Work stress can have a negative impact for both individuals and organizations, warranting research on how to recover from it. This research analyzes how the relationship between video games and work recovery differs depending on the genre of the video game played. In addition, these relationships are compared against the relationships between the recovery experiences and other leisure activities. Participants were asked to provide information on how often they play video games and engage in other leisure activities. In addition, two different measures of the four components of work recovery (psychological detachment from work, relaxation, mastery experiences, and control) were included. The data was analyzed using a multivariate regression framework. Based on the literature review, it was predicted that different genres of video games will relate differently with the different recovery experiences, and video games will relate differently with the different recovery experiences compared to the other leisure activities. Results showed that the different video game genres did relate differently to the experiences of work recovery, but not in the predicted directions. The overarching goal of this study is to further the literature on the possible benefits of video game use and to provide a basis for further research on video games and work recovery.

Completing tasks and reaching goals at work depletes employees’ energy, motivation, and attentional resources, resulting in negative stress and fatigue experiences. Taking microbreaks from work may help recover from work demands and replenish these resources by positively affecting employee well-being and performance. Therefore, this study seeks to understand the potential benefits of personal social media use as a specific microbreak activity that has become increasingly popular in recent years for employee recovery and productivity during working hours. More specifically, the engagement in social media microbreaks (SMMB) was hypothesized to positively predict both employees’ psychological detachment and perceived productivity. Cross-sectional survey data from 193 white-collar workers were collected and analyzed using linear regression. The results of this correlational study revealed that while engagement in SMMB activities positively predicted psychological detachment, perceived productivity was not found to be associated with SMMBs when holding employees’ general engagement in social media and socially desirable responding constant. Exploratory analyses showed that these relationships may be contingent on demographic, individual, and work (break) characteristics. These findings challenge the predominant negative connotation of using social media at work among employers and by contributing to a growing body of evidence suggesting the restorative nature of microbreaks. Yet, this research underlines the necessity for further research to elucidate the boundary conditions for effective (social media) microbreaks.

<p>Povratak na posao nakon operacije lumbalne diskus hernije determinisan je funkcionalnim stanjem, prisustvom i stepenom tegoba od strane lumbosakralne kičme, zahtevima na radnom mestu bolesnika ali i psihosocijalnim faktorima, koji pri oceni radne sposobnosti zaposlnih zahtevaju individualni pristup. Grupa pacijenata koja se neće vratiti na posao može biti identifikovana putem prognostičkog modela. Cilj ove studije je definisanje prognostičkog modela za povratak na posao bolesnika operisanih zbog lumbalne diskus hernije kao i identifikacija najznačajnijih faktora rizika odgovornih za lo&scaron; ishod operativnog lečenja, posmatrano kroz prizmu povratka na posao. Istraživanje je prospektivna studija koja je obuhvatila ukupno 200 ispitanika, koji su operisani zbog lumbalne diskus hernije na jednom nivou i praćeni su u vremenskom period do 12 meseci nakon operativnog lečenja. U statističku ananlizu je u&scaron;lo 153 bolesnika, koji su ispunili kriterijume selekcije ispitanika studije. Nakon određivanja značaja posmatranih biolo&scaron;kih, profesionalnih i psihosocijalnih faktora rizika za povratak na posao, kreirani su i evaluirani prognostički modeli bazirani na svim i na odabranim atributima desetostrukom kros-validacijom: stablo odlučivanja (DT), model vi&scaron;eslojnih perceptrona (MLP) i model potpornih vektora (SVM). Za predviđanje povratka na posao najveću tačnost, specifičnost i senzitivnost za odabrane atribute postiže model potpornih - podržavajućih vektora (SVM). Najbolju intuitivnu i praktičnu vrednost za predviđanje povratka na posao pruža model stabla odluka (DT). Identifikacijom najznačajnijih faktora rizika za nepovoljan ishod povratka na posao omogućeno je preventivno delovanje na iste, u cilju smanjenja broja pacijenata sa umanjenjem radne sposobnosti i invaliditeta.</p> / <p>Return to work after lumbar discectomy is determinated by functional status, presence and degree of discomfort in the lumbosacral spine, the requirements in the workplace of patients and psychosocial factors that in the assessment of working capabilities require an individual approach. Groups of patients which don&rsquo;t return to work after surgery could be identified by predictive model. The aim of this study is to define prognostic model to return to work patients after lumbar discectomy, as well as the identification major risk factors responsible for the poor outcome of operative treatment viewed through the prism of returning to work. This prospective study included a total of 200 patients, who underwent surgery for lumbar disc herniation on one level and were followed up in period of 12 months following surgery. The statistical analysis included 153 patients who fulfilled all selection criteria of the study subjects. After determining significance of the observed biological, professional and psychosocial risk factors for return to work, prognostic models were designed and evaluated based on all and selected attributes by tenfold cross-validation: decision tree (DT) model of multilayer perception (MLP) model and support vector (SVM). For the prediction of return to work best accuracy, specificity and sensitivity for selected attributes, is achieved by supporting vector model (SVM). The decision tree model (DT) provides the best intuitive and practical value for predicting return to work. By identifying the most important risk factors for adverse outcome for return to work it is made possible for preventive actions, to reduce the number of patients with reduced work ability and disability.</p>