Digital Convergence & Social Psychiatry Lab.

Digital Convergence & Social Psychiatry Lab. Department of Psychiatry,
Korea University College of Medicine, Seoul, Korea

Digital Convergence & Social Psychiatry Lab.

[고대안암병원] 수면 딥 페노타이핑 연구를 참여해주실 연구 참여자(불면증상군)를 모집합니다.고려대학교 안암병원(연구책임자 : 정신건강의학과 조철현 교수)에서 진행하는 본 연구는 정상수면군부터 불면증상군까지의 연구대상...
01/02/2024

[고대안암병원] 수면 딥 페노타이핑 연구를 참여해주실 연구 참여자(불면증상군)를 모집합니다.

고려대학교 안암병원(연구책임자 : 정신건강의학과 조철현 교수)에서 진행하는 본 연구는 정상수면군부터 불면증상군까지의 연구대상자의 수면 관련 임상, 유전체, 뇌 활성도, 디지털 표현형을 통합적으로 확보하기 위해 실시하고 있습니다.

연구는 총 4주 간 진행되며, 연구 기간 동안 총 2회 병원에 방문하여 어플 설치 및 전두엽 활성도 검사(fNIRS), 웨어러블 디바이스 착용을 시행하게 됩니다 (1차 방문시 약 1시간 30분~2시간, 2차 방문시 약 15~20분 소요).
연구에 참여하시는 동안 웨어러블 디바이스를 계속 착용하셔야 하며(수면 중에도), 어플을 이용하여 매일 그 날의 수면 및 일상 정보를 입력해주시면 됩니다(매일 약 1분 소요). 연구를 모두 완료하실 경우, 총 13만 6000원의 보상이 지급됩니다. 중도 탈락할 경우 참여율에 따라 보상이 차등 지급됩니다.
진행 과정에서 참여자가 연구 참여에 어려움을 느끼지 않을 수 있도록 최선을 다할 것입니다.

이번 연구는 불면증상군을 대상으로 시행되므로, 관심 있으신 분들은 아래의 불면증 자가진단을 시행하신 후 불면증상군(15점 이상) 기준이 충족되실 경우
연구참여 링크를 통해 신청해주시기 바랍니다.

불면증 자가증단 링크 : https://goodsleep.or.kr/how_2/index.php?hca=1
연구참여 링크 : https://docs.google.com/forms/d/1uFyCzzlFaCKMUJwmPemdtvwDEVQpTL_H3J5oQyU1utA/edit

문의
- 이메일 : [email protected]

Background:During the COVID-19 pandemic, urban inhabitants faced significant challenges in maintaining connections with ...
23/01/2024

Background:
During the COVID-19 pandemic, urban inhabitants faced significant challenges in maintaining connections with nature, adhering to nutritional guidelines, and managing mental well-being.

Objective:
Recognizing the urgent need for innovative approaches, this study was designed to explore the potential benefits of a specific digital intervention, the rice-farming simulation game Sakuna: Of Rice and Ruin, for nature relatedness, nutritional behaviors, and psychological well-being.

Methods:
A total of 66 adults without any prior major psychiatric disorders residing in an urban area were recruited for the study. They were randomly assigned to 2 groups through block randomization: the immediate intervention group (IIG; 34/66, 52%) and the waitlist group (32/66, 48%). Participants in the IIG were instructed to play the game for at least 4 days per week for 3 weeks, with each session lasting from 30 minutes to 3 hours. Assessments were performed at baseline, week 1, and week 3. The Nature Relatedness Scale (NR) and Nutrition Quotient Scale were used to evaluate nature relatedness and nutritional state, respectively. Furthermore, psychological state was assessed using the World Health Organization Quality of Life–Brief Version (WHOQOL-BREF), Brief Fear of Negative Evaluation Scale, Social Avoidance and Distress Scale, Toronto Alexithymia Scale, State-Trait Anxiety Inventory, Center for Epidemiologic Studies Depression Scale Revised, and Korean Resilience Quotient.

Results:
This study’s results revealed significant time interactions between the IIG and waitlist group for both the total NR score (P=.001) and the score of the self subdomain of NR (P.05).

Conclusions:
Our findings suggest that the rice-farming game intervention might have positive effects on nature relatedness, nature-friendly dietary behaviors, quality of life, anxiety, depression, interpersonal relationships, and resilience among urban adults during the COVID-19 pandemic. The impact of pronature games in confined urban environments provides valuable evidence of how digital technologies can be used to enhance urban residents’ affinity for nature and psychological well-being. This understanding can be extended in the future to other digital platforms, such as metaverses.

Background: During the COVID-19 pandemic, urban inhabitants faced significant challenges in maintaining connections with nature, adhering to nutritional guidelines, and managing mental well-being. Objective: Recognizing the urgent need for innovative approaches, this study was designed to explore th...

A   model with wearable data from ABCD study predicts   & sleep problems in children, offering potential for early detec...
18/03/2023

A model with wearable data from ABCD study predicts & sleep problems in children, offering potential for early detection & screening via digital phenotypes. A step towards innovative evaluation methods for children's mental health.

This diagnostic study develops a machine learning model using data from wearable digital devices to detect attention-deficit/hyperactivity disorder (ADHD) and sleep problems in children.

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