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      Assessing the Quality of the World Health Organization’s Skin NTDs App as a Training Tool in Ghana and Kenya: Protocol for a Cross-sectional Study


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          Neglected tropical diseases (NTDs) affect over 1.5 billion people worldwide, the majority of them belonging to impoverished populations in low- and middle-income countries (LMICs). Skin NTDs are a subgroup of NTDs that manifest primarily as skin lesions. The diagnosis and treatment of skin NTDs entail considerable resources, including trained personnel and financial backing. Many interventions are being launched and evaluated, particularly mobile health (mHealth) interventions, such as Skin NTDs App, a training and decision support tool offered by the World Health Organization (WHO) for frontline health workers (FHWs). As most digital health guidelines prioritize the thorough evaluation of mHealth interventions, it is essential to conduct a rigorous and validated assessment of Skin NTDs App.


          We aim to assess the quality of version 3 of Skin NTDs App, developed for the WHO by Universal Doctor and Netherlands Leprosy Relief as a training and decision support tool for FHWs.


          A cross-sectional study will be conducted in 2 LMICs: Ghana and Kenya. We will use snowball sampling recruitment to select 48 participants from the target population of all FHWs dealing with skin NTDs. The sample group of FHWs will be asked to download and use Skin NTDs App for at least 5 days before answering a web-based survey containing demographic variables and the user Mobile App Rating Scale (uMARS) questionnaire. A semistructured interview will then be conducted. Quantitative and qualitative data will be analyzed using SPSS (version 25; SPSS Inc), with statistical significance for all tests set at a 95% CI and P≤.05 considered significant. Data derived from the semistructured interviews will be clustered in themes and coded to enable analysis of various dimensions using ATLAS.ti.


          The estimated completion date of the study is in the third quarter of 2022. The results are expected to show that Skin NTDs App version 3 has a good reported user experience, as assessed using the uMARS scale. No differences are expected to be found, except for those related to experience in dermatology and the use of mobile technology that could influence the final score. Semistructured interviews are expected to complete the results obtained on the uMARS scale. Moreover, they will be the previous step before assessing other aspects of the app, such as its efficiency and how it should be disseminated or implemented.


          This study is the first step in a qualitative and quantitative assessment of Skin NTDs App as a training and support tool for FHWs diagnosing and managing skin NTDs. Our results will serve to improve future versions of the App.

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          Systematic methodological review: developing a framework for a qualitative semi-structured interview guide.

          To produce a framework for the development of a qualitative semi-structured interview guide.
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            Semistructured interviewing in primary care research: a balance of relationship and rigour

            Semistructured in-depth interviews are commonly used in qualitative research and are the most frequent qualitative data source in health services research. This method typically consists of a dialogue between researcher and participant, guided by a flexible interview protocol and supplemented by follow-up questions, probes and comments. The method allows the researcher to collect open-ended data, to explore participant thoughts, feelings and beliefs about a particular topic and to delve deeply into personal and sometimes sensitive issues. The purpose of this article was to identify and describe the essential skills to designing and conducting semistructured interviews in family medicine and primary care research settings. We reviewed the literature on semistructured interviewing to identify key skills and components for using this method in family medicine and primary care research settings. Overall, semistructured interviewing requires both a relational focus and practice in the skills of facilitation. Skills include: (1) determining the purpose and scope of the study; (2) identifying participants; (3) considering ethical issues; (4) planning logistical aspects; (5) developing the interview guide; (6) establishing trust and rapport; (7) conducting the interview; (8) memoing and reflection; (9) analysing the data; (10) demonstrating the trustworthiness of the research; and (11) presenting findings in a paper or report. Semistructured interviews provide an effective and feasible research method for family physicians to conduct in primary care research settings. Researchers using semistructured interviews for data collection should take on a relational focus and consider the skills of interviewing to ensure quality. Semistructured interviewing can be a powerful tool for family physicians, primary care providers and other health services researchers to use to understand the thoughts, beliefs and experiences of individuals. Despite the utility, semistructured interviews can be intimidating and challenging for researchers not familiar with qualitative approaches. In order to elucidate this method, we provide practical guidance for researchers, including novice researchers and those with few resources, to use semistructured interviewing as a data collection strategy. We provide recommendations for the essential steps to follow in order to best implement semistructured interviews in family medicine and primary care research settings.
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              Development and Validation of the User Version of the Mobile Application Rating Scale (uMARS)

              Background The Mobile Application Rating Scale (MARS) provides a reliable method to assess the quality of mobile health (mHealth) apps. However, training and expertise in mHealth and the relevant health field is required to administer it. Objective This study describes the development and reliability testing of an end-user version of the MARS (uMARS). Methods The MARS was simplified and piloted with 13 young people to create the uMARS. The internal consistency and test-retest reliability of the uMARS was then examined in a second sample of 164 young people participating in a randomized controlled trial of a mHealth app. App ratings were collected using the uMARS at 1-, 3,- and 6-month follow up. Results The uMARS had excellent internal consistency (alpha = .90), with high individual alphas for all subscales. The total score and subscales had good test-retest reliability over both 1-2 months and 3 months. Conclusions The uMARS is a simple tool that can be reliably used by end-users to assess the quality of mHealth apps.

                Author and article information

                JMIR Res Protoc
                JMIR Res Protoc
                JMIR Research Protocols
                JMIR Publications (Toronto, Canada )
                December 2022
                8 December 2022
                : 11
                : 12
                : e39393
                [1 ] School of Health Sciences Universitat de Girona Girona Spain
                [2 ] eHealth Lab Research Group eHealth Center & School of Health Sciences Universitat Oberta de Catalunya Barcelona Spain
                [3 ] Prevention, Treatment and Care Unit Department of Control of Neglected Tropical Diseases World Health Organization Geneve Switzerland
                [4 ] Consulting in Health Informatics Nairobi Kenya
                [5 ] Kumasi Center for Collaborative Research in Tropical Medicine Kumasi Ghana
                Author notes
                Corresponding Author: Carme Carrion mcarrionr@ 123456uoc.edu
                Author information
                ©Asmae Frej, Mireia Cano, José A Ruiz-Postigo, Paul Macharia, Richard Odame Phillips, Yaw Ampem Amoako, Carme Carrion. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 08.12.2022.

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

                : 9 May 2022
                : 10 July 2022
                : 28 July 2022
                : 2 November 2022

                skin ntds app,mhealth,mobile health,neglected tropical diseases,skin neglected tropical diseases,low- and middle-income countries


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