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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.
Aims: Inadequate treatment is one of the factors interfering with a successful social and working life. Among students, it can impair their health and learning progress. In the field of medicine the problem of inadequate treatment seems widespread. This study examines wether inadequate treatment in internships differs between medicine and other academic disciplines.
Method: Using a questionnaire, the frequency, forms and severity of inadequate treatment among students were compared between the disciplines of medicine, civil engineering and teaching.
Results: 69,3% of medical students reported inadequate treatment during their internships, about twice as many as students of other disciplines. The ratios of verbal, non-verbal and organisational inadequate treatment were similar between the different academic disciplines. However, medical students executed tasks without receiving sufficient safety precautions or training significantly more often (sevenfold) than students of other disciplines. In total however, the experienced incidents of inadequate treatment were seen as similarly severe across the different academic fields.
Conclusion: Inadequate treatment of students during internships is a larger problem in medicine than in civil engineering or teaching, particularly concerning the performance of unsafe tasks. With regard to the health of students and patients, inadequate treatment in the medical education should be tackled. Previous studies suggest that this goal can be achieved only through longtime extensive measures on the level of students, lecturers, faculty and teaching hospitals.
Background: The alpha7 nicotinic acetylcholine receptor (Chrna7) plays an essential anti-inflammatory role in immune homeostasis and was recently found on mast cells (MC). Psychosocial stress can trigger MC hyperactivation and increases pro-inflammatory cytokines in target tissues such as the skin. If the cholinergic system (CS) and Chrna7 ligands play a role in these cascades is largely unknown. Objective: To elucidate the role of the CS in the response to psychosocial stress using a mouse-model for stress-triggered cutaneous inflammatory circuits. Methods: Key CS markers (ACh, Ch, SLURP-1, SLURP-2, Lynx1, Chrm3, Chrna7, Chrna9, ChAT, VAChT, Oct3, AChE, and BChE) in skin and its MC (sMC), MC activation, immune parameters (TNFα, IL1β, IL10, TGFβ, HIF1α, and STAT3) and oxidative stress were analyzed in skin from 24 h noise-stressed mice and in cultured MC (cMC) from C57BL/6 or Chrna7-Knockout mice. Results: First, Chrna7 and SLURP-1 mRNA were exclusively upregulated in stressed skin. Second, histomorphometry located Chrna7 and SLURP-1 in nerves and sMC and demonstrated upregulated contacts and increased Chrna7+ sMC in stressed skin, while 5 ng/mL SLURP-1 degranulated cMC. Third, IL1β+ sMC were high in stressed skin, and while SLURP-1 alone had no significant effect on cMC cytokines, it upregulated IL1β in cMC from Chrna7-KO and in IL1β-treated wildtype cMC. In addition, HIF1α+ sMC were high in stressed skin and Chrna7-agonist AR-R 17779 induced ROS in cMC while SLURP-1 upregulated TNFα and IL1β in cMC when HIF1α was blocked. Conclusions: These data infer that the CS plays a role in the regulation of stress-sensitive inflammatory responses but may have a surprising pro-inflammatory effect in healthy skin, driving IL1β expression if SLURP-1 is involved.