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Design, Application, and Actionability of US Public Health Data Dashboards: Scoping Review

Design, Application, and Actionability of US Public Health Data Dashboards: Scoping Review

Reference 123: R and D and innovation efforts during the COVID-19 pandemic: the role of universities

Gretchen Stahlman, Itzhak Yanovitzky, Miriam Kim

J Med Internet Res 2025;27:e65283

Linguistic Markers of Pain Communication on X (Formerly Twitter) in US States With High and Low Opioid Mortality: Machine Learning and Semantic Network Analysis

Linguistic Markers of Pain Communication on X (Formerly Twitter) in US States With High and Low Opioid Mortality: Machine Learning and Semantic Network Analysis

While we observed linguistic variations between HDS and LDS, the effect sizes were modest (Cohen d=0.04-0.19) [50]. Centering the study on states with the highest and lowest opioid-related death rates may inadvertently omit the multifaceted nature of chronic pain experiences throughout the United States. Aspects such as health care access, socioeconomic dynamics, and cultural nuances might influence chronic pain experiences and their linguistic expression across regions.

ShinYe Kim, Winson Fu Zun Yang, Zishan Jiwani, Emily Hamm, Shreya Singh

J Med Internet Res 2025;27:e67506

Combining Artificial Intelligence and Human Support in Mental Health: Digital Intervention With Comparable Effectiveness to Human-Delivered Care

Combining Artificial Intelligence and Human Support in Mental Health: Digital Intervention With Comparable Effectiveness to Human-Delivered Care

Clinical effectiveness was quantified by calculating the change in anxiety symptoms, measured using the GAD-7, from baseline to final score, and estimating a within-participant effect size (Cohen d). A negative mean change denotes a reduction in GAD-7 total scores. Absolute Cohen d values are presented. The threshold for a clinically meaningful reduction in symptoms was defined as a change greater than the reliable change index of the GAD-7 scale (minimum of a 4-point reduction) [54].

Clare E Palmer, Emily Marshall, Edward Millgate, Graham Warren, Michael Ewbank, Elisa Cooper, Samantha Lawes, Alastair Smith, Chris Hutchins-Joss, Jessica Young, Malika Bouazzaoui, Morad Margoum, Sandra Healey, Louise Marshall, Shaun Mehew, Ronan Cummins, Valentin Tablan, Ana Catarino, Andrew E Welchman, Andrew D Blackwell

J Med Internet Res 2025;27:e69351

Analyzing Usage of the Metaverse by Associations of Patients With Prostate Cancer During the 2023 Blue Ribbon Campaign: Cross-Sectional Survey Study

Analyzing Usage of the Metaverse by Associations of Patients With Prostate Cancer During the 2023 Blue Ribbon Campaign: Cross-Sectional Survey Study

Schematic overview of the metaverse associations of patients with prostate cancer, showing (A) the campaign introduction area, (B) the informational sector, (C) a live Q&A session, and (D) a segment of an educational session. Q&A: question and answer. Distribution and collection of the questionnaire for this study were managed by Enzaim Health, a health care marketing communications company.

Jung Ki Jo, Yeeun Kim, Yun-Sok Ha, Kwang Taek Kim, Sangjun Yoo, Woo Suk Choi, Jihye Yang, Jaeeun Shin, Sun Il Kim, Jeong Hyun Kim

J Med Internet Res 2025;27:e63030

Enhancing Access to Neuraxial Ultrasound Phantoms for Medical Education of Pediatric Anesthesia Trainees: Tutorial

Enhancing Access to Neuraxial Ultrasound Phantoms for Medical Education of Pediatric Anesthesia Trainees: Tutorial

Stages of phantom production, with A to C showing steps 1 to 4, D showing steps 5 and 6, E showing steps 7 and 8, and F showing step 9. (A): Cut gel in an extra container placed inside a portable oven set to 270 °F (132 °C). (B): Melted, bubble-free gel in the extra container. (C): Two mold pans. (D): Spine model, with anterior side up, placed in cooled, bubble-free layer. (E): Spine model submerged completely in gel and cooled.

Leah Webb, Melissa Masaracchia, Kim Strupp

JMIR Med Educ 2025;11:e63682