Delayed school start time is associated with better sleep, mental health, and life satisfaction among residential high-school students: A prospective study.

This study examined the longer-term individual- and school-level changes in students seven months after a one-hour delay in school start time (SST). Two cohorts of Grade 11 students (N = 227; 60.8% female, age = 17.0 [0.85]) at a residential high school in Hong Kong completed a questionnaire assessing sleep duration, insomnia symptoms, depression, anxiety, stress, and subjective well-being in 2017 and 2018, respectively. One of the cohorts was reassessed seven months after the implementation of a delay in SST, from 7:30am to 8:30am (n = 83, 65.1% female). School-level data on breakfast consumption, attendance, tardiness, and health clinic visits were collected. Between-group and within-group prospective comparisons suggest that the delay in SST was associated with improved sleep duration, mental health, and life satisfaction. School-level data revealed increased breakfast consumption and decreased unexcused absences, tardiness, and clinic visits.

The Sequelae and Moderators of Influence of Dandruff on Mental Health Among Mainland Chinese Adults.

Introduction: The psychological impact of dandruff has been largely understudied. Methods: In this cross-sectional study (N = 2116), we examined the consequences of self-perception of dandruff severity on mental health, quality of life, and sleep quality among Chinese adults. Additionally, we examined the moderating factors that influence these associations. Results: Bivariate analyses revealed that greater self-perceived dandruff severity was associated with poorer mental health, lower quality of life, and reduced sleep quality. Furthermore, dandruff severity was positively correlated with appearance anxiety, feelings of helplessness, and perceived stigma. Individuals with more severe dandruff experienced increased teasing and ostracism and, subsequently, heightened psychological distress. Moderation analyses demonstrated that females were more adversely affected by dandruff than males, and those with comorbid skin conditions or a history of being teased and ostracized during adolescence due to dandruff experienced exacerbated negative outcomes. Discussion: This study highlights the need for further research on the psychological consequences of self-perceived severity of dandruff and potential interventions to mitigate its impact.

A group-based transdiagnostic sleep and circadian treatment for major depressive disorder: A randomized controlled trial.

OBJECTIVE: Sleep and circadian disturbance is highly comorbid with a range of psychological disorders, especially major depressive disorder (MDD). In view of the complexity of sleep and circadian problems in MDD, this study aimed to evaluate the efficacy of a group-based transdiagnostic intervention for sleep and circadian dysfunction (TranS-C) for improving depressive symptoms and sleep and circadian functions. METHOD: One hundred fifty-two adults diagnosed with comorbid MDD and sleep and circadian dysfunctions were randomized into TranS-C group treatment (TranS-C; n = 77) or care as usual (CAU; n = 75) control group. The TranS-C group received six weekly 2-hr group sessions of TranS-C, whereas the CAU group continued to receive usual care. Assessments were at baseline, immediate (Week 7), and 12-week (Week 19) posttreatment. Primary and secondary outcomes included depression, anxiety, sleep disturbances, fatigue, quality of life, and functional impairment. RESULTS: The TranS-C group showed significant improvement in depressive symptoms (p < .001, d = 0.84), insomnia severity (p < .001, d = 0.77), sleep disturbances (p < .001, d = 1.15), sleep-related impairment (p < .001, d = 1.22), fatigue (p < .001, d = 1.06), anxiety symptoms (p = .004, d = 0.67), quality of life (p < .001, d = 0.71), and sleep diary-derived parameters (ps < .05, d = 0.12-0.77) relative to the CAU group at immediate posttreatment. These treatment gains remained significant at 12-week follow-up. Significant improvement in functional impairment was also noted at 12-week follow-up. CONCLUSIONS: TranS-C was efficacious and acceptable in alleviating depressive symptoms and sleep and circadian disruptions in adults with MDD. The group format appears to be a low-cost, widely disseminable option to deliver TranS-C. Further research on TranS-C to examine its benefits on other psychiatric disorders is warranted. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Efficacy of ChatGPT in Cantonese Sentiment Analysis: Comparative Study.

BACKGROUND: Sentiment analysis is a significant yet difficult task in natural language processing. The linguistic peculiarities of Cantonese, including its high similarity with Standard Chinese, its grammatical and lexical uniqueness, and its colloquialism and multilingualism, make it different from other languages and pose additional challenges to sentiment analysis. Recent advances in models such as ChatGPT offer potential viable solutions. OBJECTIVE: This study investigated the efficacy of GPT-3.5 and GPT-4 in Cantonese sentiment analysis in the context of web-based counseling and compared their performance with other mainstream methods, including lexicon-based methods and machine learning approaches. METHODS: We analyzed transcripts from a web-based, text-based counseling service in Hong Kong, including a total of 131 individual counseling sessions and 6169 messages between counselors and help-seekers. First, a codebook was developed for human annotation. A simple prompt ("Is the sentiment of this Cantonese text positive, neutral, or negative? Respond with the sentiment label only.") was then given to GPT-3.5 and GPT-4 to label each message's sentiment. GPT-3.5 and GPT-4's performance was compared with a lexicon-based method and 3 state-of-the-art models, including linear regression, support vector machines, and long short-term memory neural networks. RESULTS: Our findings revealed ChatGPT's remarkable accuracy in sentiment classification, with GPT-3.5 and GPT-4, respectively, achieving 92.1% (5682/6169) and 95.3% (5880/6169) accuracy in identifying positive, neutral, and negative sentiment, thereby outperforming the traditional lexicon-based method, which had an accuracy of 37.2% (2295/6169), and the 3 machine learning models, which had accuracies ranging from 66% (4072/6169) to 70.9% (4374/6169). CONCLUSIONS: Among many text analysis techniques, ChatGPT demonstrates superior accuracy and emerges as a promising tool for Cantonese sentiment analysis. This study also highlights ChatGPT's applicability in real-world scenarios, such as monitoring the quality of text-based counseling services and detecting message-level sentiments in vivo. The insights derived from this study pave the way for further exploration into the capabilities of ChatGPT in the context of underresourced languages and specialized domains like psychotherapy and natural language processing.