scholarly journals Evaluation of the Nomological Validity of Cognitive, Emotional, and Behavioral Factors for the Measurement of Developer Experience

2021 ◽  
Vol 11 (17) ◽  
pp. 7805
Author(s):  
Heeyoung Lee ◽  
Younghwan Pan
Keyword(s):  
Deep Learning ◽  
Delphi Study ◽  
Reliability And Validity ◽  
Measurement Instrument ◽  
Measurement Model ◽  
Second Order ◽  
Current Work ◽  
Development Platform ◽  
Learning Platform ◽  
Nomological Validity

Background: Developer experience should be considered a key factor from the beginning of the use of development platform, but it has not been received much attention in literature. Research Goals: The present study aimed to identify and validate the sub-constructs and item measures in the evaluation of developer experience toward the use of a deep learning platform. Research Methods: A Delphi study as well as a series of statistical methodologies including the assessment of data normality, common method bias, and exploratory and confirmatory factor analysis were utilized to determine the reliability and validity of a measurement model proposed in the present work. Results: The results indicate that the measurement model proposed in this work successfully ensures the nomological validity of the three second-order constructs of cognitive, affective, and behavioral components to explain the second-order construct of developer experience at p < 0.5 Conclusions: The measurement instrument developed from the current work should be used to measure the developer experience during the use of a deep learning platform. Implication: The results of the current work provide important insights into the academia and practitioners for the understanding of developer experience.

The measurement structure of dispositional hope: Hierarchical and bifactor models

2018 ◽  
Vol 46 (4) ◽  
pp. 597-606
Author(s):  
Zhihua Li ◽  
Xiayun Yin ◽  
Huilin Yang ◽  
Jianxiang Tian
Keyword(s):  
Cultural Context ◽  
Reliability And Validity ◽  
Measurement Model ◽  
Second Order ◽  
Hope Theory ◽  
Fit Indices ◽  
Confirmatory Factor ◽  
Bifactor Models ◽  
Dispositional Hope ◽  
Wish Fulfillment

Hope is a higher-order cognitive construct relating to expectations of or beliefs in wish fulfillment, which has been conceptualized as consisting of 2 components: pathways thinking (the perceived means available to individuals that allow them to achieve their goals) and agency thinking (belief in one's ability to succeed in using the identified pathways). We aimed to clarify the measurement structure of the Chinese version of the Adult Dispositional Hope Scale, using a sample of 751 university student participants. We employed confirmatory factor analysis to compare 1-factor, 2-factor, second-order, and bifactor models. The results showed that all models fit the measured data well. However, the bifactor model had the best fit indices, whereas the second-order model was the most consistent with the theoretical measurement model. To verify that hope theory and the corresponding instruments can be confidently applied to cross-cultural samples, it is necessary to further assess their reliability and validity in a Chinese cultural context through a measurement structure analysis.

Confirmation of a measurement model for manufacturing flexibility development practices

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ruchi Mishra
Keyword(s):  
Reliability And Validity ◽  
Measurement Instrument ◽  
Measurement Model ◽  
Manufacturing Flexibility ◽  
Process Technology ◽  
Content Type ◽  
Supplier Integration ◽  
Advanced Manufacturing Technologies ◽  
Operational Improvement ◽  
Manufacturing Technologies

PurposeThe study aims to conceptualize and empirically develop an instrument to measure manufacturing flexibility development practices in firms.Design/methodology/approachUsing a dataset of 315 responses, a series of procedures were used to develop, modify and refine item measures of constructs to enhance their reliability and validity. Further, following a competing model strategy, alternative models were compared to finalize the manufacturing flexibility development practices.FindingsThe study develops 36-item instrument capturing eight distinct constructs that influence manufacturing flexibility development, namely operational improvement practices, supplier integration practices, advanced manufacturing technologies, advanced human resource practices, supplier flexibility, customer integration practices, marketing and manufacturing integration practices and product-process technology integration. The derived factors exhibit an adequate level of consistency, reliability and validity.Research limitations/implicationsSince the external environment is always affected by externalities, tools and technologies used to develop flexibility may also vary over time. Therefore, the developed measurement instrument can be used over the medium term. Further, the statistical generalizability of this study cannot be drawn beyond the scope of this sample.Practical implicationsThe derived items measure and their underlying factor structure facilitates practitioners to identify areas that need attention. Practically, practitioners should strive to improve multiple factors that influence manufacturing flexibility to arrive at the full realization of flexibility.Originality/valueThis study is probably the first to develop an instrument for assessing the factors influencing the potential of manufacturing flexibility.

scholarly journals Automatic detection of 39 fundus diseases and conditions in retinal photographs using deep neural networks

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ling-Ping Cen ◽  
Jie Ji ◽  
Jian-Wei Lin ◽  
Si-Tong Ju ◽  
Hong-Jie Lin ◽  
...  
Keyword(s):  
Deep Learning ◽  
High Efficiency ◽  
Characteristic Curve ◽  
Weighted Average ◽  
Age Related Macular Degeneration ◽  
Learning Platform ◽  
Age Related ◽  
Public Data ◽  
Primary Test ◽  
Retinal Fundus

AbstractRetinal fundus diseases can lead to irreversible visual impairment without timely diagnoses and appropriate treatments. Single disease-based deep learning algorithms had been developed for the detection of diabetic retinopathy, age-related macular degeneration, and glaucoma. Here, we developed a deep learning platform (DLP) capable of detecting multiple common referable fundus diseases and conditions (39 classes) by using 249,620 fundus images marked with 275,543 labels from heterogenous sources. Our DLP achieved a frequency-weighted average F1 score of 0.923, sensitivity of 0.978, specificity of 0.996 and area under the receiver operating characteristic curve (AUC) of 0.9984 for multi-label classification in the primary test dataset and reached the average level of retina specialists. External multihospital test, public data test and tele-reading application also showed high efficiency for multiple retinal diseases and conditions detection. These results indicate that our DLP can be applied for retinal fundus disease triage, especially in remote areas around the world.

scholarly journals The Multifocal Approach to Sharing in Shared Decision Making: A Critical Appraisal of the MAPPIN’SDM

2021 ◽  
pp. 0272989X2110107
Author(s):  
David Forner ◽  
Christopher W. Noel ◽  
Laura Boland ◽  
Arwen H. Pieterse ◽  
Cornelia M. Borkhoff ◽  
...  
Keyword(s):  
Decision Making ◽  
Shared Decision Making ◽  
Critical Appraisal ◽  
Reliability And Validity ◽  
Measurement Instrument ◽  
Face Validity ◽  
Shared Decision ◽  
Measurement Instruments ◽  
Multiple Perspectives ◽  
Property Assessment

Objective Shared decision making integrates health care provider expertise with patient values and preferences. The MAPPIN’SDM is a recently developed measurement instrument that incorporates physician, patient, and observer perspectives during medical consultations. This review sought to critically appraise the development, sensibility, reliability, and validity of the MAPPIN’SDM and to determine in which settings it has been used. Methods This critical appraisal was performed through a targeted review of the literature. Articles outlining the development or measurement property assessment of the MAPPIN’SDM or that used the instrument for predictor or outcome purposes were identified. Results Thirteen studies were included. The MAPPIN’SDM was developed by both adapting and building on previous shared decision making measurement instruments, as well as through creation of novel items. Content validity, face validity, and item quality of the MAPPIN’SDM are adequate. Internal consistency ranged from 0.91 to 0.94 and agreement statistics from 0.41 to 0.92. The MAPPIN’SDM has been evaluated in several populations and settings, ranging from chronic disease to acute oncological settings. Limitations include high reading levels required for self-administered patient questionnaires and the small number of studies that have employed the instrument to date. Conclusion The MAPPIN’SDM generally shows adequate development, sensibility, reliability, and validity in preliminary testing and holds promise for shared decision making research integrating multiple perspectives. Further research is needed to develop its use in other patient populations and to assess patient understanding of complex item wording.

Assessing Music Expertise

2021 ◽  
Vol 38 (4) ◽  
pp. 406-421
Author(s):  
Ziyong Lin ◽  
André Werner ◽  
Ulman Lindenberger ◽  
Andreas M. Brandmaier ◽  
Elisabeth Wenger
Keyword(s):  
Hierarchical Model ◽  
Structural Equation ◽  
Measurement Instrument ◽  
Second Order ◽  
Equation Modeling ◽  
General Factor ◽  
General Music ◽  
Professional Musicians ◽  
Unidimensional Model ◽  
Amateur Musicians

We introduce the Berlin Gehoerbildung Scale (BGS), a multidimensional assessment of music expertise in amateur musicians and music professionals. The BGS is informed by music theory and uses a variety of testing methods in the ear-training tradition, with items covering four different dimensions of music expertise: (1) intervals and scales, (2) dictation, (3) chords and cadences, and (4) complex listening. We validated the test in a sample of amateur musicians, aspiring professional musicians, and students attending a highly competitive music conservatory (n = 59). Using structural equation modeling, we compared two factor models: a unidimensional model postulating a single factor of music expertise; and a hierarchical model, according to which four first-order subscale factors load on a second-order factor of general music expertise. The hierarchical model showed better fit to the data than the unidimensional model, indicating that the four subscales capture reliable variance above and beyond the general factor of music expertise. There were reliable group differences on both the second-order general factor and the four subscales, with music students outperforming aspiring professionals and amateur musicians. We conclude that the BGS is an adequate measurement instrument for assessing individual differences in music expertise, especially at high levels of expertise.

scholarly journals On the objectivity, reliability, and validity of deep learning enabled bioimage analyses

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Dennis Segebarth ◽  
Matthias Griebel ◽  
Nikolai Stein ◽  
Cora R von Collenberg ◽  
Corinna Martin ◽  
...  
Keyword(s):  
Deep Learning ◽  
Signal To Noise Ratio ◽  
Biological Effects ◽  
Reliability And Validity ◽  
Ground Truth ◽  
Training Data ◽  
Model Organisms ◽  
Data Annotation ◽  
Bioimage Analysis ◽  
Model Training

Bioimage analysis of fluorescent labels is widely used in the life sciences. Recent advances in deep learning (DL) allow automating time-consuming manual image analysis processes based on annotated training data. However, manual annotation of fluorescent features with a low signal-to-noise ratio is somewhat subjective. Training DL models on subjective annotations may be instable or yield biased models. In turn, these models may be unable to reliably detect biological effects. An analysis pipeline integrating data annotation, ground truth estimation, and model training can mitigate this risk. To evaluate this integrated process, we compared different DL-based analysis approaches. With data from two model organisms (mice, zebrafish) and five laboratories, we show that ground truth estimation from multiple human annotators helps to establish objectivity in fluorescent feature annotations. Furthermore, ensembles of multiple models trained on the estimated ground truth establish reliability and validity. Our research provides guidelines for reproducible DL-based bioimage analyses.

How nostalgia forges place attachment and revisit intention: a moderated mediation model

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Heetae Cho
Keyword(s):  
Place Attachment ◽  
Reliability And Validity ◽  
Measurement Model ◽  
Past Experience ◽  
Content Type ◽  
Sport Fans ◽  
Mediating Role ◽  
Moderated Mediation Model ◽  
Revisit Intention ◽  
Sport Consumer Behavior

PurposeAnalyzing sport fans' emotions has attracted much attention and offered important implications for research on sport consumer behavior. As such, diverse emotional factors have been considered to understand their behavioral responses. However, the concept of nostalgia has been examined to a lesser extent in the context of sport. Thus, this study investigated the role of nostalgia and its relationships with place attachment and revisit intention. The frequency of past experience was used as a moderator in this study.Design/methodology/approachData collection was performed during six professional baseball games in South Korea, and 461 responses were collected from sport tourists. This study tested the reliability and validity of the measurement model and examined the relationships between constructs.FindingsResults showed that nostalgia positively affected place attachment and revisit intention; place attachment played a mediating role between nostalgia and revisit intention. In addition, this study found that the relationship between nostalgia and place attachment was moderated by past experience.Originality/valueThis study identified how nostalgia can drive the development of a bond between place and sport fans, encouraging them to keep returning to the place where they are attached.

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