Evidence map›Paper›PMID 31924171›Full record

ArticleBMC medical research methodology2020

Validity and bias on the online active Australia survey: activity level and participant factors associated with self-report bias.

Rachel G Curtis, Timothy Olds, Ronald Plotnikoff, Corneel Vandelanotte, Sarah Edney, Jillian Ryan, Carol Maher

Open access · goldAbstract readValidation Study
In one paragraph

Article in BMC medical research methodology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

11 citing papers in PubMed, 32 citations in OpenAlex.

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  6. Impact of Long Working Hours on Mental Health: Evidence from China.International journal of environmental research and public health · 2023
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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

7 authors at 3 institutions in 1 country.

Rachel G CurtisAlliance for Research in Exercise, Nutrition, and Activity, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia. Rachel.Curtis@unisa.edu.au.ORCID 0000-0002-1341-7804
Timothy OldsAlliance for Research in Exercise, Nutrition, and Activity, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia.
Ronald PlotnikoffPriority Research Centre for Physical Activity and Nutrition, The University of Newcastle, Callaghan, NSW, 2308, Australia.
Corneel VandelanottePhysical Activity Research Group, School of Health, Medical and Applied Sciences, Central Queensland University, Rockhampton, QLD, 4702, Australia.
Sarah EdneyAlliance for Research in Exercise, Nutrition, and Activity, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia.
Jillian RyanAlliance for Research in Exercise, Nutrition, and Activity, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia.
Carol MaherAlliance for Research in Exercise, Nutrition, and Activity, University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia.
University of South Australia · AUCentral Queensland University · AUUniversity of Newcastle Australia · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis study examined the criterion validity of the online Active Australia Survey, using accelerometry as the criterion, and whether self-report bias was related to level of activity, age, sex, education, body mass index and health-related quality of life.

methodsThe online Active Australia Survey was validated against the GENEActiv accelerometer as a direct measure of activity. Participants (n = 344) wore an accelerometer for 7 days, completed the Active Australia Survey, and reported their health and demographic characteristics. A Spearman's rank coefficient examined the association between minutes of moderate-to-vigorous physical activity recorded on the Active Australia Survey and GENEActiv accelerometer. A Bland-Altman plot illustrated self-report bias (the difference between methods). Linear mixed effects modelling was used to examine whether participant factors predicted self-report bias.

resultsThe association between moderate-to-vigorous physical activity reported on the online Active Australia Survey and accelerometer was significant (r

conclusionsThe online Active Australia Survey showed limited criterion validity against accelerometry. Self-report bias was related to activity level and mental health-related quality of life. Caution is recommended when interpreting studies using the online Active Australia Survey.

Indexed as

ExerciseHealth BehaviorSedentary BehaviorSelf ReportAccelerometryAdolescentAdultAgedAustraliaFemaleHumansMaleMiddle AgedPsychometricsReproducibility of ResultsSmartphoneAccelerometryPhysical activityPsychometricsQuestionnaire

Identifiers

PMID31924171
PMCPMC6954551
OpenAlexW3000626072

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.