Psychosocial treatments for nightmares in adults and children: a systematic review.

BACKGROUND: As nightmares may be a risk factor for, or symptom of, multiple psychological disorders, some researchers suggest that nightmares should be screened, diagnosed, and treated. Treatments for nightmares include trauma-focused Cognitive Behavioural Therapy and Image Rehearsal Therapy, and pharmacological interventions such as prazosin and nitrazepam. As recent research has put into question our current understanding of treatment efficacy, there is a need to systematically review findings related to the effectiveness of nightmare treatments to inform best practice. The current review assessed the efficacy of psychosocial treatments of nightmare in all cohorts. METHODS: A systematic search of four databases for peer reviewed journal articles from 2000 onwards produced 69 (35 RCTs, 34 non-RCTs) eligible articles that underwent narrative synthesis. RESULTS: The results provide strong evidence for exposure and image rehearsal treatments for the reduction of nightmare frequency, severity, and distress, in civilian, military, idiopathic, and posttraumatic stress disorder (PTSD) cohorts. There is emerging evidence that self-guided and brief treatment modalities offer efficient and effective treatment options. There is an urgent need for clinical trials of treatment effectiveness in children. CONCLUSIONS: The results suggest that treatments for nightmares are most effective when they facilitate a sense of control or mastery by directly targeting the nightmare content and/or the client's emotional responses to the nightmare content. TRIAL REGISTRATION: A review protocol was registered with PROSPERO (CRD42020204861).

Exploring the digital footprint of depression: a PRISMA systematic literature review of the empirical evidence.

BACKGROUND: This PRISMA systematic literature review examined the use of digital data collection methods (including ecological momentary assessment [EMA], experience sampling method [ESM], digital biomarkers, passive sensing, mobile sensing, ambulatory assessment, and time-series analysis), emphasizing on digital phenotyping (DP) to study depression. DP is defined as the use of digital data to profile health information objectively. AIMS: Four distinct yet interrelated goals underpin this study: (a) to identify empirical research examining the use of DP to study depression; (b) to describe the different methods and technology employed; (c) to integrate the evidence regarding the efficacy of digital data in the examination, diagnosis, and monitoring of depression and (d) to clarify DP definitions and digital mental health records terminology. RESULTS: Overall, 118 studies were assessed as eligible. Considering the terms employed, "EMA", "ESM", and "DP" were the most predominant. A variety of DP data sources were reported, including voice, language, keyboard typing kinematics, mobile phone calls and texts, geocoded activity, actigraphy sensor-related recordings (i.e., steps, sleep, circadian rhythm), and self-reported apps' information. Reviewed studies employed subjectively and objectively recorded digital data in combination with interviews and psychometric scales. CONCLUSIONS: Findings suggest links between a person's digital records and depression. Future research recommendations include (a) deriving consensus regarding the DP definition and (b) expanding the literature to consider a person's broader contextual and developmental circumstances in relation to their digital data/records.

Adolescent Popularity: Distinct Profiles and Associations with Excessive Internet Usage and Interpersonal Sensitivity.

Peer popularity constitutes a pivotal developmental task to adolescents' current and future adaptation. This study identified distinct adolescent popularity profiles and explored their links with excessive Internet usage and interpersonal sensitivity. The sample included 2090 students attending Greek high schools (Mage = 16.16, SD = 0.91). Their popularity was measured via self-report and peer sociometric means. They also responded to the Internet Addiction Test (IAT) and the Interpersonal Sensitivity subscale of the Symptom Checklist-90-Revised (SCL-90-R). A sequence of latent profile analysis, ANOVAs and linear regression models were performed. Three distinct popularity profiles were revealed: the "Average Confident" (68.4%), the "Socially Vulnerable" (26.8%), and the "Insecure Bi-Strategic" (4.8%). These profiles did not significantly vary regarding their Internet usage and interpersonal sensitivity behaviours. Interestingly, lower self-perceived popularity predicted higher interpersonal sensitivity, whereas higher actual popularity predicted excessive Internet use. Findings have important implications for student-tailored mental health prevention and intervention practices.