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Inclusion of Individuals With Lived Experiences in the Development of a Digital Intervention for Co-Occurring Depression and Cannabis Use: Mixed Methods Investigation

As such, we included EBEs, or individuals with problematic depressive symptoms and cannabis use, to help design the digital intervention, AMP-C. This study focuses on the first interview in a larger project with an iterative and longitudinal design to the development of AMP-C.

Amanda C Collins, Sukanya Bhattacharya, Jenny Y Oh, Abigail Salzhauer, Charles T Taylor, Kate Wolitzky-Taylor, Robin L Aupperle, Alan J Budney, Nicholas C Jacobson

JMIR Form Res 2024;8:e54751

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Patient Engagement in a Multimodal Digital Phenotyping Study of Opioid Use Disorder

Cynthia I Campbell, Ching-Hua Chen, Sara R Adams, Asma Asyyed, Ninad R Athale, Monique B Does, Saeed Hassanpour, Emily Hichborn, Melanie Jackson-Morris, Nicholas C Jacobson, Heather K Jones, David Kotz, Chantal A Lambert-Harris, Zhiguo Li, Bethany McLeman, Varun Mishra, Catherine Stanger, Geetha Subramaniam, Weiyi Wu, Christopher Zegers, Lisa A Marsch

J Med Internet Res 2023;25:e45556

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Evaluating the Impact of Mask Mandates and Political Party Affiliation on Mental Health Internet Search Behavior in the United States During the COVID-19 Pandemic: Generalized Additive Mixed Model Framework

In particular, this study serves to complement the work by Jacobson et al [22], where an attenuation of mental health search term activity was found in the United States after stay-at-home orders were implemented.

Joseph A Gyorda, Damien Lekkas, George Price, Nicholas C Jacobson

J Med Internet Res 2023;25:e40308

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End User Participation in the Development of an Ecological Momentary Intervention to Improve Coping With Cannabis Cravings: Formative Study

Molly A Anderson, Alan J Budney, Nicholas C Jacobson, Inbal Nahum-Shani, Catherine Stanger

JMIR Form Res 2022;6(12):e40139

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Using Smartphone Sensor Paradata and Personalized Machine Learning Models to Infer Participants’ Well-being: Ecological Momentary Assessment

However, as demonstrated by Jacobson and Chung [25], such models can most likely be used to inform personalized models. A final question we investigated was whether the working models could be traced back to a pattern of successful predictors that would be indicative of a certain outcome. In the related analyses, we found that, despite finding that the algorithms performed similarly, they treated the data differently.

Alexander Hart, Dorota Reis, Elisabeth Prestele, Nicholas C Jacobson

J Med Internet Res 2022;24(4):e34015

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Using the COVID-19 Pandemic to Assess the Influence of News Affect on Online Mental Health-Related Search Behavior Across the United States: Integrated Sentiment Analysis and the Circumplex Model of Affect

(C) Higher spin and lower pulse. (D) Lower spin and lower pulse. To investigate the association between mental health search term activity and affective dynamics of COVID-19 news reporting across the United States, 8 separate mixed effects models were constructed.

Damien Lekkas, Joseph A Gyorda, George D Price, Zoe Wortzman, Nicholas C Jacobson

J Med Internet Res 2022;24(1):e32731

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The Challenges in Designing a Prevention Chatbot for Eating Disorders: Observational Study

On the assumption that internet-based programs can provide easy and convenient access to EDs prevention, we developed a cognitive behavior–based program called Student Bodies (C). Human-moderated (guided) versions of Student Bodies have been shown to be associated with moderate improvements in ED-related attitudes, including reductions in negative body image and the desire to be thin [9-12]. Human moderators helped reinforce the use of the program by providing support and feedback.

William W Chan, Ellen E Fitzsimmons-Craft, Arielle C Smith, Marie-Laure Firebaugh, Lauren A Fowler, Bianca DePietro, Naira Topooco, Denise E Wilfley, C Barr Taylor, Nicholas C Jacobson