Into the Wild, Out of the Woods: A Systematic Case Study on Facilitating Emotional Change.

Cognitive and behavioral treatment programs for individuals who have committed sexual offenses (ISOs) have shown significant but small effect sizes. A growing body of research points toward the importance of difficulties in affect regulation (AR) as a risk factor for sexual recidivism. On this basis, it seems important to target difficulties in AR in treatment. The current systematic case study investigates the potential contribution of emotion-focused therapy (EFT) to changing problematic AR in ISOs. Kevin was a high-risk offender with a traumatic history who met the diagnostic criteria of pedophilic and borderline disorders, with serious AR difficulties. Self-report outcome measures, observation measures, and a biomarker were used to track changes in AR, psychological symptoms, and distress during baseline (Phase A); treatment as usual (Phase B); treatment with an EFT component added (Phase C); and follow-up (Phase A). Statistically significant change was found in AR, psychological symptoms, and distress during treatment (Phase B + C); however, it is not possible to attribute these changes causally to EFT. An examination of the qualitative process data provides deeper insights into how the client reacted to specific EFT interventions. Verbatim clinical vignettes are included to clarify key interventions, hindrances, and mechanisms of change. This study provides preliminary support for the role of therapy to facilitate emotional change in ISOs.

Boosting the precision of mediation analyses of randomised experiments through covariate adjustment.

Analyses of randomised experiments frequently include attempts to decompose the intention-to-treat effect into a direct and indirect effect, mediated by given intermediaries, with the aim to shed light onto the treatment mechanism. Methods from causal mediation analysis have facilitated this by allowing for arbitrary models for the outcome and the mediator. They thereby generalise the traditional approach to direct and indirect effects, which is essentially limited to linear models. The default maximum likelihood methods make use of a model for the conditional distribution of the mediator, given treatment and baseline covariates, but are prone to bias when that model is misspecified. In randomised experiments, specification of such model can be easily avoided, but at the expense of a sometimes major efficiency loss when those baseline covariates are predictive of the mediator. In this article, we develop a compromise approach: it makes use of a model for the mediator to optimally extract information from the baseline covariate data but is insulated from the impact of misspecification of that model; it achieves this by exploiting the known randomisation probabilities. Simulation studies and the analysis of a randomised study show major efficiency gains and confirm our theoretical findings that the default methods from causal mediation analysis are sometimes, although not always, reasonably robust to model misspecification. Copyright © 2017 John Wiley & Sons, Ltd.

Vicarious experiences and detection accuracy while observing pain and touch: The effect of perspective taking.

In this study, we investigated the effects of observing pain and touch in others on vicarious somatosensory experiences and the detection of subtle somatosensory stimuli. Furthermore, the effect of taking a first- versus a third-person perspective was investigated. Undergraduates (N = 57) viewed videos depicting hands being pricked (pain), hands being touched by a cotton swab (touch), and control scenes (same approaching movement of a hand as in the other video categories, but without the painful/touching object) while experiencing vibrotactile stimuli themselves on the left, on the right, or on both hands. Participants reported the location at which they felt a somatosensory stimulus. The vibrotactile stimuli and visual scenes were applied in a spatially congruent or incongruent way, and other trials were presented without vibrotactile stimuli. The videos were depicted in first-person perspective and third-person perspective (i.e., the videos were shown upside down). We calculated the proportions of correct responses and false alarms (i.e., numbers of trials on which a vicarious somatosensory experience was reported congruent or incongruent to the site of the visual information). Pain-related scenes facilitated the detection of tactile stimuli and augmented the number of vicarious somatosensory experiences, as compared with observing the touch or control videos. Detection accuracy was higher for videos depicted in first-person perspective than for those in third-person perspective. Perspective had no effect on the number of vicarious somatosensory experiences. This study indicates that somatosensory detection is particularly enhanced during the observation of pain-related scenes, as compared to the observation of touch or control videos. These research findings further demonstrate that perspective taking impacts somatosensory detection, but not the report of vicarious experiences.

Data-analytical stability of cluster-wise and peak-wise inference in fMRI data analysis.

BACKGROUND: Carp (2012) demonstrated the large variability that is present in the method sections of fMRI studies. This methodological variability between studies limits reproducible research. NEW METHOD: Evaluation protocols for methods used in fMRI should include data-analytical stability measures quantifying the variability in results following choices in the methods. Data-analytical stability can be seen as a proxy for reproducibility. To illustrate how one can perform such evaluations, we study two competing approaches for topological feature based inference (random field theory and permutation based testing) and two competing methods for smoothing (Gaussian smoothing and adaptive smoothing). We compare these approaches from the perspective of data-analytical stability in real data, and additionally consider validity and reliability in simulations. RESULTS: There is clear evidence that choices in the methods impact the validity, reliability and stability of the results. For the particular comparison studied, we find that permutation based methods render the most valid results. For stability and reliability, the performance of different smoothing and inference types depends on the setting. However, while being more reliable, adaptive smoothing can evoke less stable results when using larger kernel width, especially with cluster size based permutation inference. COMPARISON WITH EXISTING METHODS: While existing evaluation methods focus on validity and reliability, we show that data-analytical stability enables to further distinguish between performance of different methods. CONCLUSION: Data-analytical stability is an important additional criterion that can easily be incorporated in evaluation protocols.

Sexual and relational satisfaction in couples where the woman has polycystic ovary syndrome: a dyadic analysis.

STUDY QUESTION: How are objective characteristics of polycystic ovary syndrome (PCOS) and PCOS-related concerns associated with the sexual and relational satisfaction of PCOS women and their partners? SUMMARY ANSWER: Both objective PCOS characteristics (parity, women's body mass index (BMI) and current unfulfilled wish to conceive) and PCOS-related concerns (women's infertility-related and acne-related concerns) were associated with sexual and/or relational satisfaction, although some associations differed for PCOS women and their partners. WHAT IS KNOWN ALREADY: There is some evidence indicating an association between objective PCOS characteristics and sexual satisfaction of PCOS women, but this evidence is conflicting, scarce, and often validated questionnaires have not been used to evaluate sexual satisfaction. No evidence is available about the association of: (i) PCOS with relational satisfaction; (ii) PCOS-related concerns with sexual and relational satisfaction; and (iii) PCOS with sexual and relational satisfaction as experienced by partners of PCOS women. STUDY DESIGN, SIZE, DURATION: We set up a cross-sectional study from April 2007 until April 2009, including 31 overweight (BMI ≥ 25 kg/m(2)) women with PCOS and at a reproductive age as well as their partners with whom they had a committed intimate relationship at the time of recruitment. PARTICIPANTS/MATERIALS, SETTING, METHODS: The study was performed at the fertility center of the Ghent University Hospital. Objective PCOS characteristics were registered and PCOS-related concerns were evaluated by the PCOS Questionnaire. Sexual (SS) and relational (RS) satisfaction were measured by the Maudsley Marital Questionnaire (MMQ). Dyadic statistical analyses were performed using linear mixed models (α < 0.05). MAIN RESULTS AND THE ROLE OF CHANCE: A lower parity tended to be associated with higher levels of sexual and relational satisfaction, with a significantly stronger association in PCOS women than in their partners (p(SS) = 0.015 and p(RS) = 0.009). A higher BMI tended to be associated with lower and higher satisfaction levels (sexual and relational) in PCOS women and their partners, respectively, with a significantly stronger association in the partners (p(SS) = 0.029 and p(RS) = 0.021). The presence of a current unfulfilled wish to conceive and a higher level of infertility-related concerns was significantly more strongly associated with a higher level of relational satisfaction for PCOS women than for their partners (p(RS) = 0.021 and p(RS) = 0.011, respectively). Higher levels of acne-related concern were significantly associated with lower levels of sexual satisfaction in both PCOS women (p(SS) = 0.025) and their partners (p(SS) = 0.002). LIMITATIONS, REASONS FOR CAUTION: The fact that this study was performed in a sample of PCOS women who were all overweight and the small sample size are important limitations. Data were partially missing in some couples but this limitation was dealt with by using linear mixed models. WIDER IMPLICATIONS OF THE FINDINGS: Our results suggest a differential association of PCOS with sexual and relational satisfaction between PCOS women and their partners. This should be kept in mind during the psychological guidance of couples dealing with PCOS. STUDY FUNDING/COMPETING INTERESTS: V.D.F. is holder of a Special PhD Fellowship of the Flemish Foundation for Scientific Research (FWO-Vlaanderen). P.D.S. is holder of a fundamental clinical research mandate of the Flemish Foundation for Scientific Research (FWO-Vlaanderen). This research also received financial support by Merck Serono and Artevelde University College Ghent. There are no competing interests.

Efficacy and safety of sitagliptin when added to ongoing metformin therapy in patients with type 2 diabetes.

AIM: To assess the addition of sitagliptin to ongoing metformin therapy in patients with type 2 diabetes who were inadequately controlled [haemoglobin A(1c) (HbA(1c)) 7-11%] on metformin monotherapy. METHODS: Patients (n = 273) on metformin (>/=1500 mg/day) were randomized to receive the addition of once-daily placebo, sitagliptin 100 mg or rosiglitazone 8 mg in a 1 : 1 : 1 ratio for 18 weeks. The efficacy analysis was based on the all-patients-treated population using an analysis of co-variance with change in HbA(1c) from baseline as the primary endpoint. RESULTS: The mean baseline HbA(1c) was 7.7% for the entire cohort. After 18 weeks, both active add-on therapies led to greater improvements in HbA(1c) from baseline: -0.73% for sitagliptin (p < 0.001 vs. placebo) and -0.79% for rosiglitazone compared with -0.22% for placebo. No difference was observed between the sitagliptin and rosiglitazone treatments (0.06% [95% confidence interval (CI): -0.14 to 0.25]). The proportion of patients achieving an HbA(1c) < 7% was greater with sitagliptin (55%) and rosiglitazone (63%) compared with placebo (38%). Body weight increased from baseline with rosiglitazone (1.5 kg) compared with body weight reduction with sitagliptin (-0.4 kg) and placebo (-0.8 kg). The difference in body weight between the sitagliptin and rosiglitazone groups was 1.9 kg (95% CI: 1.3-2.5). In a prespecified analysis, the proportion of patients experiencing a greater than 3-kg increase in body weight was 21% in the rosiglitazone group compared with 2% in both the sitagliptin and placebo groups. Both active treatments were generally well tolerated, with no increased risk of hypoglycaemia or gastrointestinal adverse events compared with placebo. CONCLUSIONS: In this 18-week study, the addition of sitagliptin was effective and well tolerated in patients with type 2 diabetes inadequately controlled with metformin monotherapy. Treatment with sitagliptin produced similar reductions in HbA(1c) compared with the addition of rosiglitazone.

Causal proportional hazards models and time-constant exposure in randomized clinical trials.

The last decade saw enormous progress in the development of causal inference tools to account for noncompliance in randomized clinical trials. With survival outcomes, structural accelerated failure time (SAFT) models enable causal estimation of effects of observed treatments without making direct assumptions on the compliance selection mechanism. The traditional proportional hazards model has however rarely been used for causal inference. The estimator proposed by Loeys and Goetghebeur (2003, Biometrics vol. 59 pp. 100-105) is limited to the setting of all or nothing exposure. In this paper, we propose an estimation procedure for more general causal proportional hazards models linking the distribution of potential treatment-free survival times to the distribution of observed survival times via observed (time-constant) exposures. Specifically, we first build models for observed exposure-specific survival times. Next, using the proposed causal proportional hazards model, the exposure-specific survival distributions are backtransformed to their treatment-free counterparts, to obtain - after proper mixing - the unconditional treatment-free survival distribution. Estimation of the parameter(s) in the causal model is then based on minimizing a test statistic for equality in backtransformed survival distributions between randomized arms.

A causal proportional hazards estimator for the effect of treatment actually received in a randomized trial with all-or-nothing compliance.

Survival data from randomized trials are most often analyzed in a proportional hazards (PH) framework that follows the intention-to-treat (ITT) principle. When not all the patients on the experimental arm actually receive the assigned treatment, the ITT-estimator mixes its effect on treatment compliers with its absence of effect on noncompliers. The structural accelerated failure time (SAFT) models of Robins and Tsiatis are designed to consistently estimate causal effects on the treated, without direct assumptions about the compliance selection mechanism. The traditional PH-model, however, has not yet led to such causal interpretation. In this article, we examine a PH-model of treatment effect on the treated subgroup. While potential treatment compliance is unobserved in the control arm, we derive an estimating equation for the Compliers PROPortional Hazards Effect of Treatment (C-PROPHET). The jackknife is used for bias correction and variance estimation. The method is applied to data from a recently finished clinical trial in cancer patients with liver metastases.

Baseline information in structural failure time estimators for the effect of observed treatment compliance.

Structural accelerated failure time models allow expression of the effect of treatment actually received in placebo-controlled randomized trials with non-compliance. Without further assumptions, the structural parameter is typically estimated via a series of auxiliary logrank tests, searching for the structural parameter that back-transforms treated survival times to latent treatment-free survival times which are equally distributed between randomized arms. In this paper we investigate to what extent score tests involving baseline covariates provide more powerful auxiliary tests and lead to more precise estimates of the structural parameter without compromising the alpha-level. We propose a set of estimating equations which combines score components for covariate effects based on the control arm only, with a log-likelihood score for treatment effect based on both arms. Analytic results for exponential models as well as simulation studies for the semi-parametric approach indicate that in many practical situations this incorporation of baseline covariates leads to more precise estimators of the structural effect. Relative efficiency is shown to depend on the selective nature of compliance. In a leukaemia trial we find the length of the 95 per cent confidence interval for the structural parameter is reduced to two-thirds of the original length by incorporating baseline covariates in this way.

Accounting for correlation and compliance in cluster randomized trials.

This paper discusses causal inference with survival data from cluster randomized trials. It is argued that cluster randomization carries the potential for post-randomization exposures which involve differentially selective compliance between treatment arms, even for an all or nothing exposure at the individual level. Structural models can be employed to account for post-randomization exposures, but should not ignore clustering. We show how marginal modelling and random effects models allow to adapt structural estimators to account for clustering. Our findings are illustrated with data from a vitamin A trial for the prevention of infant mortality in the rural plains of Nepal.

Vitamin A and infant mortality: beyond intention-to-treat in a randomized trial.

This paper investigates the effect of one dose of vitamin A on subsequent 4 month mortality in children under 6 months of age in a randomized, double-blind placebo-controlled community trial in Nepal. An earlier published intention-to-treat analysis showed no benefit, but ignored the information on actual receipt of treatment. Structural failure time models (Robins and Tsiatis, '91) use randomization based inference and incorporate compliance information which is possibly selective. The data presented here offer some new challenges for this approach: ward-based randomization induces correlation between survival outcomes; and the actual receipt of vitamin A dose is not always recorded. To tackle the problem of the clustered survival data we consider a robust version of the structural parameter vector estimator. A sensitivity analysis captures boundaries for the estimated structural parameters reflecting a range of potential values of children whose true receipt of treatment is unknown. The analysis suggests that the effect of vitamin A was beneficial in the beginning of the trial but towards the end of the trial there was a reversal of this effect.