A Group Intervention to Promote Resilience in Nursing Professionals: A Randomised Controlled Trial.

In this study, a new group intervention program to foster resilience in nursing professionals was tested for efficacy. In total, 72 nurses were recruited and randomised to either an intervention condition or to a wait list control condition. The study had a pre-test, post-test, follow-up design. The eight-week program targeted six resilience factors: cognitive flexibility, coping, self-efficacy, self-esteem, self-care, and mindfulness. Compared to the control group, the intervention group reported a significant improvement in the primary outcome mental health (measured with the General Health Questionnaire) from pre-test (M = 20.79; SD = 9.85) to post-test (M = 15.81; SD = 7.13) with an estimated medium effect size (p = 0.03, η2 = 0.08) at post-test. Further significant improvements were found for resilience and other resilience related outcomes measures. The individual stressor load of the subjects was queried retrospectively in each measurement. Stress levels had a significant influence on mental health. The intervention effect was evident even though the stress level in both groups did not change significantly between the measurements. Follow-up data suggest that the effects were sustained for up to six months after intervention. The resilience intervention reduced mental burden in nurses and also positively affected several additional psychological outcomes.

The Frequent Stressor and Mental Health Monitoring-Paradigm: A Proposal for the Operationalization and Measurement of Resilience and the Identification of Resilience Processes in Longitudinal Observational Studies.

Resilience has been defined as the maintenance or quick recovery of mental health during and after times of adversity. How to operationalize resilience and to determine the factors and processes that lead to good long-term mental health outcomes in stressor-exposed individuals is a matter of ongoing debate and of critical importance for the advancement of the field. One of the biggest challenges for implementing an outcome-based definition of resilience in longitudinal observational study designs lies in the fact that real-life adversity is usually unpredictable and that its substantial qualitative as well as temporal variability between subjects often precludes defining circumscribed time windows of inter-individually comparable stressor exposure relative to which the maintenance or recovery of mental health can be determined. To address this pertinent issue, we propose to frequently and regularly monitor stressor exposure (E) and mental health problems (P) throughout a study's observation period [Frequent Stressor and Mental Health Monitoring (FRESHMO)-paradigm]. On this basis, a subject's deviation at any single monitoring time point from the study sample's normative E-P relationship (the regression residual) can be used to calculate that subject's current mental health reactivity to stressor exposure ("stressor reactivity," SR). The SR score takes into account the individual extent of experienced adversity and is comparable between and within subjects. Individual SR time courses across monitoring time points reflect intra-individual temporal variability in SR, where periods of under-reactivity (negative SR score) are associated with accumulation of fewer mental health problems than is normal for the sample. If FRESHMO is accompanied by regular measurement of potential resilience factors, temporal changes in resilience factors can be used to predict SR time courses. An increase in a resilience factor measurement explaining a lagged decrease in SR can then be considered to index a process of adaptation to stressor exposure that promotes a resilient outcome (an allostatic resilience process). This design principle allows resilience research to move beyond merely determining baseline predictors of resilience outcomes, which cannot inform about how individuals successfully adjust and adapt when confronted with adversity. Hence, FRESHMO plus regular resilience factor monitoring incorporates a dynamic-systems perspective into resilience research.

Psychological interventions to foster resilience in healthcare professionals.

BACKGROUND: Resilience can be defined as the maintenance or quick recovery of mental health during or after periods of stressor exposure, which may result from a potentially traumatising event, challenging life circumstances, a critical life transition phase, or physical illness. Healthcare professionals, such as nurses, physicians, psychologists and social workers, are exposed to various work-related stressors (e.g. patient care, time pressure, administration) and are at increased risk of developing mental disorders. This population may benefit from resilience-promoting training programmes. OBJECTIVES: To assess the effects of interventions to foster resilience in healthcare professionals, that is, healthcare staff delivering direct medical care (e.g. nurses, physicians, hospital personnel) and allied healthcare staff (e.g. social workers, psychologists). SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, 11 other databases and three trial registries from 1990 to June 2019. We checked reference lists and contacted researchers in the field. We updated this search in four key databases in June 2020, but we have not yet incorporated these results. SELECTION CRITERIA: Randomised controlled trials (RCTs) in adults aged 18 years and older who are employed as healthcare professionals, comparing any form of psychological intervention to foster resilience, hardiness or post-traumatic growth versus no intervention, wait-list, usual care, active or attention control. Primary outcomes were resilience, anxiety, depression, stress or stress perception and well-being or quality of life. Secondary outcomes were resilience factors. DATA COLLECTION AND ANALYSIS: Two review authors independently selected studies, extracted data, assessed risks of bias, and rated the certainty of the evidence using the GRADE approach (at post-test only). MAIN RESULTS: We included 44 RCTs (high-income countries: 36). Thirty-nine studies solely focused on healthcare professionals (6892 participants), including both healthcare staff delivering direct medical care and allied healthcare staff. Four studies investigated mixed samples (1000 participants) with healthcare professionals and participants working outside of the healthcare sector, and one study evaluated training for emergency personnel in general population volunteers (82 participants). The included studies were mainly conducted in a hospital setting and included physicians, nurses and different hospital personnel (37/44 studies). Participants mainly included women (68%) from young to middle adulthood (mean age range: 27 to 52.4 years). Most studies investigated group interventions (30 studies) of high training intensity (18 studies; > 12 hours/sessions), that were delivered face-to-face (29 studies). Of the included studies, 19 compared a resilience training based on combined theoretical foundation (e.g. mindfulness and cognitive-behavioural therapy) versus unspecific comparators (e.g. wait-list). The studies were funded by different sources (e.g. hospitals, universities), or a combination of different sources. Fifteen studies did not specify the source of their funding, and one study received no funding support. Risk of bias was high or unclear for most studies in performance, detection, and attrition bias domains. At post-intervention, very-low certainty evidence indicated that, compared to controls, healthcare professionals receiving resilience training may report higher levels of resilience (standardised mean difference (SMD) 0.45, 95% confidence interval (CI) 0.25 to 0.65; 12 studies, 690 participants), lower levels of depression (SMD -0.29, 95% CI -0.50 to -0.09; 14 studies, 788 participants), and lower levels of stress or stress perception (SMD -0.61, 95% CI -1.07 to -0.15; 17 studies, 997 participants). There was little or no evidence of any effect of resilience training on anxiety (SMD -0.06, 95% CI -0.35 to 0.23; 5 studies, 231 participants; very-low certainty evidence) or well-being or quality of life (SMD 0.14, 95% CI -0.01 to 0.30; 13 studies, 1494 participants; very-low certainty evidence). Effect sizes were small except for resilience and stress reduction (moderate). Data on adverse effects were available for three studies, with none reporting any adverse effects occurring during the study (very-low certainty evidence). AUTHORS' CONCLUSIONS: For healthcare professionals, there is very-low certainty evidence that, compared to control, resilience training may result in higher levels of resilience, lower levels of depression, stress or stress perception, and higher levels of certain resilience factors at post-intervention. The paucity of medium- or long-term data, heterogeneous interventions and restricted geographical distribution limit the generalisability of our results. Conclusions should therefore be drawn cautiously. The findings suggest positive effects of resilience training for healthcare professionals, but the evidence is very uncertain. There is a clear need for high-quality replications and improved study designs.

Mental Imagery Training Increases Wanting of Rewards and Reward Sensitivity and Reduces Depressive Symptoms.

High reward sensitivity and wanting of rewarding stimuli help to identify and motivate repetition of pleasant activities. This behavioral activation is thought to increase positive emotions. Therefore, both mechanisms are highly relevant for resilience against depressive symptoms. Yet, these mechanisms have not been targeted by psychotherapeutic interventions. In the present study, we tested a mental imagery training comprising eight 10-minute sessions every second day and delivered via the Internet to healthy volunteers (N = 30, 21 female, mean age of 23.8 years, Caucasian) who were preselected for low reward sensitivity. Participants were paired according to age, sex, reward sensitivity, and mental imagery ability. Then, members of each pair were randomly assigned to either the intervention or wait condition. Ratings of wanting and response bias toward probabilistic reward cues (Probabilistic Reward Task) served as primary outcomes. We further tested whether training effects extended to approach behavior (Approach Avoidance Task) and depressive symptoms (Beck Depression Inventory). The intervention led to an increase in wanting (p < .001, η2p= .45) and reward sensitivity (p = .004, η2p= .27). Further, the training group displayed faster approach toward positive edibles and activities (p = .025, η2p= .18) and reductions in depressive symptoms (p = .028, η2p= .16). Results extend existing literature by showing that mental imagery training can increase wanting of rewarding stimuli and reward sensitivity. Further, the training appears to reduce depressive symptoms and thus may foster the successful implementation of exsiting treatments for depression such as behavioral activation and could also increase resilience against depressive symptoms.

Neural correlates of valence generalization in an affective conditioning paradigm.

In case of uncertainty, predictions that are based on prior, similar experiences guide our decision by processes of generalization. Over-generalization of negative information has been identified as an important feature of several psychopathologies, including anxiety disorders and depression, and might underlie biased interpretation of ambiguous information. Here, we investigated the neural correlates of valence generalization to ambiguous stimuli using a translational affective conditioning task during fMRI. Twenty-five healthy individuals participated in a conditioning procedure with (1) an initial acquisition phase, where participants learned the positive and negative valence of two different tones (reference tones) through their responses and subsequent feedback and (2) a test phase, where participants were presented with the previously learned reference tones and three additional tones with intermediate frequency to the learned reference tones. By recording the responses to these intermediate stimuli we were able to assess the participantsí interpretation of ambiguous tones as either positive or negative. Behavioral results revealed a graded response pattern to the three intermediate tones, which was mirrored on the neural level. More specifically, parametric analyses OF BOLD responses to all five tones revealed a linear effect in bilateral anterior insula and SMA with lowest activation to the negative reference tone and highest activation to the positive negative tone. In addition, a cluster in the SMA showed a reverse-quadratic response, i.e., the strongest response for the most ambiguous tone. These findings suggest overlapping regions in the salience network that mediate valence generalization and decision-making under ambiguity, potentially underlying biased ambiguous cue interpretation.

Sensitivity to positive and negative feedback in euthymic patients with bipolar I disorder: the last episode makes the difference.

OBJECTIVES: It is unclear whether abnormalities in cognition and motivation, such as altered feedback processing, observed during euthymia represent trait markers of bipolar I disorder (BD-I) or scars from previous episodes that also occur in major depression (MD). The present research examines how previous episodes influence sensitivity to positive and negative feedback, applying multiple hierarchical regression analysis with number of past depressive and manic episodes, residual mood symptoms, affective quality of the last episode, time in remission, medication, illness severity, and age as predictors. METHODS: The study included 23 euthymic patients with BD-I, 19 remitted patients with MD, and 19 healthy persons who underwent a task which discriminates whether persons learn better from negative or positive feedback. RESULTS: For both models, predicting sensitivity to positive [F((5,60)) = 6.50, p = 0.001, adjusted R(2) = 0.22] and negative feedback [F((5,60)) = 5.12, p = 0.001, adjusted R(2) = 0.22], the quality of the last affective episode was the only significant predictor. BD-I patients who last experienced a manic episode learned well from positive but not negative feedback, whereas BD-I patients who last experienced a depressive episode showed the opposite pattern. CONCLUSIONS: Our data identify differences in response to positive and negative consequences carrying over into the euthymic state that are qualitatively related to the polarity of the preceding episode, whereas other disease-related variables had no significant influence. This sheds new light on previous inconsistent data in euthymic BD-I patients and could also guide tailored treatment.