Social service availability & proximity and the over-representation of minority children in child welfare.
|Abstract:||The goal of this study was to assess whether child welfare services were available and proximal in identified, predominantly Black and Hispanic ZIP code areas of three southern cities. GIS mapping of services contained in a state 2-1-1 community services data base revealed that there were no treatment services and/or no public transportation and/or lengthy public (bus) transportation times in 50% of the identified areas of one city and in almost 25% of the three cities combined. The authors suggest service availability and proximity should increase the likelihood of parent enrollment, attendance and completion which should increase parent dependency court compliance rates. Further, they suggest that court compliance rates should increase the rate of return of Black children to their parents and thereby reduce child welfare caseloads. Given, the logic of their argument, the authors go on to recommend that child welfare administrators annually perform GIS analyses of State 2-1-1 community services data bases to keep abreast of child welfare service availability and proximity. Additionally, they offer a number of recommendations for how to increase service availability and proximity in predominantly Black and Hispanic urban areas.|
Community service (Analysis)
Dorch, Edwina L.
|Publication:||Name: Journal of Health and Human Services Administration Publisher: Southern Public Administration Education Foundation, Inc. Audience: Academic Format: Magazine/Journal Subject: Government; Health Copyright: COPYRIGHT 2010 Southern Public Administration Education Foundation, Inc. ISSN: 1079-3739|
|Issue:||Date: Winter, 2010 Source Volume: 33 Source Issue: 3|
|Product:||Product Code: 8340000 Community Services NAICS Code: 6242 Community Food and Housing, and Emergency and Other Relief Services|
|Geographic:||Geographic Scope: United States Geographic Code: 1USA United States|
Imagine the following scenario:
A teacher accuses you of improperly disciplining your child to the point of maltreatment. A child welfare caseworker investigates the accusation, agrees and recommends that you attend a parent education class to learn more appropriate methods of discipline. A judge accepts the caseworker's professional judgment regarding the severity of the discipline and temporarily withdraws your custody rights and asks the caseworker to place your child in foster care until you learn more appropriate disciplinary techniques. You leave the court room, without your child and the rest of the morning you search for a parent education class to comply with the judge's orders. You determine that there is a class, offered at night, twice a week, for eight weeks and that you can be put on the waiting list to attend when a vacancy becomes available. You add your name to the waiting list but you are concerned that you have been put on a waiting list and that the agency is uncertain when you will be notified that you can enroll and complete the class. Yet, the indeterminate wait-time for service is not what worries you the most. What causes you more anxiety and apprehension about your ability to comply with the judge's orders is that--- you don't own a car and you have determined there is no city bus transportation to the agency address which is ten miles from your home.
This study was undertaken to determine the likelihood that such a scenario could happen in Black and Hispanic urban areas for which families have relatively high involvement with the child welfare system.
REASONABLE EFFORTS TO PROVIDE CHILD WELFARE SERVICES
The Adoption Assistance and Child Welfare Act (AACWA, P.L. 96-272, 1980) authorizes States to be reimbursed by the Federal Government for expenses incurred while administering foster care and adoption services if States submit "reasonable efforts" plans for approval by the Secretary of Health and Human Services. Reasonable efforts plans are state-specific (consult Child Welfare Information Gateway, 2006 for a comprehensive summary of each state's reasonable efforts statues), but fundamentally, AACWA mandates that judges scrutinize the "reasonable efforts" of every case within 60 days of foster care placement to determine if reasonable efforts actually have been made.
There have been innumerable disputes over the term "reasonable efforts" (see Kosanovich and Joseph, 2005 for a comprehensive summary of class action lawsuits, settlements and consent decrees against child welfare agencies for failure to provide services) but the most cited legal interpretation of the policy is embodied SUTER ET AL. v. ARTIST M. ET AL. (No. 90-1488, 1992) which alleged that the Director of the Illinois child welfare agency failed to make reasonable efforts to preserve and reunite families. The suit further alleged that in failing to provide services, he violated [section] 671(a)(15) of the AACWA. However, the court ruled that Section 671(a)(15) did not confer private rights to citizens to litigate against the government for failing to provide services. Furthermore the court reiterated that AACWA only requires States to have an approved case plan.
Contrary to the AACWA legislation, the Indian Child Welfare Act (ICWA) requires agencies to make "active efforts" to provide remedial services designed to prevent the breakup of Indian families. Hence, the ICWA's "active efforts" requirement is more stringent than the AACWA's "reasonable efforts" requirement (for an exhaustive summary of court rulings which draw distinctions between "active and "reasonable" efforts standards, consult Andrews, 2002). Conflicting legislation and numerous court cases reveal a lack of both government and legal consensus regarding the provision of services to families. Additionally, the term "reasonable" inherently implies a level of individual discretion and its' intrinsic lack of specificity causes unease in parents, caseworkers, administrators and judges alike.
Yet, the Children's Bureau, a federal agency housed under Health and Human Services points out that there are three distinct aspects to the term: (1) reasonable efforts to assure child safety; (2) reasonable efforts to provide services and to maintain and/or reunify families; and (3) reasonable efforts to provide permanent homes for children when they cannot be reunified with their families (Child Appointed Special Advocates 2010). Furthermore, Alice Shotton, a legislative consultant, formerly an attorney with the Youth Law Center in San Francisco (which litigates to reduce out of home care) identifies the main components of "active efforts" to reunify families. Specifically, she indicates that the basic steps are: (1) identification of the danger that puts the children at risk of placement and justifies state intervention, (2) determining how the family problems are causing the danger to the children and (3) designing and providing services for the family to alleviate or diminish the danger to the child (Shotton 1989-1990). Shotton adds that, while the agency has the duty to make reasonable efforts, the court has the duty to determine whether the agency actually does so. Shotton also states that, it is attorneys who must investigate agency's assertions of reasonable efforts and challenge their assertions when appropriate. In other words, judges are to rely on attorneys to determine the amount and type of services offered and/or provided to the families and to determine whether said amount is reasonable.
The federal government's entrustment of these determinations to the legal justice system, people who regularly make decisions about the credibility of human actions, seemed appropriate, but the resulting child client ethnicity statistics have caused some (see, for example, Roberts, 1999 and Pelton, 1993) to question whether reasonable efforts are indeed being made.
CHILD WELFARE CLIENT ETHNIC DISPROPORTIONALITY
There is an ongoing debate in journals as to whether or not Black and White incidence of maltreatment is the same. The reason for the ongoing debate is caused by the fact that the congressionally mandated National Incidence Studies (see Sedlack & Broadhurst, 1996) yielded different results than subsequent analyses by other researchers. Even so, there is a consensus that Black children are placed in foster care at a greater rate than white children and all other minority children. Further, their rates are higher at every stage along the child welfare service continuum: from reporting to investigation, to substantiation, to placement (a number of authors have provided data on the percentages of Black children at each service stage but most notably Hill, 2006).
There are three categories of reasons for the overrepresentation of minorities in child welfare: child and parent factors, organizational factors and community factors (consult several chapters in Derezotes et al. for various descriptions of each of these). But with respect to community factors, Shotton (1989-1990) indicates that it is incumbent upon caseworkers and judges to determine the amount and types of community services available. Further, such determinations are usually made by performing a community needs or assets assessment.
Community Needs / Assets Assessments
In a very thorough review of community needs assessments, Witkin (1994) noted some of the more exotic assessment methodologies (such as the nominal group process, Delphi techniques, incident techniques and environmental scanning). However, there are basically five types of community needs assessments: The Existing Data Approach, the Attitude Survey Approach, the Key Informant Approach, the Community Forum and the Focus Group Interview Approach. However, a quick review of the definitions of these five approaches will help make the case for a sixth approach. The Existing Data Approach utilizes already compiled statistical data to obtain insights about community resources. This approach uses descriptive statistics such as census data, labor surveys, bank deposit data, sales tax reports, police reports, or school and hospital information to prepare an assessment report for the community. The Attitude Survey Approach utilizes information gathered from a representative sample of community residents. Data is collected by personal interviews, telephone surveys, hand-delivered questionnaires or mail questionnaires. Responses are generally representative of the whole community. The Key Informant Approach utilizes community leaders and decision makers who are knowledgeable about the community and can accurately identify priority needs and concerns. Key informants complete questionnaires or are interviewed to obtain their impressions of community needs. The information is then analyzed and reported to the community. The Community Forum Approach utilizes public meeting(s) during which participants discuss the needs facing the community, their priority, and options for addressing these priority needs. All members of the community are encouraged to attend and express their concerns. Finally, The Focus Groups Interview Approach utilizes a group of people selected for their particular skills, experience, views, or positions to sort out the needs of the community (These descriptions are taken from the ISUE website March, 2010).
Geographic Information Systems (GIS)
The use of existing data is what distinguishes the Existing Data Approach from the four other approaches and the reason why the use of Geographic Information Systems (GIS) software can be listed under the Existing Data Approach. More specifically, GIS software utilizes address information in existing data bases to generate maps. For those unfamiliar with GIS, Robertson and Wier (1998) indicate that GIS is a relatively new technology; that it was initially developed in Canada in the 1960s for land inventory; that it was not until the 1980s that GIS became more widely used in other fields and that it was not until the 1990s that it began to be used by human service agencies. The article goes on to indicate how GIS can be used for a variety of child welfare administrative tasks including planning caseworker visits, recruitment and placement of foster care and plotting of caseload demographics. Two years after the Robertson and Weir article, Ernst (2000) was probably the first to use GIS to assist a child welfare agency (in Maryland) in mapping the rates and distribution of child abuse. However, Arundel et al. (2005) demonstrate how GIS could be used to map child welfare community services. Specifically he performed a GIS analysis of social service address stored in a Canadian 2-1-1 community services data base.
Call center specialists use the same database to refer residents to nearby services (although residents who own or have access to computers can go online and find the same information themselves). Since 1997, United Way of America, in partnership with the Alliance of Information and Referral Systems, has assisted many states in implementing 2-1-1 services. Databases are typically updated once a year. Accreditation for the service is provided by the Alliance of Information and Referral Systems (AIRS). In 2000, the Federal Communications Commission (FCC) approved 2-1-1 for nation-wide use. Presently, roughly half of the states have 2-1-1 databases that can make referrals statewide (AIRS, 2010).
Arundel's GIS analyses allowed Canadian legislators and community residents to determine the amount of assets available which subsequently allowed them to better conceptualize their community development options. Specifically, neighborhood assets were assessed from five perspectives: availability, proximity, access, capacity and quality. Availability was the existence or absence of an asset or resource. Proximity was the physical distance and real and perceived proximity barriers like major roads or hills. Access was defined as hours of service, user fees and client eligibility criteria. Capacity included elements such as level and nature of funding, amount of physical building space and staffing levels and expertise and quality was defined in terms of the cultural sensitivity and language-appropriateness (See Table 1).
The study presented below attempted to assess the extent to which GIS analyses of a state 2-1-1 community service data base could be useful in determining the availability and proximity of child welfare services in predominantly Black and Hispanic areas of three cities in Texas.
Texas Community Needs /Assets Assessments
The Center for the Study of Social Policy (2004) indicated that 46 states had an over-representation of Black children in foster care relative to their percent in the state population. Further, in their categorization of states as being either moderate, high or extreme in their overrepresentation, of Black children in foster care, they characterized Texas as being high. Texas child welfare, like other states, has engaged in a number of initiatives to reduce the amount of disproportionality in their state. And like other states it has engaged in community initiatives to reduce the over-representation of Black children in foster care.
Texas Department of Family Protective Services (DFPS) community engagement model originated in the Beaumont-Port Arthur, Texas region in the late 1990s. The Model consists of four interdependent stages: Community Awareness and Engagement, Community Leadership, Community Organization, and Community Accountability. The model is steeped in anti-racist principles and its' methodology consists, in part, of collecting and elevating anecdotal stories from community residents who have been involved in the child welfare system. Disproportionality specialists and community advisory committees (concerned with the over-representation of minority children in child welfare) are located in each of eleven regions throughout the state.
Since 2008, Texas DFPS has been involved in assessing the "expressed" needs (Bradshaw, 1972) of minority communities through the use of key Informants, community forums and focus groups and DFPS has acknowledged that some communities have a wealth of treatment resources, while others have few (Texas Child and Family Services Review, February 2009, p.75). Yet, DFPS was uncertain whether there were substantial service gaps throughout predominantly Black and Hispanic ZIP codes with relatively high involvement in the child welfare system and they were uncertain as to whether these service gaps impacted minority and particularly Black overrepresentation in their child welfare system and hence should be included in their various statistical causal models.
CHILD CLIENT ETHNIC DISPROPORTIONALITY AND CAUSAL MODELING
As part of Senate Bill 6 passed by the 79th Texas Legislature in 2005, Texas DFPS prepares ongoing reports on child welfare disproportionality. Their first report indicated "There was a pattern of overrepresentation in counties with sizable African-American populations: Dallas, Bexar, Tarrant, Harris, and Travis counties" (Texas Health and Human Services Commission, Department of Family and Protective Services, January, 2006 p. 5). In response to this over-representation in these counties, Texas DFPS developed a "Removals Model" and a "Substitute Care Model."
The Removals Model used an "adjusted odds ratio" which was calculated from logistical regression analysis to determine contribution of a number of variables (such as ethnicity, gender, age, income, number of children in household, married parent, teen parent, number of alleged victims, alleged perpetrators, type of allegation). The odds were measured against the CPS decision to close the case with no further action. Their State-wide analysis did not reveal a consistent association between ethnicity and the decision to remove a child from the home when controlling for the other factors (such as poverty, family structure, age of the alleged victim, type of alleged abuse, and the source of the report).
The Substitute Care Model examined the speed with which children in substitute care obtained a permanent placement or aged out at age 18. Risk ratios were calculated in the same way as odds ratios described above. However, when other factors (mentioned above) were taken into account, Texas DFPS found Black children spent significantly more time in substitute care. Child welfare researchers have used logistic regression models, almost exclusively, to examine the weight of the contribution of various factors to placement in foster care and family reunification (for example, see Gryzlak et al., Sedlak and Schultz, Baird, Johnson and Harris et al. in Derezotes et al., 2005). Thus, Texas DFPS uses a type of analysis commonly used by researchers in child welfare. Unfortunately, logistic regression modeling (child welfare researcher's analysis of choice) has not been decisive in arriving at a cause or a set of causes for the overrepresentation of Blacks in foster care. What's more, there has been a fierce and ongoing debate as to whether ethnicity or poverty is the key factor in producing the overrepresentation (Bartholet, 2009 provides for an extensive review of the history of the debate).
In addition to using regression analysis to parse the relative contributions of a number of factors to foster care placement, Texas DFPS, like a number of other states, has been using a Relative Rate Index to compare the foster care outcomes children from various ethnic groups. Specifically, DFPS uses Caucasian clients as a reference and compares the rates of occurrence for other groups to White rates which is always one. A number greater than one means that group is more likely to have an event occur than White children and a number less than one meant that the group was less likely to have the event occur than White children (a history of the development of the Relative Rate Index can be found on the website for the National Resource Center for Family Centered Practice at the University of Iowa, School of Social Work).
The Texas DFPS Relative Rate Index revealed that between 2005 and 2008, the rate of removal for African American children went from 8.7 percent to 6.2 percent, a 2.5 percentage point net decrease, and the rate of removals for Native American children went from 9.9 percent to 7.8 percent, a 2.2 percentage point net decrease (Texas Department of Family and Protective Services, March 2010). Even so, the rate at which Black children enter foster care remains high and, above all other ethnic groups in Texas. Hence, the search for the causes of such high Black foster care rates continued.
This study did not attempt to assess the extent to which ethnicity contributed to the over-representation of Blacks in the Texas child welfare system and it did not attempt to assess the extent to which amount of their family income contributed to their over-representation. Instead, in collaboration with DFPS, this study attempted to determine whether it was possible lack of treatment services in predominantly Black and Hispanic areas could be a lurking (or hidden) factor contributing to the over-representation of Blacks in the child welfare system.
The logic of the study was as follows: If predominantly Black and Hispanic areas lack treatment services, then administrators should consider treatment availability and proximity as "lurking" or unrecognized causal factors in future causal models predicting the likelihood of child welfare family involvement. However, if predominantly Black and Hispanic areas have services within a proximal distance, then there is no need to include amount of treatment services in future causal models as other factors are probably causing the ethnic variance in involvement in the child welfare system.
Parent Education Treatment Services
Parents accused of child abuse and/or neglect need a range of community services but there is some evidence that certain types of services are needed more than others. Specifically, it is estimated that more than half of all parents involved in the child welfare system nationwide, including those with children in foster care as well as those receiving services at home, attend parent education programs. As a result, approximately 440,000 American families participate in voluntary or court-mandated parent education programs each year (Barth et al. 2005). These statistics suggests parent education is pivotal to child welfare reasonable efforts to maintain and reunify families. Hence, the goal of this study was to perform a GIS analysis of the Texas 2-1-1 community services data base to determine the availability and proximity of parent education services in ZIP codes with high rates of involvement with the child welfare system.
Texas Department of Health and Human Services, Department of Family and Protective Services (DFPS), is divided into 11 regions and this study involved three of the eleven regions (see Figure 1). Texas DFPS indicated "There was a pattern of overrepresentation in counties with sizable African-American populations: Dallas, Bexar, Tarrant, Harris, and Travis counties" (Texas Health and Human Services Commission, Department of Family and Protective Services, Jan. 2006 p. 5). However, DFPS identified eight ZIP codes in the Dallas-Fort Worth-Arlington area, Region 3; eight ZIP codes in the Houston area, Region 6 and sixteen ZIP codes in the San Antonio area, Region 8 (see Table 2 for a list of the specific ZIP codes). Black residents ranged from 7.8% to 78.2% in Dallas ZIP codes, from 54.37% to 93.82% in Houston ZIP Codes and from 1.93% to 58.56% in San Antonio ZIP codes (i.e., the greatest number of Black residents was in Houston ZIP codes). Residents' incomes ranged from $18,161 to$ 54,433 in Dallas ZIP codes; from $17,183 to $39,436 in Houston ZIP codes and from $18,304 to $46,417 in San Antonio ZIP codes (i.e., the lowest income range was in Houston).
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Child Welfare Ethnic Disproportionality in Texas
In Texas, the rate at which Black families are investigated, substantiated, or placed in foster care is approximately twice the rate at which they are represented in the state child population. American Indians, Caucasians and Hispanics are as likely to be investigated, substantiated and placed in foster care as they are represented in the state child population. Asians and Pacific Islanders are much less likely to be investigated, substantiated, or placed in foster care than they are represented in the state child population (The Texas Health and Human Services Commission, Department of Family and Protective Services, July, 2006).
Phase Two: The Texas 2-1-1 Database
2-1-1 Texas, a private, not-for-profit 501(c)(3) organization formerly known the Community Helpline, provides free information over the phone and on-line regarding health and human services provided by more than 60,000 state and local programs. It is accredited by the national Alliance of Information and Referral Systems (AIRS).
Three call center supervisors (who had received several weeks of call center training in locating services) identified parent education agencies and created a list of agencies stored in the 2-1-1 Texas data base. They used both the terms "parent education" and "parenting classes" to select the agencies listed. Phase Three: Calculating Distances
Step One: Data Base Creation
Three tables were created in Microsoft Excel for Dallas, Houston and San Antonio. Each table consisted of six columns (i.e., a Name, Address, City and ZIP Code, driving distance and public transit time column).
Step Two: Calculation of Driving Time to Destination
Driving time was calculated using the online version of Google Maps. Driving time was calculated from the center each of the 32 ZIP codes to each facility within a ten mile driving radius of the ZIP code. Google Maps allows for two inputs when calculating driving distance: a starting address and a destination address. Hence the center of the ZIP code was used as the starting address and the SA and PE address (e.g. 123 N. Main St., City, TX, 70123) was the destination address.
Step Three: Calculation of Amount of Mileage to Destination
The mileage from these two points was inserted into the appropriate Excel cell--across from the agency name. This step was repeated for estimated public transit times according the season of the year and the time of day. Wednesday mid-morning was chosen to standardize all calculations.
Step Four: Map Creation
In order to study the availability of facilities in relation to ZIP codes, a process called geocoding was used, whereby a street address (such as 123 N. Main St., City, TX 70123) was translated into an exact geographic location. Geocoding takes regular addresses as input and gives latitude and longitude as output. There are numerous websites and software programs that could have been used for this. However, Batchgeocode was chosen because of its simplicity. Specifically, this site accepted four fields (agency name, street address, city and ZIP code) that were copied from the Excel file for each of the six tables with 2-1-1 facility address information.
We downloaded a .KML file (using the "Google Earth KML" button). A KML file is a "Keyhole Markup Language" file, giving Google Maps or Google Earth information on latitude and longitude, or other map data. This file was then uploaded to a custom Google Map and displayed in combination with any other map. To upload a map to Google Maps online, you must have a Google account, which can be created at https://www.google.com/accounts. At the Google Maps website (http://maps.google.com), click the "My Maps" link, followed by "Create new map." Clicking the "Import" link, the user may browse his or her computer for the previously downloaded .KML file. Once selected and uploaded, Google Maps can display the 2-1-1 facility location data.
Google Earth allows the user to create and display custom overlays--or additional information such as colorized shapes--onto a map. ZIP code boundaries were overlaid and manually traced over with a polygon tool (a tool in Google Earth which allows the user to create custom shapes, in this case shapes that conform to the boundaries of a ZIP code), allowing us to color and shade each ZIP code area. The maps of these regions' ZIP codes were saved as a .KML file and uploaded to the browser-based Google Maps (at http://maps.google.com) and added to the previously completed geocoded facilities maps (see step 3 in the Creating the maps section above). Excel spreadsheet calculations
The number of parent education referrals per ZIP was assessed by tabulating the number of number of time parent education appeared in the approved electronic case plans per zip code/ for the year 2008 (see PE agencies column, Table 2).
The 2-1-1 Texas community service data bases did not provide information on either agency capacity or agency quality. The implications of this missing information (as well as the implications for accessibility information) are presented in the discussion section below.
Some identified ZIP codes had zero agencies but a large number of parent referrals e.g., ZIP code 78223 in San Antonio had zero parent education agencies but 94 parent referrals and ZIP code 78229 in San Antonio had zero parent education agencies but 84 parent referrals. Other zip codes had a large number of agencies relative to the number of parent referrals e.g., ZIP Code 78204 in San Antonio had 20 agencies and 28 parent referrals (see Table 2). Homeschool Instruction for Parents of Preschool Youngsters (HIPPY), AVANCE and DePelchin were three private parent education agencies with multiple locations in one or more of each of the cities studied.
Dallas GIS Map Results
Dallas/Arlington/Fort Worth ZIP codes identified by the Department of Family Protective Services (DFPS) diproportionality task force members are colored on the map below. Each balloon is a parent education agency listed in the 2-1-1 Texas community services data base. Circled areas of each shaded ZIP code reveal areas of the identified ZIP codes that lack parent education agencies. DFPS provided contracts to thirty-eight parent education agencies in the Dallas-Arlington area. However, the maps below reveal that contracted agencies were located in the circled areas of need.
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Dallas Availability and Proximity Results
Five of the eight (or 62%) of the identified ZIP codes in the Dallas-Arlington-Fort Worth area had at least one agency within two miles; all eight had at least one agency within five miles and all eight had at least one agency within ten miles. Driving distances ranged from 5.2 to 9.17 miles and public transportation time ranged from 31.33 to 62.56 minutes. Dallas, Texas
Houston GIS Map Results
Houston ZIP codes identified by the Department of Family Protective Services (DFPS) disproportionality task force members are shaded on the map below. Each balloon on the colored ZIP code area is a parent education agency listed in the 2-1-1 Texas community services data base. Circled areas of each colored ZIP code reveal areas that lack parent education agencies. DFPS provided contracts to ten (10) parent education agencies. However, the maps below reveal that contracted agencies were not located in the circled areas of need.
Houston Availability and Proximity Results
Only one of the eight ZIP codes (or, only 12.5%) of the identified ZIP codes in the Houston area had at least one agency within two miles; four (or, only 50%) had at least one agency within five miles and six (or 75%) had at least one agency within ten miles. The average driving distance ranged from 9.8 to 18.2 miles and public transportation time ranged from 57.1 to 124.6 minutes (or over two hours).
San Antonio GIS Map Results
San Antonio ZIP codes identified by the Department of Family Protective Services (DFPS) disproportionality task force members are shaded on the map below. Each balloon on the colored ZIP code area is a parent education agency listed in the 2-1-1 Texas community services data base. Circled areas of the colored ZIP code reveal areas that lack parent education agencies. DFPS provided contracts to three parent education agencies but these were not located in the circled areas of need.
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San Antonio Availability and Proximity Results
Eight of the sixteen (or, 50%) of the identified San Antonio ZIP codes had at least one agency within two miles; thirteen (or, 81%) had at least one agency within five miles and 15 (or, 93%) had at least one agency within 10 miles. The average driving distance ranged from1.1 miles to 17.34 miles and the average driving time ranged from 40.78 to 82.73 minutes (or over an hour).
Large numbers of Black children were being placed in foster care in Houston, Dallas and San Antonio and Texas DFPS suspected poverty was the primary cause for the over-representation. DFPS was aware that there were service gaps throughout the state but administrators wondered if it was possible there were substantial service gaps in predominantly Black and Hispanic areas and further they wondered if it was possible these service gaps could be contributing to the amount of Black and Hispanic children in their the child welfare system.
This study attempted to answer the question--"Are there gaps in parent education services in predominantly Black and Hispanic areas of Dallas, Houston and San Antonio. The answer was and remains important because amount of service availability is one measure of one type of state and local child welfare system effort to maintain children in their homes and/or to reunify children with their parents i.e., one measure of the amount of "reasonable efforts" being made by the state and local child welfare stakeholders. Additionally, a determination of the availability and proximity of services in predominantly Black and Hispanic areas might help us understand the factors that contribute to the over-representation of minority children at all stages of the child welfare system.
Community Needs / Assets Assessments: Service Availability and Proximity
A series of GIS analyses of the 2-1-1 Texas data base revealed that, although roughly 75% of the identified ZIP code areas had one or more agencies within a proximal distance, 50 % in one city and approximately 25% across all three cities had no agencies within a five-mile driving radius of the identified ZIP codes and/or no bus transportation and/or long public transportation times. Results also revealed that DFPS parent education contractors were not located in most identified areas of concern. Moreover, results revealed a number of multiple-location private agencies were not located in many identified areas of concern. These results provided Texas DFPS with objective data about (parent education) treatment service availability, proximity and gaps in predominantly Black and Hispanic areas with relatively high rates of involvement in the child welfare system and suggest service availability and proximity should be considered a potential contributing factor to the over-representation of Black children in the child welfare system.
Child Client Ethnic Disproportionality And Causal Modeling
Using their Substitute Care Model, Texas DFPS has examined the speed with which children in substitute care obtained a permanent placement or, aged-out, at age 18, and they found that, when other factors were taken into account, Black children spent significantly more time in substitute care (p. 10). The city of Houston has the greatest number of Black foster care placements in Texas and this study found that fifty percent of the identified, predominantly Black, Houston, ZIP codes had no parent education agencies within a five-mile driving radius. What is interesting to note about this finding is that, in Texas, there is no Hispanic child welfare disproportionality and this study found that there is an abundance of parent education agencies in San Antonio which is predominantly Hispanic. The fact that many predominantly Black areas lack treatment services and that many predominantly Hispanic areas had an abundance of treatment services suggest that services could be a "lurking" (hidden and/or correlated) variable contributing to high rates of minority involvement in the child welfare system (see Figure 8 for a graphic representation of this idea).
Only further research can establish the true validity of the impact of the availability of treatment services on foster care. Yet Table 1 gives Texas DFPS the capability of examining the contribution of various service dimensions to the over-representation of Black children in foster care. In other words, Table 1 allows Texas DFPS to quantify service dimensions and include them in their Removal and Substitute Care Models and regression equations. Additionally, in the future, a community service availability score can be the number of (parent education) services in an identified area; a community proximity score can be the average driving distance and/or public transit travel time in an identified area; a capacity score can be the average number of agency slots in the area etc. Further, given this type of quantification of service dimensions, a composite community service score can be generated such that the availability score + the proximity score + the capacity score + quality score + the accessibility score = a composite community service score. The quantification of service dimensions allows Texas DFPS to look at environmental attributions of causality in addition to person (or, parent, child and caseworker) attributions of causality for the over-representation of minority children in the child welfare system.
The Race Matters Consortium has played a leading role in developing a Racial Equity Scorecard and the Scorecard allows stakeholders to determine the rate of disproportionality across various ethnic groups. This study provided an opportunity to develop a table like Table 2 which can now enable Texas child welfare stakeholders to determine the availability and proximity of (parent education) treatment services in predominantly minority areas with high rates of involvement with the child welfare system relative to the availability and proximity of services in other areas that have less involvement in the child welfare system. Hence, it can be considered a first iteration of a Community Treatment Services Equity Scorecard, or a complement to the Racial Equity Scorecard.
Macro Level "Reasonable Efforts " To Provide Parent Education And Reduce Disproportionality
Texas DFPS community advisory committees in Region 3 (Dallas, Denton and Tarrant counties); Region 6 (Houston, Sunnyside, 5th Ward and 3rd Ward) and Region 8 (Bexar County, San Antonio) have accomplished a great deal. Specifically, they acknowledged community leadership, assembled key informants, raised community awareness, improved communication and assessed "expressed" community needs. However, they did not have objective data of community needs.
Texas DFPS recognizes that knowledge management is a process of creating, sharing, considering and using knowledge (Nutley et al., 2007). Hence, they are considering the appointment of "knowledge brokers" whose job description will include navigating between regional disproportionality specialists and regional disproportionality advisory committees (each responsible for assessing the causal factors involved in the overrepresentation of minority children in the child welfare system) and researchers and initiating, monitoring, disseminating and integrating research hypotheses, methods and results.
Further, DFPS Texas is considering the viability of the following suggested strategies for improving the availability, proximity, capacity, accessibility and quality of the parent education services:
Parent Education Availability, Proximity, and Capacity DFPS is considering:
* Hiring a Geographic Information System Software (GIS) expert to perform regular GIS analyses of the 2-1-1 Texas 2-1-1 community service data base(s) to supplement current case-by-case reasonable efforts. Stakeholders could consult Robertson and Wier (1998) for advice the use of GIS soft and hardware in child welfare; * Revising the current parent education contractor Requests for Proposal (RFP). Revised RFPs could: (1) target service contracts for Black and Hispanic ZIP code areas with high foster care rates; (2) purchase the number of parent education slots at least comparable to the number of parent education referrals in an area; (3) offer contracts to agencies that have an identified range of course and certificate types for a range of clients types per Meeker and Johnson 2005, Lundahl et al. 2006 and Smith et al. 1994 and evidence-based parent education programs per Meeker & Levison Johnson, 2005 or Kaminski et al. 2008; * Creating a community subcommittee to review state family preservation and reunification services funding and attend to Kasia O'Neill Murray's overview of our current child welfare financing structure and the major avenues through which federal funds enter the system (Pew Charitable Trust, 2007).
* Collaborating with philanthropic funders: Almost two million dollars was donated to parent education agencies in Texas (The Foundation Center, 2010). DFPS could collaborate with these same philanthropic funders to provide services in identified areas and to place self-directed CDROM parent education classes such as Parenting Wisely in area public hospital maternity and pediatric wards, YMCA and Boys and Girls Clubs and local libraries as a prevention strategy.
* Purchasing vans and assigning (retired) caseworkers to provide parent education from the vans in identified disproportionality areas: In Charlottesville, Virginia, purple colored vans park in both neighborhoods and in shopping malls and "parents walk over to get advice on problems they are having with their kids, information about upcoming parenting classes and workshops or just a friendly ear to listen. They can step into the van to watch a video about positive discipline, communication skills, child development or stress reduction strategies, or to borrow a parenting book, meet with a group of neighbors to brainstorm solutions to common problems, and/or request an individual parent consultation session" (Mobile Parent Education Project, 2010). DFPS parent education staff in vans could supplement staff in the current Family Resource Centers (FRC, 2010).
* Contracting with area university professors who specialize in parent education to produce public access television parent education: Dallas iMedia Network is a private nonprofit corporation and public access television provider in Dallas and Houston MediaSource (HMS) is a non-commercial 501(c)(3) Public Access Television channel in Houston. Parents could complete public-access parent education courses in their own homes and public access coordinators could submit parent's certificates of completion to their caseworkers.
Parent Education Quality DFPS is considering:
* Creating minimum quality standards for parent education classes. Foster parents are required to attend parent education classes for a specified number of hours on specified topics ranging from attachment issues, loss issues, discipline, effects of abuse and neglect and sexual abuse (Parent Resource for Information, Development and Education, PRIDE 2010). Further, divorcing parents are required to attend parent education courses for a specified number of hours on specific topics (Texas Family Code [section] 105.009--The Parent Education and Family Stabilization Course). Hence stakeholders could advocate for a minimum number of hours of instruction on specified topics according to child welfare case allegation type.
* Evaluating their parent education programs. Matthews, J & Hudson, A. (2001), the National Parent Education Network, NPEN (2010), the Children Youth and the Families Education and Youth Research Network (CYFERnet, 2010) all provide very thorough discussions of best-practice parent education evaluation tools and strategies and stakeholders could build similar parent education evaluation units.
* Creating a statewide method of credentialing or certifying parent educators. The University of Minnesota, Parent and Family Education Licensure program prepares parent educators to teach courses on intellectual, emotional, cultural, social, and physical needs of both parents and children UMN (2010). The University of North Texas offers classes in parent education but does not have offer a credentialing or certificate program. Child welfare stakeholders could advocate for a University-based parent education certificate program in Texas.
* Providing community needs/assets assessment training to child welfare judges and prosecutors and child welfare administrators. Training could be provided through the National Council of Juvenile and Family Court Judges (NCJF, 2010) and the Court Improvement Project (CIP, 2010). Court mediation programs, joint agency-court training, automated docketing, case tracking, linked agencycourt data systems, one judge/one family models, time-specific docketing are all CIP initiatives. And, community needs/assets assessments could be yet another training initiative.
* Advocating for 2-1-1 Texas to provide capacity and quality information. The Texas Health and Human Services Commission distributes and collects a standardized form to 23 regional Texas 2-1-1 community services data base providers. However, the standardized form does not have a section where agencies could indicate their capacity, accreditation, staff credentialing or evidence-based curriculum. Senators Patty Murray (D-WA) and Richard Burr (R-NC) are sponsoring S 211 and HR 211 which, if passed, will provide a grant to each state to assist with the establishment of a 2-1-1 system (United Way, 2010) and this money could be used to help create a 2-1-1 Texas community services data base that store agency capacity, quality and accessibility information needed by child welfare stakeholders.
[FIGURE 8 OMITTED]
This study served as the first stage of an assessment of the impact of service availability and proximity on the over-representation of minorities in child welfare. The intent of this initial stage was to call attention to a missing component of the child welfare disproportionality discussions and to demonstrate a methodology for assessing treatment service dimensions. However, a more rigorous research design is needed to perform a comparative community needs assessment across ethnic groups and areas of each city.
In some areas community services were not available, in some they were not proximal and in some there was no public transportation. Yet, it is possible parents were nonetheless able to attend parent education classes in spite of the distance of the nearest agency, the cost of gasoline or the cost of public transportation. However, can there be any doubt that these factors constitute substantial deterrents to completion of required parent education classes. GIS analyses of 2-1-1 community services data bases make it possible to produce objective assessments of service availability and proximity (and possibly even capacity and quality). Hence maps and analyses should be considered by caseworkers, administrators, judges and federal reviewers when determining whether reasonable (active and equitable) efforts have been made.
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EDWINA L. DORCH
The Bush School of Government and Public Service Texas A&M University
Table 1 Asset Variables Facilitating Conditions Barrier Conditions Availability Present Absent Planned/ developing Lost (e.g., cut or relocated Proximity Within neighborhood Natural or constructed physical barriers Not Reasonably close (depends easily accessible by on users) roads or transit Not close to neighborhood Good Transportation to users asset Accessibility No/low user fees or User fees/no subsidies equipment/participation Restrictive eligibility fees Limited hours of Promotion outreach to operation potential users Long waiting lists No limited wait times No eligibility requirement Appropriate hours of operation Capacity Not at full capacity all Always over capacity the time Well maintained and underfunded physical conditions State of disrepair Adequate use of volunteers to enrich Understaffed program Over-reliance on Continuous program and stable program funding volunteers to run basic programs Quality Responsive to users Hierarchy of support provided (e. g. , Culturally based or English speaking vs. sensitive non-English speaking) Multilingual and Rigid/inflexible modes multicultural of service/support Adaptivemodes of service/ Under-skilled staff support Appropriate expertise and skill base Table 2 The Community Parent Education Assets Index City ZIP Code Population Land area( # Black Region 03--Dallas/ Arlington Dallas 75216 49681 14.23 38889 Denton 76201 48808 12.71 4319 76205 35424 28.88 2804 Ft. Worth 76103 14302 5.82 3409 76104 17511 5.85 10018 76105 22047 5.69 11091 76112 39436 11.04 18371 76119 40484 15.84 22470 Region 06--Houston Houston 77004 30379 6.09 21999 77016 29753 10.45 23650 77026 27593 6.84 18649 77047 11112 14.19 7942 77048 14267 11.01 12579 77051 13235 5.62 12417 77033 27676 6.02 23327 77088 47739 11.15 25956 Region 08--San Antonio Kerville 78028 33883 257.71 726 Seguin 78155 39843 359.32 2573 San 78201 47387 7.19 914 Antonio 78202 11746 2.33 5044 78204 11905 2.77 119 78207 56348 7.14 1787 78208 5079 1. 777 78209 40675 10.55 1698 78210 37345 7.19 2484 78216 37282 14.03 1446 78217 32502 10.85 3028 78220 16668 7.08 9761 78223 43225 39.47 1870 78227 46668 22.3 3705 78229 27585 5.98 2029 78242 28786 9.06 1386 City ZIP Code % Black # Hispanic % Hispanic Region 03--Dallas/ Arlington Dallas 75216 78.28% 9421 19.00% Denton 76201 8.85% 8768 18.00% 76205 7.92% 4062 11.50% Ft. Worth 76103 23.84% 4289 30.00% 76104 57.21% 4585 26.20% 76105 50.31% 9004 40.80% 76112 46.58"% 4155 10.50% 76119 55.50% 9378 23.20% Region 06--Houston Houston 77004 72.42% 3570 11.80% 77016 79.49% 5084 17.10% 77026 67.59% 8574 31.10% 77047 71.47% 1945 17.50% 77048 88.17% 1098 7.70% 77051 93.82% 519 3.90% 77033 84.29% 3801 13.70% 77088 54.37% 10502 22.00% Region 08--San Antonio Kerville 78028 2.14% 6668 19.70% Seguin 78155 6.46% 16119 40.50% San 78201 1.93% 38881 82.00% Antonio 78202 42.94% 6113 52.00% 78204 1.00% 10847 91.10% 78207 3.17% 52268 92.80% 78208 15.30% 3763 74.10% 78209 4.17% 9926 24.20% 78210 6.65% 30088 80.60% 78216 3.88% 15621 41.90% 78217 9.32% 10123 31.10% 78220 58.56% 4970 29.80% 78223 4.33% 29701 67.30% 78227 7.94% 29376 63.70% 78229 7.36% 13531 49.10% 78242 4.81% 23036 80.00% City ZIP Code White % of White Med Income Region 03--Dallas/ Arlington Dallas 75216 4568 9.19% 24960 Denton 76201 36449 74.68% 30231 76205 28577 80.67% 54433 Ft. Worth 76103 7878 55.08% 33019 76104 4291 24.50% 18161 76105 5777 26.20% 22710 76112 17130 43.44% 34295 76119 12345 30.49% 27377 Region 06--Houston Houston 77004 5082 16.73% 20840 77016 2992 10.06% 23835 77026 4596 16.66% 17183 77047 1935 17.41% 35384 77048 827 5.80% 27391 77051 274 2.07% 17529 77033 1687 6.10% 26544 77088 12602 26.40% 39436 Region 08--San Antonio Kerville 78028 29868 88.15% 34374 Seguin 78155 29260 73.44% 37642 San 78201 33305 70.28% 26725 Antonio 78202 3918 33.36% 18304 78204 7008 58.87% 24153 78207 34930 61.99% 20117 78208 2831 55.74% 20692 78209 35236 86.63% 46417 78210 21320 57.09% 26522 78216 29349 78.72% 35324 78217 23963 73.73% 40967 78220 4115 24.69% 26920 78223 27539 63.71% 30145 78227 27506 58.94% 30222 78229 18434 66.83% 30675 78242 17033 59.17% 27556 City ZIP Code PE referrals PE agencies (5 mile) Region 03--Dallas/ Arlington Dallas 75216 40 1 Denton 76201 8 4 76205 11 3 Ft. Worth 76103 37 5 76104 46 10 76105 87 4 76112 124 2 76119 80 3 Region 06--Houston Houston 77004 Unk 3 77016 Unk 0 77026 Unk 1 77047 Unk 0 77048 Unk 0 77051 Unk 0 77033 Unk 1 77088 Unk 2 Region 08--San Antonio Kerville 78028 121 4 Seguin 78155 89 2 San 78201 76 9 Antonio 78202 46 19 78204 26 20 78207 217 18 78208 24 11 78209 39 5 78210 84 12 78216 60 1 78217 58 6 78220 46 0 78223 94 0 78227 150 8 78229 84 0 78242 98 5 Dallas, Texas Table 3: Parent Education Availability City ZIP code PE PE PE Dallas 75216 1 1 6 Denton 76201 2 4 4 76205 0 3 4 Ft. Worth 76103 1 5 13 76104 1 10 10 76105 2 4 11 76112 0 2 10 76119 0 3 9 Dallas Texas Table 4: Parent Education Proximity Parent Education Facilities ZIP code Driving Public Distance Transit Time (Mile) (Minute) Dallas 75216 9.68 62.56 Denton 76201 5.2 NA 76205 6.78 NA 76103 6.97 31.33 76104 6.71 36.33 Ft. Worth 76105 6.89 33 76112 8.52 43 76119 9.17 NA Houston, Texas Table 5: Parent Education Availability City ZIP code PE PE PE Houston 77004 3 3 10 77016 0 0 0 77026 0 1 7 77047 0 0 0 77088 0 2 4 77048 0 0 1 77051 0 0 10 77033 0 1 6 Houston, Texas Table 6: Parent Education Proximity Public ZIP code Driving Transit Distance Time Ft. Worth 76119 9.17 NA Houston 77004 9.77 57.11 77016 17.92 101.63 77026 14.4 76.68 77047 15.79 124.58 77088 14.68 86.58 77048 18.22 117.53 77051 12.09 73.47 77033 12.81 75 San Antonio, Texas Table 7: Parent Education Availability City ZIP code PE PE PE Kerrville 78028 4 4 4 Seguin 78155 2 2 2 San 78201 0 9 26 Antonio 78202 5 19 26 78204 9 20 29 78207 11 18 31 78208 4 11 26 78209 0 5 29 78210 5 12 24 78216 0 1 7 78217 0 6 7 78220 0 0 7 78223 0 0 0 78227 7 8 18 78229 0 0 17 78242 0 5 19 San Antonio, Texas Table 8: Parent Education Proximity Public Driving Transit Distance Time City ZIP code (Mile) (Minute) Kerrville 78028 0.28 N/A Seguin 78155 1.1 N/A San Antonio 78201 7.82 45.46 78202 7.05 41.84 78204 6.11 41.65 78207 5.71 40.78 78208 7.55 44.16 78209 9.12 48.38 78210 7.51 42.32 78216 12.4 69.78 78217 14 60.57 78220 12.75 73.43 78223 17.34 82.73 78227 10.04 60.76 78229 10.84 56.14 78242 12.61 68.97
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