Running head: INNOVATION IN PRACTICE

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The Impact of Education on a Mental Health Provider’s Willingness to Adopt Innovation in the
Diagnostic Process
Cara L. Quade, PMHNP-BC
Arizona State University

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Abstract

In today’s healthcare environment, there is ample evidence to support early identification of
disease and implementation of effective treatment to improve patient outcomes. The objectives
of this clinical intervention were twofold; the implementation of an innovative change within an
organization, allowing for systematic screening through incorporation of the Mood Disorder
Questionnaire (MDQ), and evaluation of mental health provider’s willingness to incorporate
practice change. A pre and post quasi-experimental design evaluated the attitude of providers
regarding practice change using the Evidence-Based Practice Attitude Scale and the utilization of
the MDQ following educational intervention. Parametric testing was used to explore
the relationship between education specific to practice change and the provider's attitude through
the use of the paired t test. The Chi-square test evaluated the use of the MDQ by clinic healthcare
providers in relation to an innovative practice change. Results of this study illustrate enhanced
provider willingness to adopt innovation and increased MDQ use following the intervention.
Ensuring provider access to screening tools and education during the process of practice change
provides a strategy for early intervention enhanced willingness to support practice evolution.
Keywords: MDQ, innovation, provider willingness, EBPAS, practice change

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The Impact of Education on a Mental Health Provider’s Willingness to Adopt Innovation in the
Diagnostic Process
In today’s healthcare environment, there is ample evidence to support early identification
of disease and implementation of effective treatment to improve patient outcomes. In order to
accomplish this task it is essential that providers have reliable tools available to them in clinical
practice that gather psychiatric symptomatology in an efficient manner and willingness to adopt
innovation. The objectives of this clinical intervention were twofold; the implementation of an
innovative change within an organization, allowing for systematic screening through
incorporation of the Mood Disorder Questionnaire (MDQ), and evaluation of mental health
provider’s willingness to incorporate practice change.
Background and Significance
According to the National Institute of Mental Health statistics (NIMH, 2014), there are an
estimated 43.6 million adults in the United States with any mental illness, representing 18.1% of
all adults. This data represents nearly 44 million individuals and research completed by the
NIMH suggests only half this number receive treatment (NIMH, 2002). Despite the prevalence
of psychiatric disorders, many individuals go without treatment due to being undiagnosed or
being misdiagnosed (Ali, Teich, & Mutter, 2015). Under-recognition of psychiatric disorders is
common and results in substantial delay in diagnosis, subsequent initiation of treatment, and
poorer outcomes (Patel et al., 2015).
Challenges in the Clinical Setting: Internal Evidence
In a community mental health clinic in rural Arizona it is evident that the current process
of psychiatric evaluation leads to variable results due to differing levels of thoroughness,
skill/experience, and documentation of symptomatology. Additionally, information gathered

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through random selection retrospective electronic chart review of 100 charts illustrated that
collection/documentation of symptomatology is not consistently adequate in regards to
diagnostic formulation based on the Diagnostic Statistical Manual (DSM-V) symptom criteria
for diagnostic inclusion. This led to misdiagnosis 25% of the time and subsequent introduction of
ineffective/inappropriate treatment. Identification of this problem led to consideration of ideas
that would allow for a more streamlined and evidence-based process by which information is
gathered, so to assure more reliable/valid results in the diagnostic formulation phase of
psychiatric treatment. Through direct interview of the administration and clinical staff, it was
found that outpatient psychiatric providers feel limited in the ability to fully assess individuals
due to short appointment times, delay in follow-up, and complex interviews that interfere with
successful information gathering.
Delay in Treatment
Explanations for delay in treatment have been attributed to poor detection of the illness,
misdiagnosis, and initiation of inappropriate treatment (Altamura, 2015). To better explain delay
in initiation of recommended treatment; Drancourt et al. (2013) propose that delay is often due to
insufficient awareness of illness, lack of screening, and implementation of appropriate treatment.
Therefore, to reduce the duration of untreated illness they support aggressive strategies to
identify disorders including tools to improve diagnostic reliability and instigation of systemic
screening (Drancourt et al., 2013). One strategy to improve diagnostic reliability and systemic
screening includes the use of screening tools in combination with the traditional interview as
they act to facilitate targeted diagnoses, treatment, and provides links to empirical literature
(Baer and Blais, 2010).

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Psychiatric questionnaires improve diagnostic accuracy with a standardized approach to
the collection of pertinent data. The use of screening tools translates into better identification and
earlier intervention/treatment, providing building blocks to improve quality of service (Barwick,
Boydell, Cunningham, and Ferguson, 2004). The use of screening tools may contribute to routine
use of standardized assessment and potentially transform the practice of psychiatry into
mainstream medicine, improving the quality of care for all psychiatric patients (Ricci, Calugi,
Miniati, and Fagiolini, 2013). This inquiry led to the clinically relevant PICO question, “In
patients who present with depression (P), how does using the Mood Disorder Questionnaire in
addition to clinical assessment (I) compared to clinical assessment alone (C) affect the diagnostic
accuracy of unipolar versus bipolar depression (0)?”
Search Strategy
Evidence pertaining to the clinical question presented above was obtained by performing
an extensive search of the following databases: US National Library of Medicine National
Institutes of Health (PubMed), Cumulative Index to Nursing and Allied Health Literature
(CINAHL), Psychology Information (PsycINFO), and Cochrane Database of Systematic
Reviews. Keywords included; psychiatry, screening, diagnosis, bipolar, mood disorder
questionnaire, and MDQ. Exclusion factors included studies published before 2011, those
written in a language other than English, protocols, doctoral dissertations, and/or age groups <18
years old. Studies chosen for inclusion included adult patients, those from other countries,
pregnancy/postpartum, inpatient and outpatient settings. All of the studies chosen for inclusion
were required to be well-documented with conclusive evidence of descriptive statistical data
addressing the reliability of the MDQ in evaluating BD disorder. Data was extracted from each

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study during the review process and organized in the evidence table for concise analysis
(Appendix A).
Evidence Synthesis: Critical Appraisal and Conclusions
Twelve studies were chosen for inclusion in this search for evidence. The levels of
evidence in the selected studies ranged from level I through level III, with one meta-analysis, a
systemic search, random controlled trials, and cohort studies (Melnyk and Fineout-Overholt,
2015). Conclusions were drawn from the evidence based on critical evaluation of the study
populations, settings, and related data analysis (Appendices A & B). The variety of research
settings, sample of individuals, diagnostic groups, and structured diagnostic interview styles
provided improved generalizability for application of the MDQ as a systematic part of the
clinical assessment process.
In conclusion, the main goal of this literature review was to determine if addition of the
MDQ in the clinical assessment process affects the diagnostic accuracy of UPD versus BD
depression. The reliability and validity of the MDQ in detecting BD is documented throughout
these articles, with p values <0.001 and 95% confidence intervals, which illustrate statistical
significance and reliability of the MDQ (Appendix A). The most substantial conclusion is that
the MDQ is an excellent tool for detecting a recent (hypo)manic episode, screening for BP
during both pregnancy and postpartum periods, and in detecting previously unrecognized BP
illness when used within a general population sample (without exclusion of BP illness)
(Appendices A & B). This information supports the use of the MDQ in a systematic screening
endeavor during the process of clinical assessment; providing improved diagnostic accuracy,
treatment implementation, and subsequent patient outcomes.
Purpose and Rationale

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The purpose of this project is twofold. First, the goal was to implement the use of the
MDQ the within diagnostic process as part of an innovative organizational change; thereby
improving the identification of BD and resultant patient outcomes. The second purpose of this
project was to evaluate mental health provider’s willingness to incorporate the use of an
evidence-based tool (MDQ) within the diagnostic process. The project outcome allows
healthcare providers to have a strategy for early intervention that includes identification of BD
specific symptoms through use of the MDQ; ultimately supporting accurate diagnosis and timely
implementation of treatment based on established guidelines.
EBP Model and Theoretical Framework
The ACE Star Model of Knowledge Transformation facilitated the practice
transformation. This model organizes the concepts of improvement of care, providing a
framework to organize evidence-based practice (EBP) processes illustrated in five major stages
of knowledge transformation (Stevens, 2004). Stevens (2004) introduces five stages, which
include discovery research, evidence summary, translation to guidelines, practice integration, and
process/outcome evaluation. Discovery research generates knowledge through inquiry and
research methodologies. Evidence summary allows for synthesis of research knowledge into a
single meaningful statement that reflects the science. The third step requires translation of the
evidence into recommendations for practice. The next step requires practice integration to create
a more sustainable system, involving individual and organizational practices. Process and
outcome evaluation act as the final step. This stage allows for evaluation of the EBP impact on
care outcomes, efficacy and efficiency of the practice change, patient/provider satisfaction, and
other various endpoints (Stevens, 2004). This model provided a foundation for sustained practice

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change based on evidence-based research, with the intent to enhance patient care through
improved diagnostics and treatment implementation.
The diffusion of innovation theory (DOI) provided the theoretical framework necessary
to guide this intervention (Rogers, 2003)(Appendix C). This theory offers valuable
understanding of the process of change, stressing the need for communication within the
adoption process (Kaminski, 2011). Rogers identified five categories of adopters and described
their influence on both innovation and adoption of change (Rogers, 2003). Rogers’ theory
allowed a step-wise guide for adoption of innovation to include the knowledge stage (literature
search and provider exposure), persuasion stage (education of providers), decision/evaluation
stage (data analysis), implementation stage (intervention implementation), and the confirmation
of adoption stage (data analysis and outcome evaluation) ( Kaminski, 2011).
Purpose Statement
The evidence gained through extensive literature review supports a systematic change in
practice, to include the use of the MDQ during the evaluation of patients presenting for
psychiatric care. Although system change is necessary to provide an improved mechanism for
data collection and enhanced diagnostic ability, it is imperative that the providers are educated of
the importance and routinely utilize the knowledge gained from the questionnaire when
formulating diagnoses. In order to evaluate the efficacy of this intervention, outcomes were
measured to include systemic use of the MDQ and the provider’s attitude toward an evidencebased practice change.
Applying Evidence into Practice: Project Methods
Project implementation required evaluation of the environment, project management, and
change management (Moran, Burson, and Conrad, 2014). Initial evaluation of the environment

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focused on the setting, the organizational culture, and the stakeholders. Subsequent project
intervention focused on the innovative change itself, to include related ethics and participants.
Setting
The setting of this project is an outpatient clinic within a rural mental health organization
in Northern Arizona. The organization was incorporated in March of 1966 and has a long and
steady history of providing behavioral health services to the local community. The organization
consists of a staff of just over 200, a budget of approximately $18 million per year, and provides
some 4,000 individuals with over 150,000 behavioral health services annually.

Intervention
This clinical intervention presents an innovative change in healthcare delivery, requiring a 3phase process for completion. The initial phase of this intervention included implementation of
the practice change, which allowed for systematic screening of individuals that presented for
psychiatric treatment. Thereby, the MDQ results were available for incorporation in the initial
diagnostic formulation and subsequent treatment planning. The second phase of the intervention
focused on education of the organization’s providers at the beginning of the data collection
phase. Learning objectives included recognition of the prevalence of BD, understanding of the
diagnostic challenges related to BD, identification of the complications related to delay in
initiation of treatment, knowledge of the MDQ, and utilization of rating scales to aid the
diagnosis of BD. The third stage of this intervention focused on the evaluation of the provider’s
willingness to adopt innovation in the diagnostic process, measured by the Evidence Based
Practice Attitude Scale (EBPAS).
Ethics: Protection of Human Subjects and Recruitment

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In order to assure protection of human subjects during the process of this intervention,
Arizona State University International Review Board approval was obtained prior to initiation of
the project and the plan was adhered to in full. Recruitment of the participants occurred at the
setting described above and during an extension endeavor offered by Health Choice Integrated
Care, for which institutional support was granted. In order to protect the participants, random
identification numbers were placed on the initial cover letter, pre-, and post-educational session
questionnaires. The survey measures were not linked with practitioner identities. No identifying
data from the patient’s MDQ survey was recorded during this project, as the chart review is only
intended to assess whether or not the MDQ was completed following the innovative practice
change.
Design
A pre and post quasi-experimental design evaluated the utilization of the MDQ following
educational intervention and the attitude of providers regarding practice change using the
EBPAS. Evaluation included the use of instruments, data collection, and subsequent analysis
using SPSS® version 23 statistical package. Parametric and Nonparametric tests were used to
analyze the outcome variables. The critical value was set at p<0.05.
Instruments
In order to evaluate the efficacy of this practice change, outcome measurement included
the use of the Mood Disorder Questionnaire (MDQ) and the provider’s attitude toward an
evidence-based practice change. Two instruments were used to measure the outcome variables,
the MDQ and the Evidence-Based Practice Attitude Scale (EBPAS).
The Mood Disorder Questionnaire. The MDQ scale is a 15-item self-screening
instrument that aids in the diagnosis of bipolar disorder (see Appendix D). The instrument

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consists of 3 sections, which include symptom endorsement, symptom clustering, and severity of
problem caused (Twiss, Jones, and Anderson, 2008). The first section consists of 13 yes/no
statements; the second section consists of one yes/no question specific to the simultaneous
occurrence of the symptoms presented; the third section consists of one question concerning the
influence of the symptoms. To accurately identify the presence of BD, the suggested standard
cutoff score is 7 or more symptoms with simultaneous occurrence and moderate or greater
impairment (Wang et al., 2015). The MDQ illustrates a summary sensitivity (.62) and specificity
(.85) in detection of BD in psychiatric outpatients with a cutoff score of 7 (Wang et al., 2015;
Hirschfeld et al., 2003). Additionally, Lin et al. (2011) found the internal consistency reliability of
the tool to be 82% and the context validity index to be 80%.
Evidence-Based Practice Attitude Scale. The EBPAS was developed to evaluate mental
healthcare provider’s attitudes towards evidence-based practice (see Appendix E). The scale is a
15-item Likert Scale that measures openness to innovation and perceived importance of using
research-based innovations in clinical practice (Aarons, 2004). The first 8 questions review the
individual’s feelings about using new types of interventions, therapy, or treatment. The last 7
questions review the individual’s likelihood of adopting innovative treatments if they had
received training specific to the intervention. The items are broken down into 4 scales, which
include requirements, appeal, openness and divergence (Aarons, 2004). Subscale scores are
computed using a mean score for each item set in order to determine the total score. Chronbach’s
alpha illustrated internal consistency in reliability, ranging from high to moderate (3 items;
α=0.93), appeal (4 items; α = 0.74), openness (4 items; α=0.81), divergence (4 items; α=0.66), and
EBPAS Total (15-items; α=0.79) (Aarons, 2004).
Data Collection

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The MDQ data was collected once 8 weeks after the MDQ practice change was initiated.
Data extraction included a retrospective chart review of all new psychiatric evaluations
completed within the 8-week period prior to intervention and focused on MDQ use by providers,
provider type, and patient’s primary diagnosis. Post-intervention data was obtained by reviewing
the charts of individuals with psychiatric evaluations completed within the 8-week period
subsequent to the intervention. The collection process was identical for audit of pre and postintervention data.
Psychiatric providers were asked to complete the EBPAS prior to the educational session,
which included demographic questions. Participants then spent 30 minutes in the educational
intervention prior to completing the post-education EBPAS. The EBPAS allowed for evaluation
of the provider’s attitude toward the practice change both before and after a 30-minute
educational session regarding use of the MDQ. The educational session was conducted during the
medical staff meeting for all staff. Evaluation of EBPAS results illustrated the effectiveness of
education when implementing innovative change.
Chart Audit. Chart audit provides a tool for quality improvement that illustrates purpose
in required measurements, administrative requirements, research, and quality improvement
(Quality improvement, 2017). Research applications include audits to determine prevalence of
conditions by taking a snapshot sample to evaluate if processes are being followed (University
Hospitals Bristol, 2017).
Data Analysis
The SPSS® version 23 statistical package was used to analyze the data. Descriptive
statistics were used to describe the sample and outcome variables. A chi-square test was
conducted to test the use of the MDQ in relation to the innovative practice change. A chi-square

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evaluates whether or not two variables are independent of each other (Cronk, 2014). A paired ttest was used test the provider’s willingness to adopt innovation in practice in relationship to
education. A paired t-test is a parametric test that allows the comparison of two scores (Keller
and Kelvin, 2014). The critical value was set at p<0.05.
Project Results
The plan for statistical analysis included evaluation of three specific data sets; provider
demographics, the use of the MDQ pre- and post-implementation of the practice change, and
evaluation of the EBPAS pre-and post-educational intervention.
Descriptive statistics were used to evaluate the sample (n=29), that included 8 psychiatric
providers in a rural mental healthcare organization and 21 additional participants from the
extension opportunity. The sample (n=29) consisted of 10 (34.5%) psychiatrists, 18 (62.1%) nurse
practitioners (NPs), and 1 (3.4%) physician’s assistant (PA). The ages were categorized into 4 age
groups: 18-34 (n=1, 3.4%), 34-54 (n=13, 44.8%), 55-74 (n=11, 37.9%), and 75+ years (n=4,
13.8%). Years of experience in the psychiatric field were 6-10(n=5, 17.2%), 11-15 (n=9, 31.0%),
16-20 (n=7, 24.1%), 21-25 (n=2, 6.9%), and 26+ (n=6, 20.7%). The providers were asked if they
had previously used psychiatric screening questionnaires. Twenty-six (89.7%) of the responders
answered yes; however, a greater percentage had utilized screening questionnaires, 19 (65.5%)
had not used the MDQ in practice. The reasons provided were the following: the tool was not
available (n=12, 44.4%), takes too much time (n=4, 13.8%), or other (n=3, 10.3%).
The chart audit consisted of 300 chart reviews; including all new psychiatric evaluations
within the 8 weeks before and after the intervention. The average age of patients was 31.80
(SD=19.30) years, 207 (69%) of which were adults and 93 (31%) child or adolescent. Appraisal
of all new psychiatric evaluations (n=181) completed within the 8 weeks prior to systemic

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screening implementation illustrated that the MDQ was used in 27 (14.9%) of all evaluations.
The evaluations were completed by differing provider specialties, to include 2 (1.1%) PAs, 148
(81.8%) by NPs, and 31 (17.1%) by psychiatrists. The MDQ was not used by the Pas; however,
it was used in 21 out of 127 (16.5%) evaluations by NPs, and 6 out of 25 (24%) by physicians.
The chart audits (n=119) following implementation of systematic screening illustrated that the
MDQ was used in 94 (79%) of the evaluations. Eleven (9.2%) MDQ evaluations were completed
by physicians and 108 (90.8%) were competed by NPs, illustrating improved MDQ use by NPs
(78.7%) and physicians (90.9%). A chi-square test of independence was calculated comparing
the results of MDQ use pre and post-intervention. No significant relationship was found (χ2(1) =
.575, p< .001). Pre and post-intervention MDQ use appear to be independent events, indicating
that there is not significant dependence of one variable upon the other (Cronk, 2014).
A paired t test was used to evaluate the provider’s attitude towards willingness to adopt
innovation. Analysis compared the average pre and posttest EBPAS domain scores for
requirement, appeal, openness, and divergence (See Table 1). A paired-samples t test was
calculated to compare the mean pre-intervention scores to the mean post-intervention scores. The
mean on the pre-intervention was 40.69 (sd=8.05), and the mean on the post-intervention was
41.17 (sd=7.57). A significant increase from pretest to posttest was found (t(28)=-1.09), p<.001).
This demonstrates that education regarding practice change significantly affects provider’s
willingness to adopt innovation in the practice setting.
Table 1
Pre and Posttest EBPAS Scores
EBPAS Scale
Requirement
Appeal
Openness
Divergence

n
29
29
29
29

Pre
M(SD)
7.10(4.09)
12.00(2.60)
10.48(3.46)
11.10(2.98)

min
.00
6.0
1.0
4.0

max
12.0
16.0
15.0
16.0

n
29
29
29
29

Post
M(SD)
6.86(4.18)
12.38(2.53)
11.24(2.77)
10.69(2.61)

min
.00
6.0
3.0
4.0

max
12.0
16.0
16.0
16.0

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Discussion

This project offers value through both insights and consequences of evidence-based
practice evolution. Firstly, through the process of a strategic change, innovation can occur within
the practice setting. This sets the stage for improved patient outcomes through systemic
screening; ultimately allowing for identification of disorders and more timely treatment
implementation. Secondly, this project brings about awareness of the importance of provider
participation in innovative change. The implications of this project are potentially limitless, as it
indicates that team involvement and education have the potential to enhance the process of
innovation.
Limitations
This study has several important limitations. The design is a simple pre-post design that
includes a small sample size. This reduces generalizability and the strength of statistical analysis
available for use in data evaluation. Another limitation is present within the systemic screening
endeavor, as paper questionnaires were used. This left room for human error, in that they were not
given to every patient, nor uploaded to the electronic health record in all cases. Additionally, this
study does not address the knowledge gained from MDQ use or impact on patient outcomes.
Future research recommendations include use of larger sample sizes and electronic measures to
assure more consistency in strategic enactment of change, as well as the impact on patient
outcomes.
Sustainability
The complex healthcare environment requires evidence-based approaches to care delivery,
alongside interprofessional collaboration, to assure process sustainment (White, Pillay, and
Huang, 2016). In order to assure sustainability of this intervention, recommendations include

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incorporating the use of the MDQ in the electronic medical record, regular auditing of use in the
diagnostic process, and ongoing educational endeavors to support improved collaboration
between the evidence and clinical practice.
Summary
The practice environment is complex and providers face numerous challenges in
providing care to patients in an efficient manner. This paper illustrates the need for healthcare
providers to have a strategy for early intervention that includes identification of bipolar specific
symptoms through use of the MDQ; ultimately supporting accurate diagnosis and timely
implementation of treatment based on established guidelines. Additionally, innovation in practice
is necessary in order to implement best practice findings in a timely fashion. Through
incorporation of provider education and engagement there is enhanced willingness to adopt
innovation in the practice setting. This supports improved patient and system-specific outcomes.
The combined efforts of this innovative practice change have a foundation of evidence-based
literature subsequently guided by outcome measurement, which acts to ultimately enhance
provider efficiency and efficacy in the diagnostic process and improve patient outcomes.

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10.1371/journal.pone.0126530.
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Poon, Y., Chung, K., Tso, K., Chang, C., & Tang, D. (2011). The use of the mood disorder
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111–117.

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21

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APPLICATION OF THE MOOD DISORDER QUESTIONNAIRE

21

Appendix A
Evaluation Table
Citation

Conceptual
Framework

Design/Method

Sample/Setting

Major
Variables &
Definitions

Measurement

Data Analysis

Findings

Decision for Use
in Practice/
Application to
Practice

Wang, H. R. (2015). The
validity of the mood
disorder questionnaire for
screening bipolar disorder:
A meta-analysis.
Population: Worldwide,
with evaluation of Eastern
versus Western countries
Funding: Nothing to
declare
Bias: None reported
LOE: I

None Stated,
Constructivist
Theory
implied.

Design:
Comprehensive
literature search using
multiple databases.
Method of the Cochran
Diagnostic Test
Accuracy Working
group for Metaanalysis. Bivariate
random effects model.
Purpose: To calculate
the summary
sensitivity and
specificity,
determining the
diagnostic accuracy of
the MDQ.
Inclusion Criteria:
studies provided data
regarding diagnostic
accuracy of the MDQ
for screening BP,
DSM or ICD was used

n = 21 studies

IV1: Ψ Eval

QUADAS 2

IP and OP

IV2: MDQ

1,346 articles reviewed
for inclusion. 1,276
excluded (didn’t meet
criteria), 4 were poster
abstracts, 4 did not
provide information
regarding diagnostic
accuracy of the MDQ
and one was a review
article

DVI: Ψ DG/ A

MDQ with standard
and modified cutoff
score.

7 studies excluded
patients with prior DX
of BP. 14 included
both patients with
MDD and BP.
20 studies -MDQ
standard cutoff score
7.

DV2: MDQ
Score/DX A

Diagnostic accuracy
of the MDQ
evaluated via
analysis of HSROC

Cochrane
Diagnostic Test
Accuracy
Working Group.
Calculation of
summary
sensitivity,
summary
specificity, and
pooled DORs.
Subgroup
analyses
evaluating
impact on
diagnostic
accuracy.
Bivariate
Random Effects
Model
Pooled DORs
using STATA

No significant
differences in
diagnostic
accuracy
between
countries.
At cutoff of 7,
summary
sensitivity was
low and
heterogeneity
was high.

Clinicians may
consider modifying
the cutoff to improve
sensitivity of the
MDQ.
Consider various
population
characteristics.

Studies
excluding PTS
with BP
reduced SN to
0.37 (95% CI),
with SP of 0.88.
Studies with
MDD and BD
SN=0.76 and

Ψ –Psychiatric, A- Accuracy, AA- Average Age, ADJ-Adjustment Disorder, AF-Atypical Features, AOI- Age of Onset of Illness, AX-Anxiety Disorder, AUC- Area Under the Curve, BP- Bipolar
Disorder, BPI- Bipolar I Disorder, BPII- Bipolar II Disorder, BPNOS- Bipolar Disorder Not Otherwise Specified, - BSDS- Bipolar Spectrum Diagnostic Scale, CD- College Degree 2 year, CIConfidence Interval, CIDI-Composite International Diagnostic Interview, CL-Common Law, CP- Clinical Practice, DC-Discharge, DD NOS-Depressive Disorder Not Otherwise Specified, DEPDepression, DEM-Dementia, DO-Disorder, DOI- Duration of Illness in Months, DOR-Diagnostic Odds Ratios, DV1-Dependent Variable 1, DV2-Dependent Variable 2, DX- Diagnosis, DYSDysthymia, ED-Education, EVAL-Evaluation, F-Female, FHX-Family History, FU-Follow Up, HAM- Hamilton Depression Rating Scale, HCL-32- Hypomania Checklist-32, HS- High School,
HSROC-Hierarchical Summary Receiver Operating Characteristics, IC-Informed Consent, IP- Inpatient, IV1-Independent Variable 1,IV2- Independent Variable 2, LOE-Level of Evidence, LOEDLevel of Education, M- Male, MA-Married, MDD- Major Depressive Disorder, MDE-Major Depressive Episode, MDQ- Mood Disorder Questionnaire, MDQ-C- Mood Disorder Questionnaire Chinese
Version, MED-Medical Disorder, MH-Mental Health, MINI- Mini Neuropsychological Interview, MR- Mental Retardation, MS-Marital Status, N-Number, NESDA-Netherlands Study of Depression
and Anxiety, NOHRD- Netherlands Organization for Health Research and Development, OA-Onset Age, NPV- Negative Predictive Value, OCD-Obsessive Compulsive Disorder, ORG-Organic
Disorder, OP-Outpatient, PG-Pregnant, PP- Postpartum, PPV- Positive Predictive Value, PSYCH- Psychotic Disorder, PTS-Patients, Q-Questionnaire, QOL-Quality of Life, QUADAS 2- Quality
Assessment of Diagnostic Accuracy Studies-2, ROC- Receiver Operating Characteristic, S- Single, SCID- Standard Clinical Interview for DSM Disorders, SD-Standard Deviation, SEIFA-SocioEconomic Index For Areas SN- Sensitivity, SP- Specificity, SSPS- Statistical Package for the Social Sciences, SUB- Substance Disorder,TR-Treatment Resistant, UN- University Degree, UPD-Unipolar
Depression, YR-Year

APPLICATION OF THE MOOD DISORDER QUESTIONNAIRE
Citation

Conceptual
Framework

Design/Method

Sample/Setting

24
Major
Variables &
Definitions

Measurement

Data Analysis

Findings

Decision for Use
in Practice/
Application to
Practice

as the standard
reference diagnostic
method, and published
in peer-reviewed
journal.

Western Countries=11,
Eastern=10.

SP=0.81
Applying
optimal cutoff
at 7, SN=0.78,
SP=0.76

All studies based on
DSM-IV or DSM-IVTR

Exclusion Criteria:
PTS without mood
disorders were
participants, studies
were conducted in
general population
samples, or studies
were written in
languages other than
English.

Frey, B. N. (2012).
Sensitivity and specificity
of the mood disorder
questionnaire as a
screening tool for bipolar
disorder during pregnancy
and the postpartum period.

None Stated.
Donabedian
Model
inferred.

Design: Crosssectional psychometric
study. Consecutive.

Low SN and SP
explained by
lowering of the
prevalence
through
extraction of
BD cases and
remaining cases
that were more
difficult to
diagnose.
N= 150 (PG N-95, PP
N-55)

IV1-Ψ EVAL
DV1- Ψ DX A

Age range= 17-43

MDQ SN and SP
analysis.

SN, SP, PPV,
NPV, and
chancecorrected level
of agreement
were obtained
using statistical
package R,
version 2.13.1

Standard cutoff
score of 7:
SN=0.39,
SP=0.91, 95%
CI

Using alternative
scoring algorithm
makes the MDQ an
excellent tool
beneficial in
screening for BP
during both PG and
PP periods.

Psychometric data
interpreted
Mean 30.1
according to the
criteria:
Modified cutoff
SD=5.5
>0.80=excellent/hig
at 8: SN=0.87,
Population: PG or PP
hly correlated, 0.80SP=0.85, 95%
MS- S(26%), CL
women referred to a
0.70=
CI
Prevalence of
women’s mental health OP
good/adequate
gestational diabetes
Ψ –Psychiatric, A-Accuracy, AA- Average Age, ADJ-Adjustment Disorder, AF-Atypical Features, AOI- Age of Onset of Illness, AUC- Area Under the Curve, AX-Anxiety Disorder, BP- Bipolar
Disorder, BPI- Bipolar I Disorder, BPII- Bipolar II Disorder, BPNOS- Bipolar Disorder Not Otherwise Specified, - BSDS- Bipolar Spectrum Diagnostic Scale, CD- College Degree 2 year, CIConfidence Interval, CIDI-Composite International Diagnostic Interview, CL-Common Law, CP-Clinical Practice, DC-Discharge, DD NOS-Depressive Disorder Not Otherwise Specified, DEPDepression, DEM-Dementia, DO-Disorder, DOI- Duration of Illness in Months, DOR-Diagnostic Odds Ratios, DV1-Dependent Variable 1, DV2-Dependent Variable 2, DX- Diagnosis, DYSDysthymia, ED-Education, EVAL-Evaluation, F-Female, FHX-Family History, FU-Follow Up, HAM- Hamilton Depression Rating Scale, HCL-32- Hypomania Checklist-32, HS- High School,
HSROC-Hierarchical Summary Receiver Operating Characteristics, IC-Informed Consent, IP- Inpatient, IV1-Independent Variable 1,IV2- Independent Variable 2, LOE-Level of Evidence, LOEDLevel of Education, M- Male, MA-Married, MDD- Major Depressive Disorder, MDE-Major Depressive Episode, MDQ- Mood Disorder Questionnaire, MDQ-C- Mood Disorder Questionnaire Chinese
Version, MED-Medical Disorder, MH-Mental Health, MINI- Mini Neuropsychological Interview, MR- Mental Retardation, MS-Marital Status, N-Number, NESDA-Netherlands Study of Depression
and Anxiety, NOHRD- Netherlands Organization for Health Research and Development, NPV-Negative Predictive Value, OA-Onset Age, OCD-Obsessive Compulsive Disorder, ORG-Organic
Disorder, OP-Outpatient, PG-Pregnant, PP- Postpartum,,PPV-Positive Predictive Value, PSYCH- Psychotic Disorder, PTS-Patients, Q-Questionnaire, QOL-Quality of Life, QUADAS 2- Quality
Assessment of Diagnostic Accuracy Studies-2, ROC- Receiver Operating Characteristic, S- Single, SCID- Standard Clinical Interview for DSM Disorders,SD-Standard Deviation, SEIFA- SocioEconomic Index for Areas, SN- Sensitivity, SP- Specificity, SSPS- Statistical Package for the Social Sciences, SUB- Substance Disorder, TR-Treatment Resistant,UN- University Degree, UPD-Unipolar
Depression, YR-Year
Purpose: to investigate
the use of the MDQ as
a screening tool for BP
in a community-based
population of PG and
PP women.

DV2- MDQ
score/ DX A

APPLICATION OF THE MOOD DISORDER QUESTIONNAIRE
Citation

Conceptual
Framework

Design/Method

Sample/Setting

25
Major
Variables &
Definitions

Measurement

Data Analysis

Findings

Decision for Use
in Practice/
Application to
Practice

program in Ontario.

Inclusion Criteria:
Women who were PG
or PP
Exclusion Criteria: All
other populations.

Funding: Supported in part
by the Father Sean
O’Sullivan Research
Award.

(13.3%), MA (58%)

correlation, 0.690.50= fair/fair
correlation,
<0.50=poor/poor
correlation

ED- HS (16.7%), CD
(27.3), UN (26.7)

(2-6%) is similar to
bipolar disorder
(4%), yet providers
fail to regularly
screen for BP.

ΨDX- MDD (50.7%),
AX (17.3%), BP
(12%), ADJ (9.3%),
SUB (3.3%), PSYCH
(2%)

Bias: No financial
relationships relevant to
the subject of this article.
LOE:III
Boschloo, L. (2013). The
mood disorder
questionnaire (MDQ) for
detecting (hypo)manic
episodes: Its validity and
impact of recall bias.

None Stated.
Donabedian
Model
inferred.

Design: Longitudinal
research design,
Intervention study.

IV1-Ψ EVAL
DV1- Ψ DX A

N=2981

Population: Adult patient
recruited from various
sites, Netherlands.

Purpose: to examine
the validity of the
MDQ in detecting
hypomanic episode
and explore the impact
of recall bias.

Funding: The study was
supported by participating
universities and mental
health care organizations

Inclusion Criteria:PTS
with DEP or AX DX
or referred without
DX.

Bias: Authors have

Sample: data derived
from the NESDA.

With DP DX= 2329
(78%)
Without DP DX= 652
(22%)
Recruited from the
community (19%),
Primary care (54%),
and OP MH (27%)
Recruited

DV2- MDQ
score A

Presence of
(hypo)mania
measured with
CIDI
MDQ, with
standard cutoff at 7

Conducted
using SPSS
version 20.0
Internal
consistency
expressed in
Cronbach’s
alpha:
substantial
(0.81-1.00),
moderate (0.610.80), fair (0.410.60), slight
(0.11-0.40) and
virtually no

Reliability:
internal
consistency
0.84, cronbachs
alpha 0.85.

The validity of the
MDQ for detecting a
recent (hypo)manic
episode was
excellent.

Validity:
AUC=0.83,
95% CI,
p<0.001,
SN=0.85,
SP=0.65

Standard cutoff point
≥7 appeared optimal.
With good SN and
SP. However, there
was poor
performance for
lifetime episodes.

Standard cutoff
≥7 showed to
be optimal with
SN=0.83 and

Ψ –Psychiatric, A-Accuracy, AA- Average Age, ADJ-Adjustment Disorder, AF-Atypical Features, AOI- Age of Onset of Illness, AUC- Area Under the Curve, AX-Anxiety Disorder, BP- Bipolar
Disorder, BPI- Bipolar I Disorder, BPII- Bipolar II Disorder, BPNOS- Bipolar Disorder Not Otherwise Specified, - BSDS- Bipolar Spectrum Diagnostic Scale, CD- College Degree 2 year, CIConfidence Interval, CIDI-Composite International Diagnostic Interview, CL-Common Law, CP-Clinical Practice, DC-Discharge, DD NOS-Depressive Disorder Not Otherwise Specified, DEPDepression, DEM-Dementia, DO-Disorder, DOI- Duration of Illness in Months, DOR-Diagnostic Odds Ratios, DV1-Dependent Variable 1, DV2-Dependent Variable 2, DX- Diagnosis, DYSDysthymia, ED-Education, EVAL-Evaluation, F-Female, FHX-Family History, FU-Follow Up, HAM- Hamilton Depression Rating Scale, HCL-32- Hypomania Checklist-32, HS- High School,
HSROC-Hierarchical Summary Receiver Operating Characteristics, IC-Informed Consent, IP- Inpatient, IV1-Independent Variable 1,IV2- Independent Variable 2, LOE-Level of Evidence, LOEDLevel of Education, M- Male, MA-Married, MDD- Major Depressive Disorder, MDE-Major Depressive Episode, MDQ- Mood Disorder Questionnaire, MDQ-C- Mood Disorder Questionnaire Chinese
Version, MED-Medical Disorder, MH-Mental Health, MINI- Mini Neuropsychological Interview, MR- Mental Retardation, MS-Marital Status, N-Number, NESDA-Netherlands Study of Depression
and Anxiety, NOHRD- Netherlands Organization for Health Research and Development, NPV-Negative Predictive Value, OA-Onset Age, OCD-Obsessive Compulsive Disorder, ORG-Organic
Disorder, OP-Outpatient, PG-Pregnant, PP- Postpartum,,PPV-Positive Predictive Value, PSYCH- Psychotic Disorder, PTS-Patients, Q-Questionnaire, QOL-Quality of Life, QUADAS 2- Quality
Assessment of Diagnostic Accuracy Studies-2, ROC- Receiver Operating Characteristic, S- Single, SCID- Standard Clinical Interview for DSM Disorders,SD-Standard Deviation, SEIFA- SocioEconomic Index for Areas, SN- Sensitivity, SP- Specificity, SSPS- Statistical Package for the Social Sciences, SUB- Substance Disorder, TR-Treatment Resistant,UN- University Degree, UPD-Unipolar
Depression, YR-Year

APPLICATION OF THE MOOD DISORDER QUESTIONNAIRE
Citation

Conceptual
Framework

Design/Method

Sample/Setting

26
Major
Variables &
Definitions

Measurement

Data Analysis

Findings

Decision for Use
in Practice/
Application to
Practice

received speaking fees and
unrestricted grants from
pharmaceutical companies
and NOHRD.
LOE:II

Gan, Z. (2012). Validation
of the Chinese version of
the mood disorder
questionnaire for screening
bipolar disorder among
patient with a current
depressive episode.
Population: patients treated
in the psychiatry
department, the 3rd
Affiliated Hospital of Sun
Yat-sen University.
Funding: Natural Science
Foundation of Guangdong
Province, China.

None Stated.
Donabedian
Model
inferred.

Exclusion Criteria:
PTS with primary BP
DX, insufficient
command of the Dutch
language, incomplete
EVAL, incomplete
MDQ data, OCD,
SUB, PSYCH, or
ORG.

Consecutively

Design: Controlled
Trial- Intervention
study

N- 142 consecutive
PTS

Purpose: Evaluate the
validity of the Chinese
version of the MDQ in
screening BP in PTS
with current MDE.
Inclusion Criteria:
Eligible subjects were
treated concurrently
for MDE in the
psychiatric
department, who
provided informed

(0.00-0.10)

SP=0.82

Performance of
MDQ in
detecting
lifetime
hypomanic
episode
examined by
processing a
ROC curve.
IV1-SCID-1

Instrument use of
SCID-I

IV2-MDQ
INP=102 (71.8%),
OP= 40 (28.2%)
122 completed the 1
YR FU.
BPI Group:
AA=28±8.7,
OA=25.4±8.2,
DOI=42.1±34.4,
F=5(25%),
AF=6(30%)
BPII Group:
AA=29.2±8.6,

Statistical
analysis using
SPSS 13.0

MDQ
DV1- Initial Ψ
DX
DV2- Final Ψ
DX/ A
DV3-MDQ
score/ DX A

Mann-Whitney
U and Chisquare test.
Cronbach alpha
used to access
internal
consistency.
ROC curve
plotted for
screening
performance.

MDQ showed
good accuracy
with BP, even
with cutoff of 4.
SN=0.72,
SP=0.73
Cronbach
coefficient for
the MDQ=
0.735

MDQ is more
sensitive in detecting
BPI versus BPII.
MDQ (even without
section 2 and 3) is a
valid tool for BPII
and previously
unrecognized BPI.

BP
AUC=0.803,
p<0.001,

BPI
Optimal cutoff
AUC=0.826,
was determined
Ψ –Psychiatric, A-Accuracy, AA- Average Age, ADJ-Adjustment Disorder, AF-Atypical Features, AOI- Age of Onset of Illness, AUC- Area Under the Curve, AX-Anxiety Disorder, BP- Bipolar
Disorder, BPI- Bipolar I Disorder, BPII- Bipolar II Disorder, BPNOS- Bipolar Disorder Not Otherwise Specified, - BSDS- Bipolar Spectrum Diagnostic Scale, CD- College Degree 2 year, CIConfidence Interval, CIDI-Composite International Diagnostic Interview, CL-Common Law, CP-Clinical Practice, DC-Discharge, DD NOS-Depressive Disorder Not Otherwise Specified, DEPDepression, DEM-Dementia, DO-Disorder, DOI- Duration of Illness in Months, DOR-Diagnostic Odds Ratios, DV1-Dependent Variable 1, DV2-Dependent Variable 2, DX- Diagnosis, DYSDysthymia, ED-Education, EVAL-Evaluation, F-Female, FHX-Family History, FU-Follow Up, HAM- Hamilton Depression Rating Scale, HCL-32- Hypomania Checklist-32, HS- High School,
HSROC-Hierarchical Summary Receiver Operating Characteristics, IC-Informed Consent, IP- Inpatient, IV1-Independent Variable 1,IV2- Independent Variable 2, LOE-Level of Evidence, LOEDLevel of Education, M- Male, MA-Married, MDD- Major Depressive Disorder, MDE-Major Depressive Episode, MDQ- Mood Disorder Questionnaire, MDQ-C- Mood Disorder Questionnaire Chinese
Version, MED-Medical Disorder, MH-Mental Health, MINI- Mini Neuropsychological Interview, MR- Mental Retardation, MS-Marital Status, N-Number, NESDA-Netherlands Study of Depression
and Anxiety, NOHRD- Netherlands Organization for Health Research and Development, NPV-Negative Predictive Value, OA-Onset Age, OCD-Obsessive Compulsive Disorder, ORG-Organic
Disorder, OP-Outpatient, PG-Pregnant, PP- Postpartum,,PPV-Positive Predictive Value, PSYCH- Psychotic Disorder, PTS-Patients, Q-Questionnaire, QOL-Quality of Life, QUADAS 2- Quality
Assessment of Diagnostic Accuracy Studies-2, ROC- Receiver Operating Characteristic, S- Single, SCID- Standard Clinical Interview for DSM Disorders,SD-Standard Deviation, SEIFA- SocioEconomic Index for Areas, SN- Sensitivity, SP- Specificity, SSPS- Statistical Package for the Social Sciences, SUB- Substance Disorder, TR-Treatment Resistant,UN- University Degree, UPD-Unipolar
Depression, YR-Year

APPLICATION OF THE MOOD DISORDER QUESTIONNAIRE
Citation

Conceptual
Framework

Design/Method

Sample/Setting

27
Major
Variables &
Definitions

Measurement

Data Analysis

Findings

Decision for Use
in Practice/
Application to
Practice

Bias: Authors report no
competing interests

consent.
Exclusion Criteria:
PTS who declined or
with a Ψ or physical
DO that prevented
them from being
interviewed or
undermined their
ability to provide
accurate information
and those refused to
provide IC.

LOE:III

Poon, Y. (2011). The use
of the mood disorder
questionnaires, hypomanic
checklist-32 and clinical
predictors for screening
previously unrecognized
bipolar disorder in a
general psychiatry setting.
Population: General
psychiatric setting in Hong
Kong
Funding: Not reported

None Stated.
Donabedian
Model
inferred.

Design: Randomized
controlled trial.
Purpose: examine
clinical predictors of
BP an determine the
best approach for
screening previously
unrecognized BP in
the general population.
Inclusion Criteria:
ethnic Chinese, aged
18-64, no previous DX
of BP, PSYCH, MR,
Dementia and AG.

OA=25.7±9.3,
DOI=51.8±61.3,
F=27(54%), AF=8
(16%)

by maxing the
Youden’s
index(=SN+SP1)

UPD Group:
AA=33.6±10.5,
OA=31.2±10.9,
DOI=30.8±33.0,
F=29(55.8%),
AF=6(11.5%)

IV1-BP FHX

MDQ

AA=50,Range 18-64

IV2-AOI <21

HCL-32

F=66.8%m M=23.2%

DV1- Ψ DX A

SCID

2/3 MA

DV2- MDQ
score/ DX A

AA illness onset= 37.5
(range 10-62)
FHX- 20%
MDE/MDD and 7.9%

BPII
AUC=0.794,
p<0.001
ROC analysis
illustrated
improved cutoff
at 4 and 5,
illustrating far
improved SP
and SN

N=340

65% =secondary ED
status or +

p<0.001

SPSS version
15.0.
Multivariable
logistic
regression.
Categorical
variables
analyzed by chisquare or
Fisher’s exact
text.
P<0.05

MDQ SN=0.65,
SP=0.77,PPV=
0.24, NPR=0.95
BP FHX
SN=0.23,
SP=0.93,
PPV=0.28,
NPV=0.91

MDQ is a valid and
reliable screening
instrument for
previously
unrecognized BP.
Optimal cutoff was
4+ symptoms.

MDQ and BP
FHX SN=0.71,
SP=0.72,
PPV=0.22,
NPV=0.96

Ψ –Psychiatric, A-Accuracy, AA- Average Age, ADJ-Adjustment Disorder, AF-Atypical Features, AOI- Age of Onset of Illness, AUC- Area Under the Curve, AX-Anxiety Disorder, BP- Bipolar
Disorder, BPI- Bipolar I Disorder, BPII- Bipolar II Disorder, BPNOS- Bipolar Disorder Not Otherwise Specified, - BSDS- Bipolar Spectrum Diagnostic Scale, CD- College Degree 2 year, CIConfidence Interval, CIDI-Composite International Diagnostic Interview, CL-Common Law, CP-Clinical Practice, DC-Discharge, DD NOS-Depressive Disorder Not Otherwise Specified, DEPDepression, DEM-Dementia, DO-Disorder, DOI- Duration of Illness in Months, DOR-Diagnostic Odds Ratios, DV1-Dependent Variable 1, DV2-Dependent Variable 2, DX- Diagnosis, DYSDysthymia, ED-Education, EVAL-Evaluation, F-Female, FHX-Family History, FU-Follow Up, HAM- Hamilton Depression Rating Scale, HCL-32- Hypomania Checklist-32, HS- High School,
HSROC-Hierarchical Summary Receiver Operating Characteristics, IC-Informed Consent, IP- Inpatient, IV1-Independent Variable 1,IV2- Independent Variable 2, LOE-Level of Evidence, LOEDLevel of Education, M- Male, MA-Married, MDD- Major Depressive Disorder, MDE-Major Depressive Episode, MDQ- Mood Disorder Questionnaire, MDQ-C- Mood Disorder Questionnaire Chinese
Version, MED-Medical Disorder, MH-Mental Health, MINI- Mini Neuropsychological Interview, MR- Mental Retardation, MS-Marital Status, N-Number, NESDA-Netherlands Study of Depression
and Anxiety, NOHRD- Netherlands Organization for Health Research and Development, NPV-Negative Predictive Value, OA-Onset Age, OCD-Obsessive Compulsive Disorder, ORG-Organic
Disorder, OP-Outpatient, PG-Pregnant, PP- Postpartum,,PPV-Positive Predictive Value, PSYCH- Psychotic Disorder, PTS-Patients, Q-Questionnaire, QOL-Quality of Life, QUADAS 2- Quality
Assessment of Diagnostic Accuracy Studies-2, ROC- Receiver Operating Characteristic, S- Single, SCID- Standard Clinical Interview for DSM Disorders,SD-Standard Deviation, SEIFA- SocioEconomic Index for Areas, SN- Sensitivity, SP- Specificity, SSPS- Statistical Package for the Social Sciences, SUB- Substance Disorder, TR-Treatment Resistant,UN- University Degree, UPD-Unipolar
Depression, YR-Year

APPLICATION OF THE MOOD DISORDER QUESTIONNAIRE
Citation

Conceptual
Framework

Design/Method

Sample/Setting

28
Major
Variables &
Definitions

Measurement

Data Analysis

Findings

Decision for Use
in Practice/
Application to
Practice

Bias: Not reported
LOE:II

Lin, C. (2011). Reliability
and validity of the Chinese
version of the mood
disorder questionnaire.
Population: PTS receiving
OP services in a medical
center in Taiwan.
Funding: Not Reported
Bias:Not reported
LOE:II

None Stated.
Donabedian
Model
inferred.

Exclusion
Criteria:Those that did
not meet inclusion
criteria.

BP

Design: Intervention
study. Measures
included Personal
information
questionnaire, MINI,
and MDQ-C

N=170

IV1-Ψ MINI

AA= 38.94 (±13.77).

IV2-MDQ-C

F=97 (57.06%)

DV1- Ψ DX A

M=73 (42.94%)
Purpose: to extend
previous studies by
examining the
psychometric
properties of the
MDQ, helping
professionals to
identify BP in CP.

Education:
HS-88.22%
Diagnosis based on
MINI:
BP I-67(39.41%)

DV2- MDQ
score/ DX A

Personal
information
Questionnaire
(gender, FHX,
occupation, age).
MINI
MDQ

Internal
consistency of
the MDQ
determined with
Cronbach’s
alpha.

Internal
consistency of
0.75

Cronbach’s
alpha to
determine
reliability.

Internal
consistency
reliability= .82

Bartlett’s test of
sphericity and
Kaiser-MeyerOlkin measure
of sampling
adequacy

Context
Validity index
80%
Youden index
Cutoff 6:
SN=0.85,
SP=0.87
Cutoff 7:
SN=0.75,
SP=0.93

Psychometric
property analysis
illustrated optimal
cutoff of 6, noting
that 85% of patients
with BP will screen
positive and 87%
without would be
ruled out.
Cross-cultural
consistency with
good reliability,
validity, SN and SP.

Able to discriminate
Inclusion Criteria:
BP from the general
BPII-25 (14.71%)
(a)adult PTS, (b) DG
population.
Cutoff 8:
BPNOS-3 (1.76%)
with a mood disorder
SN=0.53,
Concludes improved
according to the DSM,
MDD- 75 (44.12%)
SP=0.99
ability for nursing
including Depressive
staff to screen,
DO and BP, (c) able to
Optimal cutoff
identifying mood
follow instructions for
Ψ –Psychiatric, A-Accuracy, AA- Average Age, ADJ-Adjustment Disorder, AF-Atypical Features, AOI- Age of Onset of Illness, AUC- Area Under the Curve, AX-Anxiety Disorder, BP- Bipolar
Disorder, BPI- Bipolar I Disorder, BPII- Bipolar II Disorder, BPNOS- Bipolar Disorder Not Otherwise Specified, - BSDS- Bipolar Spectrum Diagnostic Scale, CD- College Degree 2 year, CIConfidence Interval, CIDI-Composite International Diagnostic Interview, CL-Common Law, CP-Clinical Practice, DC-Discharge, DD NOS-Depressive Disorder Not Otherwise Specified, DEPDepression, DEM-Dementia, DO-Disorder, DOI- Duration of Illness in Months, DOR-Diagnostic Odds Ratios, DV1-Dependent Variable 1, DV2-Dependent Variable 2, DX- Diagnosis, DYSDysthymia, ED-Education, EVAL-Evaluation, F-Female, FHX-Family History, FU-Follow Up, HAM- Hamilton Depression Rating Scale, HCL-32- Hypomania Checklist-32, HS- High School,
HSROC-Hierarchical Summary Receiver Operating Characteristics, IC-Informed Consent, IP- Inpatient, IV1-Independent Variable 1,IV2- Independent Variable 2, LOE-Level of Evidence, LOEDLevel of Education, M- Male, MA-Married, MDD- Major Depressive Disorder, MDE-Major Depressive Episode, MDQ- Mood Disorder Questionnaire, MDQ-C- Mood Disorder Questionnaire Chinese
Version, MED-Medical Disorder, MH-Mental Health, MINI- Mini Neuropsychological Interview, MR- Mental Retardation, MS-Marital Status, N-Number, NESDA-Netherlands Study of Depression
and Anxiety, NOHRD- Netherlands Organization for Health Research and Development, NPV-Negative Predictive Value, OA-Onset Age, OCD-Obsessive Compulsive Disorder, ORG-Organic
Disorder, OP-Outpatient, PG-Pregnant, PP- Postpartum,,PPV-Positive Predictive Value, PSYCH- Psychotic Disorder, PTS-Patients, Q-Questionnaire, QOL-Quality of Life, QUADAS 2- Quality
Assessment of Diagnostic Accuracy Studies-2, ROC- Receiver Operating Characteristic, S- Single, SCID- Standard Clinical Interview for DSM Disorders,SD-Standard Deviation, SEIFA- SocioEconomic Index for Areas, SN- Sensitivity, SP- Specificity, SSPS- Statistical Package for the Social Sciences, SUB- Substance Disorder, TR-Treatment Resistant,UN- University Degree, UPD-Unipolar
Depression, YR-Year

APPLICATION OF THE MOOD DISORDER QUESTIONNAIRE
Citation

Conceptual
Framework

Design/Method

Sample/Setting

29
Major
Variables &
Definitions

Measurement

Data Analysis

Findings

Decision for Use
in Practice/
Application to
Practice

answering the Q.

6 with
AUC=0.86

disorders in clinical
practice and
potentially reduce the
rate of suicide and
improved QOL.

T-tests for
continuous data
and chi-square
tests for
categorical data

Cutoff 6:
SN=0.741,
SP=0.844,
PPV=.923,NPV
=.563

Increased use in
primary care and Ψ
clinics
recommended.

Two-tailed pvalue<0.05

Cutoff 7:
SN=0.605,
SP=0.873

Exclusion Criteria:
Those that did not
meet inclusion criteria
or complete the
screening process.
Lee, D. (2013). Usefulness
of the combined
application of the mood
disorder questionnaire and
the bipolar spectrum
diagnostic scale in
screening for bipolar
disorder.
Population: Korea,
psychiatric IP and OP
settings
Funding: None reported
Bias: No bias reported.
LOE:II

None Stated.
Donabedian
Model
inferred.

Design: Controlled
trial (intervention
study). MDQ and
BSDS, with 1 year FU.

Setting: Gyeongsang
National University
Hospital between
3/2009 and 3/2011.

Purpose: examine
whether combined
application of the
MDQ and BSDS is
more effective than
either tool in screening
for BP.

Sample of IPS and
OPS experiencing a
current MDE.

IV1- MDQ

MDQ

IV2-BSDS

BSDS

IV3—Ψ EVAL

Inclusion Criteria: Age
18-65, current MDE
Exclusion Criteria:
Patients with MR,
DEM, PSYCH, severe
agitation, severe MED
& ORG.

DV1- Ψ DX A

N=131

DV2- MDQ
score/ DX A

Group 1: BP (N=81,
AA=35.5 ±11.9 years)

DV3- BSDS
score/ DX A

Group 2:MDD (N=32,
AA=41.4± 10.6 years)
No significant
differences found in
terms of sex, LOE, or

SPSS version
12.0

Cutoff of 6=best SN
and SP
MDQ more effective
for BPI than BPII

DG Specific:
BPI SN=1.00,
SP0.844

Combination of
MDQ and BSDS is
more effective than
either alone.

BPII SN=.643,
SP=.465
BPNOS
SN=.739,

Ψ –Psychiatric, A-Accuracy, AA- Average Age, ADJ-Adjustment Disorder, AF-Atypical Features, AOI- Age of Onset of Illness, AUC- Area Under the Curve, AX-Anxiety Disorder, BP- Bipolar
Disorder, BPI- Bipolar I Disorder, BPII- Bipolar II Disorder, BPNOS- Bipolar Disorder Not Otherwise Specified, - BSDS- Bipolar Spectrum Diagnostic Scale, CD- College Degree 2 year, CIConfidence Interval, CIDI-Composite International Diagnostic Interview, CL-Common Law, CP-Clinical Practice, DC-Discharge, DD NOS-Depressive Disorder Not Otherwise Specified, DEPDepression, DEM-Dementia, DO-Disorder, DOI- Duration of Illness in Months, DOR-Diagnostic Odds Ratios, DV1-Dependent Variable 1, DV2-Dependent Variable 2, DX- Diagnosis, DYSDysthymia, ED-Education, EVAL-Evaluation, F-Female, FHX-Family History, FU-Follow Up, HAM- Hamilton Depression Rating Scale, HCL-32- Hypomania Checklist-32, HS- High School,
HSROC-Hierarchical Summary Receiver Operating Characteristics, IC-Informed Consent, IP- Inpatient, IV1-Independent Variable 1,IV2- Independent Variable 2, LOE-Level of Evidence, LOEDLevel of Education, M- Male, MA-Married, MDD- Major Depressive Disorder, MDE-Major Depressive Episode, MDQ- Mood Disorder Questionnaire, MDQ-C- Mood Disorder Questionnaire Chinese
Version, MED-Medical Disorder, MH-Mental Health, MINI- Mini Neuropsychological Interview, MR- Mental Retardation, MS-Marital Status, N-Number, NESDA-Netherlands Study of Depression
and Anxiety, NOHRD- Netherlands Organization for Health Research and Development, NPV-Negative Predictive Value, OA-Onset Age, OCD-Obsessive Compulsive Disorder, ORG-Organic
Disorder, OP-Outpatient, PG-Pregnant, PP- Postpartum,,PPV-Positive Predictive Value, PSYCH- Psychotic Disorder, PTS-Patients, Q-Questionnaire, QOL-Quality of Life, QUADAS 2- Quality
Assessment of Diagnostic Accuracy Studies-2, ROC- Receiver Operating Characteristic, S- Single, SCID- Standard Clinical Interview for DSM Disorders,SD-Standard Deviation, SEIFA- SocioEconomic Index for Areas, SN- Sensitivity, SP- Specificity, SSPS- Statistical Package for the Social Sciences, SUB- Substance Disorder, TR-Treatment Resistant,UN- University Degree, UPD-Unipolar
Depression, YR-Year

APPLICATION OF THE MOOD DISORDER QUESTIONNAIRE
Citation

Conceptual
Framework

Design/Method

Sample/Setting

30
Major
Variables &
Definitions

Measurement

Data Analysis

Findings

Decision for Use
in Practice/
Application to
Practice

MS.
Rybakowski, J. K. (2012).
Use of the hypomania
checklist-32 and the mood
disorder questionnaire for
detecting bipolarity in
1,051 patients with major
depressive disorder.

None Stated.
Donabedian
Model
inferred.

Design: All Poland
Multi-Center
Intervention study

Sample: 150 OP
clinics, representing 16
regions of Poland.

IV1- MDQ

Purpose: to use the
HCL-32 and the MDQ
for detecting bipolarity
in depressed patients

N=1,051

IV3—Ψ EVAL

Bias: Authors declare no
conflict of interest.
LOE:II

Ψ EVAL by trained
psychiatrist

IV2-HCL-32

STATA
Statistical
Software

MDQ
HCL-32
F=752

Inclusion Criteria:
diagnosis of MDE or
MDD (current or past)
and 18 years or older.

Exclusion Criteria:
diagnosis of
dysthymia, BPI, BPII,
HAM Score over 17,
treatment with moodstabilizing drugs, MR,
SUB, or severe MED.

IV4-HAM
HAM

M=299

Population: Poland
Funding: Supported by a
grant provided by SanofiAventis Poland

SP=.467

DV1- MDQ
Score/ DX A

Age=18-77
HCL-32 score=10.3±
8.0,37.5% reached
cutoff for BP
MDQ Score 3.6 ±3.2,
20% reached cutoff for
BP

DV2- HCL-32
Score/ DX A

Chi2 test,
Kruskal-Wallis.
Two-sided with
significance at
5%.

Mean MDQ
score=3.6±3.2
(mean± SD).
Mean HCL-32
10.3±8.0
(mean± SD)
Spearman
correlation
coefficient=0.7
7 (p<0.001)
F:0.75, M:0.81

Large group of
depressed patients
evaluated with
scales. More than 1/3
met BP criteria.
Corroborates an
association between
refractoriness of
depression to
treatment with AD
drugs and indices of
bipolarity found by
other researchers.

PTS TR with
AD drugs in
MDQ+ and
MDQ- =26.4%
and 12.4%

Kung, S. (2015). Screening None Stated.
Design: Controlled
N= 860 (1330 -284 for
IV1-Ψ EVAL
SCID
JMP 10.0
Cutoff 6:
Clinical utilization of
for bipolar disorders:
Donabedian
trial-intervention
incomplete MDQ -135
SN=0.949,
the MDQ as a
IV2-MDQ
MDQ
Clinical utilization of the
Model
study.
for recurrent
SP=0.561
screening instrument
mood disorders
inferred.
admission-51 for other
on the IP unit.
Purpose: Evaluate the
Cutoff 7:
questionnaire on an
Ψ –Psychiatric, A-Accuracy, AA- Average Age, ADJ-Adjustment Disorder, AF-Atypical Features, AOI- Age of Onset of Illness, AUC- Area Under the Curve, AX-Anxiety Disorder, BP- Bipolar
Disorder, BPI- Bipolar I Disorder, BPII- Bipolar II Disorder, BPNOS- Bipolar Disorder Not Otherwise Specified, - BSDS- Bipolar Spectrum Diagnostic Scale, CD- College Degree 2 year, CIConfidence Interval, CIDI-Composite International Diagnostic Interview, CL-Common Law, CP-Clinical Practice, DC-Discharge, DD NOS-Depressive Disorder Not Otherwise Specified, DEPDepression, DEM-Dementia, DO-Disorder, DOI- Duration of Illness in Months, DOR-Diagnostic Odds Ratios, DV1-Dependent Variable 1, DV2-Dependent Variable 2, DX- Diagnosis, DYSDysthymia, ED-Education, EVAL-Evaluation, F-Female, FHX-Family History, FU-Follow Up, HAM- Hamilton Depression Rating Scale, HCL-32- Hypomania Checklist-32, HS- High School,
HSROC-Hierarchical Summary Receiver Operating Characteristics, IC-Informed Consent, IP- Inpatient, IV1-Independent Variable 1,IV2- Independent Variable 2, LOE-Level of Evidence, LOEDLevel of Education, M- Male, MA-Married, MDD- Major Depressive Disorder, MDE-Major Depressive Episode, MDQ- Mood Disorder Questionnaire, MDQ-C- Mood Disorder Questionnaire Chinese
Version, MED-Medical Disorder, MH-Mental Health, MINI- Mini Neuropsychological Interview, MR- Mental Retardation, MS-Marital Status, N-Number, NESDA-Netherlands Study of Depression
and Anxiety, NOHRD- Netherlands Organization for Health Research and Development, NPV-Negative Predictive Value, OA-Onset Age, OCD-Obsessive Compulsive Disorder, ORG-Organic
Disorder, OP-Outpatient, PG-Pregnant, PP- Postpartum,,PPV-Positive Predictive Value, PSYCH- Psychotic Disorder, PTS-Patients, Q-Questionnaire, QOL-Quality of Life, QUADAS 2- Quality
Assessment of Diagnostic Accuracy Studies-2, ROC- Receiver Operating Characteristic, S- Single, SCID- Standard Clinical Interview for DSM Disorders,SD-Standard Deviation, SEIFA- SocioEconomic Index for Areas, SN- Sensitivity, SP- Specificity, SSPS- Statistical Package for the Social Sciences, SUB- Substance Disorder, TR-Treatment Resistant,UN- University Degree, UPD-Unipolar
Depression, YR-Year

APPLICATION OF THE MOOD DISORDER QUESTIONNAIRE
Citation

Conceptual
Framework

Design/Method

Sample/Setting

31
Major
Variables &
Definitions

Measurement

Data Analysis

Findings

Decision for Use
in Practice/
Application to
Practice

inpatient mood disorders
unit.

MDQ in an IP setting
for clinical validation.

Population: Inpatient mood
disorder clinic Mayo,
Rochester, MN, USA

Inclusion Criteria: PTS
with a DC DG of
UPD, MDD, DD NOS,
DYS, or BP were
included.
Exclusion Criteria:
Non-primary mood
disorder were
excluded.

Funding: Not Reported
Bias: authors declare that
they have no competing
interests.

diagnosis)

DV1- Ψ DX

464 (54%)=
Concurrence of
symptoms and at least
moderate severity

DV2- MDQ
score/ DX A

SN=0.924,
SP=0.639
Cutoff 8:
SN=0.856,
SP=0.714,

234 + screens with
cutoff of 7
200 + screens with
cutoff score of 8.

Outcomes suggest
optimal OP MDQ
cutoff of 7 and IP
cutoff of 8.
Purpose of a
screening instrument
is to alert and does
not obviate the need
for a thorough
history and
confirmatory steps of
a diagnosis.

LOE:III
Rucci, P. (2013). A review
of self-report and
interview-based
instruments to assess
mania and hypomania
symptoms.
Population: Adult MH
Italy
Funding: Not reported.
Bias: Not reported

None Stated.

Design/Method:
Systematic search
strategy devised and
queried on Medline
from 1973-2012.
Purpose: overview of
the self-report and
interview-based
instruments to assess
mania/hypomania
symptoms and related
features. Focus on
psychometric

Sample: 43 Studies
describing 31
instruments, 17 selfreport and 14
interview-based.

IV1-Ψ
instrument
DV1- internal
consistency
DV2- validity
DV3-factor
analysis
DV4-inter-rater
reliability

Self-report
questionnaires
(MDQ,HCL32,BSDS,Mood
Spectrum).

Factor analysis
and latent
structure
analysis (Rasch
analysis).

Interview-based
instruments
(YMRS, BRMAS)

Search terms:
mania,
hypomania,
bipolar
spectrum, mood
spectrum,
instrument,
rating scale,
questionnaire,

MDQ SN=0.61,
SP=0.87,
PPV=0.58,
NPV=0.88
Cutoff of 6
provided the
best balance of
SN=0.76 and
SP=0.86

Increasing the use of
self-report
instruments to screen
BP in high-risk PTS
presenting with
depression may
contribute to
increasing the use of
routine standardized
assessment.
Self-rating scales
have an advantage of
being able to assess
the PTS internal

Ψ –Psychiatric, A-Accuracy, AA- Average Age, ADJ-Adjustment Disorder, AF-Atypical Features, AOI- Age of Onset of Illness, AUC- Area Under the Curve, AX-Anxiety Disorder, BP- Bipolar
Disorder, BPI- Bipolar I Disorder, BPII- Bipolar II Disorder, BPNOS- Bipolar Disorder Not Otherwise Specified, - BSDS- Bipolar Spectrum Diagnostic Scale, CD- College Degree 2 year, CIConfidence Interval, CIDI-Composite International Diagnostic Interview, CL-Common Law, CP-Clinical Practice, DC-Discharge, DD NOS-Depressive Disorder Not Otherwise Specified, DEPDepression, DEM-Dementia, DO-Disorder, DOI- Duration of Illness in Months, DOR-Diagnostic Odds Ratios, DV1-Dependent Variable 1, DV2-Dependent Variable 2, DX- Diagnosis, DYSDysthymia, ED-Education, EVAL-Evaluation, F-Female, FHX-Family History, FU-Follow Up, HAM- Hamilton Depression Rating Scale, HCL-32- Hypomania Checklist-32, HS- High School,
HSROC-Hierarchical Summary Receiver Operating Characteristics, IC-Informed Consent, IP- Inpatient, IV1-Independent Variable 1,IV2- Independent Variable 2, LOE-Level of Evidence, LOEDLevel of Education, M- Male, MA-Married, MDD- Major Depressive Disorder, MDE-Major Depressive Episode, MDQ- Mood Disorder Questionnaire, MDQ-C- Mood Disorder Questionnaire Chinese
Version, MED-Medical Disorder, MH-Mental Health, MINI- Mini Neuropsychological Interview, MR- Mental Retardation, MS-Marital Status, N-Number, NESDA-Netherlands Study of Depression
and Anxiety, NOHRD- Netherlands Organization for Health Research and Development, NPV-Negative Predictive Value, OA-Onset Age, OCD-Obsessive Compulsive Disorder, ORG-Organic
Disorder, OP-Outpatient, PG-Pregnant, PP- Postpartum,,PPV-Positive Predictive Value, PSYCH- Psychotic Disorder, PTS-Patients, Q-Questionnaire, QOL-Quality of Life, QUADAS 2- Quality
Assessment of Diagnostic Accuracy Studies-2, ROC- Receiver Operating Characteristic, S- Single, SCID- Standard Clinical Interview for DSM Disorders,SD-Standard Deviation, SEIFA- SocioEconomic Index for Areas, SN- Sensitivity, SP- Specificity, SSPS- Statistical Package for the Social Sciences, SUB- Substance Disorder, TR-Treatment Resistant,UN- University Degree, UPD-Unipolar
Depression, YR-Year

APPLICATION OF THE MOOD DISORDER QUESTIONNAIRE
Citation

Conceptual
Framework

Design/Method

Sample/Setting

32
Major
Variables &
Definitions

Measurement

Data Analysis

Findings

Decision for Use
in Practice/
Application to
Practice

LOE:I

properties, pros/cons.

interview and
validity,
reliability,
psychometric
properties

Inclusion Criteria:
published in a peerreviewed book or
journal in English.

states and avoid
clinician
misinterpretation.

Exclusion Criteria: Did
not meet inclusion
criteria.
Leao, I. (2012). Cross
validation with the mood
disorder questionnaire
(MDQ) of an instrument
for the detection of
hypomania in brazil:the 32
item hypomania symptom
check-list, first revision
(Hcl-32-R1). Population:
Psychiatric patient in
Brazil
Funding: None.
Bias: Leao has no conflict
of interest. Del Porto is a
member of the
international board of
Lundbeck and a speaker

None Stated.
Donabedian
Model
inferred

Design: RCT. Random
selection.

Setting: Psychiatric
Outpatient.

Purpose: Evaluation of
scales to improve and
simplify identification
of BP

N=200
F=80%

IV1- MDQ

HCL-32

IV2-HCL-32-R1

MDQ

IV3—Ψ
EVAL(SCIDCV)

SCID

M=20%
Inclusion Criteria:
adults, written consent.
Exclusion Criteria:
Those with
schizophrenia and
severe organic
diseases.

AA=44 (16-73)

DV1- MDQ
Score/ DX A

BP spectrum=59.5%,
cyclothymia=39%

DV2- HCL-32R1 Score/ DX A
DV3-Ψ DG

Internal
consistency
evaluation using
Cronbach’s
alpha.
Mann Whitney
test and t-test.
Varimax
rotation was
used to identify
the factor
structure of the
MDQ scree test.

MDQ SN=0.68,
SP=0.63,
AUC=0.723
MDQ
reproducibility
is 0.69

Questionnaires
represent a potential
improvement in the
clinicians’ ability to
detect and correctly
treat bipolar disorder.

MDQ 1st
administration
=0.761
Cronbach’s
alpha
2nd
administration=
0.782

Ψ –Psychiatric, A-Accuracy, AA- Average Age, ADJ-Adjustment Disorder, AF-Atypical Features, AOI- Age of Onset of Illness, AUC- Area Under the Curve, AX-Anxiety Disorder, BP- Bipolar
Disorder, BPI- Bipolar I Disorder, BPII- Bipolar II Disorder, BPNOS- Bipolar Disorder Not Otherwise Specified, - BSDS- Bipolar Spectrum Diagnostic Scale, CD- College Degree 2 year, CIConfidence Interval, CIDI-Composite International Diagnostic Interview, CL-Common Law, CP-Clinical Practice, DC-Discharge, DD NOS-Depressive Disorder Not Otherwise Specified, DEPDepression, DEM-Dementia, DO-Disorder, DOI- Duration of Illness in Months, DOR-Diagnostic Odds Ratios, DV1-Dependent Variable 1, DV2-Dependent Variable 2, DX- Diagnosis, DYSDysthymia, ED-Education, EVAL-Evaluation, F-Female, FHX-Family History, FU-Follow Up, HAM- Hamilton Depression Rating Scale, HCL-32- Hypomania Checklist-32, HS- High School,
HSROC-Hierarchical Summary Receiver Operating Characteristics, IC-Informed Consent, IP- Inpatient, IV1-Independent Variable 1,IV2- Independent Variable 2, LOE-Level of Evidence, LOEDLevel of Education, M- Male, MA-Married, MDD- Major Depressive Disorder, MDE-Major Depressive Episode, MDQ- Mood Disorder Questionnaire, MDQ-C- Mood Disorder Questionnaire Chinese
Version, MED-Medical Disorder, MH-Mental Health, MINI- Mini Neuropsychological Interview, MR- Mental Retardation, MS-Marital Status, N-Number, NESDA-Netherlands Study of Depression
and Anxiety, NOHRD- Netherlands Organization for Health Research and Development, NPV-Negative Predictive Value, OA-Onset Age, OCD-Obsessive Compulsive Disorder, ORG-Organic
Disorder, OP-Outpatient, PG-Pregnant, PP- Postpartum,,PPV-Positive Predictive Value, PSYCH- Psychotic Disorder, PTS-Patients, Q-Questionnaire, QOL-Quality of Life, QUADAS 2- Quality
Assessment of Diagnostic Accuracy Studies-2, ROC- Receiver Operating Characteristic, S- Single, SCID- Standard Clinical Interview for DSM Disorders,SD-Standard Deviation, SEIFA- SocioEconomic Index for Areas, SN- Sensitivity, SP- Specificity, SSPS- Statistical Package for the Social Sciences, SUB- Substance Disorder, TR-Treatment Resistant,UN- University Degree, UPD-Unipolar
Depression, YR-Year

APPLICATION OF THE MOOD DISORDER QUESTIONNAIRE
Citation

Conceptual
Framework

Design/Method

Sample/Setting

33
Major
Variables &
Definitions

Measurement

Data Analysis

Findings

Decision for Use
in Practice/
Application to
Practice

for pharmaceuticals
LOE:II
Dodd, S. (2009).
Reliability of the mood
disorder questionnaire:
comparison with the
structured clinical
interview for the DSM-IVTR in a population sample.
Population: Women
included in a large
epidemiological study in
Australia.
Funding:Not reported
Bias:None reported
LOE:II

None Stated.

Design: RCT.
Intervention study.

Initial Sample:
N=1494 women

Purpose: Investigate
reliability of the MDQ

AA=54 years (21-94)

IV1-Ψ EVAL/

Status assessed with
the SCID-I

(SCID-I)

Inclusion Criteria: age
21-94, women, written
consent

Exclusion Criteria:
lack of participation in
the clinical interview
or MDQ scale,
inability to provide
consent, death,
inability to be
contacted.

MDQ
IV2-MDQ

FU Sample (10 yrs):
N=1066
AA=51(34-66)
Education: primary 41
(3.8%), part secondary
444 (41.7%),
secondary 271 (25.4%)
Psychotropic use: 150
(14.1%)

SEIFA index score
DV1- Ψ DX
DV2- MDQ
score/ DX A

Minitab version
15. Manual 2x2
table of
association.

MDQ SN=0.25,
SP=0.99,
PPV=0.28,
NPV=0.98,
Kappa=0.25

Results for the MDQ
SN and SP vary
greatly depending on
PT population.
Reliable screening
tools to detect BP in
clinical and
community
populations are of
overt value and the
development of
novel tools and
refinement of
existing instruments
is warranted.

Smoking: 150 (14.1%)

Ψ –Psychiatric, A-Accuracy, AA- Average Age, ADJ-Adjustment Disorder, AF-Atypical Features, AOI- Age of Onset of Illness, AUC- Area Under the Curve, AX-Anxiety Disorder, BP- Bipolar
Disorder, BPI- Bipolar I Disorder, BPII- Bipolar II Disorder, BPNOS- Bipolar Disorder Not Otherwise Specified, - BSDS- Bipolar Spectrum Diagnostic Scale, CD- College Degree 2 year, CIConfidence Interval, CIDI-Composite International Diagnostic Interview, CL-Common Law, CP-Clinical Practice, DC-Discharge, DD NOS-Depressive Disorder Not Otherwise Specified, DEPDepression, DEM-Dementia, DO-Disorder, DOI- Duration of Illness in Months, DOR-Diagnostic Odds Ratios, DV1-Dependent Variable 1, DV2-Dependent Variable 2, DX- Diagnosis, DYSDysthymia, ED-Education, EVAL-Evaluation, F-Female, FHX-Family History, FU-Follow Up, HAM- Hamilton Depression Rating Scale, HCL-32- Hypomania Checklist-32, HS- High School,
HSROC-Hierarchical Summary Receiver Operating Characteristics, IC-Informed Consent, IP- Inpatient, IV1-Independent Variable 1,IV2- Independent Variable 2, LOE-Level of Evidence, LOEDLevel of Education, M- Male, MA-Married, MDD- Major Depressive Disorder, MDE-Major Depressive Episode, MDQ- Mood Disorder Questionnaire, MDQ-C- Mood Disorder Questionnaire Chinese
Version, MED-Medical Disorder, MH-Mental Health, MINI- Mini Neuropsychological Interview, MR- Mental Retardation, MS-Marital Status, N-Number, NESDA-Netherlands Study of Depression
and Anxiety, NOHRD- Netherlands Organization for Health Research and Development, NPV-Negative Predictive Value, OA-Onset Age, OCD-Obsessive Compulsive Disorder, ORG-Organic
Disorder, OP-Outpatient, PG-Pregnant, PP- Postpartum,,PPV-Positive Predictive Value, PSYCH- Psychotic Disorder, PTS-Patients, Q-Questionnaire, QOL-Quality of Life, QUADAS 2- Quality
Assessment of Diagnostic Accuracy Studies-2, ROC- Receiver Operating Characteristic, S- Single, SCID- Standard Clinical Interview for DSM Disorders,SD-Standard Deviation, SEIFA- SocioEconomic Index for Areas, SN- Sensitivity, SP- Specificity, SSPS- Statistical Package for the Social Sciences, SUB- Substance Disorder, TR-Treatment Resistant,UN- University Degree, UPD-Unipolar
Depression, YR-Year

APPLICATION OF THE MOOD DISORDER QUESTIONNAIRE

34

Appendix B
Synthesis Table: MDQ Screening for Bipolar Disorder

Wang

Author

Frey

Boschloo

Gan

Poon

Lin

Lee

Rybakowski

Kung

Ricci

Leao

Dodd

Study Characteristics
Year

2015

2012

2013

2012

2011

2011

2013

2012

2015

2013

2012

2009

LOE

I

III

II

III

II

II

II

II

III

I

II

II

Country

Worldwide

Cana
da

Netherlands

China

China

Taiwan

Korea

Poland

USA

Italy

Brazil

Australia

Setting

IP/OP

OP

OP

IP

OP

OP

IP/OP

OP

IP

IP/OP

OP

OP

Population Demographics
Sample
NR (21 S)

150

2087

142

305

170

113

1051

133

SR

200

1066

Mean Age

NR

30.1

44.7

28.6

50.0

38.94

38.2

18.7

40.7

SR

44.0

54.0

Female Gender(%)

NR

100

66.6

45.7

66.9

57.06

66.2

71.3

65.6

SR

59.5

100

N

BP Excluded

X (7 S)

BP Included

X (14 S)

X
X

X

X

X
X

X

X

X

X

X

Independent Variables
SCID/ Ψ EVAL

X

X

X

X

X

Ψ EVAL- Psychiatric Evaluation, AOI- Age of Onset of Illness, BP- Bipolar, BSDS- Bipolar Spectrum Diagnostic Scale, CIDI-Composite International Diagnostic
Interview, FHX-Family History, GP- General Practice, HAM-Hamilton Rating Scale, HCL-32-Hypomania Checklist-32, IP- Inpatient, LOE- Level of Evidence, MAMeta Analysis, MDQ- Mood Disorder Questionnaire, N- Number,NR- Not Reported, OP- Outpatient, S- Studies, SCID- Structured Clinical Interview for the DSMIV, SN- Sensitivity, SP-Specificity, SR- Systemic Review

APPLICATION OF THE MOOD DISORDER QUESTIONNAIRE

35

Author

Wang

Frey

Boschloo

Gan

Poon

Lin

Lee

Rybakowski

Kung

MDQ

X

X

X

X

X

X

X

X

X

Ricci

Leao

Dodd

X

X

X

X

X

X

CIDI

X

BSDS
X

HCL-32

X
X

MINI

Measurable Outcomes
SN(%)

89

83

89

72

65

85

74

NR

86

61

68

73

SP(%)

84

82

84

73

77

87

84

NR

71

87

63

90

X

X

X

X

X

X

X

Optimal MDQ
Score Cutoff
≥7
<7

X
X

X (4+)

X (6)

X

Ψ EVAL- Psychiatric Evaluation, AOI- Age of Onset of Illness, BP- Bipolar, BSDS- Bipolar Spectrum Diagnostic Scale, CIDI-Composite International Diagnostic
Interview, FHX-Family History, GP- General Practice, HAM-Hamilton Rating Scale, HCL-32-Hypomania Checklist-32, IP- Inpatient, LOE- Level of Evidence, MAMeta Analysis, MDQ- Mood Disorder Questionnaire, N- Number,NR- Not Reported, OP- Outpatient, S- Studies, SCID- Structured Clinical Interview for the DSMIV, SN- Sensitivity, SP-Specificity, SR- Systemic Review

APPLICATION OF THE MOOD DISORDER QUESTIONNAIRE
Appendix C

(Rogers, 2003)

APPLICATION OF THE MOOD DISORDER QUESTIONNAIRE

Appendix D

APPLICATION OF THE MOOD DISORDER QUESTIONNAIRE

Appendix E