Holistic Evaluation Research Articles

Counting steps.

The use of step count as a metric of synthetic efficiency carries opportunities and challenges. Here, proposals are made to standardize what constitutes a synthetic step and how steps are counted. These proposals may be beneficial in the holistic evaluation of published synthetic routes.

A SUMMARY ON FITRADEOFF METHOD WITH METHODOLOGICAL AND PRACTICAL DEVELOPMENTS AND FUTURE PERSPECTIVES

This paper presents a broad overview of main contributions related to the FITradeoff (Flexible and Interactive Tradeoff) method. FITradeoff is a multicriteria method developed within the scope of the Multiattribute Value Theory (MAVT), considering partial information from the decision maker (DM) in the preference modelling process. Over the last few years, several methodological developments on this method have been published in the literature, as well as practical applications to a wide range of multicriteria decision problems. The most recent methodological advances are related to preference modelling process, which now integrate the two paradigms of elicitation by decomposition and holistic evaluation. Furthermore, contributions from behavioral studies, some of them including decision neuroscience, have enhanced the DSS free available for FITradeoff. In this paper, all previously developed works related to the FITradeoff method are approached, considering both methodological developments and practical applications. A summary on the different modeling approaches for solving different decision problematics (choice, ranking, sorting and portfolio) with FITradeoff is presented. The recently proposed combination of preference modeling paradigms - elicitation by decomposition and holistic evaluation - within the FITradeoff decision process is explained, as well its potential advantages for the elicitation process. Moreover, a brief review on the practical applications of the method in different contexts is presented. In addition, this work also brings a summary on the results of behavioral experiments conducted using neuroscience tools with the FITradeoff method, as well the methodological insights resulted from them, and future perspectives of potential research topics related to the FITradeoff method.

EXPLORING THE COMBINATION OF HOLISTIC EVALUATION AND ELICITATION BY DECOMPOSITION IN FITRADEOFF: PRIORITIZING CULTURAL TOURISM PRODUCTS IN POLAND

This paper presents the problem of the prioritization of cultural tourism products (CTP) in Czeladź, one of the post-industrial towns in southern Poland. For the decision analysis, the new flexibility features of the FITradeoff multiple criteria method will be explored. In particular, this paper focuses on the combination of two preference modeling paradigms in the decision process: elicitation by decomposition, in the consequences space; and holistic evaluation, in the alternatives space. The FITradeoff method is a multiple criteria decision method for preferences elicitation in additive aggregation models, that works based on partial information about the decision maker’s preferences. The new decision process with the FITradeoff Decision Support System (DSS) will be explored and discussed in detail. The advantages of combination of two types of preference modeling are highlighted, with the possibility of shortening the decision problem with holistic judgments made based on graphical visualizations, saving time and effort from decision makers.

Objective and subjective evaluation of a passive low-back exoskeleton during simulated logistics tasks.

Musculoskeletal disorders remain the most common work-related health problem in the European Union. The most common work-related musculoskeletal disorder reported by workers is backache, especially in the logistics sector. Thus, this article aims to evaluate the effects of a commercial passive low-back exoskeleton during simulated logistics tasks. Thirty participants were recruited for this study. Typical logistics tasks were simulated in a laboratory environment. Cross-over research design was utilized to assess the effects of the exoskeleton on heart rate, trunk inclination, trunk acceleration, throughput, and perceived exertion. Also, usability and acceptance were obtained using a custom questionnaire. We found mostly non-significant differences. Effects on throughput varied widely between workplaces. Usability ratings were poor and acceptance moderate. The study suggests that a holistic evaluation and implementation approach for industrial exoskeletons is necessary. Further, prior to exoskeleton implementation, workplace adaptation might be required.

Evaluating collaborative rationality-based decisions: a literature review

Decision making has evolved throughout the years, nowadays harnessing massive amounts and types of data through the unprecedented capabilities of data science, analytics, machine learning, and artificial intelligence. This has potentially led to higher quality and more informed decisions based on the collaborative rationality between humans and machines, no longer bounded by the cognitive capacity and limited rationality of each on their own. However, the multiplicity of modes of collaboration and interaction between humans and machines has also increased the complexity of decision making, consequentially complicating ex-ante and ex-post decision evaluation. Nevertheless, evaluation remains crucial to enable human and machine learning, rationalization, and sensemaking. This paper addresses the need for more research on why and how to evaluate collaborative rationality-based decisions, setting the stage for future studies in developing holistic evaluation solutions. By analyzing four relevant streams of literature: 1) classical decision theory and organizational management, 2) cognitive and neuroscience, 3) AI and ML, and 4) data-driven decision making, we highlight the limitations of current literature in considering a holistic evaluation perspective. Finally, we elaborate the theoretical underpinnings from the knowledge base on how humans and machines evaluate decisions, and the considerations for evaluating collaborative rationality-based decisions.

A Multi-level Fusion System for Intelligent Capture and Assessment of Student Activity in Physical Training based on Machine Learning

To record and evaluate students' physical education class participation, this study proposes using a Machine Learning aided Physical Training Framework (ML-PTF). Improve student achievement in physical education with the help of the Multi-level Fusion System that employs machine learning strategies. The system integrates sensor data, video data, and contextual data to deliver a holistic and precise evaluation of student engagement. This study's simulation analysis shows that the ML-PTF improves the reliability of evaluating universities' physical education programs. A important reference path and paradigm for advancing tertiary-level physical education for graduates, the multi-level fusion system also provides an investigation of information technology and language education integration. The experimental findings demonstrate that the ML-PTF is superior to other approaches in terms of learning rate, f1-score, precision, and probability, as well as student engagement, involvement, and recognition accuracy.

Evaluating the Global Strategy and Plan of Action on Public Health, Innovation, and Intellectual Property

Acknowledging the dearth in the research arena and deficiencies in the technology sector to promote public health standards, the World Health Assembly and the other member states adopted a global strategy and plan of action on public health, innovation, and intellectual property in 2008. Since the adoption of the policy, some progress has been observed in minimizing the caseload resulting because of diseases that predominantly affect disadvantaged or vulnerable sections of the community. Realizing the prevailing gap on different fronts of the global strategy, the World Health Organization has authorized an external agency to perform a holistic and exhaustive evaluation of the implementation of different aspects. To conclude, the health sector has many shortcomings in the area of improving the health indicators of the masses, and it becomes even more important in cases of developing nations. Owing to the presence of numerous public health challenges in the region, it is extremely important to prioritize the issues and deal with them in a systematic manner to improve the quality of life of the general population.

Commentary on “Early Developmental Trends in High-Risk Neonates Later Diagnosed With Autism Spectrum Disorder”

“How could I apply this information?” The number of children in the United States diagnosed with autism spectrum disorder (ASD) increased in the past 20 years from 1 in 150 in 2000 to 1 in 44 children in 2021.1 Although the disorder can be reliably diagnosed as early as 2 years or age, most children are not diagnosed until 4 years or age. This creates a substantial gap for children and families who need support. Motor skills offer an important opportunity for early interventionists, and specifically physical therapists, to screen for ASD if an association between early motor performance and later diagnosis can be established. Using the Test of Infant Motor Performance (TIMP), a well-validated early motor assessment, with a population of infants known to be at elevated risk2 may be a logical first step toward early detection. Yet, this study clearly establishes that testing of early motor performance does not detect differences in children who are later diagnosed with ASD. Specific items might have predictive value, rather than total scores. These findings support the importance of holistic developmental evaluation and the importance of advanced transdisciplinary training for providers who serve young, at-risk infants to understand how these domains interact and change across early development and in relationship to ASD. “What should I be mindful of when applying this information?” Medical management of prematurity is constantly advancing. Differences in medical care may create different risks and developmental outcomes. Longitudinal follow-up, across all developmental domains, is critical to understand these changing risks and outcomes. The authors discuss that standardized tests may not detect subtle indicators of ASD. Eye gaze and shifting, self-regulation, social interactions, and play skills should be considered. Physical therapists should continue to use assessment of motor skills, paired with screening of social, communication, and play skills, to detect signs of ASD early and refer to appropriate health care partners. Beth Ennis, PT, EdD, PCS University of St Augustine for Health Sciences St Augustine, Florida Sandra Jensen-Willett, PT, PhD, PCS Munroe-Meyer Institute University of Nebraska Medical Center Omaha, Nebraska

Development and Validation of a Multidimensional Short Version Zarit Burden Interview (ZBI-9) for Caregivers of Persons With Cognitive Impairment.

There is a lack of appreciation of the full dimensionality of the original 22-item Zarit Burden Interview (ZBI) in the development of short versions. Existing short versions are premised upon a 1-factor or 2-factor structure or statistical techniques for item selection. Thus, there is a need for ZBI short versions that considers the multidimensional constructs of role strain, personal strain, and worry about performance (WaP) during item selection to provide a more holistic and comprehensive evaluation. To develop and validate a short version of ZBI through a combined quantitative and qualitative approach that incorporates the validated 4-factor structure of role strain demands; role strain-control; personal strain, and WaP. We studied 202 caregivers of patients with dementia (84.2%) or mild cognitive impairment (15.8%) attending a memory clinic in Singapore. Confirmatory factor analysis and qualitative considerations from expert consensus were used for item selection. Confirmatory factor analysis fit statistics support the 4-factor structure. The 9-item ZBI-9 showed good internal consistency (Cronbach's α=0.87) and convergent validity with anxiety and depression (Pearson correlation: Hospital Anxiety and Depression sub-scales, r≥0.56, P <0.001; ZBI- 22, r=0.95, P <0.001). Using a cut-off score of ≥13, ZBI-9 displayed good discriminatory ability for depressive symptoms (area under curve=0.79, P <0.001; sensitivity=70%, specificity=75%). The ZBI-9 also displayed comparable performance to the 22-item full version and three 12-item short versions. The ZBI-9 is a multidimensional short-version assessment tool for caregivers of persons with dementia and mild cognitive impairment that is reliable, valid, and discriminates depressive symptoms.

A Survey on Evaluating the Quality of Autonomic Internet of Things Applications

The rapid evolution of the Internet of Things (IoT) facilitates the development of IoT applications in domains such as manufacturing, smart cities, retail, agriculture, etc. Such IoT applications collect data, analyze, and extract insightful information to enable decision-making and actuation. There is an unprecedented growth of IoT applications that automate decision-making and actuation without requiring human intervention, which we term autonomic IoT applications. The increasing scale of such applications necessitates holistic measurement and evaluation of application quality. Existing literature has evaluated quality from an end-user perspective, which may be unsuitable when dealing with the complexity of modern IoT applications, especially when they are autonomic. In this paper, we refer to IoT application quality as the aggregate quantitative value of various IoT quality metrics measured at each stage of the autonomic IoT application life cycle. We present an in-depth survey of current state-of-the-art techniques and approaches for evaluating quality of IoT applications. In particular, we survey various definitions to identify the factors that contribute to understanding and evaluating quality in IoT. Furthermore, we present open issues and identify future research directions towards realizing fine-grained quality evaluation of IoT applications. We envision that the identified research directions will, in turn, enable real-time diagnostics of IoT applications and make them quality-aware. This survey can serve as the basis for designing and developing modern, resilient quality-aware autonomic IoT applications.

“Beyond the Catch: A Holistic Socioeconomic Evaluation of Aghanashini's Fishing Communities”

“Beyond the Catch: A Holistic Socioeconomic Evaluation of Aghanashini's Fishing Communities”

Tailoring two white chromatographic platforms for simultaneous estimation of ritonavir-boosted nirmatrelvir in their novel pills: degradation, validation, and environmental impact studies.

As the COVID-19 pandemic is not yet over, Pfizer has launched the novel pill Paxlovid® (Nirmatrelvir (NMV) co-packaged with ritonavir (RIT)) as an effective medication for hospitalized and non-hospitalized patients. Making pharmaceutical analysis greener and more sustainable has lately become the main direction of the research community. In this context, two fast, green, and stability-indicating chromatographic methods were designed for the neat quantitative determination of NMV and RIT in their bulk and dosage forms. Method I is deemed the first electro-driven attempt for the assay of Paxlovid®. Herein, the optimized conditions of the Micellar Electrokinetic Chromatographic (MEKC) method were 50 mM borate buffer at pH 9.2 with 25 mM sodium lauryl sulfate (SDS) being used as the background electrolyte (BGE) on a deactivated fused silica capillary (50 cm effective length × 50 μm id). Method II was an isocratic reversed-phase HPLC separation method using Zorbax-Eclipse C18 (4.6 × 250 mm, 5 μm particle size) column and 50 mM ammonium acetate buffer at pH 5 and acetonitrile as mobile phase constituents at a flow rate of 1 mL min-1. For the sake of simplicity and increasing sensitivity, a single wavelength of 210 nm was used for the two methods to assay both drugs. Linear correlations between peak areas and concentration were observed in the ranges of 10-200 μg mL-1 for NMV and 5-100 μg mL-1 RIT in both methods. The impact of versatile stress conditions such as hydrolysis, oxidation, and photolysis on the stability of NMV and RIT was studied. Fortunately, both methodologies were able to separate both drugs from their degradants. Thus, the stability indicating power of the methods was proved. The derived methods were statistically validated in agreement with the ICH guidelines. Furthermore, the environmental friendliness and sustainability of these methods were investigated and compared with the cited methods using the holistic multicriteria evaluation tools namely Hexagon, AGREE, and RGB12 metrics. Conclusively, the proposed methods offered reliable, feasible, economic, white, and stability-indicating alternatives to the cited chromatographic methods.

Are we discriminating towards guests with disabilities? Accessibility analyses of public restaurants facilities in the Republic of Slovenia

Previous studies have not considered the importance of managers? perspectives for assuring accessibility, and no international benchmarking standards for public restaurant accessibility assessment exist. This study aims to: (1) Propose a holistic evaluation framework for the overall (physical, functional, and communicational) assessment of restaurant accessibility; (2) Identify managers? perceptions of accessibility; and (3) Determine differences in restaurant accessibility according to managers? and restaurants? characteristics. This study was conducted in two stages: literature and legislative analyses and exploratory research using focus groups (the national disability organisations representatives) and field research. The European (EU) and the national legislation were thoroughly analysed and compared to the Americans with disabilities act (ADA). A self-administered questionnaire was distributed to 180 managers of small and medium-sized (SME) restaurant enterprises in Slovenia. Bivariate and cluster analyses (CA) were used. Two clusters of restaurants (less and better accessible) were identified. Results indicate that physical barriers, though strictly regulated at the EU level, still present a significant shortcoming in providing accessible services. Functional and communicational barriers prove less problematic. Results also reveal that more accessible restaurants are bigger, have more employees, invest more in IT, and their managers have greater understanding and skills in this area. The evaluation tool enables a holistic approach to accessibility analysis by following the guest?s logical movement path. Besides stricter control, policymakers, interior designers, and restaurant service providers should collaborate closely with disability organisations. Restaurant service providers should be trained on disability issues.

Perspectives of Frequent Users of Emergency Departments on a Case Management Intervention: A Qualitative Study.

Effective management of frequent users of emergency departments (FUED) remains challenging. Case management (CM) has shown to improve patient quality of life while reducing ED visits and associated costs. However, little data is available on FUED's perception of CM outside of North America to further improve CM implementation. Explore the FUED's perspectives about CM in Switzerland. Semi-structured qualitative interviews eliciting FUED's experiences of CM were conducted among 20 participants (75% female; mean age = 40.6, SD = 12.8) across 6 hospital ED. Inductive content analysis. Most participants were satisfied with the CM program. In particular, FUEDs identified the working relationship with the case manager (cm) as key for positive outcomes, and also valued the holistic evaluation of their needs and resources. Overall, patients reported increased motivation and health literacy, as well as facilitated interactions within the healthcare system. Conversely, a small number of participants reported negative views on CM (ie, stigmatization, lack of concrete outcomes). Barriers identified were cm's lack of time, COVID-19's negative impact on CM organization, as well as lack of clarity on the objectives of CM. FUED perceived CM as useful, in particular establishing a working relationship with the cm. Our results suggest that CM can be further improved by (1) professionals remaining non-judgmental toward FUED, (2) making sure the aims and objectives of the CM are understood by the participants, and (3) allowing more time for the cm to carry out their work.

Performance Evaluation System Based on Multi-Indicators for Signal Recognition

Nowadays, the electromagnetic environment is becoming more and more complex, and it is increasingly difficult to accurately identify electromagnetic signals. At the same time, the quality of models and algorithms largely determines the final result of electromagnetic signal recognition, and a comprehensive and holistic evaluation system is needed to assess the quality of model or algorithm performance in the field of electromagnetic signal recognition. To address this phenomenon, this paper uses different machine learning models and AdaBoost algorithms to identify 100 classes of WiFi radiation source electromagnetic signals. In this paper, the classification performance, complexity and robustness of the models are evaluated comprehensively in three aspects respectively, and a multi-dimensional evaluation system for signal recognition is constructed, and the differences between different model algorithms in signal recognition effects are compared and analyzed, and the correlations between each evaluation index in different dimensions are explored. The experimental results show that different machine learning models and algorithms have different recognition effects on electromagnetic signals, among which the recognition accuracy of ResNet can reach more than 90%, but its computational complexity is high and easily affected by noise. DNN has poor recognition effect and the highest computational complexity, but it is not easily affected by noise. The AdaBoost algorithm does not necessarily improve the recognition classification accuracy of the underlying classifier. The evaluation system established in this paper is meaningful for assessing the performance of models and algorithms.

3D-Printed Musical Instruments: Lessons Learned from Five Case Studies

The music field is lively and creative, and innovation in the final product is a leading force in the sector. However, the physical instruments used by musicians to produce their craft are highly conservative and have developed little over the last centuries. Computers, audio software, and electronic musical instruments have been integrated into musical practice, but acoustic instrument design has remained virtually frozen. Although mass production methods are frequently applied to musical instrument production nowadays, the designs have changed minimally, which makes the musical landscape unique. Additive manufacturing (AM) provides novel possibilities that can be of interest in music and musical research. In this article, we present the results of five case studies on AM use within specific musical niches. Each niche represents a unique market space and cultural background that is critical in tradition-oriented environments. Starting from the analysis of these five case studies, we extract lessons on AM application to unique environments. From these, we discuss the potential for AM-driven innovation in design and production in general and propose a holistic evaluation matrix for identifying suitable market niches.

Influential Characteristics and Benefits of Cloud ERP Adoption in New Zealand SMEs: A Vendors’ Perspective

Cloud enterprise resource planning (ERP) systems are hosted services offering opportunities for small and medium-sized enterprises (SMEs) that often lack IT resources. Few studies have examined the adoption of cloud ERP systems in SMEs, specifically, from the perspective of cloud ERP vendors who are the domain experts. Drawing on vendors’ perspectives in the New Zealand (NZ) context, this paper evaluates the influential characteristics for adopting cloud ERP systems in SMEs. The paper uses an integrative model combining the technological, organizational, and environmental (TOE) framework with the unified theory of acceptance and use of technology (UTAUT) based on individual dimension for a holistic evaluation. Findings reveal novel characteristics including system reliability and data security that influence adoption of cloud ERP. Further, benefits are identified such as reduced cost and time for deployment, increased scalability, and improved accessibility. The paper presents new insights that can help SME managers successfully adopt cloud ERP in their firms in addition to providing practical guidelines for adoption in NZ. The development of a theoretical model integrating TOE and UTAUT is a novel approach, substantially contributing to the body of knowledge.

A Sensor-Based Platform for Early-Stage Parkinson's Disease Monitoring.

Biosensing platforms have gained much attention in clinical practice screening thousands of samples simultaneously for the accurate detection of important markers in various diseases for diagnostic and prognostic purposes. Herein, a framework for the design of an innovative methodological approach combined with data processing and appropriate software in order to implement a complete diagnostic system for Parkinson's disease exploitation is presented. The integrated platform consists of biochemical and peripheral sensor platforms for measuring biological and biometric parameters of examinees, a central collection and management unit along with a server for storing data, and a decision support system for patient's state assessment regarding the occurrence of the disease. The suggested perspective is oriented on data processing and experimental implementation and can provide a powerful holistic evaluation of personalized monitoring of patients or individuals at high risk of manifestation of the disease.

Frailty assessment as part of transplant listing: yes, no or maybe?

Frailty, characterized by a decreased physiological reserve and an increased vulnerability to stressors, is common among kidney transplant (KT) candidates and recipients. In this review, we present and summarize the key arguments for and against the assessment of frailty as part of KT evaluation. The key arguments for including frailty were: (i) sheer prevalence and far-reaching consequences of frailty on KT, and (ii) the ability to conduct a more holistic and objective evaluation of candidates, removing the inaccuracy associated with 'eye-ball' assessments of transplant fitness. The key argument against were: (i) lack of agreement on the definition of frailty and which tools should be used in renal populations, (ii) a lack of clarity on how, by whom and how often frailty assessments should be performed, and (iii) a poor understanding of how acute stressors affect frailty. However, it is the overwhelming opinion that the time has come for frailty assessments to be incorporated into KT listing. Although ongoing areas of uncertainty exist and further evidence development is needed, the well-established impact of frailty on clinical and experiential outcomes, the invaluable information obtained from frailty assessments, and the potential for intervention outweigh these limitations. Proactive and early identification of frailty allows for individualized and improved risk assessment, communication and optimization of candidates.

Representation Matters: One Urology Residency Program's Approach to Increasing Workforce Diversity

ObjectiveTo address the challenge in urology in recruiting physicians from backgrounds racially and ethnically underrepresented in medicine (URiM), we sought to design, implement, and evaluate methods for recruiting URiM candidates to our urology residency program. MethodsWe developed a 3-pronged approach aimed at increasing the number of interviewed applicants, and subsequently number of URiM residents recruited to our program. The 3 facets included: (1) funded visiting student rotation, (2) holistic evaluation of applications, (3) implemented targeted outreach. Statistical analysis of the applicants interviewed and matched into our residency program, as well as traditional metrics used for residency recruitment, were performed from 2015 to 2022. ResultsThe number of URiM interviewees significantly increased from 6.1% in 2015 to its peak, 40%, in 2020. In 2015, there were no URiM residents in our urology residency program. By 2022, the total URiM complement increased to 35%. In evaluating traditional metrics of residency recruitment, there was no significant difference in mean USMLE Step 1 score before compared with after the implementation of our recruitment approach. The maximum rank number reached to fill the urology residency positions also remained relatively stable throughout the study period, with a range from 5 to 38. ConclusionWe demonstrate that the implementation of our innovative and intentional 3-pronged recruitment approach effectively increased the number of URiM interviewees and residents in our residency program. The diversification of our urology workforce depends on the implementation of such efforts, and we encourage urologists to lead the way on such initiatives.