This project is led by Professor MAK Winnie Wing Sze under Department of Psychology, The Chinese University of Hong Kong. It is funded by The Hong Kong Jockey Club Charities Trust.
Purpose: To examine the effectiveness of the online and offline services delivered through the platform of blended mental well-being
Target: Adults aged 18 years old or above with access to the Internet
Detail: Participants can register via an online system and gain access to the services. The services provided will be blended (online and offline modes) and participants are free to join at their own will. During the use of the platform, the system will provide different assessments and user data will be recorded for the purpose of services effectiveness evaluation.
Risk: According to the existing literature, this study does not cause any disturbance or potential risk to the participants.
Confidentiality: All data is confidential. Data transmission of the online system is encrypted. No personnel without authorization could access the data. The results of the reports will only contain overall results without individually identifiable information. Information may also be used in project promotion and planning purposes.
Participation is completely voluntary. Participants can withdraw from the study anytime without reasons and adverse consequences.
Should you have any enquiries about the study, please contact us (info@jcthplus.org). Should you have any enquires about the rights of research participants, please contact the Joint Chinese University of Hong Kong – New Territories East Cluster Clinical Research Ethics Committee (3505 3935 / crec@cuhk.edu.hk).
If you agree to join the study and understand the following:
- I understand the purpose, procedure and risk of the study
- I understand that I can raise my questions about the study to the researcher anytime
- I understand that my participation is voluntary and I can withdraw anytime
- I understand that the data is confidential and only for research and ethics review
- I understand that results of the data will be published and no individuals will be identified
- I understand that users’ data will be stored in the server for data and research analysis
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