Self-reported alcohol consumption during participation in a text messaging-based online drinking moderation platform.

BACKGROUND: Many individuals with excessive alcohol consumption desire moderation but do not seek formalized treatment. Commercially available, technology-assisted options are flexible and highly accessible, yet often not empirically validated. METHODS: Individuals desiring alcohol moderation (age 21+) self-selected to use Sunnyside®, a web application with tailored and adaptive text messaging. The evaluable dataset included 46,411 members who completed a baseline assessment, enrolled in the program, and tracked their drinking at least once. An adaptive and customizable weekly plan was generated from typical drinking patterns, goals, and weekly reported progress. Personalized daily messages included reminders for real-time drink tracking, plans, and available interactive messaging with peer coaches. Generalized mixed-effect growth models characterized change in drinks per week and daily drinking for 12 weeks after enrollment. Models allowed for nonlinear change and individual variability across members and weeks. RESULTS: A majority (64.3%) of members reported typically drinking 7 of 7 days per week at baseline. During tracking, drinks per week decreased most in the initial weeks and slowed thereafter, with an overall 33% reduction in weekly drink counts. More severe alcohol-use patterns and concern over drinking at baseline were associated with greater relative benefit. CONCLUSIONS: Drinking patterns appeared amenable to change during 12 weeks of daily drink tracking with Sunnyside®, a tailored web program to reduce drinking and improve overall wellness. Overall, the findings of this naturalistic study, one of the first of its kind, supplement data from randomized clinical trials and support the use of adaptive, technology-assisted tools for alcohol moderation.

Improving Access and Quality of Behavioral Health Services for Health Care Employees.

OBJECTIVE: To describe key features and the initial implementation of an employer-sponsored program designed to increase access to quality mental health treatment for employees of a large health care system. Methods: Retrospective data were collected on employer's efforts to develop a programmatic solution to address barriers to accessing quality mental health treatment among its employees and on initial program implementation. Results: Data from the initial cohort ( N = 1049) of program participants support the use of low threshold digital tools to enhance access to care, the importance of care navigation and a robust curated provider network in matching employees to appropriate care options, and the value of providing online, evidence-based psychotherapy to facilitate high rates of treatment engagement. Conclusions: Findings can help inform employers about approaches to improve access to quality mental health treatment for their employees.

Linkage facilitation services for opioid use disorder: Taxonomy of facilitation practitioners, goals, and activities.

INTRODUCTION: This article proposes a taxonomy of linkage facilitation services used to help persons with opioid use disorder access treatment and recovery resources. Linkage facilitation may be especially valuable for persons receiving medication for opioid use disorder (MOUD) given the considerable barriers to treatment access and initiation that have been identified. The science of linkage facilitation currently lacks both consistent communication about linkage facilitation practices and a conceptual framework for guiding research. METHODS: To address this gap, this article presents a taxonomy derived from expert consensus that organizes the array of practitioners, goals, and activities associated with linkage services for OUD and related needs. Expert panelists first independently reviewed research reports and policy guidelines summarizing the science and practice of linkage facilitation for substance use disorders generally and OUD specifically, then met several times to vet the conceptual scheme and content of the taxonomy until they reached a final consensus. RESULTS: The derived taxonomy contains eight domains: facilitator identity, facilitator lived experience, linkage client, facilitator-client relationship, linkage activity, linkage method, linkage connectivity, and linkage goal. For each domain, the article defines basic domain categories, highlights research and practice themes in substance use and OUD care, and introduces innovations in linkage facilitation being tested in one of two NIDA-funded research networks: Justice Community Opioid Innovation Network (JCOIN) or Consortium on Addiction Recovery Science (CoARS). CONCLUSIONS: To accelerate consistent application of this taxonomy to diverse research and practice settings, the article concludes by naming several considerations for linkage facilitation workforce training and implementation.

Automated, tailored adaptive mobile messaging to reduce alcohol consumption in help-seeking adults: A randomized controlled trial.

AIMS: To test differential outcomes between three 6-month text-messaging interventions to reduce at-risk drinking in help-seeking adults. DESIGN: A three-arm single-blind randomized controlled trial with 1-, 3-, 6- and 12-month follow-ups. SETTING: United States. A fully remote trial without human contact, with participants recruited primarily via social media outlets. PARTICIPANTS: Seven hundred and twenty-three adults (mean = 39.9 years, standard deviation = 10.0; 62.5% female) seeking to reduce their drinking were allocated to 6 months of baseline 'tailored statically' messaging (TS; n = 240), 'tailored adaptive' messaging (TA; n = 239) or 'drink tracking' messaging (DT; n = 244). INTERVENTIONS: TS consisted of daily text messages to reduce harmful drinking that were tailored to demographics and alcohol use. TA consisted of daily, tailored text messages that were also adapted based on goal achievement and proactive prompts. DT consisted of a weekly assessment for self-reported drinking over the past 7 days. MEASUREMENTS: The primary outcome measure was weekly sum of standard drinks (SSD) at 6-month follow-up. Secondary outcome measures included drinks per drinking day (DDD), number of drinking days (NDD) per week and heavy drinking days (HDD) at 1-, 3-, 6- and 12-month follow-ups. FINDINGS: At 6 months, compared with DT, TA resulted in significant SSD reductions of 16.2 (from 28.7 to 12.5) drinks [adjusted risk ratio (aRR) = 0.80, 95% confidence interval (CI) = 0.71, 0.91] using intent-to-treat analysis. TA also resulted in significant improvements in DDD (aRR = 0.84; 95% CI = 0.77-0.92) and drinking days per week (b = -0.39; 95% CI = -0.67, -0.10), but not HDD compared with DT at 6 months. TA was not significantly different from TS at any time-point, except DDD at 6 months. All groups made improvements in SSD at 12-month follow-up compared with baseline with an average reduction of 12.9 drinks per week across groups. CONCLUSIONS: Automated tailored mobile messaging interventions are scalable solutions that can reduce weekly alcohol consumption in remote help-seeking drinkers over time.

Impacts of COVID-19 on alcohol use among help-seeking adults.

The coronavirus (COVID-19) pandemic has been associated with both increased and decreased alcohol use. Authors explored reasons for increased and decreased alcohol use since the COVID-19 lockdown (March 2020) in a sample of help-seeking adults (HSA) participating in a remote-based alcohol reduction text-messaging intervention in the USA. At the time of recruitment, the HSA in this study were interested in reducing rather than stopping their alcohol consumption. An optional self-report questionnaire was completed by 324 participants (mean age 41.6 ± 10.2 years; 71.5% female; 83.9% White) in February 2021. Survey questions assessed sociodemographic factors, social stressors (quarantine conditions, employment status, changes to daily routine), and drinking patterns. Authors fit two ordinal logistic regression models: one for increased drinking and one for decreased drinking, as functions of the potential predictors and control variables. Most participants (n = 281; 87.0%) reported drinking more than usual since COVID-19 lockdown began. The most common self-reported reasons for drinking more were increased stress/anxiety (74.7%), boredom (69.4%), and spending more time at home (65.5%) whereas reasons for drinking less were less socializing (33.7%) and worrying about how alcohol would impact the immune system (31.5%). Identifying as female, severity of changes to daily routine, and increased access to alcohol were significantly associated with drinking more than usual. These data suggest that the general consequences of the pandemic in the general population (e.g., boredom) led to greater alcohol use among help-seeking adults attempting to reduce their drinking. Identifying these factors may help create more targeted interventions during public health crises.

Implementing a text-messaging intervention for unhealthy alcohol use in emergency departments: protocol for implementation strategy development and a pilot cluster randomized implementation trial.

BACKGROUND: Unhealthy alcohol use (UAU) is a leading cause of premature mortality among adults in the USA. Emergency departments (EDs) are key intervention settings for UAU but often have limited time and resources. One low-burden, scalable approach to address UAU is text-messaging interventions. Despite strong research support and promise for scalability, there is little research on how to implement such interventions in healthcare settings. The process of providers making them available to patients in an efficient way within already busy and overburdened ED workflows and patients adopting them remains a new area of research. The purpose of this three-phase study is to develop and test an implementation strategy for UAU text-messaging interventions in EDs. METHOD: Our first aim is to examine barriers and facilitators to staff offering and patients accepting a text-messaging intervention in the ED using an explanatory, sequential mixed methods approach. We will examine alcohol screening data in the electronic health records of 17 EDs within a large integrated health system in the Northeast and conduct surveys among chairpersons in each. This data will be used to purposively sample 4 EDs for semi-structured interviews among 20 clinical staff, 20 patients, and 4 chairpersons. Our second aim is to conduct a stakeholder-engaged intervention mapping process to develop a multi-component implementation strategy for EDs. Our third aim is to conduct a mixed method 2-arm cluster randomized pilot study in 4 EDs that serve ~11,000 UAU patients per year to assess the feasibility, acceptability, and preliminary effectiveness of the implementation strategy. The Integrated Promoting Action on Research Implementation in Health Services framework will guide study activities. DISCUSSION: Low-burden technology, like text messaging, along with targeted implementation support and strategies driven by identified barriers and facilitators could sustain large-scale ED-based alcohol screening programs and provide much needed support to patients who screen positive while reducing burden on EDs. The proposed study would be the first to develop and test this targeted implementation strategy and will prepare for a larger, fully powered hybrid effectiveness-implementation trial. Findings may also be broadly applicable to implementation of patient-facing mobile health technologies. TRIAL REGISTRATION: This study was registered at ClinicalTrials.gov (NCT05350878) on 4/28/2022.

Effort-Optimized Intervention Model: Framework for Building and Analyzing Digital Interventions That Require Minimal Effort for Health-Related Gains.

The majority of digital health interventions lean on the promise of bringing health and self-care into people's homes and hands. However, these interventions are delivered while people are in their triggering environments, which places competing demands on their attention. Individuals struggling to change or learn a new behavior have to work hard to achieve even a minor change because of the automatic forces propelling them back to their habitual behaviors. We posit that effort and burden should be explored at the outset and throughout the digital intervention development process as a core therapeutic mechanism, beyond the context of design or user experience testing. In effort-focused conceptualization, it is assumed that, even though goals are rational and people want to achieve them, they are overtaken by competing cognitive, emotional, and environmental processes. We offer the term effort-optimized intervention to describe interventions that focus on user engagement in the face of competing demands. We describe design components based on a 3-step process for planning an effort-optimized intervention: (1) nurturing effortless cognitive and environmental salience to help people keep effort-related goals prominent despite competition; (2) making it as effortless as possible to complete therapeutic activities to avoid ego depletion and self-efficacy reduction; and (3) turning the necessary effortful activities into sustainable assets. We conclude by presenting an example of designing a digital health intervention based on the effort-optimized intervention model.

Correction: The Digital Marshmallow Test (DMT) Diagnostic and Monitoring Mobile Health App for Impulsive Behavior: Development and Validation Study.

[This corrects the article DOI: 10.2196/25018.].

The Digital Marshmallow Test (DMT) Diagnostic and Monitoring Mobile Health App for Impulsive Behavior: Development and Validation Study.

BACKGROUND: The classic Marshmallow Test, where children were offered a choice between one small but immediate reward (eg, one marshmallow) or a larger reward (eg, two marshmallows) if they waited for a period of time, instigated a wealth of research on the relationships among impulsive responding, self-regulation, and clinical and life outcomes. Impulsivity is a hallmark feature of self-regulation failures that lead to poor health decisions and outcomes, making understanding and treating impulsivity one of the most important constructs to tackle in building a culture of health. Despite a large literature base, impulsivity measurement remains difficult due to the multidimensional nature of the construct and limited methods of assessment in daily life. Mobile devices and the rise of mobile health (mHealth) have changed our ability to assess and intervene with individuals remotely, providing an avenue for ambulatory diagnostic testing and interventions. Longitudinal studies with mobile devices can further help to understand impulsive behaviors and variation in state impulsivity in daily life. OBJECTIVE: The aim of this study was to develop and validate an impulsivity mHealth diagnostics and monitoring app called Digital Marshmallow Test (DMT) using both the Apple and Android platforms for widespread dissemination to researchers, clinicians, and the general public. METHODS: The DMT app was developed using Apple's ResearchKit (iOS) and Android's ResearchStack open source frameworks for developing health research study apps. The DMT app consists of three main modules: self-report, ecological momentary assessment, and active behavioral and cognitive tasks. We conducted a study with a 21-day assessment period (N=116 participants) to validate the novel measures of the DMT app. RESULTS: We used a semantic differential scale to develop self-report trait and momentary state measures of impulsivity as part of the DMT app. We identified three state factors (inefficient, thrill seeking, and intentional) that correlated highly with established measures of impulsivity. We further leveraged momentary semantic differential questions to examine intraindividual variability, the effect of daily life, and the contextual effect of mood on state impulsivity and daily impulsive behaviors. Our results indicated validation of the self-report sematic differential and related results, and of the mobile behavioral tasks, including the Balloon Analogue Risk Task and Go-No-Go task, with relatively low validity of the mobile Delay Discounting task. We discuss the design implications of these results to mHealth research. CONCLUSIONS: This study demonstrates the potential for assessing different facets of trait and state impulsivity during everyday life and in clinical settings using the DMT mobile app. The DMT app can be further used to enhance our understanding of the individual facets that underlie impulsive behaviors, as well as providing a promising avenue for digital interventions. TRIAL REGISTRATION: ClinicalTrials.gov NCT03006653; https://www.clinicaltrials.gov/ct2/show/NCT03006653.

mPulse Mobile Sensing Model for Passive Detection of Impulsive Behavior: Exploratory Prediction Study.

BACKGROUND: Mobile health technology has demonstrated the ability of smartphone apps and sensors to collect data pertaining to patient activity, behavior, and cognition. It also offers the opportunity to understand how everyday passive mobile metrics such as battery life and screen time relate to mental health outcomes through continuous sensing. Impulsivity is an underlying factor in numerous physical and mental health problems. However, few studies have been designed to help us understand how mobile sensors and self-report data can improve our understanding of impulsive behavior. OBJECTIVE: The objective of this study was to explore the feasibility of using mobile sensor data to detect and monitor self-reported state impulsivity and impulsive behavior passively via a cross-platform mobile sensing application. METHODS: We enrolled 26 participants who were part of a larger study of impulsivity to take part in a real-world, continuous mobile sensing study over 21 days on both Apple operating system (iOS) and Android platforms. The mobile sensing system (mPulse) collected data from call logs, battery charging, and screen checking. To validate the model, we used mobile sensing features to predict common self-reported impulsivity traits, objective mobile behavioral and cognitive measures, and ecological momentary assessment (EMA) of state impulsivity and constructs related to impulsive behavior (ie, risk-taking, attention, and affect). RESULTS: Overall, the findings suggested that passive measures of mobile phone use such as call logs, battery charging, and screen checking can predict different facets of trait and state impulsivity and impulsive behavior. For impulsivity traits, the models significantly explained variance in sensation seeking, planning, and lack of perseverance traits but failed to explain motor, urgency, lack of premeditation, and attention traits. Passive sensing features from call logs, battery charging, and screen checking were particularly useful in explaining and predicting trait-based sensation seeking. On a daily level, the model successfully predicted objective behavioral measures such as present bias in delay discounting tasks, commission and omission errors in a cognitive attention task, and total gains in a risk-taking task. Our models also predicted daily EMA questions on positivity, stress, productivity, healthiness, and emotion and affect. Perhaps most intriguingly, the model failed to predict daily EMA designed to measure previous-day impulsivity using face-valid questions. CONCLUSIONS: The study demonstrated the potential for developing trait and state impulsivity phenotypes and detecting impulsive behavior from everyday mobile phone sensors. Limitations of the current research and suggestions for building more precise passive sensing models are discussed. TRIAL REGISTRATION: ClinicalTrials.gov NCT03006653; https://clinicaltrials.gov/ct2/show/NCT03006653.

Objective User Engagement With Mental Health Apps: Systematic Search and Panel-Based Usage Analysis.

BACKGROUND: Understanding patterns of real-world usage of mental health apps is key to maximizing their potential to increase public self-management of care. Although developer-led studies have published results on the use of mental health apps in real-world settings, no study yet has systematically examined usage patterns of a large sample of mental health apps relying on independently collected data. OBJECTIVE: Our aim is to present real-world objective data on user engagement with popular mental health apps. METHODS: A systematic engine search was conducted using Google Play to identify Android apps with 10,000 installs or more targeting anxiety, depression, or emotional well-being. Coding of apps included primary incorporated techniques and mental health focus. Behavioral data on real-world usage were obtained from a panel that provides aggregated nonpersonal information on user engagement with mobile apps. RESULTS: In total, 93 apps met the inclusion criteria (installs: median 100,000, IQR 90,000). The median percentage of daily active users (open rate) was 4.0% (IQR 4.7%) with a difference between trackers (median 6.3%, IQR 10.2%) and peer-support apps (median 17.0%) versus breathing exercise apps (median 1.6%, IQR 1.6%; all z≥3.42, all P<.001). Among active users, daily minutes of use were significantly higher for mindfulness/meditation (median 21.47, IQR 15.00) and peer support (median 35.08, n=2) apps than for apps incorporating other techniques (tracker, breathing exercise, psychoeducation: medians range 3.53-8.32; all z≥2.11, all P<.05). The medians of app 15-day and 30-day retention rates were 3.9% (IQR 10.3%) and 3.3% (IQR 6.2%), respectively. On day 30, peer support (median 8.9%, n=2), mindfulness/meditation (median 4.7%, IQR 6.2%), and tracker apps (median 6.1%, IQR 20.4%) had significantly higher retention rates than breathing exercise apps (median 0.0%, IQR 0.0%; all z≥2.18, all P≤.04). The pattern of daily use presented a descriptive peak toward the evening for apps incorporating most techniques (tracker, psychoeducation, and peer support) except mindfulness/meditation, which exhibited two peaks (morning and night). CONCLUSIONS: Although the number of app installs and daily active minutes of use may seem high, only a small portion of users actually used the apps for a long period of time. More studies using different datasets are needed to understand this phenomenon and the ways in which users self-manage their condition in real-world settings.

A Text Message Intervention with Adaptive Goal Support to Reduce Alcohol Consumption Among Non-Treatment-Seeking Young Adults: Non-Randomized Clinical Trial with Voluntary Length of Enrollment.

BACKGROUND: Stand-alone text message-based interventions can reduce binge drinking episodes (≥4 drinks for women and ≥5 drinks for men) among nontreatment-seeking young adults, but may not be optimized. Adaptive text message support could enhance effectiveness by assisting context-specific goal setting and striving, but it remains unknown how to best integrate it into text message interventions. OBJECTIVE: The objective of this study was to evaluate young adults' engagement with a text message intervention, Texting to Reduce Alcohol Consumption 2 (TRAC2), which focuses on reducing weekend alcohol consumption. TRAC2 incorporated preweekend drinking-limit goal-commitment ecological momentary assessments (EMA) tailored to past 2-week alcohol consumption, intraweekend goal reminders, self-efficacy EMA with support tailored to goal confidence, and maximum weekend alcohol consumption EMA with drinking limit goal feedback. METHODS: We enrolled 38 nontreatment-seeking young adults (aged 18 to 25 years) who screened positive for hazardous drinking in an urban emergency department. Following a 2-week text message assessment-only run-in, subjects were given the opportunity to enroll in 4-week intervention blocks. We examined patterns of EMA responses and voluntary re-enrollment. We then examined how goal commitment and goal self-efficacy related to event-level alcohol consumption. Finally, we examined the association of length of TRAC2 exposure with alcohol-related outcomes from baseline to 3-month follow-up. RESULTS: Among a diverse sample of young adults (56% [28/50] female, 54% [27/50] black, 32% [12/50] college enrolled), response rates to EMA queries were, on average, 82% for the first 4-week intervention block, 75% for the second 4-week block, and 73% for the third 4-week block. In the first 4 weeks of the intervention, drinking limit goal commitment was made 68/71 times it was prompted (96%). The percentage of subjects being prompted to commit to a drinking limit goal above the binge threshold was 52% (15/29) in week 1 and decreased to 0% (0/15) by week 4. Subjects met their goal 130/146 of the times a goal was committed to (89.0%). There were lower rates of goal success when subjects reported lower confidence (score <4) in meeting the goal (76% [32/42 weekends]) compared with that when subjects reported high confidence (98% [56/57 weekends]; P=.001). There were reductions in alcohol consumption from baseline to 3 months, but reductions were not different by length of intervention exposure. CONCLUSIONS: Preliminary evidence suggests that nontreatment-seeking young adults will engage with a text message intervention incorporating self-regulation support features, resulting in high rates of weekend drinking limit goal commitment and goal success.

Comparing daily drivers of problem drinking among older and younger adults: An electronic daily diary study using smartphones.

BACKGROUND: By 2030, numbers and proportions of older adults with substance-use problems are expected to increase. While risk factors for problem drinking in late life have been identified, it remains unknown whether these factors drive daily drinking among older problem drinkers. This study examined the daily drivers of drinking among problem drinkers, moderated by age, utilizing ecological momentary assessment (EMA). METHOD: Participants (N = 139), ages 20-73, received daily EMA online surveys completed via a smartphone prior to initiation of treatment. Multilevel modeling tested the moderating impact of age on within- and between-person relationships between drinking and focal predictors (mood, loneliness, boredom, stress, poor sleep, social factors, alcohol salience, commitment and confidence not to drink heavily). RESULTS: Older adults reported greater alcohol consumption when daily boredom levels were higher. Heavier drinking among younger adults was associated with poorer sleep quality. Greater daily confidence, daily commitment and daily alcohol salience did not impact drinking to the same extent for older adults as for younger adults. Greater person-level commitment predicted reduced drinking equivalently across age, but low person-level commitment predicted greater drinking among older adults compared to their younger counterparts. CONCLUSION: Older adults may have unique daily drivers of drinking that are not fully realized in current research and intervention efforts. Addressing the growing substance-use treatment needs among this population will require identifying the unique drivers of drinking among older adults, such as boredom, when compared to younger adults.

Building partnerships: a pilot study of stakeholders' attitudes on technology disruption in behavioral health delivery and research.

Collaborations between scientists, care providers, and technology industry professionals are becoming more relevant for developing, testing, and implementing behavioral health technologies. As the need for such partnerships increases, it is important to understand stakeholders' attitudes about their role in partnering for developing such technologies and how much do they expect technology to impact behavioral research and care. The aim of this study was to investigate how much technology disruption do stakeholders expect in healthcare, as well as their perceived contribution in partnering for developing behavioral health technologies. Stakeholders (N = 74) responded to an online convenience sampling survey. Over 89% of participants reported expecting that technology will bring at least a moderate amount of disruption in the current models of behavioral healthcare, with respondents with the most experience in digital health expecting the most disruption. As for their perception of each other's role in partnering for developing behavioral health technologies, one group's weakness was considered to be complemented by another group's strength. Academics were perceived as having more theoretical and research expertise but being less technology-savvy, while industry professionals were considered to excel at technological and marketing activities. Providers were considered to have the most clinical and real-world healthcare industry expertise. Our results indicate that technology is expected to disrupt current healthcare models, while also highlighting the need for collaboration, as no single group was considered to have sufficient expertise and resources to develop successful, effective behavioral health technologies on its own. These results may contribute to a better understanding of how technology disruption is affecting behavioral healthcare from the standpoint of its key players, which may lead to better collaborative models of research and care delivery.

More Than a Text Message: Dismantling Digital Triggers to Curate Behavior Change in Patient-Centered Health Interventions.

Digital triggers such as text messages, emails, and push alerts are designed to focus an individual on a desired goal by prompting an internal or external reaction at the appropriate time. Triggers therefore have an essential role in engaging individuals with digital interventions delivered outside of traditional health care settings, where other events in daily lives and fluctuating motivation to engage in effortful behavior exist. There is an emerging body of literature examining the use of digital triggers for short-term action and longer-term behavior change. However, little attention has been given to understanding the components of digital triggers. Using tailoring as an overarching framework, we separated digital triggers into 5 primary components: (1) who (sender), (2) how (stimulus type, delivery medium, heterogeneity), (3) when (delivered), (4) how much (frequency, intensity), and (5) what (trigger's target, trigger's structure, trigger's narrative). We highlighted key considerations when tailoring each component and the pitfalls of ignoring common mistakes, such as alert fatigue and habituation. As evidenced throughout the paper, there is a broad literature base from which to draw when tailoring triggers to curate behavior change in health interventions. More research is needed, however, to examine differences in efficacy based on component tailoring, to best use triggers to facilitate behavior change over time, and to keep individuals engaged in physical and mental health behavior change efforts. Dismantling digital triggers into their component parts and reassembling them according to the gestalt of one's change goals is the first step in this development work.

Anxiety: There is an app for that. A systematic review of anxiety apps.

BACKGROUND: Smartphones and mobile devices have become ubiquitous, and with the rapid advance of technology, the number of health applications (apps) that are available for consumers on these devices is constantly growing. In particular, there has been a recent proliferation of anxiety apps. However, there has been no review of the quality or content of these anxiety apps and little is known about their purpose, the features they contain, and their empirical support. The goal of this systematic review was to assess the commercially available anxiety apps. METHODS: A list of anxiety apps was collected in January 2017, using the Power Search function of iTunes and Google Play. Of 5,078 identified apps, 52 met our inclusion criteria (i.e., being defined as an anxiety/worry relief app, and offering psychological techniques aimed primarily at reducing anxiety) and were further reviewed. RESULTS: The majority (67.3%) of the currently available anxiety apps were found to lack the involvement of health care professionals in their development, and very few (3.8%) of them have been rigorously tested. CONCLUSIONS: At the moment, although anxiety apps have the potential to enhance access to mental health care, there is a marked discrepancy between the wealth of commercially available apps, and the paucity of data regarding their efficacy and effectiveness. Although the great promise of apps is their ability to increasing access to evidence-based mental health, the field is not quite there yet and the full potential of apps for treating anxiety has yet to be exploited.

Mobile phone messaging for illicit drug and alcohol dependence: A systematic review of the literature.

ISSUES: Mobile phone use has increased dramatically and concurrent with rapid developments in mobile phone-based health interventions. The integration of text messaging interventions promises to optimise the delivery of care for persons with substance dependence with minimal disruption to clinical workflows. We conducted a systematic review to assess the acceptability, feasibility and clinical impact of text messaging interventions for persons with illicit drug and alcohol dependence. APPROACH: Studies were required to evaluate the use of text messaging as an intervention for persons who met Diagnostic and Statistical Manual of Mental Disorders, 4th edition criterion for a diagnosis of illicit drug and/or alcohol dependence. Authors searched for articles published to date in MEDLINE (pubmed.gov), the Cochrane Library, EMBASE, CINAHL, Google Scholar and PsychINFO. KEY FINDINGS: Eleven articles met the search criteria for this review and support the acceptability and feasibility of text messaging interventions for addressing illicit drug and alcohol dependence. Most studies demonstrated improved clinical outcomes, medication adherence and engagement with peer support groups. Text messaging interventions also intervened on multiple therapeutic targets such as appointment attendance, motivation, self-efficacy, relapse prevention and social support. IMPLICATIONS: Suggestions for future research are described, including intervention design features, clinician contact, privacy measures and integration of behaviour change theories. CONCLUSION: Text messaging interventions offer a feasible platform to address a range of substances (i.e. alcohol, methamphetamine, heroin and alcohol), and there is increasing evidence supporting further larger-scale studies. [Tofighi B, Nicholson JM, McNeely J, Muench F, Lee JD. Mobile phone messaging for illicit drug and alcohol dependence: A systematic review of the literature. Drug Alcohol Rev 2017;36:477-491].

A pilot study of online feedback for adult drinkers 50 and older: Feasibility, efficacy, and preferences for intervention.

Normative (NF) and personalized feedback (PF) are moderately effective brief interventions for at-risk drinking middle-aged and older adults. This study tested the feasibility of online feedback for drinkers 50 and older. This study's aims were to identify whether there is differential effectiveness of PF over NF in prompting drinkers 50years old and older to plan for change and to determine potential preferences for intervention among adult drinkers 50 and older with practical knowledge about computers. METHOD: Using Amazon's Mechanical Turk, 138 male and female drinkers aged 50 to 75+ were recruited to complete an online survey that asked about their: perceptions of their drinking, quantity and frequency of drinking, and any comorbid health and/or mental health disorders/medications. They were then provided either NF or PF. NF provided information about how participants' drinking compared to their same age and gendered peers. PF provided information about level of risk to health and provided recommendations for safe levels of drinking. After feedback, participants were evaluated for their reactions (e.g., "How much does this worry you?") and their plan to change their drinking. Participants were asked about preferences for interventions. RESULTS: 80% of participants rated themselves a no or low-risk drinker, yet 52.2% were found to be at-risk drinkers. Overall, participants reported feedback was helpful, and 43.9% made some kind of plan to change. Participants in NF were significantly more likely to make a plan for change than those in PF. Participants reported that they most preferred an online (40.9%) or a brief in-person (31.8%) intervention. CONCLUSION: Findings revealed that brief online feedback was feasible, though limited to those who are computer knowledgeable. Unexpectedly, NF outperformed PF, suggesting that peer comparisons may be more motivating for adults 50 and older than previously thought. Finally, an online intervention appears to be a preferred intervention for alcohol use among this particular group of drinkers.

A Randomized Controlled Pilot Trial of Different Mobile Messaging Interventions for Problem Drinking Compared to Weekly Drink Tracking.

INTRODUCTION: Recent evidence suggests that text messaging may help to reduce problem drinking as an extension to in-person services, but very little is known about the effectiveness of remote messaging on problem drinking as a stand-alone intervention, or how different types of messages may improve drinking outcomes in those seeking to moderate their alcohol consumption. METHODS: We conducted an exploratory, single-blind randomized controlled pilot study comparing four different types of alcohol reduction-themed text messages sent daily to weekly drink self-tracking texts in order to determine their impact on drinking outcomes over a 12-week period in 152 participants (≈ 30 per group) seeking to reduce their drinking on the internet. Messaging interventions included: weekly drink self-tracking mobile assessment texts (MA), loss-framed texts (LF), gain-framed texts (GF), static tailored texts (ST), and adaptive tailored texts (TA). Poisson and least squares regressions were used to compare differences between each active messaging group and the MA control. RESULTS: When adjusting for baseline drinking, participants in all messaging groups except GF significantly reduced the number of drinks consumed per week and the number of heavy drinking days compared to MA. Only the TA and GF groups were significantly different from MA in reducing the number of drinking days. While the TA group yielded the largest effect sizes on all outcome measures, there were no significant differences between active messaging groups on any outcome measure. 79.6% of individuals enrolled in the study wanted to continue receiving messages for an additional 12 weeks at the end of the study. DISCUSSION: Results of this pilot study indicate that remote automated text messages delivered daily can help adult problem drinkers reduce drinking frequency and quantity significantly more than once-a-week self-tracking messages only, and that tailored adaptive texts yield the largest effect sizes across outcomes compared to MA. Larger samples are needed to understand differences between messaging interventions and to target their mechanisms of efficacy.

An exploratory study of mobile messaging preferences by age: Middle-aged and older adults compared to younger adults.

INTRODUCTION: Mobile technologies, such as short message service or text messaging, can be an important way to reach individuals with medical and behavioral health problems who are homebound or geographically isolated. Optimally tailoring messages in short message service interventions according to preferences can enhance engagement and positive health outcomes; however, little is known about the messaging preferences of middle-aged and older adults. METHODS: Utilizing secondary data, global messaging preferences were examined to inform the development of short message service interventions for adults of all ages. Two hundred and seventy-seven adults were recruited through an online labor market. They completed an online survey by evaluating message dyads in 22 content groupings. Dyads were identical in subject matter but structurally or linguistically varied. Participants selected the message in each dyad they would prefer to receive when attempting to meet a self-selected personal goal. Preferences were tested for two age groups ≤50 and 51 and older. RESULTS: Findings reveal adults 51 and older have clear messaging preferences that differ significantly from the younger group for only two content groupings; specifically, they prefer no emoticon to a smiley face emoticon and "you" statements rather than "we" statements. CONCLUSION: Recommendations for optimizing messaging for older adults are reviewed.