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Future Me, a Prospection-Based Chatbot to Promote Mental Well-Being in Youth: Two Exploratory User Experience Studies

Future Me, a Prospection-Based Chatbot to Promote Mental Well-Being in Youth: Two Exploratory User Experience Studies

The thematic framework used to code participant inputs was based on the COM-B model for behavior change [35], which identifies 3 key requirements needed for behavior change: capabilities (C), opportunities (O), and motivations (M). The transtheoretical model of behavior change was used to develop the framework for coding Future Me’s responses, which posits that behavior change occurs through stages: pre-contemplation, contemplation, preparation, action, maintenance, and termination [36].

Martin Dechant, Eva Lash, Sarah Shokr, Ciarán O'Driscoll

JMIR Form Res 2025;9:e74411

Bringing Executive Function Testing Online: Assessment Validation Study

Bringing Executive Function Testing Online: Assessment Validation Study

(B) Example of sequentially presented trials of the target and sample foils. Responses are correct if the participant selects “no” to all foil images within a limited response window. The adaptive dimension of the assessment was target frequency, with lower target frequencies increasing task difficulty. There are 7 possible target frequency levels: 40%, 35%, 30%, 25%, 20%, 15%, and 10%. All participants began the assessment at a target frequency of 30%.

Mouna Attarha, Ana Carolina de Figueiredo Pelegrino, Lydia Ouellet, Sarah-Jane Grant, Etienne de Villers-Sidani, Thomas Van Vleet

JMIR Form Res 2025;9:e75687

Authors’ Response to Peer Review of “Using Electrooculography and Electrodermal Activity During a Cold Pressor Test to Identify Physiological Biomarkers of State Anxiety: Feature-Based Algorithm Development and Validation Study”

Authors’ Response to Peer Review of “Using Electrooculography and Electrodermal Activity During a Cold Pressor Test to Identify Physiological Biomarkers of State Anxiety: Feature-Based Algorithm Development and Validation Study”

“Sixteen participants (N=16) between ages 26-31 took part in the study, and demographic information, including race and gender, was collected and is summarized in Table 2a-b. Each trial lasted about 10-15 minutes and was divided into three phases: baseline, CPT (Cold Pressor Test), and recovery. The length of the trial and the data used for feature analysis is as detailed in Table 2c-d.” The captions of the figures should have statistical information when relevant.

Jadelynn Dao, Ruixiao Liu, Sarah Solomon, Samuel Aaron Solomon

JMIRx Med 2025;6:e77440

Using Electrooculography and Electrodermal Activity During a Cold Pressor Test to Identify Physiological Biomarkers of State Anxiety: Feature-Based Algorithm Development and Validation Study

Using Electrooculography and Electrodermal Activity During a Cold Pressor Test to Identify Physiological Biomarkers of State Anxiety: Feature-Based Algorithm Development and Validation Study

B. Blink examples (blue) plotted against wire examples (green), as filtered EOG voltage signals, normalized per peak between 0 and 1. Peaks are time-aligned by time, in seconds, from the center of peak. Wire signals typically have higher variability. C. A singular blink peak. The purple dot marks the peak of the blink event, while the outer edges of the red and grey shaded sections represent the boundaries used for feature extraction.

Jadelynn Dao, Ruixiao Liu, Sarah Solomon, Samuel Aaron Solomon

JMIRx Med 2025;6:e69472

The Safety of Telerehabilitation: Systematic Review

The Safety of Telerehabilitation: Systematic Review

(B) Distribution of adverse event relatedness to the intervention across rehabilitation populations. Incidence of adverse events per 100 sessions across rehabilitation populations. Regarding the control groups, a total of 137 adverse events were recorded during 29,688 sessions (0.46 adverse events per 100 sessions). As with the intervention groups, information on the type, severity, and relatedness of adverse events was infrequently provided.

Hila Shnitzer, Josh Chan, Thomas Yau, McKyla McIntyre, Angie Andreoli, Ailene Kua, Mark Bayley, Carl Froilan Leochico, Meiqi Guo, Sarah Munce

JMIR Rehabil Assist Technol 2025;12:e68681