36 Clinical Trials for Various Conditions
To address both loneliness and engagement in perinatal and OUD care among perinatal women, the investigators plan to adapt an existing texting support chatbot, Penny, to make it appropriate for use by women who are pregnant and postpartum and dealing with OUD. The newly adapted chatbot, Penny COPILOT, will allow for two way short message service (SMS) messaging to respond appropriately and accurately to user generated input. The investigative team, in collaboration with the Penn Mixed Methods Research Lab (MMRL) and Penn's Way 2 Health Team, will use intervention mapping guided by the Consolidated Framework for Implementation Science. The investigators will conduct a needs assessment, assemble an advisory board, engage in pretesting to ensure safety and refine content, and pilot test the resultant adapted Penny COPILOT in a sample of 20 perinatal women with OUD to evaluate acceptability, feasibility, and patient satisfaction. The goal is to develop and refine an acceptable, feasible, and satisfactory supportive texting chatbot to promote patient engagement in perinatal and OUD care and decrease perceived loneliness.
The goal of this clinical trial is to learn if Therabot-CALM (Cannabis, Anxiety, Low Mood) has acceptability among users and could work to improve the symptoms of persons with cannabis use disorder and anxiety and/or depression. The main question it aims to answer is: What is the usability, feasibility, and acceptability of Therabot-CALM in persons with Cannabis Use Disorder and Anxiety and/or Depression? Participants will * Take a screening questionnaire * Participate in two virtual 1-hour interviews to provide feedback on app design and suggest features. * Engage with Therabot-CALM in a 4-week clinical trial and provide feedback on their app experience in a third virtual interview
Atrial Fibrillation is a chronic disease with significant health consequences like increased risk of stroke, heart failure, heart attack and death. Educating patients about the disease is important for them to be able to understand the condition better, feel empowered and take an active part in their care plan. AI technology can potentially be used to impart such education. However, doing so with care and empathy is equally important. Therefore, it is necessary to ensure when AI technology is used to impart education about atrial fibrillation to patients, the humane aspects of the interaction are rigorously tested. This study examines a way to impart atrial fibrillation education through interaction with an AI chatbot, that uses text and links to educational videos. To participate in this study, people need to be age 18 or older and have a history of newly diagnosed atrial fibrillation. Approximately 40 individuals will be asked to take part in this study. The first step to the study will be reading through, understanding, and signing an informed consent. People who then agree to join the study will have a one-time interaction with the AI chatbot and structured educational material by using an iPad provided to them for the approximately 1 hour duration of the study. People in the study will obtain atrial fibrillation education by typing one by one on the iPad, up to 10 questions about the disease. Answers will include text and links to videos. Before and after atrial fibrillation education, people who join this study will be asked to fill out a survey. The study team will teach patients how to use the iPad and type in questions.
Rosie the Chatbot is an educational chatbot that moms can have on their computers or cellphones and will work by moms typing in their questions about pregnancy, health, infant milestones, and other variety of health related topics and receiving back a response immediately. Rosie only provides information from verified sources such as children's hospitals, health organizations and government agencies. Rosie does not ask moms to provide any personal information on her or her child, her chat is completely confidential, it works in English and Spanish and will be free.
Breast cancer screening disparities among Black women persist despite health system recognition and outreach. However, current evidence on how to tailor and optimize implementation strategies for breast cancer screening outreach is limited. The proposed study is part of a larger project to design a chatbot for breast cancer screening outreach to Black women and will focus on optimizing the chatbot persona. Using the Multiphase Optimization Strategy (MOST) framework, the investigators will conduct a randomized factorial experiment to assess the individual components of chatbot persona for breast cancer screening and identify which components have the greatest effect on trust and engagement for Black women. This information will guide the design of an optimized chatbot intervention that achieves the primary outcomes.
Primary Objective: Conduct pilot study to assess effects of brief negotiation interview (BNI) Chatbot among individuals involved in the Connecticut criminal justice system with opioid use disorder (OUD). Study Duration: Approximately 2 years (1 year for study activities, 1 year for data analysis) Study Design: This is a prospective, randomized study to evaluate the effectiveness of a BNI Chatbot on patients with OUD compared with Standard Care (SC). Number of Study Sites: The offices of the Center for Progressive Recovery, LLC and the New Haven Police Department Detention Center (NHPD). Study Population: The study population includes adult individuals with OUD who are involved in the Connecticut criminal justice system and not currently receiving medication-assisted treatment for their OUD. Number of Participants: Sixty participants Primary Outcome Variable: Attendance at participants first treatment appointment within four weeks of referral among participants in the BNI Chatbot vs. Standard Care (SC) groups. Secondary Outcome and Exploratory Outcome Variables: Secondary outcomes include readiness and intention to engage in buprenorphine (bup) treatment, and urine toxicology test-confirmed drug use at four weeks among participants in BNI Chatbot vs. SC groups. Exploratory outcomes include ratings of feasibility, acceptability and satisfaction between study groups, and a comparison of study findings to engagement data from previous in-person studies, including BNI+bup, and other digital programs, such as reSET-O, and DynamiCare.
This study is designed to study the feasibility and acceptability of the Open to Options (O2O) Chatbot prototype. The O2O program is an existing patient support program with content currently delivered via in-person counseling with a trained mental health professional or via an existing web-based program (Let's Talk Treatment Options).The Chatbot is an automated, menu-based agent being developed in this study to extend the reach and accessibility of the O2O program via the Chatbot's "virtual coaching".
The goal of this observational study is to evaluate the feasibility and acceptability of a 12-week intervention utilizing a Fitbit and artificial intelligence (AI)-delivered diabetes self-management education and support (DSMES) with tailored text messages. The main question it aims to answer is: Does providing a wearable fitness and activity tracker plus AI-tailored and DSMES improve clinical outcomes for patients with type 2 diabetes? Participants will complete a baseline visit, wear a Fitbit and answer text messages for 12-weeks, and complete by a final visit.
The goal of this clinical trial is to learn if/how an AI chatbot can support patients who in recovery for substance use, specifically those who are receiving medication for opioid use disorder. Can the chatbot help lower drug use? Can the chatbot help improve clinical appointment adherence? Can the chatbot help patients build self-efficacy in leading their own recovery journey? Will the chatbot help reduce workload burden for primary care teams? Can the chatbot serve as a safe, useful and engaging tool to support patients? Researchers will investigate the effects of using a chatbot to support follow-up care for patients in opioid use recovery. Participants will: * Receive access to a chatbot for 12 weeks that they can use to prepare for upcoming clinical appointments, find community resources, learn about urge-surfing and wellness techniques, and query for assistance with other recovery-related information and tasks * Complete surveys and provide user feedback
The research team would like to test how efficacious an artificial intelligence chatbot is in delivering supportive behavioral interventions in populations with anxiety, depression, or eating concerns.
The purpose of this study is to develop a chatbot intervention to promote PrEP awareness and uptake among Black men who have sex with men (MSM) in the Southern United States.
The goal of this project is to test the efficacy of a chatbot intervention for reducing HPV vaccine hesitancy among African American parents. An online experiment will be conducted to test the effectiveness of the chatbot intervention with African American parents. Results of this project will inform future communication interventions for reducing vaccine hesitancy among African American parents.
Unhealthy sleep and cardiometabolic risk are two major public health concerns in emerging Black/African American (BAA) adults. Evidence-based sleep interventions such as cognitive-behavioral therapy for insomnia (CBT-I) are available but not aligned with the needs of this at-risk group. Innovative work on the development of an artificial intelligence sleep chatbot using CBT-I guidelines will provide scalable and efficient sleep interventions for emerging BAA adults.
The purpose of this project is to identify effective strategies to assist survivors of childhood and young adult cancers (diagnosed between birth and age 39) who have not returned for follow-up cancer care for 3 or more years, to reengage with the health care system. The investigator will evaluate the effect of a novel, bidirectional conversational agent ("Penny"), compared to usual care, to assist patients with scheduling appointments, lab work as well as scans and specialty appointments as needed.
This study aims to empirically test the theoretical mechanisms of relational perceptions in the context of building and testing a relational artificial intelligence (AI) chatbot for improving physical activity (PA) behaviors among a sedentary adult population in the U.S. The aim of the study is to build and experimentally test relational capacities of AI chatbot in inducing positive human-AI relationship and leading to higher PA behavior change intention. During the 7-day intervention, the relational chatbot will educate participants on physical activity using 5 types of relational messages during a PA intervention including 1) social dialogue, 2) empathy, 3) self-disclosure, 4) meta-relational communication, and 5) humor. On the other hand, the non-relational chatbot will only deliver PA intervention messages, without relational cues. Relational chatbot condition will be compared to the non-relational chatbot condition to assess its effectiveness. The objective of this study is to test the efficacy of the mobile app intervention leveraging chatbots in increasing participants' relationship perception and physical activity behavior change.
In this study, the investigators aim to compare a mobile health platform, known as a 'chatbot,' that leverages artificial intelligence and natural language processing to scale communication, to 'usual care' that patients would receive. This comparison will enable the investigators to determine if the chatbot system can improve rates of recommendation for genetic testing among patients at elevated risk of harboring a familial cancer syndrome in an all-Medicaid gynecology clinic. Furthermore, the investigators aim to evaluate facilitators of inequity in regard to patient access to and utilization of genetic testing services.
In this prospective quality improvement study, we will develop and evaluate the feasibility and acceptability of an online patient self-reported G8 screening tool which will allow us to efficiently identify G8 positive older cancer patients to be referred to our Senior Adult Oncology Center (SAOC) for a Comprehensive Geriatric Assessment (CGA).
Evaluate the feasibility of using a chatbot combined with continuous activity monitoring to proactively identify, appropriately triage and help manage patients' symptoms during cancer treatment Determine whether such an early outpatient clinic-based intervention can decrease rates of excess triage visits Correlate changes in activity and early symptom management to emergency department visits, unplanned inpatient hospitalizations and treatment breaks
There has been a dramatic paradigm shift over the last 25 years within cancer care due to the onset of many new targeted therapies and a transition from inpatient to outpatient care. Hand in hand with this shift has been the increased development and use of oral anti-cancer drugs, including cytotoxic chemotherapies that patients self-administer at home versus administration of an intravenous product at an infusion center. One of the main drivers for the growth and popularity of oral chemotherapy has been patient preference. However, an incorrect assumption exists among patients that oral therapy is associated with minimal side effects. According to the 2008 NCCN Task Force Report on Oral Chemotherapy, "some patients may incorrectly assume that oral chemotherapy is not "real" chemotherapy and is more akin to taking a vitamin or antibiotic. Furthermore, patients must understand that oral equivalents of cytotoxic therapies, such as capecitabine, have side effects that are similar to their parenteral counterparts in this case, fluorouracil. The need to monitor for side effects and titrate dosages increases the complexity of oral chemotherapy regimens". Self-administration of these complex oral therapies causes patients to become more autonomous in their care, without medical supervision of doses between office visits. Due to the lack of oversight, there is a concern of compromised efficacy if patients take less than the prescribed doses, or increased, sometimes life-threatening, toxicity, often between office visits, if more than the prescribed dose is taken. Both daily dose and schedule can be complicated for patients to comprehend and follow. Capecitabine is a particularly complex oral chemotherapy, with 2 pill dose sizes, dosing by Body Surface Area (BSA), twice a day dosing, and days of on therapy and days off of therapy. For this reason, capecitabine has been chosen as the backbone for regimens that will be studied. As noted in section 5.3 capecitabine might be combined with other oral chemotherapies, Parenteral chemotherapy or radiation therapy. The investigators believe there is an opportunity in this space to improve oral chemotherapy adherence by walking patients through how and when to take their oral therapies remotely, as well as to better manage toxicity by gathering more information from the patient during their treatment.
Eating disorders (EDs) are serious mental illnesses associated with high morbidity and mortality, clinical impairment, and comorbid psychopathology. Although evidence-based treatments for EDs have been established, the treatment gap is wide. Indeed, \<20% of individuals with EDs receive treatment. There is need for a novel solution not only to identify individuals with EDs but also to encourage mental health services use and to address treatment barriers. This study aims to implement a conversational agent or "chatbot" that is optimized to increase mental health services use among individuals with EDs through such features as: 1) education on the seriousness and consequences of EDs; 2) engaging the user in motivational interviewing to overcome barriers to care; 3) providing a personalized recommendation for seeking intervention; 4) repeated check-ins with the user to encourage follow-up with care. This study will utilize a randomized optimization trial with adults who have completed screening on the National Eating Disorders Association (NEDA) website and screen positive for an ED but are not in treatment to determine chatbot feasibility and to generate data on the effect of the chatbot on motivation for treatment and mental health services use. This trial will employ the Multiphase Optimization Strategy framework, using a 2\^4 full factorial design, to randomly assign participants to a combination of the four proposed intervention components (n=16 conditions) to isolate the active ingredients.
A wide gap exists between the number of people needing alcohol treatment and those actually receiving it. This study builds on a previous one that indicated that smartphone-based intervention can help increase the number of people who receive alcohol intervention services and decrease treatment barriers. Improvements to the previously developed app, Step Away, will be made. In addition, a new method of delivering the Step Away intervention via an online, interactive chatbot, will be developed with the goal of improving engagement and effectiveness. Participants will be recruited and outcomes between the two interventions examined to determine if the Step Away chatbot has enhanced user engagement, intervention fidelity and outcome efficacy in comparison to the Step Away app amongst a group of problem drinkers. Participants will also be interviewed to determine their perceptions of both interventions with a view towards understanding barriers to user engagement.
The goal of this research is to bridge a significant "effectiveness" gap in the treatment of depression. The investigators have developed a chatbot which will assist in performing measurement-based care (MBC) via Facebook Messenger. Participants will be randomized to either Usual Care or Usual Care with additional Chatbot Care.
To evaluate the impact of AI-powered chatbot interactions versus traditional educational handouts on increasing participants' knowledge of oral cancer and its prevention
The purpose of this research study is to refine customized in-app notifications in order to optimize users' experience with a mobile app called Wysa for Chronic Pain. This app is designed to support people who have chronic pain and who also experience symptoms of depression and/or anxiety. This version of the app is not currently available to the public. Eligible participants will be asked to download and use the Wysa for Chronic Pain study app for several weeks, and to use it as they normally would if they were not part of a research study. At the beginning and end of the study period, participants will be asked to complete brief surveys about their mood, pain, physical function, and sleep. Additionally, a few participants will be asked to share their experience with the study app at the end of the research study in a casual interview using a secure audio/video recorded call. Participating in the interview portion is optional.
The purpose of this study is to determine the feasibility of a conversational artificial intelligence (AI) system to have a meaningful clinical conversation with a patient prior to an urgent care visit with their primary care physician. In this study, patients who are seeking an urgent care visit (that is, any type of medical visit with their primary care provider for a new complaint) will first have a conversation with an AI system. This interaction with the AI system will happen less than a week before their visit with their physician, and will be supervised by an independent physician who will interrupt in case there are any concerns about patient safety. After the interaction, a summary of the conversation will be sent to the patient's PCP, who will review prior to the in-person visit. The researchers will investigate: * Patient views on the AI system * PCP views on the AI system * Overall safety, as measured by the physician safety supervisor * Quality of clinical conversations, measured by standardized rubrics * Quality of diagnostic and management plans generated by the AI; these will not be shared with the patient or physician, but will be generated after the fact and compared with the actual diagnosis and management plan.
This feasibility pilot trial seeks to examine the feasibility and target engagement of a coping skills and psychoeducational intervention delivered via an automated conversational chatbot named SMILEY in reducing frequency and stress associated with online victimization among marginalized youth, including those who are Black, Hispanic, and LGBTQ+, and experiencing depression and online victimization. The primary inquiry of this study is whether SMILEY can enhance the safety and decrease stress levels in online environments for marginalized youth coping with depression and online victimization. Participants will engage with materials, including interactive web resources, to learn safe social media practices and provide coping skills for experiencing online victimization. These materials will cover topics such as managing online time, addressing negative comments, and fostering positive connections. Participants will interact with SMILEY at their own pace over 4 weeks. This interaction will provide information and guidance on dealing with online victimization and the associated stress.
Building on our successful pilot work to develop a Motivational Interviewing (MI)-capable chatbot and cessation coach, the investigators propose to address the problems of intrinsic motivation and social barriers to smoking cessation by evaluating a highly scalable and easily accessible digital-coaching intervention that 1) promotes readiness to change using a technology-assisted MI (TAMI) chatbot, 2) provides compelling and accessible multilingual education about smoking cessation tools, and 3) develops a tailored quit plan addressing social barriers to treatment initiation and sustainment.
The overarching goal of this study is to establish initial proof of mechanism for precision interventions in an adult population.
This study seeks to enhance genetic education and increase the uptake of genetic testing for hereditary cancer risk among cancer survivors. The study will focus on the feasibility and acceptability of a digital intervention designed to improve cancer genomic care. The study objectives are to: 1. Finalize the development and optimize the usability of the CATALYST digital intervention (also known as the relational assistant \[RA\]). 2. Evaluate the feasibility and acceptability of a streamlined cancer genomic care delivery model for cancer survivors. Participants will be randomized to one of two study arms: the RA intervention arm or the enhanced usual care (EUC) arm. 3. Assess the uptake of genetic counseling (GC) and genetic testing (GT) and conduct a process evaluation to identify barriers and facilitators to GC, GT, and engagement with the CATALYST intervention and the RA.
The goal of this observational study is to increase genetic education and genetic testing for hereditary cancer risk among Black cancer survivors. The study will: 1. Test the effectiveness of a chatbot intervention (also called relational agent, or RA) vs. enhanced usual care (EUC) on engagement in genetic education and requests for genetic testing. 2. Evaluate the impact of the chatbot vs. EUC on the process that participants use to make decisions and evaluate effects on well-being (also called psychosocial outcomes). 3. Explore the ways (methods) that influence how participants experience the intervention. The main questions this study aims to answer are which group - the chatbot (RA) group or the EUC group - is more likely to request genetic testing and which group is more likely to get (engage with) genetic education. Participants will be randomly assigned to either the chatbot (RA) group or EUC group. This means each participant has an equal chance of being placed in either group, just like flipping a coin. Each group will receive genetic education and have an opportunity to request genetic testing. Researchers will compare the chatbot (RA) group and the EUC group to see which may request more GT (genetic testing) and which group engages more with genetic education.