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.

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.

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.

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.

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.

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.

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.

Error compensation during finger force production after one- and four-finger voluntarily fatiguing exercise.

The effect of muscle fatigue on error compensation strategies during multi-finger ramp force production tasks was investigated. Thirteen young, healthy subjects were instructed to produce a total force with four fingers of the right hand to accurately match a visually displayed template. The template consisted of a 3-s waiting period, a 3-s ramp force production [from 0 to 30% maximal voluntary contraction (MVC)], and a 3-s constant force production. A series of 12 ramp trials was performed before and after fatigue. Fatigue was induced by a 60-s maximal isometric force production with either the index-finger only or with all four fingers during two separate testing sessions. The average percent of drop was 38.2% in the MVC of the index finger after index-finger fatiguing exercise and 38.3% in the MVC of all fingers after four-finger fatiguing exercise. The ability of individual fingers to compensate for each other's errors in order for the total force to match the preset template was quantified as the error compensation index (ECI), i.e., the ratio of the sum of variances of individual finger forces and the variance of the total force. By comparing pre- and post-fatigue performance during four-finger ramp force production, we observed that the variance of the total force was not significantly changed after one- or four-finger fatiguing exercise. The ECI significantly decreased after four-finger fatiguing exercise, especially during the last second of the ramp; while the ECI remained unchanged after index finger single-finger fatiguing exercise. These results suggest that the central nervous system is able to utilize the abundant degrees of freedom to compensate for partial impairment of the motor apparatus induced by muscle fatigue to maintain the desired performance. However, this ability is significantly decreased when all elements of the motor apparatus are impaired.