Letter to the Editor
Online social media: New data, new horizons in psychosis treatment

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Big data, big thinking

The authors make excellent points in relation to the opportunity for mobile in real time evaluations to overcome the limitations of traditional assessment procedures through collecting rich, idiographic, ecologically valid data. This information can be used to both unravel contextual factors surrounding the occurrence of psychotic symptoms and guide in real time interventions. Looking forward, these new technologies can be used to collect large-scale longitudinal datasets, significantly

Online social media: a new paradigm for interventions in psychosis

Online social media interventions provide a new paradigm in psychosis treatment. Online social networking can be used to counteract social isolation and disadvantage — a risk factor for developing psychosis and poor symptomatic and functional outcomes (Norman et al., 2005, Norman et al., 2012), enhance engagement with online interventions — a key challenge in the field (Eysenbach, 2005), and improve uptake and acquisition of therapeutic strategies. The integration of online social media and

Rigour in evaluation, rigour in development

As the authors pointed out, technologies can indeed outpace the timelines for traditional randomised controlled trials. However, the field needs to guard against prematurely embracing innovation without rigorously evaluating potential risk and treatment effectiveness. The WHO Global eHealth Evaluation Meeting's Call to Action (Bellagio, September 2011) consensus statement stated that “to improve health and reduce health inequalities, rigorous evaluation of eHealth is necessary to generate

The science of developing online interventions

The design process of new online and mobile interventions is pivotal in ensuring high quality interventions that are relevant, engaging and effective. The development process needs to follow well-established procedures of user-centred design (Alvarez-Jimenez et al., 2014). Ongoing development needs to be informed by usage data as well as participants feedback. In order to meet the need for innovation and ongoing engagement we require robust, testable theoretical models of engagement and novel

Contributors

MA-J wrote the first draft of the manuscript. MA-C, CG-B, S-B, PD-M and JF-G critically revised the manuscript. All authors contributed to and have approved the final manuscript.

Conflict of interest

The authors report no additional financial or other affiliation relevant to the subject of this article.

Acknowledgements

A/Prof Alvarez-Jimenez is supported by the CR Roper Fellowship, Faculty of Medicine, Dentistry, and Health Science, the University of Melbourne and a Career Development Fellowship (APP1082934) by the National Health and Medical Research Council (NHMRC). No funding body had any involvement in any aspect of the study or manuscript. Dr Bendall is supported by an early career research fellowship from the NHMRC (APP1036425). Drs M.A. Alcazar-Corcoles and C. González-Blanch were supported by the

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