Evidence map›Paper›PMID 28391233›Full record

SynthesisBMJ open2017

TAxonomy of Self-reported Sedentary behaviour Tools (TASST) framework for development, comparison and evaluation of self-report tools: content analysis and systematic review.

P M Dall, E H Coulter, C F Fitzsimons, D A Skelton, Sfm Chastin, Seniors USP Team

Abstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in BMJ open, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 6 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

31 citing papers in PubMed, 6 syntheses or guidelines pooled it.

  1. Pooled it
  2. Interventions for reducing sedentary behaviour in people with stroke.The Cochrane database of systematic reviews · 2021
    Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Article
  8. Article
  9. Sedentary time at school and work in Canada.Canadian journal of public health = Revue canadienne de sante publique · 2024
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Alternatives for Measuring Sitting Accumulation in Workplace Surveys.Journal of occupational and environmental medicine · 2021
    Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Worldwide surveillance of self-reported sitting time: a scoping review.The international journal of behavioral nutrition and physical activity · 2020
    Article
  20. Sedentary behaviour surveillance in Canada: trends, challenges and lessons learned.The international journal of behavioral nutrition and physical activity · 2020
    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

6 authors.

P M DallInstitute for Applied Health Research, Glasgow Caledonian University, Glasgow, UK.
E H CoulterDepartment of Nursing and Healthcare, Glasgow University, Glasgow, UK.
C F FitzsimonsSport, Physical Education and Health Sciences Institute, Edinburgh University, Edinburgh, UK.
D A SkeltonInstitute for Applied Health Research, Glasgow Caledonian University, Glasgow, UK.
Sfm ChastinInstitute for Applied Health Research, Glasgow Caledonian University, Glasgow, UK.
Seniors USP Team

Funding

Medical Research Council MR/K00414X/1Medical Research Council MR/K025023/1
6 · The paper itself

Abstract

objectiveSedentary behaviour (SB) has distinct deleterious health outcomes, yet there is no consensus on best practice for measurement. This study aimed to identify the optimal self-report tool for population surveillance of SB, using a systematic framework.

designA framework, TAxonomy of Self-reported Sedentary behaviour Tools (TASST), consisting of four domains (type of assessment, recall period, temporal unit and assessment period), was developed based on a systematic inventory of existing tools. The inventory was achieved through a systematic review of studies reporting SB and tracing back to the original description. A systematic review of the accuracy and sensitivity to change of these tools was then mapped against TASST domains. DATA SOURCES: Systematic searches were conducted via EBSCO, reference lists and expert opinion. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: The inventory included tools measuring SB in adults that could be self-completed at one sitting, and excluded tools measuring SB in specific populations or contexts. The systematic review included studies reporting on the accuracy against an objective measure of SB and/or sensitivity to change of a tool in the inventory.

resultsThe systematic review initially identified 32 distinct tools (141 questions), which were used to develop the TASST framework. Twenty-two studies evaluated accuracy and/or sensitivity to change representing only eight taxa. Assessing SB as a sum of behaviours and using a previous day recall were the most promising features of existing tools. Accuracy was poor for all existing tools, with underestimation and overestimation of SB. There was a lack of evidence about sensitivity to change.

conclusionsDespite the limited evidence, mapping existing SB tools onto the TASST framework has enabled informed recommendations to be made about the most promising features for a surveillance tool, identified aspects on which future research and development of SB surveillance tools should focus. TRIAL REGISTRATION NUMBER: International prospective register of systematic reviews (PROPSPERO)/CRD42014009851.

Indexed as

Public HealthSedentary BehaviorBehavior TherapyBenchmarkingHealth PromotionHumansPopulation SurveillanceSelf Reportmeasurementpopulation surveillancesedentary behavioursittingvalidation

Identifiers

PMID28391233
PMCPMC5775464

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.