Introduction Gay men with prostate cancer (GMPCa) may have differential health-related quality of life (HRQOL) and sexual health outcomes than heterosexual men with prostate cancer (PCa), but existing information is based on clinical experience and small studies. Aims Our goals were to: (i) describe HRQOL and examine changes in sexual functioning and bother; (ii) explore the psychosocial aspects of sexual health after PCa; and (iii) examine whether there were significant differences on HRQOL and sexual behavior between GMPCa and published norms. Methods A convenience sample of GMPCa completed validated disease-specific and general measures of HRQOL, ejaculatory function and bother, fear of cancer recurrence, and satisfaction with prostate cancer care. Measures of self-efficacy for PCa management, illness intrusiveness, and disclosure of sexual orientation were also completed. Where possible, scores were compared against published norms. Main Outcome Measures Main outcome measures were self-reported sexual functioning and bother on the Expanded Prostate Cancer Index. Results Compared with norms, GMPCa reported significantly worse functioning and more severe bother scores on urinary, bowel, hormonal symptom scales (Ps < 0.015–0.0001), worse mental health functioning (P < 0.0001), greater fear of cancer recurrence (P < 0.0001), and were more dissatisfied with their PCa medical care. However, GMPCa reported better sexual functioning scores (P < 0.002) compared with norms. Many of the observed differences met criteria for clinical significance. Physical functioning HRQOL and sexual bother scores were similar to that of published samples. GMPCa tended to be more “out” about their sexual orientation than other samples of gay men. Conclusions GMPCa reported substantial changes in sexual functioning after PCa treatment. They also reported significantly worse disease-specific and general HRQOL, fear of recurrence, and were less satisfied with their medical care than other published PCa samples. Sexual health providers must have an awareness of the unique functional and HRQOL differences between gay and heterosexual men with PCa.

No abstract

Control conditions are the primary methodology used to reduce threats to internal validity in randomized controlled trials (RCTs). This meta-analysis examined the effects of control arm design and implementation on outcomes in RCTs examining psychological treatments for depression. A search of MEDLINE, PsycINFO, and EMBASE identified all RCTs evaluating psychological treatments for depression published through June 2009. Data were analyzed using mixedeffects models. One hundred twenty-five trials were identified yielding 188 comparisons. Outcomes varied significantly depending control condition design (p<0.0001). Significantly smaller effect sizes were seen when control arms used manualization (p=0.006), therapist training (p=0.002), therapist supervision (p=0.009), and treatment fidelity monitoring (p=0.003). There were no significant effects for differences in therapist experience, level of expertise in the treatment delivered, or nesting vs. crossing therapists in treatment arms. These findings demonstrate the substantial effect that decisions regarding control arm definition and implementation can have on RCT outcomes. KeywordsMeta-analysis, Depression, Control conditions, Randomized controlled trial design, Methodology Over the past half century, evidence has accumulated to support a number of psychological and behavioral interventions for mental health and medical conditions [6]. The backbone of treatment outcome research is the randomized controlled trial (RCT), a planned experiment designed to test the efficacy or effectiveness of an intervention. Although many aspects of RCT methodology have received considerable attention [2], until recently, surprisingly little attention has been paid to how to select and implement control conditions. The aim of this paper is to examine the effects of the design and implementation of control conditions on RCT outcomes for the treatment of depression using meta-analysis. These results will be interpreted in light of recent efforts to formulate a framework to support decisions regarding the selection, design, and implementation of control conditions [20].RCTs can vary in their aim, from explanatory trials evaluating efficacy or effectiveness under ideal conditions, to more pragmatic trials that evaluate the intervention under conditions found in clinical settings [13,28]. In either case, the experimental treatment is always determined relative to a control condition. Consequently, what an RCT reveals about the effectiveness of the experimental treatment inherently depends as much on the control condition as on the experimental treatment. One of the principal reasons for using a control condition is to eliminate alternative causal explanations. In statistical terms, the purpose of a control condition is to filter out the variance due to factors that are not specific to the experimental intervention, leaving only the variance due specifically

No abstract

No abstract