PEACH, a smartphone- and conversational agent-based coaching intervention for intentional personality change: study protocol of a randomized, wait-list controlled trial

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.

Development and Evaluation of a Smartphone-Based Chatbot Coach to Facilitate a Balanced Lifestyle in Individuals With Headaches (BalanceUP App): Randomized Controlled Trial

BACKGROUND

Primary headaches, including migraine and tension-type headaches, are widespread and have a social, physical, mental, and economic impact. Among the key components of treatment are behavior interventions such as lifestyle modification. Scalable conversational agents (CAs) have the potential to deliver behavior interventions at a low threshold. To our knowledge, there is no evidence of behavioral interventions delivered by CAs for the treatment of headaches.

OBJECTIVE

This study has 2 aims. The first aim was to develop and test a smartphone-based coaching intervention (BalanceUP) for people experiencing frequent headaches, delivered by a CA and designed to improve mental well-being using various behavior change techniques. The second aim was to evaluate the effectiveness of BalanceUP by comparing the intervention and waitlist control groups and assess the engagement and acceptance of participants using BalanceUP.

METHODS

In an unblinded randomized controlled trial, adults with frequent headaches were recruited on the web and in collaboration with experts and allocated to either a CA intervention (BalanceUP) or a control condition. The effects of the treatment on changes in the primary outcome of the study, that is, mental well-being (as measured by the Patient Health Questionnaire Anxiety and Depression Scale), and secondary outcomes (eg, psychosomatic symptoms, stress, headache-related self-efficacy, intention to change behavior, presenteeism and absenteeism, and pain coping) were analyzed using linear mixed models and Cohen d. Primary and secondary outcomes were self-assessed before and after the intervention, and acceptance was assessed after the intervention. Engagement was measured during the intervention using self-reports and usage data.

RESULTS

A total of 198 participants (mean age 38.7, SD 12.14 y; n=172, 86.9% women) participated in the study (intervention group: n=110; waitlist control group: n=88). After the intervention, the intention-to-treat analysis revealed evidence for improved well-being (treatment: β estimate=-3.28, 95% CI -5.07 to -1.48) with moderate between-group effects (Cohen d=-0.66, 95% CI -0.99 to -0.33) in favor of the intervention group. We also found evidence of reduced somatic symptoms, perceived stress, and absenteeism and presenteeism, as well as improved headache management self-efficacy, application of behavior change techniques, and pain coping skills, with effects ranging from medium to large (Cohen d=0.43-1.05). Overall, 64.8% (118/182) of the participants used coaching as intended by engaging throughout the coaching and completing the outro.

CONCLUSIONS

BalanceUP was well accepted, and the results suggest that coaching delivered by a CA can be effective in reducing the burden of people who experience headaches by improving their well-being.

TRIAL REGISTRATION

German Clinical Trials Register DRKS00017422; https://trialsearch.who.int/Trial2.aspx?TrialID=DRKS00017422.

How Is Variety in Daily Life Related to the Expression of Personality States? An Ambulatory Assessment Study

People differ in the way they live their daily lives. For some people, daily life is characterized by multiple and diverse experiences, while others have more stability and routine in their lives. However, little is known about how variety in daily life relates to the expression of personality states. The present study examined within-person associations between variety in social partners, places, and activities with state expression. Data came from an ambulatory assessment study ( N = 962, Mage = 25.49) with four assessments per day over a period of six consecutive days. The results of the multilevel modeling analyses suggest that variety in daily life is associated with some, but not all, state expressions. For instance, on days when participants experienced a greater variety in activities, they reported being less neurotic and conscientious, but also more agreeable. In addition, the links between all social partners, places, and activities with the expression of the state were examined simultaneously to obtain more detailed information on the multifaceted nature of situation-state expression links. We conclude that variety in daily life has both theoretical and empirical relevance for the expression of personality states.

A chatbot-based intervention with ELME to improve stress and health-related parameters in a stressed sample: Study protocol of a randomised controlled trial

Background

Stress levels in the general population had already been increasing in recent years, and have subsequently been exacerbated by the global pandemic. One approach for innovative online-based interventions are "chatbots" - computer programs that can simulate a text-based interaction with human users via a conversational interface. Research on the efficacy of chatbot-based interventions in the context of mental health is sparse. The present study is designed to investigate the effects of a three-week chatbot-based intervention with the chatbot ELME, aiming to reduce stress and to improve various health-related parameters in a stressed sample.

Methods

In this multicenter, two-armed randomised controlled trial with a parallel design, a three-week chatbot-based intervention group including two daily interactive intervention sessions via smartphone (á 10-20 min.) is compared to a treatment-as-usual control group. A total of 130 adult participants with a medium to high stress levels will be recruited in Germany. Assessments will take place pre-intervention, post-intervention (after three weeks), and follow-up (after six weeks). The primary outcome is perceived stress. Secondary outcomes include self-reported interoceptive accuracy, mindfulness, anxiety, depression, personality, emotion regulation, psychological well-being, stress mindset, intervention credibility and expectancies, affinity for technology, and attitudes towards artificial intelligence. During the intervention, participants undergo ecological momentary assessments. Furthermore, satisfaction with the intervention, the usability of the chatbot, potential negative effects of the intervention, adherence, potential dropout reasons, and open feedback questions regarding the chatbot are assessed post-intervention.

Discussion

To the best of our knowledge, this is the first chatbot-based intervention addressing interoception, as well as in the context with the target variables stress and mindfulness. The design of the present study and the usability of the chatbot were successfully tested in a previous feasibility study. To counteract a low adherence of the chatbot-based intervention, a high guidance by the chatbot, short sessions, individual and flexible time points of the intervention units and the ecological momentary assessments, reminder messages, and the opportunity to postpone single units were implemented.

Trial registration

The trial is registered at the WHO International Clinical Trials Registry Platform via the German Clinical Trials Register (DRKS00027560; date of registration: 06 January 2022). This is protocol version No. 1. In case of important protocol modifications, trial registration will be updated.

Personality change through a digital-coaching intervention: Using measurement invariance testing to distinguish between trait domain, facet, and nuance change

Recent intervention research has shown that personality traits can be modified through psychological interventions. However, it is unclear whether reported effects represent changes in the trait domain or only some facets or items. Using data ( N = 552) from a recent intervention trial, the present study examined the effects of a digital-coaching intervention on self- and observer-reported personality facets and items. We focused on participants who wanted to decrease in Negative Emotionality, increase in Conscientiousness or increase in Extraversion. We used measurement invariance testing to examine which level of the trait domain hierarchy changed during the intervention. For the self-reports, we found some heterogeneity in the effects on all three trait domains, but most notably Extraversion and Conscientiousness. Specifically, participants reported to increase strongly on sociability (Extraversion), and moderately on productiveness and organization (Conscientiousness), but not on the other facets of these trait domains. Observers generally reported small but non-significant changes, with no scalar invariance violations except for Extraversion. Overall, this suggests considerable heterogeneity in intervention-related personality change that can be overlooked if only focusing on the trait domain level. We discuss the relevance of measurement invariance testing and measurement approaches for personality development and intervention research.

The Effects of Health Care Chatbot Personas With Different Social Roles on the Client-Chatbot Bond and Usage Intentions: Development of a Design Codebook and Web-Based Study

BACKGROUND

The working alliance refers to an important relationship quality between health professionals and clients that robustly links to treatment success. Recent research shows that clients can develop an affective bond with chatbots. However, few research studies have investigated whether this perceived relationship is affected by the social roles of differing closeness a chatbot can impersonate and by allowing users to choose the social role of a chatbot.

OBJECTIVE

This study aimed at understanding how the social role of a chatbot can be expressed using a set of interpersonal closeness cues and examining how these social roles affect clients' experiences and the development of an affective bond with the chatbot, depending on clients' characteristics (ie, age and gender) and whether they can freely choose a chatbot's social role.

METHODS

Informed by the social role theory and the social response theory, we developed a design codebook for chatbots with different social roles along an interpersonal closeness continuum. Based on this codebook, we manipulated a fictitious health care chatbot to impersonate one of four distinct social roles common in health care settings-institution, expert, peer, and dialogical self-and examined effects on perceived affective bond and usage intentions in a web-based lab study. The study included a total of 251 participants, whose mean age was 41.15 (SD 13.87) years; 57.0% (143/251) of the participants were female. Participants were either randomly assigned to one of the chatbot conditions (no choice: n=202, 80.5%) or could freely choose to interact with one of these chatbot personas (free choice: n=49, 19.5%). Separate multivariate analyses of variance were performed to analyze differences (1) between the chatbot personas within the no-choice group and (2) between the no-choice and the free-choice groups.

RESULTS

While the main effect of the chatbot persona on affective bond and usage intentions was insignificant (P=.87), we found differences based on participants' demographic profiles: main effects for gender (P=.04, ηp2=0.115) and age (P<.001, ηp2=0.192) and a significant interaction effect of persona and age (P=.01, ηp2=0.102). Participants younger than 40 years reported higher scores for affective bond and usage intentions for the interpersonally more distant expert and institution chatbots; participants 40 years or older reported higher outcomes for the closer peer and dialogical-self chatbots. The option to freely choose a persona significantly benefited perceptions of the peer chatbot further (eg, free-choice group affective bond: mean 5.28, SD 0.89; no-choice group affective bond: mean 4.54, SD 1.10; P=.003, ηp2=0.117).

CONCLUSIONS

Manipulating a chatbot's social role is a possible avenue for health care chatbot designers to tailor clients' chatbot experiences using user-specific demographic factors and to improve clients' perceptions and behavioral intentions toward the chatbot. Our results also emphasize the benefits of letting clients freely choose between chatbots.

Why are you (un)conscientious? The dynamic interplay of goals, states, and traits in everyday life

Personality involves both trait and state components, personal goals serving a crucial regulatory function for the expression of personality states. The present study investigates the dynamic interplay between conscientiousness-related goals, conscientious personality states, and trait conscientiousness. A sample of 244 community participants responded to a baseline survey (T1), a 5-times-a-day Ecological Momentary Assessment (EMA) for 15 days, and a post-EMA survey (T2). Pre-registered multilevel analyses indicated significant contemporaneous positive and negative associations between momentary conscientious and unconscientious goals and state conscientiousness, respectively. Cross-lagged associations also emerged, with goals predicting future states of conscientiousness. A latent growth model was fitted on a subsample of participants (N = 159). Results indicated that change in trait conscientiousness from T1 to T2 was explained by growth in conscientiousness-related goals during the EMA phase, with a mediating effect of growth in state conscientiousness. Overall, the results corroborate the importance of goals for modeling contemporaneous and cross-lagged personality dynamics, both in short and longer timeframes.

Designing Personality-Adaptive Conversational Agents for Mental Health Care

Millions of people experience mental health issues each year, increasing the necessity for health-related services. One emerging technology with the potential to help address the resulting shortage in health care providers and other barriers to treatment access are conversational agents (CAs). CAs are software-based systems designed to interact with humans through natural language. However, CAs do not live up to their full potential yet because they are unable to capture dynamic human behavior to an adequate extent to provide responses tailored to users' personalities. To address this problem, we conducted a design science research (DSR) project to design personality-adaptive conversational agents (PACAs). Following an iterative and multi-step approach, we derive and formulate six design principles for PACAs for the domain of mental health care. The results of our evaluation with psychologists and psychiatrists suggest that PACAs can be a promising source of mental health support. With our design principles, we contribute to the body of design knowledge for CAs and provide guidance for practitioners who intend to design PACAs. Instantiating the principles may improve interaction with users who seek support for mental health issues.

Personality Change Profiles and Changes in Cognition Among Middle-Aged and Older Adults

Research on the relationship between personality traits and cognitive abilities has primarily used cross-sectional designs and considered personality traits individually in relation to cognitive dimensions. This study (N = 2,652) examined the relationship between Big Five personality change profiles and change in cognitive factors, episodic memory and executive functioning. Latent profile analysis was used to capture patterns of change across the Big Five traits. Three profiles of personality change were defined: Decreasers, Maintainers, and Increasers. The Decreasers declined more in episodic memory compared to the Increasers and Maintainers. Also, the Decreasers declined more in executive functioning compared to the Increasers, but not the Maintainers. The findings advance our understanding of the links between patterns of personality change and cognitive aging.

Elena+ Care for COVID-19, a Pandemic Lifestyle Care Intervention: Intervention Design and Study Protocol

Background: The current COVID-19 coronavirus pandemic is an emergency on a global scale, with huge swathes of the population required to remain indoors for prolonged periods to tackle the virus. In this new context, individuals' health-promoting routines are under greater strain, contributing to poorer mental and physical health. Additionally, individuals are required to keep up to date with latest health guidelines about the virus, which may be confusing in an age of social-media disinformation and shifting guidelines. To tackle these factors, we developed Elena+, a smartphone-based and conversational agent (CA) delivered pandemic lifestyle care intervention. Methods: Elena+ utilizes varied intervention components to deliver a psychoeducation-focused coaching program on the topics of: COVID-19 information, physical activity, mental health (anxiety, loneliness, mental resources), sleep and diet and nutrition. Over 43 subtopics, a CA guides individuals through content and tracks progress over time, such as changes in health outcome assessments per topic, alongside user-set behavioral intentions and user-reported actual behaviors. Ratings of the usage experience, social demographics and the user profile are also captured. Elena+ is available for public download on iOS and Android devices in English, European Spanish and Latin American Spanish with future languages and launch countries planned, and no limits on planned recruitment. Panel data methods will be used to track user progress over time in subsequent analyses. The Elena+ intervention is open-source under the Apache 2 license (MobileCoach software) and the Creative Commons 4.0 license CC BY-NC-SA (intervention logic and content), allowing future collaborations; such as cultural adaptions, integration of new sensor-related features or the development of new topics. Discussion: Digital health applications offer a low-cost and scalable route to meet challenges to public health. As Elena+ was developed by an international and interdisciplinary team in a short time frame to meet the COVID-19 pandemic, empirical data are required to discern how effective such solutions can be in meeting real world, emergent health crises. Additionally, clustering Elena+ users based on characteristics and usage behaviors could help public health practitioners understand how population-level digital health interventions can reach at-risk and sub-populations.

Security, privacy, and healthcare-related conversational agents: a scoping review

Health chatbots interview patients and collect health data. This process makes demands on data security and data privacy. To identify how and to what extent security and privacy are considered in current health chatbots. We conducted a scoping review by searching three bibliographic databases (PubMed, ACM Digital Library, IEEExplore) for papers reporting on chatbots in healthcare. We extracted which, how, and where data is stored by health chatbots and identified which external services have access to the data. Out of 1026 retrieved papers, we included 70 studies in the qualitative synthesis. Most papers report on chatbots that collect and process personal health data, usually in the context of mental health coaching applications. The majority did not provide any information regarding security or privacy aspects. We were able to determine limitations in literature and identified concrete challenges, including data access and usage of (third-party) services, data storage, data security methods, use case peculiarities and data privacy, as well as legal requirements. Data privacy and security in health chatbots are still underresearched and related information is underrepresented in scientific literature. By addressing the five key challenges in future, the transfer of theoretical solutions into practice can be facilitated.

Changing personality traits with the help of a digital personality change intervention

Personality traits predict important life outcomes, such as success in love and work life, well-being, health, and longevity. Given these positive relations to important outcomes, economists, policy makers, and scientists have proposed intervening to change personality traits to promote positive life outcomes. However, nonclinical interventions to change personality traits are lacking so far in large-scale naturalistic populations. This study (n = 1,523) examined the effects of a 3-mo digital personality change intervention using a randomized controlled trial and the smartphone application PEACH (PErsonality coACH). Participants who received the intervention showed greater self-reported changes compared to participants in the waitlist control group who had to wait 1 mo before receiving the intervention. Self-reported changes aligned with intended goals for change and were significant for those desiring to increase on a trait (d = 0.52) and for those desiring to decrease on a trait (d = -0.58). Observers such as friends, family members, or intimate partners also detected significant personality changes in the desired direction for those desiring to increase on a trait (d = 0.35). Observer-reported changes for those desiring to decrease on a trait were not significant (d = -0.22). Moreover, self- and observer-reported changes persisted until 3 mo after the end of the intervention. This work provides the strongest evidence to date that normal personality traits can be changed through intervention in nonclinical samples.

Personality change and sustainability attitudes and behaviors

Withstanding the climate crisis will depend in part on individuals behaving in a more environmentally sustainable manner. However, relatively little is known about the individual factors that promote sustainable attitudes and behaviors (SABs). Although there are established cross-sectional associations between personality traits and SABs, it is unclear whether changes in personality are related to increases in SABs over time, and how personality is differentially related to specific SABs. Using data from 61,479 participants in New Zealand, we tested preregistered hypotheses about how personality codevelops with valuing the environment, believing in climate change, concern about climate change, personal environmental efficacy, personal environmental sacrifice, and support for the Green Party. We found that SABs generally increased from 2009 to 2017, although there was variation across age cohorts, SAB variables, and samples. We replicated concurrent correlations between broad personality traits—particularly Agreeableness, Openness, and Honesty/Humility—and SABs and present novel evidence that increases in SAB are related to changes in traits, particularly Agreeableness. These findings have implications for both understanding the factors associated with changes in SABs over time and understanding the factors that drive personality change.

A Digital Tool to Build the Capacity of Leaders to Improve Working Conditions Related to Psychological Health and Well-Being in Teams: Intervention Approach, Prototype, and Evaluation Design of the Web-Application "wecoach"

The “wecoach” is a web-application that builds the capacities of team leaders to improve working conditions that are positively related to the psychological health and well-being of their team members. The web-application works through an automated, rule-based chat enhanced by machine learning. This so-called conversational agent guides the team leader through a systematic project cycle, providing a mind map of work and health, training materials, self-assessments, and online tools to conduct team surveys and workshops, as well as self-evaluation of progress and effectiveness. In this paper, we present the development process of this web-application, which resulted in (1) a comprehensive intervention approach, (2) the prototype, and (3) the implementation of an evaluation design for a multi-level, randomized controlled trial.

Physicians' Perceptions of the Use of a Chatbot for Information Seeking: Qualitative Study

Background

Seeking medical information can be an issue for physicians. In the specific context of medical practice, chatbots are hypothesized to present additional value for providing information quickly, particularly as far as drug risk minimization measures are concerned.

Objective

This qualitative study aimed to elicit physicians’ perceptions of a pilot version of a chatbot used in the context of drug information and risk minimization measures.

Methods

General practitioners and specialists were recruited across France to participate in individual semistructured interviews. Interviews were recorded, transcribed, and analyzed using a horizontal thematic analysis approach.

Results

Eight general practitioners and 2 specialists participated. The tone and ergonomics of the pilot version were appreciated by physicians. However, all participants emphasized the importance of getting exhaustive, trustworthy answers when interacting with a chatbot.

Conclusions

The chatbot was perceived as a useful and innovative tool that could easily be integrated into routine medical practice and could help health professionals when seeking information on drug and risk minimization measures.

Conversational Agents in Health Care: Scoping Review and Conceptual Analysis

BACKGROUND

Conversational agents, also known as chatbots, are computer programs designed to simulate human text or verbal conversations. They are increasingly used in a range of fields, including health care. By enabling better accessibility, personalization, and efficiency, conversational agents have the potential to improve patient care.

OBJECTIVE

This study aimed to review the current applications, gaps, and challenges in the literature on conversational agents in health care and provide recommendations for their future research, design, and application.

METHODS

We performed a scoping review. A broad literature search was performed in MEDLINE (Medical Literature Analysis and Retrieval System Online; Ovid), EMBASE (Excerpta Medica database; Ovid), PubMed, Scopus, and Cochrane Central with the search terms "conversational agents," "conversational AI," "chatbots," and associated synonyms. We also searched the gray literature using sources such as the OCLC (Online Computer Library Center) WorldCat database and ResearchGate in April 2019. Reference lists of relevant articles were checked for further articles. Screening and data extraction were performed in parallel by 2 reviewers. The included evidence was analyzed narratively by employing the principles of thematic analysis.

RESULTS

The literature search yielded 47 study reports (45 articles and 2 ongoing clinical trials) that matched the inclusion criteria. The identified conversational agents were largely delivered via smartphone apps (n=23) and used free text only as the main input (n=19) and output (n=30) modality. Case studies describing chatbot development (n=18) were the most prevalent, and only 11 randomized controlled trials were identified. The 3 most commonly reported conversational agent applications in the literature were treatment and monitoring, health care service support, and patient education.

CONCLUSIONS

The literature on conversational agents in health care is largely descriptive and aimed at treatment and monitoring and health service support. It mostly reports on text-based, artificial intelligence-driven, and smartphone app-delivered conversational agents. There is an urgent need for a robust evaluation of diverse health care conversational agents' formats, focusing on their acceptability, safety, and effectiveness.

Longitudinal Experience–Wide Association Studies—A Framework for Studying Personality Change

The importance of personality for predicting life outcomes in the domains of love, work, and health is well established, as is evidence that personality traits, while relatively stable, can change. However, little is known about the sources and processes that drive changes in personality traits and how such changes might impact important life outcomes. In this paper, we make the case that the research paradigms and methodological approaches commonly used in personality psychology need to be revised to advance our understanding of the sources and processes of personality change. We propose Longitudinal Experience–Wide Association Studies as a framework for studying personality change that can address the limitations of current methods, and we discuss strategies for overcoming some of the challenges associated with Longitudinal Experience–Wide Association Studies. © 2020 European Association of Personality Psychology

A Pilot Randomized Controlled Trial to Assess the Impact of Motivational Interviewing on Initiating Behavioral Therapy for Migraine

BACKGROUND

Relaxation, biofeedback, and cognitive behavioral therapy are evidence-based behavioral therapies for migraine. Despite such efficacy, research shows that only about half of patients initiate behavioral therapy recommended by their headache specialists.

OBJECTIVE

Motivational interviewing (MI) is a widely used method to help patients explore and overcome ambivalence to enact positive life changes. We tested the hypothesis that telephone-based MI would improve initiation, scheduling, and attending behavioral therapy for migraine.

METHODS

Single-blind randomized controlled trial comparing telephone-based MI to treatment as usual (TAU). Participants were recruited during their appointments with headache specialists at two sites of a New York City medical center.

INCLUSION CRITERIA

ages from 16 to 80, migraine diagnosis by United Council of Neurologic Subspecialty fellowship trained and/or certified headache specialist, and referral for behavioral therapy for prevention in the appointment of recruitment.

EXCLUSION CRITERIA

having done behavioral therapy for migraine in the past year. Participants in the MI group received up to 5 MI calls. TAU participants were called after 3 months for general follow-up data. The prespecified primary outcome was scheduling a behavioral therapy appointment, and secondary outcomes were initiating and attending a behavioral therapy appointment.

RESULTS

76 patients were enrolled and randomized (MI = 36, TAU = 40). At baseline, the mean number of headache days was 12.0 ± 9.0. Self-reported anxiety was present for 36/52 (69.2%) and depression for 30/52 (57.7%). Follow-up assessments were completed for 77.6% (59/76, MI = 32, TAU = 27). The mean number of MI calls per participant was 2.69 ± 1.56 [0 to 5]. There was a greater likelihood of those in the MI group to initiating an appointment (22/32, 68.8% vs 11/27, 40.7%, P = .0309). There were no differences in appointment scheduling or attendance. Reasons stated for not initiating behavioral therapy were lack of time, lack of insurance/funding, prioritizing other treatments, and travel plans.

CONCLUSIONS

Brief telephone-based MI may improve rates of initiation of behavioral therapy for migraine, but other barriers appear to lessen the impact on scheduling and attending behavioral therapy appointments.

Designing a Chatbot for a Brief Motivational Interview on Stress Management: Qualitative Case Study

Background

In addition to addiction and substance abuse, motivational interviewing (MI) is increasingly being integrated in treating other clinical issues such as mental health problems. Most of the many technological adaptations of MI, however, have focused on delivering the action-oriented treatment, leaving its relational component unexplored or vaguely described. This study intended to design a conversational sequence that considers both technical and relational components of MI for a mental health concern.

Objective

This case study aimed to design a conversational sequence for a brief motivational interview to be delivered by a Web-based text messaging application (chatbot) and to investigate its conversational experience with graduate students in their coping with stress.

Methods

A brief conversational sequence was designed with varied combinations of MI skills to follow the 4 processes of MI. A Web-based text messaging application, Bonobot, was built as a research prototype to deliver the sequence in a conversation. A total of 30 full-time graduate students who self-reported stress with regard to their school life were recruited for a survey of demographic information and perceived stress and a semistructured interview. Interviews were transcribed verbatim and analyzed by Braun and Clarke’s thematic method. The themes that reflect the process of, impact of, and needs for the conversational experience are reported.

Results

Participants had a high level of perceived stress (mean 22.5 [SD 5.0]). Our findings included the following themes: Evocative Questions and Clichéd Feedback; Self-Reflection and Potential Consolation; and Need for Information and Contextualized Feedback. Participants particularly favored the relay of evocative questions but were less satisfied with the agent-generated reflective and affirming feedback that filled in-between. Discussing the idea of change was a good means of reflecting on themselves, and some of Bonobot’s encouragements related to graduate school life were appreciated. Participants suggested the conversation provide informational support, as well as more contextualized feedback.

Conclusions

A conversational sequence for a brief motivational interview was presented in this case study. Participant feedback suggests sequencing questions and MI-adherent statements can facilitate a conversation for stress management, which may encourage a chance of self-reflection. More diversified sequences, along with more contextualized feedback, should follow to offer a better conversational experience and to confirm any empirical effect.