Sensitivity analyses play a crucial role in assessing the robustness of the findings or conclusions based on primary analyses of data in clinical trials. They are a critical way to assess the impact, effect or influence of key assumptions or variations—such as different methods of analysis, definitions of outcomes, protocol deviations, missing data, and outliers—on the overall conclusions of a study. The current paper is the second in a series of tutorial-type manuscripts intended to discuss and clarify aspects related to key methodological issues in the design and analysis of clinical trials. In this paper we will provide a detailed exploration of the key aspects of sensitivity analyses including: 1) what sensitivity analyses are, why they are needed, and how often they are used in practice; 2) the different types of sensitivity analyses that one can do, with examples from the literature; 3) some frequently asked questions about sensitivity analyses; and 4) some suggestions on how to report the results of sensitivity analyses in clinical trials. When reporting on a clinical trial, we recommend including planned or posthoc sensitivity analyses, the corresponding rationale and results along with the discussion of the consequences of these analyses on the overall findings of the study.

Cognitive behavioural therapy (CBT) is a widely used treatment for depression. However, limited resource availability poses several barriers to patients seeking access to care, including lengthy wait times and geographical limitations. This has prompted health care services to introduce electronically delivered CBT (eCBT) to facilitate access. Although previous reviews have compared the effects of eCBT to face-to-face CBT, there is an overall lack of adequately powered and up-to-date evidence in the literature to provide a reliable comparison between the two modes of administration. The purpose of this study is to evaluate the effects of eCBT compared to face-to-face CBT through a systematic review of the literature. To be eligible for this review, studies needed to be randomized controlled trials evaluating the clinical effectiveness of any form of eCBT compared to face-to-face CBT. These encompassed studies evaluating a wide range of outcomes including severity of symptoms, adverse outcomes, clinically relevant outcomes, global functionality, participant satisfaction, quality of life, and affordability. There were no restrictions on participant age or sex. We searched MEDLINE, EMBASE, Psych Info, Cochrane CENTRAL and CINAHL databases from inception to February 20th, 2020 using a comprehensive search strategy. All stages of literature screening and data extraction were completed independently in duplicate. Data extraction and risk of bias analyses, including GRADE ratings, were conducted on studies meeting inclusion criteria. Qualitative measures are reported in a narrative summary. We pooled quantitative data in meta-analyses to provide an estimated summary effect. This review adheres to PRISMA reporting guidelines. In total, we included 17 studies in our analyses. Our results demonstrated that eCBT was more effective than face-to-face CBT at reducing depression symptom severity (Standardized mean difference [SMD]: −1.73; 95% confidence interval [CI]: −2.72, −0.74; GRADE: moderate quality of evidence). There were no significant differences between the two interventions on participant satisfaction (SMD 0.13 95%; CI −0.32, 0.59; GRADE: low quality of evidence). One RCT reported eCBT to be less costly than face-to-face CBT (GRADE: low quality of evidence). Results did not differ when stratified by subgroups such as participant age and study location. Although we found eCBT to have moderate evidence of effectiveness in reducing symptoms of depression, high heterogeneity among studies precludes definitive conclusions for all outcomes. With the current reliance and accessibility of technology to increasing number of people worldwide, serious consideration in utilizing technology should be given to maximize accessibility for depression treatments. Our results found eCBT is at least as effective as face to face CBT, thus eCBT should be offered if preferred by patients and therapists. This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

Whether used for pain management or recreation, opioids have a number of adverse effects including hormonal imbalances. These imbalances have been reported to primarily involve testosterone and affect both males and females to the point of interfering with successful treatment and recovery. We conducted a systematic review and meta-analysis to determine the extent that opioids affect testosterone levels in both men and women, which may be relevant to improved treatment outcomes for opioid dependence and for pain management. We searched PubMed, EMBASE, PsycINFO, and CINAHL for relevant articles and included studies that examined testosterone levels in men and women while on opioids. Data collection was completed in duplicate. Seventeen studies with 2769 participants (800 opioid users and 1969 controls) fulfilled the review inclusion criteria; 10 studies were cross-sectional and seven were cohort studies. Results showed a significant difference in mean testosterone level in men with opioid use compared to controls (MD=-164.78; 95% CI: -245.47, -84.08; p<0.0001). Methadone did not affect testosterone differently than other opioids. Testosterone levels in women were not affected by opioids. Generalizability of results was limited due to high heterogeneity among studies and overall low quality of evidence. Our findings demonstrated that testosterone level is suppressed in men with regular opioid use regardless of opioid type. We found that opioids affect testosterone levels differently in men than women. This suggests that opioids, including methadone, may have different endocrine disruption mechanisms in men and women, which should be considered when treating opioid dependence.

Introduction: Despite its efficacy and widespread use, methadone maintenance treatment (MMT) continues to be widely stigmatized. Reducing the stigma surrounding MMT will help improve the accessibility, retention, and treatment outcomes in MMT. Methods: Semi-structured interviews were conducted with 18 adults undergoing MMT. Thematic content analysis was used to identify overarching themes. Results: In total, 78% of participants reported having experienced stigma surrounding MMT. Common stereotypes associated with MMT patients included the following: methadone as a way to get high, incompetence, untrustworthiness, lack of willpower, and heroin junkies. Participants reported that stigma resulted in lower self-esteem; relationship conflicts; reluctance to initiate, access, or continue MMT; and distrust toward the health care system. Public awareness campaigns, education of health care workers, family therapy, and community meetings were cited as potential stigma-reduction strategies. Discussion and Conclusion: Stigma is a widespread and serious issue that adversely affects MMT patients’ quality of life and treatment. More efforts are needed to combat MMT-related stigma.

Background: Light therapy is a known treatment for patients with seasonal affective disorder. However, the efficacy of light therapy in treating patients with non-seasonal depression remains inconclusive.Aims: To provide the current state of evidence for efficacy of light therapy in non-seasonal depressive disorders.Method: Systematic review of randomised controlled trials (RCTs) was conducted by searching MEDLINE, EMBASE, PsycINFO, CINAHL, and CENTRAL from their inception to September 2015. Study selection, data abstraction and risk of bias assessment were independently conducted in duplicate. Meta-analyses were performed to provide a summary statistic for the included RCTs. The reporting of this systematic review follows the PRISMA guidelines.Results: A meta-analysis including 881 participants from 20 RCTs demonstrated a beneficial effect of light therapy in non-seasonal depression (standardised mean difference in depression score −0.41 (95% CI −0.64 to −0.18)). This estimate was associated with significant heterogeneity (I²=60%,P=0.0003) that was not sufficiently explained by subgroup analyses. There was also high risk of bias in the included trials limiting the study interpretation.Conclusions: The overall quality of evidence is poor due to high risk of bias and inconsistency. However, considering that light therapy has minimal side-effects and our meta-analysis demonstrated that a significant proportion of patients achieved a clinically significant response, light therapy may be effective for patients with non-seasonal depression and can be a helpful additional therapeutic intervention for depression.