Evidence map›Paper›PMID 26712758›Full record

ArticleSensors (Basel, Switzerland)2015

Sedentary Behaviour Profiling of Office Workers: A Sensitivity Analysis of Sedentary Cut-Points.

Simone T Boerema, Gerard B Essink, Thijs M Tönis, Lex van Velsen, Hermie J Hermens

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Physical Behavior Profiles in Chronic Cancer-Related Fatigue.International journal of behavioral medicine · 2018
    Article
  6. Review
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

5 authors.

Simone T BoeremaTelemedicine Group, Roessingh Research and Development, P.O. Box 310, 7500 AH, Enschede, The Netherlands. s.boerema@rrd.nl.
Gerard B EssinkTelemedicine Group, Roessingh Research and Development, P.O. Box 310, 7500 AH, Enschede, The Netherlands. g.b.essink@student.utwente.nl.
Thijs M TönisTelemedicine Group, Roessingh Research and Development, P.O. Box 310, 7500 AH, Enschede, The Netherlands. t.tonis@rrd.nl.
Lex van VelsenTelemedicine Group, Roessingh Research and Development, P.O. Box 310, 7500 AH, Enschede, The Netherlands. l.vanvelsen@rrd.nl.
Hermie J HermensTelemedicine Group, Roessingh Research and Development, P.O. Box 310, 7500 AH, Enschede, The Netherlands. h.hermens@rrd.nl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Measuring sedentary behaviour and physical activity with wearable sensors provides detailed information on activity patterns and can serve health interventions. At the basis of activity analysis stands the ability to distinguish sedentary from active time. As there is no consensus regarding the optimal cut-point for classifying sedentary behaviour, we studied the consequences of using different cut-points for this type of analysis. We conducted a battery of sitting and walking activities with 14 office workers, wearing the Promove 3D activity sensor to determine the optimal cut-point (in counts per minute (m·s(-2))) for classifying sedentary behaviour. Then, 27 office workers wore the sensor for five days. We evaluated the sensitivity of five sedentary pattern measures for various sedentary cut-points and found an optimal cut-point for sedentary behaviour of 1660 × 10(-3) m·s(-2). Total sedentary time was not sensitive to cut-point changes within ±10% of this optimal cut-point; other sedentary pattern measures were not sensitive to changes within the ±20% interval. The results from studies analyzing sedentary patterns, using different cut-points, can be compared within these boundaries. Furthermore, commercial, hip-worn activity trackers can implement feedback and interventions on sedentary behaviour patterns, using these cut-points.

Indexed as

Sedentary BehaviorWorkplaceActigraphyAdultFemaleHuman ActivitiesHumansMaleMiddle AgedMonitoring, AmbulatoryReference StandardsYoung Adultaccelerometeractivity patternactivity sensorcut-pointfield triallaboratory trialoffice workerssedentary behavior

Identifiers

PMID26712758
PMCPMC4732055

What OpenQuestion holds

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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.