The aim of the paper was to systematically review the literature on computer-based psychological treatments for depression and conduct a meta-analysis of the RCT studies, including examining variables which may effect outcomes. Database and hand searches were made using specific search terms and inclusion criteria. The review included a total of 40 studies (45 published papers), and 19 RCTs (23 published papers) were included in a standard meta-analysis. The review describes the different computer-based treatments for depression, their design, communication types employed: synchronous, asynchronous, and face-to-face (F:F); alongside various types and frequency of support delivered. The evidence supports their effectiveness and highlights participant satisfaction. However, pertinent limitations are noted. Across 19 studies the meta-analysis revealed a moderate post-treatment pooled effect size d=.56 (95% confidence interval [CI] -.71, -.41), Z=7.48, p<.001). Supported interventions yielded better outcomes, along with greater retention. The results reported statistically significant clinical improvement and recovery post-treatment. The review and meta-analysis support the efficacy and effectiveness of computer-based psychological treatments for depression, in diverse settings and with different populations. Further research is needed, in particular to investigate the influence of therapist factors in supported treatments, the reasons for dropout, and the maintenance of gains post-treatment.

Previous research has shown a relationship between financial difficulties and poor mental health in students, but most research is cross-sectional. To examine longitudinal relationships over time between financial variables and mental health in students. A national sample of 454 first year British undergraduate students completed measures of mental health and financial variables at up to four time points across a year. Cross-sectional relationships were found between poorer mental health and female gender, having a disability and non-white ethnicity. Greater financial difficulties predicted greater depression and stress cross-sectionally, and also predicted poorer anxiety, global mental health and alcohol dependence over time. Depression worsened over time for those who had considered abandoning studies or not coming to university for financial reasons, and there were effects for how students viewed their student loan. Anxiety and alcohol dependence also predicted worsening financial situation suggesting a bi-directional relationship. Financial difficulties appear to lead to poor mental health in students with the possibility of a vicious cycle occurring.

Purpose: Previous cross-sectional research has examined the effect of loneliness on mental health. The purpose of this paper is to examine longitudinal relationships in students. Design/methodology/approach: A total of 454 British undergraduate students completed measures of loneliness and mental health at four time points. Findings: After controlling for demographics and baseline mental health, greater loneliness predicted greater anxiety, stress, depression and general mental health over time. There was no evidence that mental health problems increased loneliness over time. There was no relationship with alcohol problems. Baseline loneliness predicted greater eating disorder risk at follow-up and vice versa. Research limitations/implications: This study is limited by a relatively small and heavily female sample. Practical implications: Social and psychological interventions to reduce loneliness in university settings may improve mental health. Social implications: Universities should consider organising social activities to mitigate feelings of loneliness in students. Originality/value: This study adds to the literature as a longitudinal analysis showing that loneliness exacerbates poor mental health over time. This also adds to the literature for students specifically, and suggests a possible bi-directional relationship between eating disorders and loneliness for the first time.

From The Journal of Clinical Psychiatry: Computer-assisted cognitive-behavior therapy (CCBT) allows clinicians to deliver evidence-based care to more patients than would be possible with standard CBT. This meta-analysis sought to determine if additional clinician support can increase the efficacy of CCBT—read the report to learn what the authors found.