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Digital Health Interventions to Prevent Type 2 Diabetes Mellitus: Systematic Review
During the past 10 years, DHIs are being increasingly applied in T2 DM prevention, such as text messaging, web-based systems, telemedicine (TM), mobile health, software, wearables, and artificial intelligence (AI) [16,17]. A systematic review by Van Rhoon et al [18] in 2020 demonstrated that DHIs significantly reduce weight, enhance dysglycemia, and decrease T2 DM incidence.
J Med Internet Res 2025;27:e67507
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This was a noninterventional retrospective study using a text mining approach to retrieve information from social media posts (data available in the public domain) written by French speaking internet users between 2014 and 2020 (Figure 1).
JMIR Form Res 2025;9:e37160
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Initially set up by the charity Asthma UK (before it merged with the British Lung Foundation to become ALUK), the asynchronous text-based OHC has over 23,000 members and over 25,000 posts [21]. There are approximately 2000 active users per month; that is, not all users are active all the time.
J Med Internet Res 2025;27:e58167
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We also solicited feedback from participants using an open-text response format.
Sociodemographic information gathered from participants was summarized using descriptive statistics and analyzed with SPSS (version 28.0; IBM Corp). Qualitative descriptive data gathered from focus groups and interviews were audio-recorded, transcribed verbatim, and deidentified. Transcripts were subsequently analyzed using reflexive thematic analysis [33].
JMIR Cancer 2025;11:e57834
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After each block, a prompt message saying, “Please rest for a moment; press the space bar to continue” appears. In the 0=back task, participants are instructed to compare the current letter with “X” and press the F key if they are the same or the J key if they are different. In the 1=back task, starting from the second letter, participants are instructed to determine whether the current letter is the same as the previous letter, pressing the F key if they are the same or the J key if they are different.
JMIR Res Protoc 2025;14:e65958
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I think that people have grown tired of this message, especially since we’ve been discussing this for 40 years without making any progress.
In addition, few (3/37, 8%) DOLs noted potential challenges in dengue prevention related to the level of government involvement. While acknowledging the importance of government leadership in prevention efforts, they expressed hope for greater collaboration and proactive measures from governmental authorities to address the issue effectively.
J Med Internet Res 2025;27:e70997
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A Social Media Study of Portrayals of Bipolar Disorders on YouTube: Content and Thematic Analyses
Content analysis is “the systematic, objective, quantitative analysis of message characteristics” [32]. There are different forms of content analysis, for instance, whether the content analysis is performed manually or automatically; whether the categories are derived theoretically (top down) or empirically (bottom up) [33,34]. Additionally, emergent coding “is somewhere between a purely empirically derived model and a purely theoretical one” [33].
J Med Internet Res 2025;27:e67129
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Patient satisfaction data were collected throughout the project via a short questionnaire and free text options embedded into the end of the DART assessment (Multimedia Appendix 2). This was anonymized and exported into a spreadsheet for analysis. Using unstructured group and individual meetings, clinicians gave feedback on their experience of the new process to the lead researcher, which was collated and documented (Multimedia Appendix 3).
J Med Internet Res 2025;27:e67269
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One recent study using a 60-day text message intervention implemented in patients recently discharged after acute coronary syndrome had no significant effect on the CSE [42]. The researchers implemented an automated 1-way text message campaign through which patients received messages about self-management, healthy living, and follow-up care.
JMIR Form Res 2025;9:e60676
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Similarly, when asked by the research coordinator, 75% (24/32) of intervention arm participants self-reported they were unaware they had received an email or portal message asking them to complete the PATTERN medication adherence assessment, and therefore did not complete it. When probed for an explanation, most indicated they had accessed their email but did not notice the request (71%, 17/24).
JMIR Form Res 2025;9:e71676
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