Longitudinal Changes in Perceived Collective Efficacy: A Further Analysis of the Fragile Families and Child Wellbeing Data Set

Background: While there is a significant body of literature surrounding neighborhood factors, very little of existing research offers insights into long-term influences of time-varying neighborhood structural factors on the changes of collective efficacy. There is immense value in building longitudinal relationships between neighborhood structural factors and neighborhood collective efficacy when it comes to identifying key factors and implementing community level interventions. In this study, we aimed to examine 1) the long-term trajectory of collective efficacy reported by caregivers of children from birth to age 15; 2) whether the time-varying neighborhood structural factors are associated with collective efficacy over time.

Methods: This study utilized data from Waves 1 and 3-6 in the Fragile Families and Child Wellbeing Study (N=4,898). At each wave, collective efficacy was measured by two scales: informal social control subscale and social cohesion (Sampson, 1997). Neighborhood structural factors were measured from three aspects: economic disadvantage, residential instability, and ethnic heterogeneity (Sampson & Groves, 1989). Covariates included demographic information collected at Wave 1, as well as neighborhood safety, maternal depression, and focal child movement. SPSS Version 27.0 was used for descriptive and reliability analyses, and Mplus Version 8.0 (Muthén & Muthén, 2017) was used for unconditional and conditional parallel-process latent growth models. Model-fit indices RMSEA, SRMR, and CFI were used to assess the goodness of fit of the models.

Results: This study found that neighborhood social cohesion and informal social control started off high and continued to increase over time. There was significant between-person variability in both the baseline and the growth rate of neighborhood collective efficacy. All covariances among the intercept and slope growth factors of informal social control and social cohesion were significant. Changes in neighborhood structural factors are associated with the changes of collective efficacy over time. The consistent negative estimates suggested that in general, higher economic disadvantage, residential instability, and ethnic heterogeneity were associated with lower neighborhood collective efficacy.

Conclusion: We identified changes in parents’ perception of collective efficacy from children’s birth to 15, as well as the association between neighborhood structural factors and collective efficacy over time. Our study contributed to the community and neighborhood research in two ways: first, the current study extends the knowledge of the trajectory of neighborhood collective efficacy. Knowing the changes of neighborhood collective efficacy could help understand social mobility and further intervene the influences of collective efficacy on individual’s behaviors in time. Second, revealing the time-varying effects of neighborhood structural factors on collective efficacy goes beyond the traditional cross-sectional method, which significantly promotes the knowledge foundation of neighborhood and community research. Understanding the link between structural factors and process factors over time is critical for considering the multiple ways in which neighborhood environments affect residents.