Evidence map›Paper›PMID 35300730›Full record

ArticleJournal of pharmaceutical policy and practice2022

Feeling the burn in the era of COVID-19: cross-cultural adaptation and validation of the Arabic version of the Copenhagen Burnout Inventory among community pharmacists.

Dalal Youssef, Linda Abou-Abbas, Janet Youssef

Open access · goldAbstract read
In one paragraph

Article in Journal of pharmaceutical policy and practice, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
4.5field-weighted citation impact, top 6% of its field
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

6 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Article
  3. Survey on the Mental Health of Dispensing Pharmacists in the Auvergne-Rhône-Alpes Region (France).International journal of environmental research and public health · 2023
    Observational
  4. Article
  5. Psychometric Properties and Factor Structure of the Slovak Version of the Copenhagen Burnout Inventory.International journal of environmental research and public health · 2022
    Article
  6. 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

3 authors at 2 institutions in 2 countries.

Dalal YoussefBordeaux Research Center for Population Health, Institut de santé publique, d'épidémiologie et de développement (ISPED), Bordeaux University, Bordeaux, France. dyoussef@moph.gov.lb.ORCID http://orcid.org/0000-0003-3085-6849
Linda Abou-AbbasNeuroscience Research Center, Faculty of Medical Sciences, Lebanese University, Beirut, Lebanon.ORCID http://orcid.org/0000-0001-9185-3831
Janet YoussefAl Zahraa Hospital University Medical Center, Beirut, Lebanon.
Lebanese University · LBMinistry of Public Health · LB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCommunity pharmacists (CPs) are one of the frontline healthcare workers (HCWs) working diligently to provide much-needed services during the COVID-19 pandemic. Burnout was one of the detrimental outcomes of the pandemic on the mental health of Lebanese CPs. To assess the extent of this syndrome among Lebanese CPs, a psychometrically reliable and valid tool is needed.

objectivesThis study aimed to validate the Arabic version of the Copenhagen Burnout Inventory (CBI-A) for use in the assessment of burnout among CPs.

methodsA web-based cross-sectional study was conducted among Lebanese CPs over February 2021. Data were collected using an anonymous Arabic self-administered questionnaire that includes information on socio-demographic characteristics, work-related variables, in addition to the measurements: the CBI which includes personal, work-related, and patient-related dimensions of burnout, and the hospital anxiety and depression scale. Data were analyzed using SPSS and Amos software. Exploratory factor analysis and confirmatory factor analysis were performed to explore the factorial structure and to measure model fit. Cronbach's alpha was used to assess internal consistency. The criterion validity of the CBI was assessed. Multivariable linear regression analyses were used to explore the association between different aspects of burnout and mental health outcomes such as depression and anxiety.

resultsThe CBI-A showed high internal consistency with Cronbach's alphas varied from 0.774 to 0.902 and a low floor and ceiling effect (1-9%). As for the CBI-A construct validity, the exploratory factor analysis showed three factors with good factor loadings and explained 72.17% of the variance. The confirmatory analysis supported the three-factorial structure of the CBI that presented a good overall fit based on the goodness-of-fit indices. Ad hoc modifications to the model were introduced based on the modification indices to achieve a satisfactory fit by allowing one covariate error between one pair of items within the personal burnout domain. All of the 19 items were kept in the construct since they showed a good factorial weight. The CBI-A is associated with burnout-related factors in expected directions, including extensive working hours, sleeping hours, and job satisfaction, indicating, therefore, the criterion validity of the tool. CBI subscales were also found positively associated with mental health outcomes such as depression and anxiety demonstrating, in turn, a predictive validity.

conclusionThis study provides evidence for the validity and reliability of the Arabic version of CBI as an adequate tool for assessing burnout among CPs. Such an instrument could be useful for assessing such syndrome among other healthcare workers.

Indexed as

Arabic versionCommunity pharmacistsCopenhagen Burnout InventoryPsychometricValidation

Identifiers

PMID35300730
PMCPMC8929240
OpenAlexW4220678703

What OpenQuestion holds

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LicenceCC BY
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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.