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Mental illness presents a huge individual, societal and economic challenges, currently accounting for 20% of the worldwide burden of disease. There is a gap between the need for and access to services. Digital technology has been proven effective in e-mental health for preventing and treating mental health problems. However, there is a need for cross-disciplinary efforts to increase the impact of e-mental health services. This paper aims to report key challenges and possible solutions for cross-disciplinary and cross-sectorial research teams within the domain of e-mental health.

The key challenges and possible solutions will be discussed in light of the literature on effective cross-disciplinary research teams.

Six topics have been key challenges in our cross-disciplinary and cross-sectorial research team: to develop a shared understanding of the domain; to establish a common understanding of key concepts among the project participants; to involve the end-users in the research and development process; to collaborate across sectors; to ensure privacy and security of health data; and to obtain the right timing of activities according to project dependencies.

This study focuses to increase knowledge and training in cross-disciplinary and cross-sectorial research, as this is often referred to as an important tool when developing sustainable solutions for major societal challenges.

This study needs to include theory and skills training in cross-disciplinary research in research training.

Cross-disciplinary teams have the potential to address major societal challenges, including more perspectives and more stakeholders than single disciplinary research teams.

Major societal challenges require complex and sustainable solutions. However, there is a lack of knowledge about how cross-disciplinary and cross-sectorial research teams may work productively to solve these challenges. This paper shares experiences regarding the challenges and possible solutions for productive collaboration in cross-disciplinary and cross-sectorial research teams within the domain of e-mental health services.

The emergence of COVID-19 and its spread led to severe social, economic and livelihood impacts around the world. This study documented the socioeconomic impacts of COVID-19 outbreaks and lockdown on the lower-income groups. Also illustrated the impacts on the attainment of SDGs in the context of the slums of Chittagong City.

Both qualitative and quantitative data have been collected from the 150 respondents through questionnaire surveys in the slums.

The lockdown led to the decrease of 90% of the respondents' income level and affected the livelihoods of 97.33% of the respondents, with an overall score of 3.22 ± 0.67 on a four-point Likert-type scale. About 96.67% of respondents' psychological conditions have been affected high to extreme, with an overall score of 3.19 ± 0.68. The pandemic affected 74.67% of respondents' food habits, 95.33% of respondents' child education, increased domestic violence and deteriorated social security, basic service facilities and hygiene practices among the slum dwellers. The severity of COVID-19 outbreaks on the lower-income people makes it critical for the government to attain the SDG 1, SDG 2, SDG 3, SDG 4, SDG 5 (Target 5.1, 5.2) SDG 6 and SDG 16.

The findings of the study will help governments, policymakers, international organizations to adopt measures to mitigate the effects of the outbreaks.

Shorter lead time with low price and quality product demand is pivotal in the garment industry. Pressure on production lead time stresses the importance of reducing style changeover time in manufacturing factories, and this paper aims to contribute to solving the challenge by showing how the single minute exchange of die (SMED) methodology in practice can be adapted to garment factories in developing countries.

The paper investigates three cases of SMED implementation integrated with responsible, accountable, consulted, informed (RACI) matrices in garment factories in an action research approach. Both quantitative and qualitative methods are applied.

The study shows a reduction of 50% to 64% of changeover time with SMED implementation measured with two key indicators – throughout time and time to reach peak production. Moreover, the implementation depends on the application of the RACI matrix for the distribution of responsibility as well as integration with the basic production flow before and after the application of SMED.

The study can guide better SMED implementation in garment factories with limited investment by stressing the need to adapt to the specifics of the garment industry, secure the division of responsibility and integrate SMED in the production flow before and after the changeover.

Limited research on the application of SMED in the garment industry. This paper contributes to understanding the specific conditions for successful implementation in the garment industry in developing countries and addresses additional activities that help secure a sustainable implementation process.