Assessing Social Interest in Burnout Using Google Trends Data

Burnout is a serious problem in modern society and early detection methods are needed to successfully handled its multiple effects. The latter refer to working well-being, as well as to the affective, psychological, physiological, and behavioral well-being of workers. However, in many countries official statistics on this topic are not available. For this reason, we propose to use Google Trends data as proxies for the interest in burnout and to analyze them through the functional data analysis approach. The latter allows to address the so-called ‘curse of dimensionality’ of big data, enabling an effective statistical analysis when the number of variables exceeds the number of observations. Under this framework, the functional analysis of variance (FANOVA) model is used for testing a macro geographic area effect on search queries for the keyword “burnout” in Italy. The estimation of the FANOVA model is proposed in a finite dimensional space generated by a basis function representation. Thus, the functional model is reduced to a MANOVA model on the basis coefficients.Spanish Ministry of Science, Innovation and Universities MTM2017-88708-P (supported by the FEDER program

Effect of traditional yoga, mindfulness-based cognitive therapy, and cognitive behavioral therapy, on health related quality of life : A randomized controlled trial on patients on sick leave because of burnout

Background: To explore if health related quality of life(HRQoL) increased after traditional yoga(TY), mindfulness based cognitive therapy(MBCT), or cognitive behavioral therapy(CBT), in patients on sick leave because of burnout. Methods: Randomized controlled trial, blinded, in ninety-four primary health care patients, block randomized to TY, MBCT or CBT (active control) between September 2007 and November 2009. Patients were living in the Stockholm metropolitan area, Sweden, were aged 18-65 years and were on 50%-100% sick leave. A group treatment for 20 weeks, three hours per week, with homework four hours per week. HRQoL was measured by the SWED-QUAL questionnaire, comprising 67 items grouped into 13 subscales, each with a separate index, and scores from 0 (worse) to 100 (best). SWED-QUAL covers aspects of physical and emotional well-being, cognitive function, sleep, general health and social and sexual functioning. Statistics: Wilcoxon's rank sum and Wilcoxon's sign rank tests, Bonett-Price for medians and confidence intervals, and Cohen's D. Results: Twenty-six patients in the TY (21 women), and 27 patients in both the MBCT (24 women) and in the CBT (25 women), were analyzed. Ten subscales in TY and seven subscales in MBCT and CBT showed improvements, p <0.05, in several of the main domains affected in burnout, e.g. emotional well-being, physical well-being, cognitive function and sleep. The median improvement ranged from 0 to 27 points in TY, from 4 to 25 points in CBT and from 0 to 25 points in MBCT. The effect size was mainly medium or large. Comparison of treatments showed no statistical differences, but better effect (small) of both TY and MBCT compared to CBT. When comparing the effect of TY and MBCT, both showed a better effect (small) in two subscales each. Conclusions: A 20 week group treatment with TY, CBT or MBCT had equal effects on HRQoL, and particularly on main domains affected in burnout. This indicates that TY, MBCT and CBT can be used as both treatment and prevention, to improve HRQoL in patients on sick leave because of burnout, reducing the risk of future morbidity.