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      Patient Perspectives on a Targeted Text Messaging Campaign to Encourage Screening for Diabetes: Qualitative Study

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          Abstract

          Background

          A sizeable proportion of prediabetes and diabetes cases among adults in the United States remain undiagnosed. Patient-facing clinical decision support (CDS) tools that leverage electronic health records (EHRs) have the potential to increase diabetes screening. Given the widespread mobile phone ownership across diverse groups, text messages present a viable mode for delivering alerts directly to patients. The use of unsolicited text messages to offer hemoglobin A 1c (HbA 1c) screening has not yet been studied. It is imperative to gauge perceptions of “cold texts” to ensure that information and language are optimized to promote engagement with text messages that affect follow-through with health behaviors.

          Objective

          This study aims to gauge the perceptions of and receptiveness to text messages to inform content that would facilitate engagement with text messages intended to initiate a mobile health (mHealth) intervention for targeted screening. Messages were designed to invite those not already diagnosed with diabetes to make a decision to take part in HbA 1c screening and walk them through the steps required to perform the behavior based solely on an automated text exchange.

          Methods

          In total, 6 focus groups were conducted at Wake Forest Baptist Health (WFBH) between September 2019 and February 2020. The participants were adult patients without diabetes who had completed an in-person visit at the Family and Community Medicine Clinic within the previous year. We displayed a series of text messages and asked the participants to react to the message content and suggest improvements. Content was deductively coded with respect to the Health Belief Model (HBM) and inductively coded to identify other emergent themes that could potentially impact engagement with text messages.

          Results

          Participants (N=36) were generally receptive to the idea of receiving a text-based alert for HbA 1c screening. Plain language, personalization, and content, which highlighted perceived benefits over perceived susceptibility and perceived severity, were important to participants’ understanding of and receptiveness to messages. The patient-physician relationship emerged as a recurring theme in which patients either had a desire or held an assumption that their provider would be working behind the scenes throughout each step of the process. Participants needed further clarification to understand the steps involved in following through with HbA 1c screening and receiving results.

          Conclusions

          Our findings suggest that patients may be receptive to text messages that alert them to a risk of having an elevated HbA 1c in direct-to-patient alerts that use cold texting. Using plain and positive language, integrating elements of personalization, and defining new processes clearly were identified by participants as modifiable content elements that could act as facilitators that would help overcome barriers to engagement with these messages. A patient’s relationship with their provider and the financial costs associated with texts and screening may affect receptiveness and engagement in this process.

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          Most cited references35

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          Historical Origins of the Health Belief Model

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            Social Learning Theory and the Health Belief Model

            The Health Belief Model, social learning theory (recently relabelled social cognitive theory), self-efficacy, and locus of control have all been applied with varying success to problems of explaining, predicting, and influencing behavior. Yet, there is conceptual confusion among researchers and practitioners about the interrelationships of these theories and variables. This article attempts to show how these explanatory factors may be related, and in so doing, posits a revised explanatory model which incorporates self-efficacy into the Health Belief Model. Specifically, self-efficacy is proposed as a separate independent variable along with the traditional health belief variables of perceived susceptibility, severity, benefits, and barriers. Incentive to behave (health motivation) is also a component of the model. Locus of control is not included explicitly because it is believed to be incorporated within other elements of the model. It is predicted that the new formulation will more fully account for health-related behavior than did earlier formulations, and will suggest more effective behavioral interventions than have hitherto been available to health educators.
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              Evaluating barriers to adopting telemedicine worldwide: A systematic review

              Introduction and objective Studies on telemedicine have shown success in reducing the geographical and time obstacles incurred in the receipt of care in traditional modalities with the same or greater effectiveness; however, there are several barriers that need to be addressed in order for telemedicine technology to spread. The aim of this review is to evaluate barriers to adopting telemedicine worldwide through the analysis of published work. Methods The authors conducted a systematic literature review by extracting the data from the Cumulative Index of Nursing and Allied Health Literature (CINAHL) and PubMed (MEDLINE) research databases. The reviewers in this study analysed 30 articles (nine from CINAHL and 21 from Medline) and identified barriers found in the literature. This review followed the checklist from Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2009. The reviewers organized the results into one table and five figures that depict the data in different ways, organized by: barrier, country-specific barriers, organization-specific barriers, patient-specific barriers, and medical-staff and programmer-specific barriers. Results The reviewers identified 33 barriers with a frequency of 100 occurrences through the 30 articles. The study identified the issues with technically challenged staff (11%), followed by resistance to change (8%), cost (8%), reimbursement (5%), age of patient (5%), and level of education of patient (5%). All other barriers occurred at or less than 4% of the time. Discussion and conclusions Telemedicine is not yet ubiquitous, and barriers vary widely. The top barriers are technology-specific and could be overcome through training, change-management techniques, and alternating delivery by telemedicine and personal patient-to-provider interaction. The results of this study identify several barriers that could be eliminated by focused policy. Future work should evaluate policy to identify which one to lever to maximize the results.
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                Author and article information

                Contributors
                Journal
                JMIR Form Res
                JMIR Form Res
                JFR
                JMIR Formative Research
                JMIR Publications (Toronto, Canada )
                2561-326X
                2023
                17 January 2023
                : 7
                : e41011
                Affiliations
                [1 ] Department of Biostatistics and Data Science Public Health Sciences Wake Forest University School of Medicine Winston-Salem, NC United States
                [2 ] Department of Public Health Sciences University of North Carolina at Charlotte Charlotte, NC United States
                [3 ] Department of Family & Community Medicine Wake Forest University School of Medicine Winston-Salem, NC United States
                [4 ] Department of Internal Medicine Wake Forest University School of Medicine Winston-Salem, NC United States
                Author notes
                Corresponding Author: Kristin M Lenoir klenoir@ 123456wakehealth.edu
                Author information
                https://orcid.org/0000-0003-1834-7398
                https://orcid.org/0000-0001-6056-6186
                https://orcid.org/0000-0001-7879-4427
                https://orcid.org/0000-0001-7310-6525
                Article
                v7i1e41011
                10.2196/41011
                9890353
                36649056
                9760dc37-bb49-46a6-aaf8-0b64f8b93d77
                ©Kristin M Lenoir, Joanne C Sandberg, David P Miller, Brian J Wells. Originally published in JMIR Formative Research (https://formative.jmir.org), 17.01.2023.

                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 Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included.

                History
                : 11 August 2022
                : 2 September 2022
                : 4 November 2022
                : 21 November 2022
                Categories
                Original Paper
                Original Paper

                mobile health,diabetes screening,electronic health records,text messaging,clinical decision support,mhealth,diabetes,mhealth intervention

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