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Background: People share health-related experiences and treatments, such as for insomnia, in digital communities. Natural language processing tools can be leveraged to understand the terms used in digital spaces to discuss insomnia and insomnia treatments.

Objective: The aim of this study is to summarize and chart trends of insomnia treatment terms on a digital insomnia message board.

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Objective: Survivors of childhood maltreatment (CM) often experience self-stigma, the internalization of negative attitudes such as shame, self-blame, and a reluctance to disclose their experiences. These self-perceptions pose a significant barrier to treatment-seeking and may exacerbate psychiatric distress. Prior research indicates that social contact-based interventions are effective in reducing stigma, but no study to date has examined their impact on self-stigma and increasing openness to treatment-seeking among CM survivors.

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Objective: Eye movement desensitization and reprocessing therapy (EMDR) is effective in treating major depressive disorder (MDD) with childhood trauma, and virtual reality (VR) can further extend its application form. However, the utilization of VR-EMDR in treating MDD with childhood trauma is still in its infancy, and whether it can improve depressive symptoms and traumatic experience remains unknown.

Method: Seventy-two MDD patients were randomly allocated to the intervention group and the wait-list control group on a 1:1 basis.

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Ecological momentary assessment (EMA) collects real-time data in daily life, enhancing ecological validity and reducing recall bias. An EMA questionnaire that measures symptoms and transdiagnostic factors was recently developed with network modeling purposes. This study examines this EMA protocol's (a) subjective experience (e.

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Objective: Alcohol use offers social benefits for young adults, but also carries risk of significant negative consequences. Better understanding of processes driving alcohol use for those who experience negative consequences can prevent these harms. These at-risk young adults likely have drinking patterns in common and patterns unique to each individual.

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