Hypersomnolence is associated with non-remission of major depressive disorder.

OBJECTIVE: This study aimed to investigate the prevalence, clinical correlates and the relationship between hypersomnolence and clinical outcomes in a cohort of MDD patients. METHODS: This is a cross-sectional study of a MDD cohort in an university-affiliated adult psychiatric outpatient clinic. The diagnosis of MDD and severity of depression were ascertained by the clinician with structured clinical interviews. Each participant completed the Epworth Sleepiness Scale (ESS), 1-week sleep diary, and a battery of questionnaires that assessed usual sleep pattern, insomnia, anxiety, depression, fatigue and circadian preference. Hypersomnolence was defined as ESS score ≥14 among those reported ≥7 h of nighttime sleep. Univariate analysis and multiple logistic regression were used to analyze the relationships between the variables. RESULTS: Among 252 recruited subjects, 11 % met the criteria of hypersomnolence as defined by a ESS score ≥14 despite ≥7 h of nighttime sleep. Patients with hypersomnolence had greater depression ratings, higher rates of suicidal ideations over the past week, and more likely to meet a diagnosis of atypical depression (p < 0.05) than those without hypersomnolence. Step-wise logistic regression demonstrated that hypersomnolence was an independent risk factor associated with a 3-fold increase in the risk of depression non-remission (adjusted OR 3.13; 95 % CI 1.10-8.95; p = 0.034). CONCLUSION: Patients with hypersomnolence despite seemingly adequate sleep represent a subgroup of MDD patients who have a more severe illness profile with higher non-remission rate and suicidality. The findings highlight the importance of addressing both sleep and mood symptoms in the management of MDD.

Harnessing Social Media to Explore Youth Social Withdrawal in Three Major Cities in China: Cross-Sectional Web Survey.

BACKGROUND: Socially withdrawn youth belong to an emerging subgroup of youth who are not in employment, education, or training and who have limited social interaction intention and opportunities. The use of the internet and social media is expected to be an alternative and feasible way to reach this group of young people because of their reclusive nature. OBJECTIVE: The aim of this study was to explore the possibility of using various social media platforms to investigate the existence of the phenomenon of youth social withdrawal in 3 major cities in China. METHODS: A cross-sectional open Web survey was conducted from October 2015 to May 2016 to identify and reach socially withdrawn youth in 3 metropolitan cities in China: Beijing, Shanghai, and Shenzhen. To advertise the survey, 3 social media platforms were used: Weibo, WeChat, and Wandianba, a social networking gaming website. RESULTS: In total, 137 participants completed the survey, among whom 13 (9.5%) were identified as belonging to the withdrawal group, 7 (5.1%) to the asocial group, and 9 (6.6%) to the hikikomori group (both withdrawn and asocial for more than 3 months). The cost of recruitment via Weibo was US $7.27 per participant. CONCLUSIONS: Several social media platforms in China are viable and inexpensive tools to reach socially withdrawn youth, and internet platforms that specialize in a certain culture or type of entertainment appeared to be more effective in reaching socially withdrawn youth.

Assessing Suicide Risk and Emotional Distress in Chinese Social Media: A Text Mining and Machine Learning Study.

BACKGROUND: Early identification and intervention are imperative for suicide prevention. However, at-risk people often neither seek help nor take professional assessment. A tool to automatically assess their risk levels in natural settings can increase the opportunity for early intervention. OBJECTIVE: The aim of this study was to explore whether computerized language analysis methods can be utilized to assess one's suicide risk and emotional distress in Chinese social media. METHODS: A Web-based survey of Chinese social media (ie, Weibo) users was conducted to measure their suicide risk factors including suicide probability, Weibo suicide communication (WSC), depression, anxiety, and stress levels. Participants' Weibo posts published in the public domain were also downloaded with their consent. The Weibo posts were parsed and fitted into Simplified Chinese-Linguistic Inquiry and Word Count (SC-LIWC) categories. The associations between SC-LIWC features and the 5 suicide risk factors were examined by logistic regression. Furthermore, the support vector machine (SVM) model was applied based on the language features to automatically classify whether a Weibo user exhibited any of the 5 risk factors. RESULTS: A total of 974 Weibo users participated in the survey. Those with high suicide probability were marked by a higher usage of pronoun (odds ratio, OR=1.18, P=.001), prepend words (OR=1.49, P=.02), multifunction words (OR=1.12, P=.04), a lower usage of verb (OR=0.78, P<.001), and a greater total word count (OR=1.007, P=.008). Second-person plural was positively associated with severe depression (OR=8.36, P=.01) and stress (OR=11, P=.005), whereas work-related words were negatively associated with WSC (OR=0.71, P=.008), severe depression (OR=0.56, P=.005), and anxiety (OR=0.77, P=.02). Inconsistently, third-person plural was found to be negatively associated with WSC (OR=0.02, P=.047) but positively with severe stress (OR=41.3, P=.04). Achievement-related words were positively associated with depression (OR=1.68, P=.003), whereas health- (OR=2.36, P=.004) and death-related (OR=2.60, P=.01) words positively associated with stress. The machine classifiers did not achieve satisfying performance in the full sample set but could classify high suicide probability (area under the curve, AUC=0.61, P=.04) and severe anxiety (AUC=0.75, P<.001) among those who have exhibited WSC. CONCLUSIONS: SC-LIWC is useful to examine language markers of suicide risk and emotional distress in Chinese social media and can identify characteristics different from previous findings in the English literature. Some findings are leading to new hypotheses for future verification. Machine classifiers based on SC-LIWC features are promising but still require further optimization for application in real life.

Withdrawal behaviors and mental health among college students / Comportamientos de aislamiento y salud mental en estudiantes universitarios

Youth social withdrawal has raised clinical concerns, and prevention of withdrawal behavior is important yet difficult. While human evaluation of withdrawal behavior can be subjective, technology provides objective measurement for withdrawal behavior. This study aims to examine the association between withdrawal behaviors (home-stay and non-communication) and mental health status (stress, depression and loneliness). The open-access StudentLife dataset, including the location and conversation information derived from the sensor data, stress levels, and pre- and post-questionnaires of depression (PHQ-9) and loneliness (RULS) of 47 college students over 10 weeks was used. Multilevel modeling and functional regression were employed for data analysis. Daily duration of home-stay was negatively associated with daily stress levels, and the interaction effect of daily duration of home-stay and non-communication were positively associated with daily stress levels and changes in PHQ-9 and RULS scores. Smartphone data is useful to provide adjunct information to the professional clinical judgement and early detection on withdrawal behavior

El aislamiento social de los jóvenes ha generado preocupaciones clínicas y prevenir estos comportamientos es importante pero difícil. Aunque la evaluación del aislamiento puede ser subjetiva, la tecnología proporciona medidas objetivas de este comportamiento. El objetivo de este estudio es examinar la asociación entre los comportamientos de aislamiento (permanecer en casa y no comunicarse) y el estado de la salud mental (estrés, depresión y soledad). Se utilizó la base de datos de libre acceso StudentLife, incluyendo información sobre la ubicación y la conversación registrada por un sensor de datos, los niveles de estrés y medidas de autoinforme pre y pos sobre depresión (PHQ-9) y soledad (RULS) de 47 estudiantes universitarios durante 10 semanas. Para el análisis de datos se utilizaron modelos multinivel y la regresión funcional. La duración diaria de la permanencia en casa estaba negativamente asociada con los niveles diarios de estrés y el efecto de interacción de la duración diaria de la permanencia en casa y la falta de comunicación estaban positivamente relacionados con los niveles diarios de estrés y los cambios en las puntuaciones en PHQ-9 y RULS. Los datos del teléfono inteligente son útiles para obtener información complementaria al juicio clínico profesional y para la detección temprana de los comportamientos de aislamiento

Effectiveness of a Technology-Based Injury Prevention Program for Enhancing Mothers' Knowledge of Child Safety: Protocol for a Randomized Controlled Trial.

BACKGROUND: Provision of anticipatory guidance for parents is recommended as an effective strategy to prevent injuries among young children. Technology-based anticipatory guidance has been suggested to reinforce the effectiveness of injury prevention and improve parents' knowledge of child safety. OBJECTIVE: This study aims to examine the effectiveness of a technology-based injury prevention program with parental anticipatory guidance for enhancing mothers' knowledge of child safety. METHODS: In this randomized controlled trial, 308 mothers will be recruited from the antenatal clinics and postnatal wards of two major public hospitals in Hong Kong. Participating mothers will be randomly assigned into intervention and control groups. Mothers in the intervention group will be given free access to a technology-based injury prevention program with anticipatory guidance, whereas mothers in the control group will be given a relevant booklet on parenting. The injury prevention program, available as a website or on a mobile app, includes behavioral components based on the Theory of Planned Behavior. The primary outcome measure will be the change in the mother's knowledge of child safety. The secondary outcome measures will be age-appropriate domestic safety knowledge, attitudes, intentions, perceived behavioral control, and self-reported behavior related to home safety practice. We will also determine dose-response relationships between the outcome measures and the website and mobile app usage. RESULTS: Enrolment of participants will begin in October 2016. Results are expected by June 2018. CONCLUSIONS: Parents will be able to easily access the domestic injury prevention website to find information regarding child injury prevention. It is anticipated that the technology-based intervention will help parents improve their knowledge of child safety and raise their awareness about the consequences of domestic injuries and the importance of prevention. TRIAL REGISTRATION: Clinicaltrials.gov Clinicaltrials.gov NCT02835768; http://clinicaltrials.gov/ct2/show/NCT02835768 (Archived by WebCite at http://www.webcitation/6lbXYM6b9).