Qualitative Concepts Research Articles

A hybrid model-based framework for estimating ecological risk

For the protection of ecosystems, estimation of ecological risk considering multiple hazards is required. The ecological risk entails subjectivity, randomness, and fuzziness which should be managed appropriately in its estimation. This study developed a framework based on a hybrid model for estimating ecological risk by employing multi-cloud enhanced-fuzzy support vector machine (MC-FSVM). The enhanced FSVM was applied for accounting of multiple hazards, and multi-cloud was used to simultaneously take fuzziness and randomness into account. Based on the prior information, multi-cloud was developed to implement the uncertain transformation between a qualitative concept and its quantitative numerical representation. The degree of certainty derived from the constructed cloud was applied to the enhance fuzzy vector machine to construct an MC-FSVM model. Then by inputting the data into the model trained, ecological risks were graded. This framework was applied to estimate risk in seven regions from five countries and its performance was compared with other two approaches. Results showed the impact of the degree of certainty on the grading of risk and indicated that this framework can be a useful alternative for ecological risk estimation.

Coming in Warm: Qualitative Study and Concept Map to Cultivate Patient-centered Empathy in Emergency Care.

Increased empathy may improve patient perceptions and outcomes. No training tool has been derived to teach empathy to emergency care providers. Accordingly, we engaged patients to assist in creating a concept map to teach empathy to emergency care providers. We recruited patients, patient caretakers and patient advocates with emergency department experience to participate in three separate focus groups (n=18 participants). Facilitators guided discussion about behaviors that physicians should demonstrate to rapidly create trust; enhance patient perception that the physician understood the patient's point of view, needs, concerns, and fears; and optimize patient/caregiver understanding of their experience. Verbatim transcripts from the three focus groups were read by the authors, and by consensus, five major themes with 10 minor themes were identified. After creating a codebook with thematic definitions, one author reviewed all transcripts to a library of verbatim excerpts coded by theme. To test for inter-rater reliability, two other authors similarly coded a random sample of 40% of the transcripts. Authors independently chose excerpts that represented consensus and strong emotional responses from participants. Approximately 90% of opinions and preferences fell within 15 themes, with five central themes: provider transparency, acknowledgment of patient's emotions, provider disposition, trust in physician, and listening. Participants also highlighted the need for authenticity, context, and individuality to enhance empathic communication. For empathy map content, patients offered example behaviors that promote perceptions of physician warmth, respect, physical touch, knowledge of medical history, explanation of tests, transparency, and treating patients as partners. The resulting concept map was named the "Empathy Circle." Focus group participants emphasized themes and tangible behaviors to improve empathy in emergency care. These were incorporated into the Empathy Circle, a novel concept map that can serve as the framework to teach empathy to emergency care providers.

Modeling the formation of soil microaggregates

The functions of soils are intimately linked to its aggregated structure. Microaggregates formed during pedogenesis from a vast variety of mineral, organic, and biotic materials are the smallest conceivable compounds at the basis of soil structural hierarchy. Qualitative hypotheses and concepts on how aggregates form are quite elaborate, but the consistent quantitative application within a mechanistic and physically rigorous framework is still missing. This is partly caused by the fact that such an endeavor requires the combination of synergistic concepts on the transport of particles and their interactions affected by shape, size, and surface properties in aqueous suspension. Here we present a novel quantitative approach for the formation of soil microaggregates in silico that integrates diffusion-limited cluster-cluster aggregation with a probabilistic attachment following the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory of particle interactions. To represent universal mineral shapes found in soils, we implemented spherical, plate-like as well as rod-like particle morphologies inspired by weathered silicates, secondary clay minerals and pedogenic iron oxides. In this way, we developed a model that produces an explicit three-dimensional structure of aggregates emerging from hetero- as well as homo-aggregation in response to the chemical milieu. We then exploited the 3D morphology to assess functional properties of aggregates exemplified with the water retention curve and pore size distribution.

A Novel Method to Assess Safety of Buried Pressure Pipelines under Non-Random Process Seismic Excitation based on Cloud Model

It is necessary to conduct a safety assessment for pipelines which are regarded as important lifeline projects after an earthquake. Since the random process of loading in earthquake engineering requires a large amount of samples, this paper establishes a non-random vibration method based on convex model theory and applies it to small sample engineering. Moreover, a space–time analytical model of buried pipeline and a finite element model are established to solve the dynamic response of pipelines with non-random process seismic excitation. Furthermore, the randomness of the stress values of the pipeline subjected to earthquake and the fuzziness of the degree of damage to pipelines are considered. Therefore, a novel method for assessing damage to pipelines is proposed based on cloud model. The results indicate that an analysis of non-random vibration combined with the cloud inference method can solve the fuzziness and randomness of the quantitative description and qualitative concept conversion for damage evaluation of pipelines. The method is also an adaptive and effective assessment method for pipelines exposed to earthquake and is able to promote safety management of pipeline engineering.

Quality evaluation of Chinese red wine based on cloud model.

Determining the quality of red wine is based on many qualitative and quantitative factors. Compared with other evaluation methods, the cloud model has an uncertainty transformation between a qualitative concept and its corresponding quantitative value, and the uncertainty transformation included fuzziness and randomness, which is suitable for solving the complexity of red wine evaluation. This study introduced the cloud model into quality evaluation of red wine for the first time, and a novel algorithm of comprehensive cloud model was proposed based on an addition algorithm of two cloud models. Furthermore, to validate the cloud model adopted in our red wine evaluation system, we used the gray relational analysis and fuzzy evaluation method. The evaluation result for the red wine sample was Good, and the result confirmed that our cloud model can be used to evaluate the quality of red wine. PRACTICAL APPLICATIONS: In 2013, China surpassed France to become the largest country of red wine consumption in the world. Red wine is made by a natural fermentation process. There are several components that make up red wine, but the most abundant is grape juice. Ethyl alcohol is the second most abundant element and it is made naturally by the fermentation of the sugar in grape. There are more than 1,000 remaining components in the recipe for red wine, where 300 are comparatively important. Although the proportion of these components is not high, they are important factors in determining the quality of red wine. Sensory evaluation is the most common method used to determine the quality of red wine. This work has identified a cloud model that can be used, based on sensory evaluation, to determine the quality of red wine.

Pendidikan Teologi Lintas Agama dalam Meraih Keluarga Bahagia (Analisis Teori Islam, Kristen, Hindu, Budha dan Konghucu)

This article wants to reveal cross-ideological religious education in conceptualizing a happy family. The most important thing is that religious education is very urgent in forming a family of happiness that is indoctrinated in a family. This research method uses qualitative descriptive concept, with research type of library of Risert (bibliography), data collection method is using primary and secondary data and technical data analysis is using contents analysis method (deductive and inductive). Religious education is the best way to achieve the happiness of the hereafter. Religious education is the perfect solution for achieving individual happiness, the smallest group (family) and community groups. Religious education is an easy way to achieve physical and spiritual happiness in its entirety. Religious education is a necessity for every religious community as a theory to reach the happiness of soul, family and society. Happy family will be obtained if the understanding of religion that is applied by every family member in the household and society. The happiness of society is the happiest family happiness in a country or group of people, in Islamic teachings called baldatun thayyibatun wa raobbun ghafur.

Development and content validity of new patient-reported outcome questionnaires to assess the signs and symptoms and impact of atopic dermatitis: the Atopic Dermatitis Symptom Scale (ADerm-SS) and the Atopic Dermatitis Impact Scale (ADerm-IS)

Objectives: Atopic dermatitis (AD) is a chronic, relapsing skin condition, with signs and symptoms that impact patients’ lives and are best measured from the patient perspective. Therefore, there is a need for AD-specific questionnaires that are consistent with Food and Drug Administration guidance and best measurement practices, assessing sign and symptom severity and associated impacts, to support treatment efficacy in regulated trials. The objectives were to develop patient-reported outcome (PRO) questionnaires assessing sign and symptom severity, as well as impacts of moderate-to-severe adult AD.Methods: A targeted literature review and meetings with clinical experts (dermatologists) were conducted to identify AD-related sign, symptom, and impact concepts. Results were harmonized and used to construct two draft PRO questionnaires: the Atopic Dermatitis Symptom Scale (ADerm-SS; 11 items) and the Atopic Dermatitis Impact Scale (ADerm-IS; 10 items). The content validity and questionnaire content were evaluated via qualitative concept elicitation/cognitive debriefing interviews with adult patients with moderate-to-severe AD.Results: From the literature (n = 13 articles), 13 sign and symptom and 43 impact concepts were identified, while 21 sign and symptom and 48 impacts were elicited from experts (n = 3). During the patient interviews (n = 15), 19 sign and symptom and 41 impact concepts were reported, the majority of which were evaluated by the ADerm-SS and ADerm-IS, thus substantiating the content of both questionnaires. Additionally, patients interpreted both questionnaires as intended by the developers.Conclusions: The ADerm-SS and ADerm-IS can be regarded as content-valid PRO questionnaires for moderate-to-severe AD.

Clustering Cloud-Like Model-Based Targets Underwater Tracking for AUVs.

Autonomous underwater vehicles (AUVs) rely on a mechanically scanned imaging sonar that is fixedly mounted on AUVs for underwater target barrier-avoiding and tracking. When underwater targets cross or approach each other, AUVs sometimes fail to track, or follow the wrong target because of the incorrect association of the multi-target. Therefore, a tracking method adopting the cloud-like model data association algorithm is presented in order to track underwater multiple targets. The clustering cloud-like model (CCM) not only combines the fuzziness and randomness of the qualitative concept, but also achieves the conversion of the quantitative values. Additionally, the nearest neighbor algorithm is also involved in finding the cluster center paired to each target trajectory, and the hardware architecture of AUVs is proposed. A sea trial adopting a mechanically scanned imaging sonar fixedly mounted on an AUV is carried out in order to verify the effectiveness of the proposed algorithm. Experiment results demonstrate that compared with the joint probabilistic data association (JPDA) and near neighbor data association (NNDA) algorithms, the new algorithm has the characteristic of more accurate clustering.

Development and adaptation of patient-reported outcome measures for patients who experience itch associated with primary biliary cholangitis

PurposeTo conduct qualitative interviews to evaluate and refine the Itch Diary (ID) and weekly version of the PBC-40 in patients with itching associated with primary biliary cholangitis (PBC).MethodsTwenty adults with self-reported PBC diagnoses and recent/ongoing itching of at least moderate intensity participated in face-to-face qualitative combined concept elicitation (CE) interviews and cognitive interviews after completing the morning and evening versions of the ID and weekly version of the PBC-40. These questionnaires were evaluated to confirm saturation of concepts of interest and cognitively test the English language versions of the measures in patients with PBC in the US and Canada. Transcripts were organized into descriptions of PBC-related symptoms and symptom-related impacts using a structured coding framework. Two waves of interviews were conducted; revisions made after wave 1 were further tested in wave 2.ResultsInterview results confirmed the relevance of concepts presented in the PBC-40 and ID to patients’ experiences. Saturation of concept was achieved. Itching-related signs and symptoms (46%) were the most commonly expressed symptom concept in the CE interviews followed by energy-related (14%) and additional signs/symptoms (13%). Several changes to the ID were made in response to cognitive interview results. Changes to the PBC-40 included adaptations from British to North American English, and the appropriateness of a 7-day recall period was confirmed.ConclusionsRelevance of the symptom and impact concepts in the ID to measure PBC-related itch were confirmed. Adaptation of the PBC-40 to a weekly recall period and for North American English was successful.

Research on Rock Mass Quality Classification Based on An Improved Rough Set–Cloud Model

Rock mass grading is a basic problem in the construction industry and underground engineering research. Because the index parameters that affect the rock mass quality are ambiguous and random, rock mass quality classification is often uncertain. Based on this issue, this paper selects the rock quality index RQD , rock uniaxial saturated compressive strength Rw , rock mass integrity coefficient Kv , structural surface strength coefficient $K_{f}$ and groundwater seepage quantity $\omega $ as quantitative evaluation indicators to construct an evaluation system. Thirty sets of data collected in China are selected as learning samples. Through the related concepts and finite interval cloud model, the characteristic parameters of the measured data are obtained, and a cloud model is generated with a forward cloud generator to achieve the transformation between qualitative and quantitative concepts. Combined with the basic knowledge of rough set theory, the weight determination problem is transformed into an attribute importance problem. To avoid zero weights in the traditional rough set approach, this paper introduces a calculation method based on the conditional information entropy, and the weight calculation method is modified to obtain the comprehensive weights. According to the principle of the maximum membership degree, the classification of rock mass quality is performed, and the rock mass quality data are determined to have different levels of comprehensive membership. A rock mass quality evaluation method based on the coupled improved rough set–cloud model is established and successfully applied for a rock mass quality evaluation of the 0+000~0+560 test section of the second stage of underground engineering at the Guangdong Pump Storage Power Station. The results show that the model is reliable and practical and provides a new approach for uncertainty analysis and evaluation in rock engineering practice.

A Proposal for a Predictive Performance Assessment Model in Complex Sociotechnical Systems Combining Fuzzy Logic and the Functional Resonance Analysis Method (FRAM)

Modern sociotechnical systems exhibit dynamic and complex behavior, which can be difficult to anticipate, model and evaluate. The perpetually evolving nature and the emergent properties of such systems require a continuous re-evaluation of adopted safety and risk analysis methods to comply with arising challenges and ensure successful performance. One of the interesting methods proposed in recent years is the Functional Resonance Analysis Method (FRAM). FRAM adopts a systemic perspective to model sociotechnical systems characterizing non-linear relationships and quality of outcome arising from performance variability and functional resonance. This paper aims to further improve the framework and expand the spectrum of features provided by FRAM through the integration of fuzzy logic. Fuzzy logic offers adequate mathematical tools capable of quantifying qualitative concepts and uncertain information applying comprehensible inference systems based on human judgement. An example of a possible application scenario is included through a simulation of aircraft on-ground deicing operations. The preliminary results of this project present an approach to generate numerical indicators for the quality of outputs, which can allow for a more comprehensible representation of potential performance variability. The presented model, however, requires further validation and optimization work to provide more representative and reliable results.

How Contextual Frames Normalize Submission

ABSTRACTTwo studies demonstrate how contextual frames normalize submission and hereby complement and legitimize the exercise of power. Combining Kuhn’s qualitative concept of the self with Charles Osgood’s empirical measurements of self-attitudes, the first study tests the impact of the frame of submission on self-attitudes. This assessment of the self allows to quantify the influence of a frame or context. A second study tests the hypothesis that selves, organized by the context of submission, will normalize acts of submission. Computer simulations that quantitatively operationalize the Cybernetic Symbolic Interactionist perspective, find evidence for the normalizing quality of frames.

Cryptic selection forces and dynamic heritability in generalized phenotypic evolution

Individuals with different phenotypes can have widely-varying responses to natural selection, yet many classical approaches to evolutionary dynamics emphasize only how a population’s average phenotype increases in fitness over time. However, recent experimental results have produced examples of populations that have multiple fitness peaks, or that experience frequency-dependence that affects the direction and strength of selection on certain individuals. Here, we extend classical fitness gradient formulations of natural selection in order to describe the dynamics of a phenotype distribution in terms of its moments—such as the mean, variance, and skewness. The number of governing equations in our model can be adjusted in order to capture different degrees of detail about the population. We compare our simplified model to direct Wright–Fisher simulations of evolution in several canonical fitness landscapes, and we find that our model provides a low-dimensional description of complex dynamics not typically explained by classical theory, such as cryptic selection forces due to selection on trait ranges, time-variation of the heritability, and nonlinear responses to stabilizing or disruptive selection due to asymmetric trait distributions. In addition to providing a framework for extending general understanding of common qualitative concepts in phenotypic evolution – such as fitness gradients, selection pressures, and heritability – our approach has practical importance for studying evolution in contexts in which genetic analysis is infeasible.

A Linguistic Large Group Decision Making Method Based on the Cloud Model

Serving as an effective tool for describing both randomness and fuzziness of qualitative concepts, the cloud model has become a common topic of research. By realizing the uncertain transformation between qualitative concepts and quantitative data, the cloud model provides a new way to deal with group decision making problems in the linguistic environment. However, classical methods based on the cloud model mainly focus on addressing problems with a small number of decision makers. In this paper, we apply the cloud model to the decision making problems that involve a large group of decision makers. Specifically, we first define a new measure of fuzzy distance for clouds based on the $\boldsymbol { \alpha -cuts}$ . On the basis of the proposed fuzzy distance measure, we then present a new similarity measure between clouds. Next, we construct an improved clustering approach based on the traditional hierarchical clustering algorithm. Furthermore, we develop a hybrid weight scheme to obtain the cluster weight vector, which takes both the subgroup size and the variance into consideration. Moreover, we present a consensus-based method based on the cloud model for large group decision making with linguistic information. Finally, in order to confirm the validity and effectiveness of the proposed method, we give an application in the context of the Belt and Road Initiative of China, and perform some detailed comparisons to show the advantages of the proposed method.

A Study on Effectiveness Evaluation for the Physical Protection System of a High Security Prison Based on the Cloud Model

In order to improve the effectiveness and accuracy of effectiveness evaluation for the physical protection system of a high security prison, this paper analyzed factors affecting the evaluation of such a system and, on this basis, applied the cloud theory and constructed a cloud model for evaluating the effectiveness of such a system. A case study was used to discuss the risk controllability of such a system with the evaluation method based on the cloud model. The research results show that the cloud model that we constructed for effectiveness evaluation can greatly reduce the influence of subjective factors in the risk evaluation for the physical protection system of a high security prison through the setting, calculation, and analysis of relevant parameters and we found that it is more accurate and practically useful especially when it is used in the evaluation together with the fuzziness and randomness of qualitative linguistic concepts.

Analyzing Theories in the Frame Model

The frame model was developed in cognitive psychology and imported into the philosophy of science in order to provide representations of scientific concepts and conceptual taxonomies. The aim of this article is to show that beside the representation of scientific concepts the frame model is an efficient instrument to represent and analyze scientific theories. That is, we aim to establish the frame model as a representation tool for the structure of theories within the philosophy of science. For this, we will develop the notion of a theory frame and distinguish between theory frames for qualitative theories in which scientific measurement is based on nominal scales and theory frames for quantitative theories in which measurement is based on ratio scales. In three case studies, we will apply frames to a psychological, a linguistic, and a physical theory, thereby showing that the frame model is a powerful and intuitively accessible instrument to analyze the laws of scientific theories, the determination of theoretical concepts, the explanatory role of theoretical concepts, the abductive introduction of a new theoretical concept, the distinction between the core and the periphery of a theory, the diachronic development of a theory, and the distinction between qualitative and quantitative scientific concepts. Finally, we will provide a comparison to the structuralist view of theories, one of the most elaborated and applied models of theory representation.

Development and Validation of the Endometriosis Daily Pain Impact Diary Items to Assess Dysmenorrhea and Nonmenstrual Pelvic Pain.

Daily diary-based dysmenorrhea and nonmenstrual pelvic pain impact items were developed and validated to measure efficacy in endometriosis clinical trial settings. Items were developed across 3 stages of qualitative research, and their psychometric properties were explored in a phase II randomized controlled trial. Eight focus groups, 20 semistructured telephone interviews, and 15 face-to-face concept elicitation and cognitive debriefing interviews constituted the qualitative phase of the research. Psychometric properties of reliability, convergent validity, and responsiveness of the dysmenorrhea and nonmenstrual pelvic pain daily items were examined quantitatively in a phase II clinical trial of an investigational endometriosis treatment. Both qualitative concept elicitation and cognitive debriefing research yielded wording for item response options that resonated with adult women with endometriosis. Daily assessment of dysmenorrhea and nonmenstrual pelvic pain impact was the preferred measurement approach among adult women with endometriosis. Quantitatively, correlations between the dysmenorrhea and nonmenstrual pelvic pain items and other measures of pain impact provided endorsement for the items' convergent validity. Longitudinal measurement properties, involving test-retest reliability and sensitivity to change/responsiveness, offered evidence for the adequacy of the measurement properties of the daily diary-based dysmenorrhea and nonmenstrual pelvic pain impact items. Data from a phase II trial provided evidence that the daily dysmenorrhea and nonmenstrual pelvic pain impact items, developed and tested through qualitative research involving both focus groups and individual interviews, are well-defined, reliable, valid, and responsive for measuring the impact of pain in endometriosis to assess therapeutic response.

Development of a New Tool for Evaluating the Benefit of Preventive Treatments for Migraine on Functional Outcomes - The Migraine Functional Impact Questionnaire (MFIQ).

ObjectiveThe objective of this study was to develop a method for evaluating patient‐relevant outcomes of interventions for preventing migraine attacks, followed by an assessment of the content validity of a new patient‐reported outcome (PRO) instrument: the Migraine Functional Impact Questionnaire (MFIQ).BackgroundThe aim of preventive treatments for migraine is not only to reduce migraine frequency, but also to restore patients’ ability to function and improve quality of life.MethodsA multi‐stage process based on best practice methods and regulatory guidelines for ensuring content validity of PRO instruments for evaluating treatment benefit was followed. Qualitative concept elicitation interviews conducted to understand the experiences of adults with migraine underpinned the development of the instrument. The initial stage included the development of a conceptual disease model (CDM) based on information from these interviews. This CDM was used to identify the concepts of interests (COI) to evaluate outcomes of preventive treatments. The results of the interviews were also used in stage 2, to develop a measurement framework for collecting data about these COI. In the third stage, existing instruments were reviewed for coverage of the concepts in the framework and evidence of concept elicitation to the point of saturation, to support content validity. In the fourth stage, an instrument was drafted to evaluate concepts in the framework, based on the qualitative data collected from the interviews. Following a review by clinical and translation experts, the new instrument was tested in adults with migraine in the fifth stage using 2 rounds of cognitive interviews, and was modified based on interview feedback. In the last stage, the instrument was linguistically adapted, using methods recommended for PRO instruments, to ensure conceptual equivalence of language versions for use in international studies. Each language version was tested in at least 5 native speakers using cognitive interviews.ResultsResults from the concept elicitation interviews suggested that migraine had an impact on various aspects of functioning. A conceptual framework for evaluating functional outcomes was developed for the concept selected based on a review of the CDM – physical and emotional functioning, every day activities, and social/leisure activities. Existing PROs lacked coverage of some concepts in the conceptual framework, had recall periods that were inappropriate for capturing the experience of COI or did not have evidence of content validity. A novel PRO instrument, the MFIQ, was developed to address these gaps. Cognitive interviews with 9 adults with migraine resulted in minor changes to the items of the MFIQ, and a final round of 8 interviews confirmed the changes were acceptable and supported its validity. The interviews conducted to test linguistic adaptations confirmed conceptual equivalence in the 25 countries evaluated.ConclusionsDevelopment of the MFIQ followed best measurement practices to ensure content validity and followed regulatory guidelines for PRO instruments to evaluate benefits of treatments. The MFIQ was developed for use in clinical trials or clinical practice settings to track outcomes of preventive treatments that are most relevant to adults with migraine.

"His" and "Hers": Meeting the Economic Bar to Marriage.

Scholars have suggested that low-income parents avoid marriage because they have not met the so-called economic bar to marriage. The economic bar is multidimensional, referring to a bundle of financial achievements that determine whether couples feel ready to wed. Using the Building Strong Families data set of low-income parents (n = 4,444), we operationalized this qualitative concept into a seven-item index and examined whether couples who met the economic bar by achieving the majority of the items were more likely to marry than couples who did not. Meeting the bar was associated with a two-thirds increase in marriage likelihood. The bar was not positively associated with cohabitation, suggesting that it applies specifically to marriage. When we examined different definitions of the bar based on whether the mother, father, or both parents contributed items, all variants were associated with marriage, even if the bar was based on the mother's economic accomplishments alone. When mothers contributed to the economic bar, they reported significantly higher relationship quality. Our results reinforce the importance of the multidimensional economic bar for marriage entry, highlighting the role of maternal economic contributions in low-income relationships.

Bi-Level Programming Model of Cloud Manufacturing Services Based on Extension Theory

In order to select the proper cloud manufacturing services to satisfy both sides of supplier and demander, a bi-level programming model is proposed based on extension theory in this paper. Firstly, the cloud model is employed to convert qualitative concepts of language description into quantitative values. Then, according to multicriteria assessment information, the satisfactions of both providers and demanders are calculated by extension evaluation. Finally, respectively taking satisfactions of the demanders and providers as optimization goal of upper layer and lower layer, a mathematical model of bi-level programming is constructed which is solved by linear programming. Compared with traditional recommended methods, the proposed method takes full account of the interests of service providers which have long been neglected. Moreover, extension evaluation is applied to reflect the demand and preference of each subject in detail. Experimental results verify the effectiveness and applicability of the proposed model.