1.
1
A Survey Study of Mental Health Professionals’ concept of
mental illnesses. What are the main dimensions underlying
our understanding of Mental illnesses?
PSYCG096: Final Project (Research Project)- Individual Clinical Dissertation
Candidate number: FMYS0
Student Number: 110013301
Word Count: 7, 626.
Journal: This research is intended for the BioMed Central Journal (BMC).
Contribution: The author was jointly responsible for data collection alongside
another MSc student, and was solely responsible for data analysis, interpretation, and
write-up of this research paper.

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Abstract
Background.
The history of psychiatry reveals many competing models of mental health. For this reason
many have called for mental health professionals to move towards a more unified philosophy
to refine the efficiency of mental health care, by improving professionals ability to work
together. The current study intends to determine what present day mental health professionals
view as the underlying models of mental illness.
Methods.
This research employed a questionnaire design administering the Maudsley Attitude
Questionnaire, using an online survey system, sampling a wide spread of mental health
professionals (N=837). The questionnaire assessed professionals’ attitudes towards three
mental health illnesses; Major Depressive Disorder, Schizophrenia, and Antisocial
Personality Disorder, across eight of the most prominent models of mental illness. Data was
analysed by employing a two-way ANOVA and a Principal Component Analysis.
Results.
A significant difference in professional endorsement of mental health models was found, and
this was established for model endorsement for each mental illness. For schizophrenia it was
found that professionals mostly endorse a biological versus social realist model, followed by a
joint cognitive and behavioural component. For Major Depressive Disorder (MDD),
professionals most significantly endorsed a social realist model, followed by a cognitive and
behavioural component and least endorsed the biological model. Professionals most
significantly endorsed a joint social constructionist and nihilist component for Antisocial
Personality Disorder (APD), illustrating a potential lack of interest in claiming APD to be a
mental illness.
Conclusions.
Mental health professionals are most committed to combination models of mental illnesses,
coinciding with the movement of the biopsychosocial model. However some of the endorsed
models do not correspond with clinical practice, for instance the biological model of MDD
was the least significantly endorsed model. The research findings have several implications;
on professional attitudes towards disorder responsibility, stigmatization, and potential
changes to treatment regimes. For example; the importance professionals place on social
elements could be further researched to clarify if they are indeed as important as professionals
believe.
Keywords:
Survey, Mental illness, professional, training, attitudes, models.

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Introduction
Models of mental Illness
Throughout the history of mental health disorders, individuals have attempted
to understand mental illness in a diverse range of ways (Bertolote, 2008). These
approaches to explaining human behaviour hold certain perspectives, which contain a
set of assumptions about the human mind (McLeod, 2007). They hold important ideas
about the way we function, what parts of our behaviour are important to research and
using what methods. These perspectives have existed and evolved over the years to
produce a plethora of mental health models. Foerschner (2010) researched the origins
and timeline of mental illness throughout history, revealing dramatic chances in the
zeitgeist. These changes are important in understanding our interpretation of mental
illness in today’s modern era. Due to the large amount of previously reported
interpretations (Clare, 1976, Engel, 1977), there are currently a variety of ways to
understand mental illness from both mental health professionals (Deeley, 2006,
Broome, 2007), and from lay people (Tyrer & Steinberg, 2005). Therefore with so
many different mental health movements, teachings and research, these approaches
have developed into distinct models of mental illness, which form the science of
mental health.
It is important to understand what professionals working in mental health
perceive as the most influential models of mental illness. Ghaemi (2007) researched
the spread of mental illness models across professionals, and concluded that, although
psychiatric illnesses are complex phenomena that are best understood through a
pluralistic model, the most popular models at the time included biomedical, cognitive,
behavioural, psychodynamic and social perspectives. It is widely agreed that each
model has its own unique set of mechanisms that inform the way an individual would
classify, explain, and treat the mental illness (Ghaemi, 2007). Not only does this
affect the service user, but also influences the target and approach to research, for
example, either via laboratory experiments on genetic causes, or family therapy on
dysfunctional relationships. The way mental illnesses are interpreted at root level (i.e.
what symptoms are attributed to) has an immense impact on the empirical study of
mental health as a science (Good, 1995; Kleinman, 1998).

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Implications of Mental Illness Models
Research indicates that mental health professionals hold strong opinions
regarding models of mental illness, and these affect their willingness to provide
treatment in line with these models, such as medication versus psychological therapy
(Ahna, Proctora & Flanaganb, 2009). These opinions may however not be evidence-
based or follow protocol of current treatment guidelines, and for this reason
professionals’ attitudes may be negatively affecting the quality of treatment. Secker et
al (2010) followed this up using semi-structured interviews, with mental health
professionals on five different projects. They found that 2 radically different
approaches were mostly endorsed; clinical versus the social model of recovery. This
reflects a wide divide in professional attitude towards mental illness with regards to
treatment. Where these attitudes diverge from clinical guidelines, professionals may
be providing treatment based on their own clinical judgements rather than evidence-
based practice.
Explanatory models of mental illness can also have significant implications
for personal responsibility, and has potential implications in the criminal justice
system. Where behaviour is construed as a symptom of biochemical factors, the
individual is considered to not be in control, or hold responsibility, for their behaviour
(Williams, 2003). This model may justify a ‘not guilty by reason of insanity’ (NGRI)
defence, removing the individual’s responsibility for their crime (Robinson, 1998).
Slovenko (1995) highlights that almost all cases proposing this defence end with the
defendant being indefinitely committed to a psychiatric hospital, rather than a prison,
showing model interpretation holds a large bearing on an individual’s life outcome.
Explanations of a mental disorder may also impact on stigmatization. Jorm &
Griffiths (2008) believed that stigmatizing attitudes are elevated by psychiatric
labelling as well as by conceptualization of symptoms as a medical illness. The
research surveyed 3998 Australian Adults using four vignettes and measured attitudes
using a social distance and dangerousness scale. It was found that belief in
dangerousness for schizophrenia was predicted by medical illness conceptualization
and genetic causal factors. Therefore the biomedical models for mental disorders such

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as schizophrenia, may contribute to stigma. So discovering the general attitude with
which professionals view disorders could help in implementing systems to reduce
stigma accompanied by these attitudes. In support of this, research indicates that
biological explanations reduce the amount of empathy professionals provide for their
patients (Gibson, 2015; Lebowitzl & Ahn, 2014), a slightly alarming concept
considering the critical nature empathy plays in mental health care.
Finally, the models professionals choose to endorse have implications for
housing and social benefits. Burgoyne (2014) conducted a qualitative systematic
review of mental health and the setting of UK housing support, focusing on the
structural aspects of housing. Thematic analysis developed a conceptual model
containing three main determinants that enabled users to benefit from support. These
three factors were autonomy, domain and facilitation; the researchers concluded that
the “Tripod Model” illustrates the relationships between these themes. Burgoyne
(2014) suggested mental health diagnosis, treatment and support is required in an
acceptable balance to increase the chances of fruitful and continuous housing
outcomes for service-users. However, if a mental health professional chooses to
support a biological model of a mental health illness, they may focus on researching
particular aetiological models and certain treatments based on these models, therefore
potentially paying less attention to housing and social benefits issues, which appear to
play a large part in recovery.
Psychiatrist’s Perspectives
Previous investigations into this field of mental health, although somewhat
limited, have established some informative findings. Harland et al (2009) used an
online version of the Maudsley Attitude Questionnaire (2004) on trainee psychiatrists
from South London and Maudsley National Health Service (NHS), to measure how
respondents understood familiar mental illnesses in terms of propositions taken from
different models. Harland and colleagues (2009) established that within this niche
group of trainee professionals no single model was solely endorsed, and model
endorsement varied for each of the four chosen disorders i.e. Antisocial Personality
Disorder (APD), Major Depressive Disorder (MDD), Generalised Anxiety Disorder

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(GAD), and Schizophrenia. The most prominent mental illness interpretation, found
using a rigorous principal component analysis, was the attitude that schizophrenia was
explained and to be treated by the ‘biological’ model, but APD was the least endorsed
by this model. The investigative team concluded that trainee psychiatrists prefer
biological explanations for schizophrenia, but this exclusive attachment is not carried
over onto other mental disorders. Moreover, the researchers established that trainee
psychiatrists, as a profession, organise their perspective of mental disorders in a
biological versus non-biological dynamic (Harland et al, 2009). Such a simplistic
outlook on mental illness could be argued to be reductionist and may limit the
provision of quality standard care for all mental illnesses. However, McCabe and
colleagues (2006) argue that the modest convenience sample in this research limits
the generalizability of findings.
For this reason, the current research aims to establish whether this is the case
across all mental health professionals, as an overall group bias could have significant
effects for patients suffering from mental illnesses. Neglect of evidence-based
practice or national practice guidelines in favour of preferred models could negatively
impact on patient care.
Psychologist’s Perspectives
Research by Read, Moberly, Salter and Broome (In Press), similarly
conducted a study using an identical methodology with trainee clinical psychologists.
In line with Harland and Colleagues (2009), they found no single model was solely
endorsed. Rather, trainee clinical psychologists gave equal value to cognitive,
behavioural and psychodynamic interpretations over biological models of mental
disorders, across diagnoses. Moreover, much like Harland and colleagues (2009)
biological vs. non-biological dynamic, a similar contrasting belief system was found
with trainee clinical psychologists. They organised their attitudes on a biological-
psychosocial scale, a cognitive-behavioural continuum, and a psychodynamic-
spiritual dimension. It would be informative to see if these dynamics are a
phenomenon that occurs across all mental health professionals, or simply a product of
psychiatric or clinical psychology professional training.

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Both Read, et al (In Press) and Harland and colleagues (2009) research,
provides an emerging understanding of the attitudes of two prominent mental health
professions. However, psychiatry and psychology are only two of many mental health
professions that comprise psychiatry’s multi-disciplinary team (Jefferies & Chan,
2004, Craddock et al, 2008). It is therefore of interest to establish whether the same
underlying attitudes and biases are prominent within the broader spectrum of mental
health professions, which would be adversely affecting the multi-disciplinary format
used in UK mental health care.
Furthermore, the highest form of treatment and teaching quality can be seen to
potentially be lacking in the academic department of psychiatry. Miresco and
Kirmayer (2006) used a vignette method to explore whether an implicit mind-body
dichotomy existed amongst the department staff, since many have argued this issue no
longer exists. They established that when staff discussed a behavioural symptom it
was deemed due to psychological, not neurobiological causes, and with this view
service users were mostly considered to be somewhat responsible for their own
disorders. Although the outcome of this study informs of some potentially prejudicial
beliefs and practices, other research has found no such issue. For example, Brog and
Guskin (1998) used a questionnaire methodology to find students undergoing a
medical degree placed equal importance on biological and psychological elements
when contemplating treatment of mental illnesses as a whole. Some of the early
research in this field acknowledged the same mixed results issue, for example Rabkin,
(1972) deemed the available research on mental health professionals attitudes to be
mixed and lacking in theoretical basis.
Overall, research in this field is limited and findings are mixed. The current
study aimed to use an exploratory analysis to examine the significant structures of
professional attitudes towards models of mental illness. It was hypothesised that each
mental illness would be rated differently in terms of the explanatory models.
Previous research suggests that psychiatrists most strongly endorse a biological model
of schizophrenia (Harland et al, 2009), in line with NICE guidelines (NICE, 2014).
Therefore, it was hypothesised that a biological model of schizophrenia would be
most strongly endorsed by all professionals. Similarly the study aimed to explore

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which models professionals significantly endorse per mental illness and whether they
are in line with recent research evidence in the same area.
Methods
Study Design
Study Aims
This research aims to understand whether mental health professionals, as a
unit, place significantly different amounts of importance on different models of
mental illness, and whether this difference can be found for three specific mental
illnesses i.e. Schizophrenia, Major Depressive Disorder (MDD), and Antisocial
Personality Disorder (APD).
Ethical Approval
The Ethical Committee of University College London approved this study.
The link and research information was emailed to over 375 university administrators
and secretaries. An unknown amount of participants responded from the twitter and
online lancet advertisements. In total 829 professionals responded and 344 were
completed in its entirety.
Setting
This research utilised an online questionnaire survey system whereby a link to
the questionnaire could be sent over the Internet and accessed in various locations
across the UK. For this reason, the setting of the research covers several intended
locations and many more, which the researchers may be unaware of. The
questionnaire link was sent to; the top (up to) 100 University courses for nursing,
social work, occupational therapy, clinical psychology doctorate, and psychology and
psychiatry. (See Appendix 1 for a comprehensive list). Additionally, several social
media networks such as twitter accounts were used by the investigative team to
circulate the questionnaire link further, and the Lancet Online Journal also advertised
the link to the questionnaire on their website for eligible readers to complete.

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Sample
As this research aims to determine what underlying models all mental health
professionals utilize for certain mental illnesses, the research intended to draw upon a
wide variety of mental health professions. With regards to professional disciplines in
mental health, this included; psychiatry, clinical or counselling psychology, mental
health nursing, occupational therapy, social work, and arts therapy. Write-in options
were available for those who felt the available options did not match their
professional status (see Appendix 2). This sample group was intended to encompass
all professionals who may work in direct contact with patients of mental health
illness.
Materials
Measures
The questionnaire begins with a demographic section comprising items
relating to professional background, work setting, country of birth and residence (see
Appendix 3). The main section of the questionnaire used an adapted version of the
Maudsley Attitude Questionnaire (MAQ) developed in 2004; this can be found in
Harland et al (2009). The MAQ was used removing all questions related to
Generalised Anxiety Disorder (GAD) and several questions from section 1 (Questions
3,4,5,6,8,9,10,11, and 12), as they were no longer relevant to the research question.
This helped boost response rates by shortening the length of the questionnaire.
Additionally, the questionnaire was moved on to the online UCL questionnaire
website “Opinio” changing small layout elements of the original.
The order of the sections were also altered so that further demographic and
professional questions could be added to the end of the questionnaire, reducing
attrition caused by initial mundane questioning. The adapted and used version of the
MAQ can be found in Appendix 4. The main section consists of questions created to
explore mental health professionals’ attitudes towards mental illness by seeing how
respondents interpreted models of mental illness. The researchers utilized the models
initially proposed by Harland et al (2009). These models include; biological,
cognitive, behavioural, psychodynamic, social realist, social constructionist, nihilist,

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and spiritual frameworks. For each model the research followed Harland et al’s
(2009) formulation of 4 questions per mental illness to understand the entirety of the
models with regards to their aetiology, classification, research and treatment. Each of
the questions were then asked with reference to the three disorders using DSM-V
criteria, these were; Schizophrenia, Major Depressive Disorder (MDD), and
Antisocial Personality Disorder (APD). A breakdown of the questions asked per
model can be found in Table 1. The compiled questions were randomised
accordingly. Responses were laid out utilizing a five-point Likert Scale (Likert,
1932), allowing for a neutral response option, with significantly strongly agree
receiving a 5, and significantly strongly disagree receiving a 1.
Table 1. Questionnaire items arranged by model (number of the item corresponds to the order
of the item’s appearance in the questionnaire)
___________________________________________________________________________
Biological
1. The disorder results from brain dysfunction
6. The ideal classification of the disorder would be a pathophysiological one
9. The appropriate study of the disorder involves discovery of biological markers and the effects of
biological interventions
17. Treatment of the disorder should be directed at underlying biological abnormalities
Cognitive
15. Maladaptive thoughts and beliefs are normally distributed in the population and it is the extreme
ends of this distribution that account for the disorder
24. The disorder is nothing other than the sum of maladaptive thoughts, beliefs and behaviours
20. The study of the disorder should concentrate on understanding cognitive distortions and reasoning
errors
7. The disorder should be treated by challenging and restructuring maladaptive thoughts and beliefs
Behavioural
31. The disorder results from maladapted associative learning
3. The disorder is best approached through the study of abnormal behaviour
11. Studying the associations between antecedents and consequents in patients’ behaviour is the best
basis for modification of the disorder
19. The Behavioural problems in the disorder are best modified by associating new responses to a
given stimulus.
Psychodynamic
26. The disorder results from the failure to successfully complete developmental psychic stages
18. The disorder is due to unconscious factors (as defined psychodynamically)
22. The structure of the disordered psyche and its unconscious mechanisms is best understood by a
study of individual cases
28. Treatment of the disorder requires resolution of disturbed early object relationships
Social realist
14. Social factors such as prejudice, poor housing and unemployment are the main causes of the
disorder
2. The disorder arises as a consequence of social circumstances or conditions
5. The research into the disorder should focus on the identification of causative social factors
29. Government policies to reduce prejudice, poor housing and unemployment are the way to eradicate
the disorder
Social constructionist
16. There is no universal classification of disorder, only culturally relative classifications
32. The disorder is a culturally determined construction that reflects the interests and ideology of

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socially dominant groups
13. The disorder can only be understood in the context of local meanings and these meanings cannot be
extrapolated to universal classifications
10. Treatment of the disorder should be based on whatever folk treatments and models are accepted as
appropriate by the patient and their local community
Nihilist
23. Attempts to scientifically explain the disorder have resulted in no significant knowledge
27. All classifications and ‘ treatments ’ of the disorder are myths
12. Mental health professionals have no ‘ expertise ’ of the disorder over and above anyone else
4. The management of the disorder is best left to the resources of the individual
Spiritual
8. Neglecting the spiritual or moral dimension of life leads to the disorder
30. The disorder is better understood through religious or spiritual insights
25. Consulting a spiritual authority can give a better understanding of the disorder than psychiatry
21. Adherence to religious or spiritual practice is the most effective way of treating the disorder
Study Procedures
The study design used an exploratory study. As previously mentioned, the
survey was compiled in an online document on the UCL Questionnaire website
‘Opinio’. The link to this questionnaire was then circulated via email to the University
department/administrators, via the researchers twitter account, and the online lancet
journal. The Opinio survey systems collated results online and compiled them into an
SPSS Data file, PDF report, Html Report, and Raw data report, removing any issues
over anonymity when moving data for statistical analysis.
Pilot Phase
A preparatory trial phase was conducted to test whether the online survey
system worked and if the questionnaire contained any errors in clarity and formatting
that could be amended before conducting the data collection phase. The draft
questionnaire survey was sent out to the UCL Division of Psychiatry staff and the
students of the 2014-2015 MSc Clinical Mental Health Sciences course. The draft link
was circulated with an accompanying paragraph stating the main aims of the research
and the need for participants to complete the survey and provide feedback for the final
research phase. Feedback was used to remove Generalised Anxiety Disorder (GAD)
from the questionnaire, as respondents felt the questionnaire was too long and GAD
would provide little valuable findings. In total 104 participants began the pilot phase
survey, and 32 completed it.

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Validation Study
As the research used a previously validated questionnaire i.e. the MAQ by
Harland et al (2009), a repeated validation study was deemed unnecessary as
construct validity had already been accepted.
Type of analysis used
Methods used for analysis began using a within subjects two-way ANOVA to see
whether professional ratings significantly differed between categories i.e. between the
three mental illnesses, between the eight models of mental illnesses, and the
interaction between these two categories. Three principal component analyses (PCA),
one per mental illness, were then used to investigate which model factors grouped
together to produce specific professional attitudes.
Consent
Participant consent was received through their commencement of the survey.
If the participant was not willing to begin the survey they were not under any duress
to begin it, and were able to exit the online survey system whenever they felt they
wanted or needed to. The informed consent sheet can be found in Appendix 5.
Declaration of Interest
None known.

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Results
Respondent’s demographic and professional background
The sample of mental health professionals is illustrated in Table 2. From the
608 respondents, the mean number of years working within the field of mental health
was 11.65, with a ranging from 0-45 years. The majority of participants retained a
recognized professional qualification, and were working in a health care setting in the
field of psychiatry or focused in clinical or counseling psychology, mostly in the field
of depression and anxiety. The average age of the respondent was calculated at 40.26,
ranging from 19-99, with almost 70% majority female respondents. The majority of
respondents identified their ethnicity as white British, with the least represented
ethnicity being Black/Black British African.
Table
2.
Respondent’s
demographic
and
professional
background
summary
Demographic/professional background variable
No. Of
Respondents Mean Range
-Years working in Mental Health
-Recognised Qualification
Qualified Professional
Training for Professional Qualification
Working in Mental Health research
Working in Mental Health Care
Postgraduate student in mental health
Undergraduate student in mental health
-Profession qualified/training in
Psychiatry
Clinical or counselling psychology
Mental Health Nursing
Occupational Therapy
Social Work
Art Therapies
Not Applicable
Other*
-Age
-Sex
Female
Male
-Field of Work
Healthcare Setting
Research/Academia
Other
Not Answered
-Engaged in Research
608
630
378 (60%)
87 (13.8%)
67 (10.6%)
45 (7%)
41 (6.5%)
12 (1.9%)
630
86 (13.6%)
159 (25%)
59 (9%)
15 (2.3%)
75 (11.9%)
25 (3.9%)
136 (21%)
73
426
427
297 (69.56)
130 (30.44%)
702
392 (55.8%)
206 (29.3%)
104
215
631
11.65
-
-
40.26
-
-
0-45
-
-
19-99
-
-

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Yes
No
-Mental Health Population
Child and Adolescents
Dementia
Depression and Anxiety
Eating Disorders
Intellectual/Neurodevelopment
Personality Disorders
Psychosis
Substance Misuse
Not Applicable
Other
Not Answered
-Ethnicity
White British
White Irish
White other
Asian/Asian British: Indian
Asian/Asian British: Pakistani
Asian/Asian British: Bangladeshi
Asian/Asian British: Other
Black/Black British: Caribbean
Black/Black British: African
Mixed: White and Black African
Mixed: White and Asian
Mixed: Other
296 (46.9%)
335
428
112 (26%)
87 (20%)
299 (70%)
98 (23%)
97 (22.6%)
230 (53.8%)
228 (53.7%)
160 (37%)
53
40
418
424
256 (60.37%)
31 (7.3%)
96 (22.6%)
10 (2.3%)
2 (0.5%)
1 (0.2%)
6 (1.4%)
2 (0.47%)
3 (0.7%)
1 (0.2%)
7 (1.6%)
5 (1.17%)
-
-
-
-
* Available in Appendix 2.
Table
3.
Descriptive
statistics
for
the
aggregate
attitude
scores
by
model
and
by
disorder
(possible
range
3-­‐20).
Schizophrenia
Major Depressive
Disorder
Antisocial Personality
Disorder
Biological 12.64 (4.2) (4-20) 11.66 (3.9) (4-20) 10.36 (3.7) (4-20)
Behavioural 11.07 (2.5) (4-17) 11.86 (2.4) (4-17) 12.90 (2.7) (4-20)
Cognitive 11.22 (2.8) (4-20) 12.48 (2.6) (4-20) 12.41 (2.7) (4-20)
Psychodynamic 10.41 (3.2) (4-18) 10.85 (3.1) (4-20) 11.55 (3.5) (4-20)
Social Realist 12.86 (3.1) (4-20) 13.81 (2.7) (6-20) 13.87 (2.8) (4-20)
Social
Constructionist
11.02 (3.7) (4-20) 11.24 (3.5) (4-20) 11.46 (3.4) (4-20)
Nihilist 6.08 (2.4) (3-15) 6.11 (2.3) (3-15) 6.52 (2.4) (3-15)
Spiritual 7.48 (2.9) (4-17) 7.70 (2.9) (4-16) 7.77 (2.8) (4-15)

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Figure 1. Standardized mean aggregate scores by model and by mental disorder, with a
possible range of 4-16. Disorder included; Schizophrenia, MDD as Major Depressive
Disorder, and APD as Antisocial Personality Disorder. Models included; Beh-
Behavioural, Bio-Biological, Cog- Cognitive, Psych- Psychodynamic, Real-Social Realist,
Const- Social Constructionist, Nihl- Nihilist, Spir-Spiritualist.
ANOVA
A
two-­‐way
within-­‐subjects
analysis
of
variance
was
conducted
to
explore
the
impact
between
mental
illnesses
and
models
of
mental
illness,
as
measured
by
a
questionnaire
on
professional
attitudes.
Mental
health
illnesses
were
divided
into
3
levels;
Schizophrenia,
Major
Depressive
Disorder,
and
Antisocial
personality
disorder.
Mental
health
models
were
divided
into
8
levels;
biological,
behavioural,
cognitive,
psychodynamic,
social
realist,
social
constructionist,
nihilist,
and
spiritual.
The dependent variable is the attitude professionals hold
towards mental health models for the three mental health disorders.
Mauchley’s test for sphericity demonstrated that the assumption of
homogeneity of variances has been violated for mental health illnesses (W=.855, X2
(2)= 2.43, p<.001), mental health models (W=.118, X(27)2
=907.50, p<0.001), and the
4
6
8
10
12
14
16
AttitudeScore
Schizophrenia
MDD
APD

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interaction between the two (W=.001, X(104)2
=2760.21, p<0.001). Therefore
Greenhouse-Geisser corrections were applied.
The
interaction
effect
between
mental
health
illnesses
and
mental
health
models
was
statistically
significant,
F
(14,
5978)=
113.13,
p<0.
0005,
indicating
that
mental
illnesses
are
significantly
associated
with
mental
health
models.
There
was
a
statistically
significant
main
effect
for
mental
illnesses;
F
(2,
854)=
98.466,
p<0.0005,
as
well
as
a
statistically
significant
main
effect
for
mental
health
models;
F
(7,
2989)=
349,14,
p<
0.0005.
Principal Component Analysis
The same respondents were entered into each Principle component analysis
calculated for each mental illness. Sample descriptive’s for all the analysis can be
therefore be found above in Table 2.
Professional’s attitudes towards mental illnesses
In order to investigate which model factors group together 3 Principal
component analysis were conducted, 1 per mental health disorder. For each PCA, 365
participants were analysed. Participants who did not complete the whole questionnaire
were excluded from all PCA’s, and so for each PCA the average age is 40.26 (range=
19-99), 69.56% of respondents were female, and the remaining 30.44% were male.
Inspection of the scree plot was used to select the number of components for
each analysis. The questions relating to each of the three chosen mental disorders
were included in the principal components analysis to reveal the amount of variance
between the questions, which can be explained by each of the statistically significant
factors found in the initial parallel analysis.
Initial eigenvalues for schizophrenia indicated that the first five factors
explained 29%, 9%, 7%, 4%, and 4% of the variance respectively, totaling 54% of the
total variance. The sixth, seventh, and eighth factors had eigenvalues just over one;
the sixth factors explained 3% of the variance and the seventh and eighth 2%. The
first five factors were individually examined with oblimin rotations of the factor-

17.
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loading matrix. The five-factor solution, explaining 54% of the variance, was favored
due to; previous theoretical backing, the flattening off of the eigenvalues on the scree
plot after the initial three, and the inadequate interpretation and loadings from the
fourth to eighth factors.
Primary eigenvalues for major depressive disorder determined that the initial
six factors explained 23%, 10%, 7%, 4%, 4% and 3%, calculating to explain the
cumulative variance of 51%. The seventh and eighth factors had eigenvalues of up to
1%. Solutions for the first six factors were inspected employing oblimin rotations of
the factor-loading matrix. The six factor solutions explaining 51% of the variance was
endorsed for the same three reasons as used for Schizophrenia. Initiatory eigenvalues
for antisocial personality disorder signified that the initial four factors explained 21%,
10%, 7%, and 5% of the variance, adding up to explain 45% of the total variance. The
following fifth, sixth, seventh and eighth factors had eigenvalues of just over one,
each explaining 3% of the variance. Solutions one to four were examined using
oblimin rotations of the factor-loading matrix. This five-factor solution, explaining
49% of the variance, was selected for the same three reason as the previous two factor
analysis for schizophrenia and major depressive disorder.
Schizophrenia
According to the Pattern Matrix produced by PCA (found in Appendix 7), a
significant proportions of the variance was explained by 5 components, KMO= .913,
p<.001. The first component included a substantially large degree of significant
questions; 15, 23, 8, 12, 38, 22, 20, 33, 19, 35, 29, 9, 11. The most supported
statements were found in questions 15, 23, 8 and 12; these were all biological
statements such as “the appropriate study of the disorder involves discovery of
biological markers and the effects of biological interventions” (question
15). However, questions 38, 22, 20, 33, 19, 35, 29, 9, and 11 were also clustered into
this component. These questions encompassed the social realist model, with
statements such as “social factors such as prejudice, poor housing and unemployment
are the main causes of the disorder” (question 20). This leads to a single component
incorporating a biological and social realism dimension, whereby professionals are

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most likely to endorse certain sides of the component. However, as we can see from
the pattern matrix, the biological explanations are negatively correlated with
underlying factor, and the social realist explanations are positively correlated. This
indicated that the degree to which people go for biological models are less inclined to
support social realist explanations, and this is one of the main ways to account for the
variation between people’s views in this data set.
The principal component analysis formed a second component consisting of
questions 13, 26, 25, 17, 21, and 37, reflecting a cognitive and behavioural model
of schizophrenia e.g. “the disorder should be treated by challenging and
restructuring maladaptive thoughts and beliefs”. The next component formed
consisted of questions 36, 27, 31, 14, 32, 34, 28, and 24. The first group of
questions from 36, 27, 31, and 14 were statements endorsing the spiritual model,
such as “adherence to religious or spiritual practice is the most effective way of
treating the disorder” (question 27). The following questions of 32, 34, 28 and
24, included statements regarding the psychodynamic model, such as “the disorder
results from the failure to successfully complete developmental psychic stages”
(question 32). This component therefore reflects a spiritual and psychodynamic
model. The fourth component consisted of questions, which referred to the social
realist and nihilist models of schizophrenia, and the last significantly endorsed
component reflected the social constructionist and nihilist models.
Parallel analysis revealed 5 components. PCA- KMO = .913 Bartlett’s<.001
àassumptions met.
Overall variance explained by all components = 54.41%
Component 1-
Bio, Social Real.
Component 2-
Cognitive, Behav
Component 3
Spirit, PsychoD
Component 4-
Soc Real, Nihi
Component 5-
Soc Const, Nihi.
29.2% 9.31% 7.14% 4.49% 4.17%
Major Depressive Disorder
According to the Pattern Matrix produced in the MDD PCA, a significant
proportions of the variance was explained by 6 components, KMO= .913, p<.001. It
was shown that the most significantly agreed with component consisted of questions

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pertaining to the social realist model of MDD. The cognitive and behavioral models
of major depressive disorder appeared to be the second component; containing
questions such as 13 “The disorder should be treated by challenging and restructuring
maladaptive thoughts and beliefs” as well as questions 26, 21, 17, endorsing cognitive
explanations and treatments. Questions 36, 27, 31, and 14 clustered together to form
the third component, reflecting a significantly endorsed spiritual model, as seen by
question 36 “The disorder is better understood through religious or spiritual insights”.
The fourth supported component formed the psychodynamic model, containing
questions 24, 34, 32, and 28. The social constructionist and nihilist models of
schizophrenia then followed to cluster as the fifth component, containing questions
18, 29, 22, 33, 19, and 16 e.g. “mental health professionals have no ‘expertise’ of the
disorder over and above anyone else”. The last component consisted of questions 15,
8, 23, 27 and 12. These questions consisted of statements such as “The appropriate
study of the disorder involves discovery of biological markers and the effects of
biological interventions” (Question 15), allowing for the potential interpretation that
the least prominent and supported model of major depressive disorder is the
biological model.
Parallel analysis = 6 components PCA- KMO = .874 Bartlett’s <.001 à
meets assumptions
Overall variance explained by all components = 51%
Component 1-
Social Realist
Component 2-
Cog, Behav
Component 3-
Spiritual
Component 4-
Psychodynamic
Component 5-
Social C, Nihi
Component 6-
Biological
23.38% 10.57% 7.69% 4.91% 4.43% 3.8%
Antisocial Personality Disorder
By viewing the Pattern Matrix from the APD PCA, we can see that a
significant proportions of the variance was explained by 4 components, KMO= .913,
p<.001. The first component outlined questions 18, 22, 33, 29, and 19, which referred
to the social constructionist model, as well as questions pertaining to the nihilist
model, forming a social constructionist and nihilist component. A cognitive and
behavioural dimension followed second with questions 13, 25, 26 and 17. The third
component was clustered into questions 23, 15, 8 and 12; reflecting a biological vs.
social realist model i.e. professionals endorsing biological models do not tend to

20.
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endorse social realist explanations. Questions 36, 27, 31, and 14, as well as questions
24, 34, 32, and 28 clustered together to form the last spiritual and psychodynamic
component of antisocial personality disorder.
Parallel analysis = 4 components PCA- KMO =.848 Bartlett’s <.001 à
meets assumptions
Overall variance explained by all components = 45.15%
Component 1-
Social C, Nihi
Component 2-
Cognitive, Behavioural
Component 3-
Bio, Social Realist
Component 4-
Spiritual, PsychoD.
21.39% 10.53% 7.74% 5.48%

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Discussion
Main Findings
The results of this study support the belief that mental health professionals do
significantly endorse certain models more than others, and this seems to occur
specifically for each mental illness. However, the more specific propositions
regarding individual model endorsement per mental illness were not accurately
supported by the findings, which were unexpected. For instance, it was found that
professional attitude towards Schizophrenia most significantly supported a biological
versus social realist interpretation of the disorder.
The results exhibited several important findings, which might have significant
implications on clinical practice and research. Firstly, the diversity of professions
within the participant pool shows that there is a general consensus amongst
professionals regarding which models are valuable. This can most notably be seen in
the lowest mean for the nihilist model in Table 3, and in Figure 1 showing the lowest
mean for all illnesses in comparison to the other models of the illnesses. This could
imply that mental health professionals are moving away from any critical psychiatry
models, and generally towards a disorder specific and dual-dimension interpretation
of psychiatric illnesses. Without further analysis on separated professions, it could
also be argued that the profession of mental health is not yet moving towards a more
unified classification and interpretation of psychiatry which may lead to better quality
treatment through well refined multi-model concepts. For example, for many years
the nature vs. nurture argument has prevailed, and the findings for schizophrenia
propose this dispute still exists i.e. the biological model (nature) and social realist
model (nurture) were found to be at odds with each other.
Interpretations and Implications
Alternatively, some would argue that this multi-modal representation has
developed due to professional acknowledgement of the inadequate effects that anti-
psychotic medication has on many patients suffering from Schizophrenia (Harrow,
Jobe, & Faull, 2014, and Steingard, 2013), and evidence base suggesting
schizophrenia to be a complex multi-factorial disorder (Maccabe et al, 2006).
Potentially this has been aided by the development and rise of the biopsychosocial

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model (Engel, 1977), as well as recent models of psychosis such as Robin Murray’s
integrated model, which has increased in use (Frankel, Quill, & McDaniel, 2003), and
is now adopted for practice by many services, for example the Early Intervention in
Psychosis services (Borrell-Carrio, Suchman, & Epstein, 2004). This would fit in with
the current research finding of a joint cognitive and behavioural component falling
second to a biological and social constructionist component.
Current research might be highlighting professional’s additional lack of
confidence in anti-depressant medication, a subject that has been actively debated in
the academic world (Kirsch, et al, 2008, Moncrieff, Wessely, & Hardy, 2004, Hetrick
et al, 2007). This can be concluded from the finding that professionals placed the least
significance on the biological model of MDD. Indeed there is an abundance of
literature citing a ‘crisis of confidence’ in anti depressant medication (Nierenberg et
al, 2011) with some claiming antidepressants might be expensive and overused
placebos. However research simultaneously asserts that in 2008 1 out of 12
Americans aged 12 and over were taking antidepressant medication, mounting to 11%
of the population and 2.7% of youths between 12-17 (Pratt, Brody, & Gu, 2011).
Although this is a complex debate, with some empirical findings in strong
support of anti-depressant use (Levkovitz et al, 2011), especially for depressed
patients with heart disease or other chronic illness (Pizzi et al, 2011), the current
research findings display professional opinion to place the least significance on a
biological model for MDD, this would include placing little importance on
antidepressant medication as a biological treatment for MDD. The discrepancy
between belief and practice, as antidepressants are still routinely prescribed (Mojtabai
& Olfson, 2010), could potentially be explained through lack of alternative
treatments. For example; light therapy, exercise, massage, acupuncture, yoga and
meditation, and even nutritional changes (Fobbester et al, 2004), are some of the
holistic alternatives to antidepressants, but their effect on depression (especially
MDD) has found to be severely lacking (Luberto et al, 2013, Albanese et al, 2012),
and small effects are only found when used in combination with antidepressants
(Talaei et al, 2015, and Ravindran et al, 2013).
Research by Howell (2013) and Black & O’Sullivan (2012) agree with this

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lack of alternatives, despite investments to address potential issues such as social
disadvantage (Pleasence, Balmer, and Hagell, 2015). Social disadvantages are vast
and not easy to individually link to mental health, however research by Barry (2010)
proposed demographic factors such as age, gender, and ethnicity as important
determinants of social disadvantage. Friedli (2009) and Marmot (2010) argued
structural and environmental factors lead to susceptibility to mental health disorders,
alternatively McCulloch and Goldie (2010) grouped social determinants of mental
health into four sections; societal, community, family, and individual elements, each
containing 6 factors (see Appendix. 6 for comprehensive breakdown). Although
social determinants and disadvantages of mental health might be challenging to
define, research still strongly suggests these factors play an important role in mental
illness. The results of the current research may actually be showing that mental health
professionals are becoming aware of these social factors, and hoping it might provide
an alternative to other treatments, such as anti depressant medication.
The value professionals place on social factors, that the current findings have
highlighted, may potentially be demonstrating the explanatory model that
professionals are proposing for each mental illness. In this way, the results might
indicate whether professionals place an increased amount of responsibility for the
disorder on the individual themselves or alternative mechanisms. For instance, if
professionals are placing significance on social factors for Schizophrenia and MDD
then we could determine that the same factors are responsible for the disorder onset
and it’s symptoms. This could be a meaningful finding for individuals facing criminal
convictions for crimes committed whilst presenting with a mental health diagnosis.
For many years academics have hotly debated the liability individuals face for their
actions whilst unwell (MacDonald, Hucker, and Hebert, 2010), with courts of law
even placing guilt on individuals for not taking their medication (harrow, Jobe &
Faull, 2012). This is especially prominent in APD, associated with a lack of sense of
responsibility for ones own actions (Harpur, Hare, & Hakstian, 1989). Therefore the
current finings could be used in several forums to illustrate mental health
professional’s true beliefs in causes of mental illness, and this could have serious
repercussions for individuals within the criminal justice system.
Furthermore, if professionals are moving away from single model explanations and

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towards a multi-modal account of mental illness, this could precipitate (or
alternatively have followed) a reduction in stigmatizing attitudes. When using
individual models, professionals may choose to view diagnosed individuals in only
that framework, for instance viewing individuals with schizophrenia in only a
biological model, when this occurs it might feed into society who believe that the
individual has something innately wrong with them, making them instinctively erratic
and in some cases dangerous. For example Read and Harre (2001) confirmed that
biological beliefs of mental illness are correlated with increased negative attitudes,
Kingdon and Young (2007) and Angermeyer et al (2005) believed biological models
worsened stigma, and over half of the UK population believe schizophrenia is
biologically based rather than a combination of social and biological causes (Kingdon
et al, 2004). In actuality there is a very wide variety of research proposing just this,
for example Read, Harlam, Sayce and Davies (2006) conducted a systematic review
on the effect of prejudice and schizophrenia through different approaches. The
research aimed to evaluate the effectiveness of the anti-stigma programme ‘mental
illness is an illness like any other’ approach, in relation to schizophrenia. The
researchers discovered that society prefers psychosocial models of schizophrenia in
comparison to biogenetic ones, as the latter cause diagnostic labelling and are
positively related to fear and a desire for social distance. Thus the multi-modal
approach enhances public understanding of schizophrenia and reduces prejudice.
Limitations
However, although interesting to speculate what can be extrapolated from the
results, the research methodology might suffer several flaws, which limit the value of
any interpretations based on it. For example, the anonymous and online nature of the
survey meant that the majority of respondents began filling in their responses but
withdrew with ease. This severely reduced the number of respondents for the main
bulk of the attitude questions, reducing the overall sample size and limiting the
generalizability of the results. From this, and the use of a convenience sample, we
could question how representative the findings are to the general population of mental
health professionals both within the UK and internationally. Potential respondents
were only approached within the UK, although the online setting allowed for a much
wider potential scope and did actually reap a group of overseas respondents. Besides

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issues with attrition, the sampling bias concerns were worsened due to the personal
circulation of the research questionnaire by the researchers. The leading researchers
personally disseminated the questionnaire amongst colleagues and acquaintances that
they believed would complete the research, rather than focusing on extending the
research to all professions and fields of mental health. This may have caused for the
response pool to be biased towards the professions and attitudes that the researchers
maintained, thus producing a selection bias and reducing the results ability to capture
current professional true attitudes.
The attitude questionnaire used was adapted from Harland et al (2009), and so
it was believed that internal consistency verification was not needed. However
Harland et al (2009) acknowledge that due to their sample size the analysis they
conducted was based on the belief that participants would endorse the illnesses for
each model equally, but before analyzing their raw data they assessed item correlation
between and within paradigms, not a formal method of testing internal consistency. It
was observed that the question regarding cognitive treatment correlated stronger with
items of other models than models within the cognitive model. Harland and
colleagues concluded that this might have occurred due to the acceptance of cognitive
behavioural therapy across disorders even though these disorders may not be
principally interpreted using cognitive models (NICE, 2008). Regardless of whether
this can potentially be explained, the questionnaire did not entirely show internal
consistency, and so using it without conducting more rigorous internal consistency
testing severely limited the validity of the results. In comparison to Harland et al
(2009), the current research similarly showed significant endorsement of a biological
model of schizophrenia, but this was found to be at odds with an equally significant
social explanation, and was apparent for mental health professionals as a group unit
rather than solely psychiatrists.
Of additional concern is the feedback the online survey received through
Question 45, which allowed respondents to comment on any aspect of the research.
The majority of feedback outlined concerns about the difficulty participants felt in
completing the questionnaire. A large volume of the feedback outlined the issue of
questions being too definitive implying absolutes i.e. the disorder is either biological
or spiritual, allowing for only one answer to each question per illness. Respondents

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felt that a lot of the models are not mutually exclusive but have several variables in
play at once, especially when considering individual cases. This caused offence to
some respondents, causing many participants to dropout, which lead to a high level of
attrition. Many respondents also claimed to fundamentally disagree with the
terminology used, for example the term ‘disorder’ was deemed offensive, as it
assumes there is something fundamentally at fault with the individual. Some
respondents also claimed to not know what the illnesses were, potentially a definition
of each disorder could have allowed for better understanding and increased quality
results. The most prominent issue reported was the desire for respondents to answer
the questions according to the biopsychosocial model, as well as a person-centered
approach, which coincides with much of the feedback protesting the simplicity of the
questions. Respondents claimed that due to the single available answers that the
results rendered will be misleading, and not representative of their true attitude,
causing many to chose neutral responses for the majority of questions.
Strengths
Although this research has its critiques, it also has several strengths that
enhance the validity of our results. For instance, even though the dropout rates were
observable the main section containing the attitude questions received a high amount
of responses, allowing for a good effect and sample size, increasing the
generalizability of results. The online setting and ability to further distribute the
questionnaire link meant that the questionnaire reached many different mental health
professionals in a variety of settings, both academic and clinical, and of many
different ages and ethnicities. This widened the participant pool by profession, mental
health disorder industry, and geographical location, further increasing the
generalizability of results, an aspect which previous research in the same field has
failed to do. The online nature of the research provided complete anonymity as well
as the ability to dropout with no duress.
Further Research
There are many directions further research on this topic could take. For
instance, the same questionnaire could be used in the same setting and method, but
the difference between treatment and explanatory model significance could be
differentiated, allowing for a thorough investigation of whether professional attitudes

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differ between what they believe explains the onset of the disorder and what treatment
will effectively benefit patients. A contradictory finding in the current research
showed the biological treatment was the least significantly endorsed component for
MDD, yet NICE (2009) still recommend drug treatments, allowing for many
professionals to also endorse it as a treatment. Therefore further research into the
cause of this discrepancy would highlight why professionals are endorsing a treatment
that they do not believe effective. Future research might also look into the specific
aspects of social factors that have significant affects on mental health. Current
evidence cannot adequately inform the development of social capital interventions,
but by looking at what exact factors professionals believe to have the most prominent
affects on mental health, policy makers can use this to increase social support and
reduce rates of diagnosis and relapse.
As discussed earlier, professional interpretation of mental illnesses has a
prominent effect on stigma, an area that needs further research to develop programs to
increase understanding. For example Read and Harre (2001) found that increased
personal contact with an individual receiving psychiatric treatment corresponded with
positive attitudes towards psychiatric illnesses, whereas Schomerus et al (2011)
conducted a systematic review and meta-analysis of public attitudes to mental illness
and found that increasing public knowledge on biological aspects of mental illness did
not increase social acceptance of mental illness. Therefore future research could aim
to further understand what aspects of social contact increase positive attitudes, or
develop programs to effectively allow this. Another field that may help to reduce gaps
could be the development of a unifying philosophy amongst mental health
professionals, which would guide clinical practice. Norman and Peck (1999) and
Hannigan (1999) acknowledged the division amongst the professions and the
emphasis placed on different elements of the biopsychosocial model by professions,
claiming that incompatible frameworks don’t allow for a functioning
multidisciplinary team, therefore further research is needed to understand how the
professions are unified, what inherently divides them, and if service standards can be
improved through unification.

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Conclusions
Mental health professionals are most committed to combination models of
mental illnesses, coinciding with the movement of the biopsychosocial model.
However some of the endorsed models do not correspond with clinical practice, for
instance the biological model of MDD was the least significantly endorsed model, but
drug therapies are often used to treat this disorder. The research findings have several
implications; on professional attitudes towards disorder responsibility, stigmatization,
and changes to treatment regimes, for example; the importance professionals place on
social elements could be met with changes in treatments and social support
programmes.
Authors’ Contributions
JM was responsible for the respective write-up of the current research
paper, as well as the circulation of the online questionnaire link amongst University
departments and particular academic staff. JM and SJ contributed to the
development of the research objectives and methods. KD, SJ, VB, and JM were
responsible for the alterations and development of the questionnaire and online
survey, and all jointly invested in circulating the research questionnaire to
professionals for participation. VB helped with data analysis, statistical support,
and draft approval.
Acknowledgements
This study was supported by the University College London, Division of
Psychiatry, as well as Professor Sonia Johnson and Dr Vaughan Bell.

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References
Ahn, W-K., Proctor, C.C., Flanagan, E.G. (2009) Mental health clinicians’ beliefs
about the biological, psychological, and environmental bases of mental
disorders. Cognitive Science, 33 (2), 147-182.
Albanese, A., Hamill, G., Jones, J., Skuse, D., Matthews, D.R., Stanhope, R., 1994.
Reversibility of physiological growth hormone secretion in children with
psychosocial dwarfism. Clinical Endocrinology. 40, 687–692.
Angermeyer, M.C., Dietrich, S., (2005). Public beliefs about and attitudes towards
people with mental illness: a review of population studies. Acta Psychiatrica
Scandinavica; 113, 163–179.
Barry M (2010) Adopting a mental health promotion approach to public mental
health. In: I Goldie (Ed) Public Mental Health Today. Brighton: Pavilion
Publishing Ltd.
Bertolote, J. (2083) The roots of the concept of mental health. World Psychiatry, 7
(2), 113-116.
Black O and O’Sullivan I (editors) (2012) Wealth in Great Britain Wave 2: Main
results from the wealth and assets survey 2008-2010 (part 3). Office for
National Statistics.
Brog MA, Guskin KA (1998). Medical students’ judgments of mind and brain in the
etiology and treatment of psychiatric disorders. Academic Psychiatry 22, 229–
235.
Broome, M.R. (2007). Taxonomy and ontology in psychiatry: a survey of recent
literature. Philosophy, Psychiatry, and Psychology 13, 303–319.
Borrell-Carrió F, Suchman AL, Epstein RM: The biopsychosocial model 25 years
later: principles, practice, and scientific inquiry. Ann Fam Med 2004; 2:576-
582.
Burgoyne, J. (2014) Mental health and the settings of housing support- a systematic
review and conceptual model. Housing Care and support, 17 (1), 4-26.
Clare, A.W. (1976). Psychiatry in Dissent: Controversial Issues in Thought and
Practice. Tavistock : London.
Craddock, N., Antebi, D., Attenburrow, M-J., Bailey, A., Carson, A., Cowen, P.,
Craddock, B.. et al. (2008). Wake-up call for British psychiatry. The British
Journal of Psychiatry 193, 6-9.

30.
30
Deeley Q (2006). The cognitive anthropology of belief. In The Power of Belief (ed. P.
Halligan and M. Aylward), pp. 33–54. Oxford University Press : Oxford.
Engel, G. (1977). The need for a new medical model: A challenge for biomedicine.
Science, 196 (4286), 129-136.
Engel G. L. (1980). "The clinical application of the biopsychosocial model".
American Journal of Psychiatry 137 (5): 535–544.
Fobbester, D et al., Optimum Nutrition UK survey, October 2004.
Foerschner, A. M. (2010). "The History of Mental Illness: From 'Skull Drills' to
'Happy Pills'." Student Pulse, 2(09).
Foucault, M (1976). Madness and Civilization: A History of Insanity in the Age of
Reason. Tavistock: London.
Frankel RM, Quill TE, McDaniel SH (Eds.): The Biopsychosocial Approach: Past,
Present, Future.University of Rochester Press, Rochester, NY, 2003.
Friedli L (2009). Mental health, resilience and inequalities. Copenhagan: World
Health Organization Regional Office for Europe.
Ghaemi N (2007). The Concepts of Psychiatry: A Pluralistic Approach to the Mind
and Mental Illness. The Johns Hopkins University Press: Baltimore.
Gibson, J., Raphael, K., Goodyer, I., et al (2015). A call for greater transparency in
health policy development: observations from an analysis of child and
adolescent mental health policy. Evidence and Policy: Journal of Research,
Debate and Practice, 11 (1), 7-18.
Good B (1995). Medicine, Rationality, and Experience. Cambridge University Press :
Cambridge.
Hannigan, B. (1999) Joint working in community mental health: prospects and
challenges. Health and Social Care in the community, 7 (1), 25-31.
Harland, R., Antonova, E., Owen, G.S., Broome, M., Landau, S., Deeley, Q., &
Murray, R. (2009) A study of psychiatrists’ concepts of mental illness.
Psychological Medicine, 39, 967-976.
Harrow, M., Jobe, T.H., Faull, R.N. (2014) Does treatment of schizophrenia with
antipsychotic medications eliminate or reduce psychosis? A 20-year multi-
follow-up study. Psychological Medicine, 13 (2), 5-27.
Harrow, M., Jobe T.H., Faull, R.N. (2012). Do all schizophrenia patients need
antipsychotic treatment continuously throughout their lifetime? A 20-year
longitudinal study. Psychological Medicine, 42 (10), 2145-2155.

31.
31
Harpur, T. J., Hare, R. D., & Hakstian, A. R. (1989). "Two-factor conceptualization
of psychopathy: Construct validity and assessment implications.".
Psychological Assessment 1 (1): 6–17.
Hetrick SE, Merry S, McKenzie J, et al. Selective serotonin reuptake inhibitors
(SSRIs) for depressive disorders in children and adolescents. Cochrane
Database Syst Rev 2007, Issue 3
Jefferies, N. & Chan, K.K. (2004), Multidisciplinary team working: is it both hostile
and effective? International Journal of Gynaecological Cancer 14(2): 210-
211.
Jorm, A.F., & Griffiths, K.M, (2008). The public’s stigmatizing attitudes towards
people with mental disorders: how important are biomedical
conceptualizations. Acta Psyhiatrica Scandavica, 118 (4), 315-321.
Kleinman A (1998). The Illness Narratives : Suffering, Healing, and the Human
Condition. Basic Books: New York.
Kirsch I, Deacon BJ, Huedo-Medina TB, et al. Initial Severity and Antidepressant
Benefits: A Meta-Analysis of Data Submitted to the Food and Drug
Administration. PLoS Med 2008; 5(2)
Kingdon, D., & Young, A, H. (2007) Research into putative biological mechanisms of
mental disorders has been of no value to clinical psychiatry. British Journal of
Psychiatry, 191, 285-290.
Kingdon, D., Sharma,T. & Hart, D. (2004) What attitudes do psychiatrists hold
towards people with mental illness? Psychiatric Bulletin, 28, 401-406.
Lebowitz, M., & Ahn, W. (2014). Effects of biological explanations for mental
disorders on clinicians’ empathy Proceedings of the National Academy of
Sciences, 111 (50).
Levkovitz Y, Rabany L, Harel EV, Zangen A. (2011). Deep transcranial magnetic
stimulation add-on for treatment of negative symptoms and cognitive deficits
of schizophrenia: a feasibility study. International Journal of
Neuropsychopharmacology 14(7):991-6.
MacCabe J, O’Daly O, Murray RM, McGuffin P, Wright P (2006). Beyond Nature
and Nurture in Psychiatry. Informa Healthcare : Abingdon, Oxon.
MacDonald, N., Hucker, S.J., Hébert, P.C. (2010) “The crime of mental illness.”
Editorial, Canadian Medical Association Journal,182(13):1399.
Marmot M (2010) Fair Society, Healthy Lives: Strategic Review of Health

32.
32
inequalities in England post 2010.
McCulloch A and Goldie I (2010) Introduction In: I Goldie (Ed) Public Mental Health
Today. Brighton: Pavilion Publishing Ltd.
McGuffin, P., Asherson, P., Owen, M., et al (1994) The strength of the genetic effect.
Is there room for an environmental influence in the aetiology of
schizophrenia? British Journal of Psychiatry, 164, 593 -599.
McLeod, B.D., Weisz, J.R., Wood, J.J., 2007. Examining the association between
parenting and childhood depression: a meta-analysis. Clin. Psychol. Rev. 27, 986–
1003
Miresco MJ, Kirmayer LJ (2006). The persistence of mind–brain dualism in
psychiatric reasoning about clinical scenarios. American Journal of Psychiatry
163, 913–918.
Moncrieff J, Wessely S, Hardy R. Active placebos versus antidepressants for
depression. Cochrane Database Syst Rev 2004, Issue 1
Mojtabai, R., & Olfson, M. (2010). Proportion of antidepressants prescribed without a
psychiatric diagnosis is growing. Health Affiliation, 30 (8), 1434-1442.
Mojtabai R and Olfson M. Health Affairs, 2010. 30(8):1434-1442.
NICE (2008) Attention Deficit Hyperactivity Disorder: Diagnosis and Management of
ADHD in Children, Young People and Adults. NICE Clinical Guideline 72.
London: NICE.
NICE (2009) Antisocial Personality Disorder: Treatment and Management. NICE
Clinical Guideline 78. London: NICE.
NICE (2014) Psychosis: Psychosocial Interventions. NICE Clinical Guideline 51.
London: NICE.
Nierenberg, A.A., et al (2011). A heated debate over how well psychiatric
medications actually work has led some authorities in our field to suggest that
psychiatry is currently experiencing a “crisis of confidence”. Clinical
Psychiatry; 72(1):27–33).
Norman, I. & Peck, E. (1999) Working together in adult community mental health
services: an inter-professional dialogue. Journal of Mental Health, 8(3), 217-
230.
Pleasence, P., Balmer, N., & Hagell, A. (2015). Health Inequality and Access to
Justice: Young People, Mental Health and Legal Issues. Youth Access
Pratt L, Brody DJ, Gu Q. Antidepressant Use in Persons Aged 12 and Over: United

33.
33
States, 2005-2008. NCHS Data Brief. No 76. October 2011.
Pizzi C et al.,Am J Cardiology, 2011 Apr. 107(7):972-979.
Rabkin, J. G. (1972). Opinions about mental illness: A review of the literature.
Psychological Bulletin, 77, 153-171.
Ravindran AV, et al. Complementary and alternative therapies as add-on to
pharmacotherapy for mood and anxiety disorders: A systematic review.
Journal of Affective Disorders. 2013;15:707
Robinson, D. (1998). Wild beasts and idle humours: The insanity defense from
antiquity to the present.
Read, J., & Harré, N. (2001). The role of biological and genetic causal beliefs in
stigmatization of ‘mental patients.’ Journal of Mental Health, 10, 223–235.
Read, J., Haslam, N., Sayce, L., & Davies, E. Prejudice and schizophrenia: a review
of the ‘mental illness is an illness like any other’ approach. Acta Psychiatrica
Scandinavica, 114 (5), 303-318.
Schomerus G, Corrigan PW, Klauer T, Kuwert P, et al. (2011). Self-stigma in alcohol
dependence: consequences for drinking-refusal self-efficacy. Drug and
Alcohol Dependence 114(1):12-7.
Secker, M., Constantine, B., Andel, R., & Boaz. (2010). Gender differences and risk
of arrest among offenders with serious mental illness. Journal of Behavioral
Health Services & Research, 38(1), 16-28.
Slovenko, R. (1995). Psychiatry and criminal responsibility. New York: Wiley.
Steingard, S. A. (2010). A psychiatrist thinks some patients are better off without
antipsychotic drugs. The Washington Post.
Talaei, A., Moghadam, H.M., Tabassi, S.A.S., & Mohajeri, S.A. (2015). Crocin, the
main active saffron constituent, as an adjunctive treatment in Major
Depressive Disorder; A randomized, double-blind, placebo-controlled, pilot
clinical trail. Journal of Affective Disorders, 174, 51-56.
Thornicroft, G., Rose, D., & Mehta, N. (2010). Discrimination against people with
mental illness: What can psychiatrists do? Advances in Psychiatric Treatment,
16, 53–59.
Tyrer P, Steinberg D (2005). Models for Mental Disorder: Conceptual Models in
Psychiatry. Wiley : Chichester.
Williams, Christopher R. "Not Guilty By Reason of Insanity (NGRI)." Encyclopedia
of Murder and Violent Crime. Ed. . Thousand Oaks, CA: SAGE, 2003. 330-

34.
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32. SAGE Reference Online. Web. 6 Aug. 2012.
Appendix 1
Breakdown of all BSc, MSc, PhD, & DClinPsych courses for every University
contacted with a request for staff to complete and circulate the link amongst the
course department.
Nursing
1)
Glasgow
2)
East
Anglia
3)
Kings
College
London
4)
Portsmouth
5)
Nottingham
6)
West
of
England
7)
Swansea
8)
Brighton
9)
Bedfordshire
10)
Salford
11)
Bradford
12)
Cumbria
13)
City
14)
Bolton
15)
Leeds
Beckett
16)
Canterbury
Christ
Church
17)
Worcester
18)
Essex
19)
Surrey
20)
Edinburgh
21)
Cardiff
22)
York
23)
Manchester
Metropolitan
24)
Ulster
25)
De
Monfort
26)
Birmingham
27)
Hull
28)
Chester
29)
Edge
Hill
30)
Stirling
31)
Glasgow
Caledonian
32)
Staffordshire
33)
Glyndwr
34)
Kingston-­‐
St
George’s
35)
Suffolk
36)
Buckinghamshire
New
37)
Birmingham
38)
Sheffield
39)
Southampton
40)
Bangor
41)
Northumbria
42)
Brunel
43)
Huddersfield
44)
Oxford
Brookes
45)
Brunel
46)
Huddersfield
47)
Bournemouth
48)
Northampton
49)
Hertfordshire
50)
Anglia-­‐Ruskin
51)
Lincoln
52)
South
London
Bank
53)
Robert
Gordon
54)
West
London
55)
Edinburgh
Napier
56)
West
of
Scotland
57)
Liverpool
58)
Leeds
59)
Keele
60)
Manchester
61)
Queen
Margaret
62)
South
Wales
63)
Coventry
64)
Queens
Belfast
65)
Teeside
66)
Liverpool
John
Moores
67)
Sheffield
Hallam
68)
Derby
69)
Central
Lancashire
70)
Plymouth
71)
Greenwich
72)
Dundee
73)
Abertay
74)
Middlesex
Social
Work
1)
Lancaster
2)
Birmingham
3)
Glasgow
4)
Stirling
5)
Bath
6)
Strathclyde
7)
Robert
Gordon
8)
Swansea
9)
Queens
Belfast
10)
UWE
Bristol
11)
Nottingham
12)
East
Anglia
13)
Leeds
14)
Sussex
15)
Warwick
16)
York
17)Glasgow
Caledonian
18)
Portsmouth
19)
Teesside
20)
Dundee
21)
Edinburgh
22)
Brunel
23)
Kent
24)
Keele

35.
35
25)
Manchester
Metropolitan
26)
Huddersfield
27)
Middlesex
28)
Lincoln
29)
De
Monfort
30)
Coventry
31)
Ulster
32)
Oxford
Brookes
33)
Hull
34)
Northumbria
35)
Suffolk
36)
Liverpool
Hope
37)
Bournemouth
38)
Salford
39)
Anglia
Ruskin
40)
South
Wales
41)
West
of
London
42)
Central
Lancashire
43)
Bradford
44)
London
South
bank
45)
Southampton
Solent
46)
Cardiff
Metropolitan
47)
Birmingham
City
48)
Liverpool
John
Moores
49)
Goldsmiths
50)
Hertfordshire
51)
Kingston
St
Georges
52)
Winchester
53)
Plymouth
54)
Sunderland
55)
Nottingham
Trent
56)
Sheffield
Hallam
57)
Chester
58)
West
London
59)
East
London
60)
Northampton
61)
Greenwich
62)
Gloucestershire
63)
London
Metropolitan
64)
Derby
65)
Buckinghamshire
New
66)
Bradfordshire
67)
Leeds
Beckett
68)
Staffordshire
69)
Brighton
70)
St
Mark
&
St
John
71)
Chichester
72)
Glyndwr
73)
Trinity
Saint
David
74)
Cumbria
75)
Edge
Hill
76)
Canterbury
Christ
Church
77)
Worcester
Occupational
Therapy
1)
London
South
Bank
2)
York
St
John
3)
Plymouth
4)
Northampton
5)
South
Wales
6)
Derby
7)
Oxford
Brookes
8)
Worcester
9)
Teesside
10)
Brunel
11)
Cardiff
12)
UEA
13)
Glasgow
Caledonian
14)
Ulster
15)
Liverpool
16)
Bournemouth
17)
Salford
18)
Leeds
Beckett
19)
Southampton
20)
Cumbria
21)
Robert
Gordon
22)
Coventry
23)
Huddersfield
24)
Sheffield
Hallam
25)
Northumbria
26)
Essex
27)
Glyndwr
28)
Queen
Margaret
29)
Canterbury
30)
Bradford
31)
Brighton
32)
London
Metropolitan
33)
Liverpool
34)
Bradford
Clinical
Psychology
Doctorate
1)
Bangor
2)
Bath
3)
Birmingham
4)
Warwick
5)
East
Anglia
6)
East
London
7)
Edinburgh
8)
Essex
9)
Exeter
10)
Glasgow
11)
Hertfordshire
12)
KCL
13)
Lancaster
14)
Leeds
15)
Leicester
16)
Liverpool
17)
Manchester
18)
Newcastle
19)
North
Thames
20)
Oxford
21)
Plymouth
22)
Royal
Holloway
23)
Salomon’s
24)
Sheffield
25)
Southampton
26)
South
Wales
27)
Staffordshire
28)
Surrey

36.
36
29)
Teesside
30)
Lincoln
Trent
31)
Nottingham
Trent
Psychology
1)
Cambridge
2)
Bath
3)
Oxford
4)
UCL
5)
Glasgow
6)
Durham
7)
St
Andrews
8)
Birmingham
9)
Bristol
10)
Exeter
11)
Southampton
12)
Cardiff
13)
Surrey
14)
York
15)
Kent
16)
Newcastle
17)
Nottingham
18)
Warwick
19)
Lancaster
20)
Strathclyde
21)
RHUL
22)
Edinburgh
23)
Leeds
24)
Loughborough
25)
Sussex
26)
Aberdeen
27)
Stirling
28)
East
Anglia
29)
Reading
30)
Heriot-­‐Watt
31)
Sheffield
32)
Bangor
33)
Dundee
34)
Swansea
35)
Manchester
36)
Aston
37)
Portsmouth
38)
Leicester
39)
Essex
40)
Lincoln
41)
Liverpool
42)
Queens
Belfast
43)
City
44)
Goldsmiths
45)
Nottingham.
T
46)
Queen
Margaret
47)
Keele
48)
Plymouth
49)
York
St
John
50)
Coventry
51)
Abertay
52)
Hull
53)
Queen
Mary’s
54)
Manchester.
M
55)
West
of
Scot.
56)
Oxford
Brookes
57)
Northumbria
58)
Brunel
59)
Middlesex
60)
De
Montfort
61)
Chester
62)
Roehampton
63)
Bath
Spa
64)
Glyndwr
65)
Central
Lancashire
66)
Teesside
67)
Edge
Hill
68)
Hertfordshire
69)
Westminster
70)
Glasgow
Caledonian
71)
West
London
72)
Bradford
73)
Buckingham
74)
Edinburgh
Napier
75)
Brighton
76)
Bournemouth
77)
Salford
78)
Liverpool
John
Moores
79)
Winchester
80)
Greenwich
81)
Sunderland
82)
Bolton
83)
East
London
84)
Ulster
85)
Huddersfield
86)
Chichester
87)
Derby
88)
Staffordshire
89)
UWE
Bristol
90)
Aberystwyth
91)
Leeds
Trinity
92)
Leeds
Beckett
93)
Liverpool
Hope
94)
Kingston
95)
Anglia
Ruskin
96)
South
Wales
97)
Worcester
98)
Bedfordshire
99)
Canterbury
100)
Birmingham.
C
101)
Wolverhampton
102)
London
South
Bank
103)
Cumbria
104)
London
Metropolitan
105)
Sheffield
Hallam
106)
Bishop
Grosseteste
107)
Southampton
Solent
108)
Newman
109)
St
Mary’s
110)
Gloucester
111)
Cardiff
Metropolitan
112)
Suffolk
113)
Trinity
Saint
David
114)
Buckinghamshire
Psychiatry
1)
School
of
Central
Medicine
2)
Nottingham
3)
KCL
4)
Aberdeen
5)
Essex
6)
Edinburgh
7)
Birmingham
8)
Cardiff
9)
Royal
College
of
Psychiatrists
10)
Liverpool
11)
Leicester
12)
Southampton
13)
Manchester
14)
Oxford
15)
Cambridge

37.
37
Appendix 2
Write-in option for individuals who did not fit into the available options of
Psychiatry, Clinical or Counselling Psychology, Mental Health Nursing, Occupational
Therapy, Social Work, Art Therapies, Non Applicable.
Last choice text input
Early years psychotherapist
Approved Mental Health Professional
Peer Worker Speech & Language Therapy
AMHP Cbt
CBT working towards clinical doctorate
Education Systemic family psychotherapy
CBT Therapist CBT & IPT psychotherapy
Neurology Computer science 4 / 83
Clinical neuropsychology
Psychodynamic Psychotherapeutic Counselling
Counsellor in Secondary care/psychological therapist Educational Psychology
Educational Psychology
RGN Systemic Psychotherapy
CBT Post Grad Dip
mental health nursing and social work
Family Therapy
Counselling
OT
arts therapist,
CAT practitioner
Research Psychology
CBT
School nurse children with disabilities
Educational psychology
Physiotherapist
pharmacist
cognitive analytic therapy
Support services
Physiotherapist
Peer Support
Specialist psychotherapy
social work and arts psychotherapist
psychology and nursing
Nursing and education counsellor
Sport psychology and counselling psychology
Speech & Language Therapy
Cognitive and Behavioural Psychotherapist
mental health officer (Scottish equivalent of AMHP
I have a BA in Psych.
I am getting a MSW and I am a CRSS, WRAP facilitator and trainor and MHFA

38.
38
trainor
Educational psychology
CBT therapist
PhD Certified peer recovery coach
Appendix 3
The demographic questions placed at the beginning of the questionnaire
once the participants had begun.
1. Number of years working in mental health:
2. Do you have a recognised mental health qualification (e.g. in psychiatry,
clinical psychology, mental health nursing)? Please choose one of the options.
Qualified professional (e.g. clinical psychologist, mental health nurse,
occupational therapist, social worker, other qualified therapist)
Currently training for a professional qualification
Working in mental health research/academia, not clinically qualified
Working in mental health care, not clinically qualified (e.g. support worker,
assistant psychologist)
Post-graduate student in area related to mental health (not currently training
for professional qualification)
Undergraduate student in area related to mental health (not currently training
for professional qualification)
3. For qualified professionals and trainees, which profession are you
qualified/training in?
Psychiatry
Clinical or Counselling Psychology
Mental Health Nursing
Occupational Therapy
Social Work
Arts Therapies

39.
39
Not applicable
Other, please describe:
4. Where do you mainly work? Please tick all that apply
In a healthcare setting
In research/academia
Other, please describe:
5. Are you currently engaged in research?
Yes
No
6. What is your country of birth?
7. In which country do you currently reside?

40.
40
Appendix 4
The adapted version of the MAQ questionnaire used in the current
research for data collection.
Professionals' Understanding of Mental Health Problems
Thank you very much for your interest. This study looks at how different groups of people working or studying
in the field of mental health or mental health research understand mental health problems (for example,
depression and anxiety).
While taking this survey, you will be asked to complete a questionnaire which should take no more than 15
minutes of your time. You will be asked for some information regarding your professional and cultural
background, and will be asked some questions about the way you understand certain mental health problems.
Please note: To be consistent with past research, this survey uses standard ICD-10 diagnoses to describe mental
health problems. We recognise that people have differing opinions with regard to the appropriateness of these
terms, but please complete the survey with regard to the problems that these diagnoses describe.
Please attempt to answer each question.
All of your responses are collected anonymously. However, there is an option to leave an email address at the
end of this survey if you would like to be informed about the results of this study. If you choose to do so, this
information will be stored confidentially and in accordance with the Data Protection Act 1998.
This study has been approved by the University College London (UCL) Research Ethics Committee. It is being
conducted by:
Kira Dormann, MSc Student, UCL: kira.dormann.14@ucl.ac.uk
Jasmine Martinez, MSc Student, UCL, jasmine.martinez.14@ucl.ac.uk
Prof Sonia Johnson, UCL: s.johnson@ucl.ac.uk
Dr Vaughan Bell, UCL: vaughan.bell@ucl.ac.uk
Dr Niall Boyce, Editor of the Lancet Psychiatry: n.boyce@elsevier.com

41.
41
Dr Matthew Broome, Oxford University: matthew.broome@psych.ox.ac.uk
Please click 'Start' if you consent to participate in this survey.
1. 1. Number of years working in mental health:
2. Do you have a recognised mental health qualification (e.g. in psychiatry, clinical psychology, mental health
nursing)? Please choose one of the options.
Qualified professional (e.g. clinical psychologist, mental health nurse, occupational therapist, social worker,
other qualified therapist)
Currently training for a professional qualification
Working in mental health research/academia, not clinically qualified
Working in mental health care, not clinically qualified (e.g. support worker, assistant psychologist)
Post-graduate student in area related to mental health (not currently training for professional qualification)
Undergraduate student in area related to mental health (not currently training for professional qualification)
3. For qualified professionals and trainees, which profession are you qualified/training in?
Psychiatry
Clinical or Counselling Psychology
Mental Health Nursing
Occupational Therapy
Social Work
Arts Therapies
Not applicable
Other, please describe:
4. Where do you mainly work? Please tick all that apply
In a healthcare setting
In research/academia
Other, please describe:

42.
42
5. Are you currently engaged in research?
Yes
No
6. What is your country of birth?
7. In which country do you currently reside?
The following questions will explore your understanding of different mental health
problems. There are no right or wrong answers.
Please answer every question.
8. The disorder results from brain dysfunction.
Strongly disagree Disagree Neutral Agree Strongly agree
1 2 3 4 5
Schizophrenia
Major Depression
Antisocial Personality Disorder
9. The disorder arises as a consequence of social circumstances or conditions

43.
43
Strongly disagree Disagree Neutral Agree Strongly agree
1 2 3 4 5
Schizophrenia
Major Depression
Antisocial Personality Disorder
10. The disorder is best approached through the study of abnormal behaviour.
Strongly disagree Disagree Neutral Agree Strongly agree
1 2 3 4 5
Schizophrenia
Major Depression
Antisocial Personality Disorder
11. The research into the disorder should focus on the identification of causative social factors
Strongly disagree Disagree Neutral Agree Strongly agree
1 2 3 4 5
Schizophrenia
Major Depression
Antisocial Personality Disorder
12. The ideal classification of the disorder would be a pathophysiological one.
Strongly disagree Disagree Neutral Agree Strongly agree
1 2 3 4 5
Schizophrenia
Major Depression
Antisocial Personality Disorder
13. The disorder should be treated by challenging and restructuring maladaptive thoughts and
beliefs.

44.
44
Strongly disagree Disagree Neutral Agree Strongly agree
1 2 3 4 5
Schizophrenia
Major Depression
Antisocial Personality Disorder
14. Neglecting the spiritual or moral dimension of life leads to the disorder.
Strongly disagree Disagree Neutral Agree Strongly agree
1 2 3 4 5
Schizophrenia
Major Depression
Antisocial Personality Disorder
15. The appropriate study of the disorder involves discovery of biological markers and the effects of
biological interventions.
Strongly disagree Disagree Neutral Agree Strongly agree
1 2 3 4 5
Schizophrenia
Major Depression
Antisocial Personality Disorder
16. Treatment of the disorder should be based on whatever folk treatments and models are accepted
as appropriate by the patient and their local community.
Strongly disagree Disagree Neutral Agree Strongly agree
1 2 3 4 5
Schizophrenia
Major Depression
Antisocial Personality Disorder

45.
45
17. Studying the associations between antecedents and consequences in patients’ behaviour is the best basis
for modification of the disorder.
Strongly disagree Disagree Neutral Agree Strongly agree
1 2 3 4 5
Schizophrenia
Major Depression
Antisocial Personality Disorder
18. Mental health professionals have no ‘expertise’ of the disorder over and above anyone else.
Strongly disagree Disagree Neutral Agree Strongly agree
1 2 3 4 5
Schizophrenia
Major Depression
Antisocial Personality Disorder
19. The disorder can only be understood in the context of local meanings and these meanings cannot be
extrapolated to universal classifications.
Strongly disagree Disagree Neutral Agree Strongly agree
1 2 3 4 5
Schizophrenia
Major Depression
Antisocial Personality Disorder
20. Social factors such as prejudice, poor housing and unemployment are the main causes of the disorder.
Strongly disagree Disagree Neutral Agree Strongly agree
1 2 3 4 5
Schizophrenia
Major Depression
Antisocial Personality Disorder

46.
46
21. Maladaptive thoughts and beliefs are normally distributed in the population and it is the extreme ends
of this distribution that accounts for the disorder.
Strongly disagree Disagree Neutral Agree Strongly agree
1 2 3 4 5
Schizophrenia
Major Depression
Antisocial Personality Disorder
22. There is no universal classification of disorder, only culturally relative classifications.
Strongly disagree Disagree Neutral Agree Strongly agree
1 2 3 4 5
Schizophrenia
Major Depression
Antisocial Personality Disorder
23. Treatment of the disorder should be directed at underlying biological abnormalities.
Strongly disagree Disagree Neutral Agree Strongly agree
1 2 3 4 5
Schizophrenia
Major Depression
Antisocial Personality Disorder
24. The disorder is due to unconscious factors (as defined psychodynamically).
Strongly disagree Disagree Neutral Agree Strongly agree
1 2 3 4 5
Schizophrenia
Major Depression
Antisocial Personality Disorder

47.
47
25. The behavioural problems in the disorder are best modified by associating new responses to a given
stimulus.
Strongly disagree Disagree Neutral Agree Strongly agree
1 2 3 4 5
Schizophrenia
Major Depression
Antisocial Personality Disorder
26. The study of the disorder should concentrate on understanding cognitive distortions and reasoning
errors.
Strongly disagree Disagree Neutral Agree Strongly agree
1 2 3 4 5
Schizophrenia
Major Depression
Antisocial Personality Disorder
27. Adherence to religious or spiritual practice is the most effective way of treating the disorder.
Strongly disagree Disagree Neutral Agree Strongly agree
1 2 3 4 5
Schizophrenia
Major Depression
Antisocial Personality Disorder
28. The structure of the disordered psyche and its unconscious mechanisms is best understood by a study of
individual cases.
Strongly disagree Disagree Neutral Agree Strongly agree