Job Resources and Matching Active Coping Styles as Moderators of the Longitudinal Relation Between Job Demands and Job Strain

Background: Only in a few longitudinal studies it has been examined whether job resources should be matched to job demands to show stress-buffering effects of job resources (matching hypothesis), while there are no empirical studies in which the moderating effect of matching personal characteristics on the stress-buffering effect of job resources has been examined. Purpose: In this study, both the matching hypothesis and the moderating effect of matching active coping styles were examined with respect to the longitudinal relation between job demands, job resources, and job strain.Method: The study group consisted of 317 beginning teachers from Belgium. The two-wave survey data with a 1-year time lag were analyzed by means of structural equation modeling and multiple group analyses. Results: Data did not support the matching hypothesis. In addition, no support was found for the moderating effect of specific active coping styles, irrespective of the level of match. Conclusion: To show stress-buffering effects of job resources, it seems to make no difference whether or not specific types of job demands and job resources are matched, and whether or not individual differences in specific active coping styles are taken into account

Cost impact of procalcitonin-guided decision making on duration of antibiotic therapy for suspected early-onset sepsis in neonates

Abstract Backgrounds The large, international, randomized controlled NeoPInS trial showed that procalcitonin (PCT)-guided decision making was superior to standard care in reducing the duration of antibiotic therapy and hospitalization in neonates suspected of early-onset sepsis (EOS), without increased adverse events. This study aimed to perform a cost-minimization study of the NeoPInS trial, comparing health care costs of standard care and PCT-guided decision making based on the NeoPInS algorithm, and to analyze subgroups based on country, risk category and gestational age. Methods Data from the NeoPInS trial in neonates born after 34 weeks of gestational age with suspected EOS in the first 72 h of life requiring antibiotic therapy were used. We performed a cost-minimization study of health care costs, comparing standard care to PCT-guided decision making. Results In total, 1489 neonates were included in the study, of which 754 were treated according to PCT-guided decision making and 735 received standard care. Mean health care costs of PCT-guided decision making were not significantly different from costs of standard care (€3649 vs. €3616). Considering subgroups, we found a significant reduction in health care costs of PCT-guided decision making for risk category ‘infection unlikely’ and for gestational age ≥ 37 weeks in the Netherlands, Switzerland and the Czech Republic, and for gestational age < 37 weeks in the Czech Republic. Conclusions Health care costs of PCT-guided decision making of term and late-preterm neonates with suspected EOS are not significantly different from costs of standard care. Significant cost reduction was found for risk category ‘infection unlikely,’ and is affected by both the price of PCT-testing and (prolonged) hospitalization due to SAEs

Machine learning used to compare the diagnostic accuracy of risk factors, clinical signs and biomarkers and to develop a new prediction model for neonatal early-onset sepsis

Background: Current strategies for risk stratification and prediction of neonatal early-onset sepsis (EOS) are inefficient and lack diagnostic performance. The aim of this study was to use machine learning to analyze the diagnostic accuracy of risk factors (RFs), clinical signs and biomarkers and to develop a prediction model for culture-proven EOS. We hypothesized that the contribution to diagnostic accuracy of biomarkers is higher than of RFs or clinical signs. Study Design: Secondary analysis of the prospective international multicenter NeoPInS study. Neonates born after completed 34 weeks of gestation with antibiotic therapy due to suspected EOS within the first 72 hours of life participated. Primary outcome was defined as predictive performance for culture-proven EOS with variables known at the start of antibiotic therapy. Machine learning was used in form of a random forest classifier. Results: One thousand six hundred eighty-five neonates treated for suspected infection were analyzed. Biomarkers were superior to clinical signs and RFs for prediction of culture-proven EOS. C-reactive protein and white blood cells were most important for the prediction of the culture result. Our full model achieved an area-under-the-receiver-operating-characteristic-curve of 83.41% (±8.8%) and an area-under-the-precision-recall-curve of 28.42% (±11.5%). The predictive performance of the model with RFs alone was comparable with random. Conclusions: Biomarkers have to be considered in algorithms for the management of neonates suspected of EOS. A 2-step approach with a screening tool for all neonates in combination with our model in the preselected population with an increased risk for EOS may have the potential to reduce the start of unnecessary antibiotics

Acute seizure risk in patients with encephalitis: development and validation of clinical prediction models from two independent prospective multicentre cohorts

ObjectiveIn patients with encephalitis, the development of acute symptomatic seizures is highly variable, but when present is associated with a worse outcome. We aimed to determine the factors associated with seizures in encephalitis and develop a clinical prediction model.MethodsWe analysed 203 patients from 24 English hospitals (2005–2008) (Cohort 1). Outcome measures were seizures prior to and during admission, inpatient seizures and status epilepticus. A binary logistic regression risk model was converted to a clinical score and independently validated on an additional 233 patients from 31 UK hospitals (2013–2016) (Cohort 2).ResultsIn Cohort 1, 121 (60%) patients had a seizure including 103 (51%) with inpatient seizures. Admission Glasgow Coma Scale (GCS) ≤8/15 was predictive of subsequent inpatient seizures (OR (95% CI) 5.55 (2.10 to 14.64), p&lt;0.001), including in those without a history of prior seizures at presentation (OR 6.57 (95% CI 1.37 to 31.5), p=0.025).A clinical model of overall seizure risk identified admission GCS along with aetiology (autoantibody-associated OR 11.99 (95% CI 2.09 to 68.86) and Herpes simplex virus 3.58 (95% CI 1.06 to 12.12)) (area under receiver operating characteristics curve (AUROC) =0.75 (95% CI 0.701 to 0.848), p&lt;0.001). The same model was externally validated in Cohort 2 (AUROC=0.744 (95% CI 0.677 to 0.811), p&lt;0.001). A clinical scoring system for stratifying inpatient seizure risk by decile demonstrated good discrimination using variables available on admission; age, GCS and fever (AUROC=0.716 (95% CI 0.634 to 0.798), p&lt;0.001) and once probable aetiology established (AUROC=0.761 (95% CI 0.6840.839), p&lt;0.001).ConclusionAge, GCS, fever and aetiology can effectively stratify acute seizure risk in patients with encephalitis. These findings can support the development of targeted interventions and aid clinical trial design for antiseizure medication prophylaxis.</jats:sec

C-Reactive Protein, Procalcitonin, and White Blood Count to Rule Out Neonatal Early-onset Sepsis Within 36 Hours: A Secondary Analysis of the Neonatal Procalcitonin Intervention Study.

BACKGROUND: Neonatal early-onset sepsis (EOS) is one of the main causes of global neonatal mortality and morbidity, and initiation of early antibiotic treatment is key. However, antibiotics may be harmful. METHODS: We performed a secondary analysis of results from the Neonatal Procalcitonin Intervention Study, a prospective, multicenter, randomized, controlled intervention study. The primary outcome was the diagnostic accuracy of serial measurements of C-reactive protein (CRP), procalcitonin (PCT), and white blood count (WBC) within different time windows to rule out culture-positive EOS (proven sepsis). RESULTS: We analyzed 1678 neonates with 10 899 biomarker measurements (4654 CRP, 2047 PCT, and 4198 WBC) obtained within the first 48 hours after the start of antibiotic therapy due to suspected EOS. The areas under the curve (AUC) comparing no sepsis vs proven sepsis for maximum values of CRP, PCT, and WBC within 36 hours were 0.986, 0.921, and 0.360, respectively. The AUCs for CRP and PCT increased with extended time frames up to 36 hours, but there was no further difference between start to 36 hours vs start to 48 hours. Cutoff values at 16 mg/L for CRP and 2.8 ng/L for PCT provided a sensitivity of 100% for discriminating no sepsis vs proven sepsis. CONCLUSIONS: Normal serial CRP and PCT measurements within 36 hours after the start of empiric antibiotic therapy can exclude the presence of neonatal EOS with a high probability. The negative predictive values of CRP and PCT do not increase after 36 hours

Exploring UK medical school differences: the MedDifs study of selection, teaching, student and F1 perceptions, postgraduate outcomes and fitness to practise

BACKGROUND: Medical schools differ, particularly in their teaching, but it is unclear whether such differences matter, although influential claims are often made. The Medical School Differences (MedDifs) study brings together a wide range of measures of UK medical schools, including postgraduate performance, fitness to practise issues, specialty choice, preparedness, satisfaction, teaching styles, entry criteria and institutional factors. METHOD: Aggregated data were collected for 50 measures across 29 UK medical schools. Data include institutional history (e.g. rate of production of hospital and GP specialists in the past), curricular influences (e.g. PBL schools, spend per student, staff-student ratio), selection measures (e.g. entry grades), teaching and assessment (e.g. traditional vs PBL, specialty teaching, self-regulated learning), student satisfaction, Foundation selection scores, Foundation satisfaction, postgraduate examination performance and fitness to practise (postgraduate progression, GMC sanctions). Six specialties (General Practice, Psychiatry, Anaesthetics, Obstetrics and Gynaecology, Internal Medicine, Surgery) were examined in more detail. RESULTS: Medical school differences are stable across time (median alpha = 0.835). The 50 measures were highly correlated, 395 (32.2%) of 1225 correlations being significant with p < 0.05, and 201 (16.4%) reached a Tukey-adjusted criterion of p < 0.0025. Problem-based learning (PBL) schools differ on many measures, including lower performance on postgraduate assessments. While these are in part explained by lower entry grades, a surprising finding is that schools such as PBL schools which reported greater student satisfaction with feedback also showed lower performance at postgraduate examinations. More medical school teaching of psychiatry, surgery and anaesthetics did not result in more specialist trainees. Schools that taught more general practice did have more graduates entering GP training, but those graduates performed less well in MRCGP examinations, the negative correlation resulting from numbers of GP trainees and exam outcomes being affected both by non-traditional teaching and by greater historical production of GPs. Postgraduate exam outcomes were also higher in schools with more self-regulated learning, but lower in larger medical schools. A path model for 29 measures found a complex causal nexus, most measures causing or being caused by other measures. Postgraduate exam performance was influenced by earlier attainment, at entry to Foundation and entry to medical school (the so-called academic backbone), and by self-regulated learning. Foundation measures of satisfaction, including preparedness, had no subsequent influence on outcomes. Fitness to practise issues were more frequent in schools producing more male graduates and more GPs. CONCLUSIONS: Medical schools differ in large numbers of ways that are causally interconnected. Differences between schools in postgraduate examination performance, training problems and GMC sanctions have important implications for the quality of patient care and patient safety

The Analysis of Teaching of Medical Schools (AToMS) survey: an analysis of 47,258 timetabled teaching events in 25 UK medical schools relating to timing, duration, teaching formats, teaching content, and problem-based learning

BACKGROUND: What subjects UK medical schools teach, what ways they teach subjects, and how much they teach those subjects is unclear. Whether teaching differences matter is a separate, important question. This study provides a detailed picture of timetabled undergraduate teaching activity at 25 UK medical schools, particularly in relation to problem-based learning (PBL). METHOD: The Analysis of Teaching of Medical Schools (AToMS) survey used detailed timetables provided by 25 schools with standard 5-year courses. Timetabled teaching events were coded in terms of course year, duration, teaching format, and teaching content. Ten schools used PBL. Teaching times from timetables were validated against two other studies that had assessed GP teaching and lecture, seminar, and tutorial times. RESULTS: A total of 47,258 timetabled teaching events in the academic year 2014/2015 were analysed, including SSCs (student-selected components) and elective studies. A typical UK medical student receives 3960 timetabled hours of teaching during their 5-year course. There was a clear difference between the initial 2 years which mostly contained basic medical science content and the later 3 years which mostly consisted of clinical teaching, although some clinical teaching occurs in the first 2 years. Medical schools differed in duration, format, and content of teaching. Two main factors underlay most of the variation between schools, Traditional vs PBL teaching and Structured vs Unstructured teaching. A curriculum map comparing medical schools was constructed using those factors. PBL schools differed on a number of measures, having more PBL teaching time, fewer lectures, more GP teaching, less surgery, less formal teaching of basic science, and more sessions with unspecified content. DISCUSSION: UK medical schools differ in both format and content of teaching. PBL and non-PBL schools clearly differ, albeit with substantial variation within groups, and overlap in the middle. The important question of whether differences in teaching matter in terms of outcomes is analysed in a companion study (MedDifs) which examines how teaching differences relate to university infrastructure, entry requirements, student perceptions, and outcomes in Foundation Programme and postgraduate training

The Analysis of Teaching of Medical Schools (AToMS) survey: an analysis of 47,258 timetabled teaching events in 25 UK medical schools relating to timing, duration, teaching formats, teaching content, and problem-based learning

Background What subjects UK medical schools teach, what ways they teach subjects, and how much they teach those subjects is unclear. Whether teaching differences matter is a separate, important question. This study provides a detailed picture of timetabled undergraduate teaching activity at 25 UK medical schools, particularly in relation to problem-based learning (PBL). Method The Analysis of Teaching of Medical Schools (AToMS) survey used detailed timetables provided by 25 schools with standard 5-year courses. Timetabled teaching events were coded in terms of course year, duration, teaching format, and teaching content. Ten schools used PBL. Teaching times from timetables were validated against two other studies that had assessed GP teaching and lecture, seminar, and tutorial times. Results A total of 47,258 timetabled teaching events in the academic year 2014/2015 were analysed, including SSCs (student-selected components) and elective studies. A typical UK medical student receives 3960 timetabled hours of teaching during their 5-year course. There was a clear difference between the initial 2 years which mostly contained basic medical science content and the later 3 years which mostly consisted of clinical teaching, although some clinical teaching occurs in the first 2 years. Medical schools differed in duration, format, and content of teaching. Two main factors underlay most of the variation between schools, Traditional vs PBL teaching and Structured vs Unstructured teaching. A curriculum map comparing medical schools was constructed using those factors. PBL schools differed on a number of measures, having more PBL teaching time, fewer lectures, more GP teaching, less surgery, less formal teaching of basic science, and more sessions with unspecified content. Discussion UK medical schools differ in both format and content of teaching. PBL and non-PBL schools clearly differ, albeit with substantial variation within groups, and overlap in the middle. The important question of whether differences in teaching matter in terms of outcomes is analysed in a companion study (MedDifs) which examines how teaching differences relate to university infrastructure, entry requirements, student perceptions, and outcomes in Foundation Programme and postgraduate training

Job demands, job resources, and self-regulatory behavior : exploring the issue of match

In the field of Industrial and Organizational psychology, several job stress models have been developed that aim to explain the relation between job demands, job resources, and job strain. One of these job stress models is the Demand-Induced Strain Compensation (DISC) Model. The aim of this thesis was to test two key assumptions underlying the DISC Model. The first key assumption was that specific types of job demands (i.e. cognitive, emotional, and physical job demands) can best be dealt with through the activation of job resources that correspond to the type of job demands concerned (i.e. matching job resources) rather than job resources that do not correspond to the type of job demands concerned (i.e. non-matching job resources). The second key assumption was that workers who are confronted with a specific type of demanding situation at work, are generally inclined to use matching job resources to deal with these job demands. To test these two key assumptions, five studies were designed that together make up a triptych. In the first part of the triptych, the first key assumption was tested (Chapter 2). The second key assumption was tested in the second and third part of the triptych. This latter assumption was tested from two different perspectives. More specifically, in the second part of the triptych (Chapters 3 and 4), two studies were designed to gain a better understanding of the self-regulation processes involved in the activation of job resources (i.e. alertness to available job resources, evaluation of the relevance of job resources, and decision making regarding the actual use of job resources). In the third part of the triptych (Chapters 5 and 6), the moderating effect of worker’s personal characteristics (i.e. specific active coping styles and regulatory focus) on the stress-buffering effect of job resources was examined, assuming that these person variables facilitate/inhibit the activation of job resources in demanding situations at work. The studies in Chapters 2 to 6 are summarized below. A review of 29 DISC studies (Chapter 2) was conducted to test both the matching hypothesis (i.e. moderating effects of job resources are more likely to occur in case of a match between job demands and job resources than in case of a non-match) and its extended version, the triple match principle (i.e. the likelihood of finding moderating effects of job resources increases as the level of match between demands, resources, and outcomes increases). Results showed that the matching hypothesis and the triple match principle were partly supported with respect to the stress-buffering effect of job resources, whereas no support was found with respect to the activation-enhancing effect of job resources. In Chapter 3, a quasi-experimental survey study with vignettes was conducted among 217 Dutch service workers. The aim of this study was to examine workers' beliefs about the availability, relevance, and use of specific types of job resources in similar types of demanding situations at work. Results revealed that workers who are faced with high job demands generally opt for matching job resources, both in terms of relevance and use. However, despite their preference for matching job resources, workers were also inclined to use less functional non-matching job resources. Because the activation of non-matching job resources seems to be an important aspect of people’s self-regulatory behavior in demanding situations at work, a second vignette study was conducted among 92 undergraduates from a Dutch university of technology (Chapter 4). The aim of this study was to examine the extent to which people would use non-matching job resources as a substitute for matching job resources, and as a supplement to matching job resources. Results showed that, in case of high job demands, people were generally inclined to use matching job resources, and that they would use non-matching job resources more often as a supplement to matching job resources than as a substitute for matching job resources. In Chapter 5, a longitudinal survey study was conducted among 317 Belgian teachers. The aim of this study was to examine whether stress-buffering effects of job resources on the longitudinal relation between job demands and job strain are more likely to occur for workers with a specific active coping style that corresponds to the type of job resources concerned than workers with a specific active coping style that does not correspond to the type of job resources concerned. Three types of active coping styles were distinguished (i.e. cognitive, emotional, and physical active coping styles). However, because neither type of active coping style interacted with job resources to moderate the longitudinal relation between job demands and job strain, there was no statistical rationale for testing the synergistic effect of matching (versus non-matching) active coping styles. In Chapter 6, a daily diary study was conducted among 64 Dutch nursing home nurses to examine whether within-person stress-buffering effects of job resources on the short-term relation between job demands and job strain (i.e. at day level) are more likely to be found for workers who are predominantly promotion focused than workers who are predominantly prevention focused. Results revealed that regulatory focus did not make a significant contribution to the prediction of job strain, implying that there was no support for the moderating effect of regulatory focus. In all, the studies in this thesis suggested that, as far as the stress-buffering effect of job resources is concerned, matching job resources are more functional resources than non-matching job resources to deal with specific types of demanding situations at work. In addition, it can be concluded that, in case of high job demands, people generally seem to have a strong preference for matching job resources, both in terms of relevance and use. Although the activation of non-matching job resources also appears to be an important aspect of people’s self-regulatory behavior in demanding situations at work, non-matching job resources seem particularly likely to be used as a supplement to matching job resources rather than as a substitute for matching job resources. Worker’s personal characteristics (i.e. specific active coping styles and regulatory focus) did not moderate the stress-buffering effect of job resources, suggesting that the activation of job resources does not relate to these particular person variables. In anticipation of future research on the DISC Model, it can therefore be tentatively concluded that the DISC Model as it stands now seems warranted, regarding both the key assumption the DISC Model’s predictions have been based on and the type of predictors (i.e. job characteristics) included in the model