Assessing patient experience and attitude: BSC-PATIENT development, translation, and psychometric evaluation - a cross-sectional study

Background Improving the healthcare sector in Palestinian territories is challenging. Organizations frequently use the balanced scorecard (BSC) for performance evaluation (PE) worldwide. BSC includes an evaluation of five perspectives: financial, customer, internal process, knowledge and innovation, and environmental. Most HealthCare Organizations (HCO) evaluated patient satisfaction in BSC, but none considered engaging patients in the evaluation process. This paper aims to develop an instrument to engage patients in assessing BSC perspectives (BSC-PATIENT) and customize it for Palestinian hospitals. Methods This is a cross-sectional study. Two panels of experts participated in the item generation of BSC-PATIENT. Forward and backward translation processes from English to Arabic and vice versa were performed. Pretesting was performed for 30 patients at one hospital. Then, 1000 patients were recruited at 14 hospitals between January and October 2021. Construct validity was tested through exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Additionally, the composite reliability (CR), interitem correlation (IIC), and corrected item total correlation (CITC) were assessed to find redundant and low correlated items. Results The scales had high adequate model fit in EFA and CFA. All items included had loadings higher than 0.50. Although the convergent validity was less than 0.50 for some constructs, their discriminant validity, CR, IIC, and CITC showed satisfactory results except the services experience (SERV EXR) construct, which had a CR of 0.50. The final best fit model in CFA comprised ten constructs with 34 items. Conclusion BSC-PATIENT is the first self-administered questionnaire specially developed to engage patients in evaluating their experiences and attitudes based on the BSC perspectives. The questionnaire scales were carried out following relevant guidelines and regulations. The results showed adequacy in the psychometric properties of this instrument. Three-point Likert scales are recommended to assess patient experiences and attitudes since they have higher response rates. Future research can be conducted using this instrument to evaluate the impact of patient experience on attitudes toward BSC perspectives and compare the differences based on patient and hospital characteristics.

Electrical load forecasting through long short term memory

For a power supplier, meeting demand-supply equilibrium is of utmost importance. Electrical energy must be generated according to demand, as a large amount of electrical energy cannot be stored. For the proper functioning of a power supply system, an adequate model for predicting load is a necessity. In the present world, in almost every industry, whether it be healthcare, agriculture, and consulting, growing digitization and automation is a prominent feature. As a result, large sets of data related to these industries are being generated, which when subjected to rigorous analysis, yield out-of-the-box methods to optimize the business and services offered. This paper aims to ascertain the viability of long short term memory (LSTM) neural networks, a recurrent neural network capable of handling both long-term and short-term dependencies of data sets, for predicting load that is to be met by a Dispatch Center located in a major city. The result shows appreciable accuracy in forecasting future demand.

Psychometric Testing and Semantic Validation of Child Abuse Screening Tool in Urdu Language

Child abuse screening tool (CAST) has been used broadly for measuring maltreatment against children. The present study aimed to translate and validate the Child Abuse Screening Tool for two main purposes. Firstly, this scale was translated to use it as a screening tool for the abused children. Secondly, to determine concurrent validity of indigenous Child Abuse Scale (Malik & Shah, 2007) Revision by Malik and Saeed (2014). The Child Abuse Scale Revised was altered to address issues related to child abuse and sexual abuse in educational institutions, home, work place, by relatives, stranagers and servants. The scale was translated using standardized procedure of forward and backward translation. Confirmatory factor analysis was run to examine the factorial structure of Urdu translation of the scale. Convergent and discriminant analysis revealed construct validity of CAST. The results of CFA show adequate model fit; supporting the five factor solution of original scale. Thus, reliability and validity analysis indicated that the Urdu translated CAST scale is a valid and reliable tool for screening abused children in Pakistan.Keywords: abuse, translation, validity, child maltreatment, Urdu

Oocyte quality following in vitro follicle development

In vitro follicle development (IVFD) is an adequate model to obtain basic knowledge of folliculogenesis and provides a tool for ovarian toxicity screening. IVFD yielding competent oocytes may also offer an option for fertility and species preservation. To promote follicle growth and oocyte maturation in vitro, various culture systems are utilized for IVFD in rodents, domestic animals, wild animals, nonhuman primates, and humans. Follicle culture conditions have been improved by optimizing gonadotropin levels, regulatory factors, nutrient supplements, oxygen concentration, and culture matrices. This review summarizes quality assessment of oocytes generated from in vitro-developed antral follicles from the preantral stage, including oocyte epigenetic and genetic profile, cytoplasmic and nuclear maturation, preimplantation embryonic development following in vitro fertilization, as well as pregnancy and live offspring after embryo transfer. The limitations of oocyte quality evaluation following IVFD and the gaps in our knowledge of IVFD to support proper oocyte development are also discussed. The information may advance our understanding of the requirements for IVFD, with a goal of producing competent oocytes with genetic integrity to sustain embryonic development resulting in healthy offspring.

Methotrexate in the therapeutic pathway of patients with psoriasis. Analysis of clinical practice data and comparison with guidelines

Introduction Psoriasis is an inflammatory skin disease with a chronic-relapsing course. It is estimated that the prevalence in Italy is 3%. An adequate model of taking care of the patient with psoriasis allows the patient to benefit from the most suitable treatment option for his health needs. In this position statement the observations, criticalities and proposals for improvement of the Pso-Path Working Group, composed by health economists, clinicians and patients, on the diagnostic-therapeutic pathway of the patient with psoriasis have been collected. In particular, the deviation of clinical practice from the current Guidelines for the management of patients with psoriasis, which recommend the use of biologic drugs in case of non-response, intolerance or contraindication to Methotrexate or Cyclosporine, was evaluated. Method A Working Group was convened whose participants were asked to express their thoughts on the diagnostic and therapeutic pathway of the patient with psoriasis, bringing out critical elements and proposals for improvement, based on their experiences. Conclusion This position statement summarizes the experiences and consensus between clinicians and patients on actions to optimize the management of patients with psoriasis undergoing biological treatment. Compared to the epidemiological data currently available, it is believed that only a small percentage of patients with psoriasis are treated with systemic drugs. The perception of clinicians, according to their experience, confirms the data emerging from the National Report "National Observatory on the Use of Medicines" (Osmed) compiled by AIFA in 2015, according to which more than 77% of patients with psoriasis are started to treatment with biological drugs without a previous use of Methotrexate or Cyclosporine for at least 3 months. The Pso-Path Working Group came to the conclusion that it would be desirable to incentivize, through the formalization of regional guidelines, the creation of a network system that promotes not only a greater awareness, at the territorial level, of the importance and impact of the disease and the possible paths, but also the collaboration and connection between all the actors involved in the overall care of the patient.

Bell v Tavistock: Rethinking informed decision-making as the practical device of consent for medical treatment

The decision of the High Court in Bell v Tavistock has excited considerable discussion about lawful consent for puberty-blocking drug treatment for children with gender dysphoria. The present paper draws attention to a wider question that surfaces through this case: is informed decision-making an adequate practical tool for seeking and obtaining patients’ consent for medical treatment? Informed decision-making engages the premises of the rational choice theory: that people will have well-crystallised health goals; and, if they are provided with sufficient information about medical treatments, then they will be able to choose the treatment that satisfies their goals. Whilst appealing, the informed decision-making paradigm is assailed by various fallacies, which apply not only to children but also to adults. In Bell v Tavistock, the High Court seems to have recognised such fallacies, and it rejected informed decision-making as an adequate tool for consent from children with gender dysphoria. Similar considerations apply to adults in various situations. Thus, Bell v Tavistock can be seen as an attempt to refine the views on the consent that were expressed by the Supreme Court in Montgomery. It can be inferred that the Supreme Court did recognise the limitations of informed decision-making, but it did not develop this point. Further work is required to formulate an adequate model of decision-making, and Bell v Tavistock serves as a useful reminder to rethink informed decision-making as the device for consent.

A Robust Method for Detecting Item Misfit in Large Scale Assessments

Viable methods for the identification of item misfit or Differential Item Functioning (DIF) are central to scale construction and sound measurement. Many approaches rely on the derivation of a limiting distribution under the assumption that a certain model fits the data perfectly. Typical assumptions such as the monotonicity and population independence of item functions are present even in classical test theory but are more explicitly stated when using item response theory or other latent variable models for the assessment of item fit. The work presented here provides an alternative approach that does not assume perfect model data fit, but rather uses Tukey’s concept of contaminated distributions and proposes an application of robust outlier detection in order to flag items for which adequate model data fit cannot be established.

A Robust Method for Detecting Item Misfit in Large Scale Assessments

Viable methods for the identification of item misfit or Differential Item Functioning (DIF) are central to scale construction and sound measurement. Many approaches rely on the derivation of a limiting distribution under the assumption that a certain model fits the data perfectly. Typical assumptions such as the monotonicity and population independence of item functions are present even in classical test theory but are more explicitly stated when using item response theory or other latent variable models for the assessment of item fit. The work presented here provides an alternative approach that does not assume perfect model data fit, but rather uses Tukey’s concept of contaminated distributions and proposes an application of robust outlier detection in order to flag items for which adequate model data fit cannot be established.

Modeling in the Process of Verifying a Suspects and a Defendants Alibis

The author examines the use of modeling in the verification of a suspect’s and a defendant’s alibis. In the conditions of digitization, there are wide prospects for the use of such a method. Alibi verification can be viewed as a special case of the criminalistic reconstruction of the event of the crime, and the modeling method is morphologically included in the process of reconstructing the investigated event or its part. Flowcharts are designed with the use of the working systems of alibi verification proposed by the author, they reflect forensically relevant features of the investigated object that should be selected from the flow of information as information blocks and properly organized. Information blocks are interconnected and correlate with each other. The more content each block contains, the more accurate the result produced by the constructed model will be. The author concludes that modeling should result in building an adequate model of an episode of the criminal event under investigation that will reflect data on the “history” of the alibi and will make it possible to predict its variants.

Data-Driven Models for Gas Turbine Online Diagnosis

The lack of gas turbine field data, especially faulty engine data, and the complexity of fault embedding into gas turbines on test benches cause difficulties in representing healthy and faulty engines in diagnostic algorithms. Instead, different gas turbine models are often used. The available models fall into two main categories: physics-based and data-driven. Given the models’ importance and necessity, a variety of simulation tools were developed with different levels of complexity, fidelity, accuracy, and computer performance requirements. Physics-based models constitute a diagnostic approach known as Gas Path Analysis (GPA). To compute fault parameters within GPA, this paper proposes to employ a nonlinear data-driven model and the theory of inverse problems. This will drastically simplify gas turbine diagnosis. To choose the best approximation technique of such a novel model, the paper employs polynomials and neural networks. The necessary data were generated in the GasTurb software for turboshaft and turbofan engines. These input data for creating a nonlinear data-driven model of fault parameters cover a total range of operating conditions and of possible performance losses of engine components. Multiple configurations of a multilayer perceptron network and polynomials are evaluated to find the best data-driven model configurations. The best perceptron-based and polynomial models are then compared. The accuracy achieved by the most adequate model variation confirms the viability of simple and accurate models for estimating gas turbine health conditions.