Effects of Chatbot Components to Facilitate Mental Health Services Use in Individuals With Eating Disorders Following Online Screening: An Optimization Randomized Controlled Trial.

OBJECTIVE: Few individuals with eating disorders (EDs) receive treatment. Innovations are needed to identify individuals with EDs and address care barriers. We developed a chatbot for promoting services uptake that could be paired with online screening. However, it is not yet known which components drive effects. This study estimated individual and combined contributions of four chatbot components on mental health services use (primary), chatbot helpfulness, and attitudes toward changing eating/shape/weight concerns ("change attitudes," with higher scores indicating greater importance/readiness). METHODS: Two hundred five individuals screening with an ED but not in treatment were randomized in an optimization randomized controlled trial to receive up to four chatbot components: psychoeducation, motivational interviewing, personalized service recommendations, and repeated administration (follow-up check-ins/reminders). Assessments were at baseline and 2, 6, and 14 weeks. RESULTS: Participants who received repeated administration were more likely to report mental health services use, with no significant effects of other components on services use. Repeated administration slowed the decline in change attitudes participants experienced over time. Participants who received motivational interviewing found the chatbot more helpful, but this component was also associated with larger declines in change attitudes. Participants who received personalized recommendations found the chatbot more helpful, and receiving this component on its own was associated with the most favorable change attitude time trend. Psychoeducation showed no effects. DISCUSSION: Results indicated important effects of components on outcomes; findings will be used to finalize decision making about the optimized intervention package. The chatbot shows high potential for addressing the treatment gap for EDs.

Decision-making in the multiphase optimization strategy: Applying decision analysis for intervention value efficiency to optimize an information leaflet to promote key antecedents of medication adherence.

Advances in the multiphase optimization strategy (MOST) have suggested a new approach, decision analysis for intervention value efficiency (DAIVE), for selecting an optimized intervention based on the results of a factorial optimization trial. The new approach opens possibilities to select optimized interventions based on multiple valued outcomes. We applied DAIVE to identify an optimized information leaflet intended to support eventual adherence to adjuvant endocrine therapy for women with breast cancer. We used empirical performance data for five candidate leaflet components on three hypothesized antecedents of adherence: beliefs about the medication, objective knowledge about AET, and satisfaction with medication information. Using data from a 25 factorial trial (n = 1603), we applied the following steps: (i) We used Bayesian factorial analysis of variance to estimate main and interaction effects for the five factors on the three outcomes. (ii) We used posterior distributions for main and interaction effects to estimate expected outcomes for each leaflet version (32 total). (iii) We scaled and combined outcomes using a linear value function with predetermined weights indicating the relative importance of outcomes. (iv) We identified the leaflet that maximized the value function as the optimized leaflet, and we systematically varied outcome weights to explore robustness. The optimized leaflet included two candidate components, side-effects, and patient input, set to their higher levels. Selection was generally robust to weight variations consistent with the initial preferences for three outcomes. DAIVE enables selection of optimized interventions with the best-expected performance on multiple outcomes.

Intervention optimization involves using data from an optimization trial to select the combination of intervention components that are expected to successfully balance effectiveness (i.e. improving an outcome in the desired direction) with efficiency (i.e. producing a good outcome without wasting resources). Recently, a new method for selecting optimized interventions has been proposed that has a number of advantages, including the ability to use empirical information about more than one outcome variable of interest. Here, we applied this new method to identify an optimized information leaflet designed to support eventual medication adherence in women with breast cancer, using empirical information about three outcome variables that are thought to be important for later medication adherence: beliefs about the medication, objective knowledge about the medication, and satisfaction with the leaflet information. When we let beliefs about the medication be most important; knowledge about the medication to be half as important as beliefs; and satisfaction with information to be half as important as knowledge, the optimized leaflet included enhanced information about side-effects and photos and quotes from women with breast cancer. This decision remained generally the same when we systematically varied the weights used to give outcomes their relative importance.

Empirical Development of a Behavioral Intervention for African American/Black and Latino Persons with Unsuppressed HIV Viral Load Levels: An Application of the Multiphase Optimization Strategy (MOST) Using Cost-Effectiveness as an Optimization Objective.

We used results from an optimization randomized controlled trial which tested five behavioral intervention components to support HIV antiretroviral adherence/HIV viral suppression, grounded in the multiphase optimization strategy and using a fractional factorial design to identify intervention components with cost-effectiveness sufficiently favorable for scalability. Results were incorporated into a validated HIV computer simulation to simulate longer-term effects of combinations of components on health and costs. We simulated the 32 corresponding long-term trajectories for viral load suppression, health related quality of life (HRQoL), and costs. The components were designed to be culturally and structurally salient. They were: motivational interviewing counseling sessions (MI), pre-adherence skill building (SB), peer mentorship (PM), focused support groups (SG), and patient navigation (short version [NS], long version [NL]. All participants also received health education on HIV treatment. We examined four scenarios: one-time intervention with and without discounting and continuous interventions with and without discounting. In all four scenarios, interventions that comprise or include SB and NL (and including health education) were cost effective (< $100,000/quality-adjusted life year). Further, with consideration of HRQoL impact, maximal intervention became cost-effective enough to be scalable. Thus, a fractional factorial experiment coupled with cost-effectiveness analysis is a promising approach to optimize multi-component interventions for scalability. The present study can guide service planning efforts for HIV care settings and health departments.

Intervention Optimization: A Paradigm Shift and Its Potential Implications for Clinical Psychology.

To build a coherent knowledge base about what psychological intervention strategies work, develop interventions that have positive societal impact, and maintain and increase this impact over time, it is necessary to replace the classical treatment package research paradigm. The multiphase optimization strategy (MOST) is an alternative paradigm that integrates ideas from behavioral science, engineering, implementation science, economics, and decision science. MOST enables optimization of interventions to strategically balance effectiveness, affordability, scalability, and efficiency. In this review we provide an overview of MOST, discuss several experimental designs that can be used in intervention optimization, consider how the investigator can use experimental results to select components for inclusion in the optimized intervention, discuss the application of MOST in implementation science, and list future issues in this rapidly evolving field. We highlight the feasibility of adopting this new research paradigm as well as its potential to hasten the progress of psychological intervention science.

Optimizing Interventions for Equitability: Some Initial Ideas.

Interventions (including behavioral, biobehavioral, biomedical, and social-structural interventions) hold tremendous potential not only to improve public health overall but also to reduce health disparities and promote health equity. In this study, we introduce one way in which interventions can be optimized for health equity in a principled fashion using the multiphase optimization strategy (MOST). Specifically, we define intervention equitability as the extent to which the health benefits provided by an intervention are distributed evenly versus concentrated among those who are already advantaged, and we suggest that, if intervention equitability is acknowledged to be a priority, then equitability should be a key criterion that is balanced with other criteria (effectiveness overall, as well as affordability, scalability, and/or efficiency) in intervention optimization. Using a hypothetical case study and simulated data, we show how MOST can be applied to achieve a strategic balance that incorporates equitability. We also show how the composition of an optimized intervention can differ when equitability is considered versus when it is not. We conclude with a vision for next steps to build on this initial foray into optimizing interventions for equitability.

What to do after smoking relapse? A sequential multiple assignment randomized trial of chronic care smoking treatments.

AIM: To compare effects of three post-relapse interventions on smoking abstinence. DESIGN: Sequential three-phase multiple assignment randomized trial (SMART). SETTING: Eighteen Wisconsin, USA, primary care clinics. PARTICIPANTS: A total of 1154 primary care patients (53.6% women, 81.2% White) interested in quitting smoking enrolled from 2015 to 2019; 582 relapsed and were randomized to relapse recovery treatment. INTERVENTIONS: In phase 1, patients received cessation counseling and 8 weeks nicotine patch. Those who relapsed and agreed were randomized to a phase 2 relapse recovery group: (1) reduction counseling + nicotine mini-lozenges + encouragement to quit starting 1 month post-randomization (preparation); (2) repeated encouragement to quit starting immediately post-randomization (recycling); or (3) advice to call the tobacco quitline (control). The first two groups could opt into phase 3 new quit treatment [8 weeks nicotine patch + mini-lozenges plus randomization to two treatment factors (skill training and supportive counseling) in a 2 × 2 design]. Phase 2 and 3 interventions lasted ≤ 15 months. MEASUREMENTS: The study was powered to compare each active phase 2 treatment with the control on the primary outcome: biochemically confirmed 7-day point-prevalence abstinence 14 months post initiating phase 2 relapse recovery treatment. Exploratory analyses tested for phase 3 counseling factor effects. FINDINGS: Neither skill training nor supportive counseling (each on versus off) increased 14-month abstinence rates; skills on versus off 9.3% (14/151) versus 5.2% (8/153), P = 0.19; support on versus off 6.6% (10/152) versus 7.9% (12/152), P = 0.73. Phase 2 preparation did not produce higher 14-month abstinence rates than quitline referral; 3.6% (8/220) versus 2.1% [3/145; risk difference = 1.5%, 95% confidence interval (CI) = -1.8-5.0%, odds ratio (OR) = 1.8, 95% CI = 0.5-6.9]. Recycling, however, produced higher abstinence rates than quitline referral; 6.9% (15/217) versus 2.1% (three of 145; risk difference, 4.8%, 95% CI = 0.7-8.9%, OR = 3.5, 95% CI = 1.0-12.4). Recycling produced greater entry into new quit treatment than preparation: 83.4% (181/217) versus 55.9% (123/220), P < 0.0001. CONCLUSIONS: Among people interested in quitting smoking, immediate encouragement post-relapse to enter a new round of smoking cessation treatment ('recycling') produced higher probability of abstinence than tobacco quitline referral. Recycling produced higher rates of cessation treatment re-engagement than did preparation/cutting down using more intensive counseling and pharmacotherapy.

Using decision analysis for intervention value efficiency to select optimized interventions in the multiphase optimization strategy.

OBJECTIVE: Optimizing multicomponent behavioral and biobehavioral interventions presents a complex decision problem. To arrive at an intervention that is both effective and readily implementable, it may be necessary to weigh effectiveness against implementability when deciding which components to select for inclusion. Different components may have differential effectiveness on an array of outcome variables. Moreover, different decision-makers will approach this problem with different objectives and preferences. Recent advances in decision-making methodology in the multiphase optimization strategy (MOST) have opened new possibilities for intervention scientists to optimize interventions based on a wide variety of decision-maker preferences, including those that involve multiple outcome variables. In this study, we introduce decision analysis for intervention value efficiency (DAIVE), a decision-making framework for use in MOST that incorporates these new decision-making methods. We apply DAIVE to select optimized interventions based on empirical data from a factorial optimization trial. METHOD: We define various sets of hypothetical decision-maker preferences, and we apply DAIVE to identify optimized interventions appropriate to each case. RESULTS: We demonstrate how DAIVE can be used to make decisions about the composition of optimized interventions and how the choice of optimized intervention can differ according to decision-maker preferences and objectives. CONCLUSIONS: We offer recommendations for intervention scientists who want to apply DAIVE to select optimized interventions based on data from their own factorial optimization trials. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Investigation of Active Ingredients Within Internet-Delivered Cognitive Behavioral Therapy for Depression: A Randomized Optimization Trial.

Importance: There is limited understanding of how complex evidence-based psychological interventions such as cognitive behavioral therapy (CBT) for depression work. Identifying active ingredients may help to make therapy more potent, brief, and scalable. Objective: To test the individual main effects and interactions of 7 treatment components within internet-delivered CBT for depression to investigate its active ingredients. Design, Setting, and Participants: This randomized optimization trial using a 32-condition, balanced, fractional factorial optimization experiment (IMPROVE-2) recruited adults with depression (Patient Health Questionnaire-9 [PHQ-9] score ≥10) from internet advertising and the UK National Health Service Improving Access to Psychological Therapies service. Participants were randomized from July 7, 2015, to March 29, 2017, with follow-up for 6 months after treatment until December 29, 2017. Data were analyzed from July 2018 to April 2023. Interventions: Participants were randomized with equal probability to 7 experimental factors within the internet CBT platform, each reflecting the presence vs absence of specific treatment components (activity scheduling, functional analysis, thought challenging, relaxation, concreteness training, absorption, and self-compassion training). Main Outcomes and Measures: The primary outcome was depression symptoms (PHQ-9 score). Secondary outcomes include anxiety symptoms and work, home, and social functioning. Results: Among 767 participants (mean age [SD] age, 38.5 [11.62] years; range, 18-76 years; 635 women [82.8%]), 506 (66%) completed the 6-month posttreatment follow-up. On average, participants receiving internet-delivered CBT had reduced depression (pre-to-posttreatment difference in PHQ-9 score, -7.79 [90% CI, -8.21 to -7.37]; 6-month follow-up difference in PHQ-9 score, -8.63 [90% CI, -9.04 to -8.22]). A baseline score-adjusted analysis of covariance model using effect-coded intervention variables (-1 or +1) found no main effect on depression symptoms for the presence vs absence of activity scheduling, functional analysis, thought challenging, relaxation, concreteness training, or self-compassion training (posttreatment: largest difference in PHQ-9 score [functional analysis], -0.09 [90% CI, -0.56 to 0.39]; 6-month follow-up: largest difference in PHQ-9 score [relaxation], -0.18 [90% CI, -0.61 to 0.25]). Only absorption training had a significant main effect on depressive symptoms at 6-month follow-up (posttreatment difference in PHQ-9 score, 0.21 [90% CI, -0.27 to 0.68]; 6-month follow-up difference in PHQ-9 score, -0.54, [90% CI, -0.97 to -0.11]). Conclusions and Relevance: In this randomized optimization trial, all components of internet-delivered CBT except absorption training did not significantly reduce depression symptoms relative to their absence despite an overall average reduction in symptoms. The findings suggest that treatment benefit from internet-delivered CBT probably accrues from spontaneous remission, factors common to all CBT components (eg, structure, making active plans), and nonspecific therapy factors (eg, positive expectancy), with the possible exception of absorption focused on enhancing direct contact with positive reinforcers. Trial Registration: isrctn.org Identifier: ISRCTN24117387.

Effects of Behavioral Intervention Components for African American/Black and Latino Persons Living with HIV with Non-suppressed Viral Load Levels: Results of an Optimization Trial.

There is an urgent need for efficient behavioral interventions to increase rates of HIV viral suppression for populations with serious barriers to engagement along the HIV care continuum. We carried out an optimization trial to test the effects of five behavioral intervention components designed to address barriers to HIV care continuum engagement for African American/Black and Latino persons living with HIV (PLWH) with non-suppressed HIV viral load levels: motivational interviewing sessions (MI), focused support groups (SG), peer mentorship (PM), pre-adherence skill building (SB), and navigation with two levels, short (NS) and long (NL). The primary outcome was HIV viral suppression (VS) and absolute viral load (VL) and health-related quality of life were secondary outcomes. Participants were 512 African American/Black and Latino PLWH poorly engaged in HIV care and with detectable HIV viral load levels in New York City, recruited mainly through peer referral. Overall, VS increased to 37%, or 45% in a sensitivity analysis. MI and SG seemed to have antagonistic effects on VS (z = - 1.90; p = 0.057); the probability of VS was highest when either MI or SG was assigned, but not both. MI (Mean Difference = 0.030; 95% CI 0.007-0.053; t(440) = 2.60; p = 0.010) and SB (Mean Difference = 0.030; 95% CI 0.007-0.053; t(439) = 2.54; p = 0.012) improved health-related quality of life. This is the first optimization trial in the field of HIV treatment. The study yields a number of insights into approaches to improve HIV viral suppression in PLWH with serious barriers to engagement along the HIV care continuum, including chronic poverty, and underscores challenges inherent in doing so.

A posterior expected value approach to decision-making in the multiphase optimization strategy for intervention science.

In current practice, intervention scientists applying the multiphase optimization strategy (MOST) with a 2k factorial optimization trial use a component screening approach (CSA) to select intervention components for inclusion in an optimized intervention. In this approach, scientists review all estimated main effects and interactions to identify the important ones based on a fixed threshold, and then base decisions about component selection on these important effects. We propose an alternative posterior expected value approach based on Bayesian decision theory. This new approach aims to be easier to apply and more readily extensible to a variety of intervention optimization problems. We used Monte Carlo simulation to evaluate the performance of a posterior expected value approach and CSA (automated for simulation purposes) relative to two benchmarks: random component selection, and the classical treatment package approach. We found that both the posterior expected value approach and CSA yielded substantial performance gains relative to the benchmarks. We also found that the posterior expected value approach outperformed CSA modestly but consistently in terms of overall accuracy, sensitivity, and specificity, across a wide range of realistic variations in simulated factorial optimization trials. We discuss implications for intervention optimization and promising future directions in the use of posterior expected value to make decisions in MOST. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Cost-Effectiveness of Smoking Cessation Approaches in Emergency Departments.

INTRODUCTION: Americans of lower SES use tobacco products at disproportionately high rates and are over-represented as patients of emergency departments. Accordingly, emergency department visits are an ideal time to initiate tobacco treatment and aftercare for this vulnerable and understudied population. This research estimates the costs per quit of emergency department smoking-cessation interventions and compares them with those of other approaches. METHODS: Previously published research described the effectiveness of 2 multicomponent smoking cessation interventions, including brief negotiated interviewing, nicotine replacement therapy, quitline referral, and follow-up communication. Study 1 (collected in 2010-2012) only analyzed the combined interventions. Study 2 (collected in 2017-2019) analyzed the intervention components independently. Costs per participant and per quit were estimated separately, under distinct intervention with dedicated staff and intervention with repurposed staff assumptions. The distinction concerns whether the intervention used dedicated staff for delivery or whether time from existing staff was repurposed for intervention if available. RESULTS: Data were analyzed in 2021-2022. In the first study, the cost per participant was $860 (2018 dollars), and the cost per quit was $11,814 (95% CI=$7,641, $25,423) (dedicated) and $227 per participant and $3,121 per quit (95% CI=$1,910, $7,012) (repurposed). In Study 2, the combined effect of brief negotiated interviewing, nicotine replacement therapy, and quitline cost $808 per participant and $6,100 per quit (dedicated) (95% CI=$4,043, $12,274) and $221 per participant and $1,669 per quit (95% CI=$1,052, $3,531) (repurposed). CONCLUSIONS: Costs varied considerably per method used but were comparable with those of other smoking cessation interventions.

Exploring behavioral intervention components for African American/Black and Latino persons living with HIV with non-suppressed HIV viral load in the United States: a qualitative study.

BACKGROUND: The persistence of racial/ethnic inequities in rates of engagement along the HIV care continuum signals the need for novel approaches. We developed six behavioral intervention components for use in an optimization trial, grounded in a model that integrates critical race theory, harm reduction, and self-determination theory, designed to address various barriers that African American/Black and Latino persons living with HIV (PLWH) experience to the HIV care continuum. The components were: health education, motivational interviewing sessions, pre-adherence skill building, peer mentorship, focused support groups, and navigation. The present qualitative exploratory study describes participants' perspectives on the components' acceptability, feasibility, and impact. METHODS: Participants were African American/Black and Latino PLWH poorly engaged in HIV care and with non-suppressed HIV viral load in New York City. From a larger trial, we randomly selected 46 participants for in-depth semi-structured interviews. Interviews were audio-recorded and transcribed verbatim, and data were analyzed using directed content analysis. Quantitative data on sociodemographic and background characteristics and components' acceptability and feasibility were also collected. RESULTS: On average, participants were 49 years old and had lived with HIV for 19 years. Most were cisgender-male and African American/Black. Participants reported a constellation of serious social and structural challenges to HIV management including chronic poverty, unstable housing, and stigma. Across components, a non-judgmental and pressure-free approach and attention to structural and cultural factors were seen as vital to high levels of engagement, but lacking in most medical/social service settings. Prominent aspects of individual components included establishing trust (health education); developing intrinsic motivation, goals, and self-reflection (motivational interviewing sessions); learning/practicing adherence strategies and habits (pre-adherence skill building); reducing social isolation via peer role models (peer mentorship); reflecting on salient goals and common challenges with peers without stigma (focused support groups); and circumventing structural barriers to HIV management with support (navigation). Components were found acceptable and feasible. Findings suggested ways components could be improved. CONCLUSIONS: The present study advances research on interventions for African American/Black and Latino PLWH, who experience complex barriers to engagement along the HIV care continuum. Future study of the components is warranted to address racial/ethnic health inequities in HIV.

Successful Optimization of Tobacco Dependence Treatment in the Emergency Department: A Randomized Controlled Trial Using the Multiphase Optimization Strategy.

STUDY OBJECTIVE: Tobacco dependence treatment initiated in the hospital emergency department (ED) is effective. However, trials typically use multicomponent interventions, making it difficult to distinguish specific components that are effective. In addition, interactions between components cannot be assessed. The Multiphase Optimization Strategy allows investigators to identify these effects. METHODS: We conducted a full-factorial, 24 or 16-condition optimization trial in a busy hospital ED to examine the performance of 4 tobacco dependence interventions: a brief negotiation interview; 6 weeks of nicotine replacement therapy with the first dose delivered in the ED; active referral to a telephone quitline; and enrollment in SmokefreeTXT, a free short-messaging service program. Study data were analyzed with a novel mixed methods approach to assess clinical efficacy, cost-effectiveness, and qualitative participant feedback. The primary endpoint was tobacco abstinence at 3 months, verified by exhaled carbon monoxide using a Bedfont Micro+ Smokerlyzer. RESULTS: Between February 2017 and May 2019, we enrolled 1,056 adult smokers visiting the ED. Odd ratios (95% confidence intervals) from the primary analysis of biochemically confirmed abstinence rates at 3 months for each intervention, versus control, were: brief negotiation interview, 1.8 (1.1, 2.8); nicotine replacement therapy, 2.1 (1.3, 3.2); quitline, 1.4 (0.9, 2.2); SmokefreeTXT, 1.1 (0.7, 1.7). There were no statistically significant interactions among components. Economic and qualitative analyses are in progress. CONCLUSION: The brief negotiation interview and nicotine replacement therapy were efficacious. This study is the first to identify components of ED-initiated tobacco dependence treatment that are individually effective. Future work will address the scalability of the brief negotiation interview and nicotine replacement therapy by offering provider-delivered brief negotiation interviews and nicotine replacement therapy prescriptions.

Understanding heterogeneity of responses to, and optimizing clinical efficacy of, exercise training in older adults: NIH NIA Workshop summary.

Exercise is a cornerstone of preventive medicine and a promising strategy to intervene on the biology of aging. Variation in the response to exercise is a widely accepted concept that dates back to the 1980s with classic genetic studies identifying sequence variations as modifiers of the VO2max response to training. Since that time, the literature of exercise response variance has been populated with retrospective analyses of existing datasets that are limited by a lack of statistical power from technical error of the measurements and small sample sizes, as well as diffuse outcomes, very few of which have included older adults. Prospective studies that are appropriately designed to interrogate exercise response variation in key outcomes identified a priori and inclusive of individuals over the age of 70 are long overdue. Understanding the underlying intrinsic (e.g., genetics and epigenetics) and extrinsic (e.g., medication use, diet, chronic disease) factors that determine robust versus poor responses to various exercise factors will be used to improve exercise prescription to target the pillars of aging and optimize the clinical efficacy of exercise training in older adults. This review summarizes the proceedings of the NIA-sponsored workshop entitled, "Understanding Heterogeneity of Responses to, and Optimizing Clinical Efficacy of, Exercise Training in Older Adults" and highlights the importance and current state of exercise response variation research, particularly in older adults, prevailing challenges, and future directions.

Preventing Mental Health Problems in Children After High Conflict Parental Separation/Divorce Study: An Optimization Randomized Controlled Trial Protocol.

Parental divorce is a childhood stressor that affects approximately 1.1 million children in the U.S. annually. The children at greatest risk for deleterious mental health consequences are those exposed to high interparental conflict (IPC) following the separation/divorce. Research shows that children's emotional security and coping efficacy mediate the impact of IPC on their mental health. Interventions targeting their adaptive coping in response to IPC events may bolster their emotional security and coping efficacy. However, existing coping interventions have not been tested with children exposed to high post-separation/divorce IPC, nor has any study assessed the effects of individual intervention components on children's coping with IPC and their mental health. This intensive longitudinal intervention study examines the mechanisms through which coping intervention components impact children's responses to interactions in interparental relationships. A 23 factorial experiment will assess whether, and to what extent, three candidate intervention components demonstrate main and interactive effects on children's coping and mental health. Children aged 9-12 (target N = 144) will be randomly assigned to one of eight combinations of three components with two levels each: (1) reappraisal (present vs. absent), (2) distraction (present vs. absent), (3) relaxation (present vs. absent). The primary outcomes are child-report emotional security and coping efficacy at one-month post-intervention. Secondary outcomes include internalizing and externalizing problems at the three-month follow-up. Based on data from this optimization phase RCT, intervention components will be selected to comprise a multi-component intervention and assessed for effectiveness in a subsequent evaluation phase RCT.

Advancing behavioral interventions for African American/Black and Latino persons living with HIV using a new conceptual model that integrates critical race theory, harm reduction, and self-determination theory: a qualitative exploratory study.

BACKGROUND: Rates of participation in HIV care, medication uptake, and viral suppression are improving among persons living with HIV (PLWH) in the United States. Yet, disparities among African American/Black and Latino PLWH are persistent, signaling the need for new conceptual approaches. To address gaps in services and research (e.g., insufficient attention to structural/systemic factors, inadequate harm reduction services and autonomy support) and improve behavioral interventions, we integrated critical race theory, harm reduction, and self-determination theory into a new conceptual model, then used the model to develop a set of six intervention components which were tested in a larger study. The present qualitative study explores participants' perspectives on the study's acceptability, feasibility, and impact, and the conceptual model's contribution to these experiences. METHODS: Participants in the larger study were African American/Black and Latino PLWH poorly engaged in HIV care and with non-suppressed HIV viral load in New York City (N = 512). We randomly selected N = 46 for in-depth semi-structured interviews on their experiences with and perspectives on the study. Interviews were audio-recorded and professionally transcribed verbatim, and data were analyzed using directed qualitative content analysis. RESULTS: On average, participants were 49 years old (SD = 9) and had lived with HIV for 19 years (SD = 7). Most were male (78%) and African American/Black (76%). All had taken HIV medication previously. Challenging life contexts were the norm, including poverty, poor quality/unstable housing, trauma histories exacerbated by current trauma, health comorbidities, and substance use. Participants found the study highly acceptable. We organized results into four themes focused on participants' experiences of: 1) being understood as a whole person and in their structural/systemic context; 2) trustworthiness and trust; 3) opportunities for self-reflection; and 4) support of personal autonomy. The salience of nonjudgment was prominent in each theme. Themes reflected grounding in the conceptual model. Participants reported these characteristics were lacking in HIV care settings. CONCLUSIONS: The new conceptual model emphasizes the salience of systemic/structural and social factors that drive health behavior and the resultant interventions foster trust, self-reflection, engagement, and behavior change. The model has potential to enhance intervention acceptability, feasibility, and effectiveness with African American/Black and Latino PLWH.

Components of smartphone cognitive-behavioural therapy for subthreshold depression among 1093 university students: a factorial trial.

BACKGROUND: Internet-based cognitive-behavioural therapy (iCBT) is effective for subthreshold depression. However, which skills provided in iCBT packages are more effective than others is unclear. Such knowledge can inform construction of more effective and efficient iCBT programmes. OBJECTIVE: To examine the efficacy of five components of iCBT for subthreshold depression. METHODS: We conducted an factorial trial using a smartphone app, randomly allocating presence or absence of five iCBT skills including self-monitoring, behavioural activation (BA), cognitive restructuring (CR), assertiveness training (AT) and problem-solving. Participants were university students with subthreshold depression. The primary outcome was the change on the Patient Health Questionnaire-9 (PHQ-9) from baseline to week 8. Secondary outcomes included changes in CBT skills. FINDINGS: We randomised a total of 1093 participants. In all groups, participants had a significant PHQ-9 reduction from baseline to week 8. Depression reduction was not significantly different between presence or absence of any component, with corresponding standardised mean differences (negative values indicate specific efficacy in favour of the component) ranging between -0.04 (95% CI -0.16 to 0.08) for BA and 0.06 (95% CI -0.06 to 0.18) for AT. Specific CBT skill improvements were noted for CR and AT but not for the others. CONCLUSIONS: There was significant reduction in depression for all participants regardless of the presence and absence of the examined iCBT components. CLINICAL IMPLICATION: We cannot yet make evidence-based recommendations for specific iCBT components. We suggest that future iCBT optimisation research should scrutinise the amount and structure of components to examine. TRIAL REGISTRATION NUMBER: UMINCTR-000031307.

The microrandomized trial for developing digital interventions: Experimental design and data analysis considerations.

Just-in-time adaptive interventions (JITAIs) are time-varying adaptive interventions that use frequent opportunities for the intervention to be adapted-weekly, daily, or even many times a day. The microrandomized trial (MRT) has emerged for use in informing the construction of JITAIs. MRTs can be used to address research questions about whether and under what circumstances JITAI components are effective, with the ultimate objective of developing effective and efficient JITAI. The purpose of this article is to clarify why, when, and how to use MRTs; to highlight elements that must be considered when designing and implementing an MRT; and to review primary and secondary analyses methods for MRTs. We briefly review key elements of JITAIs and discuss a variety of considerations that go into planning and designing an MRT. We provide a definition of causal excursion effects suitable for use in primary and secondary analyses of MRT data to inform JITAI development. We review the weighted and centered least-squares (WCLS) estimator which provides consistent causal excursion effect estimators from MRT data. We describe how the WCLS estimator along with associated test statistics can be obtained using standard statistical software such as R (R Core Team, 2019). Throughout we illustrate the MRT design and analyses using the HeartSteps MRT, for developing a JITAI to increase physical activity among sedentary individuals. We supplement the HeartSteps MRT with two other MRTs, SARA and BariFit, each of which highlights different research questions that can be addressed using the MRT and experimental design considerations that might arise. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Advances in clinical trials methodology: Intervention optimization approaches in emergency medicine.

The classical two-arm randomized clinical trial (RCT) is designed to test the efficacy or effectiveness of an intervention, which may consist of one or more components. However, this approach does not enable the investigator to obtain information that is important in intervention development, such as which individual components of the intervention are efficacious, which are not and possibly should be removed, and whether any components interact. The Multiphase Optimization Strategy (MOST) is a new framework for development, optimization, and evaluation of interventions. MOST includes the RCT for purposes of evaluation, but inserts a phase of research before the RCT aimed at intervention optimization. The optimization phase requires one or more separate trials similar in scope to an RCT, but employing a different experimental design. The design of the optimization trial is selected strategically so as to maximize the amount of scientific information gained using the available resources. One consideration in selecting this experimental design is the type of intervention to be optimized. If a fixed intervention, i.e. one in which the same intervention content and intensity is provided to all participants, is to be optimized, a factorial experiment is often appropriate. If an adaptive intervention, i.e. one in which intervention content or intensity is varied in a principled manner, is to be optimized, a sequential multiple-assignment randomized trial (SMART) is often a good choice. The objective of this article is to describe MOST and the scientific rationale for its use; describe two current applications of MOST in emergency medicine research, one using a factorial experiment and the other using a SMART; and discuss funding strategies and potential future applications in studying the care of individuals with acute illness, injury, or behavioral disorders.