Ostracism, Psychological Capital, Perceived Social Support and Depression among Economically Disadvantaged Youths: A Moderated Mediation Model.

Mental health promotion of economically disadvantaged youths is a popular issue in current China. Economically disadvantaged youths are at greater risk of depression. Ostracism may be an important predictor of depression for them. However, no consensus has been reached on the underlying mechanism between ostracism and depression. A total of 1207 economically disadvantaged youths were recruited from six universities in China. These youths were asked to complete questionnaires measuring depression, ostracism, psychological capital, and perceived social support. A moderated mediation model was examined by using IBM SPSS STATISTICS 27macro program PROCESS version 3.5, in which psychological capital was a mediating variable, and perceived social support was a moderating variable. Lack of causal inferences and self-report bias due to the cross-sectional and self-report survey need to be considered when interpreting results. The results revealed that ostracism was positively associated with depression among economically disadvantaged youths. Psychological capital partially mediated the association. Perceived social support moderated the indirect association between ostracism and depression via psychological capital among economically disadvantaged females. Training and intentional practice of psychological capital could be the core to develop the depression interventions targeting economically disadvantaged youths with experience of ostracism. Gender and perceived social support need to be considered in developing the interventions.

Comparative efficacy and acceptability of psychosocial treatments for disruptive behaviour disorders in children and adolescents: study protocol for a systematic review and network meta-analysis.

INTRODUCTION: Disruptive behaviour disorders are common among children and adolescents, with negative impacts on the youths, their families and society. Although multiple psychosocial treatments are effective in decreasing the symptoms of disruptive behaviour disorders, comprehensive evidence regarding the comparative efficacy and acceptability between these treatments is still lacking. Therefore, we propose a systematic review and network meta-analysis, integrating both direct and indirect comparisons to obtain a hierarchy of treatment efficacy and acceptability. METHODS AND ANALYSIS: The present protocol will be reported according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols. Ten databases, including Web of Science, PubMed, PsycINFO, MEDLINE, APA PsycArticles, Psychology and Behavioral Sciences Collection, OpenDissertations, The Cochrane Library, Embase and CINAHL, will be searched from inception for randomised controlled trials of psychosocial treatments for children and adolescents with disruptive behaviour disorders, without restrictions on language, publication year and status. The primary outcomes will be efficacy at post-treatment (severity of disruptive behaviour disorders at post-treatment) and acceptability (dropout rate for any reason) of psychosocial treatments. The secondary outcomes will involve efficacy at follow-up, severity of internalising problems and improvement of social functioning. Two authors will independently conduct the study selection and data extraction, assess the risk of bias using the revised Cochrane Collaboration's Risk of Bias tool and evaluate the quality of the evidence using the Grading of Recommendations Assessment, Development and Evaluation framework to network meta-analysis. We will perform Bayesian network meta-analyses with a random effects model. Subgroup and sensitivity analyses will be performed to evaluate the robustness of the findings. ETHICS AND DISSEMINATION: The research does not require ethical approval. Results are planned to be published in journals or presented at conferences. The network meta-analysis will provide information on a hierarchy of treatment efficacy and acceptability and help make a clinical treatment choice. PROSPERO REGISTRATION NUMBER: CRD42020197448.

The uulmMAC Database-A Multimodal Affective Corpus for Affective Computing in Human-Computer Interaction.

In this paper, we present a multimodal dataset for affective computing research acquired in a human-computer interaction (HCI) setting. An experimental mobile and interactive scenario was designed and implemented based on a gamified generic paradigm for the induction of dialog-based HCI relevant emotional and cognitive load states. It consists of six experimental sequences, inducing Interest, Overload, Normal, Easy, Underload, and Frustration. Each sequence is followed by subjective feedbacks to validate the induction, a respiration baseline to level off the physiological reactions, and a summary of results. Further, prior to the experiment, three questionnaires related to emotion regulation (ERQ), emotional control (TEIQue-SF), and personality traits (TIPI) were collected from each subject to evaluate the stability of the induction paradigm. Based on this HCI scenario, the University of Ulm Multimodal Affective Corpus (uulmMAC), consisting of two homogenous samples of 60 participants and 100 recording sessions was generated. We recorded 16 sensor modalities including 4 × video, 3 × audio, and 7 × biophysiological, depth, and pose streams. Further, additional labels and annotations were also collected. After recording, all data were post-processed and checked for technical and signal quality, resulting in the final uulmMAC dataset of 57 subjects and 95 recording sessions. The evaluation of the reported subjective feedbacks shows significant differences between the sequences, well consistent with the induced states, and the analysis of the questionnaires shows stable results. In summary, our uulmMAC database is a valuable contribution for the field of affective computing and multimodal data analysis: Acquired in a mobile interactive scenario close to real HCI, it consists of a large number of subjects and allows transtemporal investigations. Validated via subjective feedbacks and checked for quality issues, it can be used for affective computing and machine learning applications.

Self-Oriented Empathy and Compassion Fatigue: The Serial Mediation of Dispositional Mindfulness and Counselor's Self-Efficacy.

This study aimed to explore the association between self-oriented empathy and compassion fatigue, and examine the potential mediating roles of dispositional mindfulness and the counselor's self-efficacy. A total of 712 hotline psychological counselors were recruited from the Mental Health Service Platform at Central China Normal University, Ministry of Education during the outbreak of Corona Virus Disease 2019, then were asked to complete the questionnaires measuring self-oriented empathy, compassion fatigue, dispositional mindfulness, and counselor's self-efficacy. Structural equation modeling was utilized to analyze the possible associations and explore potential mediations. In addition to reporting confidence intervals (CI), we employed a new method named model-based constrained optimization procedure to test hypotheses of indirect effects. Results showed that self-oriented empathy was positively associated with compassion fatigue. Dispositional mindfulness and counselor's self-efficacy independently and serially mediated the associations between self-oriented empathy and compassion fatigue. The findings of this study confirmed and complemented the etiological and the multi-factor model of compassion fatigue. Moreover, the results indicate that it is useful and necessary to add some training for increasing counselor's self-efficacy in mindfulness-based interventions in order to decrease compassion fatigue.