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Aims primarily to examine how stressful kindergarten principals as leaders and managers of their schools found their work to be, and if such job stress was related to negative emotions and job satisfaction. The secondary aim was to explore if social support from a close friend could reduce and buffer job stress. Seventy‐seven kindergarten principals in Hong Kong responded to a questionnaire containing the variables of interest. The results showed that the principals found their work to be moderately stressful. However, emotional and informational support from a close friend had beneficial impacts on stress.

The purpose of this paper is to evaluate and compare the effectiveness of two intervention formats of the Positive Parenting Programme (Triple P) – Level 4 Group Triple P (TP) and brief parent discussion group (DI) with the waitlist control group (WL).

Participants included 91 Chinese parents with preschool children in Hong Kong from eight preschools, who were randomised into the two intervention conditions (TP and DI) and a waitlist control group (WL). Parent participants completed measures on child behaviours and parenting stress before and after intervention.

Results indicated that there was a significant decrease in post-intervention child behavioural problems in the TP group, with a medium effect size when compared to the WL group. There was a decrease in post-intervention child behaviour problems in the DI group, compared with the WL group. No significant difference was found in post-intervention child behaviour problems between the TP group and the DI group.

The positive results in the present study support the extension of the implementation of Triple P interventions to the preschool setting in Hong Kong. The effectiveness of the brief parent discussion group in reducing parental report of child behaviour problems provides preliminary support for its potential as a universal preventive parenting intervention in the local context.

The study was the first evaluation of the Level-4 Triple P programme in a local school context as well as the first evaluation of effectiveness of the brief parent discussion group in the local context at the time of the study.

This paper aims to examine the housing market responses to two outbreaks of respiratory diseases in Hong Kong during the Information Era – the 2003 SARS and COVID-19 outbreaks.

The authors first investigate the aggregate housing price changes during SARS and COVID-19. Next, the authors conduct a battery of univariate analyses pertaining to the relationship between district-level housing price movements and geographic and demographic patterns during the pandemic periods. Finally, to shed light on the housing price dynamics at the micro level, the authors conduct an estate-level analysis with the data of 234 residential estates from 2003 to 2020, focusing on the impacts of SARS and COVID-19 on the idiosyncratic volatility of residential estates.

Overall, SARS and COVID-19 outbreaks are negatively associated with housing prices. However, unlike SARS, the impact of COVID-19 on housing prices was moderate and transient. The geographic imbalances of the epidemic-induced underperformance are observed at the district and estate levels. Finally, the estate-level analysis presented in this paper indicates that the average idiosyncratic volatility of residential estates is 1.5% higher during the SARS period but 3.7% lower during the COVID-19 period. Lower volatility during COVID-19 is likely explained by household learning from the SARS period.

Regulators and investors could resort to efficient information disclosure to attenuate idiosyncratic volatility's adverse impact on housing market returns.

To the best of the authors’ knowledge, the authors are among the first to examine housing market responses to the 2003 SARS and COVID-19 outbreaks using the Hong Kong housing market as a laboratory.

This paper aims to discover why such a public partnership project had been successful with a non-profit third-party alliance such as a smart city consortium (SCC) promoting smart city development.

This descriptive case study is primarily based on analysing data collected from various texts, public statements, media interviews and three semi-structured interviews with key members involved in the Covid-19 dashboard project.

The data and analysis reviews that both interpersonal and interorganisational trust, dedication and proactiveness of the leaders at SCC were major contributing factors to why SCC was able to partner with the Hong Kong Government in the Covid-19 dashboard in the first place and that the success was also a direct outcome of effective mass collaborative knowledge management activities.

The research in leadership attributes and activities in the non-profit alliance has been few and this collaborative partnership between the alliance and the government is an example of the importance of further research in smart city leadership.

In deploying projects for mass collaboration and knowledge sharing in smart city development (which is multi-disciplinary in nature). there are still many new and evolving organisational practices and leadership matters that many business leaders and city managers can learn from.

Smart city development projects involve the notion of sharing data in an open environment enabled by software and mediating tools. Successful projects such as this Hong Kong Covid-19 dashboard which serves a diverse audience can further promote the importance of an open data policy regime for the benefit of the public.

This case study covers a highly original and unique case study with the leaders at the SCC and representatives from the Hong Kong Government.

The purpose of this study is to evaluate the association between economic activity in a country, as measured by the gross domestic product (GDP) and the control of the COVID-19 pandemic outcomes, as measured by the rate of incidence and mortality increase per 100,000 population in different countries using up-to-date data, in the light of public health security capacities including prevention, detection, respond, enabling function, operational readiness, as measured by the 2019 State Party self-assessment annual reporting (SPAR) submissions of 100 countries.

For this analytical study, multiple linear regression analyses were performed for each variable with the COVID-19 incidence and mortality rates, while controlling for Human Development Index (HDI) and GDP.

Countries with higher income levels were significantly more likely to have a higher incidence and mortality rate per 100,000 population. Among the public health capacity categories, prevention of the infectious disease and detection of the pathogens were significantly associated with lower incidence and mortality of the COVID-19 pandemic. The country-level income was found to be an important negative predictor of COVID-19 control.

These findings present to decision-makers in organizing mitigation strategies to struggle emerging infectious pandemics and highlight the role of country-level income while trying to control COVID-19. In order to determine the priority settings for the fight against pandemic, national policy-makers and international organizations should notice that countries in a high-income group had better health security capacities than that of other income groups, particularly in low- and lower-middle-income groups. The results of the capabilities of health security by the income group can assist health policy makers and other international agencies in resource allocation decisions and in mitigating risk with more informed resource planning.

The income level of countries may have a positive effect on public health strategies to mitigate the risk of infection of COVID-19. This study may assist the local public authorities to gain a better level of understanding on the relationship country-level income and COVID-19 outcomes in order to take appropriate measures at the local level. The results also highlighted the importance role of public health security capacities for the pandemic control policy.

Although previous studies have examined to assess the public health capability by country-level and to describe cases and deaths by continent and by country, very limited studies have evaluated the rate of incidence and mortality of COVID-19 by country-level income and by health expenditure using the data on the health security capacities with analytical and practical approaches.

The purpose of this paper, a meta-analysis and systematic review of Mental Health First Aid (MHFA), is to focus on studies that reported trainees’ mental health literacy, attitudes and helping-related behaviors, as well as the impact of the program for the people who came into contact with trainees (i.e. recipients).

A systematic search included several online databases of published studies, dissertations or theses, and journals commonly publishing research in this area. Studies were randomized or non-randomized control trials using an intervention based upon the adult or youth MHFA curriculum.

Of the 8,257 initial articles, 16 met inclusion criteria. Small-to-moderate effect sizes (Hedges’ g=0.18–0.53) were found for the primary outcomes for the trainees with effects appearing to be maintained at follow-up. Study quality was inversely associated with effect size. No evidence of investigator allegiance was detected. Few studies examined the effects for those who received aid from a MHFA trainee. Preliminary quantitative evidence appeared lacking (Hedges’ g=−0.04 to 0.12); furthermore, a qualitative review found limited positive effects.

MHFA trainees appear to benefit from MHFA; however, objective behavioral changes are in need of greater emphasis. Additionally, considerably greater attention and effort in testing effects on distressed recipients is needed with future empirical investigations.

This is the first known review that includes preliminary findings on the effects of MHFA on the distressed recipients of the aid. It is anticipated that this will prompt further investigation into the impact of MHFA.

Investigating the subjective breathing resistance of wearing respirators requires a valid and reliable technique to measure breathing resistance. The purpose of this study is to test the validity and reliability of several rating scales and select the best for investigation of breathing resistance.

The authors designed three scales, that is, BRX scale, CP-100 scale and RVAS scale, and 30 subjects were separated into three groups, each group with a different scale. They sat for 5 min and walked for 5 min while wearing three models of respirators. After each trial, subjects were asked to complete subjective ratings of breathing resistance. Reliability was examined by the coefficient of Cronbach’s α, and validity was examined through content validity, discriminant validity and criterion validity. Generally, subjects were capable of reporting their sensation of breathing resistance by using the rating scale technique. However, the accuracy of rating strongly depended upon the properties of the scale.

The CP-100 scale was found to be highly reliable and most valid for rating subjective breath resistance. The validated CP-100 scale is very sensitive and accurate.

This is the first paper to select the best subjective scale for investigation of breathing resistance of respirators. The CP-100 scale will find wide applications in subjective breathing resistance evaluation for the use of respirators in industrial benchmarking activities. It will introduce the human factor engineering into the respirator manufacturing to improve the comfort of respirators.

Breathing resistance is the main factor that influences the wearing comfort of respirators. This paper aims to demonstrate the feasibility of using the gene expression programming (GEP) for the purpose of predicting subjective perceptions of breathing resistances of wearing respirators via surface electromyography (sEMG) and respiratory signals (RSP) sensors.

The authors developed a physiological signal monitoring system with a specific garment. The inputs included seven physical measures extracted from (RSP) and (sEMG) signals. The output was the subjective index of breathing resistances of wearing respirators derived from the category partitioning-100 scale with proven levels of reliability and validity. The prediction model was developed and validated using data collected from 30 subjects and 24 test combinations (12 respirator conditions × 2 motion conditions). The subjects evaluated 24 conditions of breathing resistances in repeated measures fashion.

The results show that the GEP model can provide good prediction performance (R² = 0.71, RMSE = 0.11). This study demonstrates that subjective perceptions of breathing resistance of wearing respirators on the human body can be predicted using the GEP via sEMG and RSP in real-time, at little cost, non-invasively and automatically.

This is the first paper suggesting that subjective perceptions of subjective breathing resistances can be predicted from sEMG and RSP sensors using a GEP model, which will remain helpful to the scientific community to start further human-centered research work and product development using wearable biosensors and evolutionary algorithms.