Crisis in Usual Care 0
Running head: CORRELATES OF A CRISIS IN USUAL CARE
Correlates of a Crisis in Children’s Psychotherapy in Usual Care
Ashley V. Robin
Thesis completed in partial fulfillment of the requirements of the Honors Program
in Psychological Sciences.
Under the direction of Dr. Leonard Bickman
Vanderbilt University
April 3, 2009
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Acknowledgements
I would like to give special thanks to the following people who helped me in completing this
project: my mentor, Dr. Leonard Bickman for all his guidance and support, Dr. Susan Kelley for
her advice on the study design, Dr. Andrade for her statistical help, Dr. Craig Smith for giving
direction in the Honors Program, and to the other committee members, Dr. David Schlundt and
Steven Killingsworth.
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Table of Contents
Abstract…………………………………………………………………………………………..3
Introduction………………………………………………………………………………….…...4
Method………………………………………………………………………………………… 11
Results…………………………………………………………………………………………..16
Discussion……………………………………………………………………………………… 24
References……………………………………………………………………………………….28
Table 1. Implementation Schedule……………………………………………………… …….32
Table 2. Odds Ratio Results from Therapeutic Alliance Logistic Regressions…………………33
Table 3. Odds Ratio Results from Symptom and Functioning Severity Logistic
Regressions ……………………………………………………………………………………...34
Table 4. Odds Ratio Results from Topics Logistic Regressions……………………….. ………35
Table 5. Logistic Regression Analysis of Crisis in a Session with TA and Topics
Covariates ……………………………………………………………………………………….36
Table 6. Logistic Regression Analysis of Crisis in a Session with SFSS and Topics
Covariates ………………………………………………………………………………...….….37
Table 7. Results from Clinician Characteristics Logistic Regression…………………...………38
Table 8. Odds Ratio Results from Client Characteristics Logistic Regressions……...…………39
Table 9. Logistic Regression Analysis of a Crisis in a Session with TA and Topics
Covariates……………………………………………………………………………………… .40
Table 10. Logistic Regression Analysis of a Crisis in a Session with SFSS and Topics
Covariates………………………………………………………………………………………..41
Table 11. Logistic Regression Analysis of a Crisis in a Session with a Client Characteristic as
Covariate…………………………………………………………………………………………42
Table 12. Logistic Regression Analysis of a Crisis in a Session with a Clinician Characteristic as
Covariate…………………………………………………………………………………………43
Table 13. Predicted Probability of a Crisis in a Session from Hypothetical Data of TA and
Topics………………………………………………………………………….…………………44
Appendix A………………………………………………………………………………………48
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Abstract
The purpose of the study was to examine crises that occur in Treatment as Usual. A
children’s mental health group was examined in order to explore the correlates of a crisis session.
N=7267 sessions, N=629 clients, and N=240 clinicians were included in the analysis. Logistic
regressions were conducted for several factors: therapeutic alliance, symptom severity, caregiver
strain, and number of topics discussed within the session. Therapeutic alliance, as rated by the
clinician, and symptom severity, as rated by the clinician, both had significant associations with
the occurrence of a crisis. The number of topics discussed within the session was also a
significant covariate of the occurrence of a crisis. These correlates provide a basis for future
studies of crises within sessions.
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Introduction
Research has highlighted the need for more accurate descriptions of Treatment as Usual
in mental health services (Kolko, 2006; Garland, Hurlburt, Hawley, 2006; Bickman, 2008). A
few studies have documented Treatment as Usual (TAU) in community settings by examining
clinicians’ treatment strategies (Weersing, Weisz, & Donenberg, 2002; Chorpita, Daleiden, &
Weisz, 2005; Bearsley-Smith, Sellick, Chesters, & Francis, 2008). Of the strategies used in
TAU, therapists have most commonly reported the use of crisis management (Bearsley-Smith et.
al, 2008). However, research has not identified the features of a “crisis session.” The studies
reporting TAU strategies have not documented descriptions of treatment at the session level,
including a session with a crisis. Without concrete descriptions of a crisis session, there has been
no agreement on the definition of a crisis. This paper will attempt to identify the features of a
crisis session in order to help clinicians identify and prevent crises from harming the therapeutic
session.
Definition of Crisis
Providing adequate descriptions of sessions with crises has been overlooked in the
research literature. No uniform definition of a crisis exists. For example, Bearsley-Smith and
colleagues (2008) define crisis management as “immediate problem solving approaches to
handle urgent or dangerous events. This might involve defusing an escalating pattern of
behavior and emotions either in person or by telephone, and is typically accompanied by
debriefing and follow-up.” In this definition, crisis management is a specific technique to handle
an immediate, escalating problem, i.e., the crisis. Another definition describes a crisis as a brief
episode of emotional distress, in which coping efforts are incapable of handling the problem
(France, 2002). However, Kleespsies and Dettmer (2000) state that crises do not necessarily
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imply urgency or danger but rather refer to long-lasting and non-specific problems, lasting from
a few days to 6 weeks. Kleepsies and Dettmer (2000) also state a crisis is a loss of psychological
equilibrium accompanied by a disruption in the individual’s baseline functioning. This
definition implies a specific change in the psychological functioning of the individual as the
basis for a crisis. Another definition more broadly describes crisis management as a general
therapeutic framework, such as cognitive-behavioral therapy and family therapy, and it
encompasses specific therapeutic strategies (Baumann, Kolko, Collins, & Herschell, 2006).
The preceding definitions do not complement each other and create ambiguity regarding
the definition of a crisis. The broadness of these definitions could expand the crisis literature to
findings about therapeutic “ruptures” in the therapeutic alliance (Safran, Crocker, McMain, &
McMurry, 1990), treatment termination, changes in symptom functioning, hospitalization,
suicidality, or any other potential problem within therapy. For the purpose of the current study,
we have not defined crisis in any specific terms. Instead, we will use the clinicians’ reports of a
crisis and then identify correlates based on their designation.
Crisis Prevention
Identifying the features of a crisis is important for prevention purposes. Clinicians must
understand what a crisis looks like in a session before engaging in prevention. According to
France (2002), secondary prevention is the optimal crisis intervention because it occurs when the
client is already facing ongoing problems. Secondary prevention also occurs during the stage of
a crisis when the clients are willing to change their coping mechanisms.
Crises progress through three stages, but the earlier the intervention the better the client’s
prognosis (France, 2002). The stages of a crisis are the impact stage, the coping stage, and the
withdrawal stage. During the impact stage, an individual experiences an uncontrollable situation.
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In the coping stage, individuals try to find some way of coping with the situation, either adaptive
or maladaptive coping methods. If the stress continues, individuals will enter the withdrawal
stage and will cease trying to resolve the problem.
Preventing crises in the impact stage may combat the feelings of learned helplessness and
uncontrollability associated with this stage (France, 2002). These feelings eventually lead to
depressive symptoms and suicidal ideations (Seligman, 1992). Learned helplessness can even
trigger a biological suicide mechanism. Preventing the crisis progression to the withdrawal stage
is also important since clients more engaged in therapy have been shown to have better
therapeutic outcomes than clients less engaged in therapy (McKay et. al, 2004). Also, if clients
are in the withdrawal stage of a crisis, then they may attempt suicide as a cry for help or as a way
of coping. Suicide attempts may occur when the crisis situation persists and their coping
mechanisms have not relieved the situation (France, 2002). The faster a clinician can intervene,
the better the prognosis may be for the client (Pollin, 1995).
Preventing a crisis represents a legal and ethical responsibility when dealing with suicidal
clients. Legally, counselors are responsible for any harm to the client caused by their negligence.
Counselors must keep records showing that they have taken proper actions when dealing with a
suicidal client. When a counselor’s client attempts suicide, the counselor can potentially be sued
for malpractice, although proving the malpractice claims is complex. Nonetheless, the legal risks
for counselors dealing with crises are still imminent (Remley, 2004).
In addition to legal issues, counselors also have ethical responsibilities for their clients.
According to the American Counseling Association Code of Ethics (2005) S2, counselors must
limit their practice only to their areas of competence. Counselor must also seek to improve their
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skills and competence. Therefore, counselors who are dealing with crises in therapy should be
knowledgeable about how to deal with their clients.
In order to deal with a crisis, the counselor must first identify the occurrence of a crisis.
Once there are proper identification features, then clinicians can try to predict and prevent the
occurrence of a crisis. Only after identification, can counselors be able to either prevent or treat
a crisis. Without adequate empirical evidence about the features of a crisis, counselors cannot
improve their competence in dealing with crises.
Consequences of Crisis in Treatment
Having competence in dealing with crises is important in combating the potential
consequences in therapy. One article states the peril of having clinicians spend most of their
time dealing with crisis management (Ivanov, 2007). Frequent crises may impede the long-term
goals of psychotherapy. It can disrupt the therapeutic progress and can obstruct time the
clinician can be using to understand the client. Time spent dealing or talking about crises cannot
be spent talking about other important issues. Dealing with a crisis also deters the clinician from
following usual protocols or strategies. According to an evidence-based decision-making
framework, a crisis must be resolved before the treatment protocol can be delivered (Chorpita,
Bernstein, & Daleiden, 2008). Crises must be resolved or prevented in order to progress through
effective therapeutic strategies.
Factors Related to Crises
Predicting the occurrence of a crisis, such as a suicidal attempt, is not currently possible
(Slaby, 1998; Jacobs, Brewer, & Klein-Benheim, 1999); however, specific factors are related to
the onset of a crisis. First, precipitating events appear to precede a crisis. The precipitating
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event can be a normal developmental change in one’s life, or it can be an unpredictable situation
(Kleespsies & Dettmer, 2000). It can be a singular event or an accumulation of stress that causes
the crisis. Second, a good therapeutic relationship is believed to help the client communicate
problems that may lead toward a crisis (France, 2002). Because of therapeutic alliance’s
association with therapeutic outcome (Shirk & Karver, 2003), the alliance rating may show an
association with the occurrence of a crisis.
Another factor that may be associated with crises is the client’s psychological functioning
or symptom severity. A crisis has been defined as a change in one’s baseline level of functioning
(Kleepsies & Dettmer, 2000). Although this definition describes the change in functioning as
signifying the actual crisis, the change may actually occur as a precursor or consequence of the
crisis. The level or a change in the level of a client’s symptoms may be associated with the
occurrence a crisis. Acquiring accurate information and assessing the clients’ risk are important
parts in preparing for a crisis (McAdams & Keener, 2008). This study will examine the clients’
symptom severity and whether or not the measure has an association with crises.
Evidence also suggests that clinicians have their own personal styles in therapy that shape
psychotherapeutic situations. Fernández-Álvarez, García, Bianco, and Santomá describe the
concept of a therapist’s personal style (2003). This concept consists of the peculiarities of a
therapist that lead the therapist to behave in a particular way regardless of the type of client or
the client’s pathology. The study hypothesizes that the therapist’s personal style influences
one’s therapeutic process and actions. The dimensions discovered in the construct of personal
style include instructional, expressive, engagement, attentional, operative, and therapy
assessment. Another study evaluates these dimensions of personal style in relation to the
clinicians’ experience (Castaneiras, Barcia, Bianco, & Fernandez-Alvarez, 2006). Inexperienced
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cognitive-oriented clinicians scored lower on the expressive dimension, reporting to be more
rigid and distant compared to experienced cognitive-oriented clinicians. In addition, compared
to the inexperienced psychoanalytic-oriented clinicians, the experienced psychoanalytic-oriented
clinicians had lower attentional scores, reporting to have a broader focus in their sessions. These
results suggest that therapists’ characteristics may influence the therapeutic outcome. Hence, we
will explore the role of therapist characteristics in our study of crises. Although therapy
components such as therapeutic alliance, client symptoms and functioning, and clinician
experience may influence the therapeutic process, their role in crisis development must be more
thoroughly examined in usual care.
Current Crisis Recording in TAU
Previous studies that have documented treatment strategies used in TAU have not
addressed the occurrence of crises. Another limitation of these studies is their failure to
document clinician actions session-by-session. Instead, therapists recall their treatment strategies
on a monthly basis or after treatment termination (i.e. Schiffman, Becker, & Daleiden, 2006;
Bearsley-Smith et. al, 2008). Also, since crises require immediate action, looking at the crisis
within a session may be more beneficial than looking at the treatment course as a whole.
Another limitation of these TAU studies has been the type of strategies that these studies
have documented. Many of these studies documented techniques based upon clinical
orientations (Weersing et. al, 2002; Bambery, Porcerelli, & Ablon, 2007). For example, one
measure, called the Therapy Procedures Checklist requires therapists to report the techniques
they used in therapy. The items on the checklist include techniques mostly from the clinical
orientations of psychodynamic, cognitive, or behavioral techniques. However, up to 18% of the
study’s sample ascribed to an orientation other than the previous three. Another study found that
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clinicians describe their techniques as eclectic rather than ascribing to one orientation (Santa Ana,
2007). Thus, examining treatment as usual based upon clinical orientation may be an inaccurate
representation of clinicians’ actual techniques. Evidence also supports the use of a common
factors framework in examining psychotherapy rather than specific clinical orientations
(Bickman, 2005). Hence, this study will examine the issues that therapists’ have documented
within a session through a session report measure. The items on this measure do not pertain to
specific clinical orientations but rather represent a common factors approach. This study will
explore the topics discussed within session to determine their relationship with the occurrence of
crises.
Another limitation of these studies is the failure to address the occurrence of crises within
TAU. One study mentions that crisis management is the most common strategy used in TAU
(Bearsley-Smith et.al, 2008); however the other studies documenting TAU do not mention crises
in their studies.
Current Study
The purpose of this study is to identify the characteristics of crises occurring within
sessions in order to describe the environment of a crisis. For the purpose of this study, we will
not propose any one definition for a crisis in therapy. Rather, we will use the clinician’s report
of time spent dealing with a crisis within a session. Roberts and Everly (2006) propose that a
crisis is not a particular dangerous event, but it is the perception of a certain situation. Using
only a clinician’s perspective of a crisis situation should not diminish the importance of its
existence, although the clinician’s perspective of therapeutic processes may differ from the
client’s perspective. For example, in one study therapists and clients viewed videotapes of
therapy sessions and subjectively identified any episode that resulted in a change in the client.
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(Fiedler & Rogge, 1989). The clinicians identified more episodes than the clients did, suggesting
that the clinicians found more noteworthy changes in therapy sessions. Clinicians may be more
sensitive to client changes, and, thus, their reports of a crisis may differ from their clients’ report.
However, using the clinicians’ reports of a crisis is appropriate for the purposes of exploring
crises in TAU and providing a framework for future crisis research.
Using the clinicians’ reports, we will then profile the characteristics of a “crisis” session.
We will explore the following covariates’ associations with the occurrence of a crisis within a
session: therapeutic alliance measures, type of topics discussed within a session, characteristics
of the clinician, characteristics of the client, symptoms and functioning of the client, and
caregiver strain. This information may serve two purposes. First, identifying the correlates of a
crisis provides a basis for understanding the definition of a crisis. Second, this study will help
identify factors that may play a role within the stages of crises. Third, this study will examine
important therapeutic factors that may be overlooked in the sparse studies of TAU. Lastly, this
study will address covariates within individual sessions rather than the whole treatment course.
This more detailed level of analysis will be helpful in examining TAU characteristics within a
session.
Method
The Center for Evaluation and Program Improvement (CEPI) developed the
Contextualized Feedback Intervention and Training (CFIT) program (Bickman, Riemer, Breda,
& Kelley, 2006). The CFIT program contains various self-scoring measures and provides online
feedback to clinicians. Although we will not be examining the effects of feedback within this
study, the clinicians receive contextualized feedback of the client and caregiver measures either
weekly or every 90 days. In order to implement the CFIT program, the CEPI group paired with a
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child therapy service, called the Providence Corporation. The CFIT trainers instructed the
Providence clinicians and their supervisors in how to use the various measures involved in the
project. The trainers also educated the clinicians about common factors, e.g., therapeutic alliance
and client satisfaction. The common factors provided a basis in the development of some of the
CFIT measures.
Participants
The data were collected from June 2006 through December 2008. The clinicians, N=240,
provided data for 7386 sessions. Of the 7386 sessions, 7267 sessions had information about
whether any time was spent on a crisis. Of these sessions with crisis information, 5635 sessions
spent no time spent dealing with a crisis, 1070 sessions spent a little time dealing with a crisis,
311 sessions spent about half of the time dealing with a crisis, and 251 sessions spent most or all
of the sessions dealing with a crisis.
The clients consisted of N=629 youth who had therapy sessions and data on these
sessions. The children ranged from age 11 to age 18. The average age was 14.7 years. Fifty-five
percent of the clients were males, and 45% of the clients were female. Data was provided for an
average of 12 sessions per youth.
The clinician participants who provided session data was N=240. Seventy-nine percent
of the clinicians were female and averaged 37.5 years of age. The clinicians reported data for an
average of 31 sessions each. The clinicians also provided data for an average of 3 clients each.
The caregivers of the youth participated in about 34% of the total session data. We have
data on the caregiver’s participation in the session for 2500 of the 7386 total sessions.
Measures
Session Report Form (SRF)
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The Session Report Form (SRF) is a self-report checklist the clinicians fill out after every
session with the client. It contains a checklist of issued that might be discussed during the
session. Examples of these issues include behavioral issues, family issues, client hope for the
future, caregiver satisfaction with life, etc. Clinicians have the option to answer that the topic
was addressed, was not addressed, or was the focus of the session. Other items on the SRF allow
the clinician to report the length, location, session participants, date, and overall rating of the
session. The SRF also contains an item pertaining to crises. The item reads, “How much time in
this session did you spend dealing with a crisis?” The possible answer choices include ‘none,’ ‘a
little,’ ‘about half,’ and ‘most or all’ of the session.
Symptom Functioning Severity Scale (SFSS)
The Symptom Functioning Severity Scale (SFSS), whose first page is shown in Appendix
A, measures the severity of the client’s emotional and behavioral problems. It is an important
indicator for measuring the treatment progress. It contains 33 items and has two subscales for
internalizing and externalizing symptoms. Examples of these internalizing and externalizing
items include ‘feel worthless,’ ‘cry easily,’ ‘throw things when mad,’ and ‘threaten or bully
others.’ Some items do not pertain to either internalizing or externalizing symptoms. Examples
of these symptoms include ‘think you don’t have friends’ ‘use drugs,’ and ‘drink alcohol.’ The
clinician, client, and caregiver filled out separated forms of the SFSS. The items on the forms
have 5 choices on a five-point Likert scale: never, hardly ever, sometimes, often, very often.
For clinician and caregiver forms, the scores range from 42 to 105. For the youth form, the
scores can range from 32 to 107.
Therapeutic Alliance Questionnaire Scale (TAQS)
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The Therapeutic Alliance Questionnaire Scale (TAQS) measures therapeutic alliance
(TA). TA is a construct describing the bond between the client and the clinician, agreement on
goals between client and clinician, and agreement on tasks of therapy between client and
clinician (Bordin, 1979). The clinicians, caregivers, and clients completed the three versions of
the form. The first pages of these forms are shown in Appendix A. The clinicians reported on
items for their alliance between the clinician and youth client and between the clinician and adult
caregiver. The caregivers reported on their alliance with the clinician, and the youth also
reported on their alliance with the clinician. The caregiver and client forms contain 13 items
pertaining to the bond and goals of therapy. The raters scored items on a 5-point Likert scale
ranging from ‘not at all,’ ‘only a little,’ ‘somewhat,’ ‘quite a bit,’ and ‘totally.’ The clinician
form only contains 2 items that ask how the clinician would rate the working alliance between
the client and the caregiver. The possible answer choices include ‘poor,’ ‘poor,’ ‘satisfactory,’
‘good,’ and ‘excellent.’ For all forms the respondents’ scores for all the items are averaged to
yield an overall TA rating ranging between 1 and 5.
Caregiver Strain Questionnaire (CSQ)
The Caregiver Strain Questionnaire (CSQ) measured the extent to which the caregivers
experienced distress in caring for a child with emotional or behavioral problems. The caregiver
self reported problematic events or behaviors that resulted from caregiver burden. Caregiver
burden has been a construct associated with how children utilize mental health services (Brannan
& Helfinger, 2001). The first page of the CSQ is shown in Appendix A. It has 21 items to
assess strain over a 1-month period. The measure includes an objective subscale and an
internalizing subjective subscale. Examples of these items include ‘worried about future,’
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‘financial strain,’ ‘sad or unhappy,’ and ‘tired or strained.’ The items range from 1(not at all a
problem) to 5 (very much a problem).
Data Collection
The participants each had a particular implementation schedule required of them, as
shown in Table 1. The clinicians filled out the Session Report Form (SRF) weekly after each
session. They also filled out the symptom severity and alliance measures alternating every 2
weeks. The clients filled out the alliance and symptom severity forms every 2 weeks for the first
4 months. After the first four months, they filled out the forms every 4 weeks. The caregivers
also had the same implementation schedule for the alliance and symptom severity measures. The
caregivers filled out the caregiver strain measure every 8 weeks for the entire length of treatment.
After the participants have recorded their measures, the clinicians returned the forms to CFIT
staff. The caregiver and client sealed their responses in an envelope so that their answers would
not be influenced by the presence of the clinician.
Although the participants were asked to adhere to the implementation schedule, data were
missing for various sessions. The most common reason for missing measures was because the
client and clinician did not meet. Other reasons for missing data measures were that the
respondent refused or there was not enough time.
Analysis Plan
The first part of the analysis created two different definitions of a crisis session based
upon the question in the SRF asking about time spent on a crisis. One definition incorporated
any session where some time was spent dealing with crisis (‘a little,’ ‘about half,’ or ‘most or
all’). A non-crisis sessions was when no time was spent dealing with crisis. The second
definition of a crisis session included only the sessions when ‘about half’ or ‘most or all’ of the
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session was spent dealing with a crisis. A non-crisis session would be any session when no time
or just a little time was spent dealing with a crisis.
Next, we used binomial logistic regressions to determine the factors likely to occur
during a session with a crisis. The independent variables were the various characteristics of the
session: therapeutic alliance, child symptoms and functioning, caregiver strain, and number or
type of session topics discussed. We will also examine specific client and clinician
characteristics, such as age, gender, number of sessions, and topics discussed. The dependent
variable is whether or not a crisis has occurred within the session. The first definition of a crisis
(‘none’ versus ‘a little,’ ‘about half,’ or ‘most or all’) was used to explore the relationships of the
covariates. Each covariate was tested in a single-covariate logistic regression model. If the
covariate showed a significant association, then the significant covariates were tested in a
multiple-covariate logistic regression. The second definition of a crisis (‘none’ and ‘a little’
versus ‘about half’ or ‘most or all’) was used to further examine the significant associations.
Results
The findings of this study describe the characteristics that are likely to occur during a
crisis within a therapeutic session based upon three levels of analysis: the session level, the
clinician level, and the client level. At the clinician and client characteristics were analyzed
separately to determine their association with crises. The client and clinician characteristics
examined, such as age and gender, were fixed effects because they cannot change across sessions.
These covariates were analyzed separately from the session-level covariates since the session
covariates change across the course of treatment.
Session Level
Therapeutic Alliance
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A binary logistic regression was conducted to determine the covariates of a crisis
occurrence within a session. The covariates at the session level include therapeutic alliance,
symptoms and functioning, caregiver strain, number of topics addressed, and type of topics
addressed. Each covariate was assessed individually within its own logistic regression model to
determine their unadjusted associations with a crisis. Table 2 displays the results of these
logistic regressions. For the unadjusted logistic regression for individual covariates, the higher
the TA, as rated by the clinician and client, the less likely a crisis occurred within a session. The
TA between the clinician and youth and between the clinician and caregiver, as rated by the
clinician, both showed a significant relationship with the occurrence of a crisis (OR=0.68,
p<0.001 CI: 0.61, 0.77; OR=0.82, p=0.002, CI: 0.72, 0.93). The TA between the clinician and
youth, as rated by the youth, also displayed a significant association with a crisis (OR=0.88,
p=0.02, CI: 0.79, 0.98); however the clinician-caregiver TA, as rated by the caregiver, did not
show a significant relationship (p=0.62).
With the significant TA covariates, a three-covariate logistic model was conducted, as
shown in the right-hand column of Table 2. The result showed that the model was significant
(p<0.001) with the following equation:
Predicted logit of (CRISIS) =
0.371 + (-0.04 )* Youth TA + (0.068 )*Clinician-caregiver TA + (-0.423)* Clinician-client TA
(p=0.35)
(p=0.51)
(p=0.44)
(p<0.001)
The clinician-client TA, as rated by the clinician, remained a significant covariate of a
crisis (OR= 0.655, p<0.001, CI: 0.550, 0.780). However, the clinician-client TA rated by the
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client and the clinician-caregiver TA rated by the clinician were no longer significant covariates
(p=0.51, p=0.43).
Symptoms and Functioning Severity Scale (SFSS)
Next, we conducted a binary logistic regression to determine the significance of the
covariate variables of symptoms and functioning of the client. The measures came from the
SFSS and were rated by the client, clinician, and caregiver. Again, each of the covariates was
evaluated individually in an unadjusted logistic regression single-predictor model, as shown in
Table 3. All three raters’ SFSS scores were significantly associated with the occurrence of a
crisis. As expected, crises were more likely to occur within session with more severe symptom
scores as rated by the client, clinician, and caregiver (OR=1.28, p<0.001, CI: 1.12, 1.46;
OR=2.23, p<0.001, CI:1.91, 2.59; OR=1.51, p<0.001, CI: 1.27, 1.80). These covariates were
then tested in a three-covariate logistic regression model. The model was significant (p<0.001).
In the model, the SFSS scores, as rated by the clinician and caregiver, remained significant
covariates of a crisis within a session (OR=1.94, p<0.001, CI: 1.49, 2.52; OR=1.25, p=0.04, CI:
1.01, 1.55), while the SFSS score rated by the client was no longer a significant covariate
(p=0.293). Another adjusted logistic regression was conducted with the significant covariates in
the previous model: the SFSS scores as rated by the clinician and the SFSS scores as rated by the
caregiver. The model was a significant (p<0.001) with the following equation:
Predicted logit of (CRISIS) = (-3.17) + (0.70)* Clinician-rated SFSS + (0.13)*Caregiver-rated
SFSS
(p<0.001)
(p<0.001)
(p=0.23)
The clinician-rated SFSS measure remained a significant covariate. When compared to less
severe symptoms, more severe symptoms were more likely to occur during a crisis session
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(OR=2.00, p<0.001 CI: 1.58, 2.54). The caregiver-rated SFSS measure was no longer a
significant covariate the clinician-rated SFFS was tested in the same model (p=0.23).
Caregiver Strain
The caregiver strain measure was the next covariate tested in a logistic regression model.
There were N=543 sessions with the measurement of caregiver strain. Contrary to our hypothesis,
caregiver strain was not a significant covariate of a crisis within a session (p=0.106).
Topics Discussed
When the number of topics discussed in a session was tested in a logistic regression
model, it was a significant covariate of a crisis. As shown in Table 4, the more topics discussed
within a session, either addressed or focused on, the more likely a crisis occurred within the
session (OR=1.15, p<0.001, CI: 1.13, 1.17). Another covariate based upon topics discussed
within a session was tested in a logistic regression model. The variable tested was the SRF index
measuring topics relating to personal or caregiver issues rather than problem-oriented topics. It
was a significant predictor of a crisis within a session. The higher the SRF index, or the more
non-problem oriented topics addressed or focused on, the more likely a crisis occurred within a
session (OR=1.12, p<0.001, 1.11, 1.14).
The two covariates detailing the number and type of topics discussed were tested within a
logistic regression in the right-hand column of Table 4. The model was a significantly associated
with the occurrence of a crisis within a session (p<0.001) with the following equation:
Predicted logit of (CRISIS) = (-2.707) + (0.168)* Number of Topics + (-0.032)*SRF Index
(p<0.001)
(p<0.001)
(p=0.04)
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In the model the higher number of topics discussed, the more likely the session had a crisis
(OR=1.18, p<0.001, CI: 1.15, 1.22). However, the SRF index no longer remained a significant
covariate since its coefficient changed by more than 10%. This variable may be an intervening
variable in the relationship of number of topics discussed and the occurrence of a crisis
(OR=0.97, p=0.04, CI: 0.94, 1.00).
Combined Models
Table 5 and Table 6 show the combined covariates used in two logistic regression models. The
SFSS and TA scores could not be tested in the same logistic regression model because they were
collected on different session dates. Thus, both SFSS and TA were tested in separate models
with the number of topics. Table 5 shows the logistic regression results of a model testing the
number of topics and TA, as rated by the clinician. The model was significant with the
following equation:
Predicted logit of (CRISIS) = (-0.86) + (-0.47)* Clinician-rated TA + (0.15)*Number of Topics
(p<0.001)
(p<0.001)
(p<0.001)
Table 13 shows the predicted probabilities of a crisis given hypothetical data of the TA
score and the number of topics discussed. The probabilities were calculated using the preceding
equation. In this model both the TA, as rated by the clinician, and number of topics discussed
remained significant covariates (OR=0.62, p<0.001, CI: 0.55, 0.70; OR=1.15, p<0.001, CI: 1.13,
1.19). Sessions with higher clinician-rated TA had about 40% lower odds of having a crisis
within a session, and sessions with more topics discussed had about 15% higher odds of having a
crisis.
Crisis in Usual Care 21
Table 6 shows the logistic regression model with the number of topics and SFSS score, as
rated by the clinician. The model was a significantly associated with occurrence of crises
(p<0.001) with the following equation:
Predicted logit of (CRISIS) = (-3.86) + (0.71)* Clinician-rated SFSS + (0.11)*Number of
Topics
(p<0.001)
(p<0.001)
(p<0.001)
Both the SFSS score and the number of topics remained significant covariates with the
occurrence of a crisis (OR= 2.03, p<0.001; OR=1.12, p<0.001, CI: 1.10, 1.15). Compared to less
severe symptoms, more severe symptoms rated by the clinician had over two times higher odds
of occurring within a crisis. Also, the higher the number of topics discussed in a session, the
more likely a crisis occurred within a session
Clinician Level
At the clinician level several fixed effects were tested in logistic regression. As shown in
Table 7, the clinician’s age was tested as a covariate in a logistic regression model, and, as
expected, it was a significant covariate (OR=1.02, p<0.001, CI: 1.02, 1.03). The older the
clinician, the more likely a crisis occurred within a session. Next, two other one-covariate
logistic regression models were conducted for the number of clients per clinician and average
number of topics discussed per clinician. The number of clients per clinician and the number of
topics per clinician were significant covariates for a crisis within a session. The smaller the
number of clients the more likely a crisis would occur within a session (OR=0.97, p<0.001, CI:
0.96, 0.99). Also, the higher the average number of topics discussed per clinician the more likely
a crisis would occur within a session (OR=1.14, p<0.001 CI: 1.12, 1.17). Lastly, the number of
Crisis in Usual Care 22
sessions per clinician was tested in logistic regression model, but it was not a significant
covariate of crises (p=0.34).
The age of the clinician, the number of clients per clinician, and the number of topics per
clinician were then tested in a two-covariate logistic regression model. The number of topics per
clinician and number of clients per clinician remained significant covariates of a crisis within a
session (OR=1.16, p<0.001, CI: 1.13, 1.19; OR=0.96, p<0.001, CI: 0.94, 0.98). However, the
age of the clinician was not a significant covariate (p=0.162).
The model had a significant association with the occurrence of crises (p<0.001) with the
following equation.
Predicted logit of (CRISIS) = (-2.56) + (0.14)* Number of topics/clinician + (0.004)*Number of
clients/clinician
(p<0.001)
(p<0.001)
(p=0.64)
The average number of topics discussed per session by clinician remained a significant covariate
of the occurrence of a crisis (OR=1.15, p<0.001, CI: 1.12, 1.17). As in the previous model, the
higher number of topics discussed, the more likely a crisis occurred. However, the number of
clients per clinician was no longer a significant covariate (p=0.64).
Client/Youth Level
Lastly, client characteristics were tested individually in one-covariate logistic regression
models. As shown in Table 8, the client’s age was a significant covariate of crises within
sessions. The older the client, the more likely the session resulted in a crisis (OR= 1.04, p=0.02,
Crisis in Usual Care 23
CI: 1.01, 1.07). The average number of topics discussed in a session by the client was also a
significant covariate. The higher the average number of topics discussed by a client, the more
likely the session had a crisis (OR=1.17 p<0.001, CI: 1.15, 1.19). However, the client’s gender
was not a significant covariate of a crisis (p=0.072). The number of sessions per client was also
not a significant covariate (p=0.901). Then a two-covariate logistic regression model was
conducted with the client’s age and average number of topics discussed by the client. The model
had a significant association with the occurrence of a crisis with the following equation:
Predicted logit of (CRISIS) = (-3.16) + (0.03)* Client’s Age + (0.15)*Number of topics
discussed by client
(p<0.001)
(p=0.06)
(p<0.001)
However, the number of topics discussed by the client remained a significant covariate
(OR=1.17, p<0.001, CI: 1.15, 1.19). That is, the more topics discussed by the client, the more
likely a crisis occurred within the session. The client’s age was no longer a significant covariate
of a crisis (p=.06).
Crisis Definition 2
Using the significant covariates, TA, SFSS, and topics discussed, a logistic regression
model was tested using the second definition of crisis. This definition codes a non-crisis as any
session spending either ‘none’ or ‘a little’ time dealing with a crisis. A crisis session is any
session spending ‘about half’ or ‘most or all’ of the session dealing with a crisis. As shown in
Table 9 and Table 10, all three covariates remained significant covariates of a crisis within a
session.
Crisis in Usual Care 24
In addition, topics discussed per session by the client and clinicians were also tested as
covariates with the second definition (Table 10 and Table 11). These number of topics discussed
by client and clinician remained significant predictors in the model.
Discussion
This paper examines the features of sessions, clients, and clinicians that were likely to
occur during a crisis in treatment as usual in children’s mental health services. Sessions in which
many topics were discussed were more likely to have a crisis than sessions with fewer topics
discussed. This relationship also existed for individual clients and clinicians. Those individuals
who discussed more topics per session were more likely to have a crisis. Although this
relationship is not a causal association, several possible explanations exist. On the one hand, the
crisis itself may involve the discussion of various issues involved in both the client’s life and
client’s therapeutic process. On the other hand, the discussion of too many topics may create a
sense of uncontrollability and provoke a crisis. Another explanation for the association might be
that clients and clinicians who are prone to crises may have more troubling issues to discuss.
Another finding of this study is the relationship between therapeutic alliance and a crisis
session. Sessions with lower ratings of TA were more likely to have a crisis. This relationship
can be expected given the importance of TA in child therapy outcomes (Kazdin, Whitley, &
Marciano, 2005). Again the relationship between TA and a crisis session is not a causal one.
Some explanations may be that higher TA buffers against the occurrence of a crisis, or a lower
TA creates a condition vulnerable to crises. Another possibility may be that the crisis creates a
lower TA, especially if the clients transfer their distress upon the relationship with the clinician.
Crisis in Usual Care 25
Another significant finding of this study is the association between symptom severity and
occurrence of a crisis. Sessions when the clinician rated higher client symptom severity had two
times higher odds of having a crisis. This association is as predicted given that the definition of
crisis may be the decline in psychological functioning (Kleepsies & Dettmer, 2000). Therefore,
higher severity of symptoms could be one of the features of a crisis. Another possibility could be
that the symptoms become more severe because of the crisis.
When the number of topics was combined with either the symptom severity covariate or
the therapeutic alliance covariate, each covariate kept their significant associations with the
occurrence of a crisis. These significant associations also appeared when using a second, stricter
definition of crisis. Confirming these associations with the second definition of crisis provided
us with reliable evidence.
Limitations of the study
Caution must be used when interpreting the clinician-rated measures as significant
covariates. Although the clinician-rated TA and clinician-rated symptom severity were
significant covariates, these associations may be influenced by the clinicians’ perception of a
crisis. The clinicians’ identification of a crisis may influence their subjective scores of the
clients’ symptoms and therapeutic alliance. When TA and symptom measures, rated by the
client and the caregiver, were tested as covariates with the clinician-rated measures, clinicianrated measures were more significantly associated with crises. This association makes sense
given that clinicians rated the occurrence of a crisis. Thus, the clinician measures probably had a
stronger association than the caregiver and client-rated measures because of the congruence in
Crisis in Usual Care 26
raters. The client and caregiver-rated measures should not be discounted as covariates since they
were significant when they were assessed individually.
One main limitation of this study is the clinicians’ self report of a crisis. Using the
clinicians’ perspective of a crisis limits the study in several ways. First, the clinician may not
necessarily agree with the client’s perception of a therapeutic event (Fiedler & Rogge, 1989).
Thus, the client or caregiver may not agree with the crises that the clinician identified.
Furthermore, the definition of a crisis was not defined for the clinicians, and the clinicians could
interpret the term in their own way. Since clinicians can act based upon their particular stylistic
dimensions, (Castanerias et al., 2006), such as engagement and attentional dimensions, some
clinicians may be more attentive or less critical of minor therapy changes. Although the
subjectivity of the definition is a limitation, it is also a necessary way to deal with the term
‘crisis.’ As discussed previously, no consistent definition of a crisis in psychotherapy exists.
Qualitative data on the exact essence of the crisis would be helpful in forming a description of a
clinician’s perceived crisis.
Another limitation of the study is the subjective nature of all the measures of the
covariates. Since an objective observer did not report the measures, we relied on the judgments
of the clients, clinicians, and caregivers. Objective observers can have different perceptions and
judgments of such therapeutic elements as therapeutic alliance (Kazdin et al., 2005).
Another limitation is the lack of predictive or causal associations between the covariates
and crisis. Since we did not analyze the covariates in a session before the crisis, we cannot
presume the covariates to be predictors of the crisis. Instead, the covariates represent correlates
of a crisis session
Crisis in Usual Care 27
The missing data also presents a limitation to our study. Since this study was
implemented in a real-world setting, the participants did not always adhere to the protocol.
Although the study accounted for over 7,000 sessions, sessions with incomplete data are not
included in the data analysis. The missing data can be especially problematic if the occurrence
of a crisis caused negligence in filling out the forms.
Future Implications
Future studies should address the limitations of this study. Qualitative data from both the
clinician and the client would be helpful in identifying an agreed upon definition in treatment as
usual settings. The results of this study have implications in treatment as usual. First, the results
of this study emphasize the importance of measurement in treatment as usual. Secondly, these
correlates can provide a basis for further examination of these covariates and of crises within
session.
Crisis in Usual Care 28
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Crisis in Usual Care 32
Table 1. Implementation Schedule
Form
Rater(s)
Session Report Form
Schedule
Clinician
Weekly after each session
-Clinician
Every 2 weeks
(SRF)
Therapeutic Alliance
Questionnaire Scale
-Client
Every 2 weeks for 4 months; then every 4 weeks
-Caregiver
Every 2 weeks for 4 months; then every 4 weeks
-Clinician
Every 2 weeks
(TAQS)
Symptom Severity &
Functioning Scale
-Client
Every 2 weeks for 4 months; then every 4 weeks
(SFSS)
-Caregiver
Caregiver Strain
Questionnaire (CQS)
Caregiver
Every 2 weeks for 4 months; then every 4 weeks
Every 8 weeks
Crisis in Usual Care 33
Table 2. Odds Ratio Results from Therapeutic Alliance Logistic Regressions
Outcome is Crisis in Session (0/1)
Sample Size N=1552
Unadjusted LR
Adjusted LR
Covariates
Single Covariate
3 covariates together
TAQS-C
Clinician-client
0.68 (0.61, 0.77)**
0.66 (0.55, 0.78)**
Clinician-caregiver
0.82 (0.717, 0.928)**
1.07 (0.90, 1.27)
TAQS-Y
0.88 (0.787, 0.977)*
0.96 (0.85, 1.08)
TAQS-A
1.04 (0.88,1.24)
Note. Confidence limits are in parenthesis
*p<0.05, **p<0.01
Crisis in Usual Care 34
Table 3. Odds Ratio Results from Symptom and Functioning Severity Logistic Regressions
Outcome is Crisis in Session (0/1)
Sample Size N=1635
Covariates
Unadjusted LR
Adjusted LR
Adjusted LR
Single Covariate
3 Covariates Together 2 Covariates Together
SFSS-C
2.23 (1.91, 2.59)**
1.94 (1.49, 2.52)**
2.00 (1.58, 2.54)**
SFSS-Y
1.28 (1.12, 1.46)** 0.91 (0.76, 1.10)
SFSS-A
1.51 (1.27, 1.80)** 1.25 (1.01, 1.55)*
1.14 (0.93, 1.39)
Note. Confidence limits are in parentheses
*p<0.05, **p<0.01
Crisis in Usual Care 35
Table 4. Odds Ratio Results from Topics Logistic Regressions
Outcome is Crisis in Session (0/1)
Sample Size N=7231
Covariates
Unadjusted LR
Adjusted LR
Single Covariate
2 Covariates Together
# Topics Discussed x Session
1.15 (1.13, 1.17)**
1.18 (1.15, 1.22)**
SRF Index
1.12 (1.11, 1.14)**
0.969 (0.941, 0.998)a
Note. Confidence limits are in parentheses
*p<0.05, **p<0.01
a
lost significance because of >10% change in coefficient value
Crisis in Usual Care 36
Table 5. Logistic Regression Analysis of Crisis in a Session with TA and Topics Covariates
Covariates
β
SE β Wald’s df
p
eβ
95% CI
2
χ
(odds ratio)
Constant
-0.86 0.25 12.13
1 <0.001
0.42
NA
TAQS-C
Clinician-client -0.47
0.06
60.37
1
<0.001
0.62
(0.55, 0.70)
# Topics
0.15
0.01 162.54 1 <0.001
1.16
(1.13, 1.19)
Discussed x
Session
Test
χ2
df
p
Overall Model Evaluation
χ2
215.60 2 <0.001
Goodness-of-fit test
Hosmer &
6.06
8
0.64
Lemeshow
Note. Sample Size N=2945 Cox and Snell R2=.071. Nagelkerke R2=0.107. NA=not applicable
Crisis in Usual Care 37
Table 6. Logistic Regression Analysis of Crisis in a Session with SFSS and Topics
Covariates
Covariates
β
SE β Wald’s df
p
eβ
95% CI
χ2
(odds ratio)
Constant
-3.86 0.22
337.71
1
<0.001
0.02
NA
SFSS--Clinician
<0.001
0.71
0.08
78.60
1
(1.74, 2.28)
2.03
# Topics
0.11
0.01
97.90
1
<0.001
1.12
(1.10, 1.15)
Discussed x
Session
Test
χ2
df
p
Overall Model Evaluation
χ2
208.68
2
<0.001
Goodness-of-fit test
Hosmer &
8.73
8
0.37
Lemeshow
Note. Samples Size N=2958 Cox and Snell R2=.068. Nagelkerke R2=0.105. NA=Not applicable
Crisis in Usual Care 38
Table 7. Results from Clinician Characteristics Logistic Regression
Outcome is Crisis (0/1)
N=4600
Covariates
Unadjusted LR
Adjusted LR
Single Covariate
3 Covariates Together
Clinician Age
1.02 (1.02, 1.03)**
1.01 (1.00, 1.01)
# of Clients x Clinician
0.973 (0.959, 0.987)**
0.96 (0.94, 0.98)**
# of Topics/Session x
1.14 (1.12, 1.17)**
1.16 (1.13, 1.19)**
Clinician
# of Sessions x
1.00 (.999, 1.00)
Clinician
Note. Confidence limits are in parentheses
*p<0.05, **p<0.01
Adjusted LR
2 Covariates Together
1.00 (0.99, 1.02)
1.15 (1.12, 1.17)**
Crisis in Usual Care 39
Table 8. Odds Ratio Results from Client Characteristics Logistic Regressions
Outcome is Crisis (0/1)
N=6349
Covariates
Unadjusted LR
Adjusted LR
Single Covariate
2 Covariates together
Client Age
1.04 (1.01, 1.07)*
1.03 (1.00, 1.06)
Client Gender
-0.11(0.80, 1.01)
# of Topics/Session x 1.17 (1.15, 1.19)**
1.17 (1.15, 1.19)**
Client
# of Sessions x Client
1.00 (0.99, 1.00)
Note. Confidence limits are in parentheses.
*p<0.05, **p<0.01
Crisis in Usual Care 40
Table 9. Logistic Regression Analysis of a Crisis in a Session with TA and Topics
Covariates
Covariates
β
SE β Wald’s df
p
eβ
95% CI
2
χ
(odds ratio)
Constant
-1.88
0.35
31.53
1
<0.001
0.14
NA
TAQS-C
Clinician-client
-0.47
0.09
29.98
1
<0.001
0.63
(0.53, 0.74)
# Topics
0.13
0.02
66.91
1
<0.001
1.14
(1.11, 1.18)
Discussed x
Session
Test
χ2
df
p
Overall Model Evaluation
χ2
89.79
2
<0.001
Goodness-of-fit test
Hosmer &
4.23
8
0.83
Lemeshow
Note. Samples Size N=2945 Cox and Snell R2=0.03. Nagelkerke R2=0.069. NA=not applicable
Crisis in Usual Care 41
Table 10. Logistic Regression Analysis of a Crisis in a Session with SFSS and Topics
Covariates
Covariates
β
SE Wald’s df
p
eβ
95% CI
2
β
χ
(odds ratio)
Constant
-5.32 0.34 250.80 1 <0.001
0.01
NA
SFSS-Clinician
<0.001
# Topics Discussed x
Session
Test
Overall Model Evaluation
χ2
0.80
0.12
42.84
1
0.09
0.02
28.52
1
χ2
df
84.48
2
2.22
(1.75, 2.82)
<0.001
1.10
(1.06, 1.14)
p
<0.001
Goodness-of-fit test
Hosmer & Lemeshow
11.15
8
0.19
2
Note. Sample Size=2958. Cox and Snell R =0.028. Nagelkerke R2=0.069. NA=not applicable.
Crisis in Usual Care 42
Table 11. Logistic Regression Analysis of a Crisis in a Session with a Client Characteristic
as Covariate
Covariates
β
SE β Wald’s df
p
eβ
95% CI
2
χ
(odds ratio)
Constant
-3.62 0.15 614.87
1
<0.001
0.03
NA
# Topics
0.12
0.01
73.90
1
Discussed/Session
x Client
Test
χ2
df
Overall Model Evaluation
χ2
71.85
1
Goodness-of-fit test
Hosmer &
49.01
8
Lemeshow
Note. Sample Size N=7267. Cox and Snell R2=0.01.
<0.001
1.12
(1.10, 1.16)
p
<0.001
<0.001
Nagelkerke R2=0.023. NA=not applicable.
Crisis in Usual Care 43
Table 12. Logistic Regression Analysis of a Crisis in a Session with a Clinician
Characteristic as Covariate
Covariates
β
SE β Wald’s df
p
eβ
95% CI
2
χ
(odds ratio)
Constant
-3.28 0.15 495.54 1
0.001
0.04
NA
# Topics
0.08
0.01
34.65
1
0.001
1.09
(1.06,1.12)
Discussed/Session
x Clinician
Test
χ2
df
p
Overall Model Evaluation
χ2
33.57
1 <0.001
Goodness-of-fit test
Hosmer &
78.78
8 <0.001
Lemeshow
Note. Sample Size N=7267. Cox and Snell R2=0.005. Nagelkerke R2=0.011. NA=not applicable.
Crisis in Usual Care 44
Table 13. Predicted Probability of a Crisis
in a Session from Hypothetical Data of
TA and Topics
TA
Score
β= -0.47
#Topics Intercept
β=0.148 β= -0.86
1
0
-0.86
Predicted
Probability
of a Crisis in
a Session
0.209159365
1
1
-0.86
0.234692781
1
2
-0.86
0.262309356
1
3
-0.86
0.291935976
1
4
-0.86
0.323441643
1
5
-0.86
0.356634854
1
6
-0.86
0.391264513
1
7
-0.86
0.427024884
1
8
-0.86
0.463564698
1
9
-0.86
0.5005
1
10
-0.86
0.537429845
1
11
-0.86
0.573953528
1
12
-0.86
0.609687778
1
13
-0.86
0.644282404
1
14
-0.86
0.677433046
1
15
-0.86
0.708890173
1
16
-0.86
0.73846392
1
17
-0.86
0.766024904
1
18
-0.86
0.791501512
TA
Score
β= -0.47
#Topics Intercept
β=0.148 β= -0.86
1
20
-0.86
Predicted
Probability
of a Crisis in
a Session
0.836169639
1
21
-0.86
0.855449731
1
22
-0.86
0.872806019
1
23
-0.86
0.888350314
1
24
-0.86
0.902207795
1
25
-0.86
0.914510861
1
26
-0.86
0.925394093
1
27
-0.86
0.93499032
1
28
-0.86
0.943427686
1
29
-0.86
0.950827587
1
30
-0.86
0.957303356
1
31
-0.86
0.96295952
1
32
-0.86
0.967891525
1
33
-0.86
0.972185793
2
0
-0.86
0.141851065
2
1
-0.86
0.160838827
2
2
-0.86
0.181829696
2
3
-0.86
0.204891176
2
4
-0.86
0.230055119
2
5
-0.86
0.257309455
2
6
-0.86
0.28659075
2
7
-0.86
0.317778454
Crisis in Usual Care 45
TA
Score
β= -0.47
#Topics Intercept
β=0.148 β= -0.86
2
8
-0.86
Predicted
Probability
of a Crisis in
a Session
0.350691735
TA
Score
β= -0.47
#Topics Intercept
β=0.148 β= -0.86
2
30
-0.86
Predicted
Probability
of a Crisis in
a Session
0.933391964
2
9
-0.86
0.385089726
2
31
-0.86
0.942023912
2
10
-0.86
0.420675748
2
32
-0.86
0.949597623
2
11
-0.86
0.457105697
2
33
-0.86
0.956227915
2
12
-0.86
0.494000288
3
0
-0.86
0.093638212
2
13
-0.86
0.53096034
3
1
-0.86
0.106976855
2
14
-0.86
0.567583836
3
2
-0.86
0.121959896
2
15
-0.86
0.60348325
3
3
-0.86
0.138715477
2
16
-0.86
0.638301558
3
4
-0.86
0.157360484
2
17
-0.86
0.671725582
3
5
-0.86
0.177993686
2
18
-0.86
0.703495691
3
6
-0.86
0.200687983
2
19
-0.86
0.73341137
3
7
-0.86
0.225482099
2
20
-0.86
0.761332715
3
8
-0.86
0.252372253
2
21
-0.86
0.787178291
3
9
-0.86
0.28130451
2
22
-0.86
0.810920123
3
10
-0.86
0.312168669
2
23
-0.86
0.832576698
3
11
-0.86
0.344794577
2
24
-0.86
0.852204883
3
12
-0.86
0.378951724
2
25
-0.86
0.869891526
3
13
-0.86
0.414352746
2
26
-0.86
0.885745374
3
14
-0.86
0.450661085
2
27
-0.86
0.899889734
3
15
-0.86
0.487502604
2
28
-0.86
0.912456133
3
16
-0.86
0.524480411
2
29
-0.86
0.923579084
3
17
-0.86
0.561191721
Crisis in Usual Care 46
TA
Score
β= -0.47
#Topics Intercept
β=0.148 β= -0.86
3
18
-0.86
Predicted
Probability
of a Crisis in
a Session
0.597245246
3
19
-0.86
0.632277546
4
6
-0.86
Predicted
Probability
of a Crisis in
a Session
0.135638245
3
20
-0.86
0.665966927
4
7
-0.86
0.153943564
3
21
-0.86
0.698043826
4
8
-0.86
0.17422137
3
22
-0.86
0.728297124
4
9
-0.86
0.196549701
3
23
-0.86
0.756576329
4
10
-0.86
0.220973892
3
24
-0.86
0.782790028
4
11
-0.86
0.247498215
3
25
-0.86
0.806901316
4
12
-0.86
0.276078043
3
26
-0.86
0.828921083
4
13
-0.86
0.306613408
3
27
-0.86
0.848900061
4
14
-0.86
0.338944819
3
28
-0.86
0.866920433
4
15
-0.86
0.372852234
3
29
-0.86
0.883087655
4
16
-0.86
0.40805784
3
30
-0.86
0.897522967
4
17
-0.86
0.444232986
3
31
-0.86
0.91035686
4
18
-0.86
0.48100914
3
32
-0.86
0.921723655
4
19
-0.86
0.517992228
3
33
-0.86
0.931757179
4
20
-0.86
0.554779235
4
0
-0.86
0.060653903
4
21
-0.86
0.59097562
4
1
-0.86
0.069655065
4
22
-0.86
0.626211958
4
2
-0.86
0.079878426
4
23
-0.86
0.66015836
4
3
-0.86
0.091454782
4
24
-0.86
0.692535528
4
4
-0.86
0.104518264
4
25
-0.86
0.723121805
4
5
-0.86
0.119202922
4
26
-0.86
0.751756062
TA
#Topics
Intercept
Predicted
TA
Score
β= -0.47
#Topics Intercept
β=0.148 β= -0.86
Crisis in Usual Care 47
Score
β= -0.47
β=0.148
β= -0.86
4
27
-0.86
Probability
of a Crisis in
a Session
0.778336762
4
28
-0.86
0.802817861
4
29
-0.86
0.825202406
4
30
-0.86
0.845534735
4
31
-0.86
0.863892109
4
32
-0.86
0.880376464
4
33
-0.86
0.895106767
5
0
-0.86
0.038791134
5
1
-0.86
0.044702217
5
2
-0.86
0.051465816
5
3
-0.86
0.059189365
5
4
-0.86
0.067988917
5
5
-0.86
0.077988235
5
6
-0.86
0.089317246
5
7
-0.86
0.102109716
5
8
-0.86
0.116500002
5
9
-0.86
0.132618767
5
10
-0.86
0.15058758
5
11
-0.86
0.17051242
5
12
-0.86
0.192476203
5
13
-0.86
0.216530622
TA
Score
β= -0.47
#Topics Intercept
β=0.148 β= -0.86
5
14
-0.86
Predicted
Probability
of a Crisis in
a Session
0.242687753
5
15
-0.86
0.270912078
5
16
-0.86
0.301113728
5
17
-0.86
0.333143845
5
18
-0.86
0.366792937
5
19
-0.86
0.401792956
5
20
-0.86
0.437823499
5
21
-0.86
0.474522086
5
22
-0.86
0.511497973
5
23
-0.86
0.548348458
5
24
-0.86
0.584676265
5
25
-0.86
0.620106432
5
26
-0.86
0.654301218
5
27
-0.86
0.686971808
5
28
-0.86
0.717886094
5
29
-0.86
0.746872278
5
30
-0.86
0.773818574
5
31
-0.86
0.798669599
5
32
-0.86
0.821420312
5
33
-0.86
0.842108397
Crisis in Usual Care 48
Appendix A
Figure 1a. Session Report Form-Side 1 ...................................................................................................... 49
Figure 1b Session Report Form-Side 2 ........................................................................................................ 50
Figure 2. TAQS-Clinician Rated ................................................................................................................... 51
Figure 3 TAQS-Client-rated ........................................................................................................................ 52
Figure 4. TAQS-Caregiver-rated .................................................................................................................. 53
Figure 6. SFSS-Client-Rated ......................................................................................................................... 55
Figure 7. SFSS-Caregiver-Rated ................................................................................................................... 56
Figure 8. Caregiver Strain Questionnaire ................................................................................................... 57
Crisis in Usual Care 49
Figure 1a. Session Report Form-Side 1
Crisis in Usual Care 50
Figure 1b Session Report Form-Side 2
Crisis in Usual Care 51
Figure 2. TAQS-Clinician Rated
Crisis in Usual Care 52
Figure 3 TAQS-Client-rated
Crisis in Usual Care 53
Figure 4. TAQS-Caregiver-rated
Crisis in Usual Care 54
Figure 5. SFSS-Clinician-Rated
Crisis in Usual Care 55
Figure 6. SFSS-Client-Rated
Crisis in Usual Care 56
Figure 7. SFSS-Caregiver-Rated
Crisis in Usual Care 57
Figure 8. Caregiver Strain Questionnaire