Background: Depression is a growing concern among university students. Chatbots provide flexible, accessible, personalized psychosocial support. Delivering Mindfulness-Based Stress Reduction (MBSR) sessions via chatbots may reduce depressive symptoms in university students. Aim: This study aims to evaluate the feasibility, acceptability, safety, and preliminary efficacy of a chatbot-based MBSR intervention for university students with depressive symptoms. Methods: A rule-based MBSR chatbot was developed and evaluated with a single-group pretest–posttest study for university students in Hong Kong ( N = 30) reporting depressive symptoms, followed by the collection of their subjective feedback. The intervention lasted eight weeks. The primary clinical outcome was depression levels, with a range of secondary outcomes. Results: The chatbot-based MBSR program demonstrated satisfying recruitment, retention, and adherence rates. The safety of the program was confirmed by the absence of any adverse events directly related to the intervention, tracked from the onset of the intervention to the completion of data assessment. Significant improvements were observed in both primary and secondary outcomes. Participant feedback highlighted the benefits of the program and its effects on depressive symptoms. Conclusions: The program has shown feasibility, acceptability, safety, and preliminary efficacy in reducing depressive symptoms among 30 university students in Hong Kong. The intervention should now be evaluated in a randomized controlled trial with follow-up. This study highlights the potential role of chatbot-based interventions in mental health promotion, nursing, and clinical practice and will inform the subsequent development of innovative digital interventions to address mental health challenges faced by university students.

Vaccine hesitancy is one of the top ten threats to global health. Artificial intelligence-driven chatbots and motivational interviewing skills show promise in addressing vaccine hesitancy. This study aimed to develop and validate an artificial intelligence-driven motivational digital assistant in decreasing COVID-19 vaccine hesitancy among Hong Kong adults. The intervention development and validation were guided by the Medical Research Council’s framework with four major steps: logic model development based on theory and qualitative interviews (n = 15), digital assistant development, expert evaluation (n = 5), and a pilot test (n = 12). The Vaccine Hesitancy Matrix model and qualitative findings guided the development of the intervention logic model and content with five web-based modules. An artificial intelligence-driven chatbot tailored to each module was embedded in the website to motivate vaccination intention using motivational interviewing skills. The content validity index from expert evaluation was 0.85. The pilot test showed significant improvements in vaccine-related health literacy (p = 0.021) and vaccine confidence (p = 0.027). This digital assistant is effective in improving COVID-19 vaccine literacy and confidence through valid educational content and motivational conversations. The intervention is ready for testing in a randomized controlled trial and has high potential to be a useful toolkit for addressing ambivalence and facilitating informed decision making regarding vaccination.

Introduction: There is a considerably large group of community-dwelling spinal cord injury (SCI) survivors living with low quality of life. Physical inactivity, depression, and chronic pain are major problems faced by SCI survivors discharged from the acute phase of treatment or inpatient rehabilitation. This study aims to evaluate the feasibility, acceptability, and preliminary effects of a Physical-Psychological Integrative (PPI) online group intervention on community-dwelling SCI survivors’ physical activity, depression, and chronic pain. Methods: This is a two-arm pilot randomized controlled trial with repeated measures (pre-, post-intervention, and 3-month follow-up) design. Seventy-two participants will be randomly assigned to two study groups. The PPI intervention group will receive a video program for physical activity training and eight-week online group psychological interventions using skills of group-based motivational interviewing and mindfulness-based stress reduction. The control group will receive an eight-week online didactic education programed. Focus-group interviews will be conducted post-intervention to explore their views about acceptance and suggested improvements to the intervention. The feasibility of study procedures and the acceptability of interventions will be evaluated. The effectiveness of the PPI intervention will be evaluated by leisure-time physical activity, depression, chronic pain, exercise efficacy, mindfulness, and quality of life. We will use the generalized estimating equation to assess intervention effects and content analysis for interview data. This study has received ethical approval from the Hong Kong Polytechnic University (HSEARS20210705004) and was registered in ClinicalTrials.gov (NCT05535400). Discussion: This study will be the first to provide empirical data on the evaluation of an online-group intervention integrating both physical activity promotion and psychological approaches, aimed at reducing physical inactivity, depression, and chronic pain for community-dwelling SCI survivors in Hong Kong. The findings could provide evidence supporting the use of PPI intervention as a novel online group support, in addressing both the physical and psychological needs of community-dwelling SCI survivors.

Background: Attitude-targeted interventions are important approaches for promoting vaccination. Educational approaches alone cannot effectively cultivate positive vaccine attitudes. Artificial intelligence (AI)–driven chatbots and motivational interviewing (MI) techniques show high promise in improving vaccine attitudes and facilitating readiness for vaccination. Objective: This study aimed to evaluate the effectiveness of a theory and evidence-based, MI-oriented AI digital assistant in improving COVID-19 vaccine attitudes among adults in Hong Kong. Methods: This 2 parallel-armed randomized controlled trial was conducted from October 2022 to June 2024. Hong Kong adults (N=177) who were vaccine-hesitant were randomly assigned into 2 study groups. The intervention group (n=91) interacted with the AI digital assistant over 5 weeks, including receiving a web-based education program comprising 5 educational modules and communicating with an AI-driven chatbot equipped with MI techniques. The control group (n=86) received WhatsApp (Meta) messages directing them to government websites for COVID-19 vaccine information and knowledge, with the same dosage as the intervention group. Primary outcomes included vaccine hesitancy. Secondary outcomes included vaccine readiness, confidence, trust in government, and health literacy. Outcomes were measured at baseline, postintervention, 3-month, and 6-month follow-up. Focus group interviews were conducted postintervention. Intervention effects were analyzed using the generalized estimating equation model. Interview data were content analyzed. Results: Decreases in vaccine hesitancy were observed while no statistically significant time-by-group interaction effects were found. The intervention showed significant time-by-group interaction effects on vaccine readiness (P=.04), confidence (P=.02), and trust in government (P=.04). Significant between-group differences with medium effect sizes were identified for vaccine readiness (Cohen d=0.52) and trust in government (Cohen d=0.54) postintervention, respectively. Increases in vaccine-related health literacy were observed, and a significant time effect was found (P=.01). In total, three categories were summarized from interview data: (1) improved vaccine literacy, confidence, and trust in government; (2) hesitancy varied while readiness improved; and (3) facilitators, barriers, and recommendations of modifications on the intervention. Conclusions: The intervention indicated promising yet significant effects on vaccine readiness while the effects on vaccine hesitancy require further confirmation. The qualitative findings; however, further consolidate the significant effects on participants’ attitudes toward vaccines. The findings provide novel evidence to encourage the adoption and refinement of a MI-oriented AI digital assistant in vaccine promotion.