The enduring effects of psychodynamic treatments vis-à-vis alternative treatments: A multilevel longitudinal meta-analysis

Although evidence suggests that the benefits of psychodynamic treatments are sustained over time, presently it is unclear whether these sustained benefits are superior to non-psychodynamic treatments. Additionally, the extant literature comparing the sustained benefits of psychodynamic treatments compared to alternative treatments is limited with methodological shortcomings. The purpose of the current study was to conduct a rigorous test of the growth of the benefits of psychodynamic treatments relative to alternative treatments across distinct domains of change (i.e., all outcome measures, targeted outcome measures, non-targeted outcome measures, and personality outcome measures). To do so, the study employed strict inclusion criteria to identify randomized clinical trials that directly compared at least one bona fide psychodynamic treatment and one bona fide non-psychodynamic treatment. Hierarchical linear modeling (Raudenbush, Bryk, Cheong, Congdon, & du Toit, 2011) was used to longitudinally model the impact of psychodynamic treatments compared to non-psychodynamic treatments at post-treatment and to compare the growth (i.e., slope) of effects beyond treatment completion. Findings from the present meta-analysis indicated that psychodynamic treatments and non-psychodynamic treatments were equally efficacious at post-treatment and at follow-up for combined outcomes (k=20), targeted outcomes (k=19), non-targeted outcomes (k=17), and personality outcomes (k=6). Clinical implications, directions for future research, and limitations are discussed.

Anger and posttraumatic stress disorder symptoms in crime victims: A longitudinal analysis

Among trauma-exposed individuals, severity of posttraumatic stress disorder (PTSD) symptoms is strongly correlated with anger. The authors used 2 longitudinal data sets with 282 and 218 crime victims, respectively, to investigate the temporal sequence of anger and PTSD symptoms following the assault. Cross-lagged regression analyses indicated that PTSD symptoms predicted subsequent level of anger, but that anger did not predict subsequent PTSD symptoms. Testing alternative models (common factor model, unmeasured 3rd variable model) that might account for spuriousness of the relation strengthened confidence in the results of the cross-lagged analyses. Further analyses suggested that rumination mediates the effect of PTSD symptoms on anger.

Does low self-esteem predict depression and anxiety? A meta-analysis of longitudinal studies

Low self-esteem and depression are strongly related, but there is not yet consistent evidence on the nature of the relation. Whereas the vulnerability model states that low self-esteem contributes to depression, the scar model states that depression erodes self-esteem. Furthermore, it is unknown whether the models are specific for depression or whether they are also valid for anxiety. We evaluated the vulnerability and scar models of low self-esteem and depression, and low self-esteem and anxiety, by meta-analyzing the available longitudinal data (covering 77 studies on depression and 18 studies on anxiety). The mean age of the samples ranged from childhood to old age. In the analyses, we used a random-effects model and examined prospective effects between the variables, controlling for prior levels of the predicted variables. For depression, the findings supported the vulnerability model: The effect of self-esteem on depression (β = -.16) was significantly stronger than the effect of depression on self-esteem (β = -.08). In contrast, the effects between low self-esteem and anxiety were relatively balanced: Self-esteem predicted anxiety with β = -.10, and anxiety predicted self-esteem with β = -.08. Moderator analyses were conducted for the effect of low self-esteem on depression; these suggested that the effect is not significantly influenced by gender, age, measures of self-esteem and depression, or time lag between assessments. If future research supports the hypothesized causality of the vulnerability effect of low self-esteem on depression, interventions aimed at increasing self-esteem might be useful in reducing the risk of depression.

From big smartphone data to worldwide research: The Mobile Data Challenge

This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale research initiative aimed at generating innovations around smartphone-based research, as well as community-based evaluation of mobile data analysis methodologies. First, we review the Lausanne Data Collection Campaign (LDCC), an initiative to collect unique longitudinal smartphone dataset for the MDC. Then, we introduce the Open and Dedicated Tracks of the MDC, describe the specific datasets used in each of them, discuss the key design and implementation aspects introduced in order to generate privacy-preserving and scientifically relevant mobile data resources for wider use by the research community, and summarize the main research trends found among the 100+ challenge submissions. We finalize by discussing the main lessons learned from the participation of several hundred researchers worldwide in the MDC Tracks.

Streaming Support for Data Intensive Cloud-Based Sequence Analysis

Cloud computing provides a promising solution to the genomics data deluge problem resulting from the advent of next-generation sequencing (NGS) technology. Based on the concepts of “resources-on-demand” and “pay-as-you-go”, scientists with no or limited infrastructure can have access to scalable and cost-effective computational resources. However, the large size of NGS data causes a significant data transfer latency from the client’s site to the cloud, which presents a bottleneck for using cloud computing services. In this paper, we provide a streaming-based scheme to overcome this problem, where the NGS data is processed while being transferred to the cloud. Our scheme targets the wide class of NGS data analysis tasks, where the NGS sequences can be processed independently from one another. We also provide the elastream package that supports the use of this scheme with individual analysis programs or with workflow systems. Experiments presented in this paper show that our solution mitigates the effect of data transfer latency and saves both time and cost of computation.

Mining tissue microarray data to uncover combinations of biomarker expression patterns that improve intermediate staging and grading of clear cell renal cell cancer

PURPOSE: Tumor stage and nuclear grade are the most important prognostic parameters of clear cell renal cell carcinoma (ccRCC). The progression risk of ccRCC remains difficult to predict particularly for tumors with organ-confined stage and intermediate differentiation grade. Elucidating molecular pathways deregulated in ccRCC may point to novel prognostic parameters that facilitate planning of therapeutic approaches. EXPERIMENTAL DESIGN: Using tissue microarrays, expression patterns of 15 different proteins were evaluated in over 800 ccRCC patients to analyze pathways reported to be physiologically controlled by the tumor suppressors von Hippel-Lindau protein and phosphatase and tensin homologue (PTEN). Tumor staging and grading were improved by performing variable selection using Cox regression and a recursive bootstrap elimination scheme. RESULTS: Patients with pT2 and pT3 tumors that were p27 and CAIX positive had a better outcome than those with all remaining marker combinations. A prolonged survival among patients with intermediate grade (grade 2) correlated with both nuclear p27 and cytoplasmic PTEN expression, as well as with inactive, nonphosphorylated ribosomal protein S6. By applying graphical log-linear modeling for over 700 ccRCC for which the molecular parameters were available, only a weak conditional dependence existed between the expression of p27, PTEN, CAIX, and p-S6, suggesting that the dysregulation of several independent pathways are crucial for tumor progression. CONCLUSIONS: The use of recursive bootstrap elimination, as well as graphical log-linear modeling for comprehensive tissue microarray (TMA) data analysis allows the unraveling of complex molecular contexts and may improve predictive evaluations for patients with advanced renal cancer.

Auditory verbal hallucinations: imaging, analysis, and intervention

In this article, we will link neuroimaging, data analysis, and intervention methods in an important psychiatric condition: auditory verbal hallucinations (AVH). The clinical and phenomenological background as well as neurophysiological findings will be covered and discussed with respect to noninvasive brain stimulation. Additionally, methods of noninvasive brain stimulation will be presented as ways to intervene with AVH. Finally, preliminary conclusions and possible future perspectives will be proposed.

Does tenofovir influence efavirenz pharmacokinetics?

INTRODUCTION: A recent report described a possible interaction between tenofovir (TFV) and efavirenz (EFV). Patients developed neuropsychiatric manifestations upon introduction of TFV on a stable EFV-containing regimen. We evaluated the possibility of a pharmacokinetic interaction between TFV and EFV by assessing cross-sectional and longitudinal data in 169 individuals receiving EFV. RESULTS: EFV plasma area-under-the-curve (AUC) levels were comparable among individuals receiving (n=18) or not receiving TFV (n=151); 57,962 versus 52,293 ng*h/ml. However, under conditions of limited EFV metabolism, that is, the group of 23 individuals carrying two copies of CYP2B6 loss/diminished-function alleles, plasma AUC values were highest among individuals receiving TFV (n=5, 353,031 ng*h/ml), compared with those not receiving TFV (n=18, 180,689 ng*h/ml). Statistical analysis identified both a global, sixfold effect of CYP2B6 loss/diminished function (P < 0.0001) and a significant interaction between the number of loss/diminished-function alleles and the co-medication with TFV (P = 0.009). CONCLUSION: Although there is no clear evidence for a pharmacokinetic interaction between TFV and EFV, we cannot rule out an interaction between these drugs restricted to individuals who are slow EFV metabolizers.

From text to codings: intercoder reliability assessment in qualitative content analysis

BACKGROUND: High intercoder reliability (ICR) is required in qualitative content analysis for assuring quality when more than one coder is involved in data analysis. The literature is short of standardized procedures for ICR procedures in qualitative content analysis. OBJECTIVE: To illustrate how ICR assessment can be used to improve codings in qualitative content analysis. METHODS: Key steps of the procedure are presented, drawing on data from a qualitative study on patients' perspectives on low back pain. RESULTS: First, a coding scheme was developed using a comprehensive inductive and deductive approach. Second, 10 transcripts were coded independently by two researchers, and ICR was calculated. A resulting kappa value of .67 can be regarded as satisfactory to solid. Moreover, varying agreement rates helped to identify problems in the coding scheme. Low agreement rates, for instance, indicated that respective codes were defined too broadly and would need clarification. In a third step, the results of the analysis were used to improve the coding scheme, leading to consistent and high-quality results. DISCUSSION: The quantitative approach of ICR assessment is a viable instrument for quality assurance in qualitative content analysis. Kappa values and close inspection of agreement rates help to estimate and increase quality of codings. This approach facilitates good practice in coding and enhances credibility of analysis, especially when large samples are interviewed, different coders are involved, and quantitative results are presented.

Statistical analysis of personal radiofrequency electromagnetic field measurements with nondetects

Exposimeters are increasingly applied in bioelectromagnetic research to determine personal radiofrequency electromagnetic field (RF-EMF) exposure. The main advantages of exposimeter measurements are their convenient handling for study participants and the large amount of personal exposure data, which can be obtained for several RF-EMF sources. However, the large proportion of measurements below the detection limit is a challenge for data analysis. With the robust ROS (regression on order statistics) method, summary statistics can be calculated by fitting an assumed distribution to the observed data. We used a preliminary sample of 109 weekly exposimeter measurements from the QUALIFEX study to compare summary statistics computed by robust ROS with a naïve approach, where values below the detection limit were replaced by the value of the detection limit. For the total RF-EMF exposure, differences between the naïve approach and the robust ROS were moderate for the 90th percentile and the arithmetic mean. However, exposure contributions from minor RF-EMF sources were considerably overestimated with the naïve approach. This results in an underestimation of the exposure range in the population, which may bias the evaluation of potential exposure-response associations. We conclude from our analyses that summary statistics of exposimeter data calculated by robust ROS are more reliable and more informative than estimates based on a naïve approach. Nevertheless, estimates of source-specific medians or even lower percentiles depend on the assumed data distribution and should be considered with caution.

Preclinical disability as a risk factor for falls in community-dwelling older adults

BACKGROUND: Falls are common and serious problems in older adults. The goal of this study was to examine whether preclinical disability predicts incident falls in a European population of community-dwelling older adults. METHODS: Secondary data analysis was performed on a population-based longitudinal study of 1644 community-dwelling older adults living in London, U.K.; Hamburg, Germany; Solothurn, Switzerland. Data were collected at baseline and 1-year follow-up using a self-administered multidimensional health risk appraisal questionnaire, including validated questions on falls, mobility disability status (high function, preclinical disability, task difficulty), and demographic and health-related characteristics. Associations were evaluated using bivariate and multivariate logistic regression analyses. RESULTS: Overall incidence of falls was 24%, and increased by worsening mobility disability status: high function (17%), preclinical disability (32%), task difficulty (40%), test-of-trend p <.003. In multivariate analysis adjusting for other fall risk factors, preclinical disability (odds ratio [OR] = 1.7, 95% confidence interval [CI], 1.1-2.5), task difficulty (OR = 1.7, 95% CI, 1.1-2.6) and history of falls (OR = 4.7, 95% CI, 3.5-6.3) were the strongest significant predictors of falls. In stratified multivariate analyses, preclinical disability equally predicted falls in participants with (OR = 1.7, 95% CI, 1.0-3.0) and without history of falls (OR = 1.8, 95% CI, 1.1-3.0). CONCLUSIONS: This study provides longitudinal evidence that self-reported preclinical disability predicts incident falls at 1-year follow-up independent of other self-reported fall risk factors. Multidimensional geriatric assessment that includes preclinical disability may provide a unique early warning system as well as potential targets for intervention.

Comparison of phenotypes of childhood wheeze and cough in 2 independent cohorts

BACKGROUND Among children with wheeze and recurrent cough there is great variation in clinical presentation and time course of the disease. We previously distinguished 5 phenotypes of wheeze and cough in early childhood by applying latent class analysis to longitudinal data from a population-based cohort (original cohort). OBJECTIVE To validate previously identified phenotypes of childhood cough and wheeze in an independent cohort. METHODS We included 903 children reporting wheeze or recurrent cough from an independent population-based cohort (validation cohort). As in the original cohort, we used latent class analysis to identify phenotypes on the basis of symptoms of wheeze and cough at 2 time points (preschool and school age) and objective measurements of atopy, lung function, and airway responsiveness (school age). Prognostic outcomes (wheeze, bronchodilator use, cough apart from colds) 5 years later were compared across phenotypes. RESULTS When using a 5-phenotype model, the analysis distinguished 3 phenotypes of wheeze and 2 of cough as in the original cohort. Two phenotypes were closely similar in both cohorts: Atopic persistent wheeze (persistent multiple trigger wheeze and chronic cough, atopy and reduced lung function, poor prognosis) and transient viral wheeze (early-onset transient wheeze with viral triggers, favorable prognosis). The other phenotypes differed more between cohorts. These differences might be explained by differences in age at measurements. CONCLUSIONS Applying the same method to 2 different cohorts, we consistently identified 2 phenotypes of wheeze (atopic persistent wheeze, transient viral wheeze), suggesting that these represent distinct disease processes. Differences found in other phenotypes suggest that the age when features are assessed is critical and should be considered carefully when defining phenotypes.

Cluster randomized clinical trials in orthodontics: design, analysis and reporting issues

Cluster randomized trials (CRTs) use as the unit of randomization clusters, which are usually defined as a collection of individuals sharing some common characteristics. Common examples of clusters include entire dental practices, hospitals, schools, school classes, villages, and towns. Additionally, several measurements (repeated measurements) taken on the same individual at different time points are also considered to be clusters. In dentistry, CRTs are applicable as patients may be treated as clusters containing several individual teeth. CRTs require certain methodological procedures during sample calculation, randomization, data analysis, and reporting, which are often ignored in dental research publications. In general, due to similarity of the observations within clusters, each individual within a cluster provides less information compared with an individual in a non-clustered trial. Therefore, clustered designs require larger sample sizes compared with non-clustered randomized designs, and special statistical analyses that account for the fact that observations within clusters are correlated. It is the purpose of this article to highlight with relevant examples the important methodological characteristics of cluster randomized designs as they may be applied in orthodontics and to explain the problems that may arise if clustered observations are erroneously treated and analysed as independent (non-clustered).

Decreasing risk of hepatitis a infection in león, nicaragua: evidence from cross-sectional and longitudinal seroepidemiology studies

BACKGROUND AND OBJECTIVES Nicaragua is highly endemic for hepatitis A. We aimed to provide an estimate of the change in the age-specific risk of hepatitis A virus (HAV) infection based on serological data from cross-sectional and longitudinal samples collected in León, Nicaragua, in 1995/96 (n = 979) and 2003 (n = 494). METHODS The observed age-specific prevalence of anti-HAV antibodies was correlated to the age-specific risk of infection by calculating the probability of freedom from infection at a specific age. RESULTS The proportion of seropositive children aged 1.5 to 6 years was 42% in 2003 compared to 67% in 1995/96. Estimated annual risk of infection for a 3-year old child was 30% (95% CI: 27.0%, 33.1%) in 1995 and 15.5% (95% CI: 12.4%, 19.0%) in 2003. There was good agreement between estimates based on cross-sectional and longitudinal data. The age-specific geometric mean of the quantified anti-HAV antibody levels assessed in 2003 was highest at age 4 and decreased steadily up to age 40. CONCLUSIONS The substantially lower risk of HAV infection in 2003 than in 1995 for young children indicates a beginning transition from high to intermediate endemicity in León, Nicaragua. Consecutive age-stratified serosurveys are useful to assess changes in risk of infection following public health interventions. The decreasing age-specific GMC of anti-HAV antibodies during adulthood in a country with endemic HAV indirectly suggests that ongoing HAV exposure in the community has marginal boosting effect on antibody levels once protective immunity has been established by natural infection.

Chronic NSAID use and long-term decline of renal function in a prospective rheumatoid arthritis cohort study

OBJECTIVES Non-steroidal anti-inflammatory drugs (NSAIDs) may cause kidney damage. This study assessed the impact of prolonged NSAID exposure on renal function in a large rheumatoid arthritis (RA) patient cohort. METHODS Renal function was prospectively followed between 1996 and 2007 in 4101 RA patients with multilevel mixed models for longitudinal data over a mean period of 3.2 years. Among the 2739 'NSAID users' were 1290 patients treated with cyclooxygenase type 2 selective NSAIDs, while 1362 subjects were 'NSAID naive'. Primary outcome was the estimated glomerular filtration rate according to the Cockroft-Gault formula (eGFRCG), and secondary the Modification of Diet in Renal Disease and Chronic Kidney Disease Epidemiology Collaboration formula equations and serum creatinine concentrations. In sensitivity analyses, NSAID dosing effects were compared for patients with NSAID registration in ≤/>50%, ≤/>80% or ≤/>90% of assessments. FINDINGS In patients with baseline eGFRCG >30 mL/min, eGFRCG evolved without significant differences over time between 'NSAID users' (mean change in eGFRCG -0.87 mL/min/year, 95% CI -1.15 to -0.59) and 'NSAID naive' (-0.67 mL/min/year, 95% CI -1.26 to -0.09, p=0.63). In a multivariate Cox regression analysis adjusted for significant confounders age, sex, body mass index, arterial hypertension, heart disease and for other insignificant factors, NSAIDs were an independent predictor for accelerated renal function decline only in patients with advanced baseline renal impairment (eGFRCG <30 mL/min). Analyses with secondary outcomes and sensitivity analyses confirmed these results. CONCLUSIONS NSAIDs had no negative impact on renal function estimates but in patients with advanced renal impairment.