Predicting compassion fatigue among psychological hotline counselors using machine learning techniques.

During the outbreak of coronavirus disease 2019, psychological hotline counselors frequently address help-seekers' traumatic experiences from time to time, which possibly causes counselors' compassion fatigue. The present study aimed to explore the predictors of compassion fatigue among a high-risk population of psychological hotline counselors. Seven hundred and twelve psychological hotline counselors were recruited from the Mental Health Service Platform at Central China Normal University, Ministry of Education, then were asked to complete the questionnaires measuring compassion fatigue, trait empathy, social support, trait mindfulness, counselor's self-efficacy, humor, life meaning, and post-traumatic growth. A chi-square test was utilized to filter for the top-20 predictive variables. Machine learning techniques, including logistic regression, decision tree, random forest, k-nearest neighbor, support vector machine, and naïve Bayes were employed to predict compassion fatigue. The results showed that the most important predictors of compassion fatigue were meaning in life, counselors' self-efficacy, mindfulness, and empathy. Except for the decision tree, the rest machine learning techniques obtained good performance. Naïve Bayes presented the highest area under the receiver operating characteristic curve of 0.803. Random forest achieved the least classification error of 23.64, followed by Naïve Bayes with a classification error of 23.85. These findings support the potential application of machine learning techniques in the prediction of compassion fatigue. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12144-021-01776-7.

Mental health concerns and network structures of psychological helpline help-seekers during the COVID-19 pandemic in China: Pandemic stage differences.

BACKGROUND: The present study aimed to investigate the pandemic stage differences of mental health helpline help-seekers emotional responses, psychiatric symptoms, and related network structures during the COVID-19 pandemic in China. METHODS: The data was collected by a large-scale psychological helpline in response to the COVID-19 pandemic in mainland China. Counselor-reported information about the help-seekers pandemic-related emotional responses and psychiatric symptoms were recorded. A total of 26,870 callers' data from February 28, 2020, to April 23, 2021, were collected in the present study. A linear probability model and network analysis were conducted to determine the differences in help-seekers mental health concerns and network structures between the pandemic (stage I, from February 28, 2020, to April 28, 2020, N = 9821) and the regular prevention and control period (stage II, from April 29, 2020, to April 23, 2021, N = 17,049). RESULTS: Results revealed that anger, sadness, and obsession symptoms increased in stage II while symptoms of anxiety, somatization, and feelings of fear and stress were relieved. The network analysis results demonstrated both stage I and II networks centered on anxiety firmly. In stage II, the connection between anxiety and hypochondria and fear's strength centrality descended significantly. LIMITATIONS: The mental health outcomes of callers only included the counselor-reported data. CONCLUSIONS: The mental health concerns of helpline callers showed pandemic-related stage differences.

Interpretation bias in health anxiety: a systematic review and meta-analysis.

Interpretation bias (i.e. the selective negative interpretation of ambiguous stimuli) may contribute to the development and maintenance of health anxiety. However, the strength of the empirical evidence for this association remains a topic of debate. This study aimed to estimate the association between health anxiety and interpretation bias and to identify potential moderators of this association. Chinese-language databases (CNKI, VIP, and Wanfang), English-language databases (Web of Science, PubMed, PsycINFO, and Scopus), and German-language databases (Psyndex and PubPsych) were searched for relevant studies. There were 36 articles (39 studies) identified by this search (N = 8984), of which 32 articles (34 studies) were included in the meta-analysis (N = 8602). Results revealed a medium overall effect size (g = 0.67). Statistically equivalent effect sizes were observed for patients diagnosed with clinical health anxiety (g = 0.58) and subclinical health anxiety (g = 0.72). The effect sizes for threat stimuli that were health related (g = 0.68) and not health related (g = 0.63) did not differ significantly. The effect size for studies using an offline paradigm (g = 0.75) was significantly higher than that for studies using an online paradigm (g = 0.50). It is concluded that health anxiety is significantly and robustly associated with interpretation bias. These findings are of central importance for the advancement of models and treatment of health anxiety.

Efficacy and mechanisms of mobile application-delivered Acceptance and Commitment Therapy for posttraumatic stress disorder in China: Study protocol for a randomized controlled trial.

Background: As a result of the COVID-19 pandemic and its far-reaching impact, the prevalence of posttraumatic stress disorder (PTSD) symptoms is increasing significantly in China. Yet access to reliable and effective psychological treatment is still limited during the pandemic. The widespread adoption of mobile technologies may provide a new way to address this gap. In this research we will develop an Acceptance and Commitment Therapy (ACT) based intervention delivered by mobile application and will test its usability, efficacy, and mechanism of its effects in relieving PTSD symptoms. Methods: A total of 147 Chinese participants with a diagnosis of PTSD according to the Clinician Administered PTSD Scale (CAPS-5) will be randomly assigned to an intervention group (app-delivered ACT), an active comparison group (app-delivered mindfulness), or a waitlist group. Participants in the intervention group or comparison group will use their respective apps for one month. Online self-report questionnaires will be used to assess the primary outcome of PTSD symptoms and the secondary outcomes symptoms of depression, symptoms of anxiety, and posttraumatic growth. The potential mediating variable to be tested is psychological flexibility and its components. These assessments will be conducted at baseline, at five times during treatment, at the end of treatment, and at 1- and 3-month follow-ups. Discussion: As far as we know, this study is the first randomized controlled trial to investigate the usability, efficacy, and mechanism of an app-delivered ACT intervention for PTSD. Furthermore, the research will assess the effect of treatment in reducing dropout rates, explore effective therapeutic components, and investigate mechanisms of symptom change, which will be valuable in improving the efficacy and usability of PTSD interventions.Trial registration: ChiCTR2200058408.

Antiviral effect and anti-COVID-19 potential of immunobiotics

Immunobiotics, a group of probiotics, have the effect of anti-infection by regulating immune function, which can be added in in foods or used to make adjuvants or medicines (biologics). Immunobiotics can stimulate the mucosal immune system of the body, regulate innate and acquired immunity and exert non-specific anti-microbial (bacterial and viral) infection effects through oral, nasal mucosa, sublingual and other routes, but the immune regulation function of immunobiotics is species-specific. Oral administration of Lactobacillus plantarum GUANKE stimulated the increase and maintenance of SARS-CoV-2 neutralization antibodies in mice even 6 months after immunization. When L. plantarum GUANKE was given immediately after SARS-CoV-2 vaccination, the level of SARS-COV-2 specific neutralizing antibody in bronchoalveolar lavage increased by 8 times in mice, which improved the local and systematic cellular immune response to SARS-CoV-2 of mice. Clinical studies have found that immunobiotics have the auxiliary effect in the treatment of COVID-19 by mitigating the symptoms and increase the level of SARS-CoV-2 specific antibody of the patients. It is necessary to conduct research and evaluation for the appropriate guideline of immunobiotics use as erly as possible to provide a new option for the prevention and control of COVID-19.

Attentional bias toward health-threat in health anxiety: a systematic review and three-level meta-analysis.

Attentional bias toward health-threat may theoretically contribute to the development and maintenance of health anxiety, but the empirical findings have been controversial. This study aimed to synthesize and explore the heterogeneity in a health-threat related attentional bias of health-anxious individuals, and to determine the theoretical model that better represents the pattern of attentional bias in health anxiety. Four databases (Web of Science, PubMed, PsycINFO, and Scopus) were searched for relevant studies, with 17 articles (N = 1546) included for a qualitative review and 16 articles (18 studies) for a three-level meta-analysis (N = 1490). The meta-analytic results indicated that the health anxiety group, compared to the control group, showed significantly greater attentional bias toward health-threat (g = 0.256). Further analyses revealed that attentional bias type, paradigm, and stimuli type were significant moderators. Additionally, compared to the controls, health-anxious individuals displayed significantly greater attention maintenance (g = 0.327) but nonsignificant attention vigilance to health-threat (g = -0.116). Our results provide evidence for the attention maintenance model in health-anxious individuals. The implications for further research and treatment of elevated health anxiety in the context of coronavirus disease-2019 (COVID-19) were also discussed.

Prediction of Online Psychological Help-Seeking Behavior During the COVID-19 Pandemic: An Interpretable Machine Learning Method.

Online mental health service (OMHS) has been named as the best psychological assistance measure during the COVID-19 pandemic. An interpretable, accurate, and early prediction for the demand of OMHS is crucial to local governments and organizations which need to allocate and make the decision in mental health resources. The present study aimed to investigate the influence of the COVID-19 pandemic on the online psychological help-seeking (OPHS) behavior in the OMHS, then propose a machine learning model to predict and interpret the OPHS number in advance. The data was crawled from two Chinese OMHS platforms. Linguistic inquiry and word count (LIWC), neural embedding-based topic modeling, and time series analysis were utilized to build time series feature sets with lagging one, three, seven, and 14 days. Correlation analysis was used to examine the impact of COVID-19 on OPHS behaviors across different OMHS platforms. Machine learning algorithms and Shapley additive explanation (SHAP) were used to build the prediction. The result showed that the massive growth of OPHS behavior during the COVID-19 pandemic was a common phenomenon. The predictive model based on random forest (RF) and feature sets containing temporal features of the OPHS number, mental health topics, LIWC, and COVID-19 cases achieved the best performance. Temporal features of the OPHS number showed the biggest positive and negative predictive power. The topic features had incremental effects on performance of the prediction across different lag days and were more suitable for OPHS prediction compared to the LIWC features. The interpretable model showed that the increase in the OPHS behaviors was impacted by the cumulative confirmed cases and cumulative deaths, while it was not sensitive in the new confirmed cases or new deaths. The present study was the first to predict the demand for OMHS using machine learning during the COVID-19 pandemic. This study suggests an interpretable machine learning method that can facilitate quick, early, and interpretable prediction of the OPHS behavior and to support the operational decision-making; it also demonstrated the power of utilizing the OMHS platforms as an always-on data source to obtain a high-resolution timeline and real-time prediction of the psychological response of the online public.

Prevalence of depressive and anxiety symptoms among Chinese older adults during the COVID-19 pandemic: A systematic review and meta-analysis.

Background: Estimating the prevalence of depressive and anxiety symptoms among older adults with different health conditions can inform mental health services for this population during the corona virus disease-2019 (COVID-19) pandemic. Method: A search of 12 scientific databases identified 17 studies with 11,237 Chinese older adults who were infected by COVID-19, were generally healthy, or had chronic illnesses. Meta-analysis was used to estimate the overall prevalence of depressive and anxiety symptoms in these three groups. Assessment criteria, region, and time phase of the pandemic were tested as sources of heterogeneity. Results: With an average risk of bias score of 6.71 (range = 6-8), the majority of included studies employed appropriate statistical methods, used validated measurement tools, and had adequate response rates; however, they might have deficiencies in sample frame, sampling method, and sample size. Within the COVID-19, general, and chronic illness groups, the prevalence of depressive symptoms was 27%, 26%, and 61%, respectively, and the prevalence of anxiety symptoms was 14%, 23%, and 85%, respectively. Among generally healthy older adults, anxiety was more prevalent during the Phase 2 (March-April 2020) of the pandemic compared with other time phases. Conclusions: The results have implications for addressing the mental health problems of Chinese older adults, especially those with chronic illnesses, during the COVID-19 pandemic.

Boosting Vaccine-Elicited Respiratory Mucosal and Systemic COVID-19 Immunity in Mice With the Oral Lactobacillus plantarum.

Boosting and prolonging SARS-CoV-2 vaccine-elicited immunity is paramount for containing the COVID-19 pandemic, which wanes substantially within months after vaccination. Here we demonstrate that the unique strain of probiotic Lactobacillus plantarum GUANKE (LPG) could promote SARS-CoV-2-specific immune responses in both effective and memory phases through enhancing interferon signaling and suppressing apoptotic and inflammatory pathways. Interestingly, oral LPG administration promoted SARS-CoV-2 neutralization antibodies even 6 months after immunization. Furthermore, when LPG was given immediately after SARS-CoV-2 vaccine inoculation, specific neutralization antibodies could be boosted >8-fold in bronchoalveolar lavage (BAL) and >2-fold in sera, T-cell responses were persistent and stable for a prolonged period both in BAL and the spleen. Transcriptional analyses showed that oral application of LPG mobilized immune responses in the mucosal and systemic compartments; in particular, gut-spleen and gut-lung immune axes were observed. These results suggest that LPG could be applied in combination with SARS-CoV-2 vaccines to boost and prolong both the effective and memory immune responses in mucosal and systemic compartments, thereby improving the efficacy of SARS-CoV-2 vaccination.

The Psychological and Behavioral Patterns of Online Psychological Help-Seekers before and during COVID-19 Pandemic: A Text Mining-Based Longitudinal Ecological Study.

Online mental health service (OMHS) platforms have contributed significantly to the public's mental health during the COVID-19 pandemic in China. However, it remains unclear why the public used OMHS platforms for psychological help-seeking (PHS) behavior and how PHS behavior varied across different stages of the COVID-19 pandemic. Based on the ecological PHS behavior data from two OMHS platforms, we extracted population, psychological problems, and influential factors of PHS behavior by text mining and time series analysis methods. Seven top-ranked psychological problems (i.e., depression and anxiety, lack of interest, suicidal tendencies, social phobia, feelings of being worried and afraid, suffering, anger) and seven influential factors (i.e., interpersonal relationships, love, family, work, psychotherapy, personal characteristics, marriage) were found. The online PHS behaviors related to different psychological problems and influential factors remained a growing trend before 2020 and have been increasing significantly due to the COVID-19 outbreak. Four main stages were found during the pandemic according to the changes in the online PHS population: sharp growth, significant decline, slight rebound, and slow decline. This study identified large-scale, spontaneous PHS behaviors among the online public during the COVID-19 pandemic and the various psychological problems and influential factors that varied across different stages of the pandemic, suggesting that the government and health practitioners should adopt effective policies and strategies to prevent and intervene in mental health problems for the online public.

Effects of Wise Intervention on Perceived Discrimination Among College Students Returning Home From Wuhan During the COVID-19 Outbreak.

At the beginning of the coronavirus disease 2019 (COVID-19) outbreak, college students returning home from Wuhan, Hubei Province, experienced various degrees of discrimination. This study first investigates perceived discrimination among college students returning home from Wuhan. Then, an experimental method is used to investigate the effectiveness of an intervention designed to reduce the perceived discrimination among those who returned to towns outside of Hubei Province. A total of 63 college students participated in the experiment. In the experimental group (N = 31), a wise intervention based on reading and writing was adopted to intervene in perceived discrimination among the participants. The results showed that the perceived discrimination among students returning from Wuhan to towns outside of Hubei Province was significantly higher than that among students returning to towns within Hubei Province. The wise intervention reduced the perceived discrimination in the experimental group but not in the control group. Further analysis found that perceived social support fully mediated the relationship between the intervention and perceived discrimination. These results provide insights on how the content of intervention (perceived social support) and the form of intervention (wise intervention) can prevent the occurrence of psychological problems in epidemic situations.

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.

A Network Analysis of Post-traumatic Stress Disorder Symptoms and Correlates During the COVID-19 Pandemic.

Background and Objective: The coronavirus disease 2019 (COVID-19) outbreak has been suggested as a collective trauma, which presents a continuing crisis. However, the specific post-traumatic implication of this crisis has not been adequately studied yet. The current study was aimed to ascertain the most central symptom and the strong connections between symptoms of post-traumatic stress disorder (PTSD). At the same time, exploring the relationship between covariates and the network of PTSD symptoms, by taking sex, anxiety, depression, suicidal ideation, quality of life, and social support as covariates, may help us to know the arise and maintenance of PTSD symptoms and give specified suggestions to people under the shadow of COVID-19. Method: The Post-traumatic Stress Disorder Checklist for Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), was used to assess the PTSD symptoms extent of 338 healthy participants over the past month. Networks were analyzed using state-of-the-art regularized partial correlation models. In addition, the centrality of the symptoms and the robustness of the results were analyzed. Results: The network analysis revealed that the especially strong connections emerged between avoidance of thoughts and avoidance of reminders, hypervigilance and exaggerated startle response, intrusive thoughts and nightmares, flashbacks and emotional cue reactivity, and detachment and restricted affect. The most central symptoms were self-destructive/reckless behavior. Incorporation of covariates into the network revealed the strong connections path between self-destructive/reckless behavior and loss of interest and depression. Conclusion: Self-destructive/reckless behavior was the most central symptom in the network of PTSD symptoms related to the COVID-19 pandemic, which as an important target of interfere may have great benefits.

Establishment of Online Platform for Psychological Assistance during a Public Health Emergency

The Coronavirus Disease 2019 (COVID-19) is raging worldwide, seriously threatening the public's mental health Online platform for psychological assistance integrated various sources to promote the public's mental health. This article, using the Mental Health Service Platform at Central China Normal University, Ministry of Education (MOE-CCNU-MHSP) as an example, aims to describe the experience of building an online platform for psychological assistance in a public health emergency and discuss the further development of the online mental health service platform so as to provide suggestions to enhance online psychological service delivery.