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This paper examines the use of text message (SMS) interventions for health-related behavioral support. It first outlines the historical progress in SMS intervention research publications and the variety of funds from US government agencies. A narrative review follows, highlighting the effectiveness of SMS interventions in key health areas, such as physical activity, diet and weight loss, mental health, and substance use, based on published meta-analyses. It then outlines advantages of text messaging compared to other digital modalities, including the real-time capability to collect information and deliver microdoses of intervention support. Crucial design elements are proposed to optimize effectiveness and longitudinal engagement across communication strategies, psychological foundations, and behavior change tactics. We then discuss advanced functionalities, such as the potential for generative artificial intelligence to improve user interaction. Finally, major challenges to implementation are highlighted, including the absence of a dedicated commercial platform, privacy and security concerns with SMS technology, difficulties integrating SMS interventions with medical informatics systems, and concerns about user engagement. Proposed solutions aim to facilitate the broader application and effectiveness of SMS interventions. Our hope is that these insights can assist researchers and practitioners in using SMS interventions to improve health outcomes and reducing disparities.

Since 1999, more than 600 000 people have died from opioid overdoses in the USA and Canada, and the current rate of mortality in each country exceeds even that of the worst year of the HIV/AIDS epidemic. The Commission's analysis of the crisis focused on seven domains: (1) the North American opioid crisis as a case study in multi-system regulatory failure, (2) opioids' dual nature as both a benefit and a risk to health, (3) building integrated, well supported, and enduring systems of care for people with substance use disorders, (4) maximising the benefits and minimising the adverse effects of the involvement of the criminal justice system with people who are addicted to opioids, (5) creating healthy environments that can yield long-term declines in the incidence of addiction, (6) stimulating greater innovation in the response to the opioid crisis, and (7) preventing the North American opioid crisis from spreading globally. The Commission therefore recommends curtailing pharmaceutical product promotion, insulating medical education from pharmaceutical industry influence, closing the so-called revolving door between regulators and industry, making post-approval drug monitoring and risk mitigation a function of government, and firewalling bodies with formal power over prescribing from industry influence. [...]a major investment in

Face-to-face brief interventions for problem drinking are effective, but they have found limited implementation in routine care and the community. Internet-based interventions could overcome this treatment gap. We investigated effectiveness and moderators of treatment outcomes in internet-based interventions for adult problem drinking (iAIs). Systematic searches were performed in medical and psychological databases to 31 December 2016. A one-stage individual patient data meta-analysis (IPDMA) was conducted with a linear mixed model complete-case approach, using baseline and first follow-up data. The primary outcome measure was mean weekly alcohol consumption in standard units (SUs, 10 grams of ethanol). Secondary outcome was treatment response (TR), defined as less than 14/21 SUs for women/men weekly. Putative participant, intervention, and study moderators were included. Robustness was verified in three sensitivity analyses: a two-stage IPDMA, a one-stage IPDMA using multiple imputation, and a missing-not-at-random (MNAR) analysis. We obtained baseline data for 14,198 adult participants (19 randomised controlled trials [RCTs], mean age 40.7 [SD = 13.2], 47.6% women). Their baseline mean weekly alcohol consumption was 38.1 SUs (SD = 26.9). Most were regular problem drinkers (80.1%, SUs 44.7, SD = 26.4) and 19.9% (SUs 11.9, SD = 4.1) were binge-only drinkers. About one third were heavy drinkers, meaning that women/men consumed, respectively, more than 35/50 SUs of alcohol at baseline (34.2%, SUs 65.9, SD = 27.1). Post-intervention data were available for 8,095 participants. Compared with controls, iAI participants showed a greater mean weekly decrease at follow-up of 5.02 SUs (95% CI -7.57 to -2.48, p < 0.001) and a higher rate of TR (odds ratio [OR] 2.20, 95% CI 1.63-2.95, p < 0.001, number needed to treat [NNT] = 4.15, 95% CI 3.06-6.62). Persons above age 55 showed higher TR than their younger counterparts (OR = 1.66, 95% CI 1.21-2.27, p = 0.002). Drinking profiles were not significantly associated with treatment outcomes. Human-supported interventions were superior to fully automated ones on both outcome measures (comparative reduction: -6.78 SUs, 95% CI -12.11 to -1.45, p = 0.013; TR: OR = 2.23, 95% CI 1.22-4.08, p = 0.009). Participants treated in iAIs based on personalised normative feedback (PNF) alone were significantly less likely to sustain low-risk drinking at follow-up than those in iAIs based on integrated therapeutic principles (OR = 0.52, 95% CI 0.29-0.93, p = 0.029). The use of waitlist control in RCTs was associated with significantly better treatment outcomes than the use of other types of control (comparative reduction: -9.27 SUs, 95% CI -13.97 to -4.57, p < 0.001; TR: OR = 3.74, 95% CI 2.13-6.53, p < 0.001). The overall quality of the RCTs was high; a major limitation included high study dropout (43%). Sensitivity analyses confirmed the robustness of our primary analyses. To our knowledge, this is the first IPDMA on internet-based interventions that has shown them to be effective in curbing various patterns of adult problem drinking in both community and healthcare settings. Waitlist control may be conducive to inflation of treatment outcomes.

Binge drinking is associated with numerous negative consequences. The prevalence and intensity of binge drinking is highest among young adults. This randomized trial tested the efficacy of a 12-week interactive text message intervention to reduce binge drinking up to 6 months after intervention completion among young adults. Young adult participants (18-25 y; n = 765) drinking above the low-risk limits (AUDIT-C score >3/4 women/men), but not seeking alcohol treatment, were enrolled from 4 Emergency Departments (EDs) in Pittsburgh, PA. Participants were randomized to one of three conditions in a 2:1:1 allocation ratio: SMS Assessments + Feedback (SA+F), SMS Assessments (SA), or control. For 12 weeks, SA+F participants received texts each Thursday querying weekend drinking plans and prompting drinking limit goal commitment and each Sunday querying weekend drinking quantity. SA+F participants received tailored feedback based on their text responses. To contrast the effects of SA+F with self-monitoring, SA participants received texts on Sundays querying drinking quantity, but did not receive alcohol-specific feedback. The control arm received standard care. Follow-up outcome data collected through web-based surveys were provided by 78% of participants at 3- months, 63% at 6-months and 55% at 9-months. Multiple imputation-derived, intent-to-treat models were used for primary analysis. At 9-months, participants in the SA+F group reported greater reductions in the number of binge drinking days than participants in the control group (incident rate ratio [IRR] 0.69; 95% CI .59 to.79), lower binge drinking prevalence (odds ratio [OR] 0.52; 95% CI 0.26 to 0.98]), less drinks per drinking day (beta -.62; 95% CI -1.10 to -0.15) and lower alcohol-related injury prevalence (OR 0.42; 95% CI 0.21 to 0.88). Participants in the SA group did not reduce drinking or alcohol-related injury relative to controls. Findings were similar using complete case analyses. An interactive text-message intervention was more effective than self-monitoring or controls in reducing alcohol consumption and alcohol-related injury prevalence up to 6 months after intervention completion. These findings, if replicated, suggest a scalable approach to help achieve sustained reductions in binge drinking and accompanying injuries among young adults. ClinicalTrials.gov NCT01688245.

Impairments in gait occur after alcohol consumption, and, if detected in real-time, could guide the delivery of “just-in-time” injury prevention interventions. We aimed to identify the salient features of gait that could be used for estimating blood alcohol content (BAC) level in a typical drinking environment. We recruited 10 young adults with a history of heavy drinking to test our research app. During four consecutive Fridays and Saturdays, every hour from 8 p.m. to 12 a.m., they were prompted to use the app to report alcohol consumption and complete a 5-step straight-line walking task, during which 3-axis acceleration and angular velocity data was sampled at a frequency of 100 Hz. BAC for each subject was calculated. From sensor signals, 24 features were calculated using a sliding window technique, including energy, mean, and standard deviation. Using an artificial neural network (ANN), we performed regression analysis to define a model determining association between gait features and BACs. Part (70%) of the data was then used as a training dataset, and the results tested and validated using the rest of the samples. We evaluated different training algorithms for the neural network and the result showed that a Bayesian regularization neural network (BRNN) was the most efficient and accurate. Analyses support the use of the tandem gait task paired with our approach to reliably estimate BAC based on gait features. Results from this work could be useful in designing effective prevention interventions to reduce risky behaviors during periods of alcohol consumption.

Low-resourced settings often lack personnel and infrastructure for alcohol use disorder treatment. We culturally adapted a Brief Negotiational Interview (BNI) for Emergency Department injury patients, the \"Punguza Pombe Kwa Afya Yako (PPKAY)\" (\"Reduce Alcohol For Your Health\") in Tanzania. This study aimed to evaluate the feasibility of a pragmatic randomized adaptive controlled trial of the PPKAY intervention. This feasibility trial piloted a single-blind, parallel, adaptive, and multi-stage, block-randomized controlled trial, which will subsequently be used to determine the most effective intervention, with or without text message booster, to reduce alcohol use among injury patients. We reported our feasibility pilot study using the Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM) framework, with recruitment and retention rates being our primary and secondary outcomes. We enrolled adult patients seeking care for an acute injury at the Kilimanjaro Christian Medical Center in Tanzania if they (1) exhibited an Alcohol Use Disorder Identification Test (AUDIT) ≥8, (2) disclosed alcohol use prior to injury, or (3) had a breathalyzer ≥0.0 on arrival. Intervention arms were usual care (UC), PPKAY, PPKAY with standard text booster, or a PPKAY with a personalized text booster. Overall, 181 patients were screened and 75 enrolled with 80% 6-week, 82.7% 3-month and 84% 6-month follow-up rates showing appropriate Reach and retention. Adoption measures showed an overwhelmingly positive patient acceptance with 100% of patients perceiving a positive impact on their behavior. The Implementation and trial processes were performed with high rates of PPKAY fidelity (76%) and SMS delivery (74%). Intervention nurses believed Maintenance and sustainability of this 30-minute, low-cost intervention and adaptive clinical trial were feasible. Our intervention and trial design are feasible and acceptable, have evidence of good fidelity, and did not show problematic deviations in protocol. Results suggest support for undertaking a full trial to evaluate the effectiveness of the PPKAY, a nurse-driven BNI in a low-income country. Trial registration number NCT02828267. https://classic.clinicaltrials.gov/ct2/show/NCT02828267.

Home blood pressure monitoring (HBPM) can improve hypertension management. Digital tools to facilitate routinized HBPM and patient self-care are underutilized and lack evidence of effectiveness. MyBP provides video-based education and automated text messaging to support continuous BP self-monitoring with recurring feedback. In this pragmatic trial, we sought to generate preliminary evidence of feasibility and efficacy in community-dwelling adults ≥55 y/o with hypertension recruited from primary care offices. Enrollees were provided a standard automatic BP cuff and randomized 2:1 to MyBP vs treatment-as-usual (control). Engagement with MyBP was defined as the proportion of BP reading prompts for which a reading was submitted, tracked over successive 2-week monitoring periods. Preliminary measures of efficacy included BP readings from phone-supervised home measurements and a self-efficacy questionnaire. Sixty-two participants (40 women, 33 Blacks, mean age 66, mean office BP 164/91) were randomized to MyBP (n = 41) or a control group (n = 21). Median follow-up was 22.9 (SD = 6.7) weeks. In the MyBP group, median engagement with HBPM was 82.7% (Q1 = 52.5, Q3 = 89.6) and sustained over time. The decline in systolic [12 mm Hg (SD = 17)] and diastolic BP [5 mm Hg (SD = 7)] did not differ between the two treatment groups. However, participants with higher baseline systolic BP assigned to MyBP had a greater decline compared to controls [interaction effect estimate −0.56 (−0.96, −0.17)]. Overall hypertension self-efficacy improved in the MyBP group. In conclusion, trial results show that older hypertensive adults with substantial minority representation had sustained engagement with this digital self-monitoring program and may benefit clinically.

Identifying older adults with risk for falls prior to discharge home from the Emergency Department (ED) could help direct fall prevention interventions, yet ED-based tools to assist risk stratification are under-developed. The aim of this study was to assess the performance of self-report and functional assessments to predict falls in the 3 months post-ED discharge for older adults. A prospective cohort of community-dwelling adults age 60 years and older were recruited from one urban ED (N = 134). Participants completed: a single item screen for mobility (SIS-M), the 12-item Stay Independent Questionnaire (SIQ-12), and the Timed Up and Go test (TUG). Falls were defined through self-report of any fall at 1- and 3-months and medical record review for fall-related injury 3-months post-discharge. We developed a hybrid-convolutional recurrent neural network (HCRNN) model of gait and balance characteristics using truncal 3-axis accelerometry collected during the TUG. Internal validation was conducted using bootstrap resampling with 1000 iterations for SIS-M, FRQ, and GUG and leave-one-out for the HCRNN. We compared performance of M-SIS, FRQ, TUG time, and HCRNN by calculating the area under the receiver operating characteristic area under the curves (AUCs). 14 (10.4%) of participants met our primary outcome of a fall or fall-related injury within 3-months. The SIS-M had an AUC of 0.42 [95% confidence interval (CI) 0.19–0.65]. The SIQ-12 score had an AUC of 0.64 [95% confidence interval (CI) 0.49–0.80]. The TUG had an AUC of 0.48 (95% CI 0.29–0.68). The HCRNN model using generated accelerometer features collected during the TUG had an AUC of 0.99 (95% CI 0.98–1.00). We found that self-report and functional assessments lack sufficient accuracy to be used in isolation in the ED. A neural network model using accelerometer features could be a promising modality but research is needed to externally validate these findings. •Self-reported screening tools lack sufficient accuracy to identify older adults who will fall.•Time to complete the Get Up and Go task lacks sufficient accuracy to identify older adults who will fall.•A neural network model of 3-axis accelerometer features collected during the TUG may be able to improve accuracy.

Many adolescents with depression do not pursue mental health treatment following a health care provider referral. We developed a theory-based automated SMS text message intervention (Text to Connect [T2C]) that attempts to reduce cognitive barriers to the initiation of mental health care. In this two-phase study, we seek to first understand the potential of T2C and then test its engagement, usability, and potential efficacy among adolescents with depression and their parents or caregivers. In phase 1, we conducted focus groups with adolescents with depression (n=9) and their parents or caregivers (n=9) separately, and transcripts were examined to determine themes. In phase 2, we conducted an open trial of T2C comprising adolescents with depression referred to mental health care (n=43) and their parents or caregivers (n=28). We assessed usability by examining program engagement, usability ratings, and qualitative feedback at the 4-week follow-up. We also assessed potential effectiveness by examining changes in perceived barriers to treatment and mental health care initiation from baseline to 4 weeks. In phase 1, we found that the themes supported the T2C approach. In phase 2, we observed high engagement with daily negative affect check-ins, high usability ratings, and decreased self-reported barriers to mental health treatment over time among adolescents. Overall, 52% (22/42) of the adolescents who completed follow-up reported that they had attended an appointment with a mental health care specialist. Of the 20 adolescents who had not attended a mental health care appointment, 5% (1/20) reported that it was scheduled for a future date, 10% (2/20) reported that the primary care site did not have the ability to help them schedule a mental health care appointment, and 15% (3/20) reported that they were no longer interested in receiving mental health care. The findings from this study suggest that T2C is acceptable to adolescents with depression and most parents or caregivers; it is used at high rates; and it may be helpful to reduce cognitive barriers to mental health care initiation.

Background: The transition from high school to college can exacerbate mental health problems in young adults yet barriers prevent seamless mental health care. Existing digital support tools show promise but are not yet designed to optimize engagement or implementation. Objective: The goal of the research was to test acceptability and effects of an automated digital Mobile Support Tool for Mental Health (MoST-MH) for young adults transitioning to college. Methods: Youths aged 18 years and older with a current mental health diagnosis preparing to transition to college (n=52; 85% female [45/52], 91% White [48/52]) were recruited from a primary care (n=31) and a mental health clinic (n=21). Participants were randomized 2:1 to either receive MoST-MH (n=34) or enhanced Usual Care (eUC; n=18). MoST-MH included periodic text message and web-based check-ins of emotional health, stressors, negative impacts, and self-efficacy that informed tailored self-care support messages. Both eUC and MoST-MH participants received links to a library of psychoeducational videos and were asked to complete web-based versions of the Mental Health Self-Efficacy Scale (MHSES), College Counseling Center Assessment of Psychological Symptoms (CCAPS), and Client Service Receipt Inventory for Mental Health (C-SRI) monthly for 3 months and the Post-Study System Usability Scale (PSSUQ) at 3-months. Results: MoST-MH participants were sent a median of 5 (range 3 to 10) text message check-in prompts over the 3-month study period and 100% were completed; participants were sent a median of 2 (range 1 to 8) web-based check-in prompts among which 78% (43/55) were completed. PSSUQ scores indicate high usability (mean score 2.0). Results from the completer analysis demonstrated reductions in mental health symptoms over time and significant between-group effects of MoST-MH compared to eUC on depressive symptom severity (d=0.36, 95% CI 0.08 to 0.64). No significant differences in mental health self-efficacy or mental health health care use were observed. Conclusions: In this pilot trial, we found preliminary evidence that MoST-MH was engaged with at high rates and found to be highly usable and reduced depression symptoms relative to eUC among youth with mental health disorders transitioning to college. Findings were measured during the COVID-19 pandemic, and the study was not powered to detect differences in outcomes between groups; therefore, further testing is needed. Trial Registration: ClinicalTrials.gov NCT04560075; https://clinicaltrials.gov/ct2/show/NCT04560075