The consequence of ignoring a nested factor on measures of effect size in analysis of variance

Developmental psychopathology as a meta-paradigm: From zero-sum science to epistemological pluralism in theory and research

In a thoughtful commentary in this journal a decade ago, Michael Rutter reviewed 25 years of progress in the field before concluding that developmental psychopathology (DP) initiated a paradigm shift in clinical science. This deduction requires that DP itself be a paradigm. According to Thomas Kuhn, canonical paradigms in the physical sciences serve unifying functions by consolidating scientists' thinking and scholarship around single, closed sets of discipline-defining epistemological assumptions and methods. Paradigm shifts replace these assumptions and methods with a new field-defining framework. In contrast, the social sciences are multiparadigmatic, with thinking and scholarship unified locally around open sets of epistemological assumptions and methods with varying degrees of inter-, intra-, and subdisciplinary reach. DP challenges few if any of these local paradigms. Instead, DP serves an essential pluralizing function, and is therefore better construed as a metaparadigm. Seen in this way, DP holds tremendous untapped potential to move the field from zero-sum thinking and scholarship to positive-sum science and epistemological pluralism. This integrative vision, which furthers Dante Cicchetti's legacy of interdisciplinarity, requires broad commitment among scientists to reject zero-sum scholarship in which portending theories, useful principles, and effective interventions are jettisoned based on confirmation bias, errors in logic, and ideology.

Serum anti-Müllerian hormone concentrations are related to embryo development: lessons from time-lapse imaging

Our objective was to study whether serum anti-Müllerian hormone (AMH) concentrations were associated with embryo morphokinetic events. This retrospective cohort study was performed in a private university-affiliated in vitro fertilization centre between March 2019 and December 2020 and included 902 oocytes cultured in a time-lapse imaging incubator, obtained from 114 intracytoplasmic sperm injection cycles performed. The relationship between AMH concentrations and morphokinetic events was investigated by considering the clustering of data (multiple embryos/patient). Evaluated kinetic markers were time to pronuclei appearance (tPNa) and fading (tPNf), time to two (t2), three (t3), four (t4), five (t5), six (t6), seven (t7), and eight cells (t8), (tSB) and time to the start of blastulation (tSB) and to blastulation (tB). Significant inverse relationships were observed between serum AMH concentrations and tPNf, t3, t4, t5, t6, t7, t8, and tB. The AMH was positively correlated with the KIDScore and implantation rate. Increased serum AMH concentrations correlated with faster embryo development. The clinical implications of this effect on embryo development warrant further investigation.

Meta-Analysis of Single-Case Experimental Design using Multilevel Modeling

Multilevel modeling (MLM) is an approach for meta-analyzing single-case experimental designs (SCED). In this paper, we provide a step-by-step guideline for using the MLM to meta-analyze SCED time-series data. The MLM approach is first presented using a basic three-level model, then gradually extended to represent more realistic situations of SCED data, such as modeling a time variable, moderators representing different design types and multiple outcomes, and heterogeneous within-case variance. The presented approach is then illustrated using real SCED data. Practical recommendations using the MLM approach are also provided for applied researchers based on the current methodological literature. Available free and commercial software programs to meta-analyze SCED data are also introduced, along with several hands-on software codes for applied researchers to implement their own studies. Potential advantages and limitations of using the MLM approach to meta-analyzing SCED are discussed.

Modeling multiple dependent variables in meta-analysis of single-case experimental design using multilevel modeling

Although meta-analyses of single-case experimental design (SCED) often include multiple types of dependent variables (DVs), multiple DVs are rarely considered within models in the analysis. Baek et al. (Journal of Experimental Education, 90(4), 934-961, 2022) identified several statistical issues that arise when researchers fail to model multiple DVs in meta-analyses of SCED data. However, the degree to which non-modeling of multiple DVs impacts the results of the meta-analysis of SCED has not been fully examined. In this simulation study, we have systematically investigated the impact of non-modeling of multiple DVs when analyzing meta SCED data using multilevel modeling. The result demonstrates that modeling multiple DVs has advantages over the non-modeling option for meta-analysis of SCED. Modeling multiple DVs enables the determination of precise effects from different DVs in addition to the unbiased and accurate average effect and accurate estimates and inferences for the error variances at the study level as well as the observation level. The current study also reveals potential factors (i.e., the number of DVs, degree of heterogeneity in the level-1 error variances and autocorrelation, and presence of the moderator effect) that impact the precision and accuracy of the variance parameters.

Association Between Initial Opioid Prescription Duration and 30-Day Risk of Receiving Repeat Opioid Among Children

OBJECTIVE

Our study evaluated the association between initial opioid prescription duration and receipt of a repeat opioid prescription in children.

METHODS

Eligible individuals were children between 1 and 17 years of age who enrolled in a Medicaid Managed Care plan and filled an incident opioid prescription during 2013 to 2018. An incident prescription was defined as receipt of an opioid analgesic without a prior use for 12 months. A repeat opioid prescription was defined as receipt of a subsequent opioid prescription within 30 days since the end of incident opioid prescription. A hierarchical multivariable logistic regression model was fitted to test the association between incident opioid prescription duration and the likelihood of receiving a repeat prescription.

RESULTS

The cohort consisted of 17,086 children receiving an incident opioid prescription in which 6272 (36.7%) received 1 to 3 days' supply, 8442 (49.4%) received 4 to 7 days' supply, 1434 (8.4%) received 8 to 10 days' supply, and 938 (5.5%) received >10 days' supply. Of these incident opioid recipients, 1780 (10.4%) filled a repeat opioid prescription. The multilevel model results indicated that, children receiving 4 to 7 days' supply (adjusted odds ratio [aOR]: 0.98 {0.9-1.1}), 8 to 10 days' supply (aOR: 1.03 [0.8-1.3]), and >10 days' supply (aOR: 0.85 [0.7-1.1]) had comparable likelihoods of receiving a repeat prescription as those receiving 1 to 3 days' supply.

DISCUSSION

Nearly 10% of children who filled an opioid prescription for acute pain received a repeat prescription. Initial prescription duration was not associated with the risk of receiving a repeat prescription.

Therapist Self-Report of Fidelity to Core Elements of Family Therapy for Adolescent Behavior Problems: Psychometrics of a Pragmatic Quality Indicator Tool

Therapist-report measures of evidence-based interventions have enormous potential utility as quality indicators in routine care; yet, few such tools have shown strong psychometric properties. This study describes reliability and validity characteristics of a therapist-report measure of family therapy techniques for treating adolescent conduct and substance use problems: Inventory of Therapy Techniques for Core Elements of Family Therapy (ITT-CEFT). Study participants included 31 staff therapists treating 68 adolescent clients in eight community-based mental health and substance use clinics. Therapists submitted ITT-CEFT checklists and companion audio recordings for 189 sessions. The ITT-CEFT contains 13 techniques identified as core elements of three manualized family therapy models that are empirically supported for the target group. Therapists also reported on their use of three motivational interventions, and independent observers coded the submitted recordings. ITT-CEFT factor validity was shown via confirmatory factor analyses of the tool's theoretical structure. Derived modules were: Family Engagement (four items; Cronbach's α = .72); Relational Orientation (five items; α = .74); and Interactional Change (four items; α = .66). Concurrent validity analyses showed fair-to-excellent therapist reliability compared to observer ratings (ICCs range .64-.75); they showed moderate therapist accuracy compared to observer mean scores, reflecting a tendency to overestimate delivery of the techniques. Discriminant validity analyses showed tool differentiation from motivational interventions. Results offer provisional evidence for the feasibility of using the therapist-report ITT-CEFT to anchor quality procedures for family therapy interventions in real-world settings.Trial Registration: The parent clinical trial is registered at www.ClinicalTrials.gov , ID: NCT03342872 (registration date: 11.10.17).

Characterizing Hypertensive Disorders of Pregnancy Among Medicaid Recipients in a Nonexpansion State

Background: The incidence of hypertensive disorders of pregnancy (HDP) are on the rise in the United States, especially in the South, which has a heavy chronic disease burden and large number of Medicaid nonexpansion states. Sizeable disparities in HDP outcomes exist by race/ethnicity, geography, and health insurance coverage. Our objective is to explore HDP in the Alabama Medicaid maternity population, and the association of maternal sociodemographic, clinical, and care utilization characteristics with HDP diagnosis. Materials and Methods: Data were from Alabama Medicaid delivery claims in 2017. Bivariate analyses were used to examine maternal characteristics by HDP diagnosis. Hierarchical generalized linear models, with observations nested at the county level, were used to assess multivariable relationships between maternal characteristics and HDP diagnosis. Results: Among women with HDP diagnosis, a higher proportion were older, Black, had other comorbidities, and had more perinatal hospitalizations or emergency visits compared with those without HDP diagnosis. There were increased odds of an HDP diagnosis for older women and those with comorbidities. Black women (adjusted odds ratio [aOR] = 1.24, 95% confidence interval [CI]: 1.16-1.33), women insured only during pregnancy by Sixth Omnibus Reconciliation Act Medicaid (aOR = 1.08, 95% CI: 1.02-1.15), and women entering prenatal care (PNC) in the second trimester (aOR = 1.10, 95% CI: 1.03-1.18) had elevated odds of HDP diagnosis compared with their counterparts. Conclusions: Beyond traditional demographic and clinical risk factors, not having preconception insurance coverage or first trimester PNC entry were associated with higher odds of HDP diagnosis. Improving the provision and timing of maternity coverage among Medicaid recipients, particularly in nonexpansion states, may help identify and treat women at risk of HDP and associated adverse perinatal outcomes.

Male age interferes with embryo growth in IVF treatment

STUDY QUESTION

Does male age affect embryo growth or quality in couples undergoing IVF treatment?

SUMMARY ANSWER

Advanced paternal age (APA) is negatively associated with the chance of an optimal eight-cell embryo on the third day of development.

WHAT IS KNOWN ALREADY

Literature shows that APA is associated with decreased sperm quality and fecundity. However, the effect of male age on embryo growth in an IVF setting remains inconclusive. Literature concerning male influences on IVF success is scarce and approaches used to analyse embryo outcomes differ by study.

STUDY DESIGN, SIZE, DURATION

This study was part of the longitudinal Epigenetic Legacy of Paternal Obesity (ELPO) study for which fathers and mothers were followed from pre-pregnancy until the birth of their child. Couples were recruited from April 2015 to September 2017. A total of 1057 embryos from 87 couples were studied.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Dutch-speaking couples planning to undergo an IVF treatment were recruited at the Leuven University Fertility Center in Flanders, Belgium. Anthropometrics were documented and compared to the general Flemish population. Semen characteristics, pregnancy rates and the following embryo characteristics were recorded: number of blastomeres, symmetry and percentage fragmentation. Statistical modelling was applied taking into account correlation of within-cycle outcomes and use of multiple cycles per couple.

MAIN RESULTS AND THE ROLE OF CHANCE

We observed a significant inverse association between APA and a key determinant for scoring of embryo quality: older men were less likely to produce an embryo of eight blastomeres at Day 3, compared to younger fathers; odds ratio for the effect of 1 year equals 0.960 (95% CI: 0.930-0.991; P = 0.011). Our finding remained significant after adjusting for female age and male and female BMI. Degree of fragmentation and symmetry were not significantly related to male age.

LIMITATIONS, REASONS FOR CAUTION

Because of the study's small sample size and its monocentric nature, a larger study is warranted to confirm our results. In addition, distribution of BMI and level of education were not representative of the general Flemish population. Although we corrected for BMI status, we do not exclude that obesity may be one of the determinants of infertility in our study population. Furthermore, it is known from other European countries that a higher education eases access to fertility treatment. Hence, caution should be taken when interpreting our findings from a fertility setting to the general population.

WIDER IMPLICATIONS OF THE FINDINGS

We suggest a heightened need for future research into male age and its potential effects on embryo growth, embryo quality and ART outcomes. Clinical decision-making and preventative public health programmes would benefit from a better understanding of the role of men, carried forward by the Paternal Origins of Health and Disease (POHaD) paradigm. We hope the current finding will encourage others to examine the role of the sperm epigenome in embryo development according to paternal age.

STUDY FUNDING/COMPETING INTEREST(S)

This work was supported by a research grant from KU Leuven University (OT/14/109). The authors declare no competing financial, professional or personal interests.

TRIAL REGISTRATION NUMBER

KU Leuven S57378 (ML11309), B322201523225.

Bayesian Analysis for Multiple-baseline Studies Where the Variance Differs across Cases in OpenBUGS

Objective: There is a growing interest in the potential benefits of applying Bayesian estimation for multilevel models of SCED data. Methodological studies have shown that Bayesian estimation resolves convergence issues, can be adequate for the small sample, and can improve the accuracy of the variance components. Despite the potential benefits, the lack of accessibility to software codes makes it difficult for applied researchers to implement Bayesian estimation in their studies. The purpose of this article is to illustrate a feasible way to implement Bayesian estimation using OpenBUGS software to analyze a complex SCED model where within-participants variability and autocorrelation may differ across cases. Method: By using extracted data from a published study, step-by-step guidance in analyzing the data using OpenBUGS software is provided, including (1) model specification, (2) prior distributions, (3) data entering, (4) model estimation, (5) convergence criteria, and (6) posterior inferences and interpretations. Result: Full codes for the analysis are provided.

Short-term psychodynamic infant-parent interventions at Child health centers: Outcomes on parental depression and infant social-emotional functioning

Randomized controlled trials (RCTs) demonstrate efficacy of parent-infant psychotherapy, but its applicability and effectiveness in public health care are less known. The method followed is Naturalistic study evaluating Short-term Psychodynamic Infant-Parent Interventions at Child Health Centers (SPIPIC) in Stockholm, Sweden. One hundred distressed mothers with infants were recruited by supervised nurses. Six therapists provided 4.3 therapy sessions on average (SD = 3.3). Sessions typically included the mothers, often with the baby present, while fathers rarely attended sessions. The Edinburgh Postnatal Depression Scale (EPDS) and the Ages and Stages Questionnaire: Social-Emotional (ASQ: SE) were distributed at baseline and at 3 and 9 months later. Data from a nonclinical group were collected simultaneously to provide norm data. Multilevel growth models on the mothers' questionnaire scores showed significant decreases over time on both measures. Nine months after baseline, 50% achieved a reliable change on the EPDS and 14% on the ASQ: SE. Prepost effect-sizes (d) were 0.70 and 0.40 for EPDS and ASQ: SE, figures that are comparable to results of other controlled studies. Psychotherapists integrated with public health care seem to achieve good results when supporting distressed mothers with brief interventions in the postnatal period. SPIPIC needs to be compared with other modalities and organizational frameworks.

A Primer for the Use of Multilevel Models in Couple and Family Therapy Research

This article serves as a primer for understanding how to use multilevel modeling (MLM) techniques in couple and family therapy outcome and process research. It outlines the use of HLM and Mplus-two of many software programs that can perform multilevel modeling-and provides an applied example of using MLM to investigate the use of postsession feedback on couple satisfaction and change, as well as the influence of trauma on the use of postsession feedback. Two graduate students in COAMFTE accredited PhD programs read the primer and provided questions to the first author that arose. Answers to these questions have been incorporated throughout the explanation of this methodological approach in hopes of addressing common stuck points for those using MLM.

Do therapist effects really impact estimates of within-patient mechanisms of change? A Monte Carlo simulation study

Objective: Existing evidence highlights the importance of modeling differential therapist effectiveness when studying psychotherapy outcome. However, no study to date examined whether this assertion applies to the study of within-patient effects in mechanisms of change. The study investigated whether therapist effects should be modeled when studying mechanisms of change on a within-patient level. Methods: We conducted a Monte Carlo simulation study, varying patient- and therapist level sample sizes, degree of therapist-level nesting (intra-class correlation), balanced vs. unbalanced assignment of patients to therapists, and fixed vs random within-patient coefficients. We estimated all models using longitudinal multilevel and structural equation models that ignored (2-level model) or modeled therapist effects (3-level model). Results: Across all conditions, 2-level models performed equally or were superior to 3-level models. Within-patient coefficients were unbiased in both 2- and 3-level models. In 3-level models, standard errors were biased when number of therapists was small, and this bias increased in unbalanced designs. Ignoring random slopes led to biased standard errors when slope variance was large; but 2-level models still outperformed 3-level models. Conclusions: In contrast to treatment outcome research, when studying mechanisms of change on a within-patient level, modeling therapist effects may even reduce model performance and increase bias.

Do We Overestimate the Within-Variability? The Impact of Measurement Error on Intraclass Coefficient Estimation

Many psychological phenomena have a multilevel structure (e.g., individuals within teams or events within individuals). In these cases, the proportion of between-variance to total-variance (i.e., the sum between-variance and within-variance) is of special importance and usually estimated by the intraclass coefficient (1) [ICC(1)]. Our contribution firstly shows via mathematical proof that measurement error increases the within-variance, which in turn decreases the ICC(1). Further, we provide a numerical example, and examine the RMSEs, alpha error rates and the inclusion of zero in the confidence intervals for ICC(1) estimation with and without measurement error. Secondly, we propose two corrections [i.e., the reliability-adjusted ICC(1) and the measurement model-based ICC(1)] that yield correct estimates for the ICC(1), and prove that they are unaffected by measurement error mathematically. Finally, we discuss our findings, point out examples of the underestimation of the ICC(1) in the literature, and reinterpret the results of these examples in the light of our new estimator. We also illustrate the potential application of our work to other ICCs. Finally, we conclude that measurement error distorts the ICC(1) to a non-negligible extent.

Effects of Therapist Feedback on the Therapeutic Alliance and Alcohol Use Outcomes in the Outpatient Treatment of Alcohol Use Disorder

BACKGROUND

It is widely accepted that the therapeutic alliance (TA) is a mediator of psychotherapy effects, but evidence is sparse that the TA is an actual mechanism of behavior change. The purpose of this study was to provide the first systematic evidence regarding the TA as a mechanism of change in the treatment of alcohol use disorder (AUD).

METHODS

Participants were 155 adult men and women presenting for individual outpatient treatment of AUD. Each was randomly assigned to 1 of 6 experienced therapists, who did or did not receive over 3 study phases postsession participant feedback on his/her ratings of the TA. All participants received a 12-session version of cognitive behavioral therapy for AUD. Participants rated the TA by use of the California Psychotherapy Alliance Scale (CALPAS) and reported their daily alcohol consumption between sessions and for 1 year posttreatment by use of the timeline followback interview. Multilevel statistical models that partitioned within- and between-participant effects and between-therapist effects were run to test the effects of feedback condition on the alliance and alcohol use, and the effects of the alliance on alcohol use.

RESULTS

The study's main hypotheses that feedback causes an enhanced therapeutic alliance and that the alliance is associated with better alcohol use outcomes were not supported.

CONCLUSIONS

Several methodological and substantive reasons for the pattern of findings are suggested, as well as directions for future research that would advance study of the TA as a mechanism of change in psychotherapy and in studying therapist effects on outcomes in general.

Effectiveness of Open-Ended Psychotherapy Under Clinically Representative Conditions

OBJECTIVE

This study investigates the effectiveness of open-ended psychotherapy in a large, naturalistic, and diverse patient cohort using rigorous and multifaceted assessments.

METHOD

Patients (N = 370) in open-ended psychotherapy completed an extensive set of self-report measures and diagnostic interviews, including long-term follow-up in order to assess stability of outcomes. About half of the patients qualified for a personality disorder at the onset of treatment. Treatments were open-ended, and on average therapists provided substantially larger treatment doses than common in the literature.

RESULTS

A substantial majority recovered from their respective Axis I (58%) and/or Axis II (55%) disorders during treatment. Patients also experienced large positive changes in self-report measures of overall psychiatric symptoms and moderate positive changes in self-reported interpersonal problems, while very few (< 3%) demonstrated negative development. The patients maintained their diagnostic and self-assessed changes at a two-and-a-half-year follow-up. In contrast, self-reported occupational functioning showed minimal improvement throughout the treatment and follow-up phase.

CONCLUSION

A naturalistic patient cohort undergoing open-ended psychotherapy demonstrates substantial and stable improvements.

Therapist effects in yearlong psychodynamic therapy: An exploratory study

A large body of research indicates that therapists can have a strong impact on treatment outcome, but little is known about the relationship between therapist effects and treatment phase. Our objective was to examine the interactive effect of therapist effectiveness and treatment phase on the outcome of 1 year of dynamic therapy. Therapists' effectiveness scores were defined as the extent of change for each therapist on the OQ-45 scores across their clients at five time points. The sample included 24 therapists who conducted psychodynamic therapy with 65 clients in a naturalistic setting. A three-level hierarchical linear model was applied. In accordance with the hypotheses, a significant main effect was found for effectiveness (estimate = 1.69, p < .05), for the two-way interactions between effectiveness and time (estimate = 1.36, p < .01), and for effectiveness and initial severity of symptoms (estimate = -0.02, p < .05). Simple slope analysis was conducted showing that among the less effective therapists, no significant change in outcome was found as time progressed; among the more effective therapists, outcome improved as time progressed. In addition, therapists were more influential in the treatments of clients with low initial severity. Our findings lend some support to the notion that therapist effects become increasingly influential as therapy progresses. The findings highlight the need for further research into changes in the magnitude of therapists' effect in various phases of therapy. Furthermore, the severity level of the initial symptoms of the client should be taken into account.

Service environment link and false discovery rate correction: Methodological considerations in population and health facility surveys

Background

Geospatial data are important in monitoring many aspects of healthcare development. Geographically linking health facility data with population data is an important area of public health research. Examining healthcare problems spatially and hierarchically assists with efficient resource allocation and the monitoring and evaluation of service efficacy at different levels. This paper explored methodological issues associated with geographic data linkage, and the spatial and multilevel analyses that could be considered in analysing maternal health service data.

Methods

The 2016 Ethiopia Demographic and Health Survey and the 2014 Ethiopia Service Provision Assessment data were used. Two geographic data linking methods were used to link these two datasets. Administrative boundary link was used to link a sample of health facilities data with population survey data for analysing three areas of maternal health service use. Euclidean buffer link was used for a census of hospitals to analyse caesarean delivery use in Ethiopia. The Global Moran’s I and the Getis-Ord Gi* statistics need to be carried out for identifying hot spots of maternal health service use in ArcGIS software. In addition to this, since the two datasets contain hierarchical data, a multilevel analysis was carried out to identify key determinants of maternal health service use in Ethiopia.

Results

Administrative boundary link gave more types of health facilities and more maternal health services as compared to the Euclidean buffer link. Administrative boundary link is the method of choice in case of sampled health facilities. However, for a census of health facilities, the Euclidean buffer link is the appropriate choice as this provides cluster level service environment estimates, which the administrative boundary link does not. Applying a False Discovery Rate correction enables the identification of true spatial clusters of maternal health service use.

Conclusions

A service environment link minimizes the methodological issues associated with geographic data linkage. A False Discovery Rate correction needs to be used to account for multiple and dependent testing while carrying out local spatial statistics. Examining maternal health service use both spatially and hierarchically has tremendous importance for identifying geographic areas that need special emphasis and for intervention purposes.

Multilevel Models to Estimate Carotid Intima-Media Thickness Curves for Individual Cardiovascular Risk Evaluation

Background and Purpose- The value of carotid intima-media thickness (cIMT)-a marker of subclinical atherosclerosis-in defining the cardiovascular risk is still debated. The aim of this study was to estimate standard cIMT progression, adjusting values over time for the main cardiovascular risk factors, in a sample of low-to-moderate cardiovascular risk subjects, to identify normative cIMT progression values. Methods- From the progression of lesions in the intima of the carotid cohort, we selected subjects who underwent 4 planned serial clinical evaluations and ultrasound cIMT determinations, on average every 4 years. Subject taking glucose-lowering therapies in secondary cardiovascular prevention or with cardiovascular risk score >5 were excluded from the analysis. The growth of cIMT across the study period (12 years) was assessed by use of individual growth curve modeling within multilevel models. Results- A total of 1175 (36% men; mean age, 53±11 years at baseline) participants at low/intermediate cardiovascular risk have been included in this analysis. A significant and marked slope of the mean and maximum cIMT growth curves (β=0.009 and β=0.012, respectively) was observed, confirming that it is a function of age. A stratified analysis by decades of age highlighted a nonlinear cIMT progression over time. In addition, different patterns of cIMT development between sex were observed. Finally, different slopes in mean and maximum cIMT curves, with a significant spread since the fifth decade, were observed in the cIMT growth curve models of subjects developing multifocal carotid atherosclerosis compared with the rest of the population. Conclusions- These findings proved that the rate of change in cIMT over time is a sign of the development of atherosclerosis, which cannot be a priori assumed linear. These data, therefore, support the clinical relevance of these growth curve models for cIMT progression to be considered as useful tool to identify subjects with faster atherosclerosis progression and thus at increased cardiovascular risk.

In pursuit of truth: A critical examination of meta-analyses of cognitive behavior therapy

OBJECTIVE

Three recent meta-analyses have made the claim, albeit with some caveats, that cognitive-behavioral treatments (CBT) are superior to other psychotherapies, in general or for specific disorders (e.g., social phobia).

METHOD

The purpose of the present article was to examine four issues in meta-analysis that mitigate claims of CBT superiority: (a) effect size, power, and statistical significance, (b) focusing on disorder-specific symptom measures and ignoring other important indicators of psychological functioning, (c) problems inherent in classifying treatments provided in primary studies into classes of treatments, and (d) the inclusion of problematic trials, which biases the results, and the exclusion of trials that fail to find differences among treatments.

RESULTS

When these issues are examined, the effects demonstrating the superiority of CBT are small, nonsignificant for the most part, limited to targeted symptoms, or are due to flawed primary studies.

CONCLUSION

Meta-analytic evidence for the superiority of CBT in the three meta-analysis are nonexistent or weak.

Benchmarking Family Therapy for Adolescent Behavior Problems in Usual Care: Fidelity, Outcomes, and Therapist Performance Differences

This study evaluated whether community therapists delivering family therapy for adolescent behavior problems in usual care achieved performance benchmarks established in controlled trials for treatment fidelity and outcomes, with particular focus on individual differences in therapist performance. The study contained N = 38 adolescents (50 % male; mean age 15 years) whose self-reported race/ethnicity was Hispanic (74 %), African American (11 %), multiracial (11 %), and other (4 %). Clients were treated by 13 therapists in one community mental health clinic that delivered family therapy as the routine standard of care. Therapists provided self-report data on adherence to core family therapy techniques; these scores were inflation-adjusted based on concordance with observer reports. Results showed that community therapists surpassed the fidelity benchmark for core family therapy techniques established by research therapists during a controlled trial. Regarding change in client functioning at 6-month follow-up, community therapists were equivalent to the benchmark for internalizing symptoms and superior for externalizing symptoms and delinquent acts. Community therapists also demonstrated a high degree of performance uniformity: Each one approximated the fidelity benchmark, and only two produced relatively weak outcomes on any of the client change indicators. Caveats for interpreting therapist performance data, given the small sample size, are described. Recommendations are made for developing therapist-report fidelity measures and utilizing statistical process control methods to diagnose therapist differences and enhance quality assurance procedures.

Changes in Problematic Anger, Shame, and Disgust in Anxious and Depressed Adults Undergoing Treatment for Emotion Dysregulation

Emotion dysregulation, the pervasive difficulty managing negative emotions, is a core problem across mood and anxiety disorders. Anger, shame, and disgust are particularly problematic emotions, impacting both disorder severity and treatment outcome. We previously found that a 16-week dialectical behavior therapy skills training group (DBT-ST) was superior to an activities-based support group (ASG) in decreasing emotion dysregulation in 44 adults with high emotion dysregulation who met diagnostic criteria for an anxiety or depressive disorder. We presently examine these participants' changes in anger, shame, disgust, and distress using self-reports collected over 6 months during and after treatment. Hierarchical linear modeling analyses show that DBT-ST was superior to ASG in decreasing anger suppression (d = 0.93) and distress (d = 1.04). Both conditions significantly reduced shame, disgust propensity, and disgust sensitivity, but neither was superior for these outcomes. The treatments did not significantly reduce anger expression. Mediation analyses suggest that condition indirectly influenced 4-month anger suppression, shame, and distress through its effect on 2-month emotion dysregulation. These findings suggest that DBT-ST is efficacious for certain problematic emotions and distress in depressed and anxious adults and that common factors may account for some, but not all, of its benefits.

Moderators in psychotherapy meta-analysis

Psychotherapy meta-analyses sometimes generate heterogeneous results, partially due to key methodological characteristics which vary between studies (e.g., psychotherapy conditions are contrasted with structurally different control conditions). Examining these potential moderator variables can help explain heterogeneous results within and between psychotherapy meta-analyses. The present manuscript provides an overview of moderators that are highly relevant to test the generalizability of effects across psychotherapy trials. These moderators mainly fall into one of the following groups: (a) structural equivalence of interventions, (b) preferences/allegiances, (c) therapist effects, and (d) sample representativeness. Individual moderators include: Bona fide psychotherapy, proximity to psychological interventions, psychotherapy orientation, pre-training of therapists, supervision, caseload of therapists, dosage, homework, patient preferences, researcher and therapist allegiance, therapist effects in nested designs, aspects of sample representativeness, multiple outcomes, and time of assessment. Our analysis of 15 psychotherapy meta-analyses published in 2016 suggests that the structural equivalence of psychotherapeutic conditions, patient and therapist preferences/allegiances, therapist effects and nested data structures as well as sample representativeness were often neglected and little-discussed as potential moderators. The manuscript describes further conceptual and methodological challenges when conducting moderator analyses such as the categorization of psychological treatments and the importance of interrater coding. We encourage meta-analysts to consider moderators which have previously shown utility in explaining heterogeneous results in the psychotherapy literature. Clinical or methodological significance of this article: Relevant moderator variables help explain heterogeneous results in psychotherapy meta-analyses. Though these variables are often overlooked, they should be regularly incorporated in meta-analyses.

Multilevel analysis of the role of human factors in regional disparities in crash outcomes

A growing body of research has examined the disparities in road traffic safety among population groups and geographic regions. These studies reveal disparities in crash outcomes between people and regions with different socioeconomic characteristics. A critical aspect of the road traffic crash epidemic that has received limited attention is the influence of local characteristics on human elements that increase the risk of getting into a crash. This paper applies multilevel logistic regression modeling techniques to investigate the influence of driver residential factors on driver behaviors in an attempt to explain the area-based differences in the severity of road crashes across the State of Alabama. Specifically, the paper reports the effects of characteristics attributable to drivers and the geographic regions they reside on the likelihood of a crash resulting in serious injuries. Model estimation revealed that driver residence (postal code or region) accounted for about 7.3% of the variability in the probability of a driver getting into a serious injury crash, regardless of driver characteristics. The results also reveal disparities in serious injury crash rate as well as significant proportions of serious injury crashes involving no seatbelt usage, driving under influence (DUI), unemployed drivers, young drivers, distracted driving, and African American drivers among some regions. The average credit scores, average commute times, and populations of driver postal codes are shown to be significant predictors for risk of severe injury crashes. This approach to traffic crash analysis presented can serve as the foundation for evidence-based policies and also guide the implementation of targeted countermeasures.

Psychological Treatments for Chronic Pain in East and Southeast Asia: A Systematic Review

BACKGROUND

Psychological treatments are recognised as generally effective for chronic pain. However, little is known about the evidence for psychological treatments for chronic pain in Asia.

PURPOSE

This study aimed (1) to identify all treatment outcome studies in the area of psychological approaches to chronic pain in adult populations of East Asia and Southeast Asia and (2) to evaluate the treatment types, the evidence for treatment outcomes and research design quality with regard to these studies.

METHODS

We identified all psychologically based treatment outcome studies for chronic pain in East and Southeast Asia by searching CENTRAL, EMBASE, PsycINFO, MEDLINE (via Ovid), Global Health and Web of Science from the beginning of each abstracting service until December 2014 (week 4).

RESULTS

Seventeen studies met inclusion criteria including a total of N = 1,890 participants. Four were randomised controlled trials (RCTs), five controlled clinical trials (CCTs) and eight cohort studies. Treatment outcomes included pain, disability, depression and anxiety. Overall, the studies included in this review showed small to medium within-group effect sizes for all four outcomes. A majority of the studies were rated as weak in design quality. Three RCTs were found to be of strong quality, one of moderate quality and only one CCT of moderate quality.

CONCLUSION

The current available literature on psychological treatments for chronic pain in East and Southeast Asia is generally small in scale, mostly preliminary and lags behind on some developments occurring in North America and Europe. Further development of treatment methods and research designs is warranted.

Adapting and validating a developmental assessment for chinese infants and toddlers: The ages & stages questionnaires: Inventory

The Chinese government has announced the 2013 Guidelines for developing a national system for early detection of disability among children under 6 years of age. However, given limited resources, challenges exist with developmental measures required in the 2013 Guidelines. In order to meet the needs for a more accurate and cost-efficient measure for developmental assessment, the Ages & Stages Questionnaires: Inventory (ASQ:I) was translated into Simplified Chinese, and validated on a regional sample of 812 Chinese children ages from 1 to 25 months. Results indicated that the Chinese ASQ:I domain scores increased across children's age. When dividing the sample into seven age intervals, Cronbach's alpha in each interval ranged from 0.59 to 0.96 across five domains. When using the whole sample for analyses, item expected a posteriori/plausible value (EAP/PV) reliability was above 0.99 in all domains, test-retest reliability using intra-class correlation analyses ranged from 0.95 to 0.99, and the agreement with the concurrent measure ranged from 0.29 to 0.89. Domain scores on the ASQ:I correctly predicted 92-99% of participating children's disability status. Findings suggested that the Chinese ASQ:I has adequate psychometric properties and thus provides a promising alternative measure for screening and progress monitoring in young children in China. Implications for future research and implementation are discussed.

Estimating Standardized Effect Sizes for Two- and Three-Level Partially Nested Data

Although previous research has discussed an effect size estimator for partially nested cluster randomized designs, the existing estimator (a) is not efficient when used with primary data, (b) can be biased when the homogeneity of variance assumption is violated, and (c) has not yet been empirically evaluated for its finite sample properties. The present paper addresses these limitations by proposing an alternative maximum likelihood estimator for obtaining standardized mean difference effect size and the corresponding sampling variance for partially nested data, as well as the variants that do not make an assumption of homogeneity of variance. The typical estimator, denoted as d (d_W with pooled SD and d_C with control arm SD), requires input of summary statistics such as observed means, variances, and the intraclass correlation, and is useful for meta-analyses and secondary data analyses; the newly proposed estimator [Formula: see text] ([Formula: see text] and [Formula: see text]) takes parameter estimates from a correctly specified multilevel model as input and is mainly of interest to researchers doing primary research. The simulation results showed that the two methods (d and [Formula: see text]) produced unbiased point and variance estimates for effect size. As expected, in general, [Formula: see text] was more efficient than d with unequal cluster sizes, especially with large average cluster size and large intraclass correlation. Furthermore, under heterogeneous variances, [Formula: see text] demonstrated a greater relative efficiency with small sample size for the unclustered control arm. Real data examples, one from a youth preventive program and one from an eating disorder intervention, were used to demonstrate the methods presented. In addition, we extend the discussion to a scenario with a three-level treatment arm and an unclustered control arm, and illustrate the procedures for effect size estimation using a hypothetical example of multiple therapy groups of clients clustered within therapists.

Acupuncture for the treatment of phantom limb syndrome in lower limb amputees: a randomised controlled feasibility study

Background

Post amputation, the complication of phantom limb pain (PLP) is prevalent and difficult to manage. This study aimed to determine whether it was feasible and acceptable to undertake a definitive multicentred randomised controlled trial assessing the effectiveness of acupuncture for treating lower limb amputees with PLP.

Methods

A mixed-methods embedded design, including a randomised controlled trial and semistructured interviews, was undertaken. A total of 15 participants with PLP were randomly assigned to receive either eight pragmatic Traditional Chinese Medicine acupuncture treatments and usual care or usual care alone over 4 weeks. Outcome measures were completed at baseline, weekly throughout the study and at 1 month post completion of the study and included: a numerical pain-rating scale, the Short-Form McGill Pain Questionnaire 2, the EQ-5D-5 L, the Hospital Anxiety and Depression Scale, the Perceived Stress Scale 10-item, the Insomnia Severity Index, and the Patient Global Impression of Change. Post completion of the trial, participants in the acupuncture group were interviewed about their experience. Feasibility-specific data were also collected.

Results

Of 24 amputees meeting the study inclusion criteria, 15 agreed to participate (recruitment rate 62.50 %). Qualitatively, acupuncture was perceived to be beneficial and effective. Quantitatively, acupuncture demonstrated clinically meaningful change in average pain intensity (raw change = 2.69) and worst pain intensity (raw change = 4.00). Feasibility-specific data identified that before undertaking a definitive trial, recruitment, practitioner adherence to the acupuncture protocol, completion of outcome measures at 1 month follow-up and blinding should be addressed. Appropriate outcome measures were identified for use in a definitive trial. Data were generated for future sample size calculations (effect size 0.64). Allowing for a 20 % dropout rate, a sample size of 85 participants per group would be needed in a future definitive trial.

Conclusions

A future definitive trial may be possible if the areas identified in this study are addressed. As acupuncture may be effective at treating PLP, and as this feasibility study suggests that a definitive trial may be possible, a multicentred trial with adequate sample size and blinding is now needed.

Trial registration

ClinicalTrials.gov Identifier: NCT02126436, registered on 4 September 2014.

Electronic supplementary material

The online version of this article (doi:10.1186/s13063-016-1639-z) contains supplementary material, which is available to authorized users.

Therapist Differentiation and Couple Clients' Perceptions of Therapeutic Alliance

Therapeutic alliance has been acknowledged as one of the catalysts for change within a therapeutic relationship. The contributions of therapists' characteristics to alliance are not often studied. From a Bowen System's Theory perspective, the therapist's level of differentiation would be highly relevant to the development of a therapeutic alliance. The hypothesis for this study was that therapists who are able to take a more differentiated stance in therapy will build a stronger therapeutic alliance. To test this hypothesis, multilevel modeling procedures were performed, using data from nine therapists and 93 couple cases collected at a large, Midwestern university. Therapist differentiation of self was found to be weakly associated with the clients' perception of therapeutic alliance across the early sessions of therapy, but not in the expected direction. Although the results were unexpected, this study provides an example of the potential of examining therapist characteristics from within one model of therapy, that can be applied across various clients and various models of therapy.

Design and analysis of clinical trials with clustering effects due to treatment

Where patients receive therapy as a group, there are good theoretical reasons to believe that variation in the outcome will be smaller for patients treated in the same group than for patients treated in different groups. Similarly, where different therapists treat different groups of patients, outcome for patients treated by the same therapist may differ less than outcome for patients treated by different therapists. Clinical trials evaluating such therapies need to consider this potential lack of independence. As with cluster-randomized trials, this has implications for the precision of treatment effects estimates and statistical power. There are nevertheless differences between clustering due to the organization of treatment and that due to randomization. In cluster-randomized trials the distribution of cluster sizes in each treatment arm should be similar as a consequence of randomization unless there is differential loss to follow-up. With clustering due to therapy group or therapist, cluster size may differ systematically between treatment arms, due to size of therapy groups or differing health professional caseload. Intra-cluster correlation may also differ between treatment arms. The implications of differential cluster size and intracluster correlation for design and analysis will be illustrated by data from two trials, the first comparing nurse practitioner care with general practitioner care, and the second comparing a group therapy with individual treatment as usual. The special case where a group therapy or therapist is compared with an unclustered treatment is examined in detail using a simulation study. The implications of differential clustering effects for sample size and power are addressed. It is argued that the design and analysis of this type of trial should take account of possible heterogeneity in cluster size and intracluster correlation.

Guidelines for Meta-Analyses of Counseling Psychology Research

This article conceptually describes the steps in conducting quantitative meta-analyses of counseling psychology research with minimal reliance on statistical formulas. The authors identify sources that describe necessary statistical formula for various meta-analytic calculations and describe recent developments in meta-analytic techniques. The authors illustrate meta-analytic procedures with recently published meta-analyses in counseling psychology, and last, they provide a guide for writing up meta-analytic studies for publication.

Estimating effect size when there is clustering in one treatment group

Some experimental designs involve clustering within only one treatment group. Such designs may involve group tutoring, therapy administered by multiple therapists, or interventions administered by clinics for the treatment group, whereas the control group receives no treatment. In such cases, the data analysis often proceeds as if there were no clustering within the treatment group. A consequence is that the actual significance level of the treatment effects is larger (i.e., actual p values are larger) than nominal. Additionally, biases will be introduced in estimates of the effect sizes and their variances, leading to inflated effects and underestimated variances when clustering in the treatment group is not taken into account. These consequences of clustering can seriously compromise the interpretation of study results. This article shows how information on the intraclass correlation can be used to obtain a correction for biases in the effect sizes and their variances, and also to obtain an adjustment to the significance test for the effects of clustering.

Is It All about the Higher Dose? Why Psychoanalytic Therapy Is an Effective Treatment for Major Depression

Empirical evidence for the effectiveness of long-term psychodynamic psychotherapy (LTPP) in patients with mood disorders is growing. However, it is unclear whether the effectiveness of LTPP is due to distinctive features of psychodynamic/psychoanalytic techniques or to a higher number of sessions. We tested these rival hypotheses in a quasi-experimental study comparing psychoanalytic therapy (i.e., high-dose LTPP) with psychodynamic therapy (i.e., low-dose LTPP) and cognitive-behavioural therapy (CBT) for depression. Analyses were based on a subsample of 77 subjects, with 27 receiving psychoanalytic therapy, 26 receiving psychodynamic therapy and 24 receiving CBT. Depressive symptoms, interpersonal problems and introject affiliation were assessed prior to treatment, after treatment and at the 1-, 2- and 3-year follow-ups. Psychoanalytic techniques were assessed from three audiotaped middle sessions per treatment using the Psychotherapy Process Q-Set. Subjects receiving psychoanalytic therapy reported having fewer interpersonal problems, treated themselves in a more affiliative way directly after treatment and tended to improve in depressive symptoms and interpersonal problems during follow-up as compared with patients receiving psychodynamic therapy and/or CBT. Multilevel mediation analyses suggested that post-treatment differences in interpersonal problems and introject affiliation were mediated by the higher number of sessions, and follow-up differences in depressive symptoms were mediated by the more pronounced application of psychoanalytic techniques. We also found some evidence for indirect treatment effects via psychoanalytic techniques on changes in introject affiliation during follow-up. These results provide support for the prediction that both a high dose and the application of psychoanalytic techniques facilitate therapeutic change in patients with major depression.

KEY PRACTITIONER MESSAGE

Psychoanalytic therapy is an effective treatment for major depression, especially in the long run. The differential effectiveness of psychoanalytic therapy cannot be fully explained by its higher dose. Distinctive features of psychoanalytic technique (e.g., focusing on patients' dreams, fantasies, sexual experiences or childhood memories) may play an important role in establishing sustained therapeutic change.

Statistical challenges in assessing potential efficacy of complex interventions in pilot or feasibility studies

Early phase trials of complex interventions currently focus on assessing the feasibility of a large randomised control trial and on conducting pilot work. Assessing the efficacy of the proposed intervention is generally discouraged, due to concerns of underpowered hypothesis testing. In contrast, early assessment of efficacy is common for drug therapies, where phase II trials are often used as a screening mechanism to identify promising treatments. In this paper, we outline the challenges encountered in extending ideas developed in the phase II drug trial literature to the complex intervention setting. The prevalence of multiple endpoints and clustering of outcome data are identified as important considerations, having implications for timely and robust determination of optimal trial design parameters. The potential for Bayesian methods to help to identify robust trial designs and optimal decision rules is also explored.

Size and consistency of problem-solving consultation outcomes: an empirical analysis

In this study, we analyzed extant data to evaluate the variability and magnitude of students' behavior change outcomes (academic, social, and behavioral) produced by consultants through problem-solving consultation with teachers. Research questions were twofold: (a) Do consultants produce consistent and sizeable positive student outcomes across their cases as measured through direct and frequent assessment? and (b) What proportion of variability in student outcomes is attributable to consultants? Analyses of extant data collected from problem-solving consultation outcome studies that used single-case, time-series AB designs with multiple participants were analyzed. Four such studies ultimately met the inclusion criteria for the extant data, comprising 124 consultants who worked with 302 school teachers regarding 453 individual students. Consultants constituted the independent variable, while the primary dependent variable was a descriptive effect size based on student behavior change as measured by (a) curriculum-based measures, (b) permanent products, or (c) direct observations. Primary analyses involved visual and statistical evaluation of effect size magnitude and variability observed within and between consultants and studies. Given the nested nature of the data, multilevel analyses were used to assess consultant effects on student outcomes. Results suggest that consultants consistently produced positive effect sizes on average across their cases, but outcomes varied between consultants. Findings also indicated that consultants, teachers, and the corresponding studies accounted for a significant proportion of variability in student outcomes. This investigation advances the use of multilevel and integrative data analyses to evaluate consultation outcomes and extends research on problem-solving consultation, consultant effects, and meta-analysis of case study AB designs. Practical implications for evaluating consultation service delivery in school settings are also discussed.

Sample size calculation for treatment effects in randomized trials with fixed cluster sizes and heterogeneous intraclass correlations and variances

When comparing two different kinds of group therapy or two individual treatments where patients within each arm are nested within care providers, clustering of observations may occur in both arms. The arms may differ in terms of (a) the intraclass correlation, (b) the outcome variance, (c) the cluster size, and (d) the number of clusters, and there may be some ideal group size or ideal caseload in case of care providers, fixing the cluster size. For this case, optimal cluster numbers are derived for a linear mixed model analysis of the treatment effect under cost constraints as well as under power constraints. To account for uncertain prior knowledge on relevant model parameters, also maximin sample sizes are given. Formulas for sample size calculation are derived, based on the standard normal as the asymptotic distribution of the test statistic. For small sample sizes, an extensive numerical evaluation shows that in a two-tailed test employing restricted maximum likelihood estimation, a safe correction for both 80% and 90% power, is to add three clusters to each arm for a 5% type I error rate and four clusters to each arm for a 1% type I error rate.

Analyzing multiple outcomes in clinical research using multivariate multilevel models

OBJECTIVE

Multilevel models have become a standard data analysis approach in intervention research. Although the vast majority of intervention studies involve multiple outcome measures, few studies use multivariate analysis methods. The authors discuss multivariate extensions to the multilevel model that can be used by psychotherapy researchers.

METHOD AND RESULTS

Using simulated longitudinal treatment data, the authors show how multivariate models extend common univariate growth models and how the multivariate model can be used to examine multivariate hypotheses involving fixed effects (e.g., does the size of the treatment effect differ across outcomes?) and random effects (e.g., is change in one outcome related to change in the other?). An online supplemental appendix provides annotated computer code and simulated example data for implementing a multivariate model.

CONCLUSIONS

Multivariate multilevel models are flexible, powerful models that can enhance clinical research.

Heterogeneity in patient-reported outcomes following low-intensity mental health interventions: a multilevel analysis

Background

Variability in patient-reported outcomes of psychological treatments has been partly attributed to therapists – a phenomenon commonly known as therapist effects. Meta-analytic reviews reveal wide variation in therapist-attributable variability in psychotherapy outcomes, with most studies reporting therapist effects in the region of 5% to 10% and some finding minimal to no therapist effects. However, all except one study to date have been conducted in high-intensity or mixed intervention groups; therefore, there is scarcity of evidence on therapist effects in brief low-intensity psychological interventions.

Objective

To examine therapist effects in low-intensity interventions for depression and anxiety in a naturalistic setting.

Data and Analysis

Session-by-session data on patient-reported outcome measures were available for a cohort of 1,376 primary care psychotherapy patients treated by 38 therapists. Outcome measures included PHQ-9 (sensitive to depression) and GAD-7 (sensitive to general anxiety disorder) measures. Three-level hierarchical linear modelling was employed to estimate therapist-attributable proportion of variance in clinical outcomes. Therapist effects were evaluated using the intra-cluster correlation coefficient (ICC) and Bayesian empirical predictions of therapist random effects. Three sensitivity analyses were conducted: 1) using both treatment completers and non-completers; 2) a sub-sample of cases with baseline scores above the conventional clinical thresholds for PHQ-9 and GAD-7; and 3) a two-level model (using patient-level pre- and post-treatment scores nested within therapists).

Results

The ICC estimates for all outcome measures were very small, ranging between 0% and 1.3%, although most were statistically significant. The Bayesian empirical predictions showed that therapist random effects were not statistically significantly different from each other. Between patient variability explained most of the variance in outcomes.

Conclusion

Consistent with the only other study to date in low intensity interventions, evidence was found to suggest minimal to no therapist effects in patient-reported outcomes. This draws attention to the more prominent source of variability which is found at the between-patient level.

Dialectical behavior therapy skills for transdiagnostic emotion dysregulation: a pilot randomized controlled trial

Difficulties with emotions are common across mood and anxiety disorders. Dialectical behavior therapy skills training (DBT-ST) reduces emotion dysregulation in borderline personality disorder (BPD). Preliminary evidence suggests that use of DBT skills mediates changes seen in BPD treatments. Therefore, we assessed DBT-ST as a stand-alone, transdiagnostic treatment for emotion dysregulation and DBT skills use as a mediator of outcome. Forty-four anxious and/or depressed, non-BPD adults with high emotion dysregulation were randomized to 16 weeks of either DBT-ST or an activities-based support group (ASG). Participants completed measures of emotion dysregulation, DBT skills use, and psychopathology every 2 months through 2 months posttreatment. Longitudinal analyses indicated that DBT-ST was superior to ASG in decreasing emotion dysregulation (d = 1.86), increasing skills use (d = 1.02), and decreasing anxiety (d = 1.37) but not depression (d = 0.73). Skills use mediated these differential changes. Participants found DBT-ST acceptable. Thirty-two percent of DBT-ST and 59% of ASG participants dropped treatment. Fifty-nine percent of DBT-ST and 50% of ASG participants complied with the research protocol of avoiding ancillary psychotherapy and/or medication changes. In summary, DBT-ST is a promising treatment for emotion dysregulation for depressed and anxious transdiagnostic adults, although more assessment of feasibility is needed.

How Low Can You Go?

Whereas general sample size guidelines have been suggested when estimating multilevel models, they are only generalizable to a relatively limited number of data conditions and model structures, both of which are not very feasible for the applied researcher. In an effort to expand our understanding of two-level multilevel models under less than ideal conditions, Monte Carlo methods, through SAS/IML, were used to examine model convergence rates, parameter point estimates (statistical bias), parameter interval estimates (confidence interval accuracy and precision), and both Type I error control and statistical power of tests associated with the fixed effects from linear two-level models estimated with PROC MIXED. These outcomes were analyzed as a function of: (a) level-1 sample size, (b) level-2 sample size, (c) intercept variance, (d) slope variance, (e) collinearity, and (f) model complexity. Bias was minimal across nearly all conditions simulated. The 95% confidence interval coverage and Type I error rate tended to be slightly conservative. The degree of statistical power was related to sample sizes and level of fixed effects; higher power was observed with larger sample sizes and level-1 fixed effects.

The ACTonHEART study: rationale and design of a randomized controlled clinical trial comparing a brief intervention based on Acceptance and Commitment Therapy to usual secondary prevention care of coronary heart disease

BACKGROUND

Modifiable risk factors, including life-style habits and psychological variables, have been increasingly demonstrated to have an important role in influencing morbidity and mortality in cardiovascular patients, and to account for approximately 90% of the population risk for cardiac events.Acceptance and Commitment Therapy (ACT) has shown effectiveness in promoting healthy behaviors, and improving psychological well-being in patients with chronic physical conditions. Moreover, a first application of an acceptance-based program in cardiac patients has revealed high treatment satisfaction and initial evidences of effectiveness in increasing heart-healthy behaviour. However, no clinical trial to date has evaluated the efficacy of an acceptance-based program for the modification of cardiovascular risk factors and the improvement of psychological well-being, compared to usual secondary prevention care.

METHODS

Approximately 168 patients will be recruited from an outpatient cardiac rehabilitation unit and randomly assigned to receive usual care or usual care + a brief ACT-based intervention. The ACT group will be administered five group therapy sessions integrating educational topics on heart-healthy behaviours with acceptance and mindfulness skills. Participants will be assessed at baseline, six weeks later (post treatment for the ACT condition), at six and twelve months follow-up.A partially-nested design will be used to balance effects due to clustering of participants into small therapy groups. Primary outcome measures will include biological indicators of cardiovascular risk and self-reported psychological well-being. Treatment effects will be tested via multilevel modeling after which the mediational role of psychological flexibility will be evaluated.

DISCUSSION

The ACTonHEART study is the first randomized clinical trial designed to evaluate the efficacy of a brief group-administered, ACT-based program to promote health behavior change and psychological well-being among cardiac patients. Results will address the effectiveness of a brief treatment created to simultaneously impact multiple cardiovascular risk factors. Conducted in the context of clinical practice, this trial will potentially offer empirical support to alternative interventions to improve quality of life and reduce mortality and morbidity rates among cardiac patients.

TRIAL REGISTRATION

clinicaltrials.gov/ (NCT01909102).

A Multidimensional and Multilevel Extension of a Random-Effect Approach to Subjective Judgment in Rating Scales

In responding to rating scale items, respondents may hold different perspectives on the given categories. The random-effect rating scale model (RERSM), developed to account for variations in the category thresholds across respondents, is unidimensional and unilevel. It becomes statistically inefficient when multiple unidimensional tests have to be analyzed and inapplicable when data have a multilevel structure (e.g., respondents nested within organizations, students nested within schools). To resolve these problems, this study develops a multidimensional and multilevel version of the RERSM. The parameters can be estimated with existing computer software. Thus, there is no need to develop estimation procedures or corresponding computer programs. Simulation studies were conducted to evaluate the parameter recovery of the multidimensional RERSM, the multilevel RERSM, and the multidimensional and multilevel RERSM using WinBUGS. The results showed that the parameter recovery was generally satisfactory. An empirical example of the application of the multidimensional and multilevel RERSM to 2006 Program for International Student Assessment inventories about attitudes toward learning sciences is provided.