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18 th National Conference on Child Abuse & Neglect April 18 – 20 Washington, D.C. Donald Baumann Saint Edwards University John Fluke & Katherine Casillas.

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Presentation on theme: "18 th National Conference on Child Abuse & Neglect April 18 – 20 Washington, D.C. Donald Baumann Saint Edwards University John Fluke & Katherine Casillas."— Presentation transcript:

1 18 th National Conference on Child Abuse & Neglect April 18 – 20 Washington, D.C. Donald Baumann Saint Edwards University John Fluke & Katherine Casillas American Humane Association Understanding Decision-Making

2 Understanding Decision-Making Overview Advances Outside Child-Welfare Assumptions in the Decision Sciences Heuristics and Biases Signal Detection Theory Decision-making Errors Cumulative Prospect Theory The Decision-Making Continuum Models in Child Welfare

3 Understanding Decision-Making Frameworks: Advances Outside Child-Welfare Engineering Psychology and Economics – Theories of riskless and risky decision-making (decision choice models) – Game Theory (mathematical models of conflict and cooperation) – Bounded rationality (doing “well enough”) – Optimization (maximizing outcomes) Artificial Intelligence – Network analysis (systems for determining causality) – Expert systems (complex decision-making system that learn) Medicine – Fuzzy trace theory (understanding the “gist”, values and inference) Psychology, Statistics and Psychophysics – Heuristics and bias (errors made in decision-making) – Normative approaches (the standards are probability & statistics) – Signal detection theory (analysis of threshold differences) – Fast and frugal reasoning (based on probability cues) – Implicit and explicit judgments (intuition and logic) – Cumulative prospect theory

4 Understanding Decision-Making Frameworks: Advances in Economics and Psychology Economics and Exchange Theory – Assumption of rationality – People weigh the costs and benefits of a decision and optimize Herbert Simon and Satisfysing – Bounded rationality- we do “well enough” – Reason is limited and we do not optimize Tversky, Kahneman and Meehl – Reason is very limited and we are poor decision-makers – Under conditions of uncertainty we use heuristics (rules of thumb) and make errors – Thinking fast and slow under different circumstances – Cumulative Prospect Theory (choices based on gains and losses) Gigerenzer – heuristics work a lot of the time – Fast and frugal reasoning (based on probability cues) – We make the choice with the best cue

5 Understanding Decision-Making Frameworks: Assumptions Assumptions – Decisions have psychological (cognitive, motivational and emotional) properties and are at the individual level – Decisions have a context – People have different thresholds for different decisions – People make errors when they make decisions – Sources of error and accuracy can be empirically understood and improved upon

6 Understanding Decision-Making Frameworks: Heuristics and Biases Overconfidence phenomenon (We overestimate the accuracy of our beliefs and incompetence feeds overconfidence) Confirmation bias (We look for evidence to justify beliefs rather than falsify them) Representativeness heuristic (The belief that things belong to a group that is typical) The availability heuristic (judging the likelihood of an event by how easily it come to mind e.g., vivid instances) Illusory thinking (The search for order in random events) Illusory correlation (The perception of a relationship where none exits – usually confirmatory) Illusion of control (The belief that chance events are subject to our control) Moods and judgment (good and bad moods bring to mind good and bad associations)

7 Understanding Decision-Making Frameworks: Implicit and Explicit Judgments Implicit (Intuitive) Judgments – Powers of intuition (fast thinking): Somewhat instantaneous making for efficiency – Limits of intuition: The speed can make us error prone when we need to slow down and think about things more Explicit Judgments – Powers of explicit judgments (slow thinking): The length of processing can make us less error prone – Limits of explicit judgments: Cognitively labor intensive and inefficient

8 A CHILD WELFARE VALUES EXERCISE (DALGLEISH)

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10 Signal Detection Theory and Decision Errors

11 Child Welfare and the Problem of False Positives- Receiver Operator Characteristics Sensitivity (true positive) Accuracy in assessing risk is generally not very good, and false positives are very likely Furthermore almost all predictive power is tied to prior occurrences N = 210,642

12 Child Welfare and the Problem of False Positives (assume actual prevelance is 10%) Sensitivity (true positive) N = 210,642 Low threshold

13 63,000 False Positives Effect of Thresholds on False Positives The assessment has an Area Under the Receiver Operator Curve = 63%: Prevalence assumed to be 10%: Applied to 100,000 children LOW THRESHOLD

14 Child Welfare and the Problem of False Positives Sensitivity (true positive) N = 210,642 High threshold Low threshold

15 34,000 False Positives Effect of Thresholds on False Positives The assessment has an Area Under the Receiver Operator Curve = 63%: Prevalence assumed to be 10%: Applied to 100,000 children HIGHER THRESHOLD

16 Child Welfare and the Problem of False Positives Sensitivity (true positive) N = 210,642 High threshold

17 63,000 False Positives 34,000 False Positives Effect of Thresholds on False Positives The assessment has an Area Under the Receiver Operator Curve = 63%: Prevalence assumed to be 10%: Applied to 100,000 children HIGHER THRESHOLDLOW THRESHOLD

18 Cumulative Prospect Theory (Tversky & Kahneman, 1992) A psychological theory for explaining non-rational decisions under uncertainty Principles – We make choices based on change in gains and losses relative to a reference point; a reference point based on what we have or know. Child Welfare Example: a child is safe at home. – Given the choice of a large sure loss compared to a chance that we either might not have a loss or have a large loss, we tend to take the risker option; we take a sure gain and do not take a risk even when a risk might increase our gains. We dislike losing more than we like winning.

19 Cumulative Prospect Theory (Tversky & Kahneman, 1992) Principles – Given the equal choice of a larger gain and smaller loss we tend to choose neither; asymmetric loss aversion. Example: There is a 50/50 chance If we provide a specific service a child will be safe for 6 months, or the child will certainly be maltreated again in 4 months. – We tend to make choices based on very unlikely events as if they are more likely; overweighting unlikely events. Example: Involving the court in a child maltreatment case is a large worry.

20 Relationships of Gains and Losses in Prospect Theory

21 EXERCISE IN PROSPECT THEORY

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24 The Continuum of Child Welfare Intervention Assessments and decisions are made at key points along the child protection continuum Each key decision point requires a specific decision and action

25 Models of Decision Making in Child Welfare

26 Models of Child Welfare Decision Making Structures and Systems of Decision Making – Stein T and Rzepnicki T. (1984). Decision Making in Child Welfare Services: Intake and Planning. Boston: Kluwer-Nijhoff Publishing. – Gleeson J. (1987). Implementing structured decision- making procedures at child welfare intake. Child Welfare 66 (2) – Wells, S. J. (1985). How we make decisions in child protective services intake and investigation. Washington, DC: American Bar Association.

27 System Models of Observed Child Welfare Decision Making Behavior Rossi, P. H., Schuerman, J. & Budde, S. (1999). Understanding decisions about child maltreatment. Evaluation Review, 23(6) Baumann, D., Kern, H., & Fluke, J. (1997). Foundations of the decision making ecology and overview. In Kern, H., Baumann, D. J., & Fluke, J. (Eds.). Worker Improvements to the Decision and Outcome Model (WISDOM): The child welfare decision enhancement project. The Children’s Bureau, Washington, D.C. Dalgleish, L.I. (2003). Risk, needs and consequences. In M.C. Calder (Ed.) Assessments in child care: A comprehensive guide to frameworks and their use. (pp ). Dorset, UK: Russell House Publishing. Munro, E. (2005) Improving practice: Child protection as a systems problem. Children and Youth Services Review, 27, Baumann, D.J., Dalgleish, L., Fluke, J., & Kern, H.(2011).The decision-making ecology. Washington, DC: American Humane Association.

28 DECISION-MAKING ECOLOGY (DME)

29 External Factors Decision Maker Factors Organizational Factors Decision Making Outcomes InfluencesDecisionsOutcomes Case Factors Decision Making Ecology/General Assessment and Decision Making Model (Baumann, Dalgleish, Fluke &Kern, 2011)

30 GENERAL ASSESSMENT AND DECISION MAKING (GADM) MODEL: THE PROCESS OF DECISION-MAKING

31 Risk assessment and decision making In many jurisdictions risk assessment is used as a way to summarise the case information. How is this assessment turned into a decision about a course of action? In general, the risk of harm has to be sufficient to warrant taking protective action.

32 Assessments and thresholds are influenced by different factors The Risk Assessment derives from case information on: the Child: the Family and the nature of the current and past concerns. Information organized into operationally defined factors. From Theory, the Threshold for Action derives from the experiences and history of the worker. – Possible consequences for the different stakeholders. – How the worker values the consequences.

33 Assessment and decision making is a difficult task Assessments and decisions are based on information that is often unclear, noisy and uncertain. Sometimes made under time pressure in a highly emotional atmosphere. There are structural and resource constraints, media interest, unpredictability of outcomes. This is: Decision making under uncertainty.

34 Crucial points: The general model for assessment and decision making. Separates: The assessment of the situation. From: The decision to something about it. – Qualitatively different factors influence assessment and decision making. Distinguishes: The person’s ability to detect the need to take action (how good they are). From: The person’s willingness to take action (their threshold).

35 If the Assessment is ABOVE the Threshold, then ACTION is taken. If the Assessment is BELOW the Threshold, then NO ACTION is taken. A General Model for Assessing the Situation and Deciding what to do about it - Dalgleish Threshold Factors Influencing Threshold for Action Information from Experiences and Organizational Factors) HIGH LOW Assessment Dimension: e.g. Risk or ‘Level of Concern’ Assessment Factors Influencing Assessment. Information from Current situation being Assessed. The Case Factors.

36 The Process of Decision Making: The Threshold Concept If threshold low, W 1 needs little evidence before taking action. Assessed level of risk or need Low High Threshold W 1 Threshold W 2 W 2 Assessment. W 1 Assessment.  If threshold high, W 2 needs much evidence before taking action.  Even if they agree on the assessment,  they disagree about taking action. Yes No *From Len Dalgleish, 2000

37 Transition slide subtitle The Structured Decision Making System (SDM) ®

38 The National Council on Crime and Delinquency, founded in 1907, is a nonprofit organization that creates just and innovative solutions to complex social problems, and works to improve the lives of all people through research, public policy

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41 What is the SDM system? A research and evidence-based decision-support system

42 What is SDM? Safety Assessment Risk Assessment Family Strengths & Needs Assessment Reunification Assessment Case Process Risk Re-assessment Screening & Response Priority Assessment One decision: one tool How can research inform tool? Clear presumptive decision Overrides (measure!) TOOL DESIGN

43 Kinds of Evidence Do the tools work? Validity Construct validity Inter-rater reliability Do people use the tools? Completion rates Process changes Worker/ family surveys Do outcomes change? Outcomes

44 What is SDM? Safety Assessment Risk Assessment Family Strengths & Needs Assessment Reunification Assessment Case Process Risk Re-assessment Screening & Response Priority Assessment Use content (DEFINITIONS) to focus information gathering Think through with family, team Discuss results with family, team Plan collaboratively PRACTICE SKILLS

45 Risk assessment is about likelihood and probability The SDM Risk Assessment Answers this questions: Based on the family’s characteristics, how likely are they to abuse and neglect their children in the next 24 months?

46 © 2012 by NCCD, All Rights Reserved California Risk Study Results N = 2,511 investigations conducted in 1995, followed for two years. California Risk Assessment Validation: A Retrospective Study, 1998

47 “Final decisions should be left to formulas, especially in low-validity environments.” p. 225

48 Typical risk assessment presumptive decisions What is the probability of future abuse or neglect? LOW MODERATE HIGH VERY HIGH close open

49 © 2012 by NCCD, All Rights Reserved Risk Level by Initial Safety Assessment N = 67, California Combined Report

50 Important Distinctions Danger/ safety Immediate Serious Guides decisions about placement Risk There is time to change the course Any level of abuse/neglect Guides decisions about case open/close Need Conditions that appear to be barriers to increased safety and reduced risk Focus of intervention

51 Key Concept Threat of Danger? + Vulnerable child? - Protective Capacity? = “unsafe child”

52 Present danger Present danger is an immediate, significant and clearly observable family condition occurring in the present tense, already endangering or threatening to endanger a child. This phenomenon is also referred to as immediate harm; immediate severe harm; or imminent harm. It is important to understand that the primary criterion that qualifies present danger is what is happening that endangers a child is happening now; it is currently in process of actively placing a child in peril.

53 Impending danger Impending danger is associated with a child living or being in a state of danger; a position of continual danger. Danger may not exist at a particular moment or be an immediate concern but a state of danger exists. Impending danger is not necessarily active in the sense that a child might be hurt immediately like is true of immediate, present danger. When a child lives in impending danger one can expect severe harm as a reasonable eventuality. Impending danger refers to threats to a child’s safety that exist; are insidious; but are not immediate, obvious, or active at the onset of CPS intervention. Impending danger refers to threats that eventually are identified and understood upon more fully evaluating and understanding individual and family conditions and functioning.

54 Safety (Danger) versus Risk Safety  concerned about imminence and severe consequences due to things being out of control Risk  broad concept regarding whether something might occur if there is not intervention; risk may be low, moderate, high.

55 Vocabulary: Safe and Unsafe Child Safe child – “Vulnerable” children are safe when there are no “threats of danger” within the family or home OR when the caregivers possess sufficient “protective capacity” to manage or control any threats. Unsafe child – Children are unsafe when they are “vulnerable,” there are “threats of danger” within the family or home AND the caregivers have insufficient “protective capacities” to manage or control the threats, making outside intervention necessary..

56 Three Types of Protective Capacity Cognitive knowledge understanding perceptions Behavioral actions activities performance Emotional feelings attitudes identification

57 Safety Plans In home safety plan combination Out of home safety plan

58 Safety Plan actions and services that will temporarily substitute for lacking parental protective capacity to control the threat of danger

59 Current decision-making tools Intake (Minnesota intake screening guidelines) North Carolina Structured Intake report (very extensive) Safety assessment (first contact) Safety plans (first contact-Alaska example) Safety assessment (end of investigation and life of case); Safety assessment Nebraska (includes information standards; threshold criteria and supervisory review of safety assessment decision and process) Safety plan (not first contact) Risk assessment Risk re-assessment Protective capacity assessments Case plan

60 Current decision-making tools Family assessments (often for Differential Response) (Ohio example) Concurrent planning (Idaho) includes ICWA considerations; 3 month intervals up to 22 months. Educational neglect (home schooling) Idaho Pediatric symptom checklist (Maine)

61 Current decision making tools Maine signs of safety UNCOPE- screening tool for drugs/alcohol (Maine) Abandonment screening tool (Nebraska) Dependency screening tool (Nebraska) Idaho safety decision tree

62 Current Decision-making tools New resource – NRCCPS website

63 18 th National Conference on Child Abuse & Neglect April 18 – 20 Washington, D.C. Tamara Fuller University of Illinois Donald J. Baumann Saint Edwards University What We Know and Current Challenges

64 What We Know and Current Challenges: Overview Tying Tools and Practices into Improved Outcomes Implementation and Decision-Making What do we Need to Know: Challenges for Research

65 What We Know and Current Challenges: Tying Tools and Practices into Improved Outcomes The Assessments – Safety – Risk – Family What are the key decisions? Investigation Substantiation Service provision Placement into care Reunification Relative Care Adoption The Instruments – CERAP – SDM – Concept Guided (Texas and Georgia) – Other

66 Illinois Child Endangerment Risk Assessment Protocol Safety assessment instrument 14 safety factors that focus on readily observable and harmful behaviors Family strengths and mitigating circumstances Safety decision – Safe: No children likely to be in immediate danger of moderate to severe harm – Unsafe: A safety plan must be developed OR one or more children must be removed from the home because without the plan they are likely to be in immediate danger of a moderate to severe nature

67 CERAP Safety Plan – What actions have or will be taken to protect each child in relation to current safety concerns? – Who is responsible for implementing each plan component? – How will the plan be monitored and by whom? – What must happen in order to terminate the plan? – What time frames have been imposed by this plan?

68 CERAP CERAP intended as a “life of case” instrument, and should be completed at several case milestones: Initial investigation Investigation closure/case opening Ongoing safety plan monitoring Unsupervised visits Reunification Case closure

69 What We Know and Current Challenges: Reviewing of the Status of Decision-Making Research Factors that Relate to Different Decision Points Case characteristics Organizational characteristics External characteristics Decision-maker Characteristics

70 What We Know and Current Challenges: Reviewing of the Status of Decision-Making Research Factors that Relate to Different Decision Points – Where are the decision-making errors The threshold shift from child protection (more false positives) to family preservation (more false negatives) The middle of the safety and risk continuums probably has greater threshold variability than the extremes The Harm Evidence model for substantiation decision (Drake, 1998 suggests we must have: (1) sufficient risk of harm coupled with (2) evidence to show it. This would suggest a high threshold, more false positives and fewer false negatives Some evidence suggests the decision-making threshold for reunification is higher than for placement. This would indicate the possibility of more protection, more false positive and fewer false negative errors. – The fallibility of decision aids (e.g., risk and safety instruments) They only predict a small amount of the variability in decisions They don’t tell us what the errors are but they do tell us how much Important to focus our attention on understanding and practical utility

71 What We Know and Current Challenges: Issues With Instruments Evaluating Risk and Safety Assessment Instruments – Scientific Integrity Face validity Content validity Construct validity – Practical Utility Influence Accessibility Efficiency

72 Evaluating the CERAP Implementation evaluations have examined how workers using the CERAP Outcome evaluations have examined whether CERAP implementation has impacted child safety

73 Impact evaluation The CERAP was implemented statewide in December 1995 Therefore, a true experimental design to assess its impact on safety was not possible A time series analysis was used to examine differences in child safety before and after CERAP implementation Additional analyses attempted to rule out alternative hypotheses

74 Impact evaluation The outcome of interest is child safety, defined in these evaluations as the number and percentage of children with an indicated report of maltreatment within 60 days of an initial report

75 60-day recurrence rates ( ) Implementation Year

76 Extended Secular Trend Analysis To strengthen the validity of the inference about CERAP effectiveness, the trend analysis was extended several years before CERAP implementation to assess whether the decline in recurrence rates was a reversal of an earlier pattern or a continuation of past trends.

77 60-day recurrence rates ( )

78 CERAP Completion Rates by Milestone MilestoneIntact Family (n=273) Substitute Care (n=288) Within 24 hours after the investigator first sees the victim 93%69% Within 5 days of case opening or transfer 73%45% Every six months for intact family cases 67%n/a Commencement of unsupervised visits n/a48% Before an administrative case review 50%77% Prior to returning home n/a50% Prior to closing a case 87%100% When child’s safety is in jeopardy 90%81%

79 CERAP Section Completion Rates CERAP sectionIntact FamilySubstitute Care Safety Factor Checklist 94%86% Family Strengths 90%88% Safety Decision 95%91% Safety Protection Plan 90%78% Plan identifies specific actions 73%63% Plan identifies who will implement 73%59% Plan identifies who will monitor 38%39%

80 Summary CERAP completion by workers in the field is consistently high during the investigation (97%), moderately high at case transfer and case closing (70%), and much lower at other milestones. When completed, the CERAP tends to be completed in its entirety, although safety plans may not be completed according to instruction.

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82 18 th National Conference on Child Abuse & Neglect April 18 – 20 Washington, D.C. Donald Baumann Saint Edwards University Lisa Merkel-Holguin American Humane Association Group Decision-Making Process

83 Group Decision-Making Processes Overview Principles of Group Decision-Making Family Involvement Models Used in Child Welfare Decision-Making Lisa will discuss later this afternoon

84 Principles of Group Decision-Making: Assumptions Our decisions are influenced by groups: We have evolved to function in groups More hands makes for light work Interactions between group members will move initial extreme positions toward the middle Coming to consensus is a good way for groups that are already cohesive to make decisions Groups make better decisions than individuals

85 Principles of Group Decision-Making: Understanding Sources of Errors in Groups The Influence of Groups on Decisions: – Groups have influence even by their mere presence: We are affected by the presence of others, even unconsciously. We do better in the presence of others when we have learned how to do something well. When we have not, we do worse More Hands Makes for Lighter Work – Many hands can make for social loafing: Collective efforts result in less than the sum of individual effort under some circumstances (additive task, unchallenging tasks, not being held accountable, etc.) Interactions Make for Compromise – Interaction between group members with different positions produces group polarization: Interaction tends to intensify opinions for the like- and unlike-minded: They shift to more extreme positions because informational and normative influences.

86 Principles of Group Decision-Making: Understanding Group Influence Consensus Decisions – Consensus can produce groupthink: High cohesiveness, group insulation, the lack of procedures for appraisal and directive leadership leads groups to poorer decisions. Group preferences for supportive vs. challenging information, as well as the need for acceptance or approval, helps facilitate groupthink. Group vs. Individual Problem Solving – Though people feel more productive when solving problems in a group, people working alone or in two’s generate more good ideas. Large brainstorming groups are especially ineffective. – Among the ways this can be overcome are to combine group and solitary brainstorming, or have members first write then read (as in networked computers), rather than speak, then listen.

87 A Brief Exercise in Setting Action Thresholds

88 Case Vignette Mother tested positive for marijuana at the birth of the child. The child was not tested. Mother admits to using marijuana weekly. Mother and the biological father reside together and have all items to meet the baby’s basic needs. Mother has two other children who are not in her care. They were committed to the legal custody of mother’s mother. That arrangement was done privately with no Agency court involvement. The Agency did substantiate Neglect in that case, but the grandmother filed on her own. Mother has been diagnosed with Major Depressive Disorder. Mother is not receiving counseling services nor is she on medication. Mother states she uses marijuana to help with her mental health. Mother has been uncooperative with the Agency in the past, but has now agreed to do a drug and alcohol assessment. Mother has resided out-of-state and has just returned to their home town in November. Father is employed and is cooperative with the Agency. He participated in a drug and alcohol assessment after admitting to past use of marijuana. Mother would be the primary caretaker of the child while the father is at work. WOR’s home visit revealed no concerns about provisions for the baby, but some concerns about caring for the baby given mother’s mental health and history of drug usage.

89 The Process of Decision Making: The Threshold Concept If threshold low, W 1 needs little evidence before taking action. Assessed level of risk or need Low High Threshold W 1 Threshold W 2 W 2 Assessment. W 1 Assessment.  If threshold high, W 2 needs much evidence before taking action.  Even if they agree on the assessment,  they disagree about taking action. Yes No *From Len Dalgleish, 2000

90 Vocabulary: Safe and Unsafe Child Safe child – “Vulnerable” children are safe when there are no “threats of danger” within the family or home OR when the caregivers possess sufficient “protective capacity” to manage or control any threats. Unsafe child – Children are unsafe when they are “vulnerable,” there are “threats of danger” within the family or home AND the caregivers have insufficient “protective capacities” to manage or control the threats, making outside intervention necessary..

91 Transition slide subtitle Implementation Science: an introduction to key concepts

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93 National implementation Research Network

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95 From Paper to Performance EffectiveNot effective Effective Good implementation Good outcomes Poor implementation Poor outcomes Not effectiveGood implementation Poor outcomes Poor implementation Poor outcomes The “how” The “what” Fixsen et al (2005), p. 69

96 Implementing Best Practices Staff competence Organizational supports Leadership Fixsen & Blase, 2008 Outcomes/ evaluation Selection Training coaching Systems intervention Facilitative administration Decision support data system Technical Adaptive INTEGRATED & COMPENSATORY

97 Stages of implementation Exploration Design/ installation Initial implementation Full implementation InnovationSustainability Fixsen et al (2005),

98 West Virginia Safety Assessment and Management System Purpose: To implement a new (CPS) safety assessment and intervention system that: – Utilizes a change management approach to fully implement the system – Permanently changes practice in WV – Results in better outcomes for children ad families

99 SAMS Mission The successful implementation of SAMS resulting in an improved system of intervention based on consistent standards; focused and efficient information collection; and a family- centered approach that will improve caregiver and family functioning and increase safety, permanency and well- being.

100 SAMS A comprehensive CPS assessment process from initial intake to case closure and a more precise way to determine safety and respond to unsafe children Will improve safety outcomes for children and families by: – Focusing services more on safety – Focusing on the protective capacities of caregivers – Improving family engagement

101 SAMS: Key to Success Fidelity – using the decision-making model as designed. Blame cannot be placed on deficiencies of the model if it is not used as designed Understanding a form cannot change practice by itself Understanding that learning takes time.

102 West Virginia’s Application of NIRN Drivers Practitioner Selection All CPS supervisors and staff implementing the SAMS model according to the Implementation Schedule. Bureau decision to utilize the concept of “Special Forces.”  A group of Program Managers, Supervisors, and Trainers who are the primary purveyors of the model and responsible for building practice competence with staff and supervisors.  Members selected to represent the best and brightest of West Virginia’s Child Welfare workforce. Working on long-range plans for staff recruitment, selection and allocation including interviewing questions based on SAMS competencies.

103 West Virginia’s Application of NIRN Drivers Training Intense focus on staff training and professional development. – NRCCPS/ACTION trains and mentors SAMS Special Forces – ACTION and SAMS Special Forces train supervisors – SAMS Special Forces and supervisors train, mentor and guide staff – Targeted training prior to SAMS training on identified issues that could negatively impact SAMS implementation. – Targeted training after SAMS implementation on issues that need more clarification or understanding. - Ongoing skills training to improve interviewing and family engagement skills.

104 West Virginia’s Application of NIRN Drivers Supervision and Coaching Major focus: build the knowledge, skills, and abilities of CPS supervisors to supervise and coach their staff. – Receive SAMS training first that includes building supervisor competencies related to SAMS. – Attend SAMS training with their staff and take a lead role in case discussions. – Attend Action field consultation to discuss implementation of the model with actual cases. – Trained on the Action Supervisor Guide this summer that discusses consultative supervision. – Developing “mini-trainings” for supervisors to use in staff meetings.

105 West Virginia’s Application of NIRN Drivers Performance Assessment Mastery of a new system of decision making and delivery occurs over time with focused consultation, supervision and quality improvement. – Fidelity monitoring integrated into clinical case consultation through the use of a standardized review instrument. – Low fidelity areas addressed through Local Maintenance Plans and Special Forces consultation. – Ongoing evaluation to be integrated into OPQI reviews.

106 West Virginia’s Application of NIRN Drivers Systems Intervention Initially not enough attention paid to stakeholder perception and understanding. – Internal stakeholders BCF Managers, Supervisors, and Staff (Child Welfare as well as other program staff); DHHR Secretary and Other Bureaus; Special Forces; Implementation and Steering Committees

107 West Virginia’s Application of NIRN Drivers Systems Intervention – External stakeholders Legislature; Court System; Education System; Health Care System; Private Agencies; Service Providers; Advocacy and Professional Organizations

108 West Virginia’s Application of NIRN Drivers Systems Intervention Implemented activities in a variety of venues for increasing stakeholder buy-in for SAMS. – Communication with the Legislature including SAMS pocket cards. – SAMS training for the legal community conducted by Regional Attorneys. – Presentations at statewide conferences and events, like NASW. – Joint trainings with service providers and staff on safety services. – Presentations at the Court Improvement Board and judicial cross- training events. – Presentations at professional and community group meetings. – Web-based course providing an introduction to SAMS for all staff. – Discussion on SAMS required at all district and regional staff meetings.

109 West Virginia’s Application of NIRN Drivers Facilitative Administration Made changes to policies and procedures to align with SAMS, including creation of transitional policies. Organizational structure refined to support SAMS. – Director and Coordinator, funded through ACCWIC. – SAMS Implementation Team. – CPS Steering Team. – Feedback from the field brought back to Implementation and Steering to address barriers and facilitate implementation. – Restructuring of office procedures, unit procedures, and staff assignments at the local level.

110 West Virginia’s Application of NIRN Drivers Facilitative Administration State, regional, and district administrators prepared for SAMS through statewide meetings and training sessions. Pre- and post-implementation meetings held with every district administrator. Pre-implementation meetings with supervisors and administrators, conducted by Action. Post-implementation consultation with supervisors and administrators, conducted by Action and Special Forces. State, regional, and district administrators attend SAMS training and consultation with their supervisors and staff.

111 West Virginia’s Application of NIRN Drivers Data Decision Systems West Virginia’s SACWIS system, FACTS, currently making changes to the system to support the SAMS assessments. Because of delays to FACTS implementation, decision made to use a paper assessment system until FACTS changes could be made. Staff still responsible for entering NCANDS and AFCARS information into the current system until FACTS changes are complete.

112 West Virginia’s Application of NIRN Drivers Data Decision Systems SAMS Fidelity Monitoring System developed with ACCWIC to collect practice-relevant fidelity data to inform implementation. – Data system currently housed with ACCWIC during development but will transition to OPQI. – Data discussed at Implementation, Management, and Special Forces meetings to identify gaps and determine necessary actions to take. – Fidelity data will be integrated into dashboards along with federal outcomes data.

113 West Virginia’s Application of NIRN Drivers Data Decision Systems Dashboards developed with TA from NRC on Data and NRC Organizational Improvement. – Will measure CFSR outcomes and fidelity data by region, county, and judicial district. – Will show information on cases that do not meet standards for managers to use to evaluate and improve performance. West Virginia has initiated a bureau-wide effort to make better use of data in management decisions.

114 West Virginia’s Application of NIRN Drivers Leadership One of West Virginia’s strengths is the involvement of key leaders in the implementation of SAMS. – Commissioner and Deputy Commissioner take a lead role and actively participate in Implementation and Steering. – Reports on SAMS progress provided at each Leadership Team and Field Operations Management Team meeting. – SAMS discussion required at all regional and district meetings. - Commissioner, Deputy Commissioner, and Regional Directors visiting districts that are implementing and meeting with staff. – Community Services Managers attending training with their supervisors and actively involved in community education.

115 What do we need to know: challenges for research?  Basic Research on Decision Making in Child Welfare  Improved Assessment  Improvements Decision Making Information  Improving the Utility of Decision Making Supports  Workforce Development  Improved Implementation

116 Katherine Casillas The Kempe Center for the Prevention and Treatment of Child Abuse and Neglect Children’s Hospital Colorado Denver, CO

117 What effects decision making in child welfare, and what can we do to change negative influences?

118 Effects on the Decision Threshold Decision Threshold Influences Intervention Outcomes Case Factors Outcomes Individual Factors Organizational Factors

119 Case Factors The Family Level of Risk Income Number of Children Marital Status Race/Ethnicity The Child –Gender –Age –Behavioral Problems –Medical Problems –Race/Ethnicity

120 Effects on the Decision Threshold Decision Threshold Influences Intervention Outcomes Case Factors Outcomes Individual Factors Organizational Factors

121 Individual Factors Decision Making Skills (e.g., good judgment) Case Skills (e.g., fact finding) Knowledge of Placements Cultural Sensitivity (e.g., awareness)

122 Effects on the Decision Threshold Decision Threshold Influences Intervention Outcomes Case Factors Outcomes Individual Factors Organizational Factors

123 Organizational Factors Supervision Agency Policy Availability of Placements Workload

124 The influence of disproportionality and disparities

125 Are racial and ethnic groups disproportionately represented in Child Protective Services (CPS)? Can the process be changed?

126 The Continuum of Intervention Assessments and decisions are made at key points along the child protection continuum Each key decision point requires a specific decision and action

127 Understanding Trends  National level data can be misleading when attempting to understand and improve child welfare at the local level.  Racial disproportionality and disparate outcomes data must be analyzed and understood at the local level.  Disparity-related dynamics can be very different from one jurisdiction to the next, even when the jurisdictions share similar characteristics. 127

128 Enumerating Disparities and Disproportionality in Decision Points Population Based Denominator Ratios Based on data from one child welfare decision (e.g., new placements/population) Easiest to obtain Decision Based Denominator Ratios Based on data from at least two child welfare decisions (e.g., new placements/opened cases) Disparity: Relative to another group 128

129 Colorado Child Population / Race & Ethnicity Legend 2010 Population Under 18 BlackBlack alone, not Hispanic or Latino49967 WhiteWhite alone, not Hispanic or Latino HispanicHispanic or Latino AsianAsian alone, not Hispanic or Latino32225 AI_ANAmerican Indian and Alaska Native Alone, Not Hispanic or Latino7298 NH_OPACNative Hawaiian and other Pacific Islander, not Hispanic or Latino1557 MultiTwo or more races, not Hispanic or Latino47285

130 FY 2011 (Jul, June, ) Children in ReferralsChild PopulationDisparity Indices Type of AnalysisEthnicityChildren% of Eligible % of (Total Minus Missing) Number of Eligible Children % Of (Total Minus Missing) Rate Per 1000 of Eligible Children Compared with White Children in Referrals Total Black %6.7% % White %37.0% % Hispanic %26.7% % Asian6281.9%0.5% % AI_AN4305.9%0.3% % NH_OPAC %0.1% % Multi %2.4% % Missing33363 *

131 FY 2011 (Jul, June, ) Children in AssessmentsChild ReferredDisparity Indices Type of AnalysisEthnicityChildren% of Eligible % of (Total Minus Missing) Number of Eligible Children % Of (Total Minus Missing) Rate Per 1000 of Eligible Children Compared with White Children in Assessments Total Black %7.1% % White %40.6% % Hispanic %30.8% % Asian %0.6%6280.5% AI_AN %0.4%4300.3% NH_OPAC %0.2%1800.1% Multi %2.7% % Missing %17.8% %

132 FY 2011 (Jul, June, ) Children in Substantiated CasesChild AssessedDisparity Indices Type of AnalysisEthnicityChildren% of Eligible % of (Total Minus Missing) Number of Eligible Children % Of (Total Minus Missing) Rate Per 1000 of Eligible Children Compared with White Children in Substantiated Cases Total % Black %8.6% % White %46.3% % Hispanic %37.7% % Asian7319.2%0.7%3810.6% AI_AN7329.9%0.7%2440.4% NH_OPAC1716.2%0.2%1050.2% Multi %3.7% % Missing2472.1%2.3% %

133 FY 2011 (Jul, June, ) Children in Removed Within 90 daysChildren Served Disparity Indices Type of Analysis EthnicityChildren % of Eligible % of (Total Minus Missing Number of Eligible Children % Of (Total Minus Missing Rate Per 1000 of Eligible Children Compared with White Children in Removed Within 90 days Total Black %3.6% % White %16.4% % Hispanic %13.2% % Asian 923.1%0.1%3919.2% AI_AN %0.5%6129.9% NH_OPA C 342.9%0.0%716.2% Multi %1.6% % Missing 42.6%0.1%1522.1%

134 FY 2011 (Jul, June, ) First Placement Congregate CareChildren RemovedDisparity Indices Type of AnalysisEthnicityChildren % of Eligible % of (Total Minus Missing) Number of Eligible Children % Of (Total Minus Missing) Rate Per 1000 of Eligible Children Compared with White First Placement Congregate Care Total Black3213.1%0.5% % White1009.0%1.5% % Hispanic717.9%1.0% % Asian 919.2% AI_AN % NH_OPAC 316.2% Multi43.6%0.1% % Missing 42.1%

135 FY 2011 (Jul, June, ) First Placement Foster CareChildren RemovedDisparity Indices Type of AnalysisEthnicityChildren % of Eligible % of (Total Minus Missing) Number of Eligible Children % Of (Total Minus Missing) Rate Per 1000 of Eligible Children Compared with White First Placement Foster Care Total Black %1.8% % White %8.5% % Hispanic %6.8% % Asian444.4%0.1%919.2% AI_AN2683.9%0.4%3129.9% NH_OPAC133.3%0.0%316.2% Multi6660.0%1.0% % Missing4100.0%0.1%42.1%

136 FY 2011 (Jul, June, ) First Placement Other CareChildren RemovedDisparity Indices Type of AnalysisEthnicityChildren % of Eligible % of (Total Minus Missing) Number of Eligible Children % Of (Total Minus Missing) Rate Per 1000 of Eligible Children Compared with White First Placement Other Care Total Black62.4%0.1% % White252.2%0.4% % Hispanic202.2%0.3% % Asian111.1%0.0%919.2% AI_AN13.2%0.0%3129.9% NH_OPAC 316.2% Multi43.6%0.1% % Missing 42.1%

137 FY 2011 (Jul, June, ) First Placement Relative CareChildren RemovedDisparity Indices Type of AnalysisEthnicityChildren % of Eligible % of (Total Minus Missing) Number of Eligible Children % Of (Total Minus Missing) Rate Per 1000 of Eligible Children Compared with White First Placement Relative Care Total Black8333.9%1.2% % White %5.9% % Hispanic %5.0% % Asian444.4%0.1%919.2% AI_AN412.9%0.1%3129.9% NH_OPAC266.7%0.0%316.2% Multi3632.7%0.5% % Missing 42.1%

138 What can we do?: Explaining Removals at the Worker Level Disparity Index Percent on Caseload Skills (AA only)Removals Workload (worker) Community Resources (worker) Family Poverty Family Risk Level AA Only

139 Organizational Interventions and the Removal Rates for African American Children Pre and Post In four of the five counties where the effort has been most intense have lowered African American removal rates

140 Discussion Are there key decision points where we should be focusing our attention? What are the explanatory factors that we should attend to? What are some suggested policy revisions that could mitigate factors in child welfare? How do we make progress in integrating and improving clinical/professional judgment in the assessment process? What are the best ways to influence decision actions?

141 Decision Making Café Please Self Select a Discussion Topic – Table 1 – Tools – Table 2 – Policy and Workforce – Table 3 – Implementation – Table 4 - Research

142 Family Group Decision Making and Family Engagement in Decision Making

143 What it is: An opportunity for the family group to gather all the needed information about the agency’s concerns in order to make well-informed decisions. Family-driven decision making planning Family as the expert What it is not: Mediation Conflict resolution process An opportunity for families to come together to hear agency professionals’ solutions Guidelines for Family Group Decision Making in Child Welfare, Description of the “It”

144 Family Involvement and Decision Making Models: – Family Group Conference or FGC (New Zealand, 1989) – Family Unity Meeting Model or FUM (Oregon, 1990) – Family Team Conferencing (FTC) as developed by the Child Welfare Practice and Policy Group – Team Decision Making (TDM) – Family Team Meetings (FTM) – Rapid Case Planning Conference – Hybrid Models that combine FGC, FTC, FUM, and other models Slide 144 Terminology

145 1.An independent Coordinator 2.Family group as key decision making partner—resources put towards finding and preparing 3.Private family time 4.When plan meets agency concerns, preference to family plan 5.Services and resources available to meet agreed upon plans American Humane Association (2008) 145 Five Core Elements of FGDM

146 Family Voice in Decision Making System Voice in Decision Making Family Involvement Continuum 1 1 Taken from: Merkel-Holguin, L. and Wilmot, L. (2005). Analyzing family involvement approaches in J. Pennell & G. Anderson (Eds.), Widening the circle: The practice and evaluation of family group conferencing with children, young persons, and their families. Washington, DC: NASW Press. May be reproduced and distributed with appropriate citation. 146

147 Family satisfaction – Conflict decreased – Felt empowered Worker satisfaction – Felt children would be better protected and greater confidence in child safety Improved relationships with child welfare agency – Felt listened to – Better understood agency’s concerns 147 Participation Satisfaction and Communication Benefits

148 More quickly linked to services Received more individualized resources More likely to receive counseling for children and mental health and parenting services for adult caregivers 148 Resources for Families

149 Placements – More stable – Less likely to be placed in institutions – More likely to be placed with extended family Beneficial impacts: more stability, better adjustment, ties to culture and traditions – Fewer temporary moves – More likely to maintain connections to siblings – Achievement of permanency sooner and less time in out- of-home care Improved child safety Reduced disproportionality 149 Child welfare outcomes


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