Data

Data for: The Acceptability and Repeatability of Spirometry Testing: A Systematic Review & Meta-Analysis

James Cook University
Barnes, Liane ; Pyne, Nadine ; Jones, Anne
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25903/rwy1-3x45&rft.title= Data for: The Acceptability and Repeatability of Spirometry Testing: A Systematic Review & Meta-Analysis&rft.identifier=10.25903/rwy1-3x45&rft.publisher=James Cook University&rft.description=Description: Chronic respiratory diseases (CRDs) decrease lung function by causing changes to the airways and other structures of the lungs. Lung function is objectively measured using spirometry and high-test quality maximises its diagnostic utility. The aims of this systematic review were to determine the overall percentage of acceptability and repeatability (AR) across a broad range of study designs and participant cohorts in the published literature and to determine which factors influence this component of spirometry quality using a generalised linear model. This data record contains: 1x .xlsx file containing extracted data parameters and an explanation of the codes used 1x .cvs file containing codes used for data analysis Software/equipment used to create/collect the data: Microsoft Excel for Microsoft 365 Systematic Review Accelerator (SRA) tools (Clark et al., 2020) Software/equipment used to manipulate/analyse the data: SPSS Statistics v30 (IBM, Denmark) Risk of Bias Summary tables and plots were generated using the Risk-of-bias VISualization (robvis) tool (McGuinness & Higgins, 2021) &rft.creator=Barnes, Liane &rft.creator=Pyne, Nadine &rft.creator=Jones, Anne &rft.date=2025&rft.relation=https://doi.org/10.1111/resp.14458&rft.coverage=Townsville, Queensland, Australia&rft_rights=&rft_rights=CC BY-NC 4.0: Attribution-Noncommercial 4.0 International http://creativecommons.org/licenses/by-nc/4.0&rft_subject=Spirometry&rft_subject=Quality Assessment&rft_subject=Chronic Respiratory Diseases&rft_subject=Respiratory diseases&rft_subject=Cardiovascular medicine and haematology&rft_subject=BIOMEDICAL AND CLINICAL SCIENCES&rft_subject=Cardiology (incl. cardiovascular diseases)&rft_subject=Evaluation of health outcomes&rft_subject=Evaluation of health and support services&rft_subject=HEALTH&rft_subject=Expanding knowledge in the biomedical and clinical sciences&rft_subject=Expanding knowledge&rft_subject=EXPANDING KNOWLEDGE&rft.type=dataset&rft.language=English Access the data

Licence & Rights:

Non-Commercial Licence view details
CC-BY-NC

CC BY-NC 4.0: Attribution-Noncommercial 4.0 International
http://creativecommons.org/licenses/by-nc/4.0

Access:

Open view details

Open: free access under license

Full description

Description: Chronic respiratory diseases (CRDs) decrease lung function by causing changes to the airways and other structures of the lungs. Lung function is objectively measured using spirometry and high-test quality maximises its diagnostic utility. The aims of this systematic review were to determine the overall percentage of acceptability and repeatability (AR) across a broad range of study designs and participant cohorts in the published literature and to determine which factors influence this component of spirometry quality using a generalised linear model.

This data record contains:

  • 1x .xlsx file containing extracted data parameters and an explanation of the codes used
  • 1x .cvs file containing codes used for data analysis

Software/equipment used to create/collect the data:

  • Microsoft Excel for Microsoft 365
  • Systematic Review Accelerator (SRA) tools (Clark et al., 2020)

Software/equipment used to manipulate/analyse the data:

  • SPSS Statistics v30 (IBM, Denmark)
  • Risk of Bias Summary tables and plots were generated using the Risk-of-bias VISualization (robvis) tool (McGuinness & Higgins, 2021)

Created: 2025-02-19

Data time period: 03 03 2022 to 31 01 2025

This dataset is part of a larger collection

Click to explore relationships graph

Spatial Coverage And Location

text: Townsville, Queensland, Australia

Identifiers
  • DOI : 10.25903/RWY1-3X45
  • Local : researchdata.jcu.edu.au//published/a4148b90eccf11ef8ba5bddfe268d013