Research Tool Research Articles

Efficacy of antipsychotics in delusional infestation.

Data remain scarce for the first-line antipsychotic choice in treating delusional infestation (DI). We evaluated the treatment responses associated with different antipsychotics in DI patients. We undertook a multicentre, retrospective observational study using anonymised electronic patient records from two hospitals in the United Kingdom from 1 January 2011 to 1 January 2023. Eligible participants were adults (≥18 years) diagnosed with DI treated with an antipsychotic, and had both an assigned baseline and follow-up Clinical Global Impression Scale (CGI-S) score. The CGI-S is a validated psychiatric research tool. Participants were excluded if they had known limited or non-adherence to an antipsychotic, or if no CGI-S scores were present at follow-up. First clinic visits before the initiation of an antipsychotic were assigned as the baseline CGI-S score. The last available CGI-S score before the patient either changed antipsychotic or left the clinic for any reason was used to assign follow-up CGI-S scores. The primary outcome was the response to each individual antipsychotic treatment, measured by the difference in the baseline and last available follow-up CGI-S scores. Differences in CGI-S changes between antipsychotic episodes were tested by analysis of variance (ANOVA). In total, 414 patient records were analysed, and data were extracted. The mean age was 61.8 years (SD 14.1). One hundred seventy (41%) of 414 patients were men and 244 (59%) were women. In total, 156 (38%) of 414 patients were eligible, yielding a total of 315 antipsychotic prescribing episodes. The ANOVA, ranking in order of treatment response, showed that the highest mean score (expressing highest treatment response) was observed in amisulpride (31 [67%] of 46) and risperidone (95 [57%] of 167), followed by some distance by quetiapine (9 [36%] of 25), aripiprazole (13 [28%] of 46) and olanzapine (7 [25%] of 28). Amisulpride and risperidone were associated with a higher treatment response than quetiapine, aripiprazole and olanzapine. Amisulpride and risperidone should therefore be considered the first-line treatment options in DI patients.

Bio2Py: An API for integrating Python with BioWin for enhanced data acquisition in wastewater treatment simulations

Commercial simulators for modeling wastewater treatment processes (WWTPs), such as BioWin, play a crucial role for optimizing the design, operation, and control of treatment facilities. These simulators offer fast and user-friendly interfaces and can be employed to enhance the efficiency of wastewater treatment plants. However, a notable limitation of BioWin and similar platforms is the lack of direct integration with Python®, a programming language renowned for its versatility and extensive data analysis and machine learning libraries. Bridging this gap constitutes an opportunity to significantly improve the simulation process by leveraging Python's capabilities. The Python package Bio2Py (BioWin to Python) is presented as a compelling solution, reconciling BioWin's specialized functionality and Python's automation and data processing strengths. By utilizing Python's PyAutoGUI package, Bio2Py automates various aspects of the simulation process, such as loading influent data, running simulations, and saving simulation results without manual intervention. The integration of BioWin with Python not only speeds up the workflow by automating repetitive tasks but also opens new possibilities, such as parameter calibration for specific wastewaters and using BioWin as a data generator for machine learning applications. This brief communication presents the Bio2Py API, illustrating its use and applicability through a simple implementation example. Bio2Py's ability to automate and optimize various aspects of wastewater treatment process simulation, including data acquisition, and its potential use for process variable optimization and parameter tuning, positions it as a valuable tool for engineers and researchers who work in this field.

The Intergenerational Program Evaluation Tool: Results of a Delphi Study

ABSTRACT Intergenerational programs innovate constantly, but tools to evaluate them lag. Measures vary across programs and usually concentrate on outcomes without attending to programming dimensions that could influence results. Such features limit generalizability and comprehension of the mechanisms by which intergenerational programs achieve their objectives. Building on theory and evidence, we developed an evaluation tool for practitioners and researchers to use as a standalone evaluation tool or in conjunction with other measures. The current paper presents results of a Delphi study used to refine the Intergenerational Program Evaluation Tool (IPET) and establish its face and content validity. Results reinforce preexisting scholarship identifying the IPET as a reliable, valid tool that will help intergenerational scholars promote evidence-based practices and assess their impact on varied goals pursued through shared programming. We describe potential uses of the tool and next steps to advance its adoption through implementation research and psychometric assessment.

The meaning landscape of the concept of the total derivative in multivariable real analysis textbooks: an analysis based on a new model of meaning

AbstractIn this paper, we propose a novel conceptual framework tailored for modeling the meaning of mathematical concepts in university-level mathematics, addressing their rigorous nature and their relationships with related concepts as well as interpretations in various contexts. Within this framework, we present a model of meaning for the concepts of total differentiability and total derivative that provides a variety of possible interpretations and aspects. We then use the proposed model of meaning as a tool for analyzing three different textbooks for mathematics majors on the topic of multidimensional differentiability. Our paper is an example of a subject matter analysis of a topic in university mathematics carried out in a structured way. The model of meaning for total differentiability presented in this paper could inspire course design and analysis including the design of assignments and assessments for students. Moreover, it could serve as a valuable research tool for further analyses. For example, it could be used as a framework for analyzing courses taught or as a basis for developing a test instrument to assess students’ understanding. With our textbook analysis, we begin to examine the landscape of textbooks regarding differentiability concepts in the multidimensional case, shedding light on the diversity of meaning facets that are covered in the textbooks. These results could be useful for guiding instructors and learners in selecting and using textbooks for teaching and learning based on their respective needs.

Can Generative AI improve social science?

Generative AI that can produce realistic text, images, and other human-like outputs is currently transforming many different industries. Yet it is not yet known how such tools might influence social science research. I argue Generative AI has the potential to improve survey research, online experiments, automated content analyses, agent-based models, and other techniques commonly used to study human behavior. In the second section of this article, I discuss the many limitations of Generative AI. I examine how bias in the data used to train these tools can negatively impact social science research—as well as a range of other challenges related to ethics, replication, environmental impact, and the proliferation of low-quality research. I conclude by arguing that social scientists can address many of these limitations by creating open-source infrastructure for research on human behavior. Such infrastructure is not only necessary to ensure broad access to high-quality research tools, I argue, but also because the progress of AI will require deeper understanding of the social forces that guide human behavior.

The Role of AI in Management

This study investigates "The Role of AI in Management" and aims to understand the impact of AI technologies on various management practices within organizations. The problem of the study arises from the increasing adoption of AI in the business world and the need to comprehend its implications for managerial decision-making, organizational efficiency, and employee experiences. The study focuses on both theoretical and practical aspects, providing insights that can inform academic research and guide organizations in leveraging AI effectively. To address the research problem, a cross-sectional study design using a questionnaire as the primary data collection tool has been selected. This design allows for the collection of quantitative data at a specific point in time, providing a snapshot of the relationship between AI and management practices. The questionnaire will be administered to professionals and managers across diverse industries, representing organizations that have implemented AI technologies in their management processes. The importance of this study lies in its theoretical and practical contributions. Theoretically, it expands the understanding of the role of AI in management by examining its impact on decision-making processes, organizational structures, and employee roles. It contributes to the existing body of knowledge by exploring the nuances and complexities of AI implementation in managerial contexts. Practically, the findings will provide insights and recommendations for organizations seeking to adopt or optimize AI technologies in their management practices. It will guide decision-makers in understanding the potential benefits, challenges, and best practices associated with AI integration. The scope of this study encompasses professionals and managers across various industries, ensuring a diverse representation of AI adoption in management practices. The focus is on organizations that have implemented AI technologies and are actively utilizing them in their decision-making processes, resource allocation, and performance evaluation. The study aims to capture the perceptions, experiences, and attitudes of participants related to the role of AI in management. Data will be collected through a structured questionnaire distributed electronically to the selected participants. The questionnaire will capture quantitative data on participants’ perceptions, experiences, and attitudes towards AI in management. It will include closed-ended and Likert-scale questions, enabling efficient data collection and analysis. The collected data will be analyzed using appropriate statistical techniques, including descriptive statistics, correlation analysis, and regression analysis. By employing this methodology and research tools, this study seeks to provide a comprehensive understanding of the impact of AI on management practices. The findings will contribute to both theoretical knowledge and practical insights, guiding organizations in leveraging AI effectively to enhance decision-making, improve operational efficiency, and foster innovation in management processes.

The Function of RNA Interference (RNAi) in Crop Enhancement- Mechanism and Applications: A Review

RNA interference (RNAi) is a conserved molecular mechanism that plays a critical role in post-transcriptional gene silencing across diverse organisms. This review delves into the role of RNAi in plant functional genomics and its applications in crop improvement, highlighting its mechanistic insights and practical implications. The overview starts with the fundamental finding of the mechanism of RNAi, following its journey from petunias to its ubiquitous presence in a wide range of species. The discovery of several kinds of regulatory non-coding small RNAs, including as phasiRNAs, miRNAs, and siRNAs, has broadened our knowledge of RNAi-mediated gene regulation beyond what is previously thought. These RNA types have an impact on gene expression through complex post-transcriptional and epigenetic mechanisms. RNA interference (RNAi) has become a potent tool for comprehending gene activities in the context of crop improvement. It has shown to be useful in determining the functions of genes for metabolic pathways, stress tolerance, and more. Furthermore, RNAi-based strategies have potential for sustainable agriculture and integrated pest management, supporting international efforts to ensure food security. The many uses of RNA interference (RNAi) are covered in this article, including improving crop nutrition, changing plant architecture, and increasing shelf life. The challenges and future prospects of RNAi technology are also explored. The worldwide geography of RNA interference research is emphasized, with notable contributions from North America, Europe, and China. In conclusion, RNA interference (RNAi) continues to be a flexible and essential tool in contemporary plant research, providing new pathways for understanding gene activities and enhancing crop characteristics. Its combination with other biotechnological techniques, such as gene editing, might influence how agriculture and sustainable food production develop in the future.

Zoom & WhatsApp digital information and communication technologies (ICTs) enhance community engaged research with women immigrants from Mexico

ABSTRACT This article demonstrates how digital information and communication technologies (ICTs) (Zoom/WhatsApp) unexpectedly and counterintuitively proved to be valuable tools for community-engaged health research when, in the context of the COVID-19 pandemic, they were integrated into a research study testing a peer support group intervention with female immigrants from Mexico. Because of pandemic restrictions, we changed the study protocol to hold meetings remotely via Zoom rather than in person as originally planned. Because we recognized that this would lack some opportunities for participants to interact and develop relationships, we created a WhatsApp chat for each group. Despite challenges for participants to use ICTs and participant-stated preference for in-person meetings, the results demonstrated that participants overwhelmingly endorsed these technologies as promoting access, participation, engagement, and satisfaction. Zoom/WhatsApp created a valuable environment both as a method for conducting research with this population, but also as part of the intervention for immigrant women to support and learn from each other. ICT adaptations have now permanently changed the way we conduct community-engaged health research.

Is elderspeak communication in simulated hospital dementia care congruent to communication in actual patient care? A mixed-methods pilot study.

Simulation offers a feasible modality to prepare nurses for challenges communicating with patients with dementia. Elderspeak communication is speech that sounds like baby talk and can lead to rejection of care by patients with dementia. However, it is unknown if simulation can be used to capture elderspeak communication in dementia care. The purpose of this mixed-methods study was to determine if simulation accurately captures elderspeak communication by nursing staff in hospital dementia care. A 3-part mixed-methods design in which (1) three dementia care simulations were designed and validated by a panel of experts, (2) communication by nursing staff completing each simulation was quantitatively compared to communication during actual patient care, and (3) views on the realism were explored using within- and across-case coding. Three simulations using different modalities (manikin, role-play, and standardised patient) were designed and validated with eight experts using the Lynn Method. Ten nursing staff were audio-recorded and their communication was coded for elderspeak communication. Results for each simulation were compared using Wilcoxon signed-rank test to recordings taken during actual dementia care encounters. Debriefings were coded for realism and results were converged. The average time using elderspeak during naturalistic care was 29.9% (SD = 20.9%) which did not differ from the average amount of elderspeak used across the three simulations modalities which ranged from 29.1% to 30.4%. Qualitative results suggested a lack of realism with the manikin condition and the nursing staff indicated preference for the simulation with the standardised patient. Communication elicited in the dementia care simulations was congruent to communication produced in actual dementia care but preference was for the standardised patient. Elderspeak communication can be accurately produced in the simulated environment which indicates that simulation is a valid method for person-centred communication training in nursing staff. Simulation offers a feasible modality to prepare nurses for challenges communicating with patients with dementia. Elderspeak communication is speech that sounds like baby talk and can lead to rejection of care by patients with dementia. However, it is unknown if simulation can be used to capture elderspeak communication in dementia care. Elderspeak communication captured in the simulated environment was congruent to communication nursing staff use during actual patient care to hospitalised persons living with dementia. This study empirically identifies that communication is elicited in similar patterns by nursing staff in the simulated environment compared to the naturalistic care environment which demonstrates that simulation can be used as a valid tool for education and research on person-centred communication. STROBE. No Patient or Public Contribution.

Expanding research impact through engaging the maker community and collaborating with digital content creators.

This paper proposes a method for increasing the impact of academic research by providing materials for public use, thus engaging the maker community, and by collaborating with internet content creators to extend the reach. We propose a framework for engagement and report a multi-year study that evaluates short, intermediate, and long-term outcomes, with a second effort to demonstrate repeatability of the short-term outcomes. In the first study, we posted forty-one 3D printable compliant mechanisms on public repositories and collaborated with physicist and content creator Derek Muller (Veritasium YouTube channel). Outputs and outcomes from this interaction were measured over 3 years. The framework was exercised again with four new 3D printable mechanisms in collaboration with engineer and STEM influencer Mark Rober. The proposed methods aim to help researchers extend the reach of their work to broader audiences, including professional engineers, hardware designers, educators, students, researchers, and hobbyists. This work demonstrates promising impacts of the framework, including (1) extending public awareness of research findings to broader audiences by engaging the maker community and collaborating with content creators, (2) accelerating the pace of innovation and further hardware-based research through public application of research findings, (3) fostering a culture of open-source design and collaboration among other researchers, engineers, educators, and makers, and (4) increasing utilization of peer-reviewed published content. These outreach practices can be valuable tools for researchers to increase impact of and excitement for their research.

Socioeconomic constraints on low‐income individuals' perceptions toward food safety

AbstractFood safety has emerged as a critical concern in Vietnam, posing a significant threat to public health due to the prevalence of unsafe foods in the market. Among those most vulnerable to contaminated foods, low‐income individuals are significantly affected. This study aimed to investigate the perceptions of food safety among this demographic, utilizing qualitative and quantitative approaches, including focus groups, survey questionnaires, and behavioral experiments using steamed bun as a stimulus. Participants were generally from low‐income classes with certain variations in household monthly income. Results from focus groups and the survey highlighted that the factors influencing food purchases included perception of safety, sensory properties, and acceptable pricing. The behavioral experiment revealed that participants with lower incomes were more inclined to select foods containing unsafe chemicals. In conclusion, the study underscored the heightened vulnerability of low‐income individuals to unsafe foods, with their perception of food safety bounded by socioeconomic status.Practical ApplicationsThe study highlights the high risk of contaminated food consumption among low‐income individuals in Vietnam, intensified by economic struggles and heightened vulnerability to food insecurity. With this demographic relying on regulations for their health, urgent actions are needed. Governmental policymakers should focus on implementing food safety educational campaigns, promoting affordable and safe alternatives, and providing food aid to economically disadvantaged communities. Mandatory food safety training programs for street food vendors, food handlers, and small businesses, coupled with regular safety practice monitoring, can play a crucial role in mitigating serious consequences. In addition, the research methodologies employed in this study, especially the behavioral experiment approach, can serve as valuable tools for researchers in the field of consumer behavior, enabling them to attain valid and reliable results.

Αξιοποιώντας το «ρίζωμα» στην κοινωνιογλωσσολογική και την εκπαιδευτική έρευνα

Focusing on people who experience multilevel invisibility and social inclusion, such as unaccompanied minors, literacies research often fails to map and understand the fluidity of their needs and the disruptions they experience in their everyday educational and social lives including school drop-out and radicalization phenomena. Therefore, it is important that we experiment with new ways of thinking and researching. In the present paper, drawing on multiple literacies theory, I showcase how deleuzoguattarian philosophy, and specifically the concept of the rhizome may influence sociolinguistic thought and provide new tools for literacies research. Specifically, applying rhizomic thinking, in order to re-imagine a non-formal second language literacy classroom interaction in a hosting center for unaccompanied minors, I build on the sociolinguistic concept of translanguaging space (Wei, 2018), so as to describe a becoming classroom and becoming learners through the interaction of smooth and striated space. Thereby, I point out how power relations unfold among language users and linguistic features that re-/de-/territorialize in the linguistic landscape of the becoming classroom. Based on this example, I reflect on what counts as literacy and discuss the implications of a deleuzoguattarian approach for a rhizomatic language education inspired by a sociolinguistic justice perspective, and what I call ‘rhizomatic hope’.

Mindfulness and Emotional Intelligence: A Study on Millennials on Hospitality

In software development, dependability and quality are critical. A Bug Tracking System (BTS) designed specifically for large-scale software projects is introduced in this significant project with the goal of streamlining bug tracking, reporting, detection, and resolution. The system provides secure authentication, a backend database that is reliable, and an easy-to-use web interface. Using cutting-edge web technologies, it offers critical features including automated notifications, progress tracking, severity assignment, and thorough bug reporting together with user-friendly interfaces for a range of user roles. Tools for data visualization help identify defect patterns and monitor projects. The project follows best practices recommended by the industry for requirements analysis, design, implementation, testing, and deployment, and it solicits ongoing input. The result is a thorough BTS that addresses defect management difficulties. Thorough testing and assessment in comparison to standards confirms its efficacy. This approach could have a big impact on software development, improving user satisfaction and quality. Furthermore, issues with bug tracking are covered, including distributed team communication, scalability, and automation balancing. Proposals for strategies to address these issues are grounded in scholarly research and professional opinions. This summary highlights the critical role that bug tracking systems play in contemporary software development, making it an invaluable tool for researchers, practitioners, and teams looking to improve bug tracking procedures and raise the caliber and effectiveness of the software development lifecycle. Keywords— Bug Tracking System, Software Development, Defect Management, Quality Assurance, Automation, Collaboration, Large-scale Projects.

Адаптация русскоязычной версии «Шкалы осознанного выбора и самосознания» (PCASS - Perceived Choice And Awareness Of Self Scale)

<p style="text-align: justify;">To date, the issue of expanding the arsenal of adapted foreign tools (or creating their own) for assessing the level of self-determination of personality remains quite relevant. For this reason, the objective of the present study was to adaptation on the Russian-language sample of the modern version of the Self-Determination Scale by K. Sheldon and co-authors, in an updated version called the Perceived Choice and Awareness of Self Scale. Methods. The scale was translated with subsequent questioning of 588 respondents (residents of Russia, students of St. Petersburg educational institutions), including 325 women and 263 men (mean age - 20,5 ± 2,39, Mo = 21). Results. When assessing the psychometric properties of the Russian-language version of the adaptable questionnaire, significant results were obtained, indicating the reproducibility of the number and structure of the factors that form the two subscales of the original methodology. Also, psychometric indicators confirm the reliability, internal consistency, structural and constructive validity of the Russian version of the methodology. In addition, according to our study, the questionnaire is characterized by high differentiating ability and diagnostic sensitivity: significant gender differences were found in the Russian-speaking sample in terms of perceived choice and self-awareness. Conclusions. According to the results obtained, the adapted version of the questionnaire has good psychometric characteristics and can be used as a qualitative research tool.</p>

The teachers’ perspective on teaching languages to Polish seniors

Abstract The aim of the study is to investigate foreign language teachers’ perspective on teaching older adults in the context of (glotto-)stereotypes about Polish third-agers. Thirty-seven lecturers, divided into two groups: one with and one without experience in teaching a foreign language to seniors, were examined. The survey study consisted of two stages based on 2 different research tools: online surveys and group interviews. Both individual responses from surveys and opinions expressed during group interviews were analyzed qualitatively with the use of a reflexive thematic analysis (TA) approach. The teachers responded to the questions regarding the following aspects: 1) seniors’ experiences in learning foreign languages; 2) older adults’ motivation, needs and expectations; 3) the role of the teacher; 4) didactic strategies. It turned out that the responses from the two groups did not differ a lot and in general the lecturers declared their willingness to work with late L2 learners. The influence of stereotypical thinking about seniors (based on the opinions of young Poles cited in the literature) on teachers who did not have experience working with this age group, was not as strong as presumed. None of the research groups’ members had had any formal education or training in teaching late L2 learners and, noteworthy, the attitudes and abilities of both teacher groups appeared to differ from the stereotypically held beliefs of Polish seniors. The comments from experienced teachers revealed their deeper awareness of seniors’ psychological needs, such as supporting them or giving positive feedback.

Towards a Culturally Adapted JVQ: Rasch Model Validation among Adolescents in India

Purpose: This study evaluates the psychometric properties of Juvenile Victimization Questionnaire (JVQ) based on the lifetime victimization and traumatic experiences reported by Indian adolescents. Method: A cohort of 350 adolescents, aged 12 to 18 years, from various schools in Aligarh District of India participated in this study. Result: The JVQ’s content validity using Fleiss Kappa analysis, Unidimensionality, and item and person reliability were assessed through rasch measurement model. Moreover, the analysis yielded promising result for the JVQ, indicating high reliability, the Fleiss Kappa score of 0.92 suggest an almost perfect agreement, while the person and item reliability scores were recorded at 0.70 and 0.90, respectively. Conclusion: This initial study supports the JVQ’s potential reliability and validity, suggesting it could be foundational tool for broader research across multiple locations.

LipidSig 2.0: integrating lipid characteristic insights into advanced lipidomics data analysis.

In the field of lipidomics, where the complexity of lipid structures and functions presents significant analytical challenges, LipidSig stands out as the first web-based platform providing integrated, comprehensive analysis for efficient data mining of lipidomic datasets. The upgraded LipidSig 2.0 (https://lipidsig.bioinfomics.org/) simplifies the process and empowers researchers to decipher the complex nature of lipids and link lipidomic data to specific characteristics and biological contexts. This tool markedly enhances the efficiency and depth of lipidomic research by autonomously identifying lipid species and assigning 29 comprehensive characteristics upon data entry. LipidSig 2.0 accommodates 24 data processing methods, streamlining diverse lipidomic datasets. The tool's expertise in automating intricate analytical processes, including data preprocessing, lipid ID annotation, differential expression, enrichment analysis, and network analysis, allows researchers to profoundly investigate lipid properties and their biological implications. Additional innovative features, such as the 'Network' function, offer a system biology perspective on lipid interactions, and the 'Multiple Group' analysis aids in examining complex experimental designs. With its comprehensive suite of features for analyzing and visualizing lipid properties, LipidSig 2.0 positions itself as an indispensable tool for advanced lipidomics research, paving the way for new insights into the role of lipids in cellular processes and disease development.

Incorporation of self-heating effect into a thermo-mechanical coupled constitutive modelling for elastomeric polyurethane

Elastomeric polyurethane (EPU) is characterised by distinctive mechanical properties, including high toughness, low glass transition temperature, and high impact resistance, that render it indispensable in diverse engineering applications from soft robotics to anti-collision devices. This study presents a thermo-mechanically coupled constitutive model for EPU, systematically incorporating hyperelasticity, viscoelasticity, thermal expansion, and self-heating effect in a thermodynamically consistent manner. Experimental data, obtained from previous studies, are then used for parameter identification and model validation, including iterative updates for temperature parameters considering the self-heating effect. Subsequently, the validated model is integrated into finite element codes, i.e., user subroutine to define a material’s mechanical behaviour (UMAT) based on the commercial finite element software ABAQUS, for the computation of three-dimensional stress-strain states, facilitating the analysis of the structural response to various mechanical loads and boundary conditions. The results obtained from simulations are compared with analytical solutions to confirm the precision of Finite Element Method (FEM) implementation. The self-heating effect is further analysed under different strain rates and temperatures. To validate the engineering significance of the FEM implementation, a plate with a hole structure is also simulated. In conclusion, this research provides a robust tool for engineers and researchers working with soft materials, enhancing their understanding and predictive capabilities, notably addressing the self-heating effect in thermo-mechanical behaviours.

The Basic Needs in Games Scale (BANGS): A new tool for investigating positive and negative video game experiences

Players’ basic psychological needs for autonomy, competence, and relatedness are among the most commonly used constructs used in research on what makes video games so engaging, and how they might support or undermine user wellbeing. However, existing measures of basic psychological needs in games have important limitations—they either do not measure need frustration, or measure it in a way that may not be appropriate for the video games domain, they struggle to capture feelings of relatedness in both single- and multiplayer contexts, and they often lack validity evidence for certain contexts (e.g., playtesting vs experience with games as a whole). In this paper, we report on the design and validation of a new measure, the Basic Needs in Games Scale (BANGS), whose 6 subscales cover satisfaction and frustration of each basic psychological need in gaming contexts. The scale was validated and evaluated over five studies with a total of 1246 unique participants. Results supported the theorized structure of the scale and provided evidence for discriminant, convergent and criterion validity. Results also show that the scale performs well over different contexts (including evaluating experiences in a single game session or across various sessions) and over time, supporting measurement invariance. Further improvements to the scale are warranted, as results indicated lower reliability in the autonomy frustration subscale, and a surprising non-significant correlation between relatedness satisfaction and frustration. Despite these minor limitations, BANGS is a reliable and theoretically sound tool for researchers to measure basic needs satisfaction and frustration with a degree of domain validity not previously available.

Assessing the Efficacy of ChatGPT Versus Human Researchers in Identifying Relevant Studies on mHealth Interventions for Improving Medication Adherence in Patients With Ischemic Stroke When Conducting Systematic Reviews: Comparative Analysis.

ChatGPT by OpenAI emerged as a potential tool for researchers, aiding in various aspects of research. One such application was the identification of relevant studies in systematic reviews. However, a comprehensive comparison of the efficacy of relevant study identification between human researchers and ChatGPT has not been conducted. This study aims to compare the efficacy of ChatGPT and human researchers in identifying relevant studies on medication adherence improvement using mobile health interventions in patients with ischemic stroke during systematic reviews. This study used the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Four electronic databases, including CINAHL Plus with Full Text, Web of Science, PubMed, and MEDLINE, were searched to identify articles published from inception until 2023 using search terms based on MeSH (Medical Subject Headings) terms generated by human researchers versus ChatGPT. The authors independently screened the titles, abstracts, and full text of the studies identified through separate searches conducted by human researchers and ChatGPT. The comparison encompassed several aspects, including the ability to retrieve relevant studies, accuracy, efficiency, limitations, and challenges associated with each method. A total of 6 articles identified through search terms generated by human researchers were included in the final analysis, of which 4 (67%) reported improvements in medication adherence after the intervention. However, 33% (2/6) of the included studies did not clearly state whether medication adherence improved after the intervention. A total of 10 studies were included based on search terms generated by ChatGPT, of which 6 (60%) overlapped with studies identified by human researchers. Regarding the impact of mobile health interventions on medication adherence, most included studies (8/10, 80%) based on search terms generated by ChatGPT reported improvements in medication adherence after the intervention. However, 20% (2/10) of the studies did not clearly state whether medication adherence improved after the intervention. The precision in accurately identifying relevant studies was higher in human researchers (0.86) than in ChatGPT (0.77). This is consistent with the percentage of relevance, where human researchers (9.8%) demonstrated a higher percentage of relevance than ChatGPT (3%). However, when considering the time required for both humans and ChatGPT to identify relevant studies, ChatGPT substantially outperformed human researchers as it took less time to identify relevant studies. Our comparative analysis highlighted the strengths and limitations of both approaches. Ultimately, the choice between human researchers and ChatGPT depends on the specific requirements and objectives of each review, but the collaborative synergy of both approaches holds the potential to advance evidence-based research and decision-making in the health care field.