Computerized Relational Agent to Deliver Alcohol Brief Intervention and Referral to Treatment in Primary Care: a Randomized Clinical Trial

Review article: Electronic screening and brief intervention for alcohol-related trauma: A systematic review and meta-analysis

This systematic review and meta-analysis aimed to evaluate the effectiveness of Electronic Screening and Brief Intervention (e-SBI) in changing or reducing alcohol consumption and/or related risk behaviours among trauma patients compared to standard of care. Following Cochrane Collaboration's guidelines and PRISMA recommendations, a search of electronic databases (MEDLINE via PubMed, CINAHL, Scopus and Web of Science) and grey literature (Google Scholar) was conducted. Randomised controlled trials (RCTs) from 1995 to 2023 were included, focusing on e-SBI for alcohol misuse in trauma patients. Quality assessment utilised the Cochrane risk of bias tool. Bayesian meta-analysis was employed for synthesising outcomes. Four RCTs, totalling 2641 participants, were included. While e-SBI demonstrated a significant reduction in problematic alcohol consumption up to 6 months post-implementation, uncertainties were noted in risk behaviours determined by: average alcohol consumption, binge drinking and alcohol-related consequences. Heterogeneity in measurements and population variations contributed to the nuanced findings. The review suggests that e-SBI may be effective in reducing problematic alcohol consumption in the short term among alcohol-related trauma patients. However, uncertainties and methodological variations highlight the need for standardised outcome measurements, consistent reporting and further exploration of e-SBI's long-term impact. Relevance to health promotion: Understanding the effectiveness of e-SBI in managing alcohol-related issues among trauma patients is crucial for health promotion. Despite uncertainties, the findings underscore the potential of e-SBI as a scalable and accessible intervention. e-SBI in the setting of the present study, emphasises the importance of tailored approaches in public health strategies.

Electronic-Screening, Brief Intervention and Referral to Treatment (e-SBIRT) for Addictive Disorders: Systematic Review and Meta-Analysis

BACKGROUND

Addictive disorders are significant global public health burdens. Treatment uptake with these disorders is low and outcomes can be mixed. Electronic screening, brief intervention, and referral to treatment (e-SBIRT) programs have potential to improve uptake and treatment outcomes. To date, however, no prior review of the literature has been conducted to gauge the effectiveness of e-SBIRT for addictive disorders.

METHODS

We conducted a systematic review and meta-analysis of the literature concerning e-SBIRT for addictive disorders by surveying the MEDLINE, PubMed, Web of Science, Scopus, Embase, and PsycInfo databases on January 17, 2023.

RESULTS

Ten articles were included at analysis reporting evaluation of e-SBIRT interventions for substance use disorders including alcohol use in a variety of settings. No articles were identified regarding treatment for behavioral addictions such as disordered/harmful gambling. Meta-analysis found e-SBIRT to be effective at reducing drinking frequency in the short term only. e-SBIRT was not found to be advantageous over control conditions for abstinence or other treatment outcomes. We identified and described common components of e-SBIRT programs and assessed the quality of available evidence, which was generally poor.

CONCLUSION

The present findings suggest that research regarding e-SBIRT is concentrated exclusively on higher-risk substance use. There is a lack of consensus regarding the effectiveness of e-SBIRT for addictive disorders. Although common features exist, e-SBIRT designs are variable, which complicates identification of the most effective components. Overall, the quality of outcome evidence is low, and furthermore, high-quality experimental treatment evaluation research is needed.

Alcohol consumption and dependence risk among male and female Veterans: Trajectories and predictors

BACKGROUND

With few exceptions, previously conducted research on hazardous drinking among Veterans has employed samples in which the majority of participants identify as male. In addition, past studies have solely focused on alcohol consumption, rather than associated risk for dependence. In this study, we expanded upon the extant literature by investigating sex differences in trajectories and predictors of change in alcohol consumption and dependence risk among post-9/11 Veterans.

METHODS

A national sample of 1649 Veterans (50.0% female) were recruited in a five-wave longitudinal study that followed Veterans for up to 16 years after deployment. We used growth curve modeling to investigate trajectories of change in alcohol consumption and dependence risk among men and women Veterans. We examined predictors of growth, including demographics, support and resources, psychiatric symptoms, and trauma exposure.

RESULTS

Among male Veterans, alcohol consumption and dependence risk remained stagnant, which is in contrast to past work using non-Veteran samples. For female Veterans, consumption exhibited initial reductions that decelerated, and dependence risk reduced at a continuous rate. PTSD diagnosis was a significant predictor of individual differences in growth for men. Psychiatric symptoms (i.e., PTSD diagnosis, probable depression diagnosis, suicidal ideation) and psychosocial functioning were significant predictors of decreasing alcohol use for women.

CONCLUSIONS

Results highlight important sex differences in patterns and predictors of change in alcohol consumption and dependence risk among post-9/11 Veterans. Findings are discussed in relation to screening for hazardous alcohol use and intervention strategies in this at-risk population.

Attrition in Conversational Agent-Delivered Mental Health Interventions: Systematic Review and Meta-Analysis

BACKGROUND

Conversational 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.

OBJECTIVE

This 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.

METHODS

We 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.

RESULTS

The 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.

CONCLUSIONS

Our 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 REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews CRD42022341415; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022341415.

RACares: a conceptual design to guide mHealth relational agent development based on a systematic review

Background

A relational agent (RA) is a digital tool tailored to communicate with users, aiming to establish a sense of social ease and emotional bond, particularly focusing on their health and well-being concerns. A mobile health (mHealth) RA is particularly crafted to communicate with users within their mobile devices. As healthcare becomes increasingly digital, these mHealth RAs can serve as personal health assistants, e.g., guiding users through medical regimens, offering reminders for medication, providing emotional support during health crises, or even aiding in mental well-being exercises. Their accessibility, especially for those in remote areas, can bridge the gap between patients and immediate health assistance, revolutionizing the way healthcare is approached and delivered.

Methods

In this paper, our primary focus is introducing a conceptual design for mHealth RAs with the aim of enhanced user engagement, personalized health interventions, consistent support, data collection and monitoring, and enhanced multimodal accessibility. To develop this conceptual design, we employed an inductive approach. This involved conducting a qualitative analysis on data gathered from a systematic literature review of RAs. Consequently, this analysis allowed us to identify a taxonomy of key design features essential for RAs.

Results

This paper provides a conceptual design of mHealth RAs which includes five stages: user input receiving stage, input processing stage, data analysis stage, output processing stage, and output generation stage. A stage is a logical assembly of interconnected functionalities (components) that work together to accomplish a certain objective or set of goals. Each stage's outputs are used as inputs in the stages that follow after it. There is also a Data and Personalization Controller for aiding the data analysis stage. The stages are logically arranged one after another as follows: input, process, analysis, and output.

Conclusions

The conceptual design aims to create RAs for various mHealth applications, including patient education, mental health counseling, and chronic disease management. This design is crucial in digital health research as it enhances patient-RA interactions, potentially improving health outcomes and experiences in non-life-threatening scenarios where RAs can be an alternative to human healthcare professionals (HCPs).

Screening, brief intervention, and referral to treatment for tobacco consumption, alcohol misuse, and physical inactivity: an equity-informed rapid review

OBJECTIVE

This rapid review systematically synthesizes evidence of the effectiveness of the Screening, Brief Intervention, and Referral (SBIR/T) approach for tobacco use, alcohol misuse, and physical inactivity.

STUDY DESIGN

This was a rapid review.

METHODS

We searched primary studies between 2012 and 2022 in seven electronic databases. The search strategy used concepts related to alcohol-related disorders, intoxication, cigarette, nicotine, physical activity, exercise, sedentary, screening, therapy, and referral. We reviewed both title/abstract and full-text using a priori set inclusion and exclusion criteria to identify the eligible studies. We appraised study quality, extracted data, and summarized the characteristics of the included studies. We applied health equity lenses in the synthesis.

RESULTS

Of the 44 included studies, most focused on alcohol misuse. SBIR/T improved patients' attitudes toward alcohol behavior change, improved readiness and referral initiation for change, and effectively reduced alcohol consumption. Few studies pertained to smoking and physical inactivity. Most studies on smoking demonstrated effectiveness pertaining to patients' acceptance of referral recommendations, improved readiness and attempts to quitting smoking, and reduced or cessation of smoking. Findings were mixed about the effectiveness of SBIR/T in improving physical activity. Minimal studies exist on the impacts of SBIR/T for these three risk factors on healthcare resource use or costs. Studies considering diverse population characteristics in the design and effectiveness assessment of the SBIR/T intervention are lacking.

CONCLUSIONS

More research on the impacts of SBIR/T on tobacco use, alcohol misuse, and physical inactivity is required to inform the planning and delivery of SBIR/T for general and disadvantaged populations.

Embodied Conversational Agents Providing Motivational Interviewing to Improve Health-Related Behaviors: Scoping Review

BACKGROUND

Embodied conversational agents (ECAs) are advanced human-like interfaces that engage users in natural face-to-face conversations and interactions. These traits position ECAs as innovative tools for delivering interventions for promoting health-related behavior adoption. This includes motivational interviewing (MI), a therapeutic approach that combines brief interventions with motivational techniques to encourage the adoption of healthier behaviors.

OBJECTIVE

This study aims to identify the health issues addressed by ECAs delivering MI interventions, explore the key characteristics of these ECAs (eg, appearance, dialogue mechanism, emotional model), analyze the implementation of MI principles and techniques within ECAs, and examine the evaluation methods and primary outcomes of studies that use ECAs providing MI interventions.

METHODS

We conducted a scoping review following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) methodology. Our systematic search covered the PubMed, Scopus, IEEE Xplore, ACM Digital, and PsycINFO databases for papers published between January 2008 and December 2022. We included papers describing ECAs developed for delivering MI interventions targeting health-related behaviors and excluded articles that did not describe ECAs with human appearances and without the necessary evaluation or MI explanation. In a multistage process, 3 independent reviewers performed screening and data extraction, and the collected data were synthesized using a narrative approach.

RESULTS

The initial search identified 404 articles, of which 3.5% (n=14) were included in the review. ECAs primarily focused on reducing alcohol use (n=5, 36%), took on female representations (n=9, 64%), and gave limited consideration to user ethnicity (n=9, 64%). Most of them used rules-driven dialogue mechanisms (n=13, 93%), include emotional behavior to convey empathy (n=8, 57%) but without an automatic recognition of user emotions (n=12, 86%). Regarding MI implementation, of 14 studies, 3 (21%) covered all MI principles, 4 (29%) included all processes, and none covered all techniques. Most studies (8/14, 57%) conducted acceptability, usability, and user experience assessments, whereas a smaller proportion (4/14, 29%) used randomized controlled trials to evaluate behavior changes. Overall, the studies reported positive results regarding acceptability, usability, and user experience and showed promising outcomes in changes in attitudes, beliefs, motivation, and behavior.

CONCLUSIONS

This study revealed significant advancements in the use of ECAs for delivering MI interventions aimed at promoting healthier behaviors over the past 15 years. However, this review emphasizes the need for a more in-depth exploration of ECA characteristics. In addition, there is a need for the enhanced integration of MI principles, processes, and techniques into ECAs. Although acceptability and usability have received considerable attention, there is a compelling argument for placing a stronger emphasis on assessing changes in attitudes, beliefs, motivation, and behavior. Consequently, inclusion of more randomized controlled trials is essential for comprehensive intervention evaluations.

Digital interventions for reducing alcohol use in general populations: An updated systematic review and meta-analysis

This article updates a 2017 review on the effectiveness of digital interventions for reducing alcohol use in the general population. An updated systematic search of the MEDLINE database was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria to identify randomized controlled trials (RCTs) published from January 2017 to June 2022 that evaluated the effectiveness of digital interventions compared with no interventions, minimal interventions, and face-to-face interventions aimed at reducing alcohol use in the general population and, that also reported changes in alcohol use (quantity, frequency, quantity per drinking day, heavy episodic drinking (HED), or alcohol use disorders identification test (AUDIT) scores). A secondary analysis was performed that analyzed data from RCTs conducted in students. The review was not preregistered. The search produced 2224 articles. A total of 80 studies were included in the review, 35 of which were published after the last systematic review. A total of 66, 20, 18, 26, and 9 studies assessed the impact of digital interventions on alcohol quantity, frequency, quantity per drinking day, HED, and AUDIT scores, respectively. Individuals randomized to the digital interventions drank 4.12 (95% confidence interval (CI): 2.88, 5.36) fewer grams of alcohol per day, had 0.17 (95% CI 0.06, 0.29) fewer drinking days per week, drank approximately 3.89 (95% CI: 0.40, 7.38) fewer grams of alcohol per drinking day, had 1.11 (95% CI: 0.32, 1.91) fewer HED occasions per month, and had an AUDIT score 3.04 points lower (95% CI: 2.23, 3.85) than individuals randomized to the control condition. Significant reductions in alcohol quantity, frequency, and HED, but not quantity per drinking day, were observed among students. Digital interventions show potential for reducing alcohol use in general populations and could be used widely at the population level to reduce alcohol-attributable harms.

Alcohol Screening and Brief Intervention in Primary Health Care in Kazakhstan—Results of a Cluster Randomised Pilot Study

Objective: The aim of this pilot trial was to assess the feasibility of ASBI in primary health care units (PHCUs) in Kazakhstan.

Methods: A two-arm cluster randomised trial in five PHCUs based on the RE-AIM framework for implementation studies was carried out. Patients with AUDIT-C scores ≥4 for females and ≥5 for males received a brief face-to-face intervention delivered by a trained physician plus information leaflet (intervention group, IG) or simple feedback including a leaflet (control group, CG).

Results: Among 7327 patients eligible for alcohol screening according to the inclusion criteria 1148 patients were screened (15.7%, IG: 11.5%, CG: 27.3%). 12.3% (N = 141) were tested AUDIT-C positive (IG: 9.9%, CG: 15.1%). Out of 112 physicians invited, 48 took part in the ASBI training, 31 finally participated in the study, 21 in the IG (2 PHCUs), 10 in the CG (3 PHCUs). The majority of physicians did not have difficulties in performing the intervention.

Conclusion: ASBI is feasible and can be implemented into PHC settings in Kazakhstan. However, the implementation depends on the willingness and interest of the PHCU and the physicians.

Factors Influencing Adherence to mHealth Apps for Prevention or Management of Noncommunicable Diseases: Systematic Review

BACKGROUND

Mobile health (mHealth) apps show vast potential in supporting patients and health care systems with the increasing prevalence and economic costs of noncommunicable diseases (NCDs) worldwide. However, despite the availability of evidence-based mHealth apps, a substantial proportion of users do not adhere to them as intended and may consequently not receive treatment. Therefore, understanding the factors that act as barriers to or facilitators of adherence is a fundamental concern in preventing intervention dropouts and increasing the effectiveness of digital health interventions.

OBJECTIVE

This review aimed to help stakeholders develop more effective digital health interventions by identifying factors influencing the continued use of mHealth apps targeting NCDs. We further derived quantified adherence scores for various health domains to validate the qualitative findings and explore adherence benchmarks.

METHODS

A comprehensive systematic literature search (January 2007 to December 2020) was conducted on MEDLINE, Embase, Web of Science, Scopus, and ACM Digital Library. Data on intended use, actual use, and factors influencing adherence were extracted. Intervention-related and patient-related factors with a positive or negative influence on adherence are presented separately for the health domains of NCD self-management, mental health, substance use, nutrition, physical activity, weight loss, multicomponent lifestyle interventions, mindfulness, and other NCDs. Quantified adherence measures, calculated as the ratio between the estimated intended use and actual use, were derived for each study and compared with the qualitative findings.

RESULTS

The literature search yielded 2862 potentially relevant articles, of which 99 (3.46%) were included as part of the inclusion criteria. A total of 4 intervention-related factors indicated positive effects on adherence across all health domains: personalization or tailoring of the content of mHealth apps to the individual needs of the user, reminders in the form of individualized push notifications, user-friendly and technically stable app design, and personal support complementary to the digital intervention. Social and gamification features were also identified as drivers of app adherence across several health domains. A wide variety of patient-related factors such as user characteristics or recruitment channels further affects adherence. The derived adherence scores of the included mHealth apps averaged 56.0% (SD 24.4%).

CONCLUSIONS

This study contributes to the scarce scientific evidence on factors that positively or negatively influence adherence to mHealth apps and is the first to quantitatively compare adherence relative to the intended use of various health domains. As underlying studies mostly have a pilot character with short study durations, research on factors influencing adherence to mHealth apps is still limited. To facilitate future research on mHealth app adherence, researchers should clearly outline and justify the app's intended use; report objective data on actual use relative to the intended use; and, ideally, provide long-term use and retention data.