Clinical Research Directory

Neural Basis of Social Cognition Deficits

Difficulties in reciprocal social interaction are hallmark features of several neuropsychiatric disorders, most notably autism spectrum disorder (ASD) and schizophrenia spectrum disorder (SSD). While recent studies have demonstrated substantial overlap in genetic etiology between ASD and SSD, little is known about common versus unique neural mechanisms that may underlie these downstream social deficits that cross diagnostic boundaries. Thus, a comprehensive imaging study examining social deficits in youth with ASD and adolescent- onset SSD at the neurochemical, connectivity, as well as functional activation level will be crucial in furthering our understanding of these underlying neural mechanisms. Specifically, the current project aims to examine how targeted social skills interventions may impact the organization of large-scale functional brain networks implicated in social cognition in these disorders, leading to improved outcomes. Thirty adolescents with ASD and 30 adolescents with SSD will undergo the Program for the Education and Enrichment of Relational Skills (PEERS), which is a 16-week parent-assisted social skills intervention that aims to improve friendship quality and social skills in teens with social difficulties. All participants will receive pre- and post-treatment MRI scans including functional MRI and magnetic resonance spectroscopy to quantify neural changes resulting from the intervention. All participants will also receive behavioral and social cognition assessments pre- and post-intervention to quantify real- world gains in social behaviors resulting from the intervention. Additionally, 30 typically developing adolescents will be recruited to serve as control participants and undergo two MRI and behavioral assessment sessions 16-weeks apart with no intervention in between. Specific aims include (1) examining inter-group disruptions in connectivity patterns, activation levels, and neurometabolite concentrations in key social brain regions pre-treatment in ASD and SSD groups, (2) examining inter-group changes in connectivity patterns, activation levels, and neurometabolite concentrations in key social brain regions in response to treatment in ASD and SSD groups, and, (3) dimensionally identifying intra-group differences in brain responses and how they relate to real-world treatment outcomes.

Comparing Sarcopenia , Physical, Psychological and Social Frailty in Hospitalized Older Women Congestive Heart Failure in Metropolitan and Rural Settings

Frailty-encompassing sarcopenia, physical, psychological, and social frailty-is common among older adults with congestive heart failure (CHF) and contributes to adverse outcomes such as rehospitalization, mortality, and poor quality of life. However, few studies have compared these conditions in congestive heart failure (CHF) patients, particularly in elderly women in Taiwan, and effective, tailored Information and Communication Technology (ICT) interventions are scarce. This three-year study aims to (1) compare baseline characteristics and incidence rates of sarcopenia, physical, psychological, and social frailty among hospitalized older women with congestive heart failure (CHF) in metropolitan versus rural hospitals; (2) evaluate risk factors associated with physical, psychological, and social frailty; (3) monitor health outcomes (rehospitalization, mortality, quality of life) during a one-year follow-up; and (4) assess the effectiveness of an Information and Communication Technology (ICT) intervention designed to enhance social connectivity and emotional well-being. In Phase 1, clinical data-including ejection fraction, congestive heart failure (CHF) stage, and comorbidity -will be collected using the 2024 Guidelines of the Taiwan Society of Cardiology, while sarcopenia will be identified via Asian Working Group for Sarcopenia (AWGS) guidelines. Physical, psychological, and social frail will be measured with the Tilburg Frailty Indicator (TFI) and Makizako's Social Frailty Questionnaire, respectively, and physical activity will be assessed using the IPAQ-S. Phase 2 will involve quarterly follow-ups over one year to compare health outcomes between metropolitan and rural settings, and to develop a predictive model of these outcomes. Phase 3 employs a quasi-experimental design with 90 participants randomized into three groups: an Information and Communication Technology (ICT) intervention group (using a dedicated app for at least 15 minutes daily, which monitors emotional status), a community-based social participation group, and a control group maintaining routine care. Key outcomes (mood, physical activity, frailty measures, and clinical status) will be assessed at baseline, immediately post-intervention, and three months thereafter. This study is expected to identify significant differences between settings and demonstrate that a tailored Information and Communication Technology (ICT) intervention can improve social connectivity and clinical outcomes in older women with congestive heart failure (CHF).

ChatGPT -Based Intervention for Social Frailty in Older Women With CHF : Gender Differences

The study is planned to be completed over three years and will focus on 500 hospitalized older adults with a diagnosis of CHF. The Biopsychosocial model will be used to conduct this study. Phase 1: This phase aims to determine the incidence rates of sarcopenia, frailty/social frailty among hospitalized older adults, and to compare these outcomes in gender differences. Sarcopenia will be identified according to the AWGS guidelines, while clinical characteristics, including ejection fraction, stage of CHF, and comorbidities, will be collected via chart review using the 2024 Guidelines of the Taiwan Society of Cardiology(Y. H. Li et al., 2024). Frailty and social frailty will be measured using the CFS, Tilburg Frailty Indicator (TFI), and Makizako's Social Frailty Questionnaire, respectively, and physical activity levels will be assessed with the International Physical Activity Questionnaire - Short Form (IPAQ-S). To develop a predictive model examining risk factors for social frailty and health outcomes, with a focus on gender differences, we will employ Structural Equation Modeling (SEM). SEM allows for the analysis of complex relationships among variables, facilitating a comprehensive understanding of how these factors interact differently across genders. Phase 2: A quasi-experimental design will be implemented, involving 174 hospitalized older adults with low social frailty scores. Participants will be randomly assigned to one of three groups. Group 1 will use the ChatGPT app for 15-30 minutes daily, with the app actively monitoring their emotional status and automatically notifying the research team and family members if signs of negative mood are detected. Group 2 will be encouraged to increase their social participation through community-based activities. The Control Group will continue their routine lifestyle without additional interventions. Before the intervention, one-on-one training will be provided to Group 1 participants on how to use ChatGPT. Key outcome measures, including mood status (loneliness, anxiety, and depression), physical activity (assessed via IPAQ-S), overall frailty (CFS \& TFI), social frailty scores, and other health indicators, will be assessed at baseline and immediately post-intervention. Phase 3: The aim of this phase is to monitor and compare the longitudinal health outcomes of interventions among the three groups. Key health outcomes will be assessed and compared every three months over a one-year period.

Parent-implemented Social Communication Treatment in Autism

An accumulation of research evidence has pointed to parent-implemented communication intervention as effective in reducing the severity of social communication deficits in autistic preschoolers. Despite even high-quality evidence, real-world translation to clinical practice remains challenging, especially for children from lower-income families, for two reasons. First, the intervention outcome is highly variable despite study-level efficacy data, most likely due to unique child and parent factors that make intervention response uneven across individual children. Second, the cost of intervention with the largest effect sizes remains high due to its one-on-one format. With the overarching goal to reduce cost and to increase intervention effectiveness at the individual-child level, this project will conduct a randomized controlled trial (RCT) to compare the effectiveness of two options for intervention to address two specific objectives. The investigators will first ascertain whether parent-implemented communication intervention taught by a speech therapist in a Group format (up to 8 families learning together) is more effective than intervention learnt by the parents themselves (learning the same materials without the guidance of a therapist) at the study level. The investigators will then evaluate what combinations of parent and child behavioral factors determine which format of intervention is likely to be more effective at the individual-child level. It is likely that not all families require the more costly Group format of intervention. Machine learning analytics with cross-validation will be used in constructing predictive models of intervention response, which will increase the likelihood of these models being generalizable to new patients. This study will be among the first examples of fulfilling the promise of Precision Medicine in providing guidance to patients and families with developmental disorders not about whether to receive intervention but which option for intervention to receive in the context of multiple options. This predict-to prescribe approach of autism intervention will likely lead to a paradigm shift in clinical practice and ultimately result in lowering the overall cost and increasing the effectiveness of intervention for autistic children as individuals.

Parent-implemented Social Communication Treatment in Preschool Children With Autism Spectrum Disorder

An accumulation of research evidence has pointed to parent-implemented communication treatment as effective in reducing the severity of social communication deficits in preschool children with ASD. Despite even high-quality evidence, real-world translation to clinical practice remains challenging, especially for children from lower-income families, for two reasons. First, the treatment outcome is highly variable despite study-level efficacy data, most likely due to unique child and parent factors that make treatment response uneven across individual children. Second, the cost of intervention with the largest effect sizes remains high due to its one-on-one format. With the overarching goal to reduce cost and to increase treatment effectiveness at the individual-child level, this project will conduct a randomized controlled trial (RCT) to compare the effectiveness of two options for intervention to address two specific objectives. The investigators will first ascertain whether parent-implemented communication treatment taught by a speech therapist in an Individual (one-on-one) format is more effective than treatment taught in a Group format (up to 8 families learning together) at the study level. The Individual format is at least 4 times more expensive than the Group format; its relative treatment effect must be empirically ascertained to justify its cost. The investigators will then evaluate what combinations of parent and child behavioral and neural factors determine which format of intervention is likely to be more effective at the individual-child level. It is likely that not all families require the more costly Individual format of intervention. Machine-learning analytics with cross-validation will be used in constructing predictive models of treatment response, which will increase the likelihood of these models being generalizable to new patients. This study will be among the first examples of fulfilling the promise of Precision Medicine in providing guidance to patients and families with developmental disorders not about whether to receive intervention but which option for intervention to receive in the context of multiple options. This predict-to-prescribe approach of ASD intervention will likely lead to a paradigm shift in clinical practice and ultimately result in lowering the overall cost and increasing the effectiveness of intervention for children with ASD as individuals.

Neural Prediction to Enhance Language

The language outcome of children receiving cochlear implantation to address bilateral sensorineural hearing loss is more variable than that of typical hearing children. The research is focused upon development of neural predictive models based upon brain imaging to forecast language after cochlear implantation on the individual child level. The long-term goal is improving children's language by using predictive models to enable a custom "predict to prescribe" approach to intervene with more effective behavioral therapy for children at risk to develop poorer language. The investigators previously developed models for short term language outcome of English-learning implanted children. The aims of this study are to 1. Develop models able to predict long term outcome for English- learning and Spanish-learning children; and 2. To evaluate whether English-learning children predicted to achieve lower language based on the investigators' previously constructed models can demonstrate significant gains from Parent Implemented Communication Treatment (PICT). PICT is an intensive parent education program about strategies to improve children's communication.