Baseline Features and Reasons for Nonparticipation in the Colonoscopy Versus Fecal Immunochemical Test in Reducing Mortality From Colorectal Cancer (CONFIRM) Study, a Colorectal Cancer Screening Trial.

Importance: The Colonoscopy Versus Fecal Immunochemical Test in Reducing Mortality From Colorectal Cancer (CONFIRM) randomized clinical trial sought to recruit 50 000 adults into a study comparing colorectal cancer (CRC) mortality outcomes after randomization to either an annual fecal immunochemical test (FIT) or colonoscopy. Objective: To (1) describe study participant characteristics and (2) examine who declined participation because of a preference for colonoscopy or stool testing (ie, fecal occult blood test [FOBT]/FIT) and assess that preference's association with geographic and temporal factors. Design, Setting, and Participants: This cross-sectional study within CONFIRM, which completed enrollment through 46 Department of Veterans Affairs medical centers between May 22, 2012, and December 1, 2017, with follow-up planned through 2028, comprised veterans aged 50 to 75 years with an average CRC risk and due for screening. Data were analyzed between March 7 and December 5, 2022. Exposure: Case report forms were used to capture enrolled participant data and reasons for declining participation among otherwise eligible individuals. Main Outcomes and Measures: Descriptive statistics were used to characterize the cohort overall and by intervention. Among individuals declining participation, logistic regression was used to compare preference for FOBT/FIT or colonoscopy by recruitment region and year. Results: A total of 50 126 participants were recruited (mean [SD] age, 59.1 [6.9] years; 46 618 [93.0%] male and 3508 [7.0%] female). The cohort was racially and ethnically diverse, with 748 (1.5%) identifying as Asian, 12 021 (24.0%) as Black, 415 (0.8%) as Native American or Alaska Native, 34 629 (69.1%) as White, and 1877 (3.7%) as other race, including multiracial; and 5734 (11.4%) as having Hispanic ethnicity. Of the 11 109 eligible individuals who declined participation (18.0%), 4824 (43.4%) declined due to a stated preference for a specific screening test, with FOBT/FIT being the most preferred method (2820 [58.5%]) vs colonoscopy (1958 [40.6%]; P < .001) or other screening tests (46 [1.0%] P < .001). Preference for FOBT/FIT was strongest in the West (963 of 1472 [65.4%]) and modest elsewhere, ranging from 199 of 371 (53.6%) in the Northeast to 884 of 1543 (57.3%) in the Midwest (P = .001). Adjusting for region, the preference for FOBT/FIT increased by 19% per recruitment year (odds ratio, 1.19; 95% CI, 1.14-1.25). Conclusions and Relevance: In this cross-sectional analysis of veterans choosing nonenrollment in the CONFIRM study, those who declined participation more often preferred FOBT or FIT over colonoscopy. This preference increased over time and was strongest in the western US and may provide insight into trends in CRC screening preferences.

Do financial incentives increase mental health treatment engagement? A meta-analysis.

OBJECTIVE: Engagement in mental health treatment is low, which can lead to poor outcomes. We evaluated the efficacy of offering patients financial incentives to increase their mental health treatment engagement, also referred to as contingency management. METHOD: We meta-analyzed studies offering financial incentives for mental health treatment engagement, including increasing treatment attendance, medication adherence, and treatment goal completion. Analyses were run within a multilevel framework. All study designs were included, and sensitivity analyses were run including only randomized and high-quality studies. RESULTS: About 80% of interventions incentivized treatment for substance use disorders. Financial incentives significantly increased treatment attendance (Hedges' g = 0.49, [0.33, 0.64], k = 30, I2 = 83.14), medication adherence (Hedges' g = 0.95, [0.47, 1.44], k = 6, I2 = 87.73), and treatment goal completion (Hedges' g = 0.61, [0.22, 0.99], k = 5, I2 = 60.55), including completing homework, signing treatment plans, and reducing problematic behavior. CONCLUSIONS: Financial incentives increase treatment engagement with medium to large effect sizes. We provide strong evidence for their effectiveness in increasing substance use treatment engagement and preliminary evidence for their effectiveness in increasing treatment engagement for other mental health disorders. Future research should prioritize testing the efficacy of incentivizing treatment engagement for mental health disorders aside from substance use. Research must also identify ways to incentivize treatment engagement that improve functioning and long-term outcomes and address ethical and systemic barriers to implementing these interventions. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Clustering of Directions Improves Goodness of Fit in Kinematic Data Collected in the Transverse Plane During Robot-Assisted Rehabilitation of Stroke Patients.

The kinematic character of hand trajectory in reaching tasks varies by movement direction. Often, direction is not included as a factor in the analysis of data collected during multi-directional reach tasks; consequently, this directionally insensitive model (DI) may be prone to type-II error due to unexplained variance. On the other hand, directionally specific models (DS) that account separately for each movement direction, may reduce statistical power by increasing the amount of data groupings. We propose a clustered-by-similarity (CS) in which movement directions with similar kinematic features are grouped together, maximizing model fit by decreasing unexplained variance while also decreasing uninformative sub-groupings. We tested model quality in measuring change over time in 10 kinematic features extracted from 72 chronic stroke patients participating in the VA-ROBOTICS trial, performing a targeted reaching task over 16 movement directions (8 targets, back- and forth from center) in the horizontal plane. Across 49 participants surviving a quality control sieve, 4.3 ± 1.1 (min: 3; max: 7) clusters were found among the 16 movement directions; clusters varied between participants. Among 49 participants, and averaged across 10 features, the better-fitting model for predicting change in features was found to be CS assessed by the Akaike Information criterion (61.6 ± 7.3%), versus DS (31.0 ± 7.8%) and DI (7.1 ± 7.1%). Confirmatory analysis via Extra Sum of Squares F-test showed the DS and CS models out-performed the DI model in head-to-head (pairwise) comparison in >85% of all specimens. Thus, we find overwhelming evidence that it is necessary to adjust for direction in the models of multi-directional movements, and that clustering kinematic data by feature similarly may yield the optimal configuration for this co-variate.