29,302 research outputs found

    Developing a Framework for Creating mHealth Surveys

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    Various issues in the design of surveys for mobile health (mHealth) research projects yet exist. As mHealth solutions become more popular, new issues are brought into consideration. Researchers need to collect some critical information from participants in these mHealth studies. These mHealth studies require a specialized framework to create surveys, track progress and analyze user data. In these procedures, mHealth’s needs differ from other studies. Therefore, there has to be a new framework that satisfies needs of mHealth research studies. Although there are studies for creating efficient, robust and user-friendly surveys, there is no solution or study, which is specialized in mHealth area and solves specific problems of mHealth research studies. mHealth research studies sometimes require real-time access to user data. Reward systems may play a key role in their study. Most importantly, storing user information securely plays a key role in these studies. There is no such solution or study, which covers all these areas. In this thesis, we present guidelines for developing a framework for creating mHealth surveys. In doing this, we hope that we propose a solution for problems of creating and using of surveys in mHealth studies

    mHealth Series:mHealth project in Zhao County, rural China - Description of objectives, field site and methods

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    BACKGROUND: We set up a collaboration between researchers in China and the UK that aimed to explore the use of mHealth in China. This is the first paper in a series of papers on a large mHealth project part of this collaboration. This paper included the aims and objectives of the mHealth project, our field site, and the detailed methods of two studies. FIELD SITE: The field site for this mHealth project was Zhao County, which lies 280 km south of Beijing in Hebei Province, China. METHODS: We described the methodology of two studies: (i) a mixed methods study exploring factors influencing sample size calculations for mHealth–based health surveys and (ii) a cross–over study determining validity of an mHealth text messaging data collection tool. The first study used mixed methods, both quantitative and qualitative, including: (i) two surveys with caregivers of young children, (ii) interviews with caregivers, village doctors and participants of the cross–over study, and (iii) researchers’ views. We combined data from caregivers, village doctors and researchers to provide an in–depth understanding of factors influencing sample size calculations for mHealth–based health surveys. The second study, a cross–over study, used a randomised cross–over study design to compare the traditional face–to–face survey method to the new text messaging survey method. We assessed data equivalence (intrarater agreement), the amount of information in responses, reasons for giving different responses, the response rate, characteristics of non–responders, and the error rate. CONCLUSIONS: This paper described the objectives, field site and methods of a large mHealth project part of a collaboration between researchers in China and the UK. The mixed methods study evaluating factors that influence sample size calculations could help future studies with estimating reliable sample sizes. The cross–over study comparing face–to–face and text message survey data collection could help future studies with developing their mHealth tools

    Can mHealth Improve Risk Assessment in Underserved Populations? Acceptability of a Breast Health Questionnaire App in Ethnically Diverse, Older, Low-Income Women.

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    Background: Use of mobile health (mHealth) tools has expanded rapidly but little research has been done on its acceptability by low-income, diverse, older patient populations. Objective: To assess the attitudes of a diverse group of underserved women on the acceptability and usability of mHealth tools in a clinical setting using a breast health questionnaire application (app) at a public hospital mammography clinic. Methods: Semi-structured interviews were conducted in a breast-imaging center of an urban safety net institution from July-August 2012. Interviews included pre- and post-questions. Women completed the Athena breast health questionnaire app on an iPad and were asked about their experience and ways to improve the tool. Results: Fifteen women age 45-75 years from diverse ethnic and educational backgrounds were interviewed. The majority of women, 11 of 15, preferred the Athena app over a paper version and all the women thought the app was easy to use. Two Spanish-speaking Latinas preferred paper; and two women, with limited mobile phone use, did not have a preference. Many women indicated that it would be necessary to have staff available for instruction and assistance if the app were to be implemented. Conclusions: mHealth tools are an acceptable, if not preferred, method of collecting health information for diverse, older, low-income women. Further studies are required to evaluate the reliability and accuracy of data collection using mHealth tools in underserved populations. mHealth tools should be explored as a novel way to engage diverse populations to improve clinical care and bridge gaps in health disparities

    Game On? Smoking Cessation Through the Gamification of mHealth: A Longitudinal Qualitative Study

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    BACKGROUND: Finding ways to increase and sustain engagement with mHealth interventions has become a challenge during application development. While gamification shows promise and has proven effective in many fields, critical questions remain concerning how to use gamification to modify health behavior. OBJECTIVE: The objective of this study is to investigate how the gamification of mHealth interventions leads to a change in health behavior, specifically with respect to smoking cessation. METHODS: We conducted a qualitative longitudinal study using a sample of 16 smokers divided into 2 cohorts (one used a gamified intervention and the other used a nongamified intervention). Each participant underwent 4 semistructured interviews over a period of 5 weeks. Semistructured interviews were also conducted with 4 experts in gamification, mHealth, and smoking cessation. Interviews were transcribed verbatim and thematic analysis undertaken. RESULTS: Results indicated perceived behavioral control and intrinsic motivation acted as positive drivers to game engagement and consequently positive health behavior. Importantly, external social influences exerted a negative effect. We identified 3 critical factors, whose presence was necessary for game engagement: purpose (explicit purpose known by the user), user alignment (congruency of game and user objectives), and functional utility (a well-designed game). We summarize these findings in a framework to guide the future development of gamified mHealth interventions. CONCLUSIONS: Gamification holds the potential for a low-cost, highly effective mHealth solution that may replace or supplement the behavioral support component found in current smoking cessation programs. The framework reported here has been built on evidence specific to smoking cessation, however it can be adapted to health interventions in other disease categories. Future research is required to evaluate the generalizability and effectiveness of the framework, directly against current behavioral support therapy interventions in smoking cessation and beyond

    A technology acceptance analysis for mhealth apps: the case of Turkey

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    The acceptance of mHealth (mobile health) apps has been on the increase throughout the world as well as in Turkey. There are two main indicators of mHealth success and acceptance, such as mHealth apps users’ satisfaction level and intention to use mHealth apps. In this context, the factors, including ease of use, trust, privacy, usefulness, and information quality are critical to analyze how they affect the acceptance of the mHealth apps by the Turkish users, and their satisfaction level with mHealth apps. Thus, the main objectives of this study are to (1) to explain how users perceive and use mHealth apps with technology acceptance analysis, (2) investigate whether the usefulness or uselessness of mHealth apps depends on user feelings about mHealth apps, (3) analyze the impacts of ease of use, trust, privacy, usefulness and information quality on mHealth users’ satisfaction and intention, and (4) identify users’ attitudes towards mHealth apps and their satisfaction level with mHealth apps in Turkey. A total of 282 participants from Turkey completed a survey analyzing the ease of use, trust, privacy, usefulness and information quality of mHealth apps to specify the reasons for mHealth acceptance. Statistical techniques were employed for data analysis. This study provides some managerial implications and scholarly recommendations to increase the acceptance of mHealth apps as well as helping mHealth apps designers to recognize the factors that influence the intention to adopt mHealth

    Identifying Medication Management Smartphone App Features Suitable for Young Adults With Developmental Disabilities: Delphi Consensus Study

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    Background: Smartphone apps can be a tool to facilitate independent medication management among persons with developmental disabilities. At present, multiple medication management apps exist in the market, but only 1 has been specifically designed for persons with developmental disabilities. Before initiating further app development targeting this population, input from stakeholders including persons with developmental disabilities, caregivers, and professionals regarding the most preferred features should be obtained. Objective: The aim of this study was to identify medication management app features that are suitable to promote independence in the medication management process by young adults with developmental disabilities using a Delphi consensus method. Methods: A compilation of medication management app features was performed by searching the iTunes App Store, United States, in February 2016, using the following terms: adherence, medication, medication management, medication list, and medication reminder. After identifying features within the retrieved apps, a final list of 42 features grouped into 4 modules (medication list, medication reminder, medication administration record, and additional features) was included in a questionnaire for expert consensus rating. A total of 52 experts in developmental disabilities, including persons with developmental disabilities, caregivers, and professionals, were invited to participate in a 3-round Delphi technique. The purpose was to obtain consensus on features that are preferred and suitable to promote independence in the medication management process among persons with developmental disabilities. Consensus for the first, second, and third rounds was defined as ≄90%, ≄80%, and ≄75% agreement, respectively. Results: A total of 75 responses were received over the 3 Delphi rounds—30 in the first round, 24 in the second round, and 21 in the third round. At the end of the third round, cumulative consensus was achieved for 60% (12/20) items in the medication list module, 100% (3/3) in the medication reminder module, 67% (2/3) in the medication administration record module, and 63% (10/16) in the additional features module. In addition to the medication list, medication reminder, and medication administration record features, experts selected the following top 3 most important additional features: automatic refills through pharmacies; ability to share medication information from the app with providers; and ability to share medication information from the app with family, friends, and caregivers. The top 3 least important features included a link to an official drug information source, privacy settings and password protection, and prescription refill reminders. Conclusions: Although several mobile apps for medication management exist, few are specifically designed to support persons with developmental disabilities in the complex medication management process. Of the 42 different features assessed, 64% (27/42) achieved consensus for inclusion in a future medication management app. This study provides information on the features of a medication management app that are most important to persons with developmental disabilities, caregivers, and professionals

    Using mHealth to improve health care delivery in India: A qualitative examination of the perspectives of community health workers and beneficiaries.

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    BACKGROUND:mHealth technologies are proliferating globally to address quality and timeliness of health care delivery by Community Health Workers (CHWs). This study aimed to examine CHW and beneficiaries' perceptions of a new mHealth intervention (Common Application Software [CAS] for CHWs in India. The objectives of the study were to seek perspectives of CHWs and beneficiaries on the uptake of CAS, changes in CHW-beneficiary interactions since the introduction of CAS and potential barriers faced by CHWs in use of CAS. Further, important contextual factors related to CHW-beneficiary interface and dynamics that may have a bearing on CAS have been described. METHODS:A qualitative study was conducted in two states of India (Bihar and Madhya Pradesh) from March-April 2018 with CHWs (n = 32) and beneficiaries (n = 55). All interviews were conducted and recorded in Hindi, transcribed and translated into English, and coded and thematically analysed using Dedoose. FINDINGS:The mHealth intervention was acceptable to the CHWs who felt that CAS improved their status in the communities where they worked. Beneficiaries' views were a mix of positive and negative perceptions. The divergent views between CHWs and beneficiaries surrounding the use and impact of CAS highlight an underlying mistrust, socio-cultural barriers in engagement, and technological barriers in implementation. All these contextual factors can influence the perception and uptake of CAS. CONCLUSIONS:mHealth interventions targeting CHWs and beneficiaries have the potential to improve performance of CHWs, reduce barriers to information and potentially change the behaviors of beneficiaries. While technology is an enabler for CHWs to improve their service delivery, it does not necessarily help overcome social and cultural barriers that impede CHW-beneficiary interactions to bring about improvements in knowledge and health behaviors. Future interventions for CHWs including mHealth interventions should examine contextual factors along with the acceptability, accessibility, and usability by beneficiaries and community members
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