Conceptual Model Research Articles

A Conceptual Model for Assessing the Risk of Unidentified Pain

Untreated or undertreated pain is well established as a significant problem, but unidentified pain is a distinct construct that still needs to be clearly modeled or fully described. This paper aims to develop a conceptual model of unidentified pain in humans with the goal of future development of an unidentified pain risk tool. A multi-phase process was employed consisting sequentially of 1) brainstorming followed by consensus building, 2) peer-review and publication of an integrative theoretical review protocol for “unidentified pain,” 3) conduct of the integrative review, and 4) a repeated brainstorming session to identify areas of risk for unidentified pain to produce a conceptual model. Brainstorming led to a consensus on “unidentified pain” as the concept of interest, followed by developing a review protocol. Twenty-four abstracts were reviewed after database searches, and four articles were included for full-text review. Three pain risk areas (hazards) were identified: cognition/communication problems, being alone or in the absence of a surrogate/proxy report, and the presence of known painful conditions or treatments and a conceptual model was developed. The hazards are posited to have the potential to both interact and be cumulative, increasing the risk for unidentified pain. There is currently no risk tool for assessing unidentified pain. The development of this conceptual model will be used for future development and psychometric testing of a tool to recognize the risk for unidentified pain in humans. PerspectiveThis focus article describes the development a conceptual model for the concept of unidentified pain in humans. This pain may occur in individuals who experience one or more interactive and cumulative hazards: cognition/communication problems, being alone, absence of a surrogate/proxy report, or presence of known painful conditions or treatments.

A Patient-Relevant Measurement Strategy to Assess Clinical Benefit of Novel Therapies for Non-metastatic Cutaneous Squamous Cell Carcinoma.

Although cutaneous squamous cell carcinoma (CSCC) is the second most common type of skin cancer, research describing the patient experience is limited. This study sought to create a conceptual model of non-metastatic disease, to assess patient-reported outcome (PRO) instruments commonly used in CSCC against this model, and to develop a patient-relevant measurement strategy for evaluating the benefit of new therapies. Researchers conducted a literature review, a review of patient blogs, and interviews with dermatologists to draft the conceptual model. A total of 22 patients with CSCC participated in 60-min phone interviews, which were subsequently transcribed, coded, and analyzed; the conceptual model was thenupdated. PRO instruments used in CSCC were assessed for content validity on the basis of this. The CSCC patient experience includes physical symptoms, psychological impacts, and behavior changes. Existing PRO instruments were assessed against the conceptual model using targeted subdomains considered to be relevant for assessing clinical benefit. Four modules of the FACE-Q® Skin Cancer instrument, plus de novo items developed for concepts not assessed by the FACE-Q® [lesion symptoms, negative treatment effects (including symptomatic), and experience of care], provide the best coverage for the concepts of interest hypothesized to show the benefit of novel treatments. This research provides a comprehensive understanding of the experience of patients with non-metastatic CSCC, and the effects of its treatment. It also identifies unmet needs in a subgroup of patients reporting negative treatment experiences. Further cognitive debriefing and psychometric analysis of de novo items are warranted for applications in clinical research.

Antecedents & After-Effects of Content Creator-Based Product Placement: Empirical Insights from Bangladesh

Purpose: The emergence of content creators in social media is a comparatively new phenomenon of interest which has rightfully attracted the digital marketers. As they have discovered a new way to connect with the audience it has inevitably led to the advent of content creator-based product placement. The study is designed to propose and test a creator product placement model uncovering the factors determining audiences’ attitude and subsequent behavioral responses. Design/Methodology: The study employed a single-cross sectional design administering a structured questionnaire-based survey on a sample of 385 respondents. A conceptual model was developed showing the hypothesized relationships among specified variables which was validated using Structural Equation Modeling. Findings: Content preference, relatability, quality, attitude toward creator, parasocial relationship, fit between content and brand and fit between creator and brand are the significant determinants of the attitude toward creator product placement. It in turn influences attitude toward brand and subsequent purchasing intention. Practical Implication: The proposed framework will aid social media marketers to formulate effective creator marketing strategies to elicit desired behavioral response from the audience. It also enriches the existing body of literature of creator marketing. Originality/Value: The study endeavors to come up with a comprehensive model to understand the behavior of the target audience toward creator product placement which is relatively unexplored and unidentified.

A novel meshless method for numerical simulation of fractured-vuggy reservoirs

This paper proposes a novel meshless numerical simulation method for fractured-vuggy reservoirs. Initially, model discretization involves extracting fracture and vug feature nodes along the contours of the reservoir bodies and in alignment with fracture orientations, tailored to the characteristics of the fractured-vuggy oil deposit. Subsequently, a connection element model is established within the influence domain. Based on the seepage equations of the connection system, a computational method for the parameters of the connection elements (connection transmissibility and connection volume) is defined. In addition, a sequential method is employed to solve for the pressure and saturation, achieving rapid prediction of the reservoir's production dynamics. On this basis, an automatic history matching algorithm is utilized for real-time fitting of oil–water dynamic indicators, inverting the characteristic parameters of the connection element model, and quantitatively characterizing the injection–production connection elements. The research findings indicate that the method is capable of rapidly fitting and predicting the dynamics of oil reservoir production. Furthermore, conceptual model examples have substantiated that it achieves comparable computational efficiency and superior computational accuracy when compared to the traditional finite difference (volume) method under the same nodal conditions. Additionally, the node arrangement for fractures and vugs is comparatively flexible, and it can ensure the integrity of the flow paths with a limited number of nodes to enhance predictive accuracy. Therefore, this method can effectively meet the rapid prediction requirements for fractured-vuggy reservoirs and also provides a novel meshless computational approach for the numerical simulation of such reservoirs.

Factors associated with Finnish, German and UK consumers' intentions to test, buy and recommend reusable fast-moving consumer goods packaging

This study investigates factors connected with consumers' intentions to test, buy and recommend reusable packaging for Fast-Moving Consumer Goods (FMCGs) by extending the Theory of Planned Behavior model with positive and negative emotions as facilitators of intentions and all behavioral determinants (i.e. attitude, subjective norm, perceived behavioral control). In addition, the connection of five perceived value dimensions (functional, emotional, social, price, environmental sustainability) and attitudes is explored. A conceptual model and relevant hypotheses were tested with consumers from Finland, Germany, and the UK (total N = 2400) through Partial Least Squares - Structural Equation Modeling (PLS-SEM). Main results show that positive emotions have a key role in consumers' assessment of reusable FMCG packaging: They have a direct and strong influence on intentions and also influence perceived behavioral control and subjective norms. Additionally, none of the examined perceived values had a significant connection with consumers' attitudes. Consumers' adoption of reusable FMCG packaging solutions can be encouraged through positive emotional experiences related to packaging reuse. Behavioral change and marketing strategies can support consumers' experiences by considering affect (e.g., positive emotions), cognition (e.g., perceived behavioral control), and social expectations (e.g., subjective norms) as influential factors.

Conceptualizing the Influence of Diversity, Equity, Inclusion, and Belonging on Professional Identity in Nursing.

Professional identity in nursing (PIN) is a multifaceted construct that evolves throughout one's nursing career. As new knowledge about PIN emerges, the influence of diversity, equity, inclusion, and belonging (DEIB) becomes increasingly vital in shaping a nurse's identity. Bronfenbrenner's ecological systems theory is used to illustrate the complex, reciprocal, and intersecting influences of DEIB in the transformational process of becoming a nurse. The authors provide an in-depth analysis of the nexus of DEIB and PIN conceptual model, examine reciprocal relationships between DEIB and the individual and collective PIN, offer a detailed case study for the application of DEIB and PIN, and make recommendations for implementing the conceptual model. The model may be used to integrate DEIB and PIN by nurses in all settings. [J Contin Educ Nurs. 2024;55(10):493-499.].

A Conceptual Model for Automation of Small Ports

Abstract For large ports and terminals, the loading and discharge operations have to a great extent been automated already. However, for the vast number of small ports, for instance all Norwegian ports, this large-scale automation is not possible due to the small size of the ports compared to the cost of introducing full automation. Still, these small ports are important logistics hubs in the transport system. They facilitate the shift from congested roads to the sea by allowing the goods to arrive closer to the final destination by using smaller, possibly autonomous, vessels. However, this puts pressure on the ports to facilitate reduced laytime in the port, to increase the port efficiency and to improve interoperability towards hinterland systems and terminals. For small ports, this means that manual and automated work processes need to exist side by side, and that it will be important to get an overview of which processes to automate and which will remain manual, in addition to the handling of the hand-over between humans and automation. This paper describes a conceptual model that can be used by small ports as a starting point on their way to introduce automation of their services supporting the cargo flow through the port. The model includes a description of port functions, tasks and responsibilities and use the concept of operational envelope to define the overall capabilities of the system, including both automation and human. This will be the starting point for how to structure the description of an operation centre that monitor and control the maritime terminal operations. The starting point for this work is a use case analysis performed in some small ports in Norway, and their need to optimize the utilization of their assets. The work is done as part of the AutoPort project which is a research project funded by the Norwegian Research Council (project number 337211). The goal of this work is to describe a methodology on how to identify the interface between automation and human operators when it comes to small ports and the movement of cargo through its terminals, and by this give a description on how different levels of automation can be implemented. The methodology consists of several steps, including definition of the context (big picture of the use case, actors and their roles, and communication), the scenario (port activities and processes), and the use cases including the control tasks performed by the automated systems.

Teleworking and Psychological Well-being:Insights and Applications for TVETInstitutions

The shift to teleworking has reshaped the work environment, introducing new dynamics and challenges. This transition is particularly relevant in the context of Technical and Vocational Education and Training (TVET), where preparing students for the evolving job market is essential.This study addresses the limited scientific analysis of how teleworking affects psychological well-being. Understanding these impacts is crucial for TVET institutions to equip students with the skills needed to thrive in remote working environments.The objectives are to identify the determinants of psychological well-being related to teleworking, analyze their impact, and propose a conceptual model linking these determinants to well-being. This study aims to fill the gap in existing research by providing concrete evidence and insights.The methodology involves a quantitative approach,using a survey questionnaire administered to 107 participants from a selected area. Data collection focuses on various factors influencing psychological well-being, and the analysis employs statistical methods to identify significant determinants and their relationships.The findings reveal key determinants of psychological well-being in teleworking, such as resilience, time management, and technology proficiency. These determinants are synthesized into a conceptual model that highlights their impacts and interconnections.The study's significance extends toTVET institutions by enhancing support services, providing mental health resources and counseling, establishing mentorship programs, and fostering partnerships with employers. These initiatives aim to better prepare students for teleworking, contributing to a healthier, more resilient workforce.

Numerical Analysis of the Influence of Preadsorbed Water on Methane Transport in Crushed Shale

Summary Methane migration in shale is affected by preadsorbed water. To understand this effect, we examined several key parameters, including the effective pore diameter Le, the pore volume distribution of Le, the effective porosity ϕe, the equivalent particle diameter da, and the water film thickness h. Using these parameters, we established an equivalent relationship linking the particle packing da and the Le and the ϕe of the capillary pores within a unit-length cuboid of particles. Based on this relationship, a conceptual model was developed to simulate methane adsorption and transport in partially saturated crushed shale, incorporating parameter estimation for the tangential momentum adjustment factor δ and methane desorption rate coefficient kd, where δ characterizes the slip flow intensity and kd is related to the Langmuir adsorption constant. The finite element method was used to calculate the methane permeability ke, Knudsen diffusion coefficient Dke, surface diffusion coefficient Ds, and adsorption phase transition rate Rm, which are all affected by adsorbed water. The model’s numerical results were validated through comparison with the results from adsorption experiments. These results revealed three distinct regions in the trend of the variation in δ with Le: a rapid increase in Region I (Le < 10 nm), a slowing increase in Region II (10 ≤ Le ≤ 100 nm), and a gradual increase in Region III (Le > 100 nm). In addition, kd is positively correlated with da. kd is also correlated with water saturation S; specifically, kd decreases when S ≤ 12%, increases when S = 12% to 45.8%, and decreases again when S exceeds 45.8%. The results also reveal overall negative correlations between h and ke, Dke, Ds and Rm. Furthermore, the rates of change in ke, Dke, Ds and Rm with increasing ε (ε is the bending coefficient associated with adsorbed water) range from 7.5% to 49.4%. Similarly, ke, Dke, and Ds increase by factors of 0.73–7.19 with increasing χ (χ is the coverage rate of the adsorbed water film). Additionally, as the adsorption time t increases, Ds initially increases rapidly, followed by a gradual increase. Between t = 500 seconds and 1,500 seconds, the rate of change in Ds decreases by 20%. Rm shows a three-stage relationship with t, namely, a rapid decrease from t = 0 seconds to 500 seconds, a steady decrease from 500 seconds to 1,000 seconds, and a stabilization from 1,000 seconds to 1,500 seconds, with Rm ranging from 1.10×10-11 mol/(m3·s) to 9.45×10-11 mol/(m3·s) overall. Ds increases with the adsorption amount ratio Ed (Ed is the ratio of the adsorption amount at t to the equilibrium adsorption amount). As Ed ranges from 0.2 to 0.6, the rate of change in Ds increases by 87% to 100%. Furthermore, Rm is negatively linearly correlated with Ed.

Patterns of spatiotemporal variations in the hydrochemistry and controlling factors of bedrock aquifers in the northern region of the Linhuan mining area

Systematically studying the hydrochemical evolution of bedrock groundwater in mining areas during mining process is crucial for effective groundwater resource management and coal mine production. The spatiotemporal characteristics and hydrochemical evolution patterns of the Permian fractured sandstone aquifer (PA) and the Carboniferous Taiyuan Formation limestone aquifer (CTA), both of which are directly associated with coal mining in the northern Linhuan mining area, China, were investigated using multivariate statistical analyses, hydrochemical graphical methods, ion ratio analysis, and a conceptual model. 72 groundwater samples, collected before and after mining, were classified into four groups by hierarchical cluster analysis (HCA). Principal component analysis (PCA) and ion ratio analysis indicated that water-rock interactions involve mineral dissolution (carbonates, gypsum, dolomite, silicates), cation exchange, and common ion effects. Hydrochemical evolution is influenced by bedrock paleotopography, aquifer hydraulic conductivity, and mining drainage. Paletopographic differences significantly influence water-rock interactions and spatial variability in hydrochemistry, with ion concentrations in groundwater increasing as paleotopographic elevation decreases. The pattern of hydraulic conductivity reflects the control exerted by variations in aquifer characteristics on mineral dissolution, leading to minor changes in hydrochemical characteristics. Mining activities disrupt the aquifer's reducing environment, resulting in a significant increase in groundwater SO42− concentration. These findings provide insights and a solid theoretical foundation for studying the hydrochemical variations patterns of groundwater and these control mechanisms in the hidden coal fields of North China.

Success Factors for Conceptual Digital Voting Model

With the advancement of technology in the digital age, blockchain technology has evolved into a technology critical to delivering secure and reliable decentralized applications. An application that has brought blockchain technology is elections to close the gap in traditional elections for transparency and credibility However, in COVID-19, bringing this technology to change elections allows access to all citizens to be able to vote. This research uses a structural equation model (SEM) questionnaire to explore the success factors of election implementation using blockchain technology was analysed from 400 voters who responded to the questionnaire using Mplus Version 7. This research has prepared a conceptual model supporting the effecting factors in implementing an election system using blockchain technology with voters The researcher has created an electoral system using blockchain technology that is readily available. Technology acceptance factor and credibility were utilized from the voters’ point of view in 9 Factors. Those interested in applying the model to improve elections using blockchain technology can study to improve elections. In addition, Conceptual model ideas were used to develop a model for acceptance and trust in elections using blockchain technology.

A study of the impact of urban spaces on social resilience in case of natural disasters: Insights from citizens affected by March 2019 flood in Aq Qala City, Iran

The number of urban crises has been notably on the rise all around the globe during the past few decades due to shifts in ecological cycles and social challenges, among other reasons. These crises have had a more pronounced impact on urban areas, which are more vulnerable. The various aspects of resilience have become the focal points in sustainable development research and other related studies, and some solutions have been proposed within the concepts and framework of sustainable development for countering these crises, among which urban resilience is more prominent owing to its inherent functional principles. Among the various aspects of resilience, social resilience is linked to the social capacities of urban regions. A review of the related literature reveals the shortage of studies about the relationship between urban spaces and social resilience. This study aims to uncover the mechanisms through which urban spaces influence social resilience following natural disasters through the perceptions of the citizens affected by the March 2019 flood in Aq Qala, Golestan Province, Iran. To achieve this, we first developed a conceptual model grounded in a review of relevant theoretical literature. Subsequently, a structured 5-point scale questionnaire was designed and distributed for data collection. The collected data was then subjected to structural equation modeling to analyze the conceptual model. The findings highlight the critical factors in forming social resilience from the perspective of Aq Qala residents, with a specific emphasis on city structure, activity, social capital, and social cohesion as integral components.

Artificial Intelligence in Human Growth and Development: Applications Through the Lifespan

Artificial intelligence (AI) applications influence human growth and development across the lifespan. This article provides a conceptual model that shows significant AI applications and their influence from prenatal to maturity using Erikson's psychosocial stages as a framework. AI influences development through diverse avenues, encompassing diagnosis, attachment formation, social skill acquisition, relationship dynamics, and caregiver support. The effects of AI interventions can be perceived as advantageous, contentious, and as raising a multitude of ethical considerations. Consequently, we propose avenues for future research endeavors to further investigate the intersection of AI and human growth and development within counseling contexts.

Mapping out Remediation: An Actionable Roadmap to Support Trainees Through Remediation

What’s NewThis qualitative analysis offers an actionable, stepwise approach to remediation. IntroductionThe goal of graduate medical education is for trainees to develop the competence needed to practice independently; however, some residents struggle to achieve competency and require remediation. Evidence around how to best facilitate remediation is lacking. The objective of this study was to understand best practices for remediation in pediatrics. MethodA national web-based survey of pediatric residency program directors (PDs) on remediation practices was performed. The survey included 3 open-ended questions about PDs’ experiences with remediation. Self-reported barriers to and strategies for remediation were systematically analyzed using inductive thematic analysis to develop a theory of effective remediation in pediatric residency training. ResultsA total of 99 out of 195 (50.8%) program directors responded. Two main themes emerged: developing a personalized plan that ensures competency attainment and fostering psychological safety. Twelve categories outline actionable steps that PDs can take to make the remediation process successful. DiscussionBuilt from insight from pediatric PDs, we propose a conceptual model for effective remediation that accounts for competency attainment while safeguarding the emotional health of the resident. The conceptual model breaks the remediation process down into four phases: identification of the learner who struggles, planning the remediation process, implementation of the plan, and assessing the outcome of the process.

Interprofessional Management of (Risk of) Malnutrition and Sarcopenia: A Grounded Theory Study from the Perspective of Professionals.

As our global population ages, malnutrition and sarcopenia are increasingly prevalent. Given the multifactorial nature of these conditions, effective management of (risk of) malnutrition and sarcopenia necessitates interprofessional collaboration (IPC). This study aimed to understand primary and social care professionals' barriers, facilitators, preferences, and needs regarding interprofessional management of (risk of) malnutrition and sarcopenia in community-dwelling older adults. We conducted a qualitative, Straussian, grounded theory study. We collected data using online semi-structured focus group interviews. A grounded theory data analysis was performed using open, axial, and selective coding, followed by developing a conceptual model. We conducted five online focus groups with 28 professionals from the primary and social care setting. We identified five selective codes: 1) Information exchange between professionals must be smooth, 2) Regular consultation on the tasks, responsibilities, and extent of IPC is needed; 3) Thorough involvement of older adults in IPC is preferred; 4) Coordination of interprofessional care around the older adult is needed; and 5) IPC must move beyond healthcare systems. Our conceptual model illustrates three interconnected dimensions in interprofessional collaboration: professionals, infrastructure, and older adults. Based on insights from professionals, interprofessional collaboration requires synergy between professionals, infrastructure, and older adults. Professionals need both infrastructure elements and the engagement of older adults for successful interprofessional collaboration.

Application of a Conceptual Stocking Model for Two Recreationally Important Species

ABSTRACTFish stocking continues to be an important and often‐used tool in fisheries management. Mortality of fish may be high in the first few days after stocking due to predation and a lack of appropriate food and habitat. The objective of this study was to develop a conceptual model that may identify stocking locations that can help improve the survival of stocked fish. We identified three factors—predator risk, zooplankton (food) availability and measures of habitat that could be important to the survival of stocked Walleye (Sander vitreus) and White Bass (Morone chrysops) fingerlings in Lake McConaughy, Nebraska. The spatial distribution of these factors was used to create a predictive surface to identify those stocking locations hypothesised to lead to higher survival. Final stocking maps identified the best 12.8% and 13.9% of the predicted area of Lake McConaughy for stocking Walleye and White Bass, respectively. Both maps predicted that the best locations were along the south‐central shoreline of Lake McConaughy. The maps for both species were interestingly similar. These results are likely due to the similarities in predators consuming the stocked species and the zooplankton consumed by fingerlings of both species. Habitat availability may be less important, or other aspects of habitat may need to be considered. Identifying the best locations for stocking based on predation risk and the availability of food and habitat could increase the survival of stocked fishes and help managers reach population objectives.

Conceptual Business Model Framework for AI-based Private 5G-IoT Networks

Conceptual Business Model Framework for AI-based Private 5G-IoT Networks

Sustainable urban water management index for developing countries. A case study in Puebla City, Mexico

Several indicator and index frameworks have been reported to assess management efficiency and promote transparency, facilitating decision-making and innovation. However, they cannot be applied in cities with limited information, making them impractical. This study proposes a Sustainable Urban Water Management Index (SUWMI) for such cities, selecting six AquaRating indicators plus two indexes recommended in the Sustainable Development Goal 6, yielding a simplified and practical version for diagnosing the management performance rate of the Water Operating Systems (WOS) in cities. Conceptual and mathematical models were defined for SUWMI, and the eight selected terms were hierarchized based on a decision tree with the participation of an expert panel and further multicriteria decision-making methodology by the Analytic Hierarchy Process (AHP) to calculate the weighting parameters. The selected indicators represent five categories on a percentage scale. The highly populated Puebla City Metropolitan Zone in Mexico was the case study. Information was gathered from five Water Operation Systems (WOS) from 2002 to 2020. The tap water area's coverage and physical efficiency improved despite the population growth due to an adequate political strategy after 2014. The SUWMI values of each WOS diagnoses its performance, highlighting their differences and providing a valuable tool for guiding urban water public policy programs. The paper proposes a simple, fast, and easy-to-calculate index that can be helpful for a broader cluster of cities and urban settlements with deficient available information, which is common in developing countries.

Conceptual design model of engaging gamification mechanic for online courses

Conceptual design model of engaging gamification mechanic for online courses

What helps Agile remote teams to be successful in developing software? Empirical evidence

Software development firms have specific goals but today's dynamic business environment, especially regarding the use of remote teams, presents great challenges due to uncertainties and multiple risks. This study investigates the facilitators of the success of Agile software development projects delivered by remote teams. We employ a conceptual research model founded on the technology-organization-environment (TOE) framework. The study contributes to the literature by exploring how remote teams affect the success of Agile software development projects. Partial least squares structural equation modeling (PLS-SEM) analysis of the data collected from 198 IT professionals revealed that perceived pressure from government, job performance, and team satisfaction are significant in explaining these projects’ success.