Association Between Socioeconomic Risk and Parenting Behaviours Association Between Socioeconomic...
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Association Between Socioeconomic Association Between Socioeconomic Risk and Parenting Behaviours Risk and Parenting Behaviours Nicole Gridley, Judy Hutchings & Helen Baker-Henningham Centre for Evidence Based Early Intervention, School of Psychology, Bangor University AIMS To investigate associations between five socioeconomic risk factors and two measures of parental language, and home stimulation outcomes, in a sample of parents living in Flying Start areas in Wales To investigate associations between multiple-risk and parental outcomes RATIONALE Socioeconomic disadvantage predicts poor parental behaviours and subsequent poor child developmental outcomes. Wales reports the highest percentage of children living in poverty (32%) relative to Britain (31%). Flying Start areas, in receipt of additional funding, are school-catchment areas with the highest proportion of children accessing free-school meals and greatest level of deprivation as defined using the Welsh Index of Mnltiple Deprivation. However, many disadvantaged families live outside these areas and are not able to receive additional services they require so it is important to identify the specific family characteristics that predict poor outcomes for children. PREDICTORS & OUTCOMES Demographic data, IT-HOME inventory scores and videos of parent-child dyads playing, that were collected as part of the Evaluation of the Incredible Years Parent-Toddler programme, were used for this study. Videos were transcribed and number of words and different words used during the final 15-minutes of free-play were calculated Demographic information provided criteria for risk factor predictors: Caregiver Education: No education beyond 16 years Marital Status: not married or cohabiting for two years Family Size*: three or more children Quality of Housing: based on bedroom standards and light, air, safety and cleanliness Employment Status: unemployed or living on benefits Parenting Outcomes: Total words Total different words Infant-Toddler HOME inventory *Family size was not correlated with any of the three outcome measures and so was excluded from the final analysis RESULTS Using stepwise linear regression employment and quality of housing independently predicted parents use of more total words, different words and better home stimulation Education beyond 17 years independently predicted better home stimulation practices (Table 1) There was a dose-response relationship between number of risk factors experienced by families and each parenting measure (Figure 1), with mothers experiencing one risk factor demonstrating poorer outcomes compared to those with no risk, but this was not significant Exposure to two or more risk factors were attributable to differences of 1 or more standard deviation TAKE HOME MESSAGE For this sample of Flying Start parents quality of housing, based on bedroom standards and housing standards, was strongly associated with poor parenting outcomes Multiple-risk was also associated with poorer parental outcomes regardless of which risk factors were present Demographic data could be used as a cost-effective method for identifying families at-risk, and in need of additional services Results are based on cross-sectional data and therefore demonstrate SAMPLE Baseline video-tapes from 81 parent-child dyads drawn from a randomised controlled trial Evaluation of the Incredible Years Parent-Toddler programme were used Parents were aged between 16 and 45 years old (M = 28.94, SD = 6.72) and were primarily mothers (n = 79). Children were aged between 12 and 36 months at recruitment. Figure 1. Association between number of risk factors and parenting measures For more information please contact Nicole. Email: [email protected] . Visit our websites: www.centreforearlyinterventionwales.co.uk http://incredible-years- wales-research.bangor.ac.uk Table 1. Predictive models of risk factors when controlling for child age and child gender *** p ≤.001 ** p ≤.01 * p ≤.05 Child age and gender entered in the first step. Employment, Marital Status, Education and Housing offered in the second step CI: confidence interval ES: effect size (regression coefficient/pooled standard deviation)
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Transcript of Association Between Socioeconomic Risk and Parenting Behaviours Association Between Socioeconomic...
Association Between Socioeconomic Risk and Association Between Socioeconomic Risk and Parenting Behaviours Parenting Behaviours Nicole Gridley, Judy Hutchings & Helen Baker-Henningham
Centre for Evidence Based Early Intervention, School of Psychology, Bangor University
AIMS
To investigate associations between five socioeconomic risk factors and two measures of parental language, and home stimulation outcomes, in a sample of parents living in Flying Start areas in Wales
To investigate associations between multiple-risk and parental outcomes
RATIONALE
Socioeconomic disadvantage predicts poor parental behaviours and subsequent poor child developmental outcomes. Wales reports the highest percentage of children living in poverty (32%) relative to Britain (31%). Flying Start areas, in receipt of additional funding, are school-catchment areas with the
highest proportion of children accessing free-school meals and greatest level of deprivation as defined using the Welsh Index of Mnltiple Deprivation. However, many disadvantaged families live outside these areas and are not able to receive additional services they require so it is important to identify the
specific family characteristics that predict poor outcomes for children.
PREDICTORS & OUTCOMES
Demographic data, IT-HOME inventory scores and videos of parent-child dyads playing, that were collected as part of the Evaluation of the Incredible Years Parent-Toddler
programme, were used for this study. Videos were transcribed and number of words and different words used during the final 15-minutes of free-play were calculated
Demographic information provided criteria for risk factor predictors:Caregiver Education: No education beyond 16 years
Marital Status: not married or cohabiting for two yearsFamily Size*: three or more children
Quality of Housing: based on bedroom standards and light, air, safety and cleanliness Employment Status: unemployed or living on benefits
Parenting Outcomes:Total words
Total different wordsInfant-Toddler HOME inventory
*Family size was not correlated with any of the three outcome measures and so was excluded from the final analysis
RESULTS
Using stepwise linear regression employment and quality of housing independently predicted parents use of more total words, different words and better home
stimulationEducation beyond 17 years independently predicted
better home stimulation practices (Table 1)There was a dose-response relationship between
number of risk factors experienced by families and each parenting measure (Figure 1), with mothers experiencing one risk factor demonstrating poorer
outcomes compared to those with no risk, but this was not significant
Exposure to two or more risk factors were attributable to differences of 1 or more standard deviation
TAKE HOME MESSAGE
For this sample of Flying Start parents quality of housing, based on bedroom standards and housing
standards, was strongly associated with poor parenting outcomes
Multiple-risk was also associated with poorer parental outcomes regardless of which risk factors were present
Demographic data could be used as a cost-effective method for identifying families at-risk, and in need of
additional servicesResults are based on cross-sectional data and therefore demonstrate correlation but do not explaining causality.
They should therefore be interpreted with caution
SAMPLE
Baseline video-tapes from 81 parent-child dyads drawn from a randomised controlled trial Evaluation of the Incredible Years Parent-Toddler programme were used
Parents were aged between 16 and 45 years old (M = 28.94, SD = 6.72) and were primarily mothers (n = 79). Children were aged between 12 and 36 months at recruitment.
Figure 1.Association between number of risk factors and parenting measures
For more information please contact Nicole. Email: [email protected].
Visit our websites: www.centreforearlyinterventionwales.co.uk http://incredible-years-wales-research.bangor.ac.uk
Table 1. Predictive models of risk factors when controlling for child age and child gender
*** p ≤.001** p ≤.01* p ≤.05Child age and gender entered in the first step. Employment, Marital Status, Education and Housing offered in the second stepCI: confidence intervalES: effect size (regression coefficient/pooled standard deviation)
