The consumer electronics (CE) industry has high turnovers and a growing demand, such as on the home entertainment segment. At the same time, it generates e-waste of the order of a dozen million tons, about one quarter of the world's total. With the purpose of improving the environmental performance of businesses, the Waste Electrical and Electronic Equipment (WEEE) Directive was put in place in Europe. Given the high competitive environment of this industry, WEEE could be a clue for competitive edge. To create an environmental and economic win-win situation, however, companies have to master reverse logistics (RL). This is particularly challenging in fast clockspeed environments, as it is the case for the CE industry. In this paper, we develop a theoretically and empirically grounded diagnostic tool for assessing a CE company's RL practices and identifying potential for RL improvement, from a business perspective. To theoretically ground the tool, we combine specific CE literature with general theory on reverse logistics management and performance improvement. To empirically ground the tool, we collect field data by combining quantitative (a multiactor survey) with qualitative (interviews and company visits) methods. We demonstrate how our tool can be used to create awareness at senior management about the reverse logistics maturity state.
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Objective To evaluate the validity and reliability of the Dutch STarT MSK tool in patients with musculoskeletal pain in primary care physiotherapy. Methods Physiotherapists included patients with musculoskeletal pain, aged 18 years or older. Patients completed a questionnaire at baseline and follow-up at 5 days and 3 months, respectively. Construct validity was assessed by comparing scores of STarT MSK items with reference questionnaires. Pearson’s correlation coefficients were calculated to test predefined hypotheses. Test-retest reliability was evaluated by calculating quadratic-weighted kappa coefficients for overall STarT MSK tool scores (range 0–12) and prognostic subgroups (low, medium and high risk). Predictive validity was assessed by calculating relative risk ratios for moderate risk and high risk, both compared with low risk, in their ability to predict persisting disability at 3 months. Results In total, 142 patients were included in the analysis. At baseline, 74 patients (52.1%) were categorised as low risk, 64 (45.1%) as medium risk and 4 (2.8%) as high risk. For construct validity, nine of the eleven predefined hypotheses were confirmed. For test-retest reliability, kappa coefficients for the overall tool scores and prognostic subgroups were 0.71 and 0.65, respectively. For predictive validity, relative risk ratios for persisting disability were 2.19 (95% CI: 1.10–4.38) for the medium-risk group and 7.30 (95% CI: 4.11–12.98) for the highrisk group. Conclusion The Dutch STarT MSK tool showed a sufficient to good validity and reliability in patients with musculoskeletal pain in primary care physiotherapy. The sample size for high-risk patients was small (n = 4), which may limit the generalisability of findings for this group. An external validation study with a larger sample of high-risk patients (�50) is recommended.
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AIM: To systematically review the available literature on the diagnostic accuracy of questionnaires and measurement instruments for headaches associated with musculoskeletal symptoms.DESIGN: Articles were eligible for inclusion when the diagnostic accuracy (sensitivity/specificity) was established for measurement instruments for headaches associated with musculoskeletal symptoms in an adult population. The databases searched were PubMed (1966-2018), Cochrane (1898-2018) and Cinahl (1988-2018). Methodological quality was assessed with the Quality Assessment of Diagnostic Accuracy Studies tool (QUADAS-2) and COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) checklist for criterion validity. When possible, a meta-analysis was performed. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) recommendations were applied to establish the level of evidence per measurement instrument.RESULTS: From 3450 articles identified, 31 articles were included in this review. Eleven measurement instruments for migraine were identified, of which the ID-Migraine is recommended with a moderate level of evidence and a pooled sensitivity of 0.87 (95% CI: 0.85-0.89) and specificity of 0.75 (95% CI: 0.72-0.78). Six measurement instruments examined both migraine and tension-type headache and only the Headache Screening Questionnaire - Dutch version has a moderate level of evidence with a sensitivity of 0.69 (95% CI 0.55-0.80) and specificity of 0.90 (95% CI 0.77-0.96) for migraine, and a sensitivity of 0.36 (95% CI 0.21-0.54) and specificity of 0.86 (95% CI 0.74-0.92) for tension-type headache. For cervicogenic headache, only the cervical flexion rotation test was identified and had a very low level of evidence with a pooled sensitivity of 0.83 (95% CI 0.72-0.94) and specificity of 0.82 (95% CI 0.73-0.91).DISCUSSION: The current review is the first to establish an overview of the diagnostic accuracy of measurement instruments for headaches associated with musculoskeletal factors. However, as most measurement instruments were validated in one study, pooling was not always possible. Risk of bias was a serious problem for most studies, decreasing the level of evidence. More research is needed to enhance the level of evidence for existing measurement instruments for multiple headaches.
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The purpose of this article is the presentation of a multidimensional guideline for the diagnosis of anxiety and anxiety-related behavior problems in people with intellectual disability (ID), with a substantial role for the nurse in this diagnostic process. DESIGN AND METHODS: The guideline is illustrated by a case report of a woman with ID with severe problems. FINDINGS: It appears that a multidimensional diagnostic approach involving multidisciplinary team efforts can result in a more accurate diagnosis and improved subsequent treatment. PRACTICE IMPLICATIONS: Nurses should be engaged in the diagnostic process because of their ability to make direct observations and to actively participate in carrying out all parts of the guideline.
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Western-European consumers have become not only more demanding on product availability in retail outlets but also on other food attributes such as quality, integrity, and safety. When (re)designing food supply-chain networks, from a logistics point of view, one has to consider these demands next to traditional efficiency and responsiveness requirements. The concept ‘quality controlled logistics’ (QCL) hypothesizes that if product quality in each step of the supply chain can be predicted in advance, goods flows can be controlled in a pro-active manner and better chain designs can be established resulting in higher product availability, constant quality, and less product losses. The paper discusses opportunities of using real-time product quality information for improvement of the design and management of ‘AgriFood Supply Chain Networks’, and presents a preliminary diagnostic instrument for assessment of ‘critical quality’ and ‘logistics control’ points in the supply chain network. Results of a tomato-chain case illustrate the added value of the QCL concept for identifying improvement opportunities in the supply chain as to increase both product availability and quality. Future research aims for the further development of the diagnostic instrument and the quantification of costs and benefits of QCL scenarios.
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Abstract Background One of the most problematic expression of ageing is frailty, and an approach based on its early identification is mandatory. The Sunfrail-tool (ST), a 9-item questionnaire, is a promising instrument for screening frailty. Aims • To assess the diagnostic accuracy and the construct validity between the ST and a Comprehensive Geriatric Assessment (CGA), composed by six tests representative of the bio-psycho-social model of frailty; • To verify the discriminating power of five key-questions of the ST; • To investigate the role of the ST in a clinical-pathway of falls’ prevention. Methods In this retrospective study, we enrolled 235 patients from the Frailty-Multimorbidity Lab of the University-Hospital of Parma. The STs’ answers were obtained from the patient’s clinical information. A patient was considered frail if at least one of the CGAs’ tests resulted positive. Results The ST was associated with the CGA’s judgement with an Area Under the Curve of 0.691 (CI 95%: 0.591–0.791). Each CGA’s test was associated with the ST total score. The five key-question showed a potential discriminating power in the CGA’s tests of the corresponding domains. The fall-related question of the ST was significantly associated with the Short Physical Performance Battery total score (OR: 0.839, CI 95%: 0.766–0.918), a proxy of the risk of falling. Discussion The results suggest that the ST can capture the complexity of frailty. The ST showed a good discriminating power, and it can guide a second-level assessment to key frailty domains and/or clinical pathways. Conclusions The ST is a valid and easy-to-use instrument for the screening of frailty.
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Light intensity and spectral composition notably impact the human circadian rhythm. The human body is a physiological system that regulates its sleep-awake cycle through a constant rhythm of light and darkness. For a long time, the lighting research field has been concerned with understanding this circadian rhythm to improve people's quality of life. To better understand the influence of light on the human circadian rhythm, a remote monitoring device was developed that reliably measures the light spectrum and human circadian rhythm in different environments, including Antarctica and a tropical location study. The designed apparatus aims to facilitate the comprehension of the impact of light on the human circadian rhythm and provide accessible measurements through cost-effective tools. Results show that the developed monitoring prototype can collect and transmit environmental and human data. Therefore, the low-cost equipment developed can be reproduced and used by research institutions to collect data in different environments and improve the understanding of the influence of light on human activities. The cross-sectional analysis of the collected data revealed evidence of the significant influence of light on regulating the human circadian rhythm in tropical and Antarctica case studies. The collected information makes it possible to predict human reactions to the light environment, correlate these responses with seasonal periods, and comprehend how various forms of artificial and natural light interact with individuals and their living spaces. This prototype offers a non-invasive tool for assessing sleep quality and daytime activities, providing knowledge of how lighting conditions can impact overall well-being.
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In practice, faults in building installations are seldom noticed because automated systems to diagnose such faults are not common use, despite many proposed methods: they are cumbersome to apply and not matching the way of thinking of HVAC engineers. Additionally, fault diagnosis and energy performance diagnosis are seldom combined, while energy wastage is mostly a consequence of component, sensors or control faults. In this paper new advances on the 4S3F diagnose framework for automated diagnostic of energy waste in HVAC systems are presented. The architecture of HVAC systems can be derived from a process and instrumentation diagram (P&ID) usually set up by HVAC designers. The paper demonstrates how all possible faults and symptoms can be extracted on a very structured way from the P&ID, and classified in 4 types of symptoms (deviations from balance equations, operational states, energy performances or additional information) and 3 types of faults (component, control and model faults). Symptoms and faults are related to each other through Diagnostic Bayesian Networks (DBNs) which work as an expert system. During operation of the HVAC system the data from the BMS is converted to symptoms, which are fed to the DBN. The DBN analyses the symptoms and determines the probability of faults. Generic indicators are proposed for the 4 types of symptoms. Standard DBN models for common components, controls and models are developed and it is demonstrated how to combine them in order to represent the complete HVAC system. Both the symptom and the fault identification parts are tested on historical BMS data of an ATES system including heat pump, boiler, solar panels, and hydronic systems. The energy savings resulting from fault corrections are estimated and amount 25%. Finally, the 4S3F method is extended to hard and soft sensor faults. Sensors are the core of any FDD system and any control system. Automated diagnostic of sensor faults is therefore essential. By considering hard sensors as components and soft sensors as models, they can be integrated into the 4S3F method.
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Due to the ageing population, the prevalence of musculoskeletal disorders will continue to rise, as well as healthcare expenditure. To overcome these increasing expenditures, integration of orthopaedic care should be stimulated. The Primary Care Plus (PC+) intervention aimed to achieve this by facilitating collaboration between primary care and the hospital, in which specialised medical care is shifted to a primary care setting. The present study aims to evaluate the referral decision following orthopaedic care in PC+ and in particular to evaluate the influence of diagnostic tests on this decision. Therefore, retrospective monitoring data of patients visiting PC+ for orthopaedic care was used. Data was divided into two periods; P1 and P2. During P2, specialists in PC+ were able to request additional diagnostic tests (such as ultrasounds and MRIs). A total of 2,438 patients visiting PC+ for orthopaedic care were included in the analysis. The primary outcome was the referral decision following PC+ (back to the general practitioner (GP) or referral to outpatient hospital care). Independent variables were consultation- and patient-related predictors. To describe variations in the referral decision, logistic regression modelling was used. Results show that during P2, significantly more patients were referred back to their GP. Moreover, the multivariable analysis show a significant effect of patient age on the referral decision (OR 0.86, 95% CI = 0.81– 0.91) and a significant interaction was found between the treating specialist and the period (p = 0.015) and between patient’s diagnosis and the period (p < 0.001). Despite the significant impact of the possibility of requesting additional diagnostic tests in PC+, it is important to discuss the extent to which the availability of diagnostic tests fits within the vision of PC+. In addition, selecting appropriate profiles for specialists and patients for PC+ are necessary to further optimise the effectiveness and cost of care.
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