<![CDATA[Physician burnout persists as moral injury grows in psychiatry, with July 4 reflection on systemic healthcare failures, ethical compromise, and peer-supported recovery.]]>
<![CDATA[Explore how major holidays like July 4 can trigger PTSD, loneliness, and grief—and why psychiatrists can help patients prepare for emotional fallout.]]>
Author Correction: Improved RNA base editing with guide RNAs mimicking highly edited endogenous ADAR substrates
Nature Biotechnology, Published online: 03 July 2026; doi:10.1038/s41587-026-03246-6
Author Correction: Improved RNA base editing with guide RNAs mimicking highly edited endogenous ADAR substrates
Identifying Behavior Change Techniques for Digital Interventions Addressing Alcohol and Tobacco Co-Use: Findings From a Delphi Consensus Study
Background: Alcohol and tobacco use frequently co-occur and contribute significantly to the global burden of disease. Despite the well-established benefits of addressing both behaviors simultaneously, health care professionals often face substantial challenges in delivering integrated interventions, including limited time, training, and resources. Digital health interventions offer a promising avenue to directly support patients in reducing alcohol and tobacco use, while bypassing some of the barriers encountered in clinical settings. However, there is a lack of consensus on the key behavior change techniques (BCTs) that must be incorporated to ensure that interventions are evidence based and contextually appropriate, making them effective. Objective: The study aims to identify expert opinions on the most suitable and effective BCTs (reflecting both behavioral relevance and delivery feasibility) to be included in a 1-time, self-guided digital intervention intended to initiate behavior change and support alcohol reduction among people trying to quit smoking. Methods: We conducted a 2-round modified Delphi study with 14 panelists with expertise in behavioral science, alcohol and tobacco treatment, and digital interventions. Panelists rated 20 BCTs identified in a previous rapid review using the acceptability, practicability, effectiveness, affordability, safety, and equity (APEASE) criteria. BCTs were deemed “appropriate” if at least 70% (n=10) of panelists agreed on all criteria. Results: Six BCTs were identified as appropriate for implementation: goal setting, action planning (individualized change plan), action planning (reduction strategies), feedback on behavior, reattribution, and pros and cons. These BCTs were considered effective for promoting behavior change through structured planning and personalized strategies. The panel reached partial consensus on several BCTs, while 8 BCTs were deemed inappropriate for a 1-time, unsupervised digital intervention. Conclusions: The results of this study offer a consensus-based view, reflecting expert opinion on the perceived appropriateness and feasibility of the BCTs that should be included in a 1-time digital intervention to address co-occurring alcohol and tobacco use.
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Using Ecological Momentary Assessment to Document and Investigate Caregiver Practices Between Pediatric Therapy Sessions: Prospective Pilot Cohort Study
Background: Determining the appropriate dosage of pediatric occupational therapy, physical therapy, and speech-language pathology services is important when supporting families of children with disabilities. However, therapy dosage is inconsistently reported, and caregiver-delivered practice between sessions is rarely documented. Ecological momentary assessment (EMA) offers a method to capture caregiver practice in real time and to examine factors that influence it. Objective: This study aims to pilot the use of EMA to measure caregiver practices between therapy sessions and to compare EMA-reported practices with caregiver recall. Methods: This pilot prospective cohort study used convenience sampling to recruit caregivers of children receiving therapy services. During September 2024, participants completed a confidential baseline Qualtrics survey in their homes, which included recall of home practice from the previous week. Participants were then invited to complete 30 days of EMA logging of daily practice. Five participants enrolled in the EMA phase, which began 24 to 72 hours after baseline survey completion and took place during October and November 2024. Semistructured follow-up interviews were conducted immediately after the 30-day EMA period. Results: Of the 34 survey participants, 5 continued to the EMA phase, contributing 150 days of data, with 82 completed entries (82/150, 55%). Caregivers primarily completed EMA logs on days when practice occurred; missing entries were coded as zero practice based on caregiver reports. Recalled practice averaged 4.5 (SD 5.65) bouts/day and 11.6 (SD 6.35) minutes/bout, totaling 71.2 (SD 121.02) minutes/day. EMA-reported practice across all days (n=150) averaged 2.7 (SD 4.39) bouts/day and 6.5 (SD 6.45) minutes/bout, totaling 23.2 (SD 14.12) minutes/day, which was substantially lower than recalled estimates. On days when practice was reported (n=82), EMA-documented practice averaged 5.2 (SD 3.28) bouts/day and 6.5 (SD 6.45) minutes/bout, totaling 23.9 (SD 14.72) minutes/day. Variability in recalled practice was high (mean 71.19, SD 121.02 min/d). Caregivers described practice as occurring in short, frequent bouts embedded within daily routines, with routine integration, child engagement, and recall of therapist strategies identified as key facilitators. Conclusions: Caregiver-delivered practice occurred in short, frequent bouts integrated into daily routines. EMA-reported practice was substantially lower than caregiver recall, suggesting that retrospective recall and prospectively reported EMA data may differ substantially. These findings highlight the importance of teaching strategies that are brief, engaging, and easily incorporated into daily routines. Despite the small sample, EMA was acceptable to a subset of caregivers who completed participation; however, substantial attrition between survey enrollment and EMA initiation suggests significant feasibility and participation barriers that warrant further investigation.
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Use of Electronic Patient Record Systems for Rapid Response to an MHRA Public Assessment Report: Retrospective Observational Study
Background: Digital health data and infrastructure facilitate rapid analysis to provide actionable data, thereby fulfilling the principles of a learning health system. In response to a report from the UK Medicines and Healthcare Products Regulatory Agency (MHRA), a rapid service evaluation was carried out to identify patterns of modified-release (MR) opioid use after elective surgery. Objective: We aimed to describe the prescribing patterns of MR opioids, methods to repurpose existing infrastructure, and the experience of collaboration between clinical and research teams using shared data pipelines. Methods: A retrospective case-control study was conducted at a tertiary care organization across multiple hospital sites in London, United Kingdom. Prescription and administration data for adult patients undergoing elective surgery between March 31, 2019, and June 20, 2025, were extracted from a standardized research data pipeline within 4 weeks of the publication of the MHRA report. Patients were screened for MR opioid prescriptions in the postoperative period and at hospital discharge. Counts and proportions of encounters in which MR opioids were administered or prescribed were evaluated across the study period. Reflections on the application of the infrastructure for this purpose were also documented. Results: Of 126,882 elective surgeries screened, 102,879 (81.1%) met the eligibility criteria. Over the study period, patients received a new MR opioid prescription after 7525 (7.3%) of the 102,879 eligible encounters, with 2438 (2.4%) encounters receiving a new MR opioid prescription at hospital discharge. Postoperative administration of MR opioids and prescribing at discharge have declined since 2020. As a result of this study, a new context-aware alert system was developed to monitor and reduce MR opioid prescribing in this surgical cohort. Reflections on the implementation experience demonstrated how collaboration between clinical and research teams in conjunction with integrated and seamless research pipelines allowed rapid knowledge generation. Key issues raised were the difficulty of validation between parallel data extraction systems and how the two different teams compared nonequitable data points and results. Conclusions: Mature digital and analytical infrastructure within health care institutions can enable swift evaluation of local practices in the context of national medication safety alerts. This can shorten action response times and improve patient care but requires close collaboration between clinicians and research teams. Shared infrastructure between teams across the learning health system improves data quality and provides easy access to the key users. Further work is needed to understand the benefits and challenges of infrastructure built for other use cases and the effectiveness of the intervention.
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Virtual Reality–Based Relaxation Training and Symptom Improvement Among Inpatients With Depressive Disorders: Retrospective Nonrandomized Comparative Study
Background: Virtual reality (VR) is increasingly used for adjunctive relaxation training in psychiatric care. However, evidence remains limited among hospitalized patients with depressive disorders, particularly in routine inpatient settings in China, and little is known about whether improvement varies by session frequency. Objective: This retrospective study examined whether adjunctive VR-based relaxation training was associated with changes in depressive and anxiety symptoms among inpatients with depressive disorders and whether improvement differed by session frequency. Methods: We conducted a retrospective, nonrandomized natural-group comparison using complete anonymized medical records from patients hospitalized in Lishui Second People’s Hospital between January 1 and December 31, 2022. Patients met () diagnostic criteria for depressive episodes or recurrent depressive disorders and were screened using predefined criteria. The analytic sample included 133 inpatients: 63 (47.4%) received adjunctive VR-based relaxation training plus usual care and 70 (52.6%) received usual care only. Usual care included pharmacotherapy and physiotherapy. The VR intervention consisted of 25-minute immersive relaxation sessions delivered approximately 3 times per week. Symptoms were assessed at admission and discharge using the 17-item Hamilton Depression Scale and Hamilton Anxiety Rating Scale. Response was defined as a reduction of 50% or more from baseline, and remission was defined as a total score of 7 or less. Baseline characteristics, outcome scores, response and remission rates, and exploratory session-frequency subgroups were compared. All analyzed variables were checked against complete medical records; no missing values were identified, and no imputation was performed. Results: The VR and control groups did not differ significantly in baseline depressive or anxiety scores. At discharge, adjunctive VR-based relaxation training was associated with lower depressive and anxiety symptom scores than usual care alone. The VR group also showed higher response rates for both depressive and anxiety symptoms and a higher anxiety remission rate, whereas depression remission was similar. Exploratory session-frequency analyses suggested that anxiety improvement may be more consistently associated with VR exposure than depression remission; however, the pattern was not strictly linear and should be interpreted cautiously because treatment frequency was linked to hospitalization duration and routine care factors. Conclusions: This study is innovative in evaluating structured VR-based relaxation training as an adjunct to routine inpatient depression care and in providing preliminary observations on session-frequency patterns in a real-world Chinese psychiatric setting. Unlike many previous VR studies conducted in noninpatient, nonclinical, or short-term experimental contexts, this study reflects everyday clinical practice among hospitalized patients with depressive disorders. The findings contribute practical evidence for integrating immersive relaxation into comprehensive inpatient care, particularly when additional anxiety relief is desired. Because the study was retrospective and nonrandomized, the findings indicate associations rather than causal effects and should be confirmed in prospective randomized controlled trials.
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Exploring Informal Caregivers’ Perception of the Olera Digital Caregiving Assistance Platform for Dementia Care: Mixed Methods Evaluation Study
Background: Informal caregivers of people living with dementia often experience high rates of caregiver burnout while providing care. Although there are many websites and mobile apps available to help caregivers, many do not use digital tools. The Olera platform was developed to be an easily adoptable web-based support tool, connecting caregivers with long-term services and supports, financial assistance, and educational resources. The platform was developed based on the Build-Measure-Learn framework with input from caregiver needs assessments and usability studies. Objective: This study aims to evaluate the quantitative and qualitative feedback of informal caregivers of people living with dementia on the second iteration of the Olera platform. The primary objective was to assess caregivers’ acceptance of this caregiving platform. The secondary objective was to use qualitative methods to explore (1) the study cohort’s challenges in daily caregiving to determine and compare them with prior literature, (2) their experience when using the Olera platform, and (3) their attitudes toward integrating artificial intelligence in caregiver services for future studies and platform development. Methods: Caregivers were recruited through various sources and screened for eligibility through an initial survey. Participants used the platform for 4 weeks and completed a survey with an adapted Technology Acceptance Survey (TAS) and qualitative open-ended questions at the end of the testing period. TAS responses were summarized with descriptive statistics, while ANOVAs, tests, and linear regressions were used to compare the differences in the overall TAS scores by caregiver characteristics. Qualitative feedback data on the platform’s usefulness were analyzed via a thematic analysis framework approach. Results: A total of 65 caregivers in the United States completed the study, with a mean age of 59.9 (SD 9.8) years. The majority were female (61/65, 95.3%), non-Hispanic or Latino White (45/65, 69.2%), and the adult child of their care recipient (42/65, 64.6%). Evaluation of the Olera platform showed a high acceptance rate, with each TAS item scoring above 5.0 and an overall TAS score of 5.83 (SD 0.85) out of 7. Higher platform use frequency was associated with higher TAS ratings in technology acceptance (=7.88, <.001). Thematic analyses elicited the caregiving challenges, evaluation of the Olera platform, and feedback on artificial intelligence–assisted support. Conclusions: The Olera platform is an example of a beneficial web-based tool, though key features were requested to be included in the next iteration. Additionally, data supported prior findings regarding informal caregiver challenges and the insufficiency of conventional support mechanisms, indicating a need for more innovative digital solutions. Future research and development efforts using the Build-Measure-Learn approach are necessary to further iterate the platform’s key features, enhance the tool, involve more informal caregivers in its improvements, and serve as a model for customizable, person-centered online care support. International Registered Report Identifier (IRRID): RR2-10.2196/64127
Linguistic Fidelity and Classification Performance of Large Language Models for Generating Synthetic Operative Notes: Evaluation Study
Background: Machine learning models for surgical applications require large, diverse datasets; however, data scarcity remains a critical limitation due to privacy regulations, institutional variability, and the rarity of many surgical procedures. Large language models (LLMs) offer a potential solution through synthetic data generation, but their performance and reliability in specialized surgical domains remain underexplored. Objective: This study aimed to evaluate the linguistic fidelity of LLM-generated operative notes for cleft lip and palate procedures and to assess their impact on natural language processing classifier performance under varying data availability conditions. Methods: A total of 630 authentic operative notes were obtained from cleft procedures (86 primary cleft lip repairs, 101 primary cleft palate repairs, and 62 primary alveolar bone grafting [ABG] procedures) performed between 2013 and 2024. GPT-4o generated matched synthetic notes using multishot prompting with anonymized examples. Linguistic fidelity was evaluated using BERTScore for semantic similarity, Jensen-Shannon divergence of part-of-speech trigrams for syntactic structure, and Bilingual Evaluation Understudy (BLEU) scores for lexical overlap. Binary classifiers using ClinicalBERT embeddings and logistic regression were trained under both full data and data-scarce (retaining 5% or 10% of positive training cases while retaining the full negative training set) conditions, with and without synthetic augmentation at approximate ratios of synthetic to real notes (1:1, 2:1, 5:1, and 10:1). Results: Synthetic notes demonstrated high semantic fidelity across all procedures (BERTScore -score: 0.86‐0.88) and low syntactic divergence (Jensen-Shannon divergence: 0.06‐0.08). BLEU scores indicated moderate lexical variation (0.14‐0.19), reflecting distinct but contextually consistent phrasing. With full datasets, synthetic augmentation did not meaningfully affect classifier performance. Under data-scarce conditions retaining 5% of positive training cases while preserving the full negative training set, the area under the curve improved from 0.915 (SD 0.056) to 0.929 (SD 0.033) for cleft lip and from 0.935 (SD 0.036) to 0.949 (SD 0.033) for cleft palate, with smaller gains for ABG (mean 0.983, SD 0.014 to mean 0.987, SD 0.015). When retaining 10% of positive training cases, performance changes were minor across procedures (cleft lip: mean 0.952, SD 0.036 to mean 0.948, SD 0.028; cleft palate: mean 0.945, SD 0.044 to mean 0.956, SD 0.036; and ABG: mean 0.989, SD 0.008 to mean 0.985, SD 0.012). Conclusions: LLM-generated operative notes exhibit strong semantic and syntactic fidelity to authentic documentation and can enhance model performance in a task-dependent manner when authentic data are limited. These findings suggest that synthetic data generation may address data scarcity challenges in specialized surgical domains, particularly for rare or underrepresented procedures, enabling robust machine learning model development.
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Digital Cognitive Behavioral Therapy for Older Adults With Symptoms of Depression: Feasibility Cohort Study
Background: Depressive symptoms are common among older adults and can significantly impact their quality of life. However, many older adults face barriers to accessing psychological treatment. Internet-based cognitive behavioral therapy (iCBT) is a promising alternative to face-to-face treatments, but its feasibility among older adults has been less extensively studied than in adult populations. Objective: This study evaluated the feasibility of guided iCBT for adults aged 55 years and older with mild to moderate depressive symptoms recruited from the general population. Methods: This study is a feasibility study with a single-group, pretest-posttest design (n=21), in which all participants received guided iCBT for 8 weeks. Assessments were conducted at baseline (T0) and after the intervention (T1). The primary outcome was feasibility, conceptualized as satisfaction, usability, engagement, and uptake of iCBT. Secondary outcome measures included depression severity, working alliance, and technical alliance. Results: Participants were mostly highly educated (13/21, 61.9%), female (18/21, 85.7%), had an average age of 59.85 (SD 4.19; range 55-68) years, and reported moderate digital literacy. Feasibility outcomes indicated high satisfaction and engagement and moderate usability. Working alliance was rated as good by both participants and coaches, and technical alliance was rated as moderate by the participants. There was a nonsignificant modest decrease in depressive symptoms (Cohen <i>d</i>=0.47). Of the 20 participants who started the intervention, all completed the first 2 modules, but completion declined across the remaining 6 modules, with only 1 (5%) participant completing all modules. Conclusions: This study found that guided iCBT has the potential to be a feasible option for older adults experiencing depressive symptoms, with participants reporting generally positive satisfaction, moderate engagement, and a moderate therapeutic bond with their coaches. However, below-average usability ratings and a moderate technical alliance suggest that some aspects of the platform require improvement. Future research should focus on improving usability and adherence, as well as testing the intervention in a larger and more diverse population.
