This randomized controlled trial investigated the efficacy of a stand-alone virtual reality exposure intervention comprising verbal interaction with virtual humans to target heterogeneous social fears in participants with social anxiety disorder. Sixty participants (Mage = 36.9 years; 63.3% women) diagnosed with social anxiety disorder were randomly assigned to individual virtual reality exposure therapy (VRET), individual in vivo exposure therapy (iVET), or waiting-list. Multilevel regression analyses revealed that both treatment groups improved from pre-to postassessment on social anxiety symptoms, speech duration, perceived stress, and avoidant personality disorder related beliefs when compared to the waiting-list. Participants receiving iVET, but not VRET, improved on fear of negative evaluation, speech performance, general anxiety, depression, and quality of life relative to those on waiting-list. The iVET condition was further superior to the VRET condition regarding decreases in social anxiety symptoms at post- and follow-up assessments, and avoidant personality disorder related beliefs at follow-up. At follow-up, all improvements were significant for iVET. For VRET, only the effect for perceived stress was significant. VRET containing extensive verbal interaction without any cognitive components can effectively reduce complaints of generalized social anxiety disorder. Future technological and psychological improvements of virtual social interactions might further enhance the efficacy of VRET for social anxiety disorder.

BackgroundThis study is one of the first randomized controlled trials investigating cognitive behavioral therapy for insomnia (CBT-I) delivered by a fully automated mobile phone app. Such an app can potentially increase the accessibility of insomnia treatment for the 10% of people who have insomnia.ObjectiveThe objective of our study was to investigate the efficacy of CBT-I delivered via the Sleepcare mobile phone app, compared with a waitlist control group, in a randomized controlled trial.MethodsWe recruited participants in the Netherlands with relatively mild insomnia disorder. After answering an online pretest questionnaire, they were randomly assigned to the app (n=74) or the waitlist condition (n=77). The app packaged a sleep diary, a relaxation exercise, sleep restriction exercise, and sleep hygiene and education. The app was fully automated and adjusted itself to a participant’s progress. Program duration was 6 to 7 weeks, after which participants received posttest measurements and a 3-month follow-up. The participants in the waitlist condition received the app after they completed the posttest questionnaire. The measurements consisted of questionnaires and 7-day online diaries. The questionnaires measured insomnia severity, dysfunctional beliefs about sleep, and anxiety and depression symptoms. The diary measured sleep variables such as sleep efficiency. We performed multilevel analyses to study the interaction effects between time and condition.ResultsThe results showed significant interaction effects (P<.01) favoring the app condition on the primary outcome measures of insomnia severity (d=–0.66) and sleep efficiency (d=0.71). Overall, these improvements were also retained in a 3-month follow-up.ConclusionsThis study demonstrated the efficacy of a fully automated mobile phone app in the treatment of relatively mild insomnia. The effects were in the range of what is found for Web-based treatment in general. This supports the applicability of such technical tools in the treatment of insomnia. Future work should examine the generalizability to a more diverse population. Furthermore, the separate components of such an app should be investigated. It remains to be seen how this app can best be integrated into the current health regimens.Trial RegistrationNetherlands Trial Register: NTR5560; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=5560 (Archived by WebCite at http://www.webcitation.org/6noLaUdJ4)

In virtual reality exposure therapy (VRET) for anxiety disorders, sense of presence in the virtual environment is considered the principal mechanism that enables anxiety to be felt. Existing studies on the relation between sense of presence and level of anxiety, however, have yielded mixed results on the correlation between the two. In this meta-analysis, we reviewed publications on VRET for anxiety that included self-reported presence and anxiety. The comprehensive search of the literature identified 33 publications with a total of 1196 participants. The correlation between self-reported sense of presence and anxiety was extracted and meta-analyzed. Potential moderators such as technology characteristics, sample characteristics including age, gender and clinical status, disorder characteristics and study design characteristics such as measurements were also examined. The random effects analysis showed a medium effect size for the correlation between sense of presence and anxiety (r = .28; 95% CI: 0.18–0.38). Moderation analyses revealed that the effect size of the correlation differed across different anxiety disorders, with a large effect size for fear of animals (r = .50; 95% CI: 0.30–0.66) and a no to small effect size for social anxiety disorder (r = .001; 95% CI: −0.19–0.19). Further, the correlation between anxiety and presence was stronger in studies with participants who met criteria for an anxiety disorder than in studies with a non-clinical population. Trackers with six degrees of freedom and displays with a larger field of view resulted in higher effect sizes, compared to trackers with three degrees of freedom and displays with a smaller field of view. In addition, no difference in effect size was found for the type of presence measurement and the type of anxiety measurement. This meta-analysis confirms the positive relation between sense of presence and anxiety and demonstrates that this relation can be affected by various moderating factors.

PurposeTo describe the development of a survey instrument designed to measure consumer perceptions of the broadband adoption within the UK households.Design/methodology/approachA survey research approach was employed to achieve overall aim and following three objectives of this research: to identify initial items that may help to explain the broadband adoption behaviour and determine them employing an exploratory survey approach; to confirm the representativeness of items to a particular construct domain employing content validity approach; and finally, to test the instrument in order to confirm the reliability of items and construct validity.FindingsThe final outcome of the instrument development process that culminated from the confirmatory study was a parsimonious, 39‐item instrument, consisting of ten scales, all with acceptable levels of content validity, reliability and construct validity.Practical implicationsThe developed instrument is relevant to both academic and practitioner communities who hold a particular interest in the study and management of broadband adoption from the household consumer perspective.Originality/valueThe most conspicuous contribution of the paper is to provide a reliable instrument that is fundamental to measure the household consumer's perceptions of adopting broadband internet.

There is much research that shows people's mood can affect their activities. This paper argues that this also applies to programmers, especially their debugging. Literature-based framework is presented linking programming with various cognitive activities as well as linking cognitive activities with moods. Further, the effect of mood on debugging was tested in two experiments. In the first experiment, programmers (n = 72) saw short movie clips selected for their ability to provoke specific moods. Afterward, they completed a debugging test. Results showed the video clips had a significant effect on programmers' debugging performance; especially, there was a significant difference after watching low-and high-arousalevoking video clips. In the second experiment, programmers' mood was manipulated by asking participants (n = 19) to dry run algorithms for at least 16 min. They performed some physical exercises before continuing dry running algorithms again. The results showed a significant increase in arousal and valence that coincided with an improvement in programmers' task performance after the physical exercises. Together, this suggests that programmers' moods influence some programming tasks such as debugging.