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Background: Use of mobile health applications to enable both clinical research and healthcare provision is promising and rapidly developing, however research on users' perceptions and acceptability of such apps is limited. The Mom2B smartphone app was developed to enable the collection of objective, moment-by-moment behavioral data from smartphone sensors, in addition to survey and voice recording data, with the aim of predicting depressive symptoms in the perinatal period.Objective: To explore the experiences and attitudes of Mom2B app users, particularly their acceptability of the app and concerns around providing data through a mobile application.Methods: Semi-structured focus group interviews were conducted online in Swedish with 14 groups, and a total of 41 participants. Participants had been active users of the Mom2B app for at least six weeks, and included pregnant and postpartum women, both with and without depression symptomatology apparent in their last screening test. Interviews were recorded, transcribed verbatim, translated to English, and evaluated using inductive thematic analysis.Results: Four themes were elicited: acceptability of sharing data, motivators and incentives, barriers to task completion, and user experience. Participants also gave suggestions for the improvement of features and user experience. Overall, app-based digital phenotyping was evaluated as a feasible and acceptable method of conducting research that also allows participants to benefit from the data they share by being able to monitor their wellbeing. Conclusions:The findings highlight the perceived duplexity of this app as an efficient and practical tool that facilitates engagement in research, as well as allows users to monitor their wellbeing and get both general and personalized information related to the perinatal period. Digital phenotyping apps should be trustworthy and accessible, and technical issues should be promptly addressed. The findings raise important considerations for the development of future mHealth research apps in cooperation with users.
Background: Use of mobile health applications to enable both clinical research and healthcare provision is promising and rapidly developing, however research on users' perceptions and acceptability of such apps is limited. The Mom2B smartphone app was developed to enable the collection of objective, moment-by-moment behavioral data from smartphone sensors, in addition to survey and voice recording data, with the aim of predicting depressive symptoms in the perinatal period.Objective: To explore the experiences and attitudes of Mom2B app users, particularly their acceptability of the app and concerns around providing data through a mobile application.Methods: Semi-structured focus group interviews were conducted online in Swedish with 14 groups, and a total of 41 participants. Participants had been active users of the Mom2B app for at least six weeks, and included pregnant and postpartum women, both with and without depression symptomatology apparent in their last screening test. Interviews were recorded, transcribed verbatim, translated to English, and evaluated using inductive thematic analysis.Results: Four themes were elicited: acceptability of sharing data, motivators and incentives, barriers to task completion, and user experience. Participants also gave suggestions for the improvement of features and user experience. Overall, app-based digital phenotyping was evaluated as a feasible and acceptable method of conducting research that also allows participants to benefit from the data they share by being able to monitor their wellbeing. Conclusions:The findings highlight the perceived duplexity of this app as an efficient and practical tool that facilitates engagement in research, as well as allows users to monitor their wellbeing and get both general and personalized information related to the perinatal period. Digital phenotyping apps should be trustworthy and accessible, and technical issues should be promptly addressed. The findings raise important considerations for the development of future mHealth research apps in cooperation with users.
BACKGROUND Although many people are supportive of their deidentified health care data being used for research, concerns about privacy, safety, and security of health care data remain. There is low awareness about how data are used for research and related governance. Transparency about how health data are used for research is crucial for building public trust. One proposed solution is to ensure that affected communities are notified, particularly marginalized communities where there has previously been a lack of engagement and mistrust. OBJECTIVE This study aims to explore patient and public perspectives on the use of deidentified data from electronic health records for musculoskeletal research and to explore ways to build and sustain public trust in health data sharing for a research program (known as “the Data Jigsaw”) piloting new ways of using and analyzing electronic health data. Views and perspectives about how best to engage with local communities informed the development of a public notification campaign about the research. METHODS Qualitative methods data were generated from 20 semistructured interviews and 8 focus groups, comprising 48 participants in total with musculoskeletal conditions or symptoms, including 3 carers. A presentation about the use of health data for research and examples from the specific research projects within the program were used to trigger discussion. We worked in partnership with a patient and public involvement group throughout the research and cofacilitated wider community engagement. RESULTS Respondents were supportive of their health care data being shared for research purposes, but there was low awareness about how electronic health records are used for research. Security and governance concerns about data sharing were noted, including collaborations with external companies and accessing social care records. Project examples from the Data Jigsaw program were viewed positively after respondents knew more about how their data were being used to improve patient care. A range of different methods to build and sustain trust were deemed necessary by participants. Information was requested about: data management; individuals with access to the data (including any collaboration with external companies); the National Health Service’s national data opt-out; and research outcomes. It was considered important to enable in-person dialogue with affected communities in addition to other forms of information. CONCLUSIONS The findings have emphasized the need for transparency and awareness about health data sharing for research, and the value of tailoring this to reflect current and local research where residents might feel more invested in the focus of research and the use of local records. Thus, the provision for targeted information within affected communities with accessible messages and community-based dialogue could help to build and sustain public trust. These findings can also be extrapolated to other conditions beyond musculoskeletal conditions, making the findings relevant to a much wider community.
BACKGROUND Use of mobile health applications to enable both clinical research and healthcare provision is promising and rapidly developing, however research on users’ perceptions and acceptability of such apps is limited. The Mom2B smartphone app was developed to enable the collection of objective, moment-by-moment behavioral data from smartphone sensors, in addition to survey and voice recording data, with the aim of predicting depressive symptoms in the perinatal period. OBJECTIVE To explore the experiences and attitudes of Mom2B app users, particularly their acceptability of the app and concerns around providing data through a mobile application. METHODS Semi-structured focus group interviews were conducted online in Swedish with 14 groups, and a total of 41 participants. Participants had been active users of the Mom2B app for at least six weeks, and included pregnant and postpartum women, both with and without depression symptomatology apparent in their last screening test. Interviews were recorded, transcribed verbatim, translated to English, and evaluated using inductive thematic analysis. RESULTS Four themes were elicited: acceptability of sharing data, motivators and incentives, barriers to task completion, and user experience. Participants also gave suggestions for the improvement of features and user experience. Overall, app-based digital phenotyping was evaluated as a feasible and acceptable method of conducting research that also allows participants to benefit from the data they share by being able to monitor their wellbeing. CONCLUSIONS The findings highlight the perceived duplexity of this app as an efficient and practical tool that facilitates engagement in research, as well as allows users to monitor their wellbeing and get both general and personalized information related to the perinatal period. Digital phenotyping apps should be trustworthy and accessible, and technical issues should be promptly addressed. The findings raise important considerations for the development of future mHealth research apps in cooperation with users.
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