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Helping people to help themselves : the development and evaluation of a non-clinical, peer-supported eTherapy model in the management of anxiety and depression in adults

Lidbetter, N

Authors

N Lidbetter



Contributors

Abstract

eTherapy interventions have widened access to evidence-based psychological therapies, particularly Cognitive Behavioural Therapy (CBT) since their introduction to primary care mental health services over a decade ago. Whilst the effectiveness of eTherapy programmes has been established and, to a degree, the acceptability of eTherapy has been strong, there are a paucity of studies undertaken in real-world settings. Even more scarce is research on service delivery models that utilise non-clinicians and instead, individuals with lived experience of mental health conditions, in the provision of support.
This portfolio of seven published works and thirteen supporting publications - two books, one book chapter, eight papers and two articles - makes a unique contribution to eTherapy literature by detailing the development and evaluation of a non-clinical, peer-supported model of eTherapy in the treatment of adults experiencing anxiety and depression in a real-world setting.
Collectively, the publications provide a body of knowledge that suggest that this novel model of pragmatic eTherapy service delivery is effective, acceptable, and capable of generating results equivalent to those generated by low intensity Improving Access to Psychological Therapy (IAPT) services. Furthermore, this model supports the widening of access to services and provision of an evidence-based, much-needed treatment for those affected by anxiety and depression, as well as for clients affected by sleep and dual diagnosis issues.

Citation

Lidbetter, N. Helping people to help themselves : the development and evaluation of a non-clinical, peer-supported eTherapy model in the management of anxiety and depression in adults. (Thesis). University of Salford

Thesis Type Thesis
Deposit Date Jan 4, 2022
Publicly Available Date Jan 4, 2022
Award Date May 7, 2021

Files

Nicola Mary Lidbetter Thesis Final Redacted Version 27.12.2021.pdf (3.7 Mb)
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Redacted version




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