Optimal sampling strategies for characterizing behavior and affect from ambulatory audio recordings.
Year: 2020
Type: article
Abstract: Advances in mobile and wearable technologies mean it is now feasible to record hours to days of participant behavior in its naturalistic context, a great boon for psychologists interested in family processes and development. While automated activity recognition algorithms exist for a limited set of behaviors, time-consuming human annotations are still required to robustly characterize the vast majority of behavioral and affective markers of interest. This report is the first to date which systematically tests the efficacy of different sampling strategies for characterizing behavior from audio recordings to provide practical guidelines for researchers. Using continuous audio recordings of the daily lives of 11 preschool-aged children, we compared sampling techniques to determine the most accurate and efficient approach. Results suggest that sampling both low and high frequency verbal and overt behaviors is best if samples are short in duration, systematically rather than randomly selected, and sampled to cover at least 12.5% of recordings. Implications for assessment of real-world behavior are discussed. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
Source: Journal of Family Psychology
DOI: 10.1037/fam0000654
Language: English
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: hybrid
Awards: INTERPERSONAL DISCLOSURE PROCESSES AND HEALTH, High-density markers of mother-infant bio-behavioral activity "in the wild": Developing a mobile-sensing paradigm to examine transmission of mental health risks, Leveraging Social Media Data and Machine Learning to Optimize Treatment Paradigms for Youth with Schizophrenia, G3339951203, Tracking and Understanding the Effects of Transformative Events in People’s Lives
OpenAlex ID: W3015813658