The influence of family therapy on psychological stress and social adaptability of depressed patients

Efficacy of systemic therapy on adults with depressive disorders: A meta-analysis

OBJECTIVE

This meta-analysis evaluates the efficacy of systemic therapy approaches on adult clients with depressive disorders.

METHODS

The illness-specific systematic review updates a previous meta-analysis on the efficacy of systemic therapy on psychiatric disorders in adulthood. It integrates the results of 30 randomized controlled trials (RCTs) comparing systemic psychotherapy for depression with an untreated control group or alternative treatments. Studies were identified through systematic searches in relevant electronic databases and cross-referencing. A random-effects model calculated weighted mean effect sizes for each type of comparison (alternative treatments, control group with no alternative treatment/waiting list) on two outcomes (depressive symptoms change, drop-out rates).

RESULTS

On average, systemic interventions show larger improvements in depressive symptoms compared to no-treatment controls at post-test (g = 1.09) and follow-up (g = 1.23). Changes do not significantly differ when comparing systemic interventions with alternative treatments (post-test g = 0.25; follow-up g = 0.09). Results also vary, in part, by participant age, publication year, and active control condition.

CONCLUSION

This meta-analysis indicates the potential benefits of systemic interventions for adult patients with depression. Future randomized clinical trials in this area should enhance study quality and include relational and other relevant outcome measures.

Analysis of physical education based on deep learning on college students’ mental health and social adaptability

With the development of learning abroad, deep learning is used in research fields. On the basis of deep learning, this article studies physical education. First, this article analyzes and explains the related concepts and current situation of physical education, and explains the measurement and definition of the mental health. Then, the function analysis algorithm of deep learning is explained and analyzed, in which the algorithm of the convolution neural network of deep learning is mainly described. Finally, through experimental analysis, it shows that the research performance of deep learning in the physical education on college students’ mental health is relatively high. At the same time, through investigation and analysis, it is proposed that physical education in deep learning can improve mental health and social adaptability relatively high. And the content of physical education should focus on increasing physical psychological education and physical practice education, which can improve college students’ mental health and social adaptability compared with other teaching contents. Therefore, when introducing deep learning, universities should strengthen the physical education of college students.