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1. Large Language Model–Based Responses to Patients’ In-Basket Messages

   https://doi.org/10.1001/jamanetworkopen.2024.22399  

   Small, William R; Wiesenfeld, Batia; Brandfield-Harvey, Beatrix; Jonassen, Zoe; Mandal, Soumik; Stevens, Elizabeth R; Major, Vincent J; Lostraglio, Erin; Szerencsy, Adam; Jones, Simon; et al (July 2024, JAMA Network Open)

   ImportanceVirtual patient-physician communications have increased since 2020 and negatively impacted primary care physician (PCP) well-being. Generative artificial intelligence (GenAI) drafts of patient messages could potentially reduce health care professional (HCP) workload and improve communication quality, but only if the drafts are considered useful. ObjectivesTo assess PCPs’ perceptions of GenAI drafts and to examine linguistic characteristics associated with equity and perceived empathy. Design, Setting, and ParticipantsThis cross-sectional quality improvement study tested the hypothesis that PCPs’ ratings of GenAI drafts (created using the electronic health record [EHR] standard prompts) would be equivalent to HCP-generated responses on 3 dimensions. The study was conducted at NYU Langone Health using private patient-HCP communications at 3 internal medicine practices piloting GenAI. ExposuresRandomly assigned patient messages coupled with either an HCP message or the draft GenAI response. Main Outcomes and MeasuresPCPs rated responses’ information content quality (eg, relevance), using a Likert scale, communication quality (eg, verbosity), using a Likert scale, and whether they would use the draft or start anew (usable vs unusable). Branching logic further probed for empathy, personalization, and professionalism of responses. Computational linguistics methods assessed content differences in HCP vs GenAI responses, focusing on equity and empathy. ResultsA total of 16 PCPs (8 [50.0%] female) reviewed 344 messages (175 GenAI drafted; 169 HCP drafted). Both GenAI and HCP responses were rated favorably. GenAI responses were rated higher for communication style than HCP responses (mean [SD], 3.70 [1.15] vs 3.38 [1.20];P = .01,U = 12 568.5) but were similar to HCPs on information content (mean [SD], 3.53 [1.26] vs 3.41 [1.27];P = .37;U = 13 981.0) and usable draft proportion (mean [SD], 0.69 [0.48] vs 0.65 [0.47],P = .49,t = −0.6842). Usable GenAI responses were considered more empathetic than usable HCP responses (32 of 86 [37.2%] vs 13 of 79 [16.5%]; difference, 125.5%), possibly attributable to more subjective (mean [SD], 0.54 [0.16] vs 0.31 [0.23];P < .001; difference, 74.2%) and positive (mean [SD] polarity, 0.21 [0.14] vs 0.13 [0.25];P = .02; difference, 61.5%) language; they were also numerically longer (mean [SD] word count, 90.5 [32.0] vs 65.4 [62.6]; difference, 38.4%), but the difference was not statistically significant (P = .07) and more linguistically complex (mean [SD] score, 125.2 [47.8] vs 95.4 [58.8];P = .002; difference, 31.2%). ConclusionsIn this cross-sectional study of PCP perceptions of an EHR-integrated GenAI chatbot, GenAI was found to communicate information better and with more empathy than HCPs, highlighting its potential to enhance patient-HCP communication. However, GenAI drafts were less readable than HCPs’, a significant concern for patients with low health or English literacy. 

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2. The Pandemic Journaling Project: A new dataset of first-person accounts of the COVID-19 pandemic

   https://doi.org/10.1371/journal.pone.0318397  

   Willen, Sarah S; Mason, Katherine A; Wurtz, Heather M; Karcher, Sebastian (September 2025, PLOS One)

   Liu, Benjamin M (Ed.)

   BackgroundThe rapid global spread of the COVID-19 pandemic affected different regions, communities, and individuals in vastly different ways that interdisciplinary social scientists are well-positioned to document and investigate. This paper describes an innovative mixed-methods dataset generated by a research study that was designed to chronicle and preserve evidence of the pandemic’s divergent effects: the Pandemic Journaling Project (PJP). The dataset was generated by leveraging digital technology to invite ordinary people around the world to document the impact of the COVID-19 pandemic on their everyday lives over a two-year period (May 2020-May 2022) using text, images, and audio. Methods and findingsPJP’s weekly, online, bilingual (English/Spanish) journaling platform was open to anyone with access to a smartphone or computer, including teens aged 15–17 with permission of a parent or guardian. Participants first completed a baseline quantitative survey, after which they were invited to create two journal entries in response to suggested narrative prompts. In each subsequent week, participants received weekly invitations to contribute via their choice of email or SMS (text message). Each invitation included a link to that week’s journaling prompts and accompanying survey questions.Participants could join the project at any point between May 2020 and May 2022. PJP employed a cohort design. Regardless of when they joined, all received the narrative prompts and accompanying survey questions in the same order. Participants could stop participating at any point, and they could later restart if they wished. The project welcomed any interested participant and sought to capture as broad a range of perspectives as possible, while also taking measures to include voices that might not otherwise be preserved in the historical record.The project launched in May 2020. In the two years it operated as a weekly journaling platform, PJP generated nearly 27,000 individual journal entries from over 1,800 people in 55 countries around the world. Data from PJP’s first phase (PJP-1) are now accessible at the Qualitative Data Repository (QDR) at Syracuse University. ConclusionsThe first phase of the Pandemic Journaling Project has produced an innovative multimedia dataset that can support studies of how the COVID-19 pandemic has affected a wide range of communities across a wide range of outcomes including mental health, reproductive health, vaccine hesitancy, and trust in health professionals, among others. The dataset is available to researchers who follow established data protection protocols and procedures. These data protection measures will be in place for 25 years, through 2049, after which all PJP-1 data will become a fully accessible public archive via QDR. 

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3. Generative AI Use and Depressive Symptoms Among US Adults

   https://doi.org/10.1001/jamanetworkopen.2025.54820  

   Perlis, Roy H; Gunning, Faith M; Uslu, Ata A; Santillana, Mauricio; Baum, Matthew A; Druckman, James N; Ognyanova, Katherine; Lazer, David (January 2026, JAMA Network Open)

   ImportanceGenerative artificial intelligence (AI) has rapidly entered mainstream use in the US, but its association with mental health has not been characterized. ObjectiveTo examine the associations of the extent and type of generative AI use among US adults with negative affective symptoms in a large, nationally representative sample. Design, Setting, and ParticipantsThis survey study used data from a 50-state US internet nonprobability survey conducted between April and May 2025. Survey respondents were aged 18 years and older. Data were analyzed in August 2025. ExposureParticipants self-reported generative AI and social media use. Main Outcomes and MeasuresThe outcome of interest, negative affect, was measured using the Patient Health Questionnaire 9-item (PHQ-9). ResultsThere were 20 847 unique participants, with mean (SD) age 47.3 (17.1) years and 10 327 (49.5%) female, 10 386 (49.8%) male, and 134 (0.6%) nonbinary participants; 2152 participants (10.3%) reported using AI at least daily, including 1053 participants (5.1%) who reported daily use and 1099 participants (5.3%) who reported use multiple times per day. Among participants who used daily or more frequently, 1033 (48.0%) reported use for work, 246 (11.4%) for school, and 1875 (87.1%) for personal applications. In survey-weighted regression models, daily or more frequent AI use was significantly more common among men, younger adults, those with higher education and income, and those in urban settings. Greater AI use was associated with greater levels of depressive symptoms in sociodemographic-adjusted regression models: (daily use: β = 1.08 [95% CI, 0.55-1.62]; multiple times per day: β = 0.86 [95% CI, 0.35-1.37]) compared with nonuse, and with greater likelihood of reporting at least moderate depressive symptoms (odds ratio [OR], 1.29 [95% CI, 1.15-1.46]); similar patterns were observed for anxiety and irritability. The highest estimates were observed among individuals using AI for personal use (β = 0.31 [95% CI, 0.10-0.52]) and those aged 25 to 44 years (β = 1.22 [95% CI, 0.70-1.74]) or 45 to 64 years (β = 1.38 [95% CI, 0.72-2.05]). Conclusions and RelevanceThis survey study found that AI use was significantly associated with greater depressive symptoms, with magnitude of differences varying by age group. Further work is needed to understand whether these associations are causal and explain heterogeneous effects. 

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4. Fractionalized Fermi liquids and the cuprate phase diagram

   https://doi.org/10.1088/1361-6633/ae530d  

   Bonetti, Pietro M; Christos, Maine; Nikolaenko, Alexander; Patel, Aavishkar A; Sachdev, Subir (April 2026, Reports on Progress in Physics)

   Abstract We review a theoretical framework for the cuprate superconductors, rooted in a fractionalized Fermi liquid (FL*) description of the intermediate-temperature pseudogap phase at low doping. The FL* theory predicted hole pockets each of fractional area $p/8$ at hole dopingp, in contrast to the area $p/4$ in spin density wave theory. Magnetotransport measurements, including observation of the Yamaji angle, show clear evidence of hole pocket quasiparticles which can tunnel coherently between square lattice layers, and are consistent with the FL* description. The FL* phase of a single-band model is described using a layer construction with a pair of ancilla qubits on each site: the Ancilla layer model (ALM). Its mean field theory yields hole pockets of area $p/8$ , and matches the gapped photoemission spectrum in the anti-nodal region of the Brillouin zone. Fluctuations are described by the SU(2) gauge theory of a background spin liquid with critical Dirac spinons. A Monte Carlo study of the thermal SU(2) gauge theory transforms the hole pockets into Fermi arcs in photoemission. One route to confinement of FL* upon lowering temperature yields ad-wave superconductor via a Kosterlitz–Thouless transition of $h/\left(2e\right)$ vortices, with nodal Bogoliubov quasiparticles featuring anisotropic velocities and vortices surrounded by charge order halos. An alternative route yields a charge-ordered metallic state that has quantum oscillations consistent with observations. These confinement transitions are driven by the condensation of a SU(2) fundamental Higgs field, which also provides a fractionalized description of intertwined orders. Increasing doping from the FL* phase in the ALM drives a transition to a conventional FL at large doping, passing through an intermediate strange metal regime. We formulate a theory of the FL*-FL metal-metal transition without a symmetry-breaking order parameter, using a critical quantum ‘charge’ liquid of mobile electrons in the presence of disorder, developed via an extension of the Sachdev–Ye–Kitaev model to two spatial dimensions. At low temperatures, and across optimal and over doping, we address the regimes of extended non-FL behavior by Griffiths effects near quantum phase transitions in disordered metals. Partly based on lectures by S S atBoulder School 2025, Dynamics of Strongly Correlated Electrons, 14–18 July.Lecture videos.Joint ICTP-WE Heraeus School and Workshop on Advances in Quantum Matter: Pushing the Boundaries, ICTP, Trieste, 4, 6 August 2025.Lecture videos.School on Quantum Dynamics of Matter, Light and Information, ICTP, Trieste, 18, 19 August 2025.Lecture videos.Croucher Advanced Study Institute for Fractional Chern Insulators, University of Hong Kong, 4, 5 September 2025.Lecture slides.Advanced School and Conference on Quantum Matter, ICTP Trieste, 1–12 December 2025.Lecture Notes.Lecture videos. 

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5. Wearable Myoelectric Interface for Neurorehabilitation (MINT) to Recover Arm Function: a Randomized Controlled Trial

   https://doi.org/10.1101/2025.06.24.25330240  

   Khorasani, Abed; Gorski, Cynthia M; Hung, Na-Teng; Hulsizer, Joel; Paul, Vivek; Tomic, Goran; Prakash, Prashanth R; Park, Sangsoo; Seo, Gang; Houskamp, Ethan J; et al (June 2025, medRxiv)

   Abstract BackgroundAbnormal muscle co-activation contributes to arm impairment after stroke. This single-blind, randomized, sham-controlled trial evaluated the feasibility and efficacy of home-based, personalized myoelectric interface for neurorehabilitation (MINT) conditioning to reduce abnormal co-activation and enhance arm function and determine the optimal number of abnormally co-activating muscles to target during training. MethodsModerately to severely impaired chronic stroke survivors were randomized to one of three MINT groups (who played customized games requiring independent activation of 2 or 3 abnormally co-activating muscles) or a sham control group (played using one muscle). All groups trained 90 minutes/day, 5 days/week at home and 1 day/week in lab, for 6 weeks, and changed trained muscle sets every 2-3 weeks. The primary outcome was the Wolf Motor Function Test (WMFT) at 6 weeks. ResultsFifty-nine participants completed the training. Participants performed 315 ± 85 (mean ± SD) repetitions daily. At week 6, participants in all MINT groups combined improved by 4 s on WMFT (p=0.0008), exceeding the minimal clinically important difference (1.5 s). Participants who trained 3 muscles simultaneously improved by 6.8 s (p=0.001), while the 2-muscle and sham groups did not change significantly. In per-protocol analysis, the 3-muscle group, but not 2-muscle groups, improved significantly more than sham (p=0.046), though not in intention-to-treat analysis. All MINT groups continued improving at 4 weeks post-training. Importantly, severely impaired participants in combined MINT groups improved more than those in sham (p=0.02). Importantly, combined MINT groups also improved their reaching range of motion significantly more than sham. Co-activation decreased by 76% in MINT groups during training. Notably, reduction in co-activation during reaching correlated significantly with improved arm function and range of motion. Other secondary outcomes did not show clinically important improvement. Stroke involving the posterior limb of the internal capsule negatively predicted response to MINT. ConclusionsHome-based MINT conditioning, especially the 3-muscle variant, is feasible, reduces co-activation, and improves arm movement and function. Clinical Trial RegistrationClinicalTrials.gov(NCT03401762) 

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