Cited by 11Health Systems, Economic Evaluations, Quality of LifeMindfulness and Compassion InterventionsMental Health Treatment and Access

Behavioral activation with mindfulness in treating subthreshold depression in primary care: A cost-utility and cost-effectiveness analysis alongside a randomized controlled trial

Sun, Yuying, Wong, Samuel Y.S., Zhang, Dexing, Chen, Cynthia H.J., Yip, Benjamin H.K.·2021·Journal of Psychiatric Research

Abstract

This study aimed to assess the cost-utility and cost-effectiveness of group-based behavioral activation with mindfulness (BAM) versus care as usual (CAU) for treating subthreshold depression in primary care. Adults aged 18 years or older with subthreshold depression were randomized into two arms and were followed up for 12 months. BAM group was provided with eight 2-h weekly treatment by trained allied healthcare workers. CAU group could access to usual medical care but did not receive extra interventions. The health service cost in the past 12 months was self-reported by the participants. Quality-adjusted Life Years (QALYs) and clinical outcome (incidence of major depressive disorder progression) were measured. Willingness-to-pay ratio for cost-utility analysis (CUA) and cost-effectiveness analysis (CEA) was US$50,000 per QALY and US$20,000 per prevented major depression case, respectively. These ratios were used in the cost-effective acceptability curve analyses to estimate the probability of cost-effectiveness of the estimated incremental cost effectiveness ratios (ICER) of BAM versus CAU. A total of 115 and 116 participants were included in the BAM group and CAU respectively. The estimated CUA ICER was US5,979 per QALY and had a probability of 0.93 that BAM was cost-effective when compared to CAU. Furthermore, when compared to CAU, BAM was cost-effective in preventing progression of major depression: the estimated CEA ICER was US$1046 per preventable case of major progression with a probability of 0.99 to be cost-effective. Group-based BAM is considered as a cost-effective alternative treatment for treating subthreshold depression by preventing major depressive disorder.

Integrity signals

Registry

Crossref · 10.1016/j.jpsychires.2020.10.006

Cites

28 of 28 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

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?

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Sun, Y., Wong, S. Y. S., Zhang, D., Chen, C. H. J., & Yip, B. H. K.
Affiliations
  • Chinese University of Hong Kong (HK)
  • National University of Singapore (SG)
Corresponding author
Yip, Benjamin H.K.
Venue
Journal of Psychiatric Research
Publisher
Elsevier BV
Published
2021-01
Volume
132
Pages
111-115
ISSN
0022-3956 (ISSN-L)
OpenAlex
W3093182004
Cited by
11
References
28
Citations by year
2025: 5 · 2024: 1 · 2022: 3 · 2021: 2
FWCI
1.06
Type
journal article
Language
en
Open access
closed
Locations
  • Journal of Psychiatric Research (publishedVersion)
  • PubMed (publishedVersion)
  • National University of Singapore (submittedVersion)
Funders
Health and Medical Research Fund (HMRF 11120501)
Topics
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
  • Social Sciences › Psychology › Clinical Psychology › Mindfulness and Compassion Interventions
  • Social Sciences › Psychology › Social Psychology › Mental Health Treatment and Access
Keywords
subthreshold depression, cost-utility analysis, cost-effectiveness, primary care, quality-adjusted life years, acceptability curves
MeSH terms
Adolescent, Adult, Cost-Benefit Analysis, Depression, Major Depressive Disorder, Humans, Primary Health Care, Quality of Life, Quality-Adjusted Life Years, Mindfulness

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