Cited by 3Mindfulness and Compassion InterventionsCOVID-19 and Mental HealthDigital Mental Health Interventions

The DOI matches its Crossref record.

I-mindfulness-based cognitive therapy (i-MBCT) in the treatment of COVID-19 related adjustment disorder. a RCT study with active control group

Open access
Holas, P.·2021·European Psychiatry

Abstract

Introduction: Adjustment disorder (AD) is described as a maladaptive reaction to an identifiable psychosocial stressor/s that usually emerges within a month after the onset of the stressor. With all uncertainty, fears and disorientation, it’s no surprise that many people have developed an AD linked to the sudden changes brought about by COVID-19, such as threat to life, imposed restrictions, and the associated changes. Mindfulness-based cognitive therapy (MBCT) has been found to be effective for depression and anxiety problems, little is known, however, about its efficacy for adjustment disorder. Objectives: The aim of the current research was to evaluate if 4 weeks long, modified internet-delivered MBCT can reduce symptoms of Covid-19 related AD. Methods: 438 individuals with a diagnosis of AD were recruited to take part in the study. They were randomly assigned to i-MBCT, i-progressive muscle relaxation training (i-PMR), and Waiting List (WL). Assessments with questionnaires evaluating AD (ADMN-20), depression (PHQ-9, HADS-D), and anxiety (HADS-A, GAD-7) were filled at baseline, 4-week, and 1-month post-randomization. 142 individuals completed baseline and 4 week assessment (i-MBCT, n= 34; i-PMR, n= 36 and WL, n=72). Results: We found a significant reduction in AD symptoms following the i-MBCT group, whereas no change was found in both control conditions. While a decrease in depressive and anxiety was found in both i-MBCT and i-PMR groups, the greatest reduction has been observed in i-MBCT. Conclusions: These preliminary findings suggest that i-MBCT can be an effective intervention in treating Covid-19 related AD, but more studies are needed. Disclosure: No significant relationships.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1192/j.eurpsy.2021.291

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

Sorted by citations

Metadata

Authors
Holas, P.
Affiliations
University of Warsaw (PL)
Corresponding author
Holas, P.
Venue
European Psychiatry
Published
2021-04
Volume
64
Issue
S1
Pages
S100-S100
ISSN
  • 0924-9338 (ISSN-L)
  • 1778-3585
OpenAlex
W3194247855
Cited by
3
References
0
Citations by year
2025: 1 · 2023: 2
FWCI
0.34
Type
journal article
Language
en
Open access
Locations
  • European Psychiatry (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Topics
  • Social Sciences › Psychology › Clinical Psychology › Mindfulness and Compassion Interventions
  • Social Sciences › Psychology › Clinical Psychology › COVID-19 and Mental Health
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
Keywords
online therapy, adjustment disorder, COVID-19 pandemic, progressive muscle relaxation, depression, anxiety, psychological stress, psychotherapy efficacy

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review