A Digital Game and School-Based Intervention for Students in Hong Kong: Quasi-Experimental Design.

BACKGROUND: In Hong Kong, with an increasing number of children experiencing mental health issues, there is a need to not only develop innovative interventions but also develop comprehensive prevention interventions so as to reduce their anxiety symptoms and enhance their emotional management and interpersonal relationships. OBJECTIVE: The aim of this study was to determine the effectiveness of The Adventures of DoReMiFa, an integration model of the cognitive-behavioral approach and positive psychology by using digital game-based and school-based mental health enhancement intervention to magnify the social and emotional health and well-being of the school children in Hong Kong aged 9 to 11 years. METHODS: A quasi-experimental design method was used to evaluate this digital game and school-based intervention. The Adventures of DoReMiFa was piloted in 4 primary schools where students were allocated to either an intervention or a control group. The participants were assessed at pre- and postintervention with a 6-month follow-up measuring their mental health knowledge, levels of anxiety symptoms, positive and negative thinking, perspective-taking, and self-esteem. RESULTS: A total of 459 primary school students from 4 primary schools participated in the study. The response rate on the questionnaires answered on the Web was up to 85.1% (391/459). Compared with the control group, the intervention group was found to have significant association with improved mental health knowledge at the time immediately after the intervention (beta=.46; P=.01) and in the 6-month postintervention period (beta=.66; P<.001); for perspective-taking, the intervention group had exhibited a significant improvement 6 months after the completion of the universal program (beta=1.50; P=.03). The intervention, however, was found not to be effective in reducing the rates of anxiety symptoms and negative thinking among the participating students. CONCLUSIONS: The Adventures of DoReMiFa, an integration of a digital game-based and school-based mental health enhancement intervention, was shown to be effective in elevating the knowledge of mental health and promoting perspective-taking in the primary school students of Hong Kong. Although there was insufficient evidence to support a reduction in symptoms of anxiety and negative automatic thoughts, the overall results were still encouraging in that a preventive effect was found, indicating that the program has the potential to enhance the mental well-being of schoolchildren. It also suggests that knowledge enhancement may not necessarily lead to behavior change, and more focused effort may be needed to achieve the translation. The implications and limitations of this study and suggestions for future research were also discussed.

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.

The diffusion of a new method of suicide: charcoal-burning suicide in Hong Kong and Taiwan.

PURPOSE: In the late 1990s, an epidemic rise in suicides by carbon monoxide poisoning from burning barbecue charcoal began in Hong Kong and Taiwan. This study investigates the diffusion of this new method of suicide. METHOD: Official mortality data for 1998-2010 in Taiwan and 1998-2009 in Hong Kong were collected; overall and method-specific suicide rates in different socio-demographic subgroups over the study period were compared. Multiple logistic regression analyses were conducted to assess the socio-demographic risk factors for charcoal-burning vs. non-charcoal-burning suicide. RESULTS: In Hong Kong, the incidence of charcoal-burning suicide increased steeply within 1 year of the first reported cases, but its use has declined from 24.2% of all suicides during the peak period (2002-2004) to 17.1% (2007-2009); in Taiwan, the pace of diffusion was slower in onset, but it remains a popular method accounting for 31.0% of all suicides in 2008-2010. The early adopters in both places tended to be young- and middle-aged men. As the epidemic progressed, the method has also been gradually adopted by older age groups and women, particularly in Taiwan, but in 2009/10, the method still accounted for <8% of suicides in those aged >60 years in both areas. CONCLUSIONS: Common features of the epidemic in both places were the greater levels of early uptake by the young- and middle-aged males. The different course of the charcoal-burning suicide epidemic may reflect social, geographic and media reporting differences. Surveillance to identify the emergence of new suicide methods is crucial in suicide prevention.

Prevalence of hikikomori and associations with suicidal ideation, suicide stigma, and help-seeking among 2,022 young adults in Hong Kong.

BACKGROUND: Young adults are at elevated risks of hikikomori (severe social withdrawal) under the COVID-19 pandemic, which could lead to psychological distress and suicidal ideation. AIMS: The present study aimed to examine the associations among hikikomori, suicide stigma, suicidal ideation, and help-seeking behaviors among young adults in Hong Kong. METHOD: This study recruited a large sample of 2,022 young adults in Hong Kong via an online survey at the end of 2021. The participants completed the Hikikomori Questionnaire and validated measures on psychological distress, suicide stigma, and suicidal ideation severity and report their help-seeking behaviors. Multivariate analysis of variance was conducted to compare the profiles of the hikikomori groups. Path analysis evaluated the effects of hikikomori and suicide stigma on occurrence and severity of suicidal ideation and their associations with help-seeking behaviors. RESULTS: Hikikomori showed significant and positive indirect effects on prevalence and severity of suicidal ideation via psychological distress. Glorification positively predicted hikikomori and suicidal ideation severity among suicidal persons. Hikikomori was associated with reduced help-seeking. Isolation and suicidal ideation were associated with greater barriers to seek help among the non-help-seekers. Perceived helpfulness of sought help was negatively associated with hikikomori and suicidal ideation among the help-seekers. CONCLUSIONS: The present findings demonstrated greater prevalence and severity of suicidal ideation and less help-seeking in young adults with hikikomori. Suicide stigma showed differential associations with hikikomori, suicidal ideation, and help-seeking behaviors.

A Decomposition of Life Expectancy and Life Disparity: Comparison Between Hong Kong and Japan.

BACKGROUND: Life expectancy and life disparity are 2 useful indicators to assess the health condition of a society. Both Hong Kong and Japan have one of the longest life expectancies in the world. Recently, Hong Kong has overtaken Japan and topped the life expectancy rankings. However, whether Hong Kong has also outperformed Japan in life disparity is still unknown. METHODS: Decomposition analyses have been conducted to evaluate age-specific contributions to the changes in life expectancy and life disparity for each of the populations. Furthermore, the differences between the 2 populations were examined over the period 1977-2016. RESULTS: Reduction in mortality of the adult and the old age groups contributes most to the increase in life expectancy for the study period. Hong Kong has a higher life disparity than Japan, and due to the great improvement in reducing premature deaths, the Hong Kong-Japan gap has been narrowing. However, in recent years, further reduction in mortality of the oldest elderly in Hong Kong has actually contributed to the increase in its disparity, thus widening its gap with Japan again. CONCLUSION: Increasing dominant influence of "saving lives at late ages" is very likely to cause the reemergence of increasing life disparity in these 2 long-lived populations.

A study of sexual satisfaction and frequency of sex among Hong Kong Chinese couples.

There have been several studies in Western societies on the causes and consequences of sexual satisfaction within marriage. Little is known, however about the marital sexual relationship in Chinese societies. Moreover, most published studies used married individuals rather than married couples as participants. The present study examined data from a well-established knowledge, attitude, and practice (KAP) survey of 1,124 Hong Kong Chinese couples on martial sexual relationship. A conceptual model was tested using structural equation modeling (SEM). Interest in sex was found to be the strongest predictor of both sexual satisfaction and frequency of sex for both husbands and wives. Among the sociodemographic variables, the following two were significantly associated with lower frequencies of sex: for wives, that of having a full-time job; and for husbands, the factor of age. Theoretical implications for research on the interplay among culture, marriage, and sex in non-Western societies are discussed.

The Contribution of Ageing to Hospitalisation Days in Hong Kong: A Decomposition Analysis.

BACKGROUND: Ageing has become a serious challenge in Hong Kong and globally. It has serious implications for health expenditure, which accounts for nearly 20% of overall government expenditure. Here we assess the contribution of ageing and related factors to hospitalisation days in Hong Kong. We used hospital discharge data from all publicly funded hospitals in Hong Kong between 2001 and 2012. METHODS: A decomposition method was used to examine the factors that account for the change of total hospitalisation days during the two periods, 2001-2004 and 2004-2012. The five factors include two demographic factors - population size and age-gender composition - and three service components - hospital discharge rate, number of discharge episodes per patient, and average length of stay (LOS) - which are all measured at age-gender group level. In order to assess the health cost burden in the future, we also project the total hospitalisation days up to 2041, for a range of scenarios. RESULTS: During the decreasing period of hospitalisation days (2001-2004), the reduction of LOS contributed to about 60% of the reduction. For the period of increase (2004-2012), ageing is associated with an increase in total hospitalisation days of 1.03 million, followed by an increase in hospital discharge rates (0.67 million), an increase in the number of discharge episodes per patient (0.62 million), and population growth (0.43 million). The reduction of LOS has greatly offset these increases (-2.19 million days), and has become one of the most significant factors in containing the increasing number of hospitalisation days. Projected increases in total hospitalisation days under different scenarios have highlighted that the contribution of ageing will become even more prominent after 2022. CONCLUSION: Hong Kong is facing increasing healthcare burden caused by the rapid increase in demand for inpatient services due to ageing. Better management of inpatient services with the aim of increasing efficiency and reducing LOS, avoidable hospitalisation and readmission, without compromising patient satisfaction and quality of service, are crucial for containing the rapid and enormous increases in total hospitalisation days for Hong Kong. The results would be relevant to many rapidly ageing societies in this region.

Evaluation of a Digital Game-Based Learning Program for Enhancing Youth Mental Health: A Structural Equation Modeling of the Program Effectiveness.

BACKGROUND: Digital game-based learning (DGBL) makes use of the entertaining power of digital games for educational purposes. Effectiveness assessment of DGBL programs has been underexplored and no attempt has been made to simultaneously model both important components of DGBL: learning attainment (ie, educational purposes of DGBL) and engagement of users (ie, entertaining power of DGBL) in evaluating program effectiveness. OBJECTIVE: This study aimed to describe and evaluate an Internet-based DGBL program, Professor Gooley and the Flame of Mind, which promotes mental health to adolescents in a positive youth development approach. In particular, we investigated whether user engagement in the DGBL program could enhance their attainment on each of the learning constructs per DGBL module and subsequently enhance their mental health as measured by psychological well-being. METHODS: Users were assessed on their attainment on each learning construct, psychological well-being, and engagement in each of the modules. One structural equation model was constructed for each DGBL module to model the effect of users' engagement and attainment on the learning construct on their psychological well-being. RESULTS: Of the 498 secondary school students that registered and participated from the first module of the DGBL program, 192 completed all 8 modules of the program. Results from structural equation modeling suggested that a higher extent of engagement in the program activities facilitated users' attainment on the learning constructs on most of the modules and in turn enhanced their psychological well-being after controlling for users' initial psychological well-being and initial attainment on the constructs. CONCLUSIONS: This study provided evidence that Internet intervention for mental health, implemented with the technologies and digital innovations of DGBL, could enhance youth mental health. Structural equation modeling is a promising approach in evaluating the effectiveness of DGBL programs.

Identifying Chinese Microblog Users With High Suicide Probability Using Internet-Based Profile and Linguistic Features: Classification Model.

BACKGROUND: Traditional offline assessment of suicide probability is time consuming and difficult in convincing at-risk individuals to participate. Identifying individuals with high suicide probability through online social media has an advantage in its efficiency and potential to reach out to hidden individuals, yet little research has been focused on this specific field. OBJECTIVE: The objective of this study was to apply two classification models, Simple Logistic Regression (SLR) and Random Forest (RF), to examine the feasibility and effectiveness of identifying high suicide possibility microblog users in China through profile and linguistic features extracted from Internet-based data. METHODS: There were nine hundred and nine Chinese microblog users that completed an Internet survey, and those scoring one SD above the mean of the total Suicide Probability Scale (SPS) score, as well as one SD above the mean in each of the four subscale scores in the participant sample were labeled as high-risk individuals, respectively. Profile and linguistic features were fed into two machine learning algorithms (SLR and RF) to train the model that aims to identify high-risk individuals in general suicide probability and in its four dimensions. Models were trained and then tested by 5-fold cross validation; in which both training set and test set were generated under the stratified random sampling rule from the whole sample. There were three classic performance metrics (Precision, Recall, F1 measure) and a specifically defined metric "Screening Efficiency" that were adopted to evaluate model effectiveness. RESULTS: Classification performance was generally matched between SLR and RF. Given the best performance of the classification models, we were able to retrieve over 70% of the labeled high-risk individuals in overall suicide probability as well as in the four dimensions. Screening Efficiency of most models varied from 1/4 to 1/2. Precision of the models was generally below 30%. CONCLUSIONS: Individuals in China with high suicide probability are recognizable by profile and text-based information from microblogs. Although there is still much space to improve the performance of classification models in the future, this study may shed light on preliminary screening of risky individuals via machine learning algorithms, which can work side-by-side with expert scrutiny to increase efficiency in large-scale-surveillance of suicide probability from online social media.