. Future efforts should streamline the READHY question profile to improve its practicality and use focus groups to elicit strategies for engaging patients with digital services.

Related collections

Most cited references 14

Record: found
Abstract: found
Article: found

Is Open Access

The grounded psychometric development and initial validation of the Health Literacy Questionnaire (HLQ)

Richard Osborne, Roy Batterham, Gerald Elsworth … (2013)

Background Health literacy has become an increasingly important concept in public health. We sought to develop a comprehensive measure of health literacy capable of diagnosing health literacy needs across individuals and organisations by utilizing perspectives from the general population, patients, practitioners and policymakers. Methods Using a validity-driven approach we undertook grounded consultations (workshops and interviews) to identify broad conceptually distinct domains. Questionnaire items were developed directly from the consultation data following a strict process aiming to capture the full range of experiences of people currently engaged in healthcare through to people in the general population. Psychometric analyses included confirmatory factor analysis (CFA) and item response theory. Cognitive interviews were used to ensure questions were understood as intended. Items were initially tested in a calibration sample from community health, home care and hospital settings (N=634) and then in a replication sample (N=405) comprising recent emergency department attendees. Results Initially 91 items were generated across 6 scales with agree/disagree response options and 5 scales with difficulty in undertaking tasks response options. Cognitive testing revealed that most items were well understood and only some minor re-wording was required. Psychometric testing of the calibration sample identified 34 poorly performing or conceptually redundant items and they were removed resulting in 10 scales. These were then tested in a replication sample and refined to yield 9 final scales comprising 44 items. A 9-factor CFA model was fitted to these items with no cross-loadings or correlated residuals allowed. Given the very restricted nature of the model, the fit was quite satisfactory: χ 2 WLSMV(866 d.f.) = 2927, p<0.000, CFI = 0.936, TLI = 0.930, RMSEA = 0.076, and WRMR = 1.698. Final scales included: Feeling understood and supported by healthcare providers; Having sufficient information to manage my health; Actively managing my health; Social support for health; Appraisal of health information; Ability to actively engage with healthcare providers; Navigating the healthcare system; Ability to find good health information; and Understand health information well enough to know what to do. Conclusions The HLQ covers 9 conceptually distinct areas of health literacy to assess the needs and challenges of a wide range of people and organisations. Given the validity-driven approach, the HLQ is likely to be useful in surveys, intervention evaluation, and studies of the needs and capabilities of individuals.

0 comments Cited 348 times – based on 0 reviews      Review now

Record: found
Abstract: found
Article: not found

The Health Education Impact Questionnaire (heiQ): an outcomes and evaluation measure for patient education and self-management interventions for people with chronic conditions.

Kathryn Whitfield, Richard Osborne, Gerald Elsworth (2007)

This paper describes the development and validation of the Health Education Impact Questionnaire (heiQ). The aim was to develop a user-friendly, relevant, and psychometrically sound instrument for the comprehensive evaluation of patient education programs, which can be applied across a broad range of chronic conditions. Item development for the heiQ was guided by a Program Logic Model, Concept Mapping, interviews with stakeholders and psychometric analyses. Construction (N=591) and confirmatory (N=598) samples were drawn from consumers of patient education programs and hospital outpatients. The properties of the heiQ were investigated using item response theory and structural equation modeling. Over 90 candidate items were generated, with 42 items selected for inclusion in the final scale. Eight independent dimensions were derived: Positive and Active Engagement in Life (five items, Cronbach's alpha (alpha)=0.86); Health Directed Behavior (four items, alpha=0.80); Skill and Technique Acquisition (five items, alpha=0.81); Constructive Attitudes and Approaches (five items, alpha=0.81); Self-Monitoring and Insight (seven items, alpha=0.70); Health Service Navigation (five items, alpha=0.82); Social Integration and Support (five items, alpha=0.86); and Emotional Wellbeing (six items, alpha=0.89). The heiQ has high construct validity and is a reliable measure of a broad range of patient education program benefits. The heiQ will provide valuable information to clinicians, researchers, policymakers and other stakeholders about the value of patient education programs in chronic disease management.

0 comments Cited 94 times – based on 0 reviews      Review now

Record: found
Abstract: found
Article: found

Is Open Access

Development of the Multidimensional Readiness and Enablement Index for Health Technology (READHY) Tool to Measure Individuals’ Health Technology Readiness: Initial Testing in a Cancer Rehabilitation Setting

Lars Kayser, Sine Rossen, Astrid Karnoe … (2019)

Background The increasing digitization of health care services with enhanced access to fast internet connections, along with wide use of smartphones, offers the opportunity to get health advice or treatment remotely. For service providers, it is important to consider how consumers can take full advantage of available services and how this can create an enabling environment. However, it is important to consider the digital context and the attributes of current and future users, such as their readiness (ie, knowledge, skills, and attitudes, including trust and motivation). Objective The objective of this study was to evaluate how the eHealth Literacy Questionnaire (eHLQ) combined with selected dimensions from the Health Education Impact Questionnaire (heiQ) and the Health Literacy Questionnaire (HLQ) can be used together as an instrument to characterize an individual’s level of health technology readiness and explore how the generated data can be used to create health technology readiness profiles of potential users of health technologies and digital health services. Methods We administered the instrument and sociodemographic questions to a population of 305 patients with a recent cancer diagnosis referred to rehabilitation in a setting that plans to introduce various technologies to assist the individuals. We evaluated properties of the Readiness and Enablement Index for Health Technology (READHY) instrument using confirmatory factor analysis, convergent and discriminant validity analysis, and exploratory factor analysis. To identify different health technology readiness profiles in the population, we further analyzed the data using hierarchical and k-means cluster analysis. Results The confirmatory factor analysis found a suitable fit for the 13 factors with only 1 cross-loading of 1 item between 2 dimensions. The convergent and discriminant validity analysis revealed many factor correlations, suggesting that, in this population, a more parsimonious model might be achieved. Exploratory factor analysis pointed to 5 to 6 constructs based on aggregates of the existing dimensions. The results were not satisfactory, so we performed an 8-factor confirmatory factor analysis, resulting in a good fit with only 1 item cross-loading between 2 dimensions. Cluster analysis showed that data from the READHY instrument can be clustered to create meaningful health technology readiness profiles of users. Conclusions The 13 dimensions from heiQ, HLQ, and eHLQ can be used in combination to describe a user’s health technology readiness level and degree of enablement. Further studies in other populations are needed to understand whether the associations between dimensions are consistent and the number of dimensions can be reduced.

0 comments Cited 30 times – based on 0 reviews      Review now

All references

Author and article information

Contributors

Serena Ramjee:

ORCID: https://orcid.org/0000-0003-4334-9918

Barts and the London School of Medicine and DentistryQueen Mary University LondonGarrod BuildingTurner StLondon, E1 2ADUnited Kingdom44 02078822239serena.ramjee1@nhs.net

Journal

Journal ID (nlm-ta): JMIR Dermatol

Journal ID (iso-abbrev): JMIR Dermatol

Journal ID (publisher-id): JDERM

Title: JMIR Dermatology

Publisher: JMIR Publications (Toronto, Canada )

ISSN (Electronic): 2562-0959

Publication date Collection: 2023

Publication date (Electronic): 8 December 2023

Volume: 6

Electronic Location Identifier: e48981

Affiliations

[1 ] Barts and the London School of Medicine and Dentistry Queen Mary University London London United Kingdom

[2 ] Dermatology Department Barts Health NHS Trust London United Kingdom

[3 ] Centre for Global Health and Equity, School of Health Sciences Swinburne University of Technology Hawthorn Australia

[4 ] Department of Public Health University of Copenhagen Copenhagen Denmark

Author notes

Corresponding Author: Serena Ramjee serena.ramjee1@ 123456nhs.net

Author information

Serena Ramjee https://orcid.org/0000-0003-4334-9918

Hanen Mohamedthani https://orcid.org/0009-0004-2755-1707

Aditya Umeshkumar Patel https://orcid.org/0000-0002-0896-7166

Rebeca Goiriz https://orcid.org/0009-0006-3548-5126

Catherine A Harwood https://orcid.org/0000-0002-1375-0965

Richard H Osborne https://orcid.org/0000-0002-9081-2699

Christina Cheng https://orcid.org/0000-0002-8950-7689

Zeeshaan-ul Hasan https://orcid.org/0000-0002-3391-2730

Article

Publisher ID: v6i1e48981

DOI: 10.2196/48981

PMC ID: 10746975

PubMed ID: 38064259

SO-VID: 300b3a50-e74b-49eb-a010-170816dfec15

Copyright © ©Serena Ramjee, Hanen Mohamedthani, Aditya Umeshkumar Patel, Rebeca Goiriz, Catherine A Harwood, Richard H Osborne, Christina Cheng, Zeeshaan-ul Hasan. Originally published in JMIR Dermatology (http://derma.jmir.org), 08.12.2023.

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Dermatology, is properly cited. The complete bibliographic information, a link to the original publication on http://derma.jmir.org, as well as this copyright and license information must be included.

History

Date received : 13 May 2023

Date revision requested : 8 August 2023

Date revision received : 13 October 2023

Date accepted : 7 November 2023

Submit your digital health research with an established publisher
- celebrating 25 years of open access