Here is an excerpt from my book (in preparation), Lavender Rising; An Intersectional History of the Queer Struggle
Psychiatry
Psychiatry
is the
branch of medicine that
is supposed to be concerned
with the study, diagnosis, and treatment of mental illness.
There
is ever-increasing concern in the psychiatric survivor movement as to how
many so-called mental illnesses can be beneficially treated using a
medical model, whether
they can be responsibly diagnosed,
and as to how
many
mental health issues are created by socio-economic and
working environments
rather
than underlying chemical
imbalances or medical
deficiencies.
My
selective history of psychiatry focuses,
in part, on its
the history in London and
Edinburgh, but also on
international material
collated during my twelve or
so years campaigning against
problematic twenty-first
century psychiatry
(beginning around the end of
2011). The
seminal work
on depressive disorders by Professor Joanne Moncrieff at UCL has
relatively recently
epitomised the urgent
need for, albeit belated,
change
to,
or replacement of,
the entire discipline of
psychiatry. See
Moncrieff (2022).
Knapton
(2023) reports
that anti-depressants raise
the risk of suicide while also giving people the means to kill
themselves. Psychologists at the University of East London, lead by
the pioneering Professor John Read, analysed
media reports of nearly 8000 coroners’ inquests in England and
Wales between 2003 and 2020 in which antidepressants were mentioned.
They found that the drugs [doubtlessly including the already notorious imapramine, Prozac, and Seroxat]were linked to 2718 cases of hanging and
2329 overdoses, of which 933 people had overdosed on the
antidepressants themselves. A further 2083 had been struck by a
train, tube, lorry or other vehicle, had jumped or fallen to their
death, drowned, shot themselves , or been involved in a fire or
electrocution. Experts said that the figures were likely to be just
the tip of the iceberg, because many suicides and inquests are not
fully reported in the media,
Psychiatry
has frequently been used to damage
native populations. For example,
Dr. Selwyn Leeks
used
electric shocks without
anaesthetic from an ECT
machine to torture over 300 children between 1972 and 1977 in
the Lake Alice psychiatric hospital in New Zealand (Smale,
2022, Ellingham,2022).
Most of the tortured
children had been sent to
Lake Alice from state-run
welfare homes and around half
were Maori boys.
The
children received electric shocks or
were injected with
paralysing drugs (e.g.
paraldehyde)
as punishments and many
were sexually or
psychologically abused.
The Crown and the
psychiatric profession reportedly
protected Leeks and he was never held to account for his heinous
sadism. He
lived for another 45 years while
his surviving victims
suffered from their horrific
childhood experiences.
Psychiatry
has been
used to damage or destroy
many queer
people’s lives
e.g by
imposing
courses of aversion
therapy for ‘sexual
perversions’ (Davison,
2020).
Even when a
psychiatric maltreatment
damages people regardless of
their gender
or
orientation, it injures a
disproportionately large number of queer folk, simply because queers
are more likely to have mental health issues.
For
Martin Harrow’s empirical investigations that help
to invalidate the cruel
treatment or non-treatment
of schizophrenia by
anti-psychotics, see Whitaker (2023). The
‘optimal’ dynamic treatment regimes proposed by Shortreed
and Moodie (2012), where
patients are switched from one harmful medication to another, are
absolutely
disgusting, because of the
miscellaneous collection of debilitating side effects (including
tardive dyskinesia and neuroleptic malignant syndrome) that the
patients could and often do suffer.
Mystification
I
will, for example, refer to this terminology in section 2.2 when I
discuss transphobic people. Rather than using Karl Marx’s
definition, I refer to
Definition
Epseilon:
The
practice and experience of ‘mystification’ is
a process by which a person
or
group of people
A
exert
or
exerts
significant influence over another person
B,
functionally
changing
B’
s
sense of identity, understanding and experience of emotional and
cognitive states, and sense of reality, in order to serve A’
s purposes.
As
a simple example, A and B
could be lovers, where A influences B into believing that B
is
a ‘top’, when in reality neither
of them are tops. As
a more disconcerting
example, psychiatrists A
frequently inappropriately influence and
mystify their patients B into
thinking that their mistreatments are actually beneficial.
Subjective
Probability Assessments
As
an interdisciplinary
Bayesian statistician,
I refer to my philosophy:
Most
statistics are potentially misleading, but some can
be useful for making
qualitative assessments.
To
give three examples:
(A)
It is very difficult to use a census to count the number of
individuals in a population, since undercounts can be quite sizeable
and related, in particular, to social deprivation. Furthermore, the
population may itself be undefined or time varying, e.g. because of
migration, birth or death.
(B)
Kinsey’s
1948 ‘estimate’ or
‘guess-timate’
that 10% of
the American male population were
at
that
time
gay
is
at best a ball-park figure owing to (a) lack of replicated
randomisation at the experimental design stage (b) lack of a
precise definition of gayness, and (c) the quite reasonable
propensity of gay men
to be
economical with the truth when
posed with the question,
owing to well-grounded
fears
of
possible repercussions.
(C)
Subjective
assertions
of
the type
LBG
people are twice
as likely to have a
mental health problem than non-LQBTQI+
people
or
TQI+
people are four times more likely to have a mental health problem
than non-LGBTQI+ people
cannot
be precisely
validated
in
numerical terms for
a host of the
same sorts of reasons.
They
can
nevertheless
provide us, in qualitative terms,
with
useful working hypotheses.
[I
am idealising the situation for the sake of simplicity.
In
practice, I would try to
make separate
assessments
for T, Q, I and the
different types of
‘+’ people].
Suppose
that
25%
of the
population
of
Freedonia
have
mental
health problems,
and
that 8%
of the entire
population
are LGB and a
further
5% are TQI+.
Then,
assuming
the truth of the two propositions in (C)
we could
base various
calculations on either
Venn
diagram
logic
or
on
Bayes
Theorem and the Law of Total Probability. See
Mathsfun [1] and
pp76-77 of Leonard and Hsu (1999)
Under
the assumptions stated, my
calculations indicate
that among
members
of the population
with mental health problems:
13.01%
are LGB
16.26%
are TQI+
70.73%
are not LGBTQI+
Suppose
that the head psychiatrist Dolly in Holy
Name Hospital
decides
that all people with mental health problems in
Freedonia
should be prescribed
with
the
potentially harmful treatment Hard
Hit,
regardless
of their gender or
orientation, for
the primary
purpose of keeping
them quiet.
Possible
choices
of Hard
Hit
include (a)
brain-damaging
Electro-Convulsive
Therapy (ECT)
or
(b)
a
neuroleptic
medication with devastating physical side effects e.g.
quetiapine
(Seroquel).
Under
the assumptions stated,
Dolly is implicitly discriminating
against TQI+ people, since their percentage
(16.26%)
among people with mental health problems is substantially greater
than their percentage (5%)
in the general population.
Now
assume
instead
that Dolly is an
evil
god-like
eugenicist, and arranges to prescribe Hard
Hit for
90%
of the LGB
patients, for 99%
of the
TQI+ patients, but
for only 10% of the non
LGBTQI+
patients.
Then
of the
patients
prescribed with Hard
Hit,
32.72%
will
be
LGB
47.51%
will
be
TQI+
19.77%
will
be
‘not LGBTQI+
Dolly’s
prescriptions would clearly amount to cruel discrimination against
LGBTQI+ people.
Such
qualitative assessments can
be useful
in many of the situations described in this
intersectional book.
Examples
involving conditional
percentages and
subjective
probabilities
are
included
at
the end of the research exercises at
the
end of
each
chapter. Further
exercises link to
the
statistical analyses of data sets. The
data
provide useful
fodder for budding
statisticians.
See
Zellner (2019) for
a history of the International Society for Bayesian Analysis (ISBA),
and
Leonard (2014)
for
a
history of Bayesian Statistics
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