Current methods for energy diagnosis in heating, ventilation and air conditioning (HVAC) systems are not consistent with process and instrumentation diagrams (P&IDs) as used by engineers to design and operate these systems, leading to very limited application of energy performance diagnosis in practice. In a previous paper, a generic reference architecture – hereafter referred to as the 4S3F (four symptoms and three faults) framework – was developed. Because it is closely related to the way HVAC experts diagnose problems in HVAC installations, 4S3F largely overcomes the problem of limited application. The present article addresses the fault diagnosis process using automated fault identification (AFI) based on symptoms detected with a diagnostic Bayesian network (DBN). It demonstrates that possible faults can be extracted from P&IDs at different levels and that P&IDs form the basis for setting up effective DBNs. The process was applied to real sensor data for a whole year. In a case study for a thermal energy plant, control faults were successfully isolated using balance, energy performance and operational state symptoms. Correction of the isolated faults led to annual primary energy savings of 25%. An analysis showed that the values of set probabilities in the DBN model are not outcome-sensitive. Link to the formal publication via its DOI https://doi.org/10.1016/j.enbuild.2020.110289
ObjectiveTo evaluate the effectiveness of psychosomatic therapy versus care as usual in primary care for patients with persistent somatic symptoms (PSS).MethodsWe conducted a pragmatic, two-armed, randomised controlled trial among primary care patients with PSS in the Netherlands that included 39 general practices and 34 psychosomatic therapists. The intervention, psychosomatic therapy, consisted of 6–12 sessions delivered by specialised exercise- and physiotherapists. Primary outcome measure: patient's level of functioning. Secondary outcomes: severity of physical and psychosocial symptoms, health-related quality of life, health-related anxiety, illness behaviour and number of GP contacts.ResultsCompared to usual care (n = 85), the intervention group (n = 84) showed no improvement in patient's level of functioning (mean difference − 0.50 [95% CI -1.10 to 0.10]; p = .10), and improvement in health-related anxiety (mean difference − 1.93 [95% CI -3.81 to −0.04]; p = .045), over 12 months. At 5-month follow-up, we found improvement in physical functioning, somatisation, and health-related anxiety. The 12-month follow-up revealed no therapy effects. Subgroup analyses showed an overall effect in patient's level of functioning for the group with moderate PSS (mean difference − 0.91 [95% CI -1.78 to −0.03]; p = .042). In the year after the end of therapy, the number of GP contacts did not differ significantly between the two groups.ConclusionWe only found effects on some secondary outcome measures, and on our primary outcome measure especially in patients with moderate PSS, the psychosomatic therapy appears promising for further study.Trial registration: the trial is registered in the Netherlands Trial Registry, https://trialsearch.who.int/Trial2.aspx?TrialID=NTR7356 under ID NTR7356.
MULTIFILE
Background: The aim of this study is to validate a newly developed nurses' self-efficacy sources inventory. We test the validity of a five-dimensional model of sources of self-efficacy, which we contrast with the traditional four-dimensional model based on Bandura's theoretical concepts. Methods: Confirmatory factor analysis was used in the development of the newly developed self-efficacy measure. Model fit was evaluated based upon commonly recommended goodness-of-fit indices, including the χ2 of the model fit, the Root Mean Square Error of approximation (RMSEA), the Tucker-Lewis Index (TLI), the Standardized Root Mean Square Residual (SRMR), and the Bayesian Information Criterion (BIC). Results: All 22 items of the newly developed five-factor sources of self-efficacy have high factor loadings (range .40-.80). Structural equation modeling showed that a five-factor model is favoured over the four-factor model. Conclusions and implications: Results of this study show that differentiation of the vicarious experience source into a peer- and expert based source reflects better how nursing students develop self-efficacy beliefs. This has implications for clinical learning environments: a better and differentiated use of self-efficacy sources can stimulate the professional development of nursing students.
