Panel Input Research Articles

Classification Criteria for Axial Disease in Youth with Juvenile Spondyloarthritis.

To develop and validate classification criteria for axial disease in youth with juvenile spondyloarthritis (SpA; AxJSpA). This international initiative consisted of four phases: 1) Item generation; 2) Item reduction; 3) Criteria development; and 4) Validation of the AxJSpA criteria by an independent team of experts in an internationally representative Validation cohort. These criteria are intended to be used on youth with a physician diagnosis of juvenile SpA and for whom axial disease is suspected. Item generation consisted of a systematic literature review and a free-listing exercise using input from international physicians and collectively resulted in 108 items. After the item reduction exercise and expert panel input, 37 items remained for further consideration. The final AxJSpA criteria domains included: imaging: active inflammation, imaging: structural lesions, pain chronicity, pain pattern, pain location, stiffness, and genetics. The most heavily weighted domains were active inflammation and structural lesions on imaging. Imaging typical of sacroiliitis was deemed necessary, but not sufficient, to classify a youth with AxJSpA. The threshold for classification of AxJSpA was a score of ≥55 (out of 100). When tested in the validation data set, the final criteria had a specificity of 97.5% (95% CI: 91.4-99.7), sensitivity of 64.3% (95% CI: 54.9-73.1) and Area Under the Receiver Operating Characteristic (AUROC) curve of 0.81 (95% CI: 0.76-0.86). The new AxJSpA classification criteria require an entry criterion, physician diagnosis of juvenile SpA, and include seven weighted domains. The AxJSpA classification criteria are validated and designed to identify participants for research studies.

Solar powered high gain DC-DC converter with FPGA controller for portable devices

A solar-powered converter design is necessary for portable devices with increased gain and reduced ripple in overall operation. This research presents a photovoltaic-powered Field Programmable Gate Array (FPGA) based on increased gain multiple output converter design and analysis. The dynamic panel input makes it difficult to operate the load. To control and make the input static to satisfy the demand, perturb and observe with a load balancing algorithm technique are used. The converter gained output is high, and batteries are used to balance the loads when solar irradiance is low. Simulation results were carried out with the presented converter circuit that can be operated with a 12 V supply as input from a renewable power source. The output gain ratio of 14 to a minimum of 40 % duty cycle operating at a switching frequency of 20 kHz has been achieved. The proposed methodology is transferred to hardware by connecting with the reconfigurable FPGA Spartan-6 development board to manage the dynamic load control system's complex logic and high processing ability. The overall performance is compared with various pre-existing systems, tabulations are made with the analysis, and experimental results are also illustrated at the end.

Adapting and testing measures of organizational context in primary care clinics in KwaZulu-Natal, South Africa

BackgroundImplementation science frameworks situate intervention implementation and sustainment within the context of the implementing organization and system. Aspects of organizational context such as leadership have been defined and measured largely within US health care settings characterized by decentralization and individual autonomy. The relevance of these constructs in other settings may be limited by differences like collectivist orientation, resource constraints, and hierarchical power structures. We aimed to adapt measures of organizational context in South African primary care clinics.MethodsWe convened a panel of South African experts in social science and HIV care delivery and presented implementation domains informed by existing frameworks and prior work in South Africa. Based on panel input, we selected contextual domains and adapted candidate items. We conducted cognitive interviews with 25 providers in KwaZulu-Natal Province to refine measures. We then conducted a cross-sectional survey of 16 clinics with 5–20 providers per clinic (N = 186). We assessed reliability using Cronbach’s alpha and calculated interrater agreement (awg) and intraclass correlation coefficient (ICC) at the clinic level. Within clinics with moderate agreement, we calculated correlation of clinic-level measures with each other and with hypothesized predictors – staff continuity and infrastructure – and a clinical outcome, patient retention on antiretroviral therapy.ResultsPanelists emphasized contextual factors; we therefore focused on elements of clinic leadership, stress, cohesion, and collective problem solving (critical consciousness). Cognitive interviews confirmed salience of the domains and improved item clarity. After excluding items related to leaders’ coordination abilities due to missingness and low agreement, all other scales demonstrated individual-level reliability and at least moderate interrater agreement in most facilities. ICC was low for most leadership measures and moderate for others. Measures tended to correlate within facility, and higher stress was significantly correlated with lower staff continuity. Organizational context was generally more positively rated in facilities that showed consistent agreement.ConclusionsAs theorized, organizational context is important in understanding program implementation within the South African health system. Most adapted measures show good reliability at individual and clinic levels. Additional revision of existing frameworks to suit this context and further testing in high and low performing clinics is warranted.

Solar Panel Cleaning System with Voltage Drop Detection

bstract: This research suggests a unique voltage drop sensor and LDR (light-dependent resistor) based solar panel dust removal detecting system. Whereas the voltage drop sensor gauges the voltage differential between the solar panel's input and output, the LDR sensor counts the amount of light reflected from the panel's surface. The system is able to precisely identify the existence of dust and assess its level of intensity by evaluating the aggregated data from these sensors. Afterwards, an automatic dust removal device, like a water spray system or robotic brush, can be started using this information. The suggested method improves the overall performance and lifespan of solar photovoltaic systems by providing an automated, economical, and efficient alternative for the removal of dust from solar panel

A systematic approach to analyzing the enablers of post-pandemic supply chain resilience in an emerging economy: a fuzzy AHP approach

PurposeThis study aims to identify the enablers of supply chain resilience (SCR) through a literature review and expert panel input in the context of Pakistan and the post-pandemic era. This study also aims to categorize and rank the identified enablers using expert panel input.Design/methodology/approachA review of the extant literature was conducted to investigate and identify the factors that contribute to SCR. The relative ranking of the enablers was carried out by a group of industry and academic experts. The expert panel was convened to compare the main categories and each enabler in pairs and to score the enablers using triangular fuzzy numbers.FindingsThis study identified 16 critical SCR enablers. Using the fuzzy analytic hierarchy process (AHP), these enablers were divided into three groups and analyzed. The results show that financial enablers, technology enablers and then social enablers are prioritized when it comes to SCR in emerging markets. The robustness of the ranking of enablers is tested through sensitivity analysis.Practical implicationsThe results shall be helpful for policymakers and managers to understand the important enablers and also help allocate resources to important enablers. Managers will be able to formulate strategies to achieve SCR in an uncertain environment.Originality/valueThis is one of the first attempts to identify and rank the enablers of SCR in an emerging economy context.

A Mixed-Methods Approach to the Development of a Disaster Food Security Framework

BackgroundLimited research on food systems and food insecurity (FI) following disasters finds contextual differences in post-disaster food systems that shape dimensions of FI. Measurement limitations make it difficult to address FI and develop effective practices for disaster-affected communities. ObjectiveTo develop, validate, and test a Disaster Food Security Framework (DFSF). DesignMixed-methods approach was used, including in-depth interviews to understand lived experiences during disasters; expert panel input to validate DFSF designed using responses from in-depth interviews; and quantitative testing of robustness of DFSF using the coronavirus disease 2019 pandemic as a disaster example. Participants and settingThe in-depth interviews included participants from Vermont (n = 5), North Carolina (n = 3), and Oklahoma (n = 2) who had been living in those states during Hurricane Irene (2011), Hurricane Florence (2018), the Moore tornadoes (2013), and coronavirus disease 2019 pandemic (2020). The expert panel consisted of researchers and practitioners from different US geographical regions and food-related disciplines (n = 18). For the quantitative testing survey, data from 4 US states (New York, New Mexico, Vermont, and Maryland; n = 3,228) from the National Food Access and COVID Research Team was used. Main outcome measuresThe outcomes from the in-depth interviews were dimensions of disaster FI, those from the expert panel was a content validity ratio, and those from the quantitative testing was the number of items and components to be included. Analyses performedInductive and deductive reasoning were using when reporting on the in-depth interviews and expert panel results, including frequencies. The quantitative testing was conducted using multiple correspondence analysis. ResultsThe in-depth interviews revealed four dimensions of FI: availability (supply and donation), accessibility (economic, physical, and social), acceptability (preference and health), and agency (infrastructure and self-efficacy). The panel of experts reported high content validity for the DFSF and its dimensions (content validity ratio >0.42), thus giving higher credibility to the DFSF. Multiple correspondence analysis performed on 25 food-related variables identified one component with 13 indicators representing three of the four dimensions: availability, acceptability, and accessibility, but not agency.

783 Consensus Criteria for Palliative Care Consults: A Modified Delphi Approach

Abstract Introduction Specialist palliative care (PC) is a limited resource, best conserved by identifying persons most likely to benefit from a PC consult. Little guidance is available for clinicians on whether/ when to consult PC. The authors previously developed empirically-derived consult criteria to guide burn providers in specialist PC consultation, refining them by expert panel input. Methods A modified three-iteration Delphi process was employed to revise and develop consensus on empirically-derived PC consult criteria in burn patients. Eligible participants (N=202) were identified by (a) having published on burn and PC (b) presented nationally on burn and PC or (c) nomination by the study team as having equivalent expertise in the field. Results Forty-three individuals participated in Iteration 1; n=34 (79%) in Iteration 3, which rank-ordered three versions of criteria and invited further revisions. Consensus eliminated the most parsimonious version. Expert review panelists integrated feedback, yielding a consensus list with 6 criteria for PC consultation and 6 criteria for consideration of PC consult. Consult criteria include patient/family request; conflicted or unclear goals of care; and high modified Baux/SCORTEN scores. Criteria for consideration include no longer meeting milestones; assistance with symptom management; or cardiac arrest. Conclusions Consensus among burn and PC providers enhances validity and supports clinical use to guide burn providers on patients most likely to benefit from specialist PC consultation. Future research should prospectively explore whether adherence to the criteria is associated with improved outcomes and potential further revision. Applicability of Research to Practice Provides guidance on PC consultation and may be used to examine outcomes.

A novel scoring system concept for de novo spinal infection treatment, the Spinal Infection Treatment Evaluation Score (SITE Score): a proof-of-concept study.

De novo infections of the spine are an increasing healthcare problem. The decision for nonsurgical or surgical treatment is often made case by case on the basis of physician experience, specialty, or practice affiliation rather than evidence-based medicine. To create a more systematic foundation for surgical assessments of de novo spinal infections, the authors applied a formal validation process toward developing a spinal infection scoring system using principles gained from other spine severity scoring systems like the Spine Instability Neoplastic Score, Thoracolumbar Injury Classification and Severity Score, and AO Spine classification of thoracolumbar injuries. They utilized an expert panel and literature reviews to develop a severity scale called the "Spinal Infection Treatment Evaluation Score" (SITE Score). The authors conducted an evidence-based process of combining literature reviews, extracting key elements from previous scoring systems, and obtaining iterative expert panel input while following a formal Delphi process. The resulting basic SITE scoring system was tested on selected de novo spinal infection cases and serially refined by an international multidisciplinary expert panel. Intra- and interobserver reliabilities were calculated using the intraclass correlation coefficient (ICC) and Fleiss' and Cohen's kappa, respectively. A receiver operating characteristic analysis was performed for cutoff value analysis. The predictive validity was assessed through cross-tabulation analysis. The conceptual SITE scoring system combines the key variables of neurological symptoms, infection location, radiological variables for instability and impingement of neural elements, pain, and patient comorbidities. Ten patients formed the first cohort of de novo spinal infections, which was used to validate the conceptual scoring system. A second cohort of 30 patients with de novo spinal infections, including the 10 patients from the first cohort, was utilized to validate the SITE Score. Mean scores of 6.73 ± 1.5 and 6.90 ± 3.61 were found in the first and second cohorts, respectively. The ICCs for the total score were 0.989 (95% CI 0.975-0.997, p < 0.01) in the first round of scoring system validation, 0.992 (95% CI 0.981-0.998, p < 0.01) in the second round, and 0.961 (95% CI 0.929-0.980, p < 0.01) in the third round. The mean intraobserver reliability was 0.851 ± 0.089 in the third validation round. The SITE Score yielded a sensitivity of 97.77% ± 3.87% and a specificity of 95.53% ± 3.87% in the last validation round for the panel treatment decision. The SITE scoring concept showed statistically meaningful reliability parameters. Hopefully, this effort will provide a foundation for a future evidence-based decision aid for treating de novo spinal infections. The SITE Score showed promising inter- and intraobserver reliability. It could serve as a helpful tool to guide physicians' therapeutic decisions in managing de novo spinal infections and help in comparison studies to better understand disease severity and outcomes.

Analyzing the barriers to sustainable procurement in an emerging economy: an interpretive structural modeling approach

PurposeThis paper aims to identify, using a literature review and expert panel input, what impedes organizations from implementing sustainable procurement, particularly in an emerging economy context.Design/methodology/approachThe extant literature review was carried out to explore and identify the barriers to sustainable procurement. Using interpretive structural modeling (ISM), the authors established a contextual relationship among the 22 identified barriers. These barriers are then classified into different categories, using the matrice d’impacts cross-multiplication appliqúe an classment (MICMAC) technique, based on their driving and dependence power.FindingsThe findings improve our understanding of the critical barriers and their direct and indirect effect on each other in obstructing sustainable procurement practices. The study is the first of its kind in identifying the barriers to sustainable procurement and developing a hierarchical relationship among barriers using an integrated ISM–MICMAC methodology based on data from an emerging economy (Pakistan). With a focus on sustainable practices, this study also responds to the United Nations Sustainable Development Goals.Practical implicationsThe results of the hierarchical model help understand which barriers are the most crucial to be fixed immediately (i.e. absence of environmental laws and lack of consumer pressure) and how different barriers could influence each other, specifically in emerging economies. The practitioners can use the findings to make more informed decisions to mitigate the crucial barriers that could impede their goals of sustainable procurement.Originality/valueThe study is the first of its kind to identify the barriers to sustainable procurement and develop a contextual relation and hierarchical framework in the Pakistani context.

Hepatitis C prevalence and elimination planning in Pakistan, a bottom-up approach accounting for provincial variation.

In Pakistan, substantial changes to hepatitis C virus (HCV) programming and treatment have occurred since the 2008 nationwide serosurvey estimated a 4.8% anti-HCV prevalence. In the absence of an updated national study, this analysis uses provincial data to estimate a national prevalence and the interventions needed to achieve elimination. Using a Delphi process, epidemiologic HCV data for the four provinces of Pakistan (accounting for 97% of the population) were reviewed with 21 subject-matter experts in Pakistan. Province-level estimates were inputted into a mathematical model to estimate the national HCV disease burden in the absence of intervention (Base), and if the World Health Organization (WHO) elimination targets are achieved by 2030 (80% reduction in new infections, 90% diagnosis coverage, 80% treatment coverage, and 65% reduction in mortality: WHO Elimination). An estimated 9,746,000 (7,573,000-10,006,000) Pakistanis were living with viraemic HCV as of January 1, 2021; a viraemic prevalence of 4.3% (3.3-4.4). WHO Elimination would require an annual average of 18.8million screens, 1.1million treatments, and 46,700 new infections prevented anually between 2022 and 2030. Elimination would reduce total infections by 7,045,000, save 152,000 lives and prevent 104,000 incident cases of hepatocellular carcinoma from 2015 to 2030. Blood surveys, programmatic data, and expert panel input uncovered more HCV infections and lower treatment numbers in the provinces than estimated using national extrapolations, demonstrating the benefits of a bottom-up approach. Screening and treatment must increase 20 times and 5 times, respectively, to curb the HCV epidemic in Pakistan and achieve elimination by 2030.

Development and Initial Psychometric Validation of the COVID-19 Pandemic Burden Index for Healthcare Workers.

The burden of COVID-19 on healthcare workers (HCWs) is reported to be increasing, yet the psychometric scales now in use evaluate only single aspects; few measure the pandemic-specific burden on HCWs comprehensively. To develop a scale to quantify the physical, mental, and socioeconomic burden of the COVID-19 pandemic on HCWs. Scale development and cross-sectional survey. Consenting HCWs aged ≥20. Development of an item-list based on literature reviews and HCW panel input, evaluation of content validity and item selection using the Delphi method, psychometric testing conducted on HCWs, validity assessment by factor analyses and hypothesis verification, internal consistency evaluation by Cronbach's alpha, test-retest analysis, and interpretability assessment. Through the Delphi process, a 29-item pilot scale was generated. In psychometric testing, data from 863 HCWs contributed to the development of the final version of this scale, called Pandemic Burden Index twenty for HCWs (PBI-20), a 20-item scale to measure six domains: fatigue, fear of infection, inadequacy as a medical professional, mental health concerns, prejudice or discrimination, and anxiety about one's livelihood and daily life. Factor analysis showed each factor corresponded to the six domains of this scale. Hypothesis verification showed the PBI-20 total score to be moderately to highly correlated with the Short Form 36 vitality score and mental health score and with intention of turnover. The PBI-20 had good internal consistency (Cronbach's alpha 0.92). Test-retest analysis showed the intraclass correlation coefficient to be 0.70 and the minimal important change to be -7.0. The psychometrically sound questionnaire we developed to measure pandemic-specific burdens for HCWs provides an understanding of comprehensive burdens on HCWs and may serve to evaluate interventions to reduce the burdens.

The Future of INCOG (Is Now).

The Future of INCOG (Is Now).

Identification and evaluation of the contextual relationship among barriers to the circular supply chain in the Pakistani context – an interpretive structural modelling approach

This paper aims to identify the potential barriers to the implementation of circular supply chain management (CSCM) in developing countries by considering a case of the Pakistani fast-moving consumer goods (FMCG) sector. By using literature review and expert panel input, this study found fourteen barriers to the implementation of the circular supply chain (CSC) and established the contextual relationship among the identified and validated barriers using interpretive structural modelling (ISM). The barriers were then classified into different categories using the MICMAC technique based on their driving and dependence power. The results helped to explore the direct and indirect effect of barriers on each other. The study also developed a hierarchical relationship among the barriers using an integrated ISM-MICMAC methodology in an emerging economy context. The results of the hierarchical model shall help to understand the impact of one particular barrier over others. Managers and organizations can use this study to inhibit the effects of barriers for successful implementation of the CSC.

Development and validation of the Adult cirrhosiS Knowledge Questionnaire.

Assessing a patient's knowledge regarding liver cirrhosis is important to improve patient outcomes. This study aimed to develop and validate the Adult cirrhosiS Knowledge Questionnaire (ASK-Q) to assess patients' knowledge regarding liver cirrhosis from multiple aspects. A 24-item ASK-Q with four domains: self-understanding (5 items), aetiology (5 items), complications (5 items) and management (9 items) of liver cirrhosis was developed based on literature review and expert panel input. It was then piloted in five English-speaking patients with liver cirrhosis. These patients commented that the font size was too small. Hence, the font was enlarged and the final version of the ASK-Q was administered to English-speaking patients with liver cirrhosis, aged ≥18 years, with or without decompensation, at a tertiary hospital, from September 2020 to November 2021, at baseline and fortnight later. Patients with encephalopathy were excluded. 120/135 patients agreed to participate (response rate = 88.9%). The overall median score was 59.1 (45.6-68.2). A total of 7/22 (31.8%) items were "easy", 14/22 (63.6%) items were "moderately easy" and 1/22 (4.5%) items were "difficult". Exploratory factor analysis extracted nine factors, and two items were omitted. The ASK-Q was able to discriminate the knowledge level of patients with and without tertiary education [59.1 (50.0-72.7) vs. 54.5 (36.4-63.6); P < 0.05]. The overall Kuder-Richardson coefficient was 0.760, indicating adequate internal consistency. At retest, 77/120 patients participated (response rate = 64.2%) and 15/22 items were not statistically significant, indicating adequate reliability. The ASK-Q was found to be a valid and reliable questionnaire for evaluating the knowledge of liver cirrhosis among English-speaking adult patients.

Palliative Care and Burn Care: Empirically Derived Referral Criteria.

Burns frequently require complex interdisciplinary care. Specialist palliative care (PC) minimizes suffering, aids in decision making, and provides family support in addition to end-of-life care. Specialist PC is a limited resource, best conserved by identifying persons most likely to benefit from a PC referral. Little guidance is available for clinicians on whether and when to refer to PC. This study's purpose was to identify referral criteria using a mixed-methods approach. Data were examined for between-group differences using Fisher's exact, chi-square, or Wilcoxon Rank Sum tests. Qualitative thematic analysis was used to analyze PC provider notes to describe interventions provided. These data formed initial referral criteria, which were reviewed by an expert panel. Significant between-group differences included dying in the burn center; whether multiple patients were transported to the burn center from one event; and ventilator days. Four themes emerged from qualitative analysis. These included managing physical aspects of care; clarifying goals of care; managing end-of-life care; and managing patient/family psychosocial distress. Expert panel input clarified referral criteria language and supplemented the proposed criteria. We present empirically derived referral criteria to guide burn providers in referring persons for specialist PC. Subsequent testing is required to determine their efficacy in improving patient/family outcomes.

0352 Compliance to Sleep Recommendations: A Big Data Analysis In Users of a Consumer Sleep Technology

Abstract Introduction The National Sleep Foundation has published sleep time duration (Hirshkowitz et al., 2015) and sleep quality (Ohayon et al., 2017) recommendations across the lifespan based on expert panel input. These recommendations offer sleep guidance to millions of individuals. Many individuals are using commercially available sleep tracking devices to measure their sleep. We analyzed the data of two non-contact radiofrequency sleep measurement devices (SleepScore Max (SleepScore Labs) and S+ (ResMed), both validated against PSG) to determine how well the users of these devices are sleeping. Methods Total Sleep Time (TST), sleep latency (SL) and sleep efficiency (SE) data of 40,892 users between 15 and 98 years old were used in this analysis, covering 5,513,369 nights of data, and averages per user were calculated. In alignment with the aforementioned papers, the data were split in 3 age groups; Young Adults (18-25), Adults (26-64) and Older Adults (&amp;gt;=65), and the criteria as listed were used, classifying the sleep indicators in 3 bins; Appropriate/Recommended, Uncertain/ May be Recommended, and Inappropriate/Not Recommended. Proportion of users meeting the Appropriate/Recommended, Uncertain/May be Appropriate and Inappropriate/Unlikely were calculated for each age group. Results In the Young Adults group most users had an Appropriate SL (SL&amp;lt;= 30 min; 79.7 %), an Appropriate SE (SE&amp;gt;=85%; 53.6 %), but only 30.0% had a Recommended TST (7 to 9 h.). In the Adult group, larger proportions of users met on average the Appropriate measures for SL (SL&amp;lt;= 30 min; 84.8%), SE (SE&amp;gt;= 85%; 58.4%), but only 27.3% slept on average the Recommended hours (TST 7 to 9 h). In the Older Adults group, the average SL and SE was considered Appropriate for most elderly users (SL&amp;lt;30min; 84.3: SE&amp;gt;=85%; 59.6%), but only 28.2% slept the Recommended amount (TST 7 to 8 h). Conclusion 30% or less users slept on average the recommended amount, whereas slightly over half of the users showed the recommended sleep efficiency, and at least 79.7% fell on average asleep within 30 minutes. These results show that sleep improvement campaigns need to focus on extending the sleep duration and sleep hygiene to improve SE. Support (If Any)

Artificial Neural Network based MPPT Algorithm with Boost Converter topology for Stand-Alone PV System

The increasing energy need in parallel with the technology development and the depletion of the resources have increased the importance of alternative energy resources. Solar energy systems are frequently preferred due to their advantages such as not having moving parts, being reliable and working without noise. Production of electricity from solar energy is obtained by serial or parallel connection of photovoltaic (PV) panels, depending on the desired voltage and current values. DC-DC converters are used to convert the energy obtained from the PV panels to the desired grid values. Maximum power point tracking (MPPT) algorithms are used in order to obtain the highest possible efficiency from the PV panels. MPPT algorithms control the duty period (D) ratio of DC-DC converters and obtain maximum energy. In this study, an Artificial Neural Network (ANN) based MPPT algorithm is proposed. Firstly, the temperature and irradiance data at the PV panel input are trained using the Levenberg-Marquardt algorithm. As a result, a reference voltage is generated and MPPT is realized by comparing it with the voltage produced by the PV panel. In order to evaluate the performance of the proposed algorithm, it is compared with the traditional MPPT methods such as Perturb &amp; Observe (P&amp;O) and Incremental Conductance (INC). As a result of the simulation studies, it has been observed that ANN based MPPT is more successful than P&amp;O and INC algorithms for several irradiance and temperature conditions.

Toward an ontology of collaborative learning healthcare systems.

ObjectiveTo establish a basis for a domain ontology ‐ a formal, explicit specification of a shared conceptualization ‐ of collaborative learning healthcare systems (CLHSs) in order to facilitate measurement, explanation, and improvement.MethodsWe adapted the “Methontology” approach to begin building an ontology of CLHSs. We specified the purpose of an ontology, acquired domain knowledge via literature review, conceptualized a common framework of CLHSs using a grounded approach, refined these concepts based on expert panel input, and illustrated concept application via four cases.ResultsThe set of concepts identified as important to include in an ontology includes goals, values, structure, actors, environment, and products. To establish this set of concepts, we gathered input from content experts in two ways. First, expert panel methods were used to elicit feedback on these concepts and to test the elicitation of terms for the vocabulary of the Values concept. Second, from these discussions we developed a mapping exercise to test the intuitiveness of the concepts, requesting that network leaders from four CLHSs complete a mapping exercise to associate characteristics of their networks with the high‐level concepts, building the vocabulary for each concept in a grounded fashion. We also solicited feedback from these participants on the experience of completing the mapping exercise, finding that the exercise is acceptable and could aid in CLHS development and collaboration. Respondents identified opportunities to improve the operational definitions of each concept to ensure that corresponding vocabularies are distinct and non‐overlapping.DiscussionOur results provide a foundation for developing a formal, explicit shared conceptualization of CLHSs. Once developed, such a tool can be useful for measurement, explanation, and improvement. Further work, including alignment to a top‐level ontology, expanding the vocabulary, and defining relations between vocabulary is required to formally build out an ontology for these uses.

Measuring fear of cancer recurrence in survivors of childhood cancer: Development and preliminary validation of the Fear of Cancer Recurrence Inventory (FCRI)-Child and Parent versions.

Fear of cancer recurrence (FCR) is a common and distressing psychosocial concern for adult cancer survivors. Data on this construct in child survivors is limited and there are no validated measures for this population. This study aimed to adapt the Fear of Cancer Recurrence Inventory-Short Form (FCRI-SF) for survivors of childhood cancer aged 8-18years (Fear of Cancer Recurrence Inventory-Child version [FCRI-C]) and their parents (Fear of Cancer Recurrence Inventory-Parent version [FCRI-P]) to self-report on their own FCR and to examine the initial psychometric properties. The FCRI-SF was adapted through expert panel input and cognitive interviews with child survivors <18years. The factor structure, internal consistency and construct and criterion validity of the FCRI-C and FCRI-P were examined in 124 survivors of childhood cancer (43% female; Mage =14.58years, SD=2.90) and 106 parents (90% mothers). All FCRI-SF items were retained for the FCRI-C with simplified language. The internal consistencies of the FCRI-C (α=0.88) and FCRI-P (α=0.83) were good. Exploratory factor analyses yielded one-factor structures for both measures. Higher scores on the FCRI-C and FCRI-P were associated with greater intolerance of uncertainty and pain catastrophizing. Higher child FCR was also related to more hypervigilance to bodily symptoms. Parents with higher FCR reported contacting their child's doctors and nurses and scheduling medical appointments for their child more frequently. Children reported significantly lower FCR compared to parents. The FCRI-C and FCRI-P demonstrated strong reliability and preliminary validity. This study offers preliminary data to support the use of the FCRI-C and FCRI-P to measure FCR in survivors of childhood cancer aged 8-18years and their parents.

Recognition of handwritten characters on the sensor matrix using a neural network

Nowadays, touch displays are becoming more common. This design combines an input device and an output device, and also allows you to create the most convenient interfaces for interacting with the user. Input recognition significantly expands the functionality of touch input, providing the ability to apply recognition of entered characters to launch a variety of functions and applications. Such systems existing today are not flexible enough in configuration and use. This paper presents the process of developing an infrared touch panel input data analysis system. A neural network is configured and trained to solve the problem of recognizing handwritten characters. The functional purpose of the program units has been briefly presented: graphical interface, COM-port reader, neural network. A graphical interface has been developed that visualizes the used touch matrix and displays function buttons, input and output fields. The interface consists of a main work window, a macro view and setup window, and an auto-identification timer setup window. A program block has been developed that allows you to create a neural network according to given settings, make a request to it and train it. Additional program functionality has been developed that allows you to run external files using the entered symbol, partially automating the program, helping the user. All developed modules have been functionally tested individually and the entire program together. Principles of neural networks training have been analyzed. Experiments have been carried out in which training of a neural network with different settings and training parameters is implemented. Among these parameters are: the number of epochs of learning, the speed of learning, the number of neurons of the hidden layer. As a result of the experiments performed, factors affecting the quality of neural network training have been identified. As a result of the training, a set of coefficients has been obtained that ensures stable operation of the neural network. The accuracy of the neural network is 96%, and the recognition speed is less than a second.