Evidence map›Paper›PMID 33611737›Full record

ArticleChild psychiatry and human development2022

Dyadic Analysis of a Self-report Physical Activity Measure for Adult-Youth Dyads.

Zachary J Kunicki, Kendra K Kattelmann, Melissa D Olfert, Lisa Franzen-Castle, Sarah E Colby, Douglas R Mathews, Adrienne A White

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In one paragraph

Article in Child psychiatry and human development, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact, top 98% 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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 3 citations in OpenAlex.

  1. Pooled it
  2. 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

7 authors at 6 institutions in 1 country.

Zachary J KunickiDepartment of Psychiatry and Human Behavior, Brown University, 345 Blackstone Boulevard, Box G-BH, Providence, RI, 02096, USA. zachary_kunicki@brown.edu.ORCID 0000-0002-3466-7589
Kendra K KattelmannDepartment of Health and Nutritional Sciences, South Dakota State University, Box 2203, Brookings, SD, SWG 443, USA.
Melissa D OlfertDivision of Animal and Nutritional Sciences, Davis College of Agriculture, Natural Resources, and Design, West Virginia University, G016 Agricultural Science Building, Morgantown, WV, USA.
Lisa Franzen-CastleNutrition and Health Sciences Department, University of Nebraska-Lincoln, 110 Ruth Leverton Hall, Lincoln, NE, USA.
Sarah E ColbyDepartment of Nutrition, University of Tennessee, Knoxville, TN, USA.
Douglas R MathewsSchool of Food and Agriculture, University of Maine, 5735 Hitchner Hall, Orono, ME, USA.
Adrienne A WhiteSchool of Food and Agriculture, University of Maine, 5735 Hitchner Hall, Orono, ME, USA.
University of Maine · USBrown University · USSouth Dakota State University · USUniversity of Nebraska–Lincoln · USUniversity of Tennessee at Knoxville · USWest Virginia University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adult physical activity levels influence youth physical activity levels, but the nature of this relationship is still unknown. Most research focusing on this topic has been conducted with accelerometers, which are ideal since self-report physical activity measures can be biased. However, self-report measures for physical activity are useful to include in studies to gather information at low-cost. The purpose of this study was to further develop a self-report adult-youth dyad measure of physical activity. This study was conducted using secondary data analysis of the physical activity measures used in an intervention on behavioral nutrition (iCook 4-H). Participants were a sample of 214 adults (M = 39.0, SD = 8.0 years) and youth (M = 9.4, SD = 0.7 years) pairs. Accelerometer data was collected for a subset of youth (n = 122). There was dependency between the adult-youth physical activity data, and a dyadic confirmatory factor analysis model showed good fit to the data and achieved metric invariance, a measure to determine if the same construct was being measured in both youth and adults. Invariance was confirmed across matched versus unmatched sex pairs and some evidence of invariance with youth accelerometer data. Based on study findings, when using self-report measures of physical activity, researchers should measure both members of the adult-youth dyad to get more accurate measurements. Further validation of these findings is needed using an objective physical activity measure, like accelerometers, with all participants and more diverse samples.

Indexed as

ExerciseAdolescentAdultHumansSelf ReportAdult-youth dyadDyadic confirmatory factor analysisPhysical activity measurementSelf-report

Identifiers

PMID33611737
OpenAlexW3130498541

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.