Evidence map›Paper›PMID 41661832›Full record

ArticlePLOS mental health2024

Behavioural activation activities for employees in the Chinese culture: A workshop.

Sijin Sun, Yao Xiao, Zheyuan Zhang, Celine Mougenot, Nick Glozier, Rafael A Calvo

Abstract read
In one paragraph

Article in PLOS mental health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Sijin SunImperial College London, London, United Kingdom.ORCID https://orcid.org/0000-0001-6276-4741
Yao XiaoIndependent Psychologist, London, United Kingdom.
Zheyuan ZhangImperial College London, London, United Kingdom.
Celine MougenotImperial College London, London, United Kingdom.
Nick GlozierThe University of Sydney, Sydney, Australia.
Rafael A CalvoImperial College London, London, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Behavioral Activation Therapy (BAT) is widely used in Western countries, and digital interventions based on BAT are also increasingly common. This study explored how BAT can be adapted for Chinese employees. Through twelve co-design workshops conducted online, a total of 46 Chinese employees actively participated in the process of defining positive activities for behavioural activation therapy. Using Hofstede's cultural dimensional theory as a framework and considering the traditional influence of Confucianism and the dynamic nature of China's contemporary socio-cultural transformation, we identified and examined culturally sensitive and controversial activities that emerged during the study. Our findings indicate that Chinese participants, when compared to their western counterparts, generally displayed less favourable attitudes towards activities such as extreme sports, religion, charitable work, family or after-work social activities. Additionally, they demonstrated less willingness to express emotions openly, provide constructive upward feedback, or seek assistance from mental health experts. Our research indicates that the implementation of behavioural activation activities, as validated in Western literature and classified into three layers in our study-general, workplace-related, and mental health-related-needs to be carefully adapted to align with the current Chinese cultural and societal context, this includes recommending leisure activities that are lighter and less risky, provide cultural sensitive advisory that facilitate effective workplace communication, and consider offering mental health self-help knowledge toolkits.

Identifiers

PMID41661832
PMCPMC12798598

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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.