Evidence map›Paper›PMID 37077178›Full record

ArticleGlobal advances in integrative medicine and health

Preventing Depression Relapse: A Qualitative Study on the Need for Additional Structured Support Following Mindfulness-Based Cognitive Therapy.

Chelsea J Siwik, Shelley R Adler, Patricia J Moran, Willem Kuyken, Zindel Segal, Jennifer Felder, Stuart Eisendrath, Frederick M Hecht

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Global advances in integrative medicine and health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Chelsea J SiwikOsher Center for Integrative Health, University of California, San Francisco, San Francisco, CA, USA.
Shelley R AdlerOsher Center for Integrative Health, University of California, San Francisco, San Francisco, CA, USA.
Patricia J MoranOsher Center for Integrative Health, University of California, San Francisco, San Francisco, CA, USA.
Willem KuykenOxford Mindfulness Centre, University of Oxford, Oxford, UK.ORCID https://orcid.org/0000-0002-8596-5252
Zindel SegalDepartment of Psychological Clinical Science, University of Toronto, Scarborough, Toronto, ON, Canada.
Jennifer FelderOsher Center for Integrative Health, University of California, San Francisco, San Francisco, CA, USA.ORCID https://orcid.org/0000-0002-4598-7836
Stuart EisendrathDepartment of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
Frederick M HechtOsher Center for Integrative Health, University of California, San Francisco, San Francisco, CA, USA.ORCID https://orcid.org/0000-0002-5782-1171

Funding

Training Researchers in Clinical Integrative Medicine (TRIM) - NOSI supplementT32AT003997 · NCCIH · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI SHELLEY R ADLER, MARIA T CHAO · 2007 to 2026
$6.6M
Mentoring and Research in Integrative MedicineK24AT007827 · NCCIH · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HECHT, FREDERICK M · 2013 to 2022
$1.8M
Optimizing a Mindfulness-Based Intervention for Poor Sleep Quality During PregnancyK23AT009896 · NCCIH · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FELDER, JENNIFER NICOLE · 2018 to 2022
$889k
NCCIH NIH HHS K23 AT009896NCCIH NIH HHS K24 AT007827NCCIH NIH HHS L30 AT011624NCCIH NIH HHS T32 AT003997
6 · The paper itself

Abstract

Background: Mindfulness-based cognitive therapy (MBCT) is an effective group intervention for reducing rates of depression relapse. However, about one-third of graduates experience relapse within 1 year of completing the course. Objective: The current study aimed to explore the need and strategies for additional support following the MBCT course. Methods: We conducted 4 focus groups via videoconferencing, two with MBCT graduates (n = 9 in each group) and two with MBCT teachers (n = 9; n = 7). We explored participants' perceived need for and interest in MBCT programming beyond the core program and ways to optimize the long-term benefits of MBCT. We conducted thematic content analysis to identify patterns in transcribed focus group sessions. Through an iterative process, multiple researchers developed a codebook, independently coded the transcripts, and derived themes. Results: Participants said the MBCT course is highly valued and was, for some, "life changing." Participants also described challenges with maintaining MBCT practices and sustaining benefits after the course despite using a range of approaches (ie, community and alumni-based meditation groups, mobile applications, taking the MBCT course a second time) to maintain mindfulness and meditative practice. One participant described finishing the MBCT course as feeling like "falling off a cliff." Both MBCT graduates and teachers were enthusiastic about the prospect of additional support following MBCT in the form of a maintenance program. Conclusion: Some MBCT graduates experienced difficulty maintaining practice of the skills they learned in the course. This is not surprising given that maintained behavior change is challenging and difficulty sustaining mindfulness practice after a mindfulness-based intervention is not specific to MBCT. Participants shared that additional support following the MBCT program is desired. Therefore, creating an MBCT maintenance program may help MBCT graduates maintain practice and sustain benefits longer-term, thereby decreasing risk for depression relapse.

Indexed as

depression relapsemaintenance programmindfulness-based cognitive therapy

Identifiers

PMID37077178
PMCPMC10108404

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.