Methodological considerations for observational coding of eating and feeding behaviors in children and their families_2017.pdf
datasetposted on 17.04.2019 by Megan Pesch, Julie Lumeng
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
Background: Behavioral 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.
Methods: When 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.
Conclusions: Behavioral 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.