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THE RECOVERY DISCOURSE SPECTRUM
I. DEFINING FACTORS OF RECOVERY
Problematic conceptualizations of “outcomes” or “recovery” result from faulty and/or insensitive measures.
There is significant discursive cacophony because of:
-the multiplicity of conflicting interest groups / stakeholders
-the multiplicity of conflicting recovery perceptions/expectations
-the multiplicity of acute and chronic diagnoses / patient types (DSM-V Axis I vs Axis II)
-the multiplicity of realistic recovery limitations given certain diagnoses (prognoses) (Axis II, III, V)
-the highly subjective / individual nature of diagnoses and psychosocial environments ( Axes IV)
II. INFLUENCING STAKEHOLDERS
Stakeholders Primary Interest Envisions Recovery as
Communities (schools, neighborhoods) risk aversion, communal safety a protective measure (Axis I)
Pharmaceuticals companies/ profit, expanded client base a product
bio-med research
Government decreasing funds spent on disability, increasing citizenry (Axis IV)
deinstitutionalization, decreasing
welfare policy allowances
Court orders identifying appropriate care/help a protective measure
Inclusion laws expanding civil rights, decreasing a socio-cultural ideal (Axis IV)
discrimination
Consumer/Client/Patient personal goals/growth, empowerment, customizable choice, entitled
emancipatory imperative, lifestyle right, normalizing process,
freedom, heal secondary deviance, full citizenship, freedom from
person-centered care marginalization
Client’s Personal Caretakers rehabilitation, correction of primary varies
and secondary deviances
Outpatient Services rehabilitation, social reintegration the mastery of re-integrative
social skills (Axes IV, V)
Bio-medical/Inpatient Services parens patrie: duty of care, interventions eliminating physical causes,
on primary deviances, reduction of reduction of disabling
hospitalizing symptoms with inevitable symptoms (Axes I, III)
iatrogenesis
Healthcare Management Org. (HMOs) lowering expenditures/coverage absence of explicit/externalized
hospitalizing behaviors

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III. CONCEPTUALIZATIONS
Since the 1994 Recovery Movement, “there has been an increasing global commitment to recovery as the
expectation for people with mental illness” (Pelletier 2015). However, even a brief survey of existing
outcome research literature demonstrates that “no gold standard instrument exists for measuring
recovery” (Scheyett 2013). While “different [conceptualizations of recovery] suggest that ‘recovery’ is a
polyvalent concept that creates an uneasy consensus point to define the management philosophy of local
services enacting mental health policy” (Pilgrim 2009), “there is no comprehensive consensus of what a
definition of ‘recovery’ is even among those individuals who are themselves in recovery from substance
abuse disorders” (Dodge 2012). Essentially, because “recovery heavily depends on personal motivation
(awareness, purpose, hope, self-determination, agency, coping, health, social function, wellness, thriving,
connectedness),” “[the] central point of incommensurability between the radical user and professional
accounts [hinges on] the ontological status of mental illness” (Pilgrim 2009, Onken 2007). Although,
“hospitalization is a complex, individually determined experience, clinicians and service users have
differing perspectives on the causal risk factors and this presents complications for those developing
relapse prevention strategies,” and outcomes measures (Mgutshini 2010). Ultimately, “a shared
appreciation of the multiple realities paves the way for the development of a conceptual risk-factor
identification model which may serve as a guide for relapse prevention” (Mgutshini 2010).
For a frame of reference, compare the World Health Organization’s (WHO) definition mental health as “a
state of well-being in which every individual realizes his/her own potential, can cope with the normal
stresses of life, can work productively and fruitfully, and is able to make a contribution to her or his
community” (WHO), with the American Psychiatric Association’s (APA) definition of mental disorder as
“a clinically significant behavioral psychological syndrome or pattern that occurs in an individual and that
is associated with present distress (e.g. a painful symptom) or disability (i.e. impairment in one of more
important areas of functioning) or with a significantly increased risk of suffering, death, pain, disability, or
an important loss of freedom…. currently considered a manifestation of a behavioral, psychological, or
biological dysfunction in the individual” (APA, 2000).
According to the “new paradigm of disability in which an interaction between an individual’s personal
characteristics and features of his/her environments, disability does not live within the person. Instead it
resides in the interface between one’s personal characteristics and aspects of the environment in which one
operates” (Onken 2007). Consequently, “the ultimate goal of the consumer-based model is [trending
towards meaning the creation of] a meaningful life of dignity and empowerment in which the consumer
defines his/her personal options and life choices to function well in such communities or environments”
(Scheyett 2013). Recovery is also referred to as “internal, temporal, external” “vision, process, or
outcome, ” “a way of life” (Onken 2007, Scheyett 2013). Other definitions include “a multidimensional,
fluid, non-sequential, complex” “process of gaining mastery over illness” that “permeates the life context
of the individual,” “the constant weaving of the elements in one’s life context (psychosocial, cultural,
spiritual, economic experiences),” “living a self-directed life, striving to reach their full potential,
improving health and wellness,” “an active process of integrating mental healthcare with daily existence,
creating a purposeful life regardless of diagnoses” (Onken 2007, Salyers 2013).
More and more, there is an emphasis on distinguishing identifiable stages of the trajectory of recovery; for
example, the SISR and SIST-R emphasize distinguished stages of recovery (rather than the traditional
pre/post treatment analyses) generally identified as: moratorium/anguish, awareness, preparation,
rebuilding/conflict, growth/purpose. Another source stratifies recovery into “extreme risk; unengaged,
poorly self-coordinating; engaged, poorly self-coordinating; coping, rehabilitating; early recovery self-
reliant” (Miller 2009). Another distinguishes personal, clinical, functional, and social domains of recovery
(Hancock 2012). There has even been emphasis on developing “enhanced the precision of the [assessment]
instrument for later stages of recovery” focusing on acceptance of illness, gaining control over symptoms,

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self-love, optimism, recreational experiences, contributing through meaningful activities, having diverse
friendships, being needed and valued, coming to terms with family relationships (Hancock 2012). Also,
increasingly measuring the client’s perceived “quality of life has become a key outcome indicator in
planning and evaluating of health services” (Fleury 2015). Additionally, there is an increasing emphasis
on self-reported outcome measures to incorporate service users’ perspective, to decrease the
bias/adulteration of clinician/rater/informant bias, to avoid service users’ suggestibility (Wolpert 2015).
The major point of contention for the strength-based model revolves around the disempowering unilateral
monopoly on patient care decisions by treatment providers (Rapp 2012). The central theme of the recovery
approach is the inclusion and empowerment of the service-user “by offering facilitation in the individual’s
life for hope, opportunity, and control” (Green 2011). The main points of departure between deficit-based
and strength-based approach is on collaborative treatment “hope-inducing” claiming that goal-setting,
naturalized and more conversational “meaningful care,” and empowering deficit skills training rather than
a diagnosis label and treatment model (Rapp 2012). Historically, however, even in social work, evaluating
behavioral baselines to identify deficits then correcting those deficits has been common practice (Rapp
2012). Strength-based, social work approaches justify deinstitutionalization and de-standardization of
recovery goals by emphasizing the “importance of recognizing consumers’ unique experiences and
characteristics within recovery” (Scheyett 2013). Moreover, this approach claims that “a single ideal recovery
instrument may not be necessary; in fact, it may counter the diversity of recovery paths and experiences
explored by consumers and social workers” (Scheyett 2013). However, although the social work industry
“has long been on the philosophy and theory that flaunts clients’ strengths, [it has fallen] short on practice,
directions, guidelines, and know-how for incorporating strength-based care into practice” (Rapp 2012). In
attempting to completely outsource mental healthcare, the push for the dominance of outpatient care
seems to neglect the medical benefits and real variegated needs of certain populations of individuals with
clinical conditions. This would be the equivalent of discontinuing all specialized physicians
(neurosurgeons, cardiologists, dentists, OB/GYN…etc.) in exchange for only general family doctors or
primary care physicians (PCPs). It is important to note the value deficit testing’s utility of encouraging
greater realistic prognosis expectations and “vigilance for those patients at risk of prolonged recovery, and
to incorporate potentially modifiable predictors into management strategies” that social work historically
has lacked (Ebrahim 2015).
Luckily, there have also been advances in clinical reform. For example, the Menninger clinic has
incorporated a routine of assessments in 2008 because “mandatory measurement and reporting of results
is perhaps the single most important step in reforming the health care system” (Allen 2009).

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IV. PATIENT TYPE / DIAGNOSES
 Child/ Adolescent/ Adult/ Geriatric
 Enduring/severe/chronic/resistant
 Juvenile/Adult Offenders
 Substance Abuse Disorders
 Combat Veterans
 Mentally abnormal offenders
 Detained psychotic offenders
 Traumatized victims of
emotional/sexual/physical abuse
Presenting…..
 Externalized aggressive behaviors
 Externalized self-harm behaviors
 Internalized Cognitions / Ideations
 Mental/Intellectual Disabilities
 Physical Disabilities
 Auditory, Visual Hallucinations
 Lucid, self-sufficient but “miserable”
“With such a wide range of people receiving a label of ‘mental disorder,’ the general consensus is that
all invested interest groups need to be “informed by a range of ethnographic investigations” or “will
be left with competing rhetoric about recovery and its meaning, or meanings may be rendered
worthless” (Pilgrim 2009). A measure for recovery cannot be globally generalizable in terms of
validity, reliability, and sensitivity because “the evaluative balance, about judging recovery by intra-
personal, interpersonal, cultural, social, and legal criteria, will inevitably vary from one form of
mental health problem to another” (Scheyett 2013, Pilgrim 2009). Ultimately, researchers argue that
“recovery is much more than a reduction of symptoms; instruments that focus extensively on
symptoms may not be of maximal usefulness” (Scheyett 2013).
"The biggest variable in any study that assesses the outcome of a treatment is often the patient. Gone
are the days when patient cohorts can be assumed to be statistically comparable just because their age
and sex distributions are similar. Patient factors including depression, pain catastrophizing,
comorbidities, race, and socioeconomic status have all been shown to have significant impacts on
both treatment outcomes and PROMs scores. All these factors are now measurable and so should be
taken into account before attempting to compare treatment outcomes in different patient populations.
While there may be merit to PROMs data collection as a means of individual practice reflection, their
usefulness cannot be extrapolated to treatment or practice comparisons without rigorous patient
population standardization." (Purnell 2016).
"Multidimensional measures that are clinically meaningful need to be developed to ensure quality
and effectiveness in youth mental health. Additionally, outcomes measures can be clinically useful
when designed to be used within routine feedback monitoring systems" (Kwan 2015).

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V. POPULATION-SPECIFIC MEASURES FOR
VARIEGATED ETHNOGRAPHIC POPULATIONS
“The legacy of medically driven studies has limited the study area to reductionist and quantitative
methodologies with little acknowledgement of worthy qualitative aspects that take account of service
user attributions for their hospitalizations” which is a major critical oversight for a dynamic
population demanding a more inclusive, comparative, phenomenological attention to precipitating
hospitalizing causes. (Mgutshini 2010, Rosenblatt 2002). “Without testing by population-specific
categories, there was less consistency and agreement” among outcome measures for mental health
conditions with vastly different etiologies and trajectories (Rosenblatt 2002). For example, more often
than not, clinicians undermine social factors and instead attribute depression as the cause of social
maladaptation and unemployment, whereas the clients and occupational therapist (OT) conversely
identify unemployment, financial trouble, loss of previous function, social exclusion, lack of social
support, break ups, exclusion from mainstream activities, and unhelpful, supportive mental healthcare
professionals as causes of depression (Mgutshini 2010). Ultimately, the advocacy for population-
specific measure combinations is based on the notion that “recovery cannot be conceptualized
separately from an understanding of the lived experience of [specific populations such as] personality
disorders” (Gillard 2015). Moreover, population specific/customized assessment combinations “need
empirically supported validation of an operationally defined concept of recovery” (Hancock 2012).
SUBSTANCE ABUSE DISORDERS (Please refer to Appendix A)
For the population of SAD, recovery is defined as “well-being, sobriety, citizenship…. [the ‘early
recovery’ stage is] 1 to 3 years, ‘sustained recovery’ [is] between 3 to 5 years, ‘stable recovery is
[beyond] 5 years” (Best 2012). Whereas “researchers operationally define recovery more often as
abstinence status,” 62% of those with substance abuse addictions rated claimed recovery is “an addict
trying to stop using;” 22% rated is as “free from substance use or addiction disorders;” and 80% rated
total abstinence as the goal. (Dodge 2012). In fact, because “the average time dependent for heroin
users was 10.8 years and for drinker 15.7 years,” an absolute abstinence definition of recovery
inevitably distorts the recovery outlook given the brevity of treatment program timeframes (Best 2012).
Although, “recovery experiences vary widely, better functioning [for those recovering from SAD] is
typically reported after longer period and is associated with supportive peer groups and more
engagement in meaningful activities, and supports models promoting the development of peer
networks immersed in local communities.” (Best 2012).
Quality of life, World Health Organization’s QOL assessment (WHOQOL-BREF)
Lifetime Drug Use History
Maudsley Addiction Profile
Recovery Group Participation Scale
Social Network/functioning
Assessment of Recovery Capital (ARC)
Treatment Outcome Profile (TOP)

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PERSONALITY DISORDERS
“[R]ecovery from a personality disorder is a more complex and lengthier process than ‘recovering’
from mental illness” (Green 2011).
JUVENILE OFFENDERS (Please refer to Appendix B)
Different screening and assessment instruments are used depending on the “ type of information
sought, characteristic of the youth involved, and the context in which screening or assessment takes
place” (US DOJ). The following is a summary of the criteria for the selection of screening and
assessment: “for low levels of reading ability, simple response formats, assess mental distress and
disorder and substance abuse needs, be amenable with diverse backgrounds, offer age and gender-
based norms across the age span, assess psychological or behavioral conditions requiring immediate
intervention, have low per-case and publisher fees, involve brief and simple administration with little
to no specialized clinical expertise, easy scoring that produces uncomplicated results, allow for quick
interpretation of scores” (US DOJ). The general consensus that the following psychiatric disorders are
among “the most frequent and troubling in juvenile justice populations” : “conduct disorders, affective
disorders, anxiety disorders, substance abuse disorders, attention deficit disorders, developmental
disabilities” (US DOJ).
The handling of juvenile offenders has shifted from the social-welfare approach to emphasizing
personal accountability (Mincey 2008).
“Theoretical perspectives for juvenile offenders is based on social control theory (emphasizing that
delinquency is based on how young people bond to society) and differential association theory (youth
respond to their environments)” (Mincey 2008).
ADULT OFFENDERS (Oklahoma Department of Corrections DOC)
TCU pre-post tests
Achievement programs/credits 09.0101c
MENTALLY DISORDERED OFFENDERS
“Warner (2010), found that a substantial number of people affected with psychotic illness recover
completely or return to a ‘good’ level of functional capacity…. [In] efforts to recover ‘best possible’
functioning and developing meaning in one’s life have been shown to lead to increased quality of
life, improved self-esteem, and enhanced functioning (including return to work)” (Green 2011).
Recovery Journey Questionnaire (RJQ) (Green 2011)
YOUTH WITH SEVERE EMOTIONAL DISTURBANCE (SED) (Please refer to Appendix C)

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 GAF
 CAFAS
 CBCL
 YSR
GERIATRIC POPULATIONS (Please refer to Appendix D)
TRAUMATIZED CHILD/ADOLESCENT VICTIMS
The effect of trauma exposure on youth is significantly underrepresented, underestimated because
clients exposed to traumatic experiences display a “complex, clinical presentation” highly
misunderstood and misdiagnosed (Zelechoski 2013). Surprisingly, PTSD is not the most common
psychiatric diagnosis in children with histories of chronic trauma exposure; instead, the failure to
distinguish symptoms from child’s reaction to trauma has labeled these youth with stigmatized
diagnoses such as depression, ADHD, oppositional defiant disorder (ODD), conduct disorder
(CD), anxiety, eating disorders, sleeping disorders, communication disorders, reactive attachment
disorders, and phobias (Zelechoski 2013). In fact, “72% of traumatized youth have family
problems, 57% have school problems, 22% have skill deficits, 66% engage in aggression, 34%
display delinquent behaviors, 31% abuse substances. 49% of traumatized youth are diagnosed with
disruptive behavior disorder, CD, ADHD, and 31% are diagnoses with depression and anxiety
versus their non-traumatized youth counterparts who are diagnosed 3 - 12% for ADHD, 6 - 16%
for CD, and 8% for depression” (Zelechoski 2013). Furthermore, “it is critical to
conceptualize/understand this population as distinct from youth without histories of traumatic
exposure” because this population requires specialized trauma-informed care. Moreover, members
of this population are also foreseeably more susceptible to physical and psychiatric disorders (such
as substance abuse, borderline personality, antisocial personality, dissociative, somatoform,
cardiovascular, metabolic, immunologic, sexual disorders, and neurobiological deficits)
overlooking the implications and potential for preventative attention is astounding (Zelechoski
2013).
VICTIMS OF PTSD
According to the National Center for PTSD, There are two main types of measures used in PTSD
evaluations: structured interviews and self-report questionnaires. Each has special features that might
make it a good choice for a particular evaluation.
Commonly used structured interviews are:
 Clinician-Administered PTSD Scale (CAPS). Created by the National Center for PTSD staff, the
CAPS is one of the most widely used PTSD interviews. The questions ask how often you have
PTSD symptoms and how intense they are. The CAPS also asks about other symptoms that
commonly occur with PTSD.

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 Structured Clinical Interview for DSM (SCID). The SCID is another widely used interview. The
SCID can be used to assess a range of mental health disorders including PTSD.
Other interviews include:
 Anxiety Disorders Interview Schedule-Revised (ADIS)
 PTSD-Interview
 Structured Interview for PTSD (SI-PTSD)
 PTSD Symptom Scale Interview (PSS-I)
Commonly used self-report Questionnaires:
 PTSD Checklist (PCL).
 Impact of Events Scale-Revised (IES-R)
 Keane PTSD Scale of the MMPI-2
 Mississippi Scale for Combat Related PTSD and the Mississippi Scale for Civilians
 Posttraumatic Diagnostic Scale (PDS)
 Penn Inventory for Posttraumatic Stress
 Los Angeles Symptom Checklist (LASC)

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VI. CONFOUNDING VARIABLES OF RECOVERY
While most attribute the readmission rates of “37% to 53% of hospitalized service users within 12 months
of discharge” to the failures of clinical care and clinicians, there is extensive, but undermined contradicting
data catalyzing the rise of self-reported surveys (Mgutshini 2010, Wolpert 2015). Unexpectedly, “Service-
users cited ‘situational circumstances,’ rather than medically accepted relapse indicators such as ‘non-
adherence with prescribed medication’ as the main reasons for readmission (Mgutshini 2010). Listed are
other (perhaps more relevant) variables of recovery:
 Patients’ engagement/participation/compliance levels (Gogel 2011)
“Recovery becomes defined by successful professional interventions and the willingness of patients to
remain engaged with services” (Pilgrim 2009).
“Many adolescents entering substance abuse treatment do not stay for the full course of prescribed
treatment” (Gogel 2011).
 Patient’s commitment to follow-up care/ aftercare maintenance (Mgustshini 2010)
 Patient’s post-discharge medicine compliance (Mgustshini 2010)
 Patients’ recovery capital (socioeconomic status (SES), region, employment, environment) (Groshkova
2013, Duffy 2013, Mincey 2008)
 Patient’s personal psychosocial stressors ( AXIS IV ) (Mgutshini 2010)
 Patients’ shifting perceptions of recovery consumer-based , recovery movement, consumer advocacy
 Patients’ shifting expectations of treatment (Ebrahim 2015)
“Negative patient recovery expectations have been associated with worse outcomes across a range of clinical
conditions” (Ebrahim 2015)
 Social Factors (Mgustshini 2010)
“the pattern of repeated relapse within brief periods, often during a period of 30 days to 6 months which is
deemed unnecessary, preventable, and uncharacteristic of the course of mental illness” (Mgutshini 2010).
“readmission risk is socially, rather than medically, pre-empted” since the causes of readmission are identified as
social maladaptation, hostile family support, social exclusion by patients more often than not (Mgutshini 2010).
 Therapeutic alliance ( )
 Staff competence (Stuber 2014)
 Staff experience levels (Stuber 2014)
 Staff education levels (Stuber 2014)
 Staff perceived workplace’s orientation to recovery/trauma informed care (Stuber 2014)
 Staff participation in intensive case management (Stuber 2014)
 Staff optimism / staff recovery orientation (Chandler 2014, Tsai 2008, Salyers 2013, Gogel 2011,
Williams 2012, Rabenschlag 2013)
“[P]arents and staff underestimate their contributions to the treatment process [contributing to parent
inattendence, and staff apathy/burnout, program dropouts] and practitioners might benefit from rethinking how
to communicate the value of these stakeholders” (Gogel 2011).
“Expectations held by professionals, including treatment providers, can exert a powerful influence on [and can
change] the behavior of those they are in the position to influence” (Salyers 2013).
“Recovery orientation is the extent to which mental health services attempt to facilitate or promote personal
recovery encompassing different aspects of service delivery and practices” (Williams 2012).
Because integral state hospitals versus community ones, receive more repeat, involuntary clients, state hospital
employees are less optimistic about recovery outcomes of the patients they treat. Consequently, state hospital
employees engage in significantly less consumer advocacy (Rabenschlag 2013). ( n = 1, 150 staff members)
 Staff job satisfaction/burnout/fatigue (Rabenschlag 2013, Chandler 2014)

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“there is empirical confirmation in a study of inpatient units that found a strong correlation between patient
satisfaction and staff satisfaction and staff [rated] working conditions” (Chandler 2014).
 Staff teamwork (Chandler 2014)
“Psychiatric inpatient seclusion rates have been found to depend partially on such factors as trust between staff…
even staff with staff interactions” (Chandler 2014).
 Facility’s treatment theoretical orientation (Chandler 2014)
“Program culture has a profound and pervasive effect on the recovery of individuals served by [said] program”
(Chandler 2014).
 Facility’s ability train employees to implement/enforce theoretical oriented care (Tsai 2008)
 The inevitable reality of prognosis of certain diagnoses; realistic quality of life outlook (Fleury 2015,
Hancock 2012)
 Types of informants (Rosenblatt 2002)
 Differences across measure accessors and raters (Rosenblatt 2002)
 Subjective nature of mental health conditions (Pilgrim 2009)
 Comorbid, physical conditions contributing to higher rates of psychiatric deficits (AXES III, V )
(Bhattacharya 2014, Kleiber 2005, Poole 2009, Ari 2009).
“Individuals with depression and/or anxiety are more likely to suffer from poor physical health, high rates of
obesity and smoking” (Bhattacharya 2014).
“The prevalence of depression in patient referred to specialist pain services: [the mean age was 47.83], 72% were
diagnosed with depression, 86% reported at least mild depression” (Poole 2009).
“92% had pain complaints at admissions with 76% reporting multiple pain complaints” (Kleiber 2005).
“Data from the WHO indicates that over 75% of patients with depression in primary care settings complain of
pain-related symptoms, such as headache, stomach pain, neck and back pain, or diffuse unspecified pain.
Worldwide, 22% of all primary care patients experience persistent pain and are 4 times more likely to have
depression or anxiety than patients who are pain-free. If the pain is diffuse, the depression risk is even higher and
QOL is poorer” (Kleiber 2005).
"Compared with the general population, individuals with chronic pain have a significantly higher prevalence of
depression (20.2% vs 9.3%), PTSD (10.7% vs 3.3%), and any anxiety disorder (35.1% vs 18.1%), according to data
from the National Comorbidity Survey" (Cheatle 2014).
"of patients with complex regional pain syndrome (CRPS) or fibromyalgia have shown particularly high rates of
suicidal ideation (74% and 48%, respectively)" (Cheatle 2014).
“Results from meta-analyses showed that individuals with depression had a 64% increased risk of development of
heart disease, and a 60% increased risk of diabetes” (Bhattacharya 2014).
“Depression or anxiety results in a 43% increased incidence or exacerbation risk of COPD particularly among
non-elderly adults” (Bhattacharya 2014).
“depression and anxiety co-occur in more than 50% of individuals” (Bhattacharya 2014).
“depression-anxiety status was associated with greater risk of asthma, arthritic, COPD, diabetes, heart disease,
hypertension, osteoporosis” (Bhattacharya 2014).
“the under-diagnosis depression [associated with chronic physical pain] is slightly higher [at 67%] than the
reported 20% - 50%” (Ari 2009).
“About 65% of patients seeking help for depression also report at least one type of pain symptom” (Harvard
Health Publications)
“Many of these characteristics of pain have been associated with specific brain systems, although much remains
to be learned. Additionally, researchers have found that many of the brain systems involved with the experience
of pain overlap with the experience of basic emotions. Consequently, when people experience negative emotions
(e.g. fear, anxiety, anger), the same brain systems responsible for these emotions also amplify the experience of
pain” (National Institute of Neurological Disorders and Stroke NIH).

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VII. APPENDICES
APPENDIX A (hand out)
APPENDIX B
U.S. Department of Justice. (2004). Screening and assessing mental health and substance use disorders among youth and the
juvenile justice system. Office of Juvenile Justice and Delinquency Prevention, 7-73.

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APPENDIX C (hand out)
APPENDIX D (hand out)

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VIII. REFERENCE LIST
Pelletier, J. F., Corbière, M., Lecomte, T., Briand, C., Corrigan, P., Davidson, L., & Rowe, M. (2015). Citizenship
and recovery: two intertwined concepts for civic recovery. BMC psychiatry, 15(37).
Scheyett, A., Deluca, J., & Morgan, C. (2013). Recovery in severe mental illnesses: a literature review of recovery
measures. Social Work Research, 37(3), 286-303.
Pilgrim, D. (2009). Recovery from mental health problems: scratching the surface without ethnography. Journal of
Social Work Practice, 23(4), 475-487. DOI: 10.1080/02650530903375033
Dodge, K., Krantz, B., & Kenny, P. J. (2012). How can we begin to measure recovery? Substance Abuse Treatment,
prevention, and policy, 5(31), 1-7. Retrieved from http://www.substanceabusepolicy.com/contents/5/1/31
Onken, S. J., Craig, C. M., Ridgway, P., Ralph, R. O., & Cook, J. A. (2007). Analysis of the definitions and
elements of recovery: a review of the literature. Psychiatric Rehabilitation Journal, 31(1), 9-22. DOI:
10.2975/31.2007.9.22
Mgutshini, T. (2010). Risk factors for psychiatric re-hospitalization: an exploration. International Journal of Mental
Health Nursing, 19, 257-267.
Miller, L., Brown, T. T., Pilon, D., Scheffler, R. M., & Davis, M. (2009). Patterns of recovery from severe mental
illness: a pilot study of outcomes. Community Mental Health Journal, 46, 177-187. DOI: 10.1007/s10597-009-
9211x
Hancock, N., Bundy, A., Honey, A., Helich, S., & Tamsett, S. (2012). Measuring the later stages of the recovery
journal: insight gained from the clubhouse members. Community Mental Health Journal, 49, 323-330.
Fleury, M. J., Grenier, G., Bamvita, J. M., Tremblay, J., Shmitz, N., & Caron, J. (2015). Predictors of quality of
life in a longitudinal study of users with severe mental disorders. Fleury et al. Health and Quality of Life
Outcomes, 11(92), 1-12. Retrieved from http://www.hqlo.com/content/11/1/92
Wolpert, M., Cheng, H., & Deighton, J. (2014). Measurement issues: review of four patient reported outcome
measures: SDQ, RCADS, C/ORS and GBO- their strengths and limitations for clinical use and service
evaluation. Child and Adolescent Mental Health, 20(1), 63-70. DOI: 10.1111/camh.12065
Green, T., Batson, A., & Gudjonsson, G. (2011). The development and initial validation of a service-user led
measure for recovery of mentally disordered offenders. The Journal of Forensic Psychiatry & Psychology, 22(2),
252-265. Retrieved from http://www.informaworld.com
Ebrahim, S., Malachowski, C., Kamal el Din, M., Mulla, S. M., Montoya, L., Bance, S., & Busse, J. W. (2015).
Measures of patients’ expectations about recovery: a systematic review. Journal of Occupational
Rehabilitation, 25, 240-255.
Salyers, M. P., Brennan, M., & Kean, J. (2013). Provider expectations for recovery scale: refining a measure of
provider attitudes. Psychiatric Rehabilitation Journal, 36(3), 153-159. DOI: 10.1037/prj0000010
Gillard, S., Turner, K., & Neffgen, M. (2015). Understanding recovery in the context of lived experience of
personality disorders: a collaborative, qualitative research study. Gillard et al. BMC Psychiatry, 15(183), 1-13.
DOI: 10.1186/s12888-015-0572-0
Rosenblatt, A., & Rosenblatt, J. A. (2002). Assessing the effectiveness of care for youth with severe emotional
disturbances: is there agreement between popular outcome measures? The Journal of Behavioral Health
Services & Research, 29(3), 259-273.

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