Prince, Ciptadi, Tao, Rozga, Martin, Rehg, Messinger
Infant
attachment is a critical indicator of healthy infant social-emotional
functioning, which is typically measured using the gold-standard Strange
Situation Procedure (SSP). However, expert-based attachment classifications
from the SSP are time-intensive (with respect both to expert training and
rating), and do not provide an objective, continuous record of infant
behavior. To continuously quantify predictors of key attachment behaviors and
dimensions, multimodal movement and audio data were collected during the SSP.
Forty-nine 1-year-olds and their mothers participated in the SSP and were
tracked in three-dimensional space using five synchronized Kinect sensors;
LENA recordings were used to quantify crying duration. Theoretically-informed
multimodal measures of attachment-related behavior (e.g., dyadic contact
duration, infant velocity of approach toward the mother, and infant crying)
were used to predict expert rating scales and dimensional summaries of
attachment outcomes. Stepwise regressions identified sets of multimodal
objective measures that were significant predictors of eight of nine of the
expert ratings of infant attachment behaviors in the SSP’s two reunions.
These multimodal measures predicted approximately half of the variance in the
summary approach/avoidance and resistance/disorganization attachment
dimensions. Incorporating all objective measures as predictors regardless of
significance levels, predicted individual ratings within an average of one
point on the original Likert scales. The results indicate that relatively
inexpensive Kinect and LENA sensors can be harnessed to quantify attachment
behavior in a key assessment protocol, suggesting the promise of objective
measurement to understanding infant-parent interaction.