Social Behavior Analysis and Thai Mental Health Questionnaire (TMHQ) Optimization for Depression Detection System

Konlakorn WONGAPTIKASEREE; Panida YOMABOOT; Kantinee KATCHAPAKIRIN; Yongyos KAEWPITAKKUN

doi:10.1587/transinf.2019IIP0003

Social Behavior Analysis and Thai Mental Health Questionnaire (TMHQ) Optimization for Depression Detection System

Konlakorn WONGAPTIKASEREE, Panida YOMABOOT, Kantinee KATCHAPAKIRIN, Yongyos KAEWPITAKKUN

Full Text Views

0

Cite this

Summary :

Depression is a major mental health problem in Thailand. The depression rates have been rapidly increasing. Over 1.17 million Thai people suffer from this mental illness. It is important that a reliable depression screening tool is made available so that depression could be early detected. Given Facebook is the most popular social network platform in Thailand, it could be a large-scale resource to develop a depression detection tool. This research employs techniques to develop a depression detection algorithm for the Thai language on Facebook where people use it as a tool for sharing opinions, feelings, and life events. To establish the reliable result, Thai Mental Health Questionnaire (TMHQ), a standardized psychological inventory that measures major mental health problems including depression. Depression scale of the TMHQ comprises of 20 items, is used as the baseline for concluding the result. Furthermore, this study also aims to do factor analysis and reduce the number of depression items. Data was collected from over 600 Facebook users. Descriptive statistics, Exploratory Factor Analysis, and Internal consistency were conducted. Results provide the optimized version of the TMHQ-depression that contain 9 items. The 9 items are categorized into four factors which are suicidal ideation, sleep problems, anhedonic, and guilty feelings. Internal consistency analysis shows that this short version of the TMHQ-depression has good to excellent reliability (Cronbach's alpha >.80). The findings suggest that this optimized TMHQ-depression questionnaire holds a good psychometric property and can be used for depression detection.

Publication: IEICE TRANSACTIONS on Information Vol.E103-D No.4 pp.771-778

Publication Date: 2020/04/01

Publicized: 2020/01/21

Online ISSN: 1745-1361

DOI: 10.1587/transinf.2019IIP0003

Type of Manuscript: Special Section PAPER (Special Section on Intelligent Information and Communication Technology and its Applications to Creative Activity Support)

Category

Authors

Konlakorn WONGAPTIKASEREE
  Mahidol University
Panida YOMABOOT
  Mahidol University
Kantinee KATCHAPAKIRIN
  Asian Institute of Technology
Yongyos KAEWPITAKKUN
  Pordeekum.AI company

Keyword

depression detection, psychological inventory, social behavior analysis, TMHQ

Cite this

Copy

Konlakorn WONGAPTIKASEREE, Panida YOMABOOT, Kantinee KATCHAPAKIRIN, Yongyos KAEWPITAKKUN, "Social Behavior Analysis and Thai Mental Health Questionnaire (TMHQ) Optimization for Depression Detection System" in IEICE TRANSACTIONS on Information, vol. E103-D, no. 4, pp. 771-778, April 2020, doi: 10.1587/transinf.2019IIP0003.
Abstract: Depression is a major mental health problem in Thailand. The depression rates have been rapidly increasing. Over 1.17 million Thai people suffer from this mental illness. It is important that a reliable depression screening tool is made available so that depression could be early detected. Given Facebook is the most popular social network platform in Thailand, it could be a large-scale resource to develop a depression detection tool. This research employs techniques to develop a depression detection algorithm for the Thai language on Facebook where people use it as a tool for sharing opinions, feelings, and life events. To establish the reliable result, Thai Mental Health Questionnaire (TMHQ), a standardized psychological inventory that measures major mental health problems including depression. Depression scale of the TMHQ comprises of 20 items, is used as the baseline for concluding the result. Furthermore, this study also aims to do factor analysis and reduce the number of depression items. Data was collected from over 600 Facebook users. Descriptive statistics, Exploratory Factor Analysis, and Internal consistency were conducted. Results provide the optimized version of the TMHQ-depression that contain 9 items. The 9 items are categorized into four factors which are suicidal ideation, sleep problems, anhedonic, and guilty feelings. Internal consistency analysis shows that this short version of the TMHQ-depression has good to excellent reliability (Cronbach's alpha >.80). The findings suggest that this optimized TMHQ-depression questionnaire holds a good psychometric property and can be used for depression detection.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2019IIP0003/_p

Copy

@ARTICLE{e103-d_4_771,
author={Konlakorn WONGAPTIKASEREE, Panida YOMABOOT, Kantinee KATCHAPAKIRIN, Yongyos KAEWPITAKKUN, },
journal={IEICE TRANSACTIONS on Information},
title={Social Behavior Analysis and Thai Mental Health Questionnaire (TMHQ) Optimization for Depression Detection System},
year={2020},
volume={E103-D},
number={4},
pages={771-778},
abstract={Depression is a major mental health problem in Thailand. The depression rates have been rapidly increasing. Over 1.17 million Thai people suffer from this mental illness. It is important that a reliable depression screening tool is made available so that depression could be early detected. Given Facebook is the most popular social network platform in Thailand, it could be a large-scale resource to develop a depression detection tool. This research employs techniques to develop a depression detection algorithm for the Thai language on Facebook where people use it as a tool for sharing opinions, feelings, and life events. To establish the reliable result, Thai Mental Health Questionnaire (TMHQ), a standardized psychological inventory that measures major mental health problems including depression. Depression scale of the TMHQ comprises of 20 items, is used as the baseline for concluding the result. Furthermore, this study also aims to do factor analysis and reduce the number of depression items. Data was collected from over 600 Facebook users. Descriptive statistics, Exploratory Factor Analysis, and Internal consistency were conducted. Results provide the optimized version of the TMHQ-depression that contain 9 items. The 9 items are categorized into four factors which are suicidal ideation, sleep problems, anhedonic, and guilty feelings. Internal consistency analysis shows that this short version of the TMHQ-depression has good to excellent reliability (Cronbach's alpha >.80). The findings suggest that this optimized TMHQ-depression questionnaire holds a good psychometric property and can be used for depression detection.},
keywords={},
doi={10.1587/transinf.2019IIP0003},
ISSN={1745-1361},
month={April},}

Copy

TY - JOUR
TI - Social Behavior Analysis and Thai Mental Health Questionnaire (TMHQ) Optimization for Depression Detection System
T2 - IEICE TRANSACTIONS on Information
SP - 771
EP - 778
AU - Konlakorn WONGAPTIKASEREE
AU - Panida YOMABOOT
AU - Kantinee KATCHAPAKIRIN
AU - Yongyos KAEWPITAKKUN
PY - 2020
DO - 10.1587/transinf.2019IIP0003
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E103-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 2020
AB - Depression is a major mental health problem in Thailand. The depression rates have been rapidly increasing. Over 1.17 million Thai people suffer from this mental illness. It is important that a reliable depression screening tool is made available so that depression could be early detected. Given Facebook is the most popular social network platform in Thailand, it could be a large-scale resource to develop a depression detection tool. This research employs techniques to develop a depression detection algorithm for the Thai language on Facebook where people use it as a tool for sharing opinions, feelings, and life events. To establish the reliable result, Thai Mental Health Questionnaire (TMHQ), a standardized psychological inventory that measures major mental health problems including depression. Depression scale of the TMHQ comprises of 20 items, is used as the baseline for concluding the result. Furthermore, this study also aims to do factor analysis and reduce the number of depression items. Data was collected from over 600 Facebook users. Descriptive statistics, Exploratory Factor Analysis, and Internal consistency were conducted. Results provide the optimized version of the TMHQ-depression that contain 9 items. The 9 items are categorized into four factors which are suicidal ideation, sleep problems, anhedonic, and guilty feelings. Internal consistency analysis shows that this short version of the TMHQ-depression has good to excellent reliability (Cronbach's alpha >.80). The findings suggest that this optimized TMHQ-depression questionnaire holds a good psychometric property and can be used for depression detection.
ER -