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Initial child welfare screening decisions, traditionally made by an individual worker, determine if a family will receive further intervention by child protective services. A multi-disciplinary team (MDT) decision-making approach for child welfare referrals aims to provide a more thorough assessment of needs and strengths and to connect families to appropriate community-based providers. This study examined 159 child welfare referrals handled by MDTs compared to 331 referrals handled via the traditional screening approach. The study used a pseudo randomization procedure to assign referrals to the study conditions: Referrals logged on 2.5 days of the week were assigned to the treatment group; all others were assigned to the comparison group. Referrals handled by an MDT were more than four times as likely as those not handled by an MDT to be referred to community-based organizations ( OR = 4.32, p < .001). There were no statistically significant differences in families' engagement with community-based organizations or child welfare outcomes. MDTs are a promising step in the initial process of connecting families to services, although they did not affect this study's longer-term outcomes.

Background: Our previous study showed that parents with mental health problems or substance abuse are at increased risk of having children removed from the home, primarily due to caregiving deficits, neglect, and prenatal exposure to substances, not physical abuse., Objective: Using a larger sample and more rigorous analysis, the present study improves and expand upon the previous study, yielding more robust explanations for why these children are at increased risk of removal., Participants and Setting: The study uses a sample of 4070 Structured Decision Making® assessments conducted by San Francisco's Child Welfare provider involving parents reported for the first time from 2007 to 2015., Methods: Using structural equation modeling, mediation models were constructed to test the indirect effects of thirteen child safety threats on safety decision., Results: Four threats explained 95% of the effect of mental health problems on safety decision, two of which retained significance in the final model: Failure to Meet Immediate Needs (OR = 1.26, p ≤ 0.01) and Previous Maltreatment (OR = 1.24, p ≤ 0.05). Seven safety threats explained 91% of the effect of co-occurring mental health problems and substance abuse, two of which retained significance in the final model: Failure to Meet Immediate Needs (OR = 1.78, p ≤ 0.001) and Physical Harm (Drug-Exposed Infant; OR = 1.57, p ≤ 0.001)., Conclusions: As previously shown, parental mental health problems and substance abuse are not ipso facto safety threats. Rather, unmet child needs account for much of the increased risk of child removal in this population, underscoring the importance of timely resource referrals., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Background: Homelessness is a risk factor for family involvement with child welfare services (CWS). Housing interventions are promising-but reasons for this are not well understood, and housing resources could be better targeted to families at risk of increased CWS involvement., Objective: We sought to better understand the relationship between homelessness and CWS involvement and examine whether homeless shelter data could combine with CWS data to enhance intervention targeting., Participants and Setting: For 4 years, we followed 2063 families investigated by the San Francisco Human Services Agency in 2011., Methods: Matching CWS data to homeless shelter data, we fit Cox models to examine the relationship between shelter use and subsequent CWS outcomes and produced ROC curves to judge model accuracy with and without shelter information., Results: Absent CWS covariates (family demographics, CWS history, and family safety and risk), past shelter entry predicted repeat maltreatment referral (HR = 1.92, p < .001), in-home case opening (HR = 1.51, p < .05), and child removal (HR = 1.95, p < .01), but not child reunification. With CWS covariates, past shelter use no longer predicted case opening and child removal, but still predicted referral (HR = 1.58, p < .01). Shelter data did not contribute to models' predictive accuracy., Conclusions: We find mixed evidence that shelter use independently leads to CWS involvement. Housing interventions might help by addressing present housing problems and family experiences correlated with past shelter use. However, we find no evidence that data matches with shelter systems could enhance targeting., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Among children investigated for maltreatment, those with parents experiencing mental illness or substance abuse are more likely to be placed out-of-home; however, little is known about why these children are at greater risk. Using a sample of 2488 Structured Decision Making ® assessments administered in San Francisco county from 2011 to 2015, we identified a profile of safety threats that accounts for why workers are more likely to determine children of parents with mental illness and/or substance abuse unsafe in the home. Eight percent of assessments in our sample involved parents with current mental illness only and 10% had comorbid substance abuse. The odds of an unsafe determination more than doubled among parents with mental illness (OR = 2.52, p < 0.001) and were nearly tenfold higher among parents with comorbid substance abuse (OR = 9.62, p < 0.001). Three safety threats accounted for all of the effect of parental mental illness on safety determination: caretaking impairment due to emotional stability/developmental status/cognitive deficiency (57%), failure to meet a child's immediate needs (30%), and threats of harm (14%). Three safety threats accounted for 55% of the effect of comorbid mental illness and substance abuse on safety determination: failure to meet a child's immediate needs (21%), presence of a drug-exposed infant (21%), and caretaking impairment due to emotional stability/developmental status/cognitive deficiency (14%). Results suggest that sustained linkage to effective mental health services and material resources at the outset of a child welfare case may help to promote faster and more likely reunification, and prevent future maltreatment., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Childhood maltreatment is associated with a variety of young adult adversities including homelessness. This study used linked administrative records to develop a population-level, epidemiological characterization of the child protection histories of young adults accessing homelessness services. The records of all 17- to 24-year-olds receiving homeless services between 2011 and 2014 in San Francisco County, California (n = 2241) were probabilistically linked to statewide child protective service (CPS) records. Findings document that 50.0% of young adults had been reported for maltreatment at least once during childhood, yet the prevalence of past CPS involvement varied across demographic and child welfare characteristics. Homeless female youth were significantly more likely to have a CPS history than male youth (58.1% vs. 41.5%). Nearly twice as many Black clients accessing homelessness services had a CPS history as did White clients (59.8% vs. 31.8%). Roughly half (47.3%) of those with a childhood history of reported maltreatment had been last reported for maltreatment in another California county. Targeting services that address past trauma and instability among homeless young adults may be justified given the prevalence of CPS history in this population., (© Society for Community Research and Action 2017.)

Building and sustaining effective child welfare practice requires an infrastructure of social work professionals trained to use data to identify target populations, connect interventions to outcomes, adapt practice to varying contexts and dynamic populations, and assess their own effectiveness. Increasingly, public agencies are implementing models of self-assessment in which administrative data are used to guide and continuously evaluate the implementation of programs and policies. The research curriculum described in the article was developed to provide Title IV-E and other students interested in public child welfare systems with hands-on opportunities to become experienced and "statistically literate" users of aggregated public child welfare data from California's administrative child welfare system, attending to the often missing link between data/research and practice improvement.

The federal government increasingly expects child welfare systems to be more responsive to the needs of their local populations, connect strategies to results, and use continuous quality improvement (CQI) to accomplish these goals. A method for improving decision making, CQI relies on an inflow of high-quality data, up-to-date research evidence, and a robust organizational structure and climate that supports the deliberate use of evidence for decision making. This article describes an effort to build and support these essential system components through one public-private child welfare agency-university partnership.

This study addresses the problem of operationalizing neighborhood boundaries by investigating foster care entry risk at three spatial scales. Foster care entries from a California county between 2000 and 2003 (n = 3,311) are geocoded to each of the three scales (N = 46 zip codes, 320 census tracts, and 983 block groups). Exploratory spatial data analysis is used to compare spatial autocorrelation of entry rates among scales. Results suggest that depending on how neighborhoods are defined, the geographic pattern of foster care incidence changes. Implications for accurately targeting services to high-risk neighborhoods and future research directions are noted.

Controlling for neighborhood demographic characteristics, this study examined the relationship of alcohol outlets with rates of Child Protective Services (CPS) referrals, substantiations, and foster care entries from 1998-2003 in 579 zip codes in California. Data for this panel study were analyzed using spatial random effects panel models. Zip codes with higher concentrations of off-premise alcohol outlets (e.g., convenience or liquor stores) and proportions of Black residents had higher rates of maltreatment. Higher average household size and median household income were generally related to lower child maltreatment rates. More specifically, the model derived estimates that an average decrease of one off-premise outlet per zip code would reduce total referrals to CPS in the 579 zip codes by 1,040 cases, substantiations by 180 cases, and foster care entries by 93 cases. Characteristics of adjacent zip codes also were related to maltreatment rates in local neighborhoods, indicating a spatial dynamic to this relationship. Reductions in number of alcohol outlets per zip code, particularly off-premise outlets, may result in lower rates of child maltreatment.