A Quantitative Evaluation of Thin Slice Sampling for Parent–Infant Interactions.
Behavioural coding is time-intensive and laborious. Thin slice sampling provides an alternative approach, aiming to alleviate the coding burden. However, little is understood about whether different behaviours coded over thin slices are comparable to those same behaviours over entire interactions. T...
| Publicado en: | Journal of Nonverbal Behavior Vol. 47; no. 2; pp. 117 - 211 |
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| Autores principales: | , , , , , , , , , , , |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Jun2023
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=163555634&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 163555634 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 01915886 JNV jtl: Journal of Nonverbal Behavior issn: 01915886 maglogo: N pubinfo: dt: Jun2023 vid: 47 iid: 2 pid: 237 pub: Springer Nature artinfo: ui: 163555634 10.1007/s10919-022-00420-7 ppf: 117 ppct: 94 formats: fmt: – @attributes: type: T – @attributes: type: P size: 1.5MB tig: atl: A Quantitative Evaluation of Thin Slice Sampling for Parent–Infant Interactions. aug: au: Burgess, Romana Costantini, Ilaria Bornstein, Marc H. Campbell, Amy Cordero Vega, Miguel A. Culpin, Iryna Dingsdale, Hayley John, Rosalind M. Kennedy, Mari-Rose Tyson, Hannah R. Pearson, Rebecca M. Nabney, Ian affil: Digital Health Engineering Group, Faculty of Engineering, Merchant Venturers Building, University of Bristol, Bristol, UK Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Bristol, UK Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD, USA Biomedicine Division, School of Biosciences, Cardiff University, Cardiff, UK Centre for Ethics in Medicine, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK Bristol NIHR Biomedical Research Centre, Bristol, UK MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK su: Nonverbal communication Quantitative research Mother-infant relationship Parent-infant relationships Parenting Father-infant relationship Descriptive statistics Verbal behavior Infant psychology Prediction models Medical coding Video recording Probability theory sug: subj: Nonverbal communication Quantitative research Mother-infant relationship Parent-infant relationships Parenting Father-infant relationship Descriptive statistics Verbal behavior Infant psychology Prediction models Medical coding Video recording Probability theory keyword: ALSPAC Behavioural coding Grown in wales Markov chain processes Parent–infant interactions ALSPAC Behavioural coding Grown in wales Markov chain processes Parent–infant interactions ab: Behavioural coding is time-intensive and laborious. Thin slice sampling provides an alternative approach, aiming to alleviate the coding burden. However, little is understood about whether different behaviours coded over thin slices are comparable to those same behaviours over entire interactions. To provide quantitative evidence for the value of thin slice sampling for a variety of behaviours. We used data from three populations of parent-infant interactions: mother-infant dyads from the Grown in Wales (GiW) cohort (n = 31), mother-infant dyads from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort (n = 14), and father-infant dyads from the ALSPAC cohort (n = 11). Mean infant ages were 13.8, 6.8, and 7.1 months, respectively. Interactions were coded using a comprehensive coding scheme comprised of 11–14 behavioural groups, with each group comprised of 3–13 mutually exclusive behaviours. We calculated frequencies of verbal and non-verbal behaviours, transition matrices (probability of transitioning between behaviours, e.g., from looking at the infant to looking at a distraction) and stationary distributions (long-term proportion of time spent within behavioural states) for 15 thin slices of full, 5-min interactions. Measures drawn from the full sessions were compared to those from 1-, 2-, 3- and 4-min slices. We identified many instances where thin slice sampling (i.e., < 5 min) was an appropriate coding method, although we observed significant variation across different behaviours. We thereby used this information to provide detailed guidance to researchers regarding how long to code for each behaviour depending on their objectives. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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