Logic Model Research Articles

Using a knowledge representation logic to estimate the availability of Imbrasia epimethea (Lepidoptera: Saturniidae), an important edible insect in Subsaharan Africa

Based on monthly abundance patterns, we model the density of Imbrasia epimethea (Drury, 1773), an important edible insect in Africa. Categorical data was collected from various regions in Cameroon, and data analysis techniques were used to infer relationships between environmental variables and the level of insect abundance. Through fuzzy logic modeling, we identified the key environmental factors and rules that influence the density of the insect. To visualize the distribution of I. epimethea across African landscapes, interpolation techniques were used on the study area matrix of geographical coordinates based on the corresponding monthly predictor variables for the most recent available year (2022). The results suggested a clear dynamic across Africa through the different months of the year with potentially overlapping generations with relatively high accuracy (>90 %). A clear relationship between regional climatic conditions and the density of I. epimethea could be established across Africa. The models provide insights into the complex dynamics of insect populations and sheds light on the stability and transferability of our results across different African regions (during stability analysis). This research offers a foundation for further investigations on sustainable food production and the promotion of edible insects as a viable protein source.

Optimizing Mutual Fund Selection with Fuzzy Logic: A Case Study of Nasdaq Exchange

This study examines mutual fund performance through advanced methodologies, emphasizing fuzzy logic and the Fuzzy Sharpe Ratio. A thorough literature review highlights recent developments, such as the integration of machine learning techniques with fuzzy logic models. The research utilizes data from the Bombay Stock Exchange spanning January 1, 2024, to October 31, 2024, applying the Fuzzy Risk-Adjusted Return method. Moreover, an analysis of major technology companies reveals Alphabet Inc as the top-ranked firm, demonstrating its robust performance metrics and establishing it as a premier investment choice. Conversely, Tesla Inc ranked lowest, reflecting comparatively weaker performance. These results illustrate the competitive dynamics and varied performance levels among leading tech companies, influenced by market strategy, innovation, and financial stability. This analysis underscores the value of fuzzy logic in enhancing mutual fund evaluations and positions Alphabet Inc as a strong candidate for investor consideration.

Design of judicial public opinion supervision and intelligent decision-making model based on Bi-LSTM

Fuzzy preference modeling in intelligent decision support systems aims to improve the efficiency and accuracy of decision-making processes by incorporating fuzzy logic and preference modeling techniques. While network public opinion (NPO) has the potential to drive judicial reform and progress, it also poses challenges to the independence of the judiciary due to the negative impact of malicious public opinion. To tackle this issue within the context of intelligent decision support systems, this study provides an insightful overview of current NPO monitoring technologies. Recognizing the complexities associated with handling large-scale NPO data and mitigating significant interference, a novel judicial domain NPO monitoring model is proposed, which centers around semantic feature analysis. This model takes into account time series characteristics, binary semantic fitting, and public sentiment intensity. Notably, it leverages a bidirectional long short-term memory (Bi-LSTM) network (S-Bi-LSTM) to construct a judicial domain semantic similarity calculation model. The semantic similarity values between sentences are obtained through the utilization of a fully connected layer. Empirical evaluations demonstrate the remarkable performance of the proposed model, achieving an accuracy rate of 85.9% and an F1 value of 87.1 on the test set, surpassing existing sentence semantic similarity models. Ultimately, the proposed model significantly enhances the monitoring capabilities of judicial authorities over NPO, thereby alleviating the burden on public relations faced by judicial institutions and fostering a more equitable execution of judicial power.

Risk Assessment for the Development of Emergency Scenarios for Tram Driver Training

(1) Background: This article presents research results from a project to develop a simulator and training program for tram drivers based on virtual reality tools. This article aims to present the research results on the risk assessment of adverse events to develop training scenarios for tram drivers. (2) Methods: The research methodology involved four steps, including the identification of adverse events based on interviews with experts, estimation of risk parameters, risk assessment using fuzzy logic, and risk evaluation to identify events recommended for the training program. (3) Results: Thirteen adverse events related to tram driving were identified and ranked according to the proposed classification. A risk assessment was then performed for the selected group of events using fuzzy logic models. The results made it possible to recommend situations that should be mapped in the virtual world as part of a tram driver training program. (4) Conclusions: The results made it possible to distinguish a group of events that should constitute the training area dedicated to tram drivers. Including the developed emergency scenarios in the training program allows employees to examine their reactions to stressful or dangerous situations and better prepare themselves for future duties.

Intervention development and optimisation of a multi-component digital intervention for the monitoring and management of hypertensive pregnancy: the My Pregnancy Care Intervention.

Hypertensive disorders of pregnancy affect around 10% of pregnancies and remain a major cause of maternal and foetal morbidity and mortality. Trials have shown that self-monitoring blood pressure during pregnancy is safe, but self-monitoring alone does not improve blood pressure control or pregnancy outcomes. This study aimed to develop and optimise a multicomponent intervention to support blood pressure monitoring, hypertension management and urine testing within current care pathways. Relevant literature, input from patient and public contributors (PPI) and stakeholder groups, and the researcher's previous experience were used to develop an initial intervention. Think-aloud interviews and focus groups with women from diverse backgrounds with lived experience of hypertension in pregnancy and healthcare professionals provided feedback on the intervention prototype (n = 29). The MRC Framework for Developing Complex Interventions guided the processes to optimise the intervention's acceptability and maximise engagement. A detailed tabulation of participants' views and logic models was produced using the COM-B model of Behaviour Change. The prototype intervention was acceptable and viable to both pregnant women with experience of hypertensive pregnancy and healthcare professionals. Emerging themes centred on how the intervention could be optimised within current National Health Service care pathways and the lives of pregnant women to support behaviour change. Key target behaviours to support the intervention included increasing understanding of blood pressure management, engagement with the intervention, monitoring blood pressure and urine and taking appropriate actions based on those readings. This informed the development of recommendations involving clear action timelines for women and evidence-based guidance to support decision-making by healthcare professionals. The findings were used to produce the multi-component My Pregnancy Care intervention, consisting of a smartphone application and an information leaflet to support blood pressure self-monitoring and proteinuria self-testing, self-management of antihypertensive medication and smartphone application use. This research provided comprehensive insight into the needs of pregnant women with hypertension and their healthcare teams regarding self-monitoring and management of blood pressure. This supported the development of a tailored multi-component digital intervention that addresses barriers to blood pressure self-management by being user-friendly, persuasive and acceptable. It is hoped that the intervention will support the monitoring and management process, collaboration between healthcare professionals and women, clinical action and improved clinical outcomes.

Abstract 4125893: Deciphering the Mechanism of Action of Drug Combinations by Boolean Modeling of Transcriptomes: a Case Study of Atorvastatin/Simvastatin and Ezetimibe

Introduction: Drug combinations offer increased therapeutic efficacy and reduced toxicity and plays a vital role in treating chronic complex diseases. Understanding a drug combination's mechanism of action (MoA) can provide important insights into its therapeutic efficacy. The MoA of many FDA-approved drugs, however, often remains unclear. Methods: In this study, we investigated the combination of a statin [atorvastatin (ATO) or simvastatin (SIM) plus ezetimibe (EZE)] and utilized drug-treated RNA-seq transcriptome data from SOAT2-only-HepG2 cells (treated with ATO 5 umol/L, EZE, 25 umol/L, their combination or vehicle) and from liver biopsies of patients with uncomplicated cholesterol gallstone disease in the Stockholm Study (a single-blind, randomized trial with SIM 80 mg daily, EZE 10 mg daily, their combination, or placebo) to decipher the underlying molecular mechanisms of the drug combination. We proposed a Boolean logical modeling framework to simulate the MoA of a drug combination. Specifically, fourteen two-variable Boolean models were used to describe the combinatory relationships of ATO/SIM and EZE. Thereafter, a pattern matching approach was applied to associate drug-induced differentially expressed genes with the idealized differential expression templates derived from Boolean models. Results: We found 1,560 and 594 genes differentially expressed in at least one treatment condition in SOAT2-only-HepG2 cells and liver biopsies, respectively. Our analysis revealed both expected and novel combinatorial modes of ATO/SIM and EZE. For example, ATO independently activates downstream genes (i.e. B 4 (ATO,EZE)=ATO), and ATO and EZE synergistically inhibits downstream genes (i.e. B 15 (ATO,EZE)=NOT (ATO AND EZE)) , as the two most prevalent MoAs in SOAT2-only-HepG2 cells (Figure 1). Similarly, the combination of SIM and EZE synergistically inhibiting downstream genes was also the most prevalent MoA in the liver biopsies. We mapped the downstream genes of each combinatorial mode to the human interactome and obtained underlying subnetworks, which are important for understanding the therapeutic effects of the drug combination. Functional enrichment and disease-association analyses of the downstream suggest the additional therapeutic indications of the drugs. Conclusion: Drug-induced transcriptomes are informative in deciphering the MoA of drug combinations using Boolean logical modeling. This framework can be easily extended to the combinations of three drugs.

Cut-free labelled calculi and decidability for intuitionistic sentential logic with identity

Abstract In this paper we consider the intuitionistic non-Fregean sentential calculus with Suszko’s identity ($\mathsf{ISCI}$). After recalling the basic concepts of the logic and its associated Hilbert proof system, we introduce a new sound and complete class of models for $\mathsf{ISCI}$, called Topological Beth (${\mathsf{TB}}$) models, that can be viewed as algebraic counterparts (and extensions) of sheaf-theoretic topological models of intuitionistic logic. From this semantical study we define a family of sound and cut-free complete labelled calculi that capture both the Kripke and the ${\mathsf{TB}}$ semantics. Using a key property of the forcing relation in ${\mathsf{TB}}$ models, called regularity, we show termination and decidability results. Finally we discuss the automation of the proof search in one of the labelled calculi and its implementation.

Advancing aquaculture: fuzzy logic-based water quality monitoring and maintenance system for precision aquaculture

AbstractAquaculture plays a vital role in global food production, and maintaining optimal water quality is essential for the health and growth of aquatic species. This research addresses the need for an efficient, adaptive solution by introducing an innovative water quality monitoring and maintenance system for aquaculture ponds. Unlike conventional systems, our approach uniquely integrates fuzzy logic with IoT technologies to optimise the precision and adaptability of pond management. The system stands out with its continuous monitoring of critical parameters such as temperature, pH, dissolved oxygen (DO), weather conditions and salinity and its ability to autonomously adjust operational controls, such as aerators and water pumps, based on dynamic environmental changes. This ensures ideal water conditions without manual intervention, providing a reliable and effective solution for aquaculture pond management. This work’s novelty lies in applying fuzzy Logic to handle the complexity and variability of aquaculture environments, allowing for nuanced control decisions that improve water quality management. The system’s efficiency was demonstrated through a 72-h operational test, where it maintained optimal DO and salinity levels, showcasing its reliability and effectiveness in real-world conditions. The fuzzy logic model has demonstrated a commendable accuracy rate of 98%. These results validate the system’s performance and underscore its practical benefits, meeting the demands of aquaculture production and significantly enhancing operational efficiency by enabling remote monitoring and rapid issue identification. This research contributes a robust technological solution for aquafarmers, offering a promising advancement in aquaculture management by improving productivity and ensuring the health and growth of aquatic species.

A Proposal for a Best-evidence Model of Care and Program Logic for Supported Accommodation for People Released From Prison.

This paper describes the development of a proposed best-evidence model of care (MoC) and program logic (PL) for supported accommodation (SA) for people released from prison. Evidence from a systematic review, interviews with clients of SA, and consultation with service providers were synthesized to develop a draft MoC that was embedded into a PL. The MoC and PL were refined in a workshop with researchers and SA providers. The MoC comprised five best-evidence core components to be standardized across any SA, operationalized by flexible activities that need to be determined by services to suit their circumstances. The PL comprised client needs that the program targets, a rationale for why core components would be effective and appropriate process and outcome measures. The development and uptake of a best-evidence MoC and clearly defined PL will help engender a larger and more rigorous SA evidence-base, and improve outcomes for people released from prison.

Community-Driven Health Promotion: Evaluation of a Rural Microgrant Program.

Microgrants for health promotion have the potential to engage communities in designing and implementing place-based interventions to improve health and social outcomes. However, the evidence base around microgrants for health promotion is limited. This study presents the evaluation of a health service-funded microgrant program for health promotion in rural Australia. The evaluation framework was developed through a participatory approach and involved collaborative logic model building and co-prioritized evaluation questions with health service staff and grant recipients. Evaluation questions focused on participation, short-term outcomes, and the perceived value of program activities. Qualitative methods (reflexive thematic analysis) were used to answer the evaluation questions. Data sources included semi-structured interviews with grantees (n = 11) and the health service's health promotion team (n = 4), electronic field notes kept by the health promotion team (n = 50 documents), electronic progress reports completed by grantees (n = 6) and information and feedback forums (n = 2). Since the program's inception in 2019, the health service has received 22 grant applications of which 15 were approved and 14 disbursed. Evaluation results show that grantees were community members with multiple roles, often with previous experience in applying for grants. Expected outcomes have been partially met, especially with regard to the program's aim of community empowerment. The most notable impact was the enhancement of participants' perception of and relationship with the health promotion team, as well as the creation of opportunities for community members such as exposure to art and bridging of social groups. Microgrants represent a feasible way to increase health opportunities and foster community participation in the planning and delivery of health promotion programs. The key program activities identified and suggested improvements can help guide program replication and adaptation by other small organizations. Community members who had previously received a health service grant were invited to participate in collaborative workshops and follow-up surveys to codesign the grant program evaluation framework, co-prioritize evaluation questions and guide the results' dissemination plan.

Model-informed precision dosing of vancomycin in clinical practice: an intervention development study.

Current guidelines recommend dosing vancomycin based on the area under the concentration time curve (AUC) to maximise efficacy and minimise the risk of nephrotoxicity. The preferred approach to AUC-guided therapy is to apply model-informed precision dosing (MIPD). However, the adoption in clinical practice has been slow. We aimed to develop an intervention, including a standardised MIPD workflow and an implementation plan for vancomycin AUC-guided dosing, in a Swedish tertiary hospital. The intervention was developed in a framework-guided process. The design phase included stakeholder feedback (nurses, pharmacists, physicians), local data collection and feasibility testing of intervention components with parallel consideration of implementation aspects. The hypothesised relationships between the different components, implementation strategies and the mechanism of action resulting in expected outcomes were represented by a logic model. The final intervention consisted of a workflow for MIPD, with defined roles and responsibilities, as well as processes for data and information transfer. Details were provided in supportive documents; an instruction on therapeutic drug monitoring (TDM) sampling and documentation for nurses, and a detailed dosing software instruction for MIPD consultants and clinical pharmacists. Activities to facilitate implementation included the development of a local clinical routine for vancomycin dosing, staff training and recurring MIPD rounds. An intervention for MIPD, with an implementation plan for AUC-guided dosing of vancomycin, was developed for a tertiary hospital setting. The process can be used as guidance for other institutions with similar context wishing to initiate MIPD.

Improving the budgetary policy of municipalities

The subject of the study is financial relations of municipalities in terms of income generation. The purpose of the article is to disclose and justify measures to increase fairness of the distribution of personal income tax by fixing the share of such a tax for the municipality in which the citizen lives but does not work. The research methods are general scientific (analysis, synthesis, deduction, classification, work with sources) and empirical ones (horizontal analysis). The article considers the problem of imbalance of local budgets caused by pendulum migration and, consequently, by outflow of income from municipalities. An information and software solution has been proposed to ensure the fair distribution of part of the personal income tax between municipalities by the place of residence and work of taxpayers. The logical model of the proposed solution and necessary changes in legislation for its implementation are described. The scope of application is the budget system of the Russian Federation, namely the spheres of municipal finance. Further research should be aimed at identifying additional reserves for strengthening the financial autonomy of municipalities. The expected results of the work include improving the financial situation of the population, optimising the budget system and leveling the level of development of municipalities. The importance of the proposed solution for balanced regional development and improving the quality of life of citizens is emphasised.

Evaluation of Tourism Development Policies in the Context of Empowering Local Communities in a Logic Model Perspective

Evaluation of Tourism Development Policies in the Context of Empowering Local Communities in a Logic Model Perspective

Activities, prerequisites, and outcomes of service coordination: A logic model for the ‘New Patterns’ intervention

Activities, prerequisites, and outcomes of service coordination: A logic model for the ‘New Patterns’ intervention

Training physicians in motivational communication: An integrated knowledge transfer study protocol.

While behavior change counseling (BCC) targeting health risk behaviors has shown efficacy for improving patient health outcomes, barriers to knowledge translation have resulted in poor uptake among health care providers (HCPs). This article outlines the development of a new BCC training framework for HCPs, from inception to readiness for efficacy testing. It provides an example of integrated knowledge translation (iKT) used in alignment with the obesity-related behavioral intervention trials model. (a) A modified Delphi process identified essential BCC skills for HCPs; (b) a survey assessed HCP attitudes and training needs; (c) an online competency assessment tool was developed using iKT mixed methods; (d) a training program was developed and refined using a logic model; and (e) the program was optimized using iterative rounds of participant feedback. A future proof-of-concept trial (f) will determine the program's readiness for full efficacy testing. A Delphi panel (n = 46) identified 11 core BCC competencies for HCPs, defining "motivational communication." The HCP survey (n = 80) showed willingness to devote 4 hr to introductory training in BCC. The Motivational Communication Competency Assessment Test (MC-CAT: an online, interactive evaluation tool) and a motivational communication training program (MOTIVATOR: accredited for continuing education by the Royal College of Physicians and Surgeons of Canada) were collaboratively developed with knowledge users. The optimization process (n = 11) provided key feedback, with minor changes being made to the program. In developing a new BCC framework, obstacles to BCC implementation were addressed through an iterative iKT process. This should improve eventual intervention uptake. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

A Machine Learning and Fuzzy Logic Model for Optimizing Digital Transformation in Renewable Energy: Insights into Industrial Information Integration

The most essential criteria to improve digital transformation in renewable energy projects should be identified. This situation helps the companies to use limited financial budgets and human resources in the most efficient way. Therefore, a new study is needed to analyze the performance indicators of the digital transformation process in renewable energy projects. Accordingly, this study aims to identify the most significant performance indicators of digital transformation for these projects. A three-stage machine learning and fuzzy logic-based decision-making model has been constructed in this process. The first stage includes the weight calculation of the experts by dimension reduction methodology. Secondly, essential factors of digital transformation in renewable energy projects are examined via Fermatean fuzzy criteria importance through intercriteria correlation (CRITIC). The final part consists of the ranking of emerging seven countries with Fermatean fuzzy weighted aggregated sum product assessment (WASPAS). On the other side, combined compromise solution (CoCoSo) method is also taken into consideration in this process to make a comparative evaluation. The main contribution of this study is the generation of novel machine learning and fuzzy logic integrated decision-making model to make evaluation related to the digital transformation of renewable energy projects. In this model, machine learning technique is used to determine the importance weights of the experts. Similarly, integrating Fermatean fuzzy numbers with CRITIC and WASPAS techniques also contributes to the literature by minimizing the uncertainty and identifying the relationship between the items. The findings demonstrate that employing qualified personnel plays the most critical role in increasing digital transformation in renewable energy projects. Additionally, government support is very critical in the successful implementation of digital transformation processes in renewable energy projects.

A Partner-Engaged Approach to Developing an Implementation Research Logic Model for a Traumatic Brain Injury-Intensive Evaluation and Treatment Program.

A partnered evaluation project with Veterans Health Administration Physical Medicine and Rehabilitation program office uses a partner-engaged approach to characterize and evaluate the national implementation of traumatic brain injury (TBI)Intensive Evaluation and Treatment Program (IETP). This paper illustrates a partner-engaged approach to contextualizing the IETP within an implementation research logic model (IRLM) to inform program sustainment and spread. The project was conducted at five IETP sites: Tampa, Richmond, San Antonio, Palo Alto, and Minneapolis. Partners included national and site program leaders, clinicians, Department of Defense Referral Representatives, and researchers. Participants included program staff ( n =46) and Service Members/Veterans ( n =48). This paper represents a component of a larger participatory-based concurrent mixed methods quality improvement project. Participant scripts and demographic surveys. Datasets were analyzed using rapid iterative content analysis; IETP model was iteratively revised with partner feedback. Each site had an IETP clinical team member participate. The IRLM was contextualized within the Consolidated Framework for Implementation Research (CFIR); systematic consensus building expert reviewed implementation strategies; RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance); and Implementation Outcomes Framework (IOF). Analyses and partner feedback identified key characteristics, determinants, implementation strategies, mechanisms, and outcomes. This partner-engaged IRLM informs implementation and sustainment of a rehabilitation program for individuals with TBI. Findings will be leveraged to examine implementation, standardize core outcome measurements, and inform knowledge translation.

SIMULATION OF THE INFLUENCE OF THE INVESTMENT ENVIRONMENT ON THE FORMATION OF AN ATTRACTIVE MACRO SPACE OF THE ECONOMY OF UKRAINE

The economic situation in most countries demonstrates an ever-increasing demand for investment resources while their supply is significantly limited. A system of factors characterized by multidirectional action forms the so-called investment environment in the country. Its structure and level of efficiency are crucial determinants for ensuring the sustainable economic development of a country. The purpose of the study is to substantiate scientific and practical recommendations for the formation of a highly efficient macro-space of the economy of Ukraine based on the implementation of rational investment policy measures. In the course of this research, an analysis of foreign investment volumes in Ukraine was conducted, and a list of factors ensuring the positive investment image of the country in the international arena was identified. The result of the study is constructed trend lines of GDP dependence on direct foreign investors in Ukraine and abroad, as well as trend lines of GDP dependence on the level of the tax burden and the integral indicator of the level of the shadow economy; the delineation of the main directions for forming an investment environment in the context of attracting foreign capital investments. The priority vectors of optimizing the investment environment in Ukraine are substantiated and the main problems of Ukraine's investment attractiveness as a motivational factor for investment activity are determined. The strategic directions for the development of investment attractiveness of the national economy under modern business conditions have been justified. The methodological basis of the research consists of a systematic, comprehensive, and evolutionary approach. The main scientific results of the study were obtained through the use of methods such as structural-logical analysis, theoretical generalization, comparative analysis, structural-functional analysis, and a comprehensive approach based on identifying cause-and-effect relationships, as well as logical, economic and mathematical modelling, analytical, and graphical methods.

EVALUATION OF THE INVESTMENT CLIMATE BASED ON FUZZY LOGIC

The subject of the study is the investment climate of the country, region and investment attractiveness of the enterprise. The article is aimed at substantiating a fuzzy logical model for assessing the investment climate of a country, region and investment attractiveness of an enterprise under the influence of three groups of factors: economic, organizational and psychological. The hypothesis of the study is that it is possible to define the investment climate (IC) and make decisions on foreign direct investment (FDI) based on data on indicators of influence factors, even if these indicators are not clearly quantified. The division of all influence factors into three groups: economic, organizational and psychological, and the definition of linguistic assessments for those factors that do not have a natural quantitative scale, allows taking into account the expert assessment of those aspects of the investment climate that are not assessed by statistical data and cannot be expressed quantitatively, but only with the help of descriptive words based on a sense of the situation. The developed model allows determining the state of the investment climate or attractiveness under the influence of a set of factors that the user determines, depending on the country, territory, enterprise and the availability of statistical and expert information. A review of previous studies shows that the development of models based on the theory of fuzzy logic, as opposed to regression analysis, allows not only to use a larger number of indicators, but also to take into account the so-called qualitative indicators that were previously not taken into account due to the impossibility of their quantitative measurement. The objective of the study is to build a model based on fuzzy modelling, which is the method of this research. The results of the study show that the use of the obtained model can help determine the investment climate based on the analysis of factors. Practical implications – obtaining a built-in model for assessing the investment climate for making investment decisions. Value/originality of the study: the developed model, unlike similar ones, is flexible, i.e. it can include any number of factors and can be used by specialists of different levels, from civil servants to entrepreneurs. The model also allows for the inclusion of any factors that the researcher deems necessary, as they can be assessed on any scale.

Patient Experiences With Group Teletherapy for the Treatment of Mental Illness: A Qualitative Study.

The authors sought to understand patient experiences with group teletherapy to inform improvements in service delivery. From December 2022 to October 2023, semistructured interviews were conducted with 20 adults with depression or bipolar disorder who had received outpatient group teletherapy in the past 2 years. A rapid thematic analysis was conducted by using a matrix to identify patterns and synthesize data. A logic model from the patients' perspective was developed by extracting common themes related to elements of effective group teletherapy. Telehealth allowed for more empowered engagement in group teletherapy and enabled better access and longitudinal attendance for many patients, compared with in-person group therapy. However, many patients reported a reduced sense of emotional intimacy and connectedness with telehealth, and some reported that technology challenges and distractions contributed to feelings of disconnection. Patients were divided in their modality preferences, but many expressed an interest in receiving at least some of their group therapy sessions by telehealth. Although group teletherapy has the potential to meet patients' needs and preferences, more work is needed to improve the quality of the experience for patients.