Hyein Jeong¹, Soobin Jang², Bo-Hyoung Jang¹, Chunhoo Cheon¹, Taek Gyu Kim³, Chan Ho Ju³, Hwimun Kim⁴, Su Yong Shin⁵, Kyeong Han Kim^6,*, Seong-Gyu Ko^1,*

International Journal of Mental Health Promotion, Vol.27, No.11, pp. 1695-1708, 2025, DOI:10.32604/ijmhp.2025.071014 - 28 November 2025

Abstract Objectives: This study aimed to evaluate the clinical effectiveness, durability, and acceptability of a Korean medicine-based online mental health self-care program for mothers. Methods: This non-randomized comparative study evaluated the clinical effectiveness, durability, and acceptability of a Korean medicine-based online mental health self-care program for mothers. Group 1 (regular version) included 120 participants who attended one live session per week for 5 weeks, while Group 2 (shortened version) included 30 participants who completed five recorded sessions within 1 week. A total of 112 participants (93.3%) in Group 1 and all 30 participants (100%) in Group 2… More >

Mely Ruiz-Aquino¹, Viter Gerson Carlos Trinidad^1,2, Aldo Alvarez-Risco³, Jaime A. Yáñez^4,5,*

International Journal of Mental Health Promotion, Vol.24, No.6, pp. 959-974, 2022, DOI:10.32604/ijmhp.2022.021172 - 28 September 2022

Abstract The general objective of this article was to construct and describe the psychometric properties of a scale of selfcare behaviors against COVID-19. It was a descriptive, cross-sectional, psychometric validation study of a scale created to measure self-care behaviors in relation to COVID-19 in a total sample of 333 probabilistically selected. Qualitative validity was evaluated by a review of 10 experts and quantitative validity by means of exploratory factor analysis using the principal components method. Internal consistency was measured with Cronbach’s alpha twice and the test-retest was evaluated by calculating the intraclass coefficient. The final scale… More >

Mouazma Batool¹, Yazeed Yasin Ghadi², Suliman A. Alsuhibany³, Tamara al Shloul⁴, Ahmad Jalal¹, Jeongmin Park^5,*

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1747-1764, 2022, DOI:10.32604/cmc.2022.025112 - 24 February 2022

Abstract Nowadays, activities of daily living (ADL) recognition system has been considered an important field of computer vision. Wearable and optical sensors are widely used to assess the daily living activities in healthy people and people with certain disorders. Although conventional ADL utilizes RGB optical sensors but an RGB-D camera with features of identifying depth (distance information) and visual cues has greatly enhanced the performance of activity recognition. In this paper, an RGB-D-based ADL recognition system has been presented. Initially, human silhouette has been extracted from the noisy background of RGB and depth images to track More >