Feasibility of a UK community-based, eTherapy mental health service in Greater Manchester: repeated-measures and between-groups study of ‘Living Life to the Full Interactive’, ‘Sleepio’ and ‘Breaking Free Online’ at ‘Self Help Services’

Elison, Sarah; Ward, Jonathan; Williams, Chris; Espie, Colin A.; Davies, Glyn; Dugdale, Stephanie; Ragan, Kathryn; Chisnall, Leanne; Lidbetter, Nicky; Smith, Keith

doi:10.1136/bmjopen-2017-016392

Cited by 28 publications

(31 citation statements)

References 63 publications

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“…We found improvements in the PHQ-9 and WSAS scores, consistent with another IAPT study which showed that the use of the dCBTi platform resulted in improvements in the PHQ-9, GAD-7 and WSAS scores (Elison et al, 2017). dCBTi has been shown to be cost-effective in one study of guided dCBTi for insomnia to teachers, with a cost saving of US$418 achieved per patient for the employer (Thiart et al, 2016).…”

Section: Discussionsupporting

confidence: 86%

“…Of the patients who had engaged sufficiently with dCBTi to be screened to be suitable for therapy, a further one-third had dropped out before therapy. Average drop-out rates have been estimated at 24.7% in a meta-analysis (Zachariae et al, 2016) and are similar to findings from a large IAPT cohort in the UK (Elison et al, 2017). dCBTi non-completers had lower baseline PSQI scores and higher sleep efficiency, which reflect better sleep quality when compared with dCBTi completers.…”

Section: Discussionsupporting

confidence: 73%

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Real-world evaluation of digital CBT for insomnia in the primary care setting – many should not log on to doze off

Anderson

2019

tCBT

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Cognitive behaviour therapy for insomnia (CBTi) has emerged as the first-line treatment for insomnia where available. Clinical trials of digital CBTi (dCBTi) have demonstrated similar efficacy and drop-out rates to face-to-face CBTi. Most patients entering clinical trials are carefully screened to exclude other sleep disorders. This is a case series review of all those referred to a dCBTi within an 18-month time period. Those initially screened, accepted after exclusion of other sleep disorders, commencing and completing therapy were assessed to understand patient population referred from general practice in the UK. 390 patient referrals were analysed. 135 were suitable for dCBTi with a high rate of other sleep disorders detected in screening. 78 completed therapy (20.0%) and 44.9% had significant improvement in sleep outcomes, achieving ≥20% improvement in final sleep efficiency. dCBTi can be used within the UK NHS with good benefit for those who are selected as having insomnia and who then complete therapy. Many referrals are made with those likely to have distinct primary sleep disorders highlighting the need for education regarding sleep and sleep disorders prior to dCBTi therapy. Key learning aims (1) The use of unsupported digital cognitive behavioural therapy for insomnia (dCBTi) requires proper patient selection. (2) There are many insomnia mimics and also previously unrecognized sleep and psychiatric disturbances that are under-diagnosed in the primary care setting that are contraindications for unsupported dCBTi. (3) The use of a stepped care approach similar to the UK’s Improving Access to Psychological Therapies (IAPT) model using dCBTi could be feasible in the public health setting.

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Section: Discussionsupporting

confidence: 86%

Section: Discussionsupporting

confidence: 73%

Real-world evaluation of digital CBT for insomnia in the primary care setting – many should not log on to doze off

Anderson

2019

tCBT

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“…The effects sizes are typically in the moderate-to-large range. Additionally, in audits of clinical services, improvements in depression were equally seen [ 67 , 68 ], suggesting these effects hold in real-world, clinical settings. It has even been suggested that the effect of dCBT for insomnia is in the same range as CBT specifically aimed at treating depression [ 59 ].…”

Section: Evidence For Dcbt For Insomniamentioning

confidence: 99%

Digital Delivery of Cognitive Behavioral Therapy for Insomnia

Luik

Zweerde

Straten

et al. 2019

Curr Psychiatry Rep

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Purpose of Review Digital cognitive behavioral therapy (dCBT) has been available for over a decade. We reviewed the evidence that accumulated over the past 5 years and discuss the implications for introducing dCBT into standard healthcare. Recent Findings Studies have consistently supported the use of dCBT to treat insomnia. Evidence is now demonstrating large short-term effects and smaller long-term effects up to 1.5 years after treatment across populations with various co-occurring health problems. The effects also extend into a range of psychological well-being factors. Mediators and moderators have been studied to understand mechanisms and create new opportunities to enhance effectiveness and reduce dropout. Incorporating personalized guidance in dCBT may further enhance effectiveness. Summary The evidence for dCBT for insomnia is strong and suggests that dCBT is ready for application in standard healthcare. Further research, digital innovation, and development of effective implementation methods are required to ensure dCBT fulfills its potential.

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“…1 One such approach is the offer of internet-based or smartphone-based interventions within healthcare services. [1][2][3][4] In the UK, their potential is recognised in health policy documents such as England's National Health Service (NHS) Long-Term Plan (https:// www.longtermplan.nhs.uk/). The plan outlines an intention to work with the voluntary sector, developers and individuals in developing a range of apps to support mental health, with an aim to offer digitally enabled models of therapy for anxiety and depression across services by 2020.…”

mentioning

confidence: 99%

“…(2) IQR, interquartile range.Key factors for unlocking the potential of digital mental health technologies…”

mentioning

confidence: 99%

Unlocking the potential for digital mental health technologies in the UK: a Delphi exercise

et al. 2020

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Background Digitally enabled services can contribute to the support, treatment and prevention of mental health difficulties; however, questions remain regarding how we can most usefully harness such technology in primary and secondary mental healthcare settings. Aims To identify barriers and facilitators to enable the potential of digital mental health in England, Scotland, Wales and Northern Ireland. Method A three-round Delphi exercise was carried out online with 16 participants from across the four nations of the UK representing the following stakeholder groups: service providers, health professionals, policymakers, lived experience, small and medium enterprises and academics. Qualitative data were collected in the first round (80 fragments) that were then coded to produce a 26-item round-two questionnaire for participant rating. Participants were given the opportunity to reconsider their scores in light of the group responses in round three. Results Eight statements under the following five themes reached consensus with median scores between 8 and 10 (i.e. important/very important): co-production; the human element; data security; funding; and regulation. Conclusions The Delphi process allowed consensus to be achieved regarding the factors that experts consider important for harnessing technology in primary and secondary mental healthcare. Knowledge of these factors can help users and providers of mental health services negotiate how best to move forward with digitally enabled systems of care.

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Feasibility of a UK community-based, eTherapy mental health service in Greater Manchester: repeated-measures and between-groups study of ‘Living Life to the Full Interactive’, ‘Sleepio’ and ‘Breaking Free Online’ at ‘Self Help Services’

Cited by 28 publications

References 63 publications

Real-world evaluation of digital CBT for insomnia in the primary care setting – many should not log on to doze off

Real-world evaluation of digital CBT for insomnia in the primary care setting – many should not log on to doze off

Digital Delivery of Cognitive Behavioral Therapy for Insomnia

Unlocking the potential for digital mental health technologies in the UK: a Delphi exercise

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