Co-developing a Mental Health and Wellbeing Chatbot With and for Young People

Young peoples' reflections about using a chatbot to promote their mental wellbeing in northern periphery areas - a qualitative study

An international research collaboration with researchers from northern Sweden, Finland, Ireland, Northern Ireland, Scotland and developed the ChatPal chatbot to explore the possibility of a multilingual chatbot to promote mental wellbeing in people of all ages. In Sweden the end users were young people. The aim of the current study was to explore and discuss Swedish young peoples' experiences of using a chatbot designed to promote their mental wellbeing. Young people aged 15-19 filled out an open-ended survey giving feedback on the ChatPal chatbot and their suggestions on improvements. A total of 122 survey responses were analysed. The qualitative content analysis of the survey responses resulted in three themes each containing two to three sub-themes. Theme 1, feeling as if someone is there when needed, which highlighted positive aspects regarding availability and accessibility. Theme 2, human-robot interaction has its limitations, which included aspects such as unnatural and impersonal conversations and limited content availability. Theme 3, usability can be improved, given technical errors due to lack of internet connection and difficulty navigating the chatbot were brought up as issues. The findings are discussed, and potential implications are offered for those designing and developing digital mental health technologies for young people.

Effects of a Chatbot-Based Intervention on Stress and Health-Related Parameters in a Stressed Sample: Randomized Controlled Trial

BACKGROUND

Stress levels and the prevalence of mental disorders in the general population have been rising in recent years. Chatbot-based interventions represent novel and promising digital approaches to improve health-related parameters. However, there is a lack of research on chatbot-based interventions in the area of mental health.

OBJECTIVE

The aim of this study was to investigate the effects of a 3-week chatbot-based intervention guided by the chatbot ELME, specifically with respect to the ability to reduce stress and improve various health-related parameters in a stressed sample.

METHODS

In this multicenter two-armed randomized controlled trial, 118 individuals with medium to high stress levels were randomized to the intervention group (n=59) or the treatment-as-usual control group (n=59). The ELME chatbot guided participants of the intervention group through 3 weeks of training based on the topics stress, mindfulness, and interoception, with practical and psychoeducative elements delivered in two daily interactive intervention sessions via a smartphone (approximately 10-20 minutes each). The primary outcome (perceived stress) and secondary outcomes (mindfulness; interoception or interoceptive sensibility; subjective well-being; and emotion regulation, including the subfacets reappraisal and suppression) were assessed preintervention (T1), post intervention (T2; after 3 weeks), and at follow-up (T3; after 6 weeks). During both conditions, participants also underwent ecological momentary assessments of stress and interoceptive sensibility.

RESULTS

There were no significant changes in perceived stress (β03=-.018, SE=.329; P=.96) and momentary stress. Mindfulness and the subfacet reappraisal significantly increased in the intervention group over time, whereas there was no change in the subfacet suppression. Well-being and momentary interoceptive sensibility increased in both groups over time.

CONCLUSIONS

To gain insight into how the intervention can be improved to achieve its full potential for stress reduction, besides a longer intervention duration, specific sample subgroups should be considered. The chatbot-based intervention seems to have the potential to improve mindfulness and emotion regulation in a stressed sample. Future chatbot-based studies and interventions in health care should be designed based on the latest findings on the efficacy of rule-based and artificial intelligence-based chatbots.

TRIAL REGISTRATION

German Clinical Trials Register DRKS00027560; https://drks.de/search/en/trial/DRKS00027560.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-doi.org/10.3389/fdgth.2023.1046202.

Use of automated conversational agents in improving young population mental health: a scoping review

Automated conversational agents (CAs) emerged as a promising solution in mental health interventions among young people. Therefore, the objective of this scoping review is to examine the current state of research into fully automated CAs mediated interventions for the emotional component of mental health among young people. Selected databases were searched in March 2023. Included studies were primary research, reporting on development, feasibility/usability, or evaluation of fully automated CAs as a tool to improve the emotional component of mental health among young population. Twenty-five studies were included (N = 1707). Most automated CAs applications were standalone preventions targeting anxiety and depression. Automated CAs were predominantly AI-based chatbots, using text as the main communication channel. Overall, the results of the current scoping review showed that automated CAs mediated interventions for emotional problems are acceptable, engaging and with high usability. However, the results for clinical efficacy are far less conclusive, since almost half of evaluation studies reported no significant effect on emotional mental health outcomes. Based on these findings, it can be concluded that there is a pressing need to improve the existing automated CAs applications to increase their efficacy as well as conducting more rigorous methodological research in this area.

Systematic Review: Patient and Public Involvement of Children and Young People in Mental Health Research

OBJECTIVE

Patient and public involvement (PPI) is an essential ethical component in mental health research, and represents a major opportunity to improve translational mental health research. The goals of this review were to (1) provide a comprehensive overview of empirical research focusing on PPI of children and young people (CYP) in mental health research studies; (2) evaluate the results with CYP and parents of those affected; and (3) derive recommendations for PPI of CYP in future mental health research studies.

METHODS

Based on an extensive literature review following the PRISMA guidelines, studies including CYP (age range: 0-21 years) in mental health research were identified and examined along a two-part analysis process considering their usability for mental health research. The conclusions drawn from the studies concerning CYP involvement were summarized and recommendations derived.

RESULTS

Overall, 19 articles reported PPI of CYP (age range: 10-26 years) in mental health research and were included for further analyses. The integrated studies differed in the type of PPI, and in the way the participation and involvement processes were presented.

CONCLUSION

Progress has been made in engaging CYP in mental health research, but there is a need for international standards, operationalization, and evaluation measures. Future research should go beyond merely reporting the PPI process itself. It should clearly indicate how and to what extent feedback from these PPI members was incorporated throughout the research process.

Adapting and Evaluating an AI-Based Chatbot Through Patient and Stakeholder Engagement to Provide Information for Different Health Conditions: Master Protocol for an Adaptive Platform Trial (the MARVIN Chatbots Study)

BACKGROUND

Artificial intelligence (AI)-based chatbots could help address some of the challenges patients face in acquiring information essential to their self-health management, including unreliable sources and overburdened health care professionals. Research to ensure the proper design, implementation, and uptake of chatbots is imperative. Inclusive digital health research and responsible AI integration into health care require active and sustained patient and stakeholder engagement, yet corresponding activities and guidance are limited for this purpose.

OBJECTIVE

In response, this manuscript presents a master protocol for the development, testing, and implementation of a chatbot family in partnership with stakeholders. This protocol aims to help efficiently translate an initial chatbot intervention (MARVIN) to multiple health domains and populations.

METHODS

The MARVIN chatbots study has an adaptive platform trial design consisting of multiple parallel individual chatbot substudies with four common objectives: (1) co-construct a tailored AI chatbot for a specific health care setting, (2) assess its usability with a small sample of participants, (3) measure implementation outcomes (usability, acceptability, appropriateness, adoption, and fidelity) within a large sample, and (4) evaluate the impact of patient and stakeholder partnerships on chatbot development. For objective 1, a needs assessment will be conducted within the setting, involving four 2-hour focus groups with 5 participants each. Then, a co-construction design committee will be formed with patient partners, health care professionals, and researchers who will participate in 6 workshops for chatbot development, testing, and improvement. For objective 2, a total of 30 participants will interact with the prototype for 3 weeks and assess its usability through a survey and 3 focus groups. Positive usability outcomes will lead to the initiation of objective 3, whereby the public will be able to access the chatbot for a 12-month real-world implementation study using web-based questionnaires to measure usability, acceptability, and appropriateness for 150 participants and meta-use data to inform adoption and fidelity. After each objective, for objective 4, focus groups will be conducted with the design committee to better understand their perspectives on the engagement process.

RESULTS

From July 2022 to October 2023, this master protocol led to four substudies conducted at the McGill University Health Centre or the Centre hospitalier de l'Université de Montréal (both in Montreal, Quebec, Canada): (1) MARVIN for HIV (large-scale implementation expected in mid-2024), (2) MARVIN-Pharma for community pharmacists providing HIV care (usability study planned for mid-2024), (3) MARVINA for breast cancer, and (4) MARVIN-CHAMP for pediatric infectious conditions (both in preparation, with development to begin in early 2024).

CONCLUSIONS

This master protocol offers an approach to chatbot development in partnership with patients and health care professionals that includes a comprehensive assessment of implementation outcomes. It also contributes to best practice recommendations for patient and stakeholder engagement in digital health research.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05789901; https://classic.clinicaltrials.gov/ct2/show/NCT05789901.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/54668.

An Integrative Survey on Mental Health Conversational Agents to Bridge Computer Science and Medical Perspectives

Mental health conversational agents (a.k.a. chatbots) are widely studied for their potential to offer accessible support to those experiencing mental health challenges. Previous surveys on the topic primarily consider papers published in either computer science or medicine, leading to a divide in understanding and hindering the sharing of beneficial knowledge between both domains. To bridge this gap, we conduct a comprehensive literature review using the PRISMA framework, reviewing 534 papers published in both computer science and medicine. Our systematic review reveals 136 key papers on building mental health-related conversational agents with diverse characteristics of modeling and experimental design techniques. We find that computer science papers focus on LLM techniques and evaluating response quality using automated metrics with little attention to the application while medical papers use rule-based conversational agents and outcome metrics to measure the health outcomes of participants. Based on our findings on transparency, ethics, and cultural heterogeneity in this review, we provide a few recommendations to help bridge the disciplinary divide and enable the cross-disciplinary development of mental health conversational agents.

Assessing acceptability and effectiveness of a pleasure-oriented sexual and reproductive health chatbot in Kenya: an exploratory mixed-methods study

Integrating pleasure may be a successful strategy for reaching young people with sexual and reproductive health and rights (SRHR) interventions. However, sexual pleasure-related programming and research remains sparse. We aimed to assess chatbot acceptability and describe changes in SRHR attitudes and behaviours among Kenyan young adults engaging with a pleasure-oriented SRHR chatbot. We used an exploratory mixed-methods study design. Between November 2021 and January 2022, participants completed a self-administered online questionnaire before and after chatbot engagement. In-depth phone interviews were conducted among a select group of participants after their initial chatbot engagement. Quantitative data were analysed using paired analyses and interviews were analysed using thematic content analysis. Of 301 baseline participants, 38% (115/301) completed the endline survey, with no measured baseline differences between participants who did and did not complete the endline survey. In-depth interviews were conducted among 41 participants. We observed higher satisfaction at endline vs. baseline on reported ability to exercise sexual rights (P ≤ 0.01), confidence discussing contraception (P ≤ 0.02) and sexual feelings/needs (P ≤ 0.001) with their sexual partner(s). Qualitative interviews indicated that most participants valued the chatbot as a confidential and free-of-judgment source of trustworthy "on-demand" SRHR information. Participants reported improvements in sex-positive communication with partners and safer sex practices due to new learnings from the chatbot. We observed increases in SRHR empowerment among young Kenyans after engagement with the chatbot. Integrating sexual pleasure into traditional SRHR content delivered through digital tools is a promising strategy to advance positive SRHR attitudes and practices among youth.

Harnessing Artificial Intelligence: Strategies for Mental Health Nurses in Optimizing Psychiatric Patient Care

This narrative review explores the transformative impact of Artificial Intelligence (AI) on mental health nursing, particularly in enhancing psychiatric patient care. AI technologies present new strategies for early detection, risk assessment, and improving treatment adherence in mental health. They also facilitate remote patient monitoring, bridge geographical gaps, and support clinical decision-making. The evolution of virtual mental health assistants and AI-enhanced therapeutic interventions are also discussed. These technological advancements reshape the nurse-patient interactions while ensuring personalized, efficient, and high-quality care. The review also addresses AI's ethical and responsible use in mental health nursing, emphasizing patient privacy, data security, and the balance between human interaction and AI tools. As AI applications in mental health care continue to evolve, this review encourages continued innovation while advocating for responsible implementation, thereby optimally leveraging the potential of AI in mental health nursing.

Artificial Intelligence-Based Chatbots for Promoting Health Behavioral Changes: Systematic Review

BACKGROUND

Artificial intelligence (AI)-based chatbots can offer personalized, engaging, and on-demand health promotion interventions.

OBJECTIVE

The aim of this systematic review was to evaluate the feasibility, efficacy, and intervention characteristics of AI chatbots for promoting health behavior change.

METHODS

A comprehensive search was conducted in 7 bibliographic databases (PubMed, IEEE Xplore, ACM Digital Library, PsycINFO, Web of Science, Embase, and JMIR publications) for empirical articles published from 1980 to 2022 that evaluated the feasibility or efficacy of AI chatbots for behavior change. The screening, extraction, and analysis of the identified articles were performed by following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines.

RESULTS

Of the 15 included studies, several demonstrated the high efficacy of AI chatbots in promoting healthy lifestyles (n=6, 40%), smoking cessation (n=4, 27%), treatment or medication adherence (n=2, 13%), and reduction in substance misuse (n=1, 7%). However, there were mixed results regarding feasibility, acceptability, and usability. Selected behavior change theories and expert consultation were used to develop the behavior change strategies of AI chatbots, including goal setting, monitoring, real-time reinforcement or feedback, and on-demand support. Real-time user-chatbot interaction data, such as user preferences and behavioral performance, were collected on the chatbot platform to identify ways of providing personalized services. The AI chatbots demonstrated potential for scalability by deployment through accessible devices and platforms (eg, smartphones and Facebook Messenger). The participants also reported that AI chatbots offered a nonjudgmental space for communicating sensitive information. However, the reported results need to be interpreted with caution because of the moderate to high risk of internal validity, insufficient description of AI techniques, and limitation for generalizability.

CONCLUSIONS

AI chatbots have demonstrated the efficacy of health behavior change interventions among large and diverse populations; however, future studies need to adopt robust randomized control trials to establish definitive conclusions.

Development of a chatbot for depression: adolescent perceptions and recommendations

BACKGROUND

Chatbots are a relatively new technology that has shown promising outcomes for mental health symptoms in adults; however, few studies have been done with adolescents or reported adolescent user experiences and recommendations for chatbot development.

METHODS

Twenty three participants ages 13-18 (M_age  = 14.96) engaged in user testing of a chatbot developed to psychoeducate adolescents on depression, teach behavioral activation, and change negative thoughts. Thematic analysis was conducted of participants' responses to user experience questions, impressions, and recommendations.

RESULTS

Over half (56.5%) of the sample completed the full intervention and provided user experience feedback online. The average NPS score was 6.04 (SD = 2.18), and 64.3% (n = 9) said they would use the chatbot in the future. Of all user experience responses, 54.5% were positive. The most common impressions were related to symptom improvement (61.1%) and availability (52.8%) The most frequent recommendations were related to solving technical problems (66%).

CONCLUSIONS

Chatbots for mental health are acceptable to some adolescents, a population that tends to be reluctant to engage with traditional mental health services. Most participants reported positive experiences with the chatbot, believing that it could help with symptom improvement and is highly available. Adolescents highlighted some technical and stylistic problems that developers should consider. More pilot and user testing is needed to develop mental health chatbots that are appealing and relevant to adolescents.

Chatbot features for anxiety and depression: A scoping review

Chatbots can provide valuable support to patients in assessing and guiding management of various health problems particularly when human resources are scarce. Chatbots can be affordable and efficient on-demand virtual assistants for mental health conditions, including anxiety and depression. We review features of chatbots available for anxiety or depression. Six bibliographic databases were searched including backward and forwards reference list checking. The initial search returned 1302 citations. Post-filtering, 42 studies remained forming the final dataset for this scoping review. Most of the studies were from conference proceedings (62%, 26/42), followed by journal articles (26%, 11/42), reports (7%, 3/42), or book chapters (5%, 2/42). About half of the reviewed chatbots had functionality targeting both anxiety and depression (60%, 25/42), whereas 38% (16/42) targeted only depression, 38% (16/42) anxiety and the remaining addressed other mental health issues along with anxiety and depression. Avatars or fictional characters were rarely used in these studies only 26% (11/42) despite their increasing popularity. Mental health chatbots could benefit in helping patients with anxiety and depression and provide valuable support to mental healthcare workers, particularly when resources are scarce. Real-time personal virtual assistance fills in this gap. Their role in mental health care is expected to increase.

Co-design of digital health interventions with young people: A scoping review

Introduction

Innovative health promotion strategies are crucial for enhancing global quality of life and curbing premature deaths. Digital health promotion is particularly impactful for young individuals often using internet-connected devices. Collaborative methodologies in digital intervention research offer insights into supporting youth during key life stages, such as adolescence. This review sought to examine the literature on digital health interventions for youth co-designed via participatory frameworks.

Methods

Following the Joanna Briggs Institute Manual and an adapted Arksey & O'Malley's 6-stage framework, this review utilised the PRISMA-ScR checklist for structured reporting. Peer-reviewed research where young individuals (15-35 years) contributed to digital health intervention design was analysed. Systematic synthesis adhered to Braun & Clarke's Thematic Analysis Guidelines, mapping data to research queries and thematic framework.

Results

Eighteen articles were systematically synthesised, revealing seven main themes: digital tool, inquiry field, report aim, participatory activities, intervention attributes and behavioural change support. Seventeen distinctive digital health interventions were assessed, mostly within risk mitigation and mental health domains. Predominantly, interventions were web-based, with mental wellness websites emerging as the prevalent tool. User experience testing stood out as the primary reported outcome.

Conclusion

Several innovative digital health interventions targeting youth have been identified. Platforms including social media, specialised apps, websites and video games are instrumental for health advice and clinical support dissemination, overcoming access and cost barriers. Participatory techniques are integral for the efficacy of digital health resources, encompassing youth aspirations and anticipations. Continued efforts will enrich comprehension of optimal practices in digital health promotion and intervention formulation.

Language Use in Conversational Agent-Based Health Communication: Systematic Review

Background

Given the growing significance of conversational agents (CAs), researchers have conducted a plethora of relevant studies on various technology- and usability-oriented issues. However, few investigations focus on language use in CA-based health communication to examine its influence on the user perception of CAs and their role in delivering health care services.

Objective

This review aims to present the language use of CAs in health care to identify the achievements made and breakthroughs to be realized to inform researchers and more specifically CA designers.

Methods

This review was conducted by following the protocols of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 statement. We first designed the search strategy according to the research aim and then performed the keyword searches in PubMed and ProQuest databases for retrieving relevant publications (n=179). Subsequently, 3 researchers screened and reviewed the publications independently to select studies meeting the predefined selection criteria. Finally, we synthesized and analyzed the eligible articles (N=11) through thematic synthesis.

Results

Among the 11 included publications, 6 deal exclusively with the language use of the CAs studied, and the remaining 5 are only partly related to this topic. The language use of the CAs in these studies can be roughly classified into six themes: (1) personal pronouns, (2) responses to health and lifestyle prompts, (3) strategic wording and rich linguistic resources, (4) a 3-staged conversation framework, (5) human-like well-manipulated conversations, and (6) symbols and images coupled with phrases. These derived themes effectively engaged users in health communication. Meanwhile, we identified substantial room for improvement based on the inconsistent responses of some CAs and their inability to present large volumes of information on safety-critical health and lifestyle prompts.

Conclusions

This is the first systematic review of language use in CA-based health communication. The results and limitations identified in the 11 included papers can give fresh insights into the design and development, popularization, and research of CA applications. This review can provide practical implications for incorporating positive language use into the design of health CAs and improving their effective language output in health communication. In this way, upgraded CAs will be more capable of handling various health problems particularly in the context of nationwide and even worldwide public health crises.

How Far Can Conversational Agents Contribute to IBD Patient Health Care—A Review of the Literature

Modern societies are facing health and healthcare challenges as never seen before. The digital world in which we are living today considers digital health interventions such as “internet-delivered” therapy (e-Therapy) or mobile apps as an integrated part of healthcare systems. Digital transformation in health care requires the active involvement of patients as the central part of healthcare interventions. In the case of chronic health conditions, such as inflammatory bowel disease (IBD), it is believed that the adoption of new digital tools helps to maintain and extend the health and care of patients, optimizing the course of the treatment of the disease. The study goal was to undertake a literature review associating the use of chatbot technology with IBD patients' health care. This study intends to support digital product developments, mainly chatbot for IBD or other chronic diseases. The work was carried out through two literature review phases. The first one was based on a systematic approach and the second was a scoping review focused only on Frontiers Journals. This review followed a planned protocol for search and selection strategy that was created by a research team discussion. Chatbot technology for chronic disease self-management can have high acceptance and usability levels. The more interaction with a chatbot, the more patients are able to increase their self-care practice, but there is a challenge. The chatbot ontology to personalize the communication still needed to have strong guidelines helping other researchers to define which Electronic Medical Records (EMRs) should be used in the chatbots to improve the user satisfaction, engagement, and dialog quality. The literature review showed us both evidence and success of these tools in other health disorders. Some of them revealed a huge potential for conversational agents as a part of digital health interventions.

TourHeart—An Online Stratified Stepped Care Mental Health Platform: Qualitative Evaluation from Multiple Stakeholders’ Perspectives (Preprint)

Background

TourHeart, a web-based stratified stepped care mental health platform, is a one-stop solution that integrates psychoeducation and other well-being promotional tools for mental health promotion and mental illness prevention and evidence-based, low-intensity psychological interventions for the treatment of people with anxiety and depressive symptoms. Instead of focusing only on symptom reduction, the platform aims to be person-centered and recovery-oriented, and continual feedback from stakeholders is sought. Understanding the perspectives of users and service providers enables platform developers to fine-tune both the design and content of the services for enhanced service personalization and personal recovery.

Objective

This qualitative study evaluated a web-based mental health platform by incorporating the perspectives of both users and service providers who administered the platform and provided coaching services. The platform included both web-based and offline services targeting adults along the mental health spectrum based on the two-continua model of mental health and mental illness.

Methods

Interview questions were designed based on the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework (RE-AIM). Views on offline services, the design of the web-based platform, user experience, and the contents of the platform were explored using semistructured interviews. A total of 27 service users and 22 service providers were recruited using purposive criterion sampling. A hybrid thematic analysis was performed to identify salient aspects of users’ and providers’ experiences with and views of the platform.

Results

Totally, 3 broad themes (namely, the quality of the platform, drivers for platform use, and coaching services) emerged from the interview data that highlighted users’ views of and experiences with the web-based platform. The platform’s general esthetics, operations, and contents were found to be critical features and drivers for continued use. Although coaching services were indispensable, participants preferred the autonomy and anonymity associated with web-based mental health services.

Conclusions

This study highlights the importance of web-based mental health services being easy to navigate and understand, being user-centric, and providing adequate guidance in self-help. It also confirms existing design standards and recommendations and suggests that more rigorous, iterative user experience research and robust evaluation should be conducted in the future adaptation of web-based stratified stepped care services, so that they can be more personalized and better promote personal recovery.

Chatbots to Support Mental Wellbeing of People Living in Rural Areas: Can User Groups Contribute to Co-design?

Digital technologies such as chatbots can be used in the field of mental health. In particular, chatbots can be used to support citizens living in sparsely populated areas who face problems such as poor access to mental health services, lack of 24/7 support, barriers to engagement, lack of age appropriate support and reductions in health budgets. The aim of this study was to establish if user groups can design content for a chatbot to support the mental wellbeing of individuals in rural areas. University students and staff, mental health professionals and mental health service users (N = 78 total) were recruited to workshops across Northern Ireland, Ireland, Scotland, Finland and Sweden. The findings revealed that participants wanted a positive chatbot that was able to listen, support, inform and build a rapport with users. Gamification could be used within the chatbot to increase user engagement and retention. Content within the chatbot could include validated mental health scales and appropriate response triggers, such as signposting to external resources should the user disclose potentially harmful information or suicidal intent. Overall, the workshop participants identified user needs which can be transformed into chatbot requirements. Responsible design of mental healthcare chatbots should consider what users want or need, but also what chatbot features artificial intelligence can competently facilitate and which features mental health professionals would endorse.