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Background: The COVID-19 pandemic placed an extraordinary burden on health care workers (HCW), who are reported to suffer from great mental stress. The current study investigates the mental health of HCW in the later phases of the pandemic. Methods: HCW completed the following questionnaires online (06/2021-02/2022, N=159): demographics (age, gender, profession, ward), Impact of Event Scale (IES-R, posttraumatic stress), State Trait Anxiety Inventory (STAI-S, state anxiety), stress-coping questionnaire (SVF-78), and bespoke corona-specific stress and protective-factor questions (5 items each). We used factor analysis to test scale properties and regression-type methods (t-tests, ANOVA, multiple regression) for hypothesis tests and effect-size estimation. Results/discussion: Mental stress in HCW is influenced by similar factors as described for earlier phases. However, differences to earlier phases were found in ward affiliation which is no longer a variable of concern for explaining differences in mental health of HCW. Further, even if nurses are the occupational group with the highest mental stress as in prior research, detailed analysis shows that medical specialists with close proximity to patients with a high-level of responsibility are the most burdened sub-group. Unlike nurses, they suffer from high levels of anxiety in addition to high levels of post-traumatic and COVID-specific stress. Analyses showed further that COVID-specific stress is the strongest predictor of mental stress, wherein COVID-specific stress factors remain the same as reported in literature on the early pandemic phases. HCW showed to use still more positive than negative coping strategies. Negative strategies increased as expected mental stress, whereas positive strategies alleviated only anxiety. Additionally, we found that doctors benefited from many protective factors while nurses had access to fewer protective factors like earlier waves. Conclusion: Data show that HCW still suffer from mental stress in the third year of the pandemic. HCW of all hospital wards may be affected by mental stress and need attention and protective measures. Medical specialists are the most burdened subgroup. Detailed analyses show that properties other than occupation, gender, or ward affiliation are more appropriate to evaluate mental stress of HCW. The findings have implications for developing specialized protection strategies for the post-pandemic phase and future pandemics.
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Lockdown enacted by government in response to the Covid-19 pandemic in Austria forced psychotherapy practice into an online-only setting for several months in 2020. Although there is evidence supporting the effectiveness of psychotherapy in remote settings, research investigating therapeutic alliance in online psychotherapy is still limited, with a specific need for research in assessing possible effects of changes in therapeutic setting from face-to-face to online and vice versa. We measured therapeutic alliance in client-therapist dyads using the Helping Alliance Questionnaire (HAQ) at the Adult Outpatient Clinic of Sigmund Freud University, Vienna. Eighty-seven dyads completed HAQ twice, assessing three time-points: after switching from face-to-face to online therapy, providing a retrospective assessment of their alliance before the setting change as well as a concurrent account of their experience during online therapy, then another assessment after switching back to face-to-face setting after lockdown restrictions were lifted. Data were analysed by fitting a multilevel linear model, where the variables person (client/therapist) and time (before online therapy; online therapy; back to face-to-face) were nested within the client-therapist dyad. We found a statistically significant small improvement in the quality of therapeutic alliance over time, but no differences due to change in therapeutic setting. Separate analysis of HAQ sub-scales revealed that clients rated their relationship statistically significantly higher than their therapists with medium effect size, while there were no differences in success ratings over time and settings, nor between clients and therapists. The findings support the feasibility of online therapy in terms of therapeutic alliance in general, and alternating between face-to-face and online therapy settings in particular.
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Introduction: Working from home has become increasingly prevalent due to the COVID-19 pandemic, creating new challenges for organizations and employees. According to the latent deprivation model proposed by Jahoda, work provides latent benefits alongside its material rewards, and losing such benefits leads to a decline in well-being. Organizational affective commitment, or affective commitment within the organization, is a prominent concept in organizational psychology that is linked to lower workforce fluctuation and increased work performance. The present research examined the impact of time spent working from home on affective commitment by examining Jahoda's "latent functions," including social contact and collective purpose, representing an innovative application of the latent deprivation model in the context of home office. Methods: Using an online questionnaire, we collected data from 456 participants (239 female and 217 male) who had been employed for at least 2 years and who had spent a proportion of their time working from home in March and April 2021. The data were analyzed using a path model, in which the potential adverse effect of time spent in home office on affective commitment to the workplace was mitigated by latent functions. Results: Specifically, we found that more time spent in home office was associated with a decrease in social contact, the impact of which on affective commitment was mediated through the perception of collective purpose. Discussion: Our findings emphasize the role of the latent benefits of work experienced by employees even when working from home, and the role of those benefits in supporting employees' commitment to the workplace. We argue that a deeper understanding of such factors is vital, as working from home is expected to remain widespread even after the pandemic.
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The ability to develop Brain-Computer Interfaces (BCI) to Intelligent Systems would offer new perspectives in terms of human supervision of complex Artificial Intelligence (AI) systems, as well as supporting new types of applications. In this article, we introduce a basic mechanism for the control of heuristic search through fNIRS-based BCI. The rationale is that heuristic search is not only a basic AI mechanism but also one still at the heart of many different AI systems. We investigate how users' mental disposition can be harnessed to influence the performance of heuristic search algorithm through a mechanism of precision-complexity exchange. From a system perspective, we use weighted variants of the A* algorithm which have an ability to provide faster, albeit suboptimal solutions. We use recent results in affective BCI to capture a BCI signal, which is indicative of a compatible mental disposition in the user. It has been established that Prefrontal Cortex (PFC) asymmetry is strongly correlated to motivational dispositions and results anticipation, such as approach or even risk-taking, and that this asymmetry is amenable to Neurofeedback (NF) control. Since PFC asymmetry is accessible through fNIRS, we designed a BCI paradigm in which users vary their PFC asymmetry through NF during heuristic search tasks, resulting in faster solutions. This is achieved through mapping the PFC asymmetry value onto the dynamic weighting parameter of the weighted A* (WA*) algorithm. We illustrate this approach through two different experiments, one based on solving 8-puzzle configurations, and the other on path planning. In both experiments, subjects were able to speed up the computation of a solution through a reduction of search space in WA*. Our results establish the ability of subjects to intervene in heuristic search progression, with effects which are commensurate to their control of PFC asymmetry: this opens the way to new mechanisms for the implementation of hybrid cognitive systems.
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Affective brain-computer interfaces (BCI) harness Neuroscience knowledge to develop affective interaction from first principles. In this article, we explore affective engagement with a virtual agent through Neurofeedback (NF). We report an experiment where subjects engage with a virtual agent by expressing positive attitudes towards her under a NF paradigm. We use for affective input the asymmetric activity in the dorsolateral prefrontal cortex (DL-PFC), which has been previously found to be related to the high-level affective-motivational dimension of approach/avoidance. The magnitude of left-asymmetric DL-PFC activity, measured using functional near infrared spectroscopy (fNIRS) and treated as a proxy for approach, is mapped onto a control mechanism for the virtual agent's facial expressions, in which action units (AUs) are activated through a neural network. We carried out an experiment with 18 subjects, which demonstrated that subjects are able to successfully engage with the virtual agent by controlling their mental disposition through NF, and that they perceived the agent's responses as realistic and consistent with their projected mental disposition. This interaction paradigm is particularly relevant in the case of affective BCI as it facilitates the volitional activation of specific areas normally not under conscious control. Overall, our contribution reconciles a model of affect derived from brain metabolic data with an ecologically valid, yet computationally controllable, virtual affective communication environment.
