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The Decision-Making Ecology

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Donald J. Baumann
Saint Edwards University
Len Dalgleish
University of Stirling, UK
John Fluke
Child Protection Research Center,
American Humane Association
Homer Kern
Child Welfare Consultant
Dec i sion-M a k i ng ec ol og y
THE
1
e authors wish to thank James Mansell for his thoughtful comments in review of this manuscript.
1
Foreword. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
Decision-Making Ecology Framework. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
The Psychological Process of Decision-Making:
The General Assessment and Decision-Making Model (GADM). . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
Applications: The DME and Thresholds along the Continuum . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
Applications: The DME and Outcomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
Applications: Training in Threshold Placement and Threshold Differences . . . . . . . . . . . . . . . . . . . . 10
Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
De c i sion-M a k i ng ecol og y
THE
Published March 2011
© 2011 American Humane Association
Suggested citation
Baumann, D. J., Dalgleish, L., Fluke, J., & Kern, H. (2011). The decision-making ecology.
Washington, DC: American Humane Association.
T h e D e c i s i o n - M a k i n g e c o l o g y
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For e word
In 1995, the authors developed the Decision-Making Ecology to help us understand a series of studies we had
conducted on decision-making and its consequences. Our findings were published as part of a 12-chapter
report we provided to the Childrens Bureau (Baumann, Fluke and Kern, 1997). Since that time we have
presented the model at numerous conferences and have had many requests for that report. In addition, we
have collaborated with others, beginning with the International Society for the Prevention of Child Abuse and
Neglect (IPSCAN) meeting in Auckland, New Zealand in 1998 and continuing through the following decade. We
then talked with other researchers throughout the United States and globally. This culminated in two decision-
making meetings in Denver at the American Humane Association in 2008 and 2010.
This monograph stems from those synergistic exchanges of ideas as our attempt to reach a broader Child
Welfare audience by introducing the model into the more formal literature. Our goals are to update what we
wrote early on, clarify the concepts in the model, and integrate Dalgleish’s (1988; 2003) work on the General
Assessment and Decision-Making Model within the Decision-Making Ecology Framework. Dalgleishs
contribution to the present framework cannot be overstated: The notion that an assessment needs to be
considered as distinct from a threshold for judgment has become central to the Decision-Making Ecology
and has helped us understand some of our recent findings. We dedicate this monograph to the memory of our
colleague, teacher, and friend, Len Dalgleish.
T h e D e c i s i o n - M a k i n g e c o l o g y
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In t roduct Ion
Over three centuries ago, beginning in the Age of
Reason, philosophers championed rational thought.
Despite the writings of Freud and others in the late
19th and early 20th centuries, the notion of rational
thought and especially rational decision-making
remained firmly entrenched in academia through the
mid 20th Century. According to two popular theories
of the time, Social Exchange Theory (Homans, 1958),
and Attribution Theory (Kelly, 1973; Jones and Davis
1966), humans calculated the costs and benefits
of various options before making a decision (the
former) and weighed personal and situational forces
before determining the cause of someone’s actions
(the latter). Both were formidable models of rational
decision-making.
During this same period, the psychological
landscape was changing. Simon (1956 & 1959),
who later received a Nobel Prize for his efforts, was
demonstrating that reason had its limits, proposing
a new “Bounded Rationality” model of decision-
making. Tversky and Kahneman (1974), the latter of
whom also received the Nobel Prize (see Kahneman,
2002), were suggesting that reasoning is even more
limited than we had thought. They provided us with
ample demonstrations of certain types of errors in
decision-making, suggesting that humans applied a
number of heuristics - - mental strategies that speed
decision-making - - under conditions of uncertainty
that often led to error. At this same time, even the
unconscious was making a comeback, stripped of
its psychoanalytic trappings (Bowers, 1984). By the
later part of the 20th century and the early part of the
21st century the idea of the rational decision maker
seemed to have given way to a less rational one. Even
so, the exchange can hardly be viewed as stable since
whether the use of heuristics is as error prone as had
been previously thought is now a matter of debate
(Gigerenzer, 1991; 1993; 1994; 1996 & 2005; Kahneman
and Tversky, 1996) and the debate surrounding
rational decision-making will continue to expand into
what Kahneman (1991) refers to as “third generation
research.
A number of other important theoretical and
empirical decision-making frameworks have also
been advanced in the sciences. These have included
foundational work in the field of judgment and
decision-making by Hammond (1955), and Edwards
(1954 & 1961). The field has also benefitted from
input from many diverse fields such as economics
(e.g., Simon, 1959), artificial intelligence (e.g., Weiss,
Kulikowski, Amarel and Sar, 1978), psychology (e.g.,
Tversky and Kahneman; 1974), engineering (e.g.,
Triantaphyllou and Mann, 1995), medicine (e.g.,
Hunink, Glasziu, Siegel, Weeks, Pliskin, Elstien, and
et. al., 2003), and even meteorology (e.g., Monahan
and Steadman, 1996). These contributions can
provide insight and understanding about decisions
made by Child Welfare protective services. Yet, the
Child Welfare field has struggled to benefit from the
knowledge gains and progress regarding decision-
making research. Instead, it has focused on correcting
errors through building risk and safety instruments
rather than understanding the source of the errors.
Two Child Welfare models in the literature are
noteworthy, however. The first is an early decision-
making model by Stein and Rzepnicki (1983). This
model outlined the systematic goals of Child Welfare
(e.g., safety and family preservation), pointing out
some key processes that included decision-making
along with important domains of information
(e.g., family, agency, courts, law, etc.). The model
broadly sketched the landscape but got little traction
empirically. The second, a systems approach by
Munro (2005), regards human error as the starting
point for understanding decision-making. It takes
into account individual factors such as skills and
knowledge, resources and constraints such as analytic
vs. intuitive judgment, along with the organizational
context in which decisions are made such as changes
in thresholds.
The Munro model is compatible with the one we
present here. As indicated, the Decision-Making
Ecology was first described in the mid 1990’s
(Baumann, et. al., 1997). Like Munro’s model, it
also takes human error as the starting point for
understanding decision-making and suggests that
decisions need to be understood within their context.
In the discussion that follows we first present the
Decision-Making Ecology Framework along with
a description of the Decision-Making Continuum
and a presentation of the General Assessment and
Decision-Making Model (GADM) that explains
the psychological process of decision-making. We
then conclude with illustrative applications of the
concepts.
T h e D e c i s i o n - M a k i n g e c o l o g y
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decIsIon-Ma k Ing ecol ogy Fr a Me wor k
The Decision-Making Ecology framework presented
here represents an effort to advance the field of Child
Welfare decision-making using the knowledge gained
from the decision-making sciences. It is a framework
for organizing decision-making research in Child
Welfare and places the topic squarely in the context of
actual protective-service operations in this field. This
is done because decisions take place within an agency
culture where a systemic context combines with the
case decisions made by the management and staff of
the agency. This model drawn initially from thinking
based on child protection screening research (Wells,
Fluke, Brown, 1995) has been successfully applied to
the problem of disproportionality (Baumann, Fluke,
Graham, Wittenstrom, Hedderson, Riveau, et. al.,
2010; Fluke, Chabot, Fallon, MacLaurin, Blackstock,
2010; Rivaux, James, Wittenstrom, Baumann, Sheets,
Henry, et. al., 2008.) the substantiation decision
(Fluke, Parry, Shapiro, Hollinshead, Bollenbacher,
Baumann, and et. al., 2001), the decision to place
children into care (Graham, Fluke, Baumann, and
Dettlaff, in preparation; Fluke, et. al., 2010), burnout
and turnover (Baumann, Kern, McFadden, and Law,
1997) and the decision to reunify children with their
families (Wittenstrom, Fluke, and Baumann, in
preparation).
As shown in Figure 1, the systemic context for
decision-making includes a set of influences displayed
as ovals. These cover the range of case, external,
organizational, and individual factors that combine
in various ways to influence decisions and outcomes.
These influences can be divided into dimensions that
represent their important features, and decisions can
be understood as a part of this entire context.
For example, case information regarding an incident
of maltreatment is necessary for a caseworker to make
informed assessments and decisions, yet some of the
assessments and decisions depend on external factors,
such as law translated into policies that govern what
constitutes an appropriate response. Furthermore,
the translation of such standards by organizational
management, and their use by staff, will vary as a
function of individual decision maker factors which
include knowledge and skill, as well as the actual
and perceived costs and benefits (outcomes) of the
decision to the decision maker, the client and/or the
agency.
Decision
Making
Figure 1
Decision-Making Ecology
Outcomes
Organizational
Factors
External
Factors
Decision Maker
Factors
Inuences Decision Outcomes
Case Factors
T h e D e c i s i o n - M a k i n g e c o l o g y
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Consider first some evidence on case factors. In
two studies (Rivaux, et. al., 2008; Dettlaff, Rivaux,
Baumann, Fluke and Rycraft, in preparation)
researchers were able to show that both the
substantiation decision and placement decision
were affected by ethnicity, risk, and poverty in
predictable ways. Findings that concern individual
factors (Baumann, et. al., 2010) indicated that
disparate placement decisions can be ameliorated
by caseworkers having higher case skills, especially
those involving cultural awareness. Consider, too,
organizational factors. Having a higher proportion
of African Americans or Hispanics on one’s caseload
(exposure) also ameliorates disparate placement
decisions for African Americans or Hispanics,
respectively. Finally, consider external factors. Fluke
and his colleagues, using the Canadian incidence
data, provide support for the possibility that the lack
of community resources was one of the sources of
placement disparities among Aboriginal Children
(Fluke, et. al., 2010). These findings illustrate that
sources of decision-making errors can be empirically
understood and their remediation made possible
within the Decision-Making Ecology.
The diamond in Figure 1 represents caseworker
decision-making. The three features of decision-
making in Child Welfare are: 1) the range of decisions
made by the caseworker, referred to as a Decision-
Making Continuum, 2) the psychological process
of decision-making, and 3) the consequences of the
decision. The key feature of the Decision-Making
Continuum shown in Figure 2 is that it runs through
the episodes, or stages of service, involved in cases
processed by Child Welfare. In fact, one way to think
about the job of a caseworker is as the coordinator of a
Decision-Making Continuum.
This continuum starts at intake (“Do I initiate an
investigation or not?”) and ends at case closure
when all children in a family are deemed to be safe
from maltreatment in the foreseeable future. It is
not uncommon for a very large number of minor
decisions to be made leading to each of the major or
key decisions.
The relative size of the cylinders in Figure 2 can be
viewed as representing case volume and the length
of the cylinders’ duration. The episodes are shown
at the top of the continuum and cover caseworker
decisions that range from intake (1) through service
provision (2) and removal (3) for the first incident and
consequently labelled as 4, 5 and 6 for the
second incident.
(1)
(2)
(3)
(4)
(5)
(6 )
ex I t
ex I t
In ta k e
In v e stIg at Ion
ser v Ic e s /reMova l
1st IncIden t
2n d IncIde n t
Figure 2
Flow of Clients through the Decision Making Continuum
T h e D e c i s i o n - M a k i n g e c o l o g y
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the Psychol ogIc a l Proce ss oF decIsIon-Ma k Ing : the
gener a l as sessMen t a nd decIsIon-Ma k Ing Mode l (gadM)
The psychological process of decision-making has
three important features. First, it is useful to make
a distinction between a judgment and a decision. As
shown in Figure 3, a judgment is an assessment of a
situation given the current case information.
This judgment may be about the amount of risk or the
strength of evidence or overall level of concern. Each
of these can be an estimate along a dimension ranging
from low to high. A decision addresses whether or not
to take a course of action. So the General Assessment
and Decision-Making (GADM) model’s alternative
title could be “A General Model for Assessing
Situations and Deciding What to Do about Them.
In this model, we assume a threshold for action that
turns an assessment of a situation into a decision-
about action.
Thus, a second important feature of the psychological
process of decision-making is a decision threshold.
A decision threshold refers to the point at which the
assessment of the case information (e.g., amount and
weight of evidence) is intense enough for one to decide
to take action. This decision threshold is a personal
“line in the sand.” It is influenced by the experiences
and history of the decision maker. These are both
their actual or vicarious experiences and their
interpretation of external factors and organizational
factors in the Decision-Making Ecology. In fact their
own internal factors might be at odds with these
external or organizational factors. The theoretical
base for the threshold concept is Signal Detection
Theory (Swets, Tanner, and Birdsall, 1955) and, more
recently, Dalgleish (1988 & 2003), who proposed the
GADM model in the child-welfare field that makes
the important distinction between assessment and
action.
A third component in the process of decision-making
is a shift in this threshold. A shift in threshold refers
to a change in the amount of evidence deemed to
be sufficient; a threshold shift would be involved
if various features of the Decision-Making Ecology
changed the basis for the decisions that fall along
the decision-making continuum. One organizational
influence that would alter the decision would be a
policy that dictates which cases would be accepted
or should be attended to immediately (e.g., age
and injury requirements for cases accepted and
prioritized). An individual factor influencing a
threshold shift might be experience. For example, a
new worker might tend to render more afrmative
decisions to be on the “safe side.” Conversely, an
experienced worker may know of — and be wary
of — the consequences for children placed in the
fostering and adoption system. Factors such as these
would change the thresholds of the individuals and
also impact the volume of cases moving through the
Decision-Making Continuum.
Fa c t or s
In F lu e nc I n g
asses s M e n t.
in f or M aTion froM
cur r ent si TuaT ion
be ing Ju D ge D
facTors
in f lu e nc i ng
th r e shol d For
act Ion
in f or M aTion
froM T h e
Decision- Ma k ers
Pe r sPec T i v e
hIgh
low
ass es sMen t
Assessment Dimension:
e.g. Risk or ‘Level of Concern’
If the Assessment is ABOVE the Threshold, the ACTION is taken.
If the Assessment is BELOW the Threshold, then NO ACTION is taken.
thr e shhold
Figure 3
A General Modle for Assessing the Situation and Deciding what
to do about it – Dalgleish
T h e D e c i s i o n - M a k i n g e c o l o g y
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aPPlIc atIons : the dMe
a nd thr e sholds a long t he
contIn uuM
The model can be applied at each of the key decision
points of the Decision-Making Continuum: At Intake
(Dalgleish, 2003), at Removal (Dalgleish, 1988),
and at Reunification (Dalgleish and Newton, 1996).
Consider the intake and the removal decisions. The
threshold for each requires adequate information to
make an assessment. The threshold may be higher
for removal, compared to that required at intake, and
this is reflected in the size of the cylinders in Figure
2 which indicate that as one moves further along the
continuum there are fewer children in the system.
Furthermore, at the right end of the Decision-Making
Continuum one might not only expect a higher level
of information needed to make an assessment, but
different types of information as well. For example,
an intake worker may primarily consider information
about the allegation, whereas an investigator making
a removal decision may additionally consider the
amenability of the situation to intervention, given
the nature of the risk. For reunification, Dalgleish
and Newton (1996), found that information about the
sustainability of change in the family was a factor
influencing the assessment of risk. Thus, different
case information needed to make an assessment
at different stages along the Decision-Making
Continuum is a major factor and it is possible that
the assessment and the threshold for a decision can
be the same, particularly at the extreme ends of the
risk continuum. However, other influences in the
Decision-Making Ecology can alter the decisions
along the Decision-Making Continuum. For example,
lowered appropriations or the passage of legislation
limiting the length of time a child may remain in
foster care (external factors) might cause the agency
to alter its policy (an organizational factor) on the
permanency planning for children in care. This would
result in a threshold shift for reunification, even under
the same assessment conditions that might have
existed prior to the policy change.
aPPlIc atIons : the dMe a nd
outcoMe s
A final feature of the Decision-Making Ecology is the
outcome of these decisions. Outcomes are represented
by the rectangle in Figure 1. The large reversed arrows
in Figure 1 indicate the assumption that, to the degree
that the consequences of decisions can be presumed,
perceived, or known, thresholds may shift through
the four influences of the Decision-Making Ecology:
case, organizational, external and individual decision
maker factors.
In the Decision-Making Ecology, outcomes are
viewed from three perspectives having to do with
consequences to the client, the decision maker and
those external to the agency. All affect the factors in
the Decision-Making Ecology, and thus the decision
thresholds. The more familiar perspective involves
outcomes to the client. Safety, permanency, and well
being are the best examples. However, another more
immediate consequence is to the decision maker. In
decision theory this is typically considered the more
immediate utility of a decision. First, it can affect
changes in decision thresholds. Consider, for example,
how a decision to close a case that results in a child
fatality would affect a decision maker’s threshold.
Second, these consequential decisions (among other
factors in the DME) can affect whether or not a worker
stays with the agency (Baumann, Kern, McFadden
and Law, 1997). Finally those consequential outcomes
that are external to the agency can include public
anxiety, media scrutiny and legislative scrutiny. Child
fatalities often generate all three. These outcomes
are all related in the sense that they can operate
simultaneously. For example, a serious recurrence
of maltreatment impacts the child and the family,
and the caseworker who may have closed the case.
Both the family and caseworker could be held
accountable in one sense or the other and all would
experience the event itself in a negative way. The
scrutiny by those external to the agency would bring
additional pressure to bear and would impact the
accountability of the agency as well. This might well
involve legislative and or policy changes (external or
organizational factors) that would change thresholds
for taking action. Even in the absence of actual events,
the decision makers perception that such outcomes
could occur undoubtedly influences thresholds.
T h e D e c i s i o n - M a k i n g e c o l o g y
9
The decisions that lead to these consequential
outcomes are fraught with uncertainty because the
decision maker cannot avoid the possibility of error.
If action is taken, the decision maker might be wrong
and if action is not taken they might be wrong as well.
Hammond (1996), calls it the “duality of error.” Table
2 below reflects these errors. It shows the four possible
outcomes for the decision to remove the children
from their home and place them in care: Two types of
correct outcomes and two incorrect ones. The box in
the upper left-hand corner shows a correct decision
to remove the child from the home. The box in the
lower right corner shows a correct decision to not
remove the child from the home. The box in the upper
right-hand corner shows that errors resulting in false
positives can result in an unwarranted placement in
care because the child was safe. The box in the lower
left-hand corner indicates that a lack of action can
result in harm to the child. One or the other of these
errors is unavoidable. Moreover, the consequences of
these errors may be considered as symmetrically bad
and they sometimes are (McMahon, 1998).
That is, a false positive error where the child is
mistakenly placed in care may be considered as
dreadful as a false negative error where the child is
not placed and re-harmed. However, they are often
asymmetrical depending on who is affected by the
error. An unwanted placement may be only annoying
compared to a child who is seriously re-harmed.
Further, agencies place greater emphasis on one
source of error over another, moving away from one
kind of error over another and willing to indulge the
opposite kind of error (Mansell, 2006).
Table 2. Outcomes for decisions to take action or not: The four-fold table.
Decision: YES
Remove
Hit
Correct outcome
False Alarm
Error
Damned if you Do
False Positive
Decision: NO
Not Remove
Miss
Error
Damned if you Dont
False Negative
Correct No
Correct outcome
T h e D e c i s i o n - M a k i n g e c o l o g y
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aPPlIc atIons : tr a InIng I n thre shol d Pl ace Me nt a n d
thr eshold dIFFere nces
Different caseworkers will value these consequences
differently. To demonstrate this and roughly identify
threshold placement, a decision maker could
answer this question: “Given that you cant avoid the
possibility of error, which one do you want to avoid
the most?” At one level the decision is nearly as simple
as that. However, it might be difficult for the decision
maker to articulate why he or she prefers to avoid
one error over another. The number of stakeholders
on the decision helps explain this dilemma. In
child protection they include: The child, the family,
the caseworker themselves, their work unit, their
supervisor, their agency, other professionals, the
courts, and society in general. For each of these
stakeholders, and for each outcome, there are sets of
consequences. Which raises the question: “Do the
various people working in child protection differ in
the values they place on consequences?” The answer
is “yes.
A memorable example came to one of the authors
(Dalgleish) during a workshop on thresholds for
people working in multidisciplinary child-protection
teams. After going through the process of making
the consequences explicit for different stakeholders,
a family physician said that he wanted to avoid
“false alarms” (false positives) because of the harm
to families falsely accused of child abuse. This was
vehemently challenged by a social worker from
a public children’s hospital who wanted to avoid
“misses” (false negatives) because she had seen many
dead and injured children.
In terms of the GADM model, the physicians
threshold was high and he may require a higher level
of risk and thus greater concern before he took action.
The social workers threshold was low and thus lower
levels of risk can generate high levels of concern
requiring her to take action. To make things equal in
this example, let us assume that they are both told
about a case and given the same case information.
Assume also that they have been well trained in an
assessment tool and have jointly assessed the case to
have moderate levels of risk.
Figure 4 indicates why the physician would not want
to take action and the social worker would. They dont
differ in their assessment of the case but they do differ
in their decision to take action or not. In the GADM
model this is called “decisional conict.” Alternatively,
but though less commonly, (Rossi, Schuerman,
and Budde, 1999), two people might have the same
threshold for action but differ in their assessment
of the case factors and the integration of the case-
factor information into a summary assessment-like
risk. The GADM model refers to this as “judgmental
conict.” Judgmental conflict is easier to resolve since
it requires both people to review the case factors and
agree on what ones to include in their assessment,
as well as the relative importance of the case factors.
Decisional conflict is much more difficult to resolve
since it depends on the relative value decision makers
place on the consequences of the possible outcomes
as discussed above.
Figure 4: Applications of the reshold Concept
No
High
Low
Ye s
reshold
Physician
Physician
Assessment
Social
Worker’s
Assessment
reshhold
Social Worker
• If threshold low, needs
little evidence before
taking action.
• If threshold high, needs
much evidence before
taking action.
• Even if they agree on the
assessment.
• ey disagree about
taking action.
T h e D e c i s i o n - M a k i n g e c o l o g y
11
suMM a ry a n d conclusIons
In this brief monograph, we have attempted to present
a case for the usefulness of the Decision-Making
Ecology combined with the General Assessment
and Decision Model. We began by making the
point that the field of Child Welfare has been slow
to take advantage of decision-making frameworks
— a dilemma that has impeded our efforts at
understanding errors in decision-making and their
context. This concern is important because if we fail
to learn from the errors we make, we limit the options
for how to address these errors in the future.
We then presented what we have learned thus
far using this framework. For example, we have
learned that the DME can be applied to a number
of contexts, including the substantiation, removal,
and reunification decisions — all of which are key
decision-making points along the Decision-Making
Continuum. It is also applicable to the context of
social problems such as disproportionality since
disparate decisions at key decision points can increase
overall disproportionality. Indeed, key factors in the
DME, such as case, individual, organizational, and
external factors, are found to increase or decrease
disparities and allow us to better understand it.
The DME also contains the General Assessment
and Decision-Making (GADM) Model which helps
to explain the psychological process of decision-
making more fully. In that regard, three psychological
processes were described. The first was the distinction
between the psychological process of assessment and
that of deciding to take a course of action. The point
being that, although the assessment (e.g., of case
factors) might be the same, individuals may differ in
the action they decide to take. This second process
is known as a decision threshold — a factor that we
again note varies among individuals based upon their
various experiences with factors in the DME. The final
important psychological process is that this threshold
can shift. Mansell (2006) provides a good example
of such a shift. He describes threshold changes in
the New Zealand Child Welfare system as a function
of the degree to which family preservation or child
protection is emphasized by policy makers over time,
which can be related to outcome concerns over child
safety in dynamic balance with the costs of services.
We also applied the Decision-Making Ecology
in this monograph to three situations as further
demonstrations of its usefulness. In the first, we used
the decisions along the Decision-Making Continuum
as an example of decision makers having different
thresholds for different decisions. The intake decision
was used as an example of a low threshold, relative
to the removal decision where higher thresholds for
taking action are more likely. A related application
that helps explain this difference is the outcomes, or
consequences, to the client, the decision maker and
those external to the agency. In this application we
introduced two types of errors that decision makers
try to avoid; false positives and negatives. Here we
noted that depending on the value of avoiding either
type of error, thresholds may differ. We also noted
that agencies place different values on avoiding
different types of errors and accepting others. Our
nal application pertained to training. There we
discussed an exercise in which different outcomes
carried different consequences for participants and
showed that one error was more likely to be avoided
over another, depending on the consequences to the
decision maker.
All of this has strong implications for policy and
practice. From a policy perspective, knowing the
source and magnitude of errors and what factors in
the DME may mitigate these errors allows clearer and
more precise policy to be written, and resources to be
better targeted. If, for example, it is known that the
amount and mixture of cases on a workers caseload
affects his or her decisions, explicitly designed
experiences with different caseload mixes can be
structured as part of on-the-job-training. Importantly,
exposure to African American clients (Baumann, et.
al., 2010) mitigates these decisions implying that such
exposure should be a part of training.
Practice might also be affected more directly by
training programs that target specific errors and how
they are mitigated. For example, one source of error
uncovered by Dettlaff and his colleagues (Dettlaff, et.
al., in preparation) and by Rivaux and her colleagues
(Rivaux, et. al., 2008), is the fundamental attribution
error. This error appears to lie behind disparate
decisions to substantiate and to place children in care.
It seems that workers may attribute poverty to the
person, rather than to the situation and are thus more
likely to have a lower threshold for decision-making
for African Americans than Anglos. More explicit
and experiential training with regard to poverty and
risk may be beneficial in improving self-awareness
concerning the fundamental attribution error.
In conclusion, in the decade or so since we began
working from within the Decision-Making Ecology
framework we have seen it bear fruit as we have
indicated herein. We, along with the colleagues we
have worked with over this period of time, would
urge the field of Child Welfare to devote more effort
to empirically understand the context of decisions
that are made, the psychological process of decision-
making, and the sources of errors that are made. The
outcome should be a major improvement in decision-
making in Child Welfare.
T h e D e c i s i o n - M a k i n g e c o l o g y
12
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De c i sio n-M a k i ng ec ol o g y
THE
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© 2011 AMERICAN HUMANE ASSSOCIATION
... Algunos modelos teóricos que podrían ser útiles respecto de los procedimientos de decisión de emparejamiento son el Modelo Ecológico de Toma de Decisiones (Baumann et al., 2011) y el Modelo de Juicio y Proceso de Decisiones en Contexto (JUDPIC; Benbenishty et al., 2015) los que otorgan un marco teórico para la evaluación y la toma de decisiones en infancia. En ambos modelos se da importancia a factores del caso, factores organizacionales, factores externos y factores relativos a quien toma la decisión 2011;Zeijlmans et al., 2018). ...
... En ambos modelos se da importancia a factores del caso, factores organizacionales, factores externos y factores relativos a quien toma la decisión 2011;Zeijlmans et al., 2018). Cabe destacar que, los modelos descritos previamente permiten incorporar elementos del contexto a la toma de decisiones y se ha investigado su utilidad en diversas decisiones, tales como la determinación de substanciación (Dettlaf, 2015) y la predicción de maltrato recurrente (Baumann et al., 2011;Fallon et al., 2015;Maguire-Jack & Font, 2014). ...
... Se realizó una entrevista semiestructurada a las y los profesionales, que fue construida con la asesoría de dos expertas en materias de infancia y que tuvo por objetivo conocer en profundidad el proceso de toma de decisiones relacionado con el emparejamiento que realizan las y los profesionales. Los temas que se incluyeron en la entrevista estuvieron determinados por la evidencia internacional del procedimiento de emparejamiento en familias de acogida (Pösö & Laakso, 2014;Zeijlmans et al., 2017) y en función de modelos teóricos descritos para la toma de decisiones en protección en infancia (Baumann et al., 2011;Benbenishty et al., 2015). ...
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Foster care is a temporary family-based placement for children whose parents cannot take care of them. A good matching between the foster family and the child might improve the outcomes of this placement. This qualitative study explored the professional decision of matching a child with a non-kinship foster family in the child protection system. We conducted 17 semi-structured interviews with professionals working in foster care agencies in five regions of Chile. Applying the hierarchical content analysis, we identified five central constructs related to the case, the caregiver, the child, the organization, and the decision makers. We discussed the preponderance of criteria used by professionals in the process of matching, the relevant content found, and the implications of the findings for research, policy and practice, with a special focus on the implications for the Chilean child protection system.
... En este sentido, el marco teórico de la ecología de la toma de decisiones (en inglés Decision Making Ecology, [DME]; Baumann et al., 1997) ha contribuido enormemente a la acumulación de evidencia empírica sobre la toma de decisiones en los sistemas de protección infantil desde una perspectiva ecológica. La idea fundamental que aporta este modelo es que las decisiones tienen lugar dentro de una serie de contextos o ecologías interconectadas que incluyen un conjunto de factores de caso, externos, organizativos y personales que se combinan de varias maneras para influir en las decisiones y los resultados de las decisiones en los servicios de protección (Baumann et al., 2011). Este marco teórico ha sido aplicado para analizar científicamente diferentes decisiones como la decisión de investigar o no un posible caso de maltrato, la separación familiar, la reunificación, el tipo de acogimiento (residencial o familiar), o el emparejamiento o matching en acogimiento familiar. ...
... El estudio de Muñoz Insunza (2020) exploró por primera vez en Chile características del proceso de decisión de emparejamiento en profesionales de programas de acogimiento familiar. Se realizaron 22 entrevistas semiestructuradas, las que incluyeron temas determinados por la evidencia internacional sobre el procedimiento de emparejamiento en familias de acogida (Pösö & Laakso, 2014;Zeijlmans et al., 2017) y definidos en función de modelos teóricos descritos para la toma de decisiones en protección en infancia (Baumann et al., 2011;Benbenishty et al., 2015). Aun cuando el tamaño de la muestra de este estudio es pequeño, el rigor del análisis realizado permitió identificar criterios utilizados por profesionales chilenos y de esta manera aproximarse a una caracterización de los procesos de emparejamiento en programas de familias de acogida del sistema de protección infantil. ...
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La importancia del cuidado y bienestar de los niños, niñas y adolescentes, y especialmente aquellos que viven en situación de vulnerabilidad, han adquirido en los últimos años una dimensión de especial de parte de una amplia diversidad de profesionales, investigadores e incluso en cuanto a su consideración en políticas publicas. En esa dirección, este libro colectivo, que congrega el trabajo de investigadores y profesionales tiene por propósito aportar innovaciones metodológicas, reportes de investigaciones y discusiones teóricas para el mejoramiento de las practicas de intervención desarrolladas en el marco de las políticas publicas de infancia en Chile.
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Child welfare (CW) agencies are charged with ensuring children’s safety; when children live with families impacted by intimate partner violence (IPV), this task can be complex. To better understand how U.S. CW agencies identify and make decisions about child maltreatment (CM) in the presence of IPV, this mixed-methods study used national data ( N = 248,654) to investigate whether IPV was more likely to be documented as co-occurring with certain types of CM. This study also explored the intersection of IPV and CM using 19 semi-structured interviews with child welfare stakeholders to gain insight into the mechanisms underpinning reporting processes. Multinomial logistical regression showed that after controlling for other risk factors, children living in a household with IPV were more likely to be determined to be physically abused and emotionally maltreated than neglected, and less likely to be determined to be sexually abused than neglected, compared with children who did not live in a household with IPV. Those children were also more likely to be determined to be emotionally maltreated than physically abused, and less likely to be determined to be sexually abused than physically abused, compared with children who did not live in a household with IPV (all results, p < .0001). Qualitative results revealed IPV and children’s exposure to IPV may be categorized as different types of CM by CW agencies and staff, and that this categorization can vary by agency and staff level. Participants also described challenges to addressing IPV within CW systems. Findings suggest national CW data may obscure when IPV and CM co-occur versus when a given type of CM is serving as a proxy for the presence of or children’s exposure to IPV, presenting challenges to interpreting child welfare data. Recommendations are presented to improve CW data accuracy and ensure the safety of children and families impacted by IPV.
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For many families whose children are placed in foster care, initial contact with the child welfare system occurs due to interactions with the healthcare system, particularly in the context of the opioid epidemic and increased attention to prenatal drug exposure. In the last decade, many previously uninsured families have gained Medicaid health coverage, which has implications for their access to healthcare services and visibility to mandatory reporters. Using administrative foster care case data from the Adoption and Foster Care Analysis and Reporting System Foster Care Files and health insurance data from the American Community Survey, this study analyzes the associations between state-level health insurance coverage and rates of foster care entry due to parental substance use between 2009 and 2019. State-level fixed effects models revealed that public, but not private, health insurance rates were positively associated with rates of foster care entry due to parental substance use. These results support the hypothesis that health insurance coverage may promote greater contact with mandatory reporters among low-income parents with substance use disorders. Furthermore, this study illustrates how healthcare policy may have unintended consequences for the child welfare system.
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This literature review of decision making (how people make choices among desirable alternatives), culled from the disciplines of psychology, economics, and mathematics, covers the theory of riskless choices, the application of the theory of riskless choices to welfare economics, the theory of risky choices, transitivity of choices, and the theory of games and statistical decision functions. The theories surveyed assume rational behavior: individuals have transitive preferences ("… if A is preferred to B, and B is preferred to C, then A is preferred to C."), choosing from among alternatives in order to "… maximize utility or expected utility." 209-item bibliography. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Chapter
This chapter presents a program of research that focuses on the decision to formally separate the child from the family as it is a central and serious intervention. Social judgment theory (SJT) and the theory of signal detectability (TSD) or signal detection theory provide methods used to study this decision problem. SJT provides a rich set of procedures with a solid philosophical and theoretical background that seem to coincide with the complexity and ambiguity of the environment in which child protection workers make their decisions. SJT is intended to be life relevant, descriptive and concerned with the development of cognitive aids for human judgment. TSD has also been widely used in applied decision making. In decision making about child abuse, TSD is useful because it separates the sensitivity with which a person can discriminate between the need for a separation order or not, from the bias that the person has towards one response or the other.
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Many decisions are based on beliefs concerning the likelihood of uncertain events such as the outcome of an election, the guilt of a defendant, or the future value of the dollar. Occasionally, beliefs concerning uncertain events are expressed in numerical form as odds or subjective probabilities. In general, the heuristics are quite useful, but sometimes they lead to severe and systematic errors. The subjective assessment of probability resembles the subjective assessment of physical quantities such as distance or size. These judgments are all based on data of limited validity, which are processed according to heuristic rules. However, the reliance on this rule leads to systematic errors in the estimation of distance. This chapter describes three heuristics that are employed in making judgments under uncertainty. The first is representativeness, which is usually employed when people are asked to judge the probability that an object or event belongs to a class or event. The second is the availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development, and the third is adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available.
Book
A three-phase model for decision making at intake for both protective services and voluntary child welfare services is described in this manual. These phases include (1) reception, in which decisions are made as to whether a case seems appropriate for agency services; (2) investigation and problem assessment, which involves assessments regarding evidence of abuse or neglect; and (3) service planning, in which case plans are formulated as written service agreements that provide a framework for service delivery and future decision making. Steps for accomplishing each phase are detailed, and decisions associated with each phase are listed in order to assist in the process of determining whether protective services, voluntary services, or both should be sought. Flow charts that show the process workers follow to make decisions are presented for each decision covered; questions arising in the process of making each decision, as well as directives for staff action, are included. Finally, case examples are presented throughout the manual, as are tasks to enhance development of the learner's decision-making skills. (MP)
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I am grateful for helpful comments by Thalia Gigerenzer, Ralph Hertwig, Lael Schooler, and Peter Todd.