Peter Musiat1, Lars Hoffmann, Ulrike Schmidt. 1. King's College London, Institute of Psychiatry, Section of Eating Disorders, PO-Box 059, De Crespigny Park, London SE15 3RH, UK. peter.musiat@kcl.ac.uk
Abstract
BACKGROUND: Personalised feedback constitutes an important component of E- and M-mental health applications (E = electronic and M = mobile computing and communication technologies) for disease prevention and management. It can be used to increase motivation, highlight risks, change attitudes and counterbalance the lack of personal contact in computerised health interventions. Research suggests that compared with targeted or generic feedback, personalised feedback is a more effective intervention component. AIMS: To discuss challenges and options for the generation and delivery of personalised feedback in E- and M-mental health interventions. Suggestions for the development of normative, summative and ipsative feedback are provided. RESULTS: We demonstrate how information from (multiple) assessments and/or data from comparable samples can be integrated into statistically supported and user-friendly feedback without including test scores. CONCLUSION: Proposals made in this paper need to be the subject of empirical studies and should be tested in terms of their feasibility, acceptability and efficacy.
BACKGROUND: Personalised feedback constitutes an important component of E- and M-mental health applications (E = electronic and M = mobile computing and communication technologies) for disease prevention and management. It can be used to increase motivation, highlight risks, change attitudes and counterbalance the lack of personal contact in computerised health interventions. Research suggests that compared with targeted or generic feedback, personalised feedback is a more effective intervention component. AIMS: To discuss challenges and options for the generation and delivery of personalised feedback in E- and M-mental health interventions. Suggestions for the development of normative, summative and ipsative feedback are provided. RESULTS: We demonstrate how information from (multiple) assessments and/or data from comparable samples can be integrated into statistically supported and user-friendly feedback without including test scores. CONCLUSION: Proposals made in this paper need to be the subject of empirical studies and should be tested in terms of their feasibility, acceptability and efficacy.
Authors: David Roe; Liron Lapid; Vered Baloush-Kleinman; Paula Garber-Epstein; Miriam Isolde Gornemann; Marc Gelkopf Journal: Community Ment Health J Date: 2016-06-20
Authors: Ruth Spence; Amanda Bunn; Stephen Nunn; Georgina M Hosang; Lisa Kagan; Helen L Fisher; Matthew Taylor; Antonia Bifulco Journal: JMIR Res Protoc Date: 2015-07-14
Authors: Si Wen; Helle Larsen; Marilisa Boffo; Raoul P P P Grasman; Thomas Pronk; Joeri B G van Wijngaarden; Reinout W Wiers Journal: JMIR Ment Health Date: 2020-05-08
Authors: Peter Musiat; Rachel Potterton; Gemma Gordon; Lucy Spencer; Michael Zeiler; Karin Waldherr; Stefanie Kuso; Martina Nitsch; Tanja Adamcik; Gudrun Wagner; Andreas Karwautz; David Daniel Ebert; Alyson Dodd; Barbara Dooley; Amy Harrison; Emma Whitt; Mark Haselgrove; Helen Sharpe; Jo Smith; Rosie Tressler; Nicholas Troop; Chantal Vinyard; Dennis Görlich; Jenny Beecham; Eva Bonin; Corinna Jacobi; Ulrike Schmidt Journal: Internet Interv Date: 2018-03-15