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Medical patients' affective well-being after emergency department admission: The role of personal and social resources and health-related variables.

ABSTRACT: BACKGROUND:Medical emergency admissions are critical life events associated with considerable stress. However, research on patients' affective well-being after emergency department (ED) admission is scarce. This study investigated the course of affective well-being of medical patients following an ED admission and examined the role of personal and social resources and health-related variables. METHODS:In this longitudinal survey with a sample of 229 patients with lower respiratory tract infections and cardiac diseases (taken between October 2013 and December 2014), positive and negative affect was measured at ED admission (T1) and at follow-up after 7 days (T2), and 30 days (T3). The role of personal and social resources (emotional stability, trait resilience, affect state, and social support) as well as health-related variables (self-rated health, multimorbidity, and psychological comorbidity) in patients' affective well-being was examined by controlling for demographic characteristics using regression analyses. RESULTS:The strength of the inverse correlation between positive and negative affect decreased over time. In addition to health-related variables, higher negative affect was predicted by higher psychological comorbidity over time (T1-T3). In turn, lower positive affect was predicted by lower self-rated health (T1-T2) and higher multimorbidity (T3). In terms of personal and social resources, lower negative affect was predicted by higher emotional stability (T2), whereas higher positive affect was predicted by stronger social support (T1-T2). CONCLUSION:Knowledge about psychosocial determinants-personal and social resources and health-related variables-of patients' affective well-being following ED admission is essential for designing more effective routine screening and treatment.

SUBMITTER: Faessler L

PROVIDER: S-EPMC6426177 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Medical patients' affective well-being after emergency department admission: The role of personal and social resources and health-related variables.

Faessler Lukas L Brodbeck Jeannette J Schuetz Philipp P Haubitz Sebastian S Mueller Beat B Perrig-Chiello Pasqualina P

PloS one 20190320 3

<h4>Background</h4>Medical emergency admissions are critical life events associated with considerable stress. However, research on patients' affective well-being after emergency department (ED) admission is scarce. This study investigated the course of affective well-being of medical patients following an ED admission and examined the role of personal and social resources and health-related variables.<h4>Methods</h4>In this longitudinal survey with a sample of 229 patients with lower respiratory ...[more]

PMID: 30893347

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Project description:BackgroundEmergency medical service (EMS) can be a burdensome occupational field, and employees can be confronted with traumatizing events. Posttraumatic stress disorder (PTSD) and depression rates among paramedics are considered higher than those in the general population. In the German setting of a physician-based EMS system, the literature provides little data on PTSD or non-PTSD-related mental health or on the correlation between PTSD and well-being.MethodsThe study collected data through a nationwide cross-sectional questionnaire survey of the German EMS. Next to gathering sociodemographic data, it used the 5-item World Health Organization Well-Being Index (WHO-5) and the Short Screening Scale for the DSM-IV-PTSD to assess well-being and identify indicators of depression and PTSD.ResultsA total of 2,731 paramedics and emergency physicians participated in the survey; 2,684 questionnaires were submitted to analysis. The average WHO-5 score was 53.15%. A total of 43.4% of participants screened positive for possible depression, as indicated by a WHO-5 score below 50%. Female gender, older age, higher total years spent working in EMS and increased body mass index were significantly correlated with lower well-being. A total of 5.4% of respondents had a positive PTSD screening result. In particular, older employees were significantly more likely to test positive for PTSD (12.2% of those over 50 years, compared to 2.8% of those under 30 years). Positive PTSD screening results were associated with significantly lower well-being. Over an average period of 1 year, the paramedics reported perceiving a median of 2 emergency missions as mentally distressing.ConclusionLow well-being and PTSD seem to be relevant experiences among German EMS despite their perception of low numbers of emergency responses as mentally distressing. Paramedics who have been diagnosed with PTSD should be investigated for depression and vice versa, as correlations in both directions exist. Special attention should be paid to older employees, who have significantly lower well-being and higher PTSD rates compared to younger employees.

Project description:Social scientists have postulated that the discrepancy between achievements and expectations affects individuals' subjective well-being. Still, little has been done to qualify and quantify such a psychological effect. Our empirical analysis assesses the consequences of positive and negative affective forecasting errors-the difference between realized and expected subjective well-being-on the subsequent level of subjective well-being.We use longitudinal data on a representative sample of 13,431 individuals from the German Socio-Economic Panel. In our sample, 52% of individuals are females, average age is 43 years, average years of education is 11.4 and 27% of our sample lives in East Germany. Subjective well-being (measured by self-reported life satisfaction) is assessed on a 0-10 discrete scale and its sample average is equal to 6.75 points.We develop a simple theoretical framework to assess the consequences of positive and negative affective forecasting errors-the difference between realized and expected subjective well-being-on the subsequent level of subjective well-being, properly accounting for the endogenous adjustment of expectations to positive and negative affective forecasting errors, and use it to derive testable predictions. Given the theoretical framework, we estimate two panel-data equations, the first depicting the association between positive and negative affective forecasting errors and the successive level of subjective well-being and the second describing the correlation between subjective well-being expectations for the future and hedonic failures and successes. Our models control for individual fixed effects and a large battery of time-varying demographic characteristics, health and socio-economic status.While surpassing expectations is uncorrelated with subjective well-being, failing to match expectations is negatively associated with subsequent realizations of subjective well-being. Expectations are positively (negatively) correlated to positive (negative) forecasting errors. We speculate that in the first case the positive adjustment in expectations is strong enough to cancel out the potential positive effects on subjective well-being of beaten expectations, while in the second case it is not, and individuals persistently bear the negative emotional consequences of not achieving expectations.

Project description:ObjectiveTo predict hospital admission at the time of ED triage using patient history in addition to information collected at triage.MethodsThis retrospective study included all adult ED visits between March 2014 and July 2017 from one academic and two community emergency rooms that resulted in either admission or discharge. A total of 972 variables were extracted per patient visit. Samples were randomly partitioned into training (80%), validation (10%), and test (10%) sets. We trained a series of nine binary classifiers using logistic regression (LR), gradient boosting (XGBoost), and deep neural networks (DNN) on three dataset types: one using only triage information, one using only patient history, and one using the full set of variables. Next, we tested the potential benefit of additional training samples by training models on increasing fractions of our data. Lastly, variables of importance were identified using information gain as a metric to create a low-dimensional model.ResultsA total of 560,486 patient visits were included in the study, with an overall admission risk of 29.7%. Models trained on triage information yielded a test AUC of 0.87 for LR (95% CI 0.86-0.87), 0.87 for XGBoost (95% CI 0.87-0.88) and 0.87 for DNN (95% CI 0.87-0.88). Models trained on patient history yielded an AUC of 0.86 for LR (95% CI 0.86-0.87), 0.87 for XGBoost (95% CI 0.87-0.87) and 0.87 for DNN (95% CI 0.87-0.88). Models trained on the full set of variables yielded an AUC of 0.91 for LR (95% CI 0.91-0.91), 0.92 for XGBoost (95% CI 0.92-0.93) and 0.92 for DNN (95% CI 0.92-0.92). All algorithms reached maximum performance at 50% of the training set or less. A low-dimensional XGBoost model built on ESI level, outpatient medication counts, demographics, and hospital usage statistics yielded an AUC of 0.91 (95% CI 0.91-0.91).ConclusionMachine learning can robustly predict hospital admission using triage information and patient history. The addition of historical information improves predictive performance significantly compared to using triage information alone, highlighting the need to incorporate these variables into prediction models.

Dataset Information

Medical patients' affective well-being after emergency department admission: The role of personal and social resources and health-related variables.

Publications

Medical patients' affective well-being after emergency department admission: The role of personal and social resources and health-related variables.

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