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Effect of a Tailored eHealth Physical Activity Intervention on Physical Activity and Depression During Postpartum: Randomized Controlled Trial (The Postpartum Wellness Study)

Effect of a Tailored eHealth Physical Activity Intervention on Physical Activity and Depression During Postpartum: Randomized Controlled Trial (The Postpartum Wellness Study)

In contrast, most previous PA interventions for postpartum individuals have relied on in-person supervised exercise sessions alone or in combination with individual health coaching [13,29,30]. The objective of this study, the POstpartum Wellness study (POW), was to test the effectiveness of an e Health PA intervention (Mom Zing) for increasing PA and decreasing depressive symptoms in individuals at high risk for PPD.

Sylvia E Badon, Nina Oberman, Maya Ramsey, Charles P Quesenberry, Elaine Kurtovich, Lizeth Gomez Chavez, Susan D Brown, Cheryl L Albright, Mibhali Bhalala, Lyndsay A Avalos

JMIR Ment Health 2025;12:e64507

A Rent Subsidy and Identity Capital Intervention for Youth Exiting Homelessness: Protocol for the Transitioning Youth Out of Homelessness 2.0 Pilot Randomized Controlled Trial

A Rent Subsidy and Identity Capital Intervention for Youth Exiting Homelessness: Protocol for the Transitioning Youth Out of Homelessness 2.0 Pilot Randomized Controlled Trial

Participants unable to attend in-person focus groups were offered the option of virtual attendance. All focus groups were audio recorded using a password-protected device. Audio recordings were transcribed verbatim by a member of the research team, and the transcripts were uploaded to the web-based application Dedoose [37] for storage and retrieval.

Naomi S Thulien, Rowen K Stark, Alexandra Amiri, Alex Abramovich, Alex Akdikmen, Alexandra Carasco, Mardi Daley, Bernice Downey, Oluwapelumi (Pukky) Fambegbe, Tyler Frederick, Stephen W Hwang, Nicole Kozloff, Amanda Noble, Cheryl Pedersen, Marsha Rampersaud, Ruth Rodney, Tadios Tibebu, Rosane Nisenbaum

JMIR Res Protoc 2025;14:e66210

Testing a Machine Learning–Based Adaptive Motivational System for Socioeconomically Disadvantaged Smokers (Adapt2Quit): Protocol for a Randomized Controlled Trial

Testing a Machine Learning–Based Adaptive Motivational System for Socioeconomically Disadvantaged Smokers (Adapt2Quit): Protocol for a Randomized Controlled Trial

Using the Co Vita Smokerlyzer breath CO monitor, participants who self-report quitting at the 6-month follow-up will be asked to complete biochemical verification remotely (the device will be mailed to them) or in person. Because of the variability of the device, participants will be asked to repeat the test 3 times. The average of these values will be used for our analyses [39]. Participants will be classified as tobacco users if their CO measurement is >6 ppm [40].

Ariana Kamberi, Benjamin Weitz, Julie Flahive, Julianna Eve, Reem Najjar, Tara Liaghat, Daniel Ford, Peter Lindenauer, Sharina Person, Thomas K Houston, Megan E Gauvey-Kern, Jackie Lobien, Rajani S Sadasivam

JMIR Res Protoc 2025;14:e63693

Clinicians’ Perceptions and Potential Applications of Robotics for Task Automation in Critical Care: Qualitative Study

Clinicians’ Perceptions and Potential Applications of Robotics for Task Automation in Critical Care: Qualitative Study

Six clinicians made statements such as patients in ICU are “already prone to feeling isolation ... feeling like there wasn’t a person in there with them enough.” Would patients miss the human touch or feel “less than” with a robot caregiver? What impact would this have on patients and clinicians?

Jiafeng Song, Rishika Iytha Sridhar, Darlene Marie Rogers, Cheryl Hiddleson, Carolyn Davis, Tina Lynn Holden, Shanna Ramsey-Haynes, Lisa Reif, Julie Swann, Craig S Jabaley, Mary Gullatte, Rishikesan Kamaleswaran

J Med Internet Res 2025;27:e62957

Beyond Hemoglobin A1c—Outcomes That Matter to Individuals With Type 1 Diabetes in Adopting Digital Health Interventions for Self-Management Support: Qualitative Study

Beyond Hemoglobin A1c—Outcomes That Matter to Individuals With Type 1 Diabetes in Adopting Digital Health Interventions for Self-Management Support: Qualitative Study

To address this question, we facilitated open-ended dialogue with participants in the context of both in-person and virtual focus groups. These focus group discussions were moderated using a focus group guide (Multimedia Appendix 1) that helped participants converse openly about their lived experiences of T1 D self-management, as well as their unique education and support needs, including their perspectives on using virtual care.

Benjamin Markowitz, Stephanie de Sequeira, Adhiyat Najam, Cheryl Pritlove, Dana Greenberg, Marley Greenberg, Chee-Mei Chan, Gurpreet Lakhanpal, Samyukta Jagadeesh, Geetha Mukerji, Rayzel Shulman, Holly O Witteman, Catherine H Yu, Gillian L Booth, Janet A Parsons, The T1ME Patient Advisory Committee

JMIR Diabetes 2024;9:e60190