Systematic review and meta-analysis of AI-based conversational agents for promoting mental health and well-being.
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SUBMITTER: Li H
PROVIDER: S-EPMC10730549 | biostudies-literature | 2023 Dec
REPOSITORIES: biostudies-literature
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Systematic review and meta-analysis of AI-based conversational agents for promoting mental health and well-being.
Li Han H Zhang Renwen R Lee Yi-Chieh YC Kraut Robert E RE Mohr David C DC
NPJ digital medicine 20231219 1
Conversational artificial intelligence (AI), particularly AI-based conversational agents (CAs), is gaining traction in mental health care. Despite their growing usage, there is a scarcity of comprehensive evaluations of their impact on mental health and well-being. This systematic review and meta-analysis aims to fill this gap by synthesizing evidence on the effectiveness of AI-based CAs in improving mental health and factors influencing their effectiveness and user experience. Twelve databases ...[more]
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Project description:BackgroundMental disorders cause substantial health-related burden worldwide. Mobile health interventions are increasingly being used to promote mental health and well-being, as they could improve access to treatment and reduce associated costs. Behavior change is an important feature of interventions aimed at improving mental health and well-being. There is a need to discern the active components that can promote behavior change in such interventions and ultimately improve users' mental health.ObjectiveThis study systematically identified mental health conversational agents (CAs) currently available in app stores and assessed the behavior change techniques (BCTs) used. We further described their main features, technical aspects, and quality in terms of engagement, functionality, esthetics, and information using the Mobile Application Rating Scale.MethodsThe search, selection, and assessment of apps were adapted from a systematic review methodology and included a search, 2 rounds of selection, and an evaluation following predefined criteria. We conducted a systematic app search of Apple's App Store and Google Play using 42matters. Apps with CAs in English that uploaded or updated from January 2020 and provided interventions aimed at improving mental health and well-being and the assessment or management of mental disorders were tested by at least 2 reviewers. The BCT taxonomy v1, a comprehensive list of 93 BCTs, was used to identify the specific behavior change components in CAs.ResultsWe found 18 app-based mental health CAs. Most CAs had <1000 user ratings on both app stores (12/18, 67%) and targeted several conditions such as stress, anxiety, and depression (13/18, 72%). All CAs addressed >1 mental disorder. Most CAs (14/18, 78%) used cognitive behavioral therapy (CBT). Half (9/18, 50%) of the CAs identified were rule based (ie, only offered predetermined answers) and the other half (9/18, 50%) were artificial intelligence enhanced (ie, included open-ended questions). CAs used 48 different BCTs and included on average 15 (SD 8.77; range 4-30) BCTs. The most common BCTs were 3.3 "Social support (emotional)," 4.1 "Instructions for how to perform a behavior," 11.2 "Reduce negative emotions," and 6.1 "Demonstration of the behavior." One-third (5/14, 36%) of the CAs claiming to be CBT based did not include core CBT concepts.ConclusionsMental health CAs mostly targeted various mental health issues such as stress, anxiety, and depression, reflecting a broad intervention focus. The most common BCTs identified serve to promote the self-management of mental disorders with few therapeutic elements. CA developers should consider the quality of information, user confidentiality, access, and emergency management when designing mental health CAs. Future research should assess the role of artificial intelligence in promoting behavior change within CAs and determine the choice of BCTs in evidence-based psychotherapies to enable systematic, consistent, and transparent development and evaluation of effective digital mental health interventions.
| S-EPMC10394504 | biostudies-literature
Project description:BackgroundConversational agents, which we defined as computer programs that are designed to simulate two-way human conversation by using language and are potentially supplemented with nonlanguage modalities, offer promising avenues for health interventions for different populations across the life course. There is a lack of open-access and user-friendly resources for identifying research trends and gaps and pinpointing expertise across international centers.ObjectiveOur aim is to provide an overview of all relevant evidence on conversational agents for health and well-being across the life course. Specifically, our objectives are to identify, categorize, and synthesize-through visual formats and a searchable database-primary studies and reviews in this research field.MethodsAn evidence map was selected as the type of literature review to be conducted, as it optimally corresponded to our aim. We systematically searched 8 databases (MEDLINE; CINAHL; Web of Science; Scopus; the Cochrane, ACM, IEEE, and Joanna Briggs Institute databases; and Google Scholar). We will perform backward citation searching on all included studies. The first stage of a double-stage screening procedure, which was based on abstracts and titles only, was conducted by using predetermined eligibility criteria for primary studies and reviews. An operational screening procedure was developed for streamlined and consistent screening across the team. Double data extraction will be performed with previously piloted data collection forms. We will appraise systematic reviews by using A Measurement Tool to Assess Systematic Reviews (AMSTAR) 2. Primary studies and reviews will be assessed separately in the analysis. Data will be synthesized through descriptive statistics, bivariate statistics, and subgroup analysis (if appropriate) and through high-level maps such as scatter and bubble charts. The development of the searchable database will be informed by the research questions and data extraction forms.ResultsAs of April 2021, the literature search in the eight databases was concluded, yielding a total of 16,351 records. The first stage of screening, which was based on abstracts and titles only, resulted in the selection of 1282 records of primary studies and 151 records of reviews. These will be subjected to second-stage screening. A glossary with operational definitions for supporting the study selection and data extraction stages was drafted. The anticipated completion date is October 2021.ConclusionsOur wider definition of a conversational agent and the broad scope of our evidence map will explicate trends and gaps in this field of research. Additionally, our evidence map and searchable database of studies will help researchers to avoid fragmented research efforts and wasteful redundancies. Finally, as part of the Harnessing the Power of Conversational e-Coaches for Health and Well-being Through Swiss-Portuguese Collaboration project, our work will also inform the development of an international taxonomy on conversational agents for health and well-being, thereby contributing to terminology standardization and categorization.International registered report identifier (irrid)DERR1-10.2196/26680.
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Project description:BACKGROUND:The use of conversational agent interventions (including chatbots and robots) in mental health is growing at a fast pace. Recent existing reviews have focused exclusively on a subset of embodied conversational agent interventions despite other modalities aiming to achieve the common goal of improved mental health. OBJECTIVE:This study aimed to review the use of conversational agent interventions in the treatment of mental health problems. METHODS:We performed a systematic search using relevant databases (MEDLINE, EMBASE, PsycINFO, Web of Science, and Cochrane library). Studies that reported on an autonomous conversational agent that simulated conversation and reported on a mental health outcome were included. RESULTS:A total of 13 studies were included in the review. Among them, 4 full-scale randomized controlled trials (RCTs) were included. The rest were feasibility, pilot RCTs and quasi-experimental studies. Interventions were diverse in design and targeted a range of mental health problems using a wide variety of therapeutic orientations. All included studies reported reductions in psychological distress postintervention. Furthermore, 5 controlled studies demonstrated significant reductions in psychological distress compared with inactive control groups. In addition, 3 controlled studies comparing interventions with active control groups failed to demonstrate superior effects. Broader utility in promoting well-being in nonclinical populations was unclear. CONCLUSIONS:The efficacy and acceptability of conversational agent interventions for mental health problems are promising. However, a more robust experimental design is required to demonstrate efficacy and efficiency. A focus on streamlining interventions, demonstrating equivalence to other treatment modalities, and elucidating mechanisms of action has the potential to increase acceptance by users and clinicians and maximize reach.
| S-EPMC6914342 | biostudies-literature
Project description:BackgroundArtificial intelligence (AI) is said to be "transforming mental health". AI-based technologies and technique are now considered to have uses in almost every domain of mental health care: including decision-making, assessment and healthcare management. What remains underexplored is whether/how mental health recovery is situated within these discussions and practices.MethodTaking conversational agents as our point of departure, we explore the ways official online materials explain and make sense of chatbots, their imagined functionality and value for (potential) users. We focus on three chatbots for mental health: Woebot, Wysa and Tess.Findings"Recovery" is largely missing as an overt focus across materials. However, analysis does reveal themes that speak to the struggles over practice, expertise and evidence that the concept of recovery articulates. We discuss these under the headings "troubled clinical responsibility", "extended virtue of (technological) self-care" and "altered ontologies and psychopathologies of time".ConclusionsUltimately, we argue that alongside more traditional forms of recovery, chatbots may be shaped by, and shaping, an increasingly individualised form of a "personal recovery imperative".
| S-EPMC7683843 | biostudies-literature
Project description:BackgroundRegular physical activity (PA) is crucial for well-being; however, healthy habits are difficult to create and maintain. Interventions delivered via conversational agents (eg, chatbots or virtual agents) are a novel and potentially accessible way to promote PA. Thus, it is important to understand the evolving landscape of research that uses conversational agents.ObjectiveThis mixed methods systematic review aims to summarize the usability and effectiveness of conversational agents in promoting PA, describe common theories and intervention components used, and identify areas for further development.MethodsWe conducted a mixed methods systematic review. We searched seven electronic databases (PsycINFO, PubMed, Embase, CINAHL, ACM Digital Library, Scopus, and Web of Science) for quantitative, qualitative, and mixed methods studies that conveyed primary research on automated conversational agents designed to increase PA. The studies were independently screened, and their methodological quality was assessed using the Mixed Methods Appraisal Tool by 2 reviewers. Data on intervention impact and effectiveness, treatment characteristics, and challenges were extracted and analyzed using parallel-results convergent synthesis and narrative summary.ResultsIn total, 255 studies were identified, 7.8% (20) of which met our inclusion criteria. The methodological quality of the studies was varied. Overall, conversational agents had moderate usability and feasibility. Those that were evaluated through randomized controlled trials were found to be effective in promoting PA. Common challenges facing interventions were repetitive program content, high attrition, technical issues, and safety and privacy concerns.ConclusionsConversational agents hold promise for PA interventions. However, there is a lack of rigorous research on long-term intervention effectiveness and patient safety. Future interventions should be based on evidence-informed theories and treatment approaches and should address users' desires for program variety, natural language processing, delivery via mobile devices, and safety and privacy concerns.
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Project description:PurposeMusic has been linked with well-being across clinical and community settings. Yet, research has focused on assessment of single dimensions of well-being and on the typical receiver of support services. Acknowledging the burden that a caring role encompasses and integrating recent proposals for a multifaceted definition of well-being, we explore the extent to which group drumming interventions translate into multidimensional well-being change for both mental health service users and carers.MethodThirty-nine participants engaged in one of a series of community drumming programmes were assessed via semi-structured interviews (n = 11) and focus groups (n = 28) at the end of each programme. Data were analysed using IPA.Results and conclusionEmotional, psychological and social dimensions of well-being emerged for both patients and carers, accounted for through six themes: (1) hedonia: positive affect and pleasant physical effects of drumming; (2) agency: initiative and sense of control; (3) accomplishment: non-specific and in relation to musical goals; (4) engagement, through focus and flow; (5) a redefinition of self, through self-awareness, construction of a positive identity, self-prospection and incorporation of a musical identity; and (6) social well-being, through connectedness and positive relationships. The potential of such interventions for clinical contexts is discussed.
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Project description:Background: Previous research indicates that the physical environment of healthcare facilities plays an important role in the health, well-being, and recovery outcomes of patients. However, prior works on mental healthcare facilities have incorporated physical environment effects from general healthcare settings and patient groups, which cannot be readily transferred to mental healthcare settings or its patients. There appears to be a specific need for evidence synthesis of physical environmental effects in mental healthcare settings by psychopathology. Purpose: This review evaluates the state (in terms of extent, nature and quality) of the current empirical evidence of physical environmental on mental health, well-being, and recovery outcomes in mental healthcare inpatients by psychopathology. Method: A systematic review (PRISMA guidelines) was performed of studies published in English, German, Dutch, Swedish, and Spanish, of all available years until September 2020, searched in Cochrane, Ovid Index, PsycINFO, PubMed, and Web of Science and identified through extensive hand-picking. Inclusion criteria were: Adult patients being treated for mental ill-health (common mental health and mood disorders, Cochrane frame); inpatient mental health care facilities; specifications of the physical and socio-physical environment (e.g., design features, ambient conditions, privacy); all types of empirical study designs. Quality assessment and data synthesis were undertaken. Results: The search retrieved 1,068 titles of which 26 met the inclusion criteria. Findings suggest that there is only indicative evidence of the impact of the physical healthcare environment on patients' mental health, well-being, and recovery outcomes. There is significant lack of pathology-specific evidence. Methodological shortcomings and empirical scarcity account for the poor evidence. Conclusion: This review highlights the need for more research using advanced study designs.
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Project description:BACKGROUND:Caring for a child with intellectual disabilities can be a very rewarding but demanding experience. Research in this area has primarily focused on mothers, with relatively little attention given to the mental health of fathers. AIMS:The purpose of this review was to summarise the evidence related to the mental health of fathers compared with mothers, and with fathers in the general population. METHOD:A meta-analysis was undertaken of all studies published by 1 July 2018 in Medline, PsycINFO, CINAHL and EMBASE, using terms on intellectual disabilities, mental health and father carers. Papers were selected based on pre-defined inclusion and exclusion criteria. RESULTS:Of 5544 results, 20 studies met the inclusion criteria and 12 had appropriate data for meta-analysis. For comparisons of fathers with mothers, mothers were significantly more likely to have poor general mental health and well-being (standardised mean difference (SMD) -0.38, 95% CI -0.56 to -0.20), as well as higher levels of depression (SMD, -0.46; 95% CI -0.68 to -0.24), stress (SMD, -0.32; 95% CI -0.46 to -0.19) and anxiety (SMD, -0.30; 95% CI -0.50 to -0.10). CONCLUSIONS:There is a significant difference between the mental health of father and mother carers, with fathers less likely to exhibit poor mental health. However, this is based on a small number of studies. More data is needed to determine whether the general mental health and anxiety of father carers of a child with intellectual disabilities differs from fathers in the general population.
| S-EPMC6854361 | biostudies-literature
Project description:Poor youth mental health is an area of global concern. Summer holiday programs may provide environments that support mental health when the structures and supports of school are not available. The aim of this review was to determine the effectiveness of summer holiday programs in improving the mental health, social-emotional well-being, and cognitive (non-academic) outcomes of children and adolescents. Studies of summer holiday programs for school-aged children (5-18 years) were included if they measured any mental, socio-emotional or cognitive (non-academic) outcome. Studies were excluded if they were published prior to 2000, targeted clinical populations or lasted less than five days. Six databases were searched (April 2023). Risk of bias was assessed using the PEDro tool. Study outcomes were grouped according to three main constructs: mental health (psychological well-being, anxiety, depression, distress, and self-perception including self-esteem, self-worth, self-concept, confidence, and competence); social-emotional well-being (behavior and social skills, e.g., communication, bullying, conflict resolution, empathy, and social skills); and cognitive function (memory, selective attention, and executive function). A fourth "other" group captured substance use, personality traits, character skills, and values. Effect sizes were calculated as the standardized mean difference between pre- and post-intervention scores. The synthesis involved a random-effects meta-analysis (presented in forest plots), where possible, with the remaining outcomes narratively synthesized. Twenty-six studies (n = 6812 participants) were included. The results of the meta-analysis suggested that summer programs showed a statistically non-significant trend toward reducing symptoms of anxiety and depression (k = 2 studies, SMD = -0.17, 95% CI -2.94, 2.60), psychological distress (k = 2 studies, SMD -0.46, 95% CI -1.71, 0.79), and no effect on self-esteem (k = 6 studies, SMD = 0.02, 95% CI -0.02, 0.06) or self-worth (k = 3 studies, SMD = 0.05, 95% CI 0.00, 0.11). Narrative syntheses indicated a pattern toward improvements in general mental health, self-perception, social-emotional outcomes, and cognition. Studies were generally small, with a high risk of bias. Summer holiday programs for children and adolescents show trends toward improving mental, social, emotional, and cognitive outcomes. Programs targeting disadvantaged children showed stronger patterns of improvement related to mental health and self-perception than programs targeting the general population. While effect sizes are small to negligible, they consistently indicate improvements. Summer programs present a promising avenue to promote mental health in children; however, further rigorously designed, clearly reported control-group studies are required to more fully understand their effects.
| S-EPMC11352663 | biostudies-literature
Project description:BackgroundConversational agents (CAs) or chatbots are computer programs that mimic human conversation. They have the potential to improve access to mental health interventions through automated, scalable, and personalized delivery of psychotherapeutic content. However, digital health interventions, including those delivered by CAs, often have high attrition rates. Identifying the factors associated with attrition is critical to improving future clinical trials.ObjectiveThis review aims to estimate the overall and differential rates of attrition in CA-delivered mental health interventions (CA interventions), evaluate the impact of study design and intervention-related aspects on attrition, and describe study design features aimed at reducing or mitigating study attrition.MethodsWe searched PubMed, Embase (Ovid), PsycINFO (Ovid), Cochrane Central Register of Controlled Trials, and Web of Science, and conducted a gray literature search on Google Scholar in June 2022. We included randomized controlled trials that compared CA interventions against control groups and excluded studies that lasted for 1 session only and used Wizard of Oz interventions. We also assessed the risk of bias in the included studies using the Cochrane Risk of Bias Tool 2.0. Random-effects proportional meta-analysis was applied to calculate the pooled dropout rates in the intervention groups. Random-effects meta-analysis was used to compare the attrition rate in the intervention groups with that in the control groups. We used a narrative review to summarize the findings.ResultsThe systematic search retrieved 4566 records from peer-reviewed databases and citation searches, of which 41 (0.90%) randomized controlled trials met the inclusion criteria. The meta-analytic overall attrition rate in the intervention group was 21.84% (95% CI 16.74%-27.36%; I2=94%). Short-term studies that lasted ≤8 weeks showed a lower attrition rate (18.05%, 95% CI 9.91%- 27.76%; I2=94.6%) than long-term studies that lasted >8 weeks (26.59%, 95% CI 20.09%-33.63%; I2=93.89%). Intervention group participants were more likely to attrit than control group participants for short-term (log odds ratio 1.22, 95% CI 0.99-1.50; I2=21.89%) and long-term studies (log odds ratio 1.33, 95% CI 1.08-1.65; I2=49.43%). Intervention-related characteristics associated with higher attrition include stand-alone CA interventions without human support, not having a symptom tracker feature, no visual representation of the CA, and comparing CA interventions with waitlist controls. No participant-level factor reliably predicted attrition.ConclusionsOur results indicated that approximately one-fifth of the participants will drop out from CA interventions in short-term studies. High heterogeneities made it difficult to generalize the findings. Our results suggested that future CA interventions should adopt a blended design with human support, use symptom tracking, compare CA intervention groups against active controls rather than waitlist controls, and include a visual representation of the CA to reduce the attrition rate.Trial registrationPROSPERO International Prospective Register of Systematic Reviews CRD42022341415; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022341415.
| S-EPMC10933752 | biostudies-literature