Poster #145 - Maternal Prenatal Distress and Predictability in Early Caregiving Behavior. Role of High Effortful Control

• In Event: 2-055 - Poster Session 06
  In Poster Session: PS 06 Section - Parenting & Parent-Child Relationships

Integrative Statement

Background: There is strong evidence showing that maternal mental health and the good quality of early caregiving behavior are crucial factors affecting healthy child development, especially regarding regulation of emotion and behavior (Glover, 2014, Korja, 2017, Sharp, 2015). Davis et al. (2017) have recently suggested predictability in caregiving behavior to be one key element affecting the developing brain of the infant. Very little is yet known, however, of the specific parental characteristics responsible for predictable caregiving behavior. Recent parenting research has suggested that besides maternal mental health, maternal self-regulatory capacity is one important factor in beneficial parenting (Bridgett, 2015; Feldman, 2009).

Aims: Aims of the current study were to explore how early maternal psychological distress and self-regulation capacity are related to the predictability of maternal caregiving behavior. On the basis of previous research, we expected that high prenatal distress symptoms and poor maternal self-regulation are associated with low predictability of caregiving behavior.

Method: Participants (n=110 mother-infant pairs) were part of a Focus Cohort sample drawn from the FinnBrain Birth Cohort Study: 36 mother reporting high levels of prenatal distress (depressive, general anxiety, and/or pregnancy-related anxiety symptoms) and their infants and 74 reporting low levels of distress. The following questionnaires were used: EPDS, SCL and PRAQ (14, 24 and 34 gwk and 6 months postpartum). Mother-infant interaction was video-recorded at 8 months of child’s age in a 20-minute free-play situation. Maternal sensory signals were analyzed with the Maternal Sensory Behavior Coding Scheme System (Davis, 2017). In the coding system, the amount and timing of the maternal sensory signals (auditory, visual, tactile) were coded. Entropy rate was calculated to characterize predictability of maternal sensory signals. Mothers’ effortful control was assessed using self-reported effortful control scale and subscales activation control, attentional control and inhibitory control from the Adult Temperament Questionnaire (Evans & Rothbart, 2007), when the child was 12 months of age.

Results: Correlational analysis showed that lower predictability in maternal care correlated negatively with maternal effortful control (r = -.38, p < .05) and activation control subscale (r = -.46, p < .01) only in mothers with high prenatal distress but not in mothers with low prenatal distress. Maternal prenatal distress symptoms did not correlate with predictability in maternal care. Based on the significant zero-order correlations, linear regression models predicting predictability in caregiving behavior were conducted. Findings of the regression models (R2 = .055, p=0.53) showed that the interaction between prenatal distress and lower activation control predicted lower predictability in maternal care, when the postnatal symptoms were covaried (b=1.671, p < . 05), see picture 1. The relation with effortful control was not significant when the postnatal symptoms were covaried.

Conclusions: According to the results mothers’ low activation control was associated with low predictability of caregiving behavior in mothers who had high distress symptoms prenatally. That is, lower activation control may be a risk factor for lower quality of caregiving behavior but only among mothers who experience higher levels of distress. Early interventions should consider these findings.

Authors

• Eeva Holmberg, The FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku; Department of Psychology, University of Turku
  Presenting Author

• Riikka Korja, University of Turku, Finland
  Non-Presenting Author

• Marjukka Pajulo, University of Turku, Finland
  Non-Presenting Author

• Elysia Poggi Davis, University of Denver, University of California-Irvine
  Non-Presenting Author

• Saara Nolvi, University of Turku, Finland
  Non-Presenting Author

• Eeva-Leena Kataja, University of Turku, Finland
  Non-Presenting Author

• Eija Sinerva, FinnBrain Birth Cohort Study, Institute of Clinical Medicine, University of Turku, Finland
  Non-Presenting Author

• Linnea Karlsson, University of Turku, Finland
  Non-Presenting Author

• Hasse Karlsson, University of Turku, Finland
  Non-Presenting Author