Model Theory Research Articles

Behavioral responses resulting from e-health services and the role of user satisfaction: the case of the online diabetes test

Purpose The advancement of technologies has made it possible for health-care organizations to provide convenient online services that enable people to manage their health conditions. Although many studies have investigated the adoption and benefits of e-health services, there has been little focus on health-oriented behaviors after adoption, particularly in relation to service quality and user satisfaction. Design/methodology/approach This paper is based on the SOR model and service quality theories to investigate behavioral responses, including word-of-mouth, intention to use and intention to act. The authors use a partial least squares structural equation modeling analysis with 194 participants and the diabetes risk test survey in Finland. Findings The results show that people are willing to engage in health self-management behaviors if they intend to use the e-health service and are satisfied with it. User satisfaction can be enhanced by improving the visual appeal of the website presentation, the quality of the presented information, as well as the usability of the website, all as components of e-health services. Originality/value The authors contribute by creating a construct “intention to act,” referring to health-oriented behaviors resulting from e-health service use. In addition, this study is among the first to apply the SOR model to investigate how user satisfaction leads to intention to use, intention to act and word-of-mouth.

Characterization of the Edge States in Colloidal Bi2Se3 Platelets.

The remarkable development of colloidal nanocrystals with controlled dimensions and surface chemistry has resulted in vast optoelectronic applications. But can they also form a platform for quantum materials, in which electronic coherence is key? Here, we use colloidal, two-dimensional Bi2Se3 crystals, with precise and uniform thickness and finite lateral dimensions in the 100 nm range, to study the evolution of a topological insulator from three to two dimensions. For a thickness of 4-6 quintuple layers, scanning tunneling spectroscopy shows an 8 nm wide, nonscattering state encircling the platelet. We discuss the nature of this edge state with a low-energy continuum model and ab initio GW-Tight Binding theory. Our results also provide an indication of the maximum density of such states on a device.

Adverse childhood experiences among black sexually minoritized men and Black transgender women in Chicago.

Adverse childhood experiences (ACE) are important predictors of mental health outcomes in adulthood. However, commonly used ACE measures such as the Behavioural Risk Factor Surveillance System (BRFSS) have not been validated among Black sexually minoritized men (SMM) nor transgender women (TW), whom are known to have higher rates of ACE and poorer mental health outcomes. Assessing the psychometric properties of the measure is important for health equity research, as measurements that are not valid for some populations will render uninterpretable results. Data are drawn from the Neighborhoods and Networks (N2) study, a longitudinal cohort of Black SMM and TW living in Southern Chicago. We conducted confirmatory factor analysis, correlation analysis and a two-parameter Item Response Theory (IRT) on the BRFSS ACE measure, an 11-item measure with 8 domains of ACE. One hundred forty seven participants (85% cisgender male) completed the BRFSS ACE measurement in the N2 study with age ranges from 16-34. The cohort were from a low socioeconomic background: about 40% of the cohort were housing insecure and made than $10,000 or less annually. They also have a high number of ACEs; 34% had endorsed 4 or more ACE domains. The three-factor structure fit the BRFSS ACE measure best; the measurement consisted of three subscales: of "Household Dysfunction", "Emotional / Physical", and "Sexual Abuse" (CFI = 0.975, TLI = 0.967, and RMSEA = 0.051). When the 8 domains of ACE were summed to one score, the total score was is correlated with depressive symptoms and anxiety scores, establishing concurrent validity. Item Response Theory model indicated that the "parental separation" domain had a low discrimination (slope) parameter, suggesting that this domain does not distinguish well between those with and without high ACE. The BRFFS ACE measure had adequate reliability, a well-replicated structure and some moderate evidence of concurrent validity among Black SMM and TW. The parental separation domain does not discriminate between those with high and low ACE experiences in this population. With changing population demographics and trends in marriage, further examination of this item beyond the current study is warranted to improve health equity research for all.

Quantitative Research on “Blockchain+Supply Chain” Financing Based on Game Theory Modeling

In the 21st century, with globalization and the “Belt and Road” economic activities. As an important financial means, supply chain financing plays a key role in trade transactions between enterprises. Supply chain financing refers to providing financial support and services to different participants in the entire supply chain through financial instruments to meet the financial needs of their production and trade activities. To address the issue of “blockchain+supply chain” financing, specifically in the traditional supply chain, the downstream of the SMEs financing difficulties has been one of the factors plaguing its development. Still, also one of the constraints on the overall supply chain operational efficiency, we use the principles of game theory to establish a game theory model between financial institutions and SMEs and use Matlab software to solve the simulation data. We use the principle of game theory to establish a game theory model between financial institutions and MSMEs, use Matlab software to solve the simulation data and analyze the financial institutions to adopt the “blockchain+supply chain” financing strategy, and MSMEs to adopt the trustworthy strategy so that the two sides can maximize the benefits, and also maximize the benefits for the whole supply side. In addition, the research process and results can provide references for relevant state departments and various social enterprises and organizations.

Research on the cognitive neural mechanism of privacy empowerment illusion cues regarding comprehensibility and interpretability for privacy disclosures.

In the era of artificial intelligence, privacy empowerment illusion has become a crucial means for digital enterprises and platforms to "manipulate" users and create an illusion of control. This topic has also become an urgent and pressing concern for current research. However, the existing studies are limited in terms of their perspectives and methodologies, making it challenging to fully explain why users express concerns about privacy empowerment illusion but repeatedly disclose their personal information. This study combines the associative-propositional evaluation model (APE) and cognitive load theory, using event-related potential (ERP) technology to investigate the underlying mechanisms of how the comprehensibility and interpretability of privacy empowerment illusion cues affect users' immediate attitudes and privacy disclosure behaviours; these mechanisms are mediated by psychological processing and cognitive load differences. Behavioural research results indicate that in the context of privacy empowerment illusion cues with low comprehensibility, users are more inclined to disclose their private information when faced with high interpretability than they are when faced with low interpretability. EEG results show that in the context of privacy empowerment illusion cues with low comprehensibility, high interpretability induces greater P2 amplitudes than does low interpretability; low interpretability induces greater N2 amplitudes than does high interpretability. This study extends the scopes of the APE model and cognitive load theory in the field of privacy research, providing new insights into privacy attitudes. Doing so offers a valuable framework through which digital enterprises can gain a deeper understanding of users' genuine privacy attitudes and immediate reactions under privacy empowerment illusion situations. This understanding can help increase user privacy protection and improve their overall online experience, making it highly relevant and beneficial.

Multiple salary comparisons, distributive justice, and employee withdrawal.

Salary comparison has well-established implications for employees' attitudes and behaviors at work. Yet how employees process information about simultaneous comparisons, particularly when internal and external comparison information is incongruent, remains controversial. In this article, we draw from the model of dispositional attribution and equity theory to predict how the incongruence of internal and external salary comparisons affects perceptions of distributive justice and subsequent employee withdrawal behavior. We hypothesized that the effect of salary comparisons on perceived distributive justice follows a hierarchically restrictive schema in which a lower salary in comparison to a referent has a greater effect than a higher salary. This further affects employee withdrawal (neglect, turnover intention, and voluntary turnover). We also propose that the effects of salary comparisons are bounded by employees' zero-sum construal of success. Three studies were conducted to test our hypotheses: a quasi-experimental study and two time-lagged field studies. Consistent with our hypotheses, we observed that, when comparison information was incongruent, underpayment compared with others more strongly affected perceived distributive justice than overpayment did. The subsequent impact on perceived distributive justice was negatively related to employee withdrawal. As expected, the effect of incongruent salary comparison information was stronger for employees with lower zero-sum construal of success. The theoretical and practical implications of these findings are discussed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Trade-off relations of quantum resource theory in Heisenberg models

Studying the relations between entanglement and coherence is essential in many quantum information applications. For this, we consider the concurrence, intrinsic concurrence and first-order coherence, and evaluate the proposed trade-off relations between them. In particular, we study the temporal evolution of a general two-qubit XYZ Heisenberg model with asymmetric spin-orbit interaction under decoherence and analyze the trade-off relations of quantum resource theory. For XYZ Heisenberg model, we confirm that the trade-off relation between intrinsic concurrence and first-order coherence holds. Furthermore, we show that the lower bound of intrinsic concurrence is universally valid, but the upper bound is generally not. These relations in Heisenberg models can provide a way to explore how quantum resources are distributed in spins, which may inspire future applications in quantum information processing.

How does green consumers' self‐concept promote willingness to pay more? A sequential mediation effect of green product virtue and green perceived value

AbstractThis study investigates the consumers' processing route of WTPM for green products from consumers' self‐concepts. Employing the norm activation model and Lazarus appraisal theory, this study proposes the direct and indirect routes of self‐concepts (i.e., green and product self‐concepts) that influence consumers' WTPM. The causal chain of green product virtue and green perceived value is explored. Online survey data for 313 Indian green consumers inform the findings. The findings reveal that consumers' product self‐concept and green self‐concept influence their WTPM through green product virtue and green perceived value. Such findings support the sequential mediation effect. This study provides an alternative and novel psychological mechanism for how consumers' self‐concepts can influence WTPM through green product virtue and green perceived value. The findings inform green marketers to use green product virtue and green perceived value to induce green consumers' WTPM while designing effective segmentation and communication strategies.

Linear mixed-effects models and least confounded residuals in the modelling of Holstein calves’ performance

Some experimental studies are carried out considering a longitudinal feature. In view of this, the classical regression models are not able to handle with it, since the independence assumption between the observations is violated. To handle with this kind of data it was proposed the called linear mixed-effects models, where it is possible to model the response variable taking into account the correlation between the observations, and even between the response variables, when there are two or more of them in study, setting a bivariate or multivariate scenario, respectively. For the diagnosis of the linear mixed-effects models the least confounded residuals are quite recommended due to their lower bias in relation to other types of residuals, but it is not so used in the literature. Using a data set of dairy calves’ performance according to three different diets over eight weeks, the linear mixed-effects models theory under univariate and bivariate approach was applied alongside the least confounded residuals in the diagnosis of the model for both approaches. Comparing the univariate and bivariate approaches, the last one was more informative presenting lower standard errors’ values for its estimates, while the least confounded residuals was more efficient than the classical residuals present in the literature.

Multifactor synergistic influence of data intelligence on consumer mobile shopping

AbstractData intelligence (DI) is constantly influencing consumers. According to the theory of environmental psychology model, when consumers are stimulated by enterprise DI in mobile shopping, they can easily transform emotional reactions into corresponding behaviors. Based on this theory, this research adopts a hybrid method combining qualitative interview and fuzzy set qualitative comparative analysis (fsQCA) to explore the multifactor synergistic effects of DI factors on consumer emotions and mobile shopping intentions. Study 1 extracts five DI factors through qualitative study using NVivo software. All but one of the five DI factors had strong effects on consumer emotions. Study 2 uses the fsQCA method to analyze large‐sample survey data, revealing four configurations of DI factors that trigger positive consumer emotions and three that trigger mobile shopping intentions. The presence of intelligent search, intelligent recommendations, and intelligent logistics are the core conditions that trigger positive consumer emotions and mobile shopping intentions, while the presence or absence of intelligent customer service and intelligent pricing trigger positive consumer emotions and mobile shopping intentions. The research results supplement the existing theories and provide practical guidance for enterprises in DI stimulus design and government in DI environment construction.

Simples in a cotilting heart

Every cotilting module over a ring R induces a t-structure with a Grothendieck heart in the derived category D(Mod-R). We determine the simple objects in this heart and their injective envelopes, combining torsion-theoretic aspects with methods from the model theory of modules and Auslander-Reiten theory.

The spectral form of the functional model for maximally dissipative operators: A Lagrange identity approach

This paper is a contribution to the theory of functional models. In particular, it develops the so-called spectral form of the functional model where the selfadjoint dilation of the operator is represented as the operator of multiplication by an independent variable in some auxiliary vector-valued function space. With the help of a Lagrange identity, in the present version the relationship between this auxiliary space and the original Hilbert space will be explicit. A simple example is provided.

Climate Change Awareness and Pro-Environmental Intentions in Sports Fans: Applying the Extended Theory of Planned Behavior Model for Sustainable Spectating

(1) Background: This study explores the intricate relationship between sports and the environment, underscoring the influence of individual awareness of climate change consequences on fostering eco-friendly behavior among sports spectators. (2) Methods: The research introduces an extended theory of planned behavior model, incorporating climate change awareness. Analyzing data from 431 participants at US professional sports events, the study measured variables like climate change awareness and theory of planned behavior constructs. (3) Results: Sequential multiple mediation analysis validated the model, revealing that climate change awareness positively predicts the intention to reduce single-use plastics in the context of sport spectatorship. This relationship was partially mediated by theory of planned behavior variables, with subjective norms identified as a crucial explanatory factor. (4) Conclusions: The study’s originality lies in shedding light on pro-environmental intentions within sports spectatorship. Its insights provide foundational knowledge for researchers and organizations aiming to devise sustainability strategies in the realm of sports.

A neural network paradigm for modeling psychometric data and estimating IRT model parameters: Cross estimation network.

This paper presents a novel approach known as the cross estimation network (CEN) for fitting the datasets obtained from psychological or educational tests and estimating the parameters of item response theory (IRT) models. The CEN is comprised of two subnetworks: the person network (PN) and the item network (IN). The PN processes the response pattern of individual respondent and generates an estimate of the underlying ability, while the IN takes in the response pattern of individual item and outputs the estimates of the item parameters. Four simulation studies and an empirical study were comprehensively and rigorously conducted to investigate the performance of CEN on parameter estimation of the two-parameter logistic model under various testing scenarios. Results showed that CEN effectively fit the training data and produced accurate estimates of both person and item parameters. The trained PN and IN adhered to AI principles and acted as intelligent agents, delivering commendable evaluations for even unseen patterns of new respondents and items.

Psychometric properties and item response theory analysis of the Persian version of the social pain questionnaire

IntroductionSocial pain is an emotional reaction which is triggered by social exclusion and has been extensively investigated in the literature. The Social Pain Questionnaire (SPQ) is a self-report instrument which is the only scale for measuring social pain as a dispositional factor. The current study aimed at examining the psychometric properties of the SPQ in an Iranian sample.Materials and methodsA sample of participants (N = 400) was recruited in a cross-sectional validation study. Exploratory Factor Analysis (EFA) as well as Confirmatory Factor Analysis (CFA) were conducted. The Item Response Theory (IRT) model parameters were evaluated and item response category curves were presented. Convergent and divergent validities as well as the reliability (by using Cronbach’s alpha coefficient) were also assessed.ResultsThe SPQ’s unidimensionality was affirmed (RMSEA = 0.078; CFI = 0.915; TLI = 0.99) and its internal consistency was robust (Cronbach’s α = 0.94). The correlation between the SPQ and the following measures endorsed its divergent and convergent validity: Self-esteem (r = −0.424), Perceived Social Support (r = −0.161), and Interpersonal Sensitivity (r = 0.636). Finally, Item Response Theory Analysis emphasized the effectiveness of the SPQ items in discerning various levels of social pain. The theta level ranged between −1 and + 1.2 and the IRT-based marginal reliability was 0.92 for the total score.DiscussionThe Persian SPQ stands as a reliable and valid measure for evaluating social pain. This scale has the potential to stimulate further research in the field for both clinical and non-clinical settings.ConclusionBy employing Item Response Theory (IRT) analysis, we have transcended the theoretical psychometric evaluation of the SPQ scale and demonstrated that SPQ is a unidimensional, valid and reliable measurement tool.

Promoting a Patient-Centered Understanding of Safety in Acute Mental Health Wards: A User-Centered Design Approach to Develop a Real-Time Digital Monitoring Tool.

Acute mental health services report high levels of safety incidents that involve both patients and staff. The potential for patients to be involved in interventions to improve safety within a mental health setting is acknowledged, and there is a need for interventions that proactively seek the patient perspective of safety. Digital technologies may offer opportunities to address this need. This research sought to design and develop a digital real-time monitoring tool (WardSonar) to collect and collate daily information from patients in acute mental health wards about their perceptions of safety. We present the design and development process and underpinning logic model and programme theory. The first stage involved a synthesis of the findings from a systematic review and evidence scan, interviews with patients (n=8) and health professionals (n=17), and stakeholder engagement. Cycles of design activities and discussion followed with patients, staff, and stakeholder groups, to design and develop the prototype tool. We drew on patient safety theory and the concepts of contagion and milieu. The data synthesis, design, and development process resulted in three prototype components of the digital monitoring tool (WardSonar): (1) a patient recording interface that asks patients to input their perceptions into a tablet computer, to assess how the ward feels and whether the direction is changing, that is, "getting worse" or "getting better"; (2) a staff dashboard and functionality to interrogate the data at different levels; and (3) a public-facing ward interface. The technology is available as open-source code. Recent patient safety policy and research priorities encourage innovative approaches to measuring and monitoring safety. We developed a digital real-time monitoring tool to collect information from patients in acute mental health wards about perceived safety, to support staff to respond and intervene to changes in the clinical environment more proactively.

Exploring the Strategic Use of TikTok for Clinical Trial Recruitment: How audiences’ Prior Short-Form Video Usage Influences Persuasive Effects

Guided by the elaboration likelihood model and framing theory, this study explores the potential of short-form video platforms (e.g. TikTok), for targeted clinical trial recruitment. An online experiment compared doctor vs. peer-led videos addressing logistical or psychological barriers to participation, mimicking common TikTok communication tactics. Results indicate that high (vs. low) TikTok users are more persuaded by recruitment messages, and they exhibit stronger intentions to participate in clinical trials. Although doctor-sourced messages generate greater credibility and a more favorable message attitude, peer-sourced messages may be more effective in increasing participation intention. Lastly, doctor-sourced videos that address logistical barriers and peer-sourced videos that discuss psychological barriers result in higher self-efficacy for clinical trial participation. This study contributes to the growing body of research on new media’s role in health communication and provides insights into how to strategically utilize TikTok and other short-form video platforms for clinical trial recruitment.

Measuring the variability of personality traits with interval responses: Psychometric properties of the dual-range slider response format : Measuring variability with interval responses.

Measuring the variability in persons' behaviors and experiences using ecological momentary assessment is time-consuming and costly. We investigate whether interval responses provided through a dual-range slider (DRS) response format can be used as a simple and efficient alternative: Respondents indicate variability in their behavior in a retrospective rating by choosing a lower and an upper bound on a continuous, bounded scale. We investigate the psychometric properties of this response format as a prerequisite for further validation. First, we assess the test-retest reliability of factor-score estimates for the width of DRS intervals. Second, we test whether factor-score estimates of the visual analog scale (VAS) and the location of DRS intervals show convergent validity. Third, we investigate whether factor-score estimates for the DRS are uncorrelated between different personality scales. We present a longitudinal multitrait-multimethod study using two personality scales (Extraversion, Conscientiousness) and two response formats (VAS, DRS) at two measurement occasions (6-8weeks apart) for which we estimate factor-score correlations in a joint item response theory model. The test-retest reliability of the width of DRS intervals was high ( ). Also, convergent validity between location scores of VAS and DRS was high ( ). Conversely, discriminant validity of the width of DRS intervals between Extraversion and Conscientiousness was poor ( ). In conclusion, the DRS seems to be a reliable response format that could be used to measure the central tendency of a trait equivalently to the VAS. However, it might not be well suited for measuring intra-individual variability in personality traits.

The collective wisdom of behavioral game theory

AbstractWe apply an algorithm from the wisdom-of-crowds literature to optimally combine behavioral game theory models to more accurately predict strategic choice in one-shot, simultaneous-move games. We find that the optimal weighted average of seven behavioral game theory models predicts out-of-sample choice behavior significantly better than any of the individual models. The crowd of behavioral game theory models is wiser than any single one of them. Different strategic choice models complement each other by capturing distinct patterns of behavior. The field of behavioral game theory is enriched by having this diversity of models.

A novel train–bridge interaction computational framework based on a meshless box girder model

In traditional train–bridge coupled system (TBCS), simply supported box girder bridges are often modeled using Euler beam elements, neglecting their spatial structure. This simplification may yield inaccurate results, impacting the running safety analysis of high-speed railway. To address this issue, a novel train–bridge interaction computational framework based on first-order shear deformation theory (FSDT) and radial point interpolation method (RPIM) for the box girder bridge model is proposed. In this model, the displacement fields of top, bottom, and web plates are represented using FSDT and numerically discretized by RPIM. The traditional TBCS is upgraded by replacing the Euler beam model with the novel model. This is the first time that the framework has been applied to TBCS field. Several numerical examples are presented to highlight the accuracy of this novel model, and illustrate the differences, and advantages of it over the traditional model. The results indicate that the proposed model closely matches the accuracy of the solid element (C3D20) model; it can provide a comprehensive bridge response compared to traditional TBCS, and the latter may underestimate the dynamic response of the structure. The proposed model holds significant potential for the simulation of box structures and widespread application in the field of TBCS.