Evidence map›Paper›PMID 29558922›Full record

Observational studyBMC public health2018

Why are some groups physically active and others not? A contrast group analysis in leisure settings.

Ansgar Thiel, Hendrik K Thedinga, Harald Barkhoff, Katrin Giel, Olesia Schweizer, Syra Thiel, Stephan Zipfel

Open access · goldAbstract readObservational Study
In one paragraph

Observational study in BMC public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.6field-weighted citation impact, top 16% 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

7 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Patterns of physical activity among nursing home residents before and during the Covid 19 pandemic-a systematic observation.European review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity · 2023
    Article
  4. Article
  5. Article
  6. 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

7 authors at 2 institutions in 2 countries.

Ansgar ThielInstitute of Sport Science, Eberhard Karls University of Tübingen, Tübingen, Germany. ansgar.thiel@uni-tuebingen.de.ORCID 0000-0001-9217-0442
Hendrik K ThedingaInstitute of Sport Science, Eberhard Karls University of Tübingen, Tübingen, Germany.
Harald BarkhoffKinesiology and Exercise Sciences, University of Hawai'i, Hilo, USA.
Katrin GielDepartment of Psychosomatic Medicine and Psychotherapy, Medical University Hospital Tübingen, Tübingen, Germany.
Olesia SchweizerInstitute of Sport Science, Eberhard Karls University of Tübingen, Tübingen, Germany.
Syra ThielInstitute of Sport Science, Eberhard Karls University of Tübingen, Tübingen, Germany.
Stephan ZipfelDepartment of Psychosomatic Medicine and Psychotherapy, Medical University Hospital Tübingen, Tübingen, Germany.
University of Tübingen · DEUniversity of Hawaii at Hilo · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThis field study aims to investigate the determinants of physical activity of particularly active and inactive groups in their leisure environments. In order to consider the context in which physical activity occurs and to investigate whether cultural settings may influence physical activity, we conducted the study at pools in different cultural environments - Hawai'i and Germany.

methodsThis study presents the quantitative data of a systematic (covert) participant observation. We recorded the physical activity of face-to-face interacting groups and analysed categories such as group size, estimated age of the group members, and verbal communication patterns. Total observation period was eight and a half months. In total, we observed 907 groups with the groups' size varying between 2 and 8 members. For the general statistics, we accessed the significance of differences regarding the degree of physical activity dependent on the target variables. To better understand activity promoting and hindering mechanisms, special attention is given to the identification of contrasting factors that characterise groups which are very active or very inactive. For this, we conducted a classification tree analysis.

resultsGeneral statistical analysis shows that, overall, the most differentiating factor regarding physical activity was the body shape of the group members. While obese groups had the lowest average activity level, groups mainly consisting of people with an athletic body shape were the most physically active. Yet, classification tree analysis reveals that obesity itself does not necessarily determine physical inactivity levels. The identification of six contrasting clusters highlights that besides the body shape several factors interact regarding a group's physical level. Such interacting factors were for example the degree of communication within the group, the gender- and age-related composition of the group, but also the equipment that had been brought to the beach/pool. Obese people were particularly inactive when they were members of frequently communicating, age-heterogeneous groups.

conclusionsOur study shows that several social factors determine the physical activity of very active and very inactive groups. In order to promote physical activity, future health initiatives should target these factors of a person's network.

Indexed as

ExerciseSedentary BehaviorSocial BehaviorAdolescentAdultAgedChildChild, PreschoolCross-Cultural ComparisonFemaleGermanyHawaiiHumansInfantInfant, NewbornLeisure ActivitiesLeisure time behaviourObesityPhysical activitySocial groups

Identifiers

PMID29558922
PMCPMC5859510
OpenAlexW2804874305

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.