Psychological distress is common in cancer patients, however, it is often unrecognized and untreated. We aimed to identify barriers to cancer patients expressing their psychological concerns, and to recommend strategies to assist oncologists to elicit, recognize, and manage psychological distress in their patients. Medline, Psychlit, and the Cochrane databases were searched for articles relating to the detection of emotional distress in patients. Patients can provide verbal and non-verbal information about their emotional state. However, many patients may not reveal emotional issues as they believe it is not a doctor's role to help with their emotional concerns. Moreover, patients may normalize or somatize their feelings. Anxiety and depression can mimic physical symptoms of cancer or treatments, and consequently emotional distress may not be detected. Techniques such as active listening, using open questions and emotional words, responding appropriately to patients' emotional cues, and a patient-centred consulting style can assist in detection. Screening tools for psychological distress and patient question prompt sheets administered prior to the consultation can also be useful. In conclusion, the application of basic communication techniques enhances detection of patients' emotional concerns. Training oncologists in these techniques should improve the psychosocial care of cancer patients.

Background Internet interventions can easily generate objective data about program usage. Increasingly, more studies explore the relationship between usage and outcomes, but they often report different metrics of use, and the findings are mixed. Thus, current evaluations fail to demonstrate which metrics should be considered and how these metrics are related to clinically meaningful change. Objective This study aimed to explore the relationship between several usage metrics and outcomes of an internet-based intervention for depression. Methods This is a secondary analysis of data from a randomized controlled trial that examined the efficacy of an internet-based cognitive behavioral therapy for depression (Space from Depression) in an adult community sample. All participants who enrolled in the intervention, regardless of meeting the inclusion criteria, were included in this study. Space from Depression is a 7-module supported intervention, delivered over a period of 8 weeks. Different usage metrics (ie, time spent, modules and activities completed, and percentage of program completion) were automatically collected by the platform, and composite variables from these (eg, activities per session) were computed. A breakdown of the usage metrics was obtained by weeks. For the analysis, the sample was divided into those who obtained a reliable change (RC)—and those who did not. Results Data from 216 users who completed pre- and posttreatment outcomes were included in the analyses. A total of 89 participants obtained an RC, and 127 participants did not obtain an RC. Those in the RC group significantly spent more time, had more log-ins, used more tools, viewed a higher percentage of the program, and got more reviews from their supporter compared with those who did not obtain an RC. Differences between groups in usage were observed from the first week in advance across the different metrics, although they vanished over time. In the RC group, the usage was higher during the first 4 weeks, and then a significant decrease was observed. Our results showed that specific levels of platform usage, 7 hours total time spent, 15 sessions, 30 tools used, and 50% of program completion, were associated with RC. Conclusions Overall, the results showed that those individuals who obtained an RC after the intervention had higher levels of exposure to the platform. The usage during the first half of the intervention was higher, and differences between groups were observed from the first week. This study also showed specific usage levels associated with outcomes that could be tested in controlled studies to inform the minimal usage to establish adherence. These results will help to better understand how to use internet-based interventions and what optimal level of engagement can most affect outcomes. Trial Registration ISRCTN Registry ISRCTN03704676; http://www.isrctn.com/ISRCTN03704676 International Registered Report Identifier (IRRID) RR2-10.1186/1471-244X-14-147

A considerable amount of stigma-related health research has been conducted in school-aged and university students, yet few studies involved young people enrolled at further education colleges. The present study aims to investigate the role of social support on the consequences of stigma on general health and social functioning in students in Colleges of Further Education (CFE) living with chronic illness. Participants of this study (n = 55) were students in CFE in Ireland aged 18-25 years diagnosed with a chronic illness. Self-report measures were used to assess stigma, social support, social functioning and general health. Using Structural Equation Modeling (SEM) with 2000 bootstrapped samples a model was constructed and tested to answer the research questions of the study. SEM revealed a good model fit to data (χ 2 = 2.12, df = 2, p = .33). Stigma negatively predicted general health and social functioning in youth living with chronic illness. The bootstrapped mediational model showed that social support from family, friends and a significant other partially mediated the influence of stigma on social functioning but not on general health. Stigma is an important element that negatively influences aspects of well-being in young adults living with chronic illnesses. Youth that perceive their environment to be more supportive tend to have less self-stigma attitudes and better functioning. Understanding how stigma operates in students in CFE can be used to design effective interventions.

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