Evidence map›Paper›PMID 29246234›Full record

ReviewThe international journal of behavioral nutrition and physical activity2017

Methodological considerations for observational coding of eating and feeding behaviors in children and their families.

Megan H Pesch, Julie C Lumeng

Open access · goldAbstract readReview
In one paragraph

Review in The international journal of behavioral nutrition and physical activity, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 2 pooled it
6.2field-weighted citation impact, top 3% 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

34 citing papers in PubMed, 2 syntheses or guidelines pooled it, 66 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Fathers' Presence Makes a Difference During Children's Evening Meals.Hispanic journal of behavioral sciences · 2026
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  14. Automated Quantification of Eye Tics Using Computer Vision and Deep Learning Techniques.Movement disorders : official journal of the Movement Disorder Society · 2024
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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

2 authors at 1 institution in 1 country.

Megan H PeschDivision of Developmental and Behavioral Pediatrics, Department of Pediatrics and Communicable Diseases, University of Michigan, 1540 E. Hospital Drive, SPC 5718, Ann Arbor, MI, 48109-5718, USA. pesch@umich.edu.
Julie C LumengDivision of Developmental and Behavioral Pediatrics, Department of Pediatrics and Communicable Diseases, University of Michigan, 300 North Ingalls Building, SPC 0406, Ann Arbor, MI, 48109-0406, USA.
University of Michigan–Ann Arbor · US

Funding

Regional Pilot And Feasibility Study Grants ProgramP30DK020572 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Mehboob A Hussain · 2013 to 2026
$24.3M
American Heart Association (US) 17FTF33630183NIDDK NIH HHS P30 DK020572
6 · The paper itself

Abstract

backgroundBehavioral coding of videotaped eating and feeding interactions can provide researchers with rich observational data and unique insights into eating behaviors, food intake, food selection as well as interpersonal and mealtime dynamics of children and their families. Unlike self-report measures of eating and feeding practices, the coding of videotaped eating and feeding behaviors can allow for the quantitative and qualitative examinations of behaviors and practices that participants may not self-report. While this methodology is increasingly more common, behavioral coding protocols and methodology are not widely shared in the literature. This has important implications for validity and reliability of coding schemes across settings. Additional guidance on how to design, implement, code and analyze videotaped eating and feeding behaviors could contribute to advancing the science of behavioral nutrition. The objectives of this narrative review are to review methodology for the design, operationalization, and coding of videotaped behavioral eating and feeding data in children and their families, and to highlight best practices.

methodsWhen capturing eating and feeding behaviors through analysis of videotapes, it is important for the study and coding to be hypothesis driven. Study design considerations include how to best capture the target behaviors through selection of a controlled experimental laboratory environment versus home mealtime, duration of video recording, number of observations to achieve reliability across eating episodes, as well as technical issues in video recording and sound quality. Study design must also take into account plans for coding the target behaviors, which may include behavior frequency, duration, categorization or qualitative descriptors. Coding scheme creation and refinement occur through an iterative process. Reliability between coders can be challenging to achieve but is paramount to the scientific rigor of the methodology. Analysis approach is dependent on the how data were coded and collapsed.

conclusionsBehavioral coding of videotaped eating and feeding behaviors can capture rich data "in-vivo" that is otherwise unobtainable from self-report measures. While data collection and coding are time-intensive the data yielded can be extremely valuable. Additional sharing of methodology and coding schemes around eating and feeding behaviors could advance the science and field.

Indexed as

Clinical CodingHealth BehaviorChildChild BehaviorChoice BehaviorEatingFeeding BehaviorFood PreferencesHumansMealsObservational Studies as TopicPilot ProjectsReproducibility of ResultsSelf ReportVideotape RecordingBehaviorChildEatingFeedingObservational analysisParentVideo

Identifiers

PMID29246234
PMCPMC5732463
OpenAlexW2772140706

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.