five

Can combining mHealth computerized CBT with post-learning oscillatory modulation optimize and stabilize improvements in self-esteem? A randomized controlled trial

收藏
Figshare2024-11-21 更新2026-04-08 收录
下载链接:
https://figshare.com/articles/dataset/Can_combining_mHealth_computerized_CBT_with_post-learning_oscillatory_modulation_optimize_and_stabilize_improvements_in_self-esteem_A_randomized_controlled_trial/27022297/2
下载链接
链接失效反馈
官方服务:
资源简介:
Self-esteem, crucial for psychological well-being, can be enhanced through targeted interventions like Cognitive Behavioral Therapy (CBT). However, traditional CBT faces accessibility barriers, and its benefits may diminish over time. Digital health interventions such as computerized CBT and mobile health (mHealth) applications offer potential solutions. Recent research suggests that brain oscillations, particularly theta rhythms, play a key role in memory consolidation. Combining computerized CBT with post-learning theta rhythm modulation may optimize and stabilize improvements in self-esteem and promote neuro-wellbeing. This six-month longitudinal study aimed to evaluate the synergistic effects of a computerized CBT intervention (GGSE) combined with post-training theta rhythm brain modulation on improving self-esteem in young adults with low self-esteem. Participants were randomly allocated to three groups: GGSE + theta Audio-Visual Entrainment (AVE) with Cranio-Electro Stimulation (CES), GGSE + beta AVE+CES (active control), and GGSE only (control). The intervention lasted three weeks. Assessments of self-esteem, maladaptive beliefs, and mood were conducted at baseline, 21 days, 42 days, and six months post-baseline. Although post-treatment oscillatory entrainment did not enhance the long-term efficacy of the intervention, treatment effects persisted for six months across all groups. These results support the potential long-term efficacy of brief, game-like, digital CBT approaches for improving self-esteem.
提供机构:
Shtoots, Limor; Levy, Daniel; Doron, Guy; Gamoran, Avi; Nadler, Asher
创建时间:
2024-11-21
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作