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Thematic analysis was performed on the cleaned dataset (n=31,319) to further examine the search trends and volume on predetermined stages of the treatment pathway, that is, symptoms → testing → diagnosis → treatment.
Discussions about COVID-19 symptoms were prevalent, with 49% of posts mentioning general symptoms, with 17% specifically referring to “COVID-19 symptoms.” Frequently mentioned symptoms included cough, fever, fatigue, pain, anxiety, breathing difficulties, and respiratory issues [24].
JMIR Form Res 2025;9:e63997
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Our targeted sample size (N≥866) is powered to detect small effects (d=0.2 approximately) between active dose conditions. The program length is 28 days, which will allow us to test for changes in more stable “trait” effects. There is considerable variation in doses for daily sessions, ranging from 10 to 30 minutes. These doses are based on a nonsystematic search of the literature, MBPs, and mindfulness apps with dosage recommendations (for details, refer to the study by Bowles et al [11]).
JMIR Res Protoc 2025;14:e72786
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Public Involvement in Cancer Research: Collaborative Evaluation Using Photovoice
In July, the research team recruited 4 public contributors with lived experience of breast (n=2), prostate (n=1), or another form of cancer (n=1) to the public involvement group. One of them was previously involved in research as a public contributor. None of the public contributors knew each other or the researchers before their involvement. The public contributors were not representative of the general population but rather emphasized the diversity of experiences [17].
JMIR Cancer 2025;11:e75741
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Interviews with health care stakeholders and AI governance experts (stage 2) are complete (n=43), and the thematic analysis has commenced. Case study selection for framework testing has been finalized in consultation with the study site. The final AI governance framework is anticipated to be finalized and disseminated by June 2025.
This study will generate critical insights into AI governance by developing and validating a framework for the safe and responsible integration of AI in health care.
JMIR Res Protoc 2025;14:e75702
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A total of 255 respondents recruited by SMIs took the baseline survey: 82.4% (n=210) of the respondents identified as women, and 68.2% (n=174) identified as Black (Table 2). In total, 64.3% (n=164) of the respondents identified as Black women, confirming our ability to reach our target audience. The respondents had a high level of formal education, with 69.0% (n=176) having a bachelor’s degree or higher. A total of 101 respondents took the follow-up survey.
J Med Internet Res 2025;27:e66128
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Demographic and military characteristics of women veterans with military environmental exposures, 2022-2024.a
a Includes self-identified demographic and military characteristics.
b Missing (n=7).
c Missing (n=4).
d Other marital status includes living with a partner, separated.
e Missing (n=9).
f Missing (n=14).
g Other combat deployments non-Gulf War I and post-9/11 deployments such as Bosnia, with some participants serving across multiple eras.
h Missing (n=12).
i Missing (n=16).
j WRIISC: War Related Illness and Injury
JMIR Form Res 2025;9:e73223
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