Evidence map›Paper›PMID 31159770›Full record

ArticleBMC public health2019

A validation study of the Eurostat harmonised European time use study (HETUS) diary using wearable technology.

Teresa Harms, Jonathan Gershuny, Aiden Doherty, Emma Thomas, Karen Milton, Charlie Foster

Open access · goldAbstract readValidation Study
In one paragraph

Article in BMC public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
3.1field-weighted citation impact, top 8% 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

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 51 citations in OpenAlex.

  1. Validity and reliability of self-reported methods for assessment of 24-h movement behaviours: a systematic review.The international journal of behavioral nutrition and physical activity · 2024
    Pooled it
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  10. Sedentary Behavior in U.S. Adults: Fall 2019.Medicine and science in sports and exercise · 2021
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  12. Observational
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  14. Feasibility Study Comparing Physical Activity Classifications from Accelerometers with Wearable Camera Data.International journal of environmental research and public health · 2020
    Article
  15. Article
  16. Work time and market integration in the original affluent society.Proceedings of the National Academy of Sciences of the United States of America · 2019
    Article
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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

6 authors at 5 institutions in 2 countries.

Teresa HarmsDepartment of Social Science, Centre for Time Use Research, University College London, 55-59 Gordon Square, London, WCH 0NU, UK. t.harms@ucl.ac.uk.
Jonathan GershunyDepartment of Social Science, Centre for Time Use Research, University College London, 55-59 Gordon Square, London, WCH 0NU, UK.
Aiden DohertyNuffield Department of Population Health, University of Oxford, Oxford, UK.
Emma ThomasMelbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.
Karen MiltonNorwich Medical School, University of East Anglia, Norwich, UK.
Charlie FosterSchool for Policy Studies, University of Bristol, Bristol, UK.
University College London · GBUniversity of Bristol · GBUniversity of East Anglia · GBUniversity of Melbourne · AUUniversity of Oxford · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe central aim was to examine the accuracy of the full range of daily activities recorded in self-report time-use diaries against data from two objective passive data collection devices (wearable camera and accelerometer) serving as criterion reference instruments. This enabled systematic checks and comparisons on the timing, sequence and duration of activities recorded from the three data sources.

methodsParticipants (n = 148) were asked to complete a single-day self-report paper time-use diary designed for use in the Harmonised European Time Use Study (HETUS), while simultaneously wearing a camera that continuously recorded images of their activities, and an accelerometer tracking physical movement. In a reconstruction interview shortly after the data collection period, participants viewed the camera images to help researchers interpret the image sequences. Of the initial 148 recruits (multi-seed snowball sample, 59% women, aged 18-91, 43% > 40) 131 returned usable diary and camera records (of whom 124 also provided a usable whole-day accelerometer record. We compare time allocation estimates from the diary and camera records, and also match the diary and camera records to the simultaneously recorded accelerometer vector magnitudes.

resultsThe data were examined at three analytic levels: aggregate, individual diarist and timeslot. The most important finding is that the estimates of mean daily time devoted to 8 of the 10 main activities differ by < 10% in the camera and diary records. The single case of major divergence (eating) can be explained by a systematic difference between the procedures followed by the self-reporting diarist and the observer coding the camera records. There are more substantial differences at the respondent level, paired t-tests showing significant differences in time spent in the 4/10 categories. 45% of all variation in the accelerometer vector magnitudes in the timeslots is explained by camera and diary records. Detailed activity classifications perform much better than METs as predictors of actigraphy.

conclusionsThe comparison of the diary with the camera and accelerometer records strongly supports using diary methodology for studying the full range of daily activity, particularly at aggregate levels. Accelerometer data could be combined with diary measures to improve estimation of METs equivalents for various types of active and sedentary behaviour.

Indexed as

Time and Motion StudiesAccelerometryActigraphyActivities of Daily LivingAdolescentAdultAgedAged, 80 and overFemaleHuman ActivitiesHumansMaleMiddle AgedReproducibility of ResultsSedentary BehaviorSelf ReportAccelerometerData calibrationPhysical activityTime-use diaryWearable camera

Identifiers

PMID31159770
PMCPMC6546612
OpenAlexW2949022559

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.