The Partial Mediator Role of Satisficing Decision-Making Style Between Trait Emotional Intelligence and Compassion Fatigue in Healthcare Professionals.

Background: Compassion fatigue (CF) represents a relevant issue for healthcare professionals. Currently, it is still unclear which psychological mechanism might lead to CF and which might protect workers from that. Decision-making styles, as well as emotional intelligence, might partially account for the presence of CF. Specifically, we hypothesized that a satisficing decision-making style would mediate the relationship between emotional intelligence and CF.Methods: A cross-sectional online survey was conducted on physicians and nurses from Italian Medical Departments. Three self-reported questionnaires were administered to collect data in accordance with our aims. A mediation model with Structural Equation Modeling on the relationship between trait emotional intelligence (TEI) and CF through the maximizing decision-making style was performed.Results: We found a significant relationship between TEI and CF (ß = -0.28, SE = 0.04, p < .001). The maximizing style partially mediated this relationship (ß = -0.04, SE = 0.01, p < .001). Moreover, negative relationships were found between sex (male), working hours, sleep quality, and CF. Conversely, a positive relationship between age and CF was demonstrated.Conclusions: Being emotionally intelligent resulted as a protective factor for developing CF, while the decision-making styles shaped the risk of developing CF.

When in doubt, Google it: distress-related information seeking in Italy during the COVID-19 pandemic.

BACKGROUND: Psychological health has been one of the aspects affected by the recent COVID-19 pandemic. We aim to evaluate the patterns of Google search for mental distress symptoms of Italian citizens during the various phases of the COVID-19 pandemic. METHODS: We assessed Google searches for psychological-health related words. We gathered and analyzed data on daily search queries on depression, anxiety, and insomnia from Google Trends, in a time ranging from the Pre-COVID phase (beginning 25th January 2020) up to the second wave phase (ending 17th October 2020). We performed three general linear models on search trends of the three words and tested whether and to what extent official data about new cases of COVID-19, information searching on new cases, and the government health measures impacted on these trends. RESULTS: Average daily search queries were higher for anxiety, followed by depression and insomnia. General linear models performed to assess differences in daily search queries for anxiety, depression and insomnia were significant, respectively [F(13, 253) = 6.80, P < .001]; [F(13, 253) = 10.25, P < .001]; [F(13, 253) = 6.61, P < .001]. Specifically, daily search queries differed among different phases of managing the COVID-19 outbreak: anxiety [F(5, 253) = 10.35, P < .001, [Formula: see text] = .17]; depression [F(5, 253) = 13.59, P < .001, [Formula: see text] = .21]; insomnia [F(5, 253) = 3.52, P = .004, [Formula: see text] = .07]. CONCLUSIONS: Our study contributed to the investigation of online information-seeking behaviors of Italians regarding mental health throughout the entire phase of the pandemic and provides insights on the possible future trends of mental distress during upcoming pandemic phases.

A meta-analysis on heart rate variability biofeedback and depressive symptoms.

Heart rate variability biofeedback (HRVB) has been used for a number of years to treat depressive symptoms, a common mental health issue, which is often comorbid with other psychopathological and medical conditions. The aim of the present meta-analysis is to test whether and to what extent HRVB is effective in reducing depressive symptoms in adult patients. We conducted a literature search on Pubmed, ProQuest, Ovid PsycInfo, and Embase up to October 2020, and identified 721 studies. Fourteen studies were included in the meta-analysis. Three meta-regressions were also performed to further test whether publication year, the questionnaire used to assess depressive symptoms, or the interval of time between T0 and T1 moderated the effect of HRVB. Overall, we analysed 14 RCTs with a total of 794 participants. The random effect analysis yielded a medium mean effect size g = 0.38 [95% CI = 0.16, 0.60; 95% PI = - 0.19, 0.96], z = 3.44, p = 0.0006. The total heterogeneity was significant, QT = 23.49, p = 0.03, I2 = 45%, which suggested a moderate variance among the included studies. The year of publication (χ2(1) = 4.08, p = 0.04) and the questionnaire used to assess symptoms (χ2(4) = 12.65, p = 0.01) significantly moderated the effect of the interventions and reduced heterogeneity. Overall, results showed that HRVB improves depressive symptoms in several psychophysiological conditions in adult samples and should be considered as a valid technique to increase psychological well-being.

Understanding Patients' Preferences: A Systematic Review of Psychological Instruments Used in Patients' Preference and Decision Studies.

BACKGROUND: Research has been mainly focused on how to elicit patient preferences, with less attention on why patients form certain preferences. OBJECTIVES: To assess which psychological instruments are currently used and which psychological constructs are known to have an impact on patients' preferences and health-related decisions including the formation of preferences and preference heterogeneity. METHODS: A systematic database search was undertaken to identify relevant studies. From the selected studies, the following information was extracted: study objectives, study population, design, psychological dimensions investigated, and instruments used to measure psychological variables. RESULTS: Thirty-three studies were identified that described the association between a psychological construct, measured using a validated instrument, and patients' preferences or health-related decisions. We identified 33 psychological instruments and 18 constructs, and categorized the instruments into 5 groups, namely, motivational factors, cognitive factors, individual differences, emotion and mood, and health beliefs. CONCLUSIONS: This review provides an overview of the psychological factors and related instruments in the context of patients' preferences and decisions in healthcare settings. Our results indicate that measures of health literacy, numeracy, and locus of control have an impact on health-related preferences and decisions. Within the category of constructs that could explain preference and decision heterogeneity, health locus of control is a strong predictor of decisions in several healthcare contexts and is useful to consider when designing a patient preference study. Future research should continue to explore the association of psychological constructs with preference formation and heterogeneity to build on these initial recommendations.