Predicting Kidney Transplant Evaluation Non-attendance.

Non-attendance to kidney transplant evaluation (KTE) appointments is a barrier to optimal care for those with kidney failure. We examined the medical and socio-cultural factors that predict KTE non-attendance to identify opportunities for integrated medical teams to intervene. Patients scheduled for KTE between May, 2015 and June, 2018 completed an interview before their initial KTE appointment. The interview assessed various social determinants of health, including demographic (e.g., income), medical (e.g. co-morbidities), transplant knowledge, cultural (e.g., medical mistrust), and psychosocial (e.g., social support) factors. We used multiple logistic regression analysis to determine the strongest predictor of KTE non-attendance. Our sample (N = 1119) was 37% female, 76% non-Hispanic White, median age 59.4 years (IQR 49.2-67.5). Of note, 142 (13%) never attended an initial KTE clinic appointment. Being on dialysis predicted higher odds of KTE non-attendance (OR 1.76; p = .02; 64% of KTE attendees on dialysis vs. 77% of non-attendees on dialysis). Transplant and nephrology teams should consider working collaboratively with dialysis units to better coordinate care, (e.g., resources to attend appointment or outreach to emphasize the importance of transplant) adjusting the KTE referral and evaluation process to address access issues (e.g., using tele-health) and encouraging partnership with clinical psychologists to promote quality of life for those on dialysis.

The Pain Anxiety Symptom Scale: Initial Development and Evaluation of 4 and 8 Item Short Forms.

Elevated levels of anxiety in relation to chronic pain have been consistently associated with greater distress and disability. Thus, accurate measurement of pain-related anxiety is an important requirement in modern pain services. The Pain Anxiety Symptom Scale (PASS) was introduced over 30 years ago, with a shortened 20-item version introduced 10 years later. Both versions of the PASS were derived using Principal Components Analysis, an established method of measure development with roots in classical test theory. Item Response Theory (IRT) is a complementary approach to measure development that can reduce the number of items needed and maximize item utility with minimal loss of statistical and clinical information. The present study used IRT to shorten the 20-item PASS (PASS-20) in a large sample of people with chronic pain (N = 2,669). Two shortened versions were evaluated, 1 composed of the single best-performing item from each of its 4 subscales (PASS-4) and the other with the 2 best-performing items from each subscale (PASS-8). Several supplementary analyses were performed, including comparative item convergence evaluations based on sample characteristics (ie, female or male sex; clinical or online sample), factor invariance testing, and criterion validity evaluation of the 4, 8, and 20-item versions of the PASS in hierarchical regression models predicting pain-related distress and interference. Overall, both shortened PASS versions performed adequately across these supplemental tests, although the PASS-4 had more consistent item convergence between samples, stronger evidence for factor invariance, and accounted for 83% of the variance accounted for by the PASS-20% and 92% of the variance accounted for by the PASS-8 in criterion variables. Consequently, the PASS-4 is recommended for use in situations where a briefer evaluation of pain-related anxiety is appropriate. PERSPECTIVE: The Pain Anxiety Symptom Scale (PASS) is an established measure of pain-related fear. This study derived 4 and 8-item versions of the PASS using IRT. Both versions showed strong psychometric properties, stability of factor structure, and relation to important aspects of pain-related functioning.

Genotypic variation rather than ploidy level determines functional trait expression in a foundation tree species in the presence and absence of environmental stress.

BACKGROUND AND AIMS: At the population level, genetic diversity is a key determinant of a tree species' capacity to cope with stress. However, little is known about the relative importance of the different components of genetic diversity for tree stress responses. We compared how two sources of genetic diversity, genotype and cytotype (i.e. differences in ploidy levels), influence growth, phytochemical and physiological traits of Populus tremuloides in the presence and absence of environmental stress. METHODS: In a series of field studies, we first assessed variation in traits across diploid and triploid aspen genotypes from Utah and Wisconsin under non-stressed conditions. In two follow-up experiments, we exposed diploid and triploid aspen genotypes from Wisconsin to individual and interactive drought stress and defoliation treatments and quantified trait variations under stress. KEY RESULTS: We found that (1) tree growth and associated traits did not differ significantly between ploidy levels under non-stressed conditions. Instead, variation in tree growth and most other traits was driven by genotypic and population differences. (2) Genotypic differences were critical for explaining variation of most functional traits and their responses to stress. (3) Ploidy level played a subtle role in shaping traits and trait stress responses, as its influence was typically obscured by genotypic differences. (4) As an exception to the third conclusion, we showed that triploid trees expressed 17 % higher foliar defence (tremulacin) levels, 11 % higher photosynthesis levels and 23 % higher rubisco activity under well-watered conditions. Moreover, triploid trees displayed greater drought resilience than diploids as they produced 35 % more new tissue than diploids when recovering from drought stress. CONCLUSION: Although ploidy level can strongly influence the ecology of tree species, those effects may be relatively small in contrast to the effects of genotypic variation in highly diverse species.

Motivational Interviewing Education and Utilization in US Physical Therapy.

INTRODUCTION: In physical rehabilitation, motivational interviewing (MI) can improve treatment adherence and therapeutic outcomes. The objective of this study was to investigate the relationship between MI education and use of MI skills in physical therapy practice in the United States. REVIEW OF LITERATURE: Motivational interviewing is an empirically supported technique for facilitating behavior change. Numerous studies have examined its use in physical rehabilitation settings. No research has examined education and utilization of MI in physical therapy in the United States. SUBJECTS: Physical therapists (PTs) in the United States (N = 785) responded to an electronic survey distributed through the special interest academies and state chapters of the American Physical Therapy Association. METHODS: Descriptive, correlational, and group comparisons were used to analyze the survey responses about MI utilization in clinical practice, characteristics of MI training, and self-reported use of MI communication skills. RESULTS: Two-thirds of the sample reported using MI and half of the sample received training in MI. Motivational interviewing training was heterogeneous, with interactive elements superior to lecture alone. Interestingly, training received in PT education programs correlated negatively with the use of the MI skills assessed in this study. Use of MI skills significantly correlated with increased perceived patient adherence and decreased struggle with patients. DISCUSSION AND CONCLUSION: Incorporation of MI into physical therapy practice has the potential to improve patient care through increased therapeutic rapport, improvement of health outcomes associated with behavior change, and improved job satisfaction. Although MI is becoming more prevalent in physical therapy practice in the United States, the results of this study suggest that MI education should include dynamic components to increase the effective use of MI skills in clinical practice.

Teacher's Corner: An R Shiny App for Sensitivity Analysis for Latent Growth Curve Mediation.

Mechanisms of behavior change are the processes through which interventions are hypothesized to cause changes in outcomes. Latent growth curve mediation models (LGCMM) are recommended for investigating the mechanisms of behavior change because LGCMM models establish temporal precedence of change from the mediator to the outcome variable. The Correlated Augmented Mediation Sensitivity Analyses (CAMSA) App implements sensitivity analysis for LGCMM models to evaluate if a mediating path (mechanism) is robust to potential confounding variables. The CAMSA approach is described and applied to simulated data, and data from a research study exploring a mechanism of change in the treatment of substance use disorder.

Profiles of Pain Acceptance and Values-Based Action in the Assessment and Treatment of Chronic Pain.

Pain acceptance and values-based action are relevant to treatment outcomes in those with chronic pain. It is unclear if patterns of responding in these 2 behavioral processes can be used to classify patients into distinct classes at treatment onset and used to predict treatment response. This observational cohort study had 2 distinct goals. First, it sought to classify patients at assessment based on pain acceptance and values-based action (N = 1746). Second, it sought to examine treatment outcomes based on class membership in a sub-set of patients completing an interdisciplinary pain rehabilitation program of Acceptance and Commitment Therapy for chronic pain (N = 343). Latent profile analysis was used in the larger sample to identify 3 distinct patient classes: low acceptance and values-based (AV) action (Low AV; n = 424), moderate acceptance and values-based action (Moderate AV; n = 983) and high acceptance and values-based action (High AV; n = 339). In the smaller treated sample, participants in the Low AV and Moderate AV class demonstrated improvements across all outcome variables, whereas those in the High AV class did not. These findings support the role of pain acceptance and values-based action in those with chronic pain. PERSPECTIVE: Individuals with chronic pain can be classified with respect to pain acceptance and values-based action and these groups may respond differently to treatment.

Leaf spectroscopy reveals divergent inter- and intra-species foliar trait covariation and trait-environment relationships across NEON domains.

Concurrent measurement of multiple foliar traits to assess the full range of trade-offs among and within taxa and across broad environmental gradients is limited. Leaf spectroscopy can quantify a wide range of foliar functional traits, enabling assessment of interrelationships among traits and with the environment. We analyzed leaf trait measurements from 32 sites along the wide eco-climatic gradient encompassed by the US National Ecological Observatory Network (NEON). We explored the relationships among 14 foliar traits of 1103 individuals across and within species, and with environmental factors. Across all species pooled, the relationships between leaf economic traits (leaf mass per area, nitrogen) and traits indicative of defense and stress tolerance (phenolics, nonstructural carbohydrates) were weak, but became strong within certain species. Elevation, mean annual temperature and precipitation weakly predicted trait variation across species, although some traits exhibited species-specific significant relationships with environmental factors. Foliar functional traits vary idiosyncratically and species express diverse combinations of leaf traits to achieve fitness. Leaf spectroscopy offers an effective approach to quantify intra-species trait variation and covariation, and potentially could be used to improve the characterization of vegetation in Earth system models.

Growth-defense trade-offs shape population genetic composition in an iconic forest tree species.

All organisms experience fundamental conflicts between divergent metabolic processes. In plants, a pivotal conflict occurs between allocation to growth, which accelerates resource acquisition, and to defense, which protects existing tissue against herbivory. Trade-offs between growth and defense traits are not universally observed, and a central prediction of plant evolutionary ecology is that context-dependence of these trade-offs contributes to the maintenance of intraspecific variation in defense [Züst and Agrawal, Annu. Rev. Plant Biol., 68, 513-534 (2017)]. This prediction has rarely been tested, however, and the evolutionary consequences of growth-defense trade-offs in different environments are poorly understood, especially in long-lived species [Cipollini et al., Annual Plant Reviews (Wiley, 2014), pp. 263-307]. Here we show that intraspecific trait trade-offs, even when fixed across divergent environments, interact with competition to drive natural selection of tree genotypes corresponding to their growth-defense phenotypes. Our results show that a functional trait trade-off, when coupled with environmental variation, causes real-time divergence in the genetic architecture of tree populations in an experimental setting. Specifically, competitive selection for faster growth resulted in dominance by fast-growing tree genotypes that were poorly defended against natural enemies. This outcome is a signature example of eco-evolutionary dynamics: Competitive interactions affected microevolutionary trajectories on a timescale relevant to subsequent ecological interactions [Brunner et al., Funct. Ecol. 33, 7-12 (2019)]. Eco-evolutionary drivers of tree growth and defense are thus critical to stand-level trait variation, which structures communities and ecosystems over expansive spatiotemporal scales.

Integrative data analysis of self-efficacy in 4 clinical trials for alcohol use disorder.

BACKGROUND: Self-efficacy has been proposed as a key predictor of alcohol treatment outcomes and a potential mechanism of success in achieving abstinence or drinking reductions following alcohol treatment. Integrative data analysis, where data from multiple studies are combined for analyses, can be used to synthesize analyses across multiple alcohol treatment trials by creating a commensurate measure and controlling for differential item functioning (DIF) to determine whether alcohol treatments improve self-efficacy. METHOD: The current study used moderated nonlinear factor analysis (MNLFA) to examine the effect of treatment on self-efficacy across four different treatment studies (N = 3720; 72.5% male, 68.4% non-Hispanic white). Self-efficacy was measured using the Alcohol Abstinence Self-Efficacy Scale (AASE) in the COMBINE Study (n = 1383) and Project MATCH (n = 1726), and the Drug Taking Confidence Questionnaire (DTCQ) in two studies of Telephone Continuing Care (TEL Study 1: n = 303; TEL Study 2: n = 212). DIF was examined across time, study, treatment condition, marital status, age, and sex. RESULTS: We identified 12 items from the AASE and DTCQ to create a commensurate measure of self-efficacy using MNLFA. All active treatments, including cognitive-behavioral treatment, a combined behavioral intervention, medication management, motivation enhancement treatment, telephone continuing care, twelve-step facilitation, and relapse prevention, were associated with significant increases in self-efficacy from baseline to posttreatment that were maintained for up to a year. Importantly, treatment as usual in community settings, which consisted of weekly group therapy that included addiction counseling and twelve-step recovery support, was not associated with significant increases in self-efficacy. CONCLUSIONS: Alcohol self-efficacy increases following treatment and numerous evidence-based treatments are associated with significant increases in self-efficacy, which are maintained over time. Community treatment that focuses solely on addiction counseling and twelve-step support may not promote increases in self-efficacy.

Physical therapists should play a greater role in managing patients with opioid use and opioid misuse.

The U.S. opioid crisis necessitates that health care providers of all types work collaboratively to manage patients taking prescription opioid medications and manage those who may be misusing prescription opioids. Musculoskeletal conditions are the most common diagnoses associated with an opioid prescription. Physical therapists commonly manage patients with musculoskeletal conditions and chronic pain. Some patients who attend physical therapy for pain management take prescription opioid medications for pain and some of these patients may be misusing prescription opioids. Physical therapists who manage patients with musculoskeletal conditions are well-positioned to help address the opioid crisis. Historically, physical therapists have not been adequately engaged in efforts to manage persons with co-occurring musculoskeletal pain and opioid misuse or OUD. The American Physical Therapy Association (APTA) has emphasized physical therapy over the use of prescription opioids for the management of painful conditions. The APTA, however, does not highlight the important role that physical therapists could play in monitoring opioid use among patients receiving treatment for pain, nor the role that physical therapists should play in screening for opioid misuse. Such screening could facilitate referral of patients suspected misuse to an appropriate provider for formal assessment and treatment. This commentary presents simulated musculoskeletal patient presentations depicting 2 common opioid use states; chronic opioid use and opioid misuse. The cases highlight and interactions that physical therapists could have with these patients and actions that the physical therapist could take when working inter-disciplinarily. Recommendations are provided that aim to increase physical therapists' knowledge and skills related to managing patients taking prescription opioid medications for pain.

Latent Class Mediation: A Comparison of Six Approaches.

Latent class mediation modeling is designed to estimate the mediation effect when both the mediator and the outcome are latent class variables. We suggest using an adjusted one-step approach in which the latent class models for the mediator and the outcome are estimated first to decide on the number of classes, then the latent class models and the mediation model are jointly estimated. We present both an empirical demonstration and a simulation study to compare the performance of this one-step approach to a standard three-step approach with modal assignment (modal) and four different modern three-step approaches. Results from the study indicate that unadjusted modal, which ignores the classification errors of the latent class models, produced biased mediation effects. On the other hand, the adjusted one-step approach and the modern three-step approaches performed well with respect to bias for estimating mediation effects, regardless of measurement quality (i.e., model entropy) and latent class size. Among the three-step approaches we investigated, the maximum likelihood method with modal assignment and the BCH correction with robust standard error estimators are good alternatives to the adjusted one-step approach, given their unbiased standard error estimations.

Trait plasticity and trade-offs shape intra-specific variation in competitive response in a foundation tree species.

The ability to tolerate neighboring plants (i.e. degree of competitive response) is a key determinant of plant success in high-competition environments. Plant genotypes adjust their functional trait expression under high levels of competition, which may help explain intra-specific variation in competitive response. However, the relationships between traits and competitive response are not well understood, especially in trees. In this study, we investigated among-genotype associations between tree trait plasticity and competitive response. We manipulated competition intensity in experimental stands of trembling aspen (Populus tremuloides) to address the covariance between competition-induced changes in functional trait expression and aspects of competitive ability at the genotype level. Genotypic variation in the direction and magnitude of functional trait responses, especially those of crown foliar mass, phytochemistry, and leaf physiology, was associated with genotypic variation in competitive response. Traits exhibited distinct plastic responses to competition, with varying degrees of genotypic variation and covariance with other trait responses. The combination of genotypic diversity and covariance among functional traits led to tree responses to competition that were coordinated among traits yet variable among genotypes. Such relationships between tree traits and competitive success have the potential to shape stand-level trait distributions over space and time.

Initial evaluation of the Chronic Pain Acceptance Questionnaire - 2.

Greater acceptance of chronic pain is associated with lesser levels of pain-related distress and disability and better overall functioning. Pain acceptance is most often assessed using the Chronic Pain Acceptance Questionnaire (CPAQ), which includes both an eight-item short form (CPAQ-8) and a twenty item parent measure (CPAQ-20). This study derived a two-item CPAQ for use in busy clinical settings and for repeated measurement during treatment, the CPAQ-2. An Item Response Theory (IRT) approach was used to identify the strongest items from the CPAQ-20, one from each of its two subscales. Next, regression analyses were conducted to evaluate the utility of the CPAQ-2 by examining variance accounted for in the CPAQ-8, CPAQ-20, and in measures of depression, pain-related fear, physical disability, and psychosocial disability. Four clinical databases were combined (N = 1,776) for the analyses. Items 9 and 14 were identified as the strongest CPAQ-20 items in the IRT analyses. The sum score of these two items accounted for over 60% of the variance in the CPAQ-8 and CPAQ-20. Furthermore, this score accounted for significant variance in measures of depression, pain-related fear, physical disability, and psychosocial disability after controlling for data collection method (i.e. in clinic or online), participant age, education, pain duration and usual pain. Finally, the amount of variance accounted for by the CPAQ-2 was comparable to that accounted for by both the CPAQ-8 and CPAQ-20. These results provide initial support for the CPAQ-2 and suggest that it is well-suited as a brief assessment of chronic pain acceptance. SIGNIFICANCE: The most frequently used measure of pain acceptance is the CPAQ, which includes both an eight-item short form, the CPAQ-8, and a longer twenty item parent measure, the CPAQ-20. The present study sought to derive a two-item measure of the CPAQ for use in busy clinical settings and for repeated measurement during treatment, the CPAQ-2. An IRT approach was used to identify the strongest items from the CPAQ-20, one from each of its two subscales in a large sample of 1,776 individuals with chronic pain. The two item measure accounted for significant variance in measures of depression, pain-related fear, physical disability, and psychosocial disability. The brief measure will be useful in assessing pain acceptance in busy clinical setting and longitudinal designs.

Foliar functional traits from imaging spectroscopy across biomes in eastern North America.

Foliar functional traits are widely used to characterize leaf and canopy properties that drive ecosystem processes and to infer physiological processes in Earth system models. Imaging spectroscopy provides great potential to map foliar traits to characterize continuous functional variation and diversity, but few studies have demonstrated consistent methods for mapping multiple traits across biomes. With airborne imaging spectroscopy data and field data from 19 sites, we developed trait models using partial least squares regression, and mapped 26 foliar traits in seven NEON (National Ecological Observatory Network) ecoregions (domains) including temperate and subtropical forests and grasslands of eastern North America. Model validation accuracy varied among traits (normalized root mean squared error, 9.1-19.4%; coefficient of determination, 0.28-0.82), with phenolic concentration, leaf mass per area and equivalent water thickness performing best across domains. Across all trait maps, 90% of vegetated pixels had reasonable values for one trait, and 28-81% provided high confidence for multiple traits concurrently. Maps of 26 traits and their uncertainties for eastern US NEON sites are available for download, and are being expanded to the western United States and tundra/boreal zone. These data enable better understanding of trait variations and relationships over large areas, calibration of ecosystem models, and assessment of continental-scale functional diversity.

To compete or defend: linking functional trait variation with life-history tradeoffs in a foundation tree species.

Although chemical deterrents to herbivory often exact costs in terms of plant growth, the manner in which those costs arise, and their physiological relationship to other functional traits, remain unclear. In the absence of appreciable herbivory, we examined interrelationships among chemical defense levels and other foliar functional traits (e.g., light-saturated photosynthesis, specific leaf area, nitrogen concentration) as co-determinants of tree growth and, by extension, competitive ability in high-density populations comprising 16 genotypes of Populus tremuloides. Across genotypes, concentrations of chemical defenses were not significantly related to other leaf functional traits, but levels of the salicinoid phenolic glycosides (SPGs) salicin, salicortin and tremulacin were each negatively correlated with relative mass growth (RMG) of aboveground woody tissue (P ≤ 0.001). RMG, in turn, underpinned 77% of the genotypic variation in relative height growth (our index of competitive ability). RMG was also positively related to light-saturated photosynthesis (P ≤ 0.001), which, together with the three SPGs, explained 86% of genotypic RMG variation (P ≤ 0.001). Moreover, results of a carbon balance simulation indicated that costs of resource allocation to SPGs, reaching nearly a third of annual crown photosynthesis, were likely mediated by substantial metabolic turnover, particularly for salicin. The lack of discernible links between foliar defense allocation and other (measured) functional traits, and the illustrated potential of metabolic turnover to reconcile influences of SPG allocation on RMG, shed additional light on fundamental physiological mechanisms underlying evolutionary tradeoffs between chemical defense investment and competitive ability in a foundation tree species.

Receipt of multiple outpatient opioid prescriptions is associated with increased risk of adverse outcomes in youth: opioid prescribing trends, individual characteristics, and outcomes from 2005 to 2016.

Data on all outpatient opioid prescriptions (N = 71,647) to youth below age 21 (N = 42,020) from 2005 to 2016 were extracted from electronic medical records within a university hospital system in New Mexico (NM) as were demographic details and markers of morbidity/mortality. Relative risk was calculated for markers of morbidity/mortality based on sociodemographic characteristics. The sample was primarily male (55.0%), Hispanic/Latinx (50.1%), English-speaking (88.9%), and publicly insured (50.1%). Mean age was 13.54 (SD = 6.50). From 2005 to 2016, overall frequency of opioid prescriptions increased by 86.6% (from 2470 to 4610) with the largest increase (206.2%) observed from 2005 to 2008 (2470-7562). Patients who were older, white, and non-Hispanic were more likely to receive multiple opioid prescriptions. Large relative increases in morbidity and mortality were documented, although base rates remained low. The percentage of individuals within the sample who experienced an overdose increased steadily from 0 in 2005 to 1.09% in 2016. Incidence of mortality increased from 0.12% of the sample to 1.39% in 2016. The proportion of individuals who received a medication for the treatment of opioid dependence increased from 0.06% in 2005 to 0.44% in 2016. Significantly increased risk of adverse outcomes was observed in patients receiving multiple opioid prescriptions, and in patients who were older, of minority race, received their first prescription in an outpatient clinic, and publicly insured or uninsured. Results add to the growing literature concerning opioid prescription rates over time. They also provide important information on potential additive risks of adverse outcomes when pediatric patients receive multiple opioid prescriptions.

From the Arctic to the tropics: multibiome prediction of leaf mass per area using leaf reflectance.

Leaf mass per area (LMA) is a key plant trait, reflecting tradeoffs between leaf photosynthetic function, longevity, and structural investment. Capturing spatial and temporal variability in LMA has been a long-standing goal of ecological research and is an essential component for advancing Earth system models. Despite the substantial variation in LMA within and across Earth's biomes, an efficient, globally generalizable approach to predict LMA is still lacking. We explored the capacity to predict LMA from leaf spectra across much of the global LMA trait space, with values ranging from 17 to 393 g m-2 . Our dataset contained leaves from a wide range of biomes from the high Arctic to the tropics, included broad- and needleleaf species, and upper- and lower-canopy (i.e. sun and shade) growth environments. Here we demonstrate the capacity to rapidly estimate LMA using only spectral measurements across a wide range of species, leaf age and canopy position from diverse biomes. Our model captures LMA variability with high accuracy and low error (R2  = 0.89; root mean square error (RMSE) = 15.45 g m-2 ). Our finding highlights the fact that the leaf economics spectrum is mirrored by the leaf optical spectrum, paving the way for this technology to predict the diversity of LMA in ecosystems across global biomes.

Sensitivity Analysis of the No-Omitted Confounder Assumption in Latent Growth Curve Mediation Models.

Latent growth curve mediation models are increasingly used to assess mechanisms of behavior change. For latent growth mediation model, like any another mediation model, even with random treatment assignment, a critical but untestable assumption for valid and unbiased estimates of the indirect effects is that there should be no omitted variable that confounds indirect effects. One way to address this untestable assumption is to conduct sensitivity analysis to assess whether the inference about an indirect effect would change under varying degrees of confounding bias. We developed a sensitivity analysis technique for a latent growth curve mediation model. We compute the biasing effect of confounding on point and confidence interval estimates of the indirect effects in a structural equation modeling framework. We illustrate sensitivity plots to visualize the effects of confounding on each indirect effect and present an empirical example to illustrate the application of the sensitivity analysis.

The (Lack of) Replication of Self-Reported Mindfulness as a Mechanism of Change in Mindfulness-Based Relapse Prevention for Substance Use Disorders.

The development and evaluation of mindfulness-based interventions for a variety of psychological and medical disorders has grown exponentially over the past 20 years. Yet, calls for increasing the rigor of mindfulness research and recognition of the difficulties of conducting research on the topic of mindfulness have also increased. One of the major difficulties is the measurement of mindfulness, with varying definitions across studies and ambiguity with respect to the meaning of mindfulness. There is also concern about the reproducibility of findings given few attempts at replication. The current secondary analysis addressed the issue of reproducibility and robustness of the construct of self-reported mindfulness across two separate randomized clinical trials of mindfulness-based relapse prevention (MBRP), as an aftercare treatment for substance use disorder. Specifically, we tested the robustness of our previously published findings, which identified a latent construct of mindfulness as a significant mediator of the effect of MBRP on reducing craving following treatment. First, we attempted to replicate the findings in a separate randomized clinical trial of MBRP. Second, we conducted sensitivity analyses to test the assumption of the no-omitted confounder bias in a mediation model. The effect of MBRP on self-reported mindfulness and overall mediation effect failed to replicate in a new sample. The effect of self-reported mindfulness in predicting craving following treatment did replicate and was robust to the no-omitted confounder bias. The results of this work shine a light on the difficulties in the measurement of mindfulness and the importance of examining the robustness of findings.

Consumption outcomes in clinical trials of alcohol use disorder treatment: Consideration of standard drink misestimation.

Background. The Food and Drug Administration recently added a new clinical endpoint for evaluating the efficacy of alcohol use disorder (AUD) treatment that is more inclusive of treatment goals besides abstinence: no heavy drinking days (NHDD). However, numerous critiques have been noted for such binary models of treatment outcome. Further, there is mounting evidence that participants inaccurately estimate the quantities of alcohol they consume during drinking episodes (i.e., drink size misestimation), which may be particularly problematic when using a binary criterion (NHDD) compared to a similar, continuous alternative outcome variable: percent heavy drinking days (PHDD). Yet, the impact of drinking misestimation on binary (e.g., NHDD) versus continuous outcome variables (e.g., PHDD) has not been studied. Objectives. Using simulation methods, the present study examined the potential impact of drink size misestimation on NHDD and PHDD. Methods. Data simulations were based on previously published findings of the amount of error in how much alcohol is actually poured when estimating standard drinks. We started with self-reported daily drinking data from COMBINE study participants with complete data (N = 888; 68.1% male), then simulated inaccuracy in those estimations based on literature on standard drink size misestimation. Results. Clinical trial effect sizes were consistently lower for NHDD than for PHDD. Drink size misestimation further lowered effect sizes for NHDD and PHDD. Conclusions. Drink size misestimation may lead to inaccurate conclusions about drinking outcomes and the comparative effectiveness of AUD treatments, including inflated type-II error rates, particularly when treatment "success" is defined by binary outcomes such as NHDD.