The Feasibility and Acceptability of Personalised Smart-Messaging To Enhance Remote Mindfulness-Based Cognitive Therapy for Recurrent Depression
Sam Malins, Cosmin Manolescu, Tim Sweeney, Kate Feenan
PsyArXiv March 25, 2026 preprint DOI: 10.31234/osf.io/2rmeu_v2 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Cohort study Qualitative |
|---|---|
| Sample size | 28 |
| Population | People with recurrent depression attending remote Mindfulness-Based Cognitive Therapy across three sites |
| Interventions | Personalised smart-messaging remote Mindfulness-Based Cognitive Therapy (rMBCT) |
| Topics | Depression Meditation |
| Key findings | Personalised smart-messaging as an adjunct to remote MBCT was taken up by 11 of 12 offered participants (92%) and was associated with significantly greater improvement in depression and functioning, with trends toward greater improvement in generalised anxiety and lower dropout. Therapists reported it enhanced therapy and outcomes but added significant administrative burden. |
Abstract
Mindfulness-Based Cognitive Therapy is a group psychological therapy that prevents relapse amongst people with recurrent depression. However, many people who attend MBCT do not fully benefit. This study assessed the feasibility, acceptability and initial clinical utility of personalised smart-messaging as an adjunct to remote Mindfulness-Based Cognitive Therapy (rMBCT) for recurrent depression to reduce dropout and improve outcomes.This cohort study compared 28 participants across three sites attending rMBCT, 12 participants were offered smart-messaging and 16 were not. Personalised smart-messaging protocols: 1) reminded participants of their personal motivations for attending rMBCT that were elicited at the initial assessment consultation 2) Prompted them to complete home practice relevant to each session and 3) Sent them their own advice for relapse prevention after group completion, using personal reminders that participants wrote in the final sessions of the group. Smart-messaging uptake, dropout, clinical outcomes, and qualitative experiences were evaluated.Eleven (92%) participants offered smart-messaging took it up. Participants attending rMBCT with smart-messaging reported significantly greater improvement in depression and functioning, with trends of greater improvement in generalised anxiety and lower dropout. Therapists reported that they felt the smart-messaging intervention enhanced rMBCT and improved outcomes but also described the significant administrative burden it added to setup.Personalised smart-messaging may be feasible and acceptable as an adjunct to rMBCT for recurrent depression for both patients and therapists. The addition of personalised smart-messaging has potential to improve clinical outcomes and reduce dropout, but there is an additional burden on therapists to incorporate it.
Comparable studies
Other observational and cohort studies on depression, most cited first.
| Study | Year | Design | Participants |
|---|---|---|---|
| Metacognitive awareness and prevention of relapse in depression: Empirical evidence. Residually depressed patients and nondepressed controls; recovered depressed patients | 2002 | Observational cohort with intervention components | |
| Psilocybin for treatment-resistant depression: fMRI-measured brain mechanisms. Patients with treatment-resistant depression | 2017 | Observational cohort | n = 19 |
| Antidepressant effects of a single dose of ayahuasca in patients with recurrent depression: a preliminary report Patients with a depressive disorder | 2015 | Observational study | |
| Concomitant BDNF and sleep slow wave changes indicate ketamine-induced plasticity in major depressive disorder Patients with treatment-resistant major depressive disorder | 2012 | Observational cohort | n = 30 |
| Altered peripheral immune profiles in treatment-resistant depression: response to ketamine and prediction of treatment outcome Healthy controls and actively depressed patients with treatment-resistant depression... | 2017 | Observational cohort | n = 59 |