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by Nicholas West
August 21, 2015
from
ActivistPost Website
Spanish version
Updated research into predictive medicine combined with apps to
achieve "mental health intervention."
Predictive technology is exploding.
The arrival of Big Data
initiatives by government, as well as a massive industry of data
brokers is not only putting privacy at risk, but is offering those
with access to the information unprecedented ways to micromanage our
lives.
Most people now seem resigned to the surveillance of our
communications devices, which have become so intertwined with modern
efficiency, economics and knowledge that there are real tradeoffs
when choosing a fully opt-out lifestyle. Wearable gadgets add a new
layer still, and are being bought into at record pace, thus donating
the information that isn't already being stolen.
However, it might be our health information that is the most
tempting, offering up potentially the most intrusive window yet into
our everyday lives.
In July of last year I covered a development by researchers at Tel
Aviv University with the announcement that a,
"Smartphone App May
Revolutionize Mental Health Treatment."
The following excerpts from the press
release were highlighted as some very stark writing on the wall.
-
There is a dire need for support
services to assist clinicians in the evaluation and
treatment of those suffering from mental illness.
-
A new smartphone-based system
detects changes in patients' behavioral patterns, and then
transmits them to professionals in real time.
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By facilitating patient
observation through smartphones, the technology also affords
patients much-needed independence from hospitals, clinicians
- and even family members.
-
Because most people own
smartphones today, we thought, Why not harness the
smartphone, a reservoir of daily activities, to monitor
behavioral patterns?
"Bipolar disorder, for
example, starts with a manic episode," said Dr. Uri Nevo.
"A patient who usually makes
five or ten calls a day might suddenly start making
dozens of calls a day. How much they talk, text, how
many places they visit, when they go to bed and for how
long - these are all indicators of mental health and
provide important insights to clinicians who want to
catch a disorder before it is full blown."
Source
At the time, researchers noted that the
concept already was well received by "psychiatrists, as well as U.S.
federal policymakers in the field."
Indeed, it has been…
Northwestern University followed Tel Aviv's announcement by
proclaiming that the standard smartphone can accurately detect
general depression with nearly 90% accuracy, merely based on GPS
location data and usage information.
Researchers seemed overjoyed from the
results obtained from just 40 participants, but it is worth noting
what their objective and conclusions state:
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Objective:
The objective of this study was
to explore the detection of daily-life behavioral markers
using mobile phone global positioning systems (GPS) and
usage sensors, and their use in identifying depressive
symptom severity.
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Conclusions:
Features extracted from mobile
phone sensor data, including GPS and phone usage, provided
behavioral markers that were strongly related to depressive
symptom severity. While these findings must be replicated in
a larger study among participants with confirmed clinical
symptoms, they suggest that phone sensors offer numerous
clinical opportunities, including continuous monitoring of
at-risk populations with little patient burden and
interventions that can provide just-in-time outreach.
Source
There are a slew of technical details
provided, but the upshot is that the complex movements, thoughts and
desires of an individual human being are being replaced by an
algorithmic overlay of sensor-feed results that transmit to
centralized professionals who apparently know you better than
yourself or your family and friends.
Is this your
life?
Using terms like "location variance" "clustering" "circadian
movement" and "transition time" is the standard operating procedure
for reductionists and technocrats everywhere whose #1 trait is what
Jon Rappoport has called
OTO - The Obsession to Organize:
OTO speaks of a bottomless fear that
somewhere, someone might be living free.
The presumption of a baseline,
incontestable "normal" level of mental health speaks to the need for
power structures and the medical establishment to seek as many
diagnoses as possible to corral and monetize populations deemed to
be wandering too far off the plantation.
-
Do you like to disconnect from
the virtual matrix for a while?
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Take a
staycation?
-
Do you generally enjoy your home
and family more than social carousing, mall strolling, and
indiscriminate consumerism?
You've been deemed NOT AVERAGE - Red
Flag in Sector 12.
And the political framework has been created. Embedded in the
Patient Protection and Affordable Care Act (aka
Obamacare), it
states quite clearly the value of data obtained from gadgets and
consumer behavior, and portends how government might mandate changes
in the near future.
Health plans, integrated delivery
systems, and other health care organizations (HCOs) increasingly
channel their patients to interventions based in part on what
they deduce from predictive models that have traditionally been
run against databases of administrative claims.
In this arena, the Affordable Care
Act (ACA) [Obamacare] is likely to exert a profound effect.
…a growing number of health care
experts…see predictive modeling as an opportunity to prevent
[disease] complications, control [hospital] readmissions,
generate more precise diagnoses and treatments, predict
risk, and control costs for a more diverse array of
population segments than previously attempted…
New data streams will become
available to providers, payers, and government as EHRs draw from
a broader array of data to create more complete insight into
patients and the care delivery process…
As HCOs gain access to data from
more varied sources, such as health risk assessments, behavioral
assessments, laboratory results, and pharmacy prescriptions
(filled and unfilled), the impact of predictive modeling will
increase.
Source
Finally, if any doubts remain about how
slippery this slope has become, listen to the following statement
from David Mohr - director of the Orwellian Center for Behavioral
Intervention Technologies at Northwestern University Feinberg School
of Medicine:
The significance of this is we can
detect if a person has depressive symptoms and the severity of
those symptoms without asking them any questions…
We now have an objective measure of
behavior related to depression. And we're detecting it
passively. Phones can provide data unobtrusively and with no
effort on the part of the user.
Naturally, following from diagnoses of
depression would be the next step: stopping actual suicides. This is
where the ethical road is probably murkiest, so let's wade through
and see what is being discussed as a solution.
Indiana University is looking to use biomarkers from blood samples
taken from those being treated for biopolar disorder and other
mental "illnesses" who they say are at a maximum risk of committing
suicide, combined with apps.
I've highlighted some sections that have
a familiar echo to what you have read above.
From the Press Release
Researchers at Indiana University School of Medicine reported
Tuesday in the Nature Publishing Group's leading journal in
psychiatry, Molecular Psychiatry, that they have developed blood
tests and questionnaire instruments that can predict with more
than 90 percent accuracy which of those patients will begin
thinking of suicide, or attempt it.
"We believe that widespread
adoption of risk prediction tests based on these findings
during healthcare assessments will enable clinicians to
intervene with lifestyle changes or treatments that can save
lives," said Alexander B. Niculescu III, M.D., Ph.D.,
professor of psychiatry and medical neuroscience at the IU
School of Medicine and attending psychiatrist and research
and development investigator at the Richard L. Roudebush
Veterans Affairs Medical Center.
Using RNA biomarkers from blood
samples along with a newly developed questionnaires in the form
of an app, the researchers were able to predict which
individuals in a group of patients being seen for a variety of
psychiatric illnesses would experience significant suicidal
ideation with approximately 92 percent accuracy.
Among patients with bipolar
disorder, the accuracy reached 98 percent, Dr. Alexander B.
Niculescu said.
The combination of biomarkers and
app was also accurate in predicting which of the patients would
be hospitalized for suicidality in the year following testing
(71 percent across all diagnoses, 94 percent for bipolar
disorder).
The questionnaires by themselves, implemented as apps on
tablets, were able to predict the onset of significant suicidal
thoughts with more than 80 percent accuracy.
The research expands upon work reported by Dr. Niculescu and
colleagues in 2013 in which they identified a panel of
biomarkers that were significantly elevated in bipolar disorder
patients with suicidal thoughts or who were hospitalized as a
result of suicide attempts.
"We now have developed a better
panel of biomarkers that are predictive across several
psychiatric diagnoses. Combined with the apps, we have a
broader spectrum predictor for suicidality," Dr. Niculescu
said.
"In additional to reproducing
and expanding our own previous work, we reproduce and expand
other groups' results in this burgeoning field."
The current study began with a group
of 217 male psychiatric participants, followed by Dr. Niculescu
and colleagues for several years with diagnoses of bipolar
disorder, major depressive disorder, schizoaffective disorder,
and schizophrenia.
The researchers identified 37
participants who switched from no suicidal ideation to high
suicidal ideation at different testing visits.
The scientists were able to identify
RNAs that were present at different levels in blood samples
taken at those different testing visits, in common across these
37 individuals. Those candidate biomarkers were then evaluated
using the Niculescu group's Convergent Functional Genomics
approach, to prioritize the best markers.
Next, working with the Marion County (Indianapolis, Ind.)
Coroner's Office, the researchers validated those prioritized
biomarkers using blood samples from 26 men who had committed
suicide.
Finally, the researchers used blood samples and medical records
from a different group of patients with the same psychiatric
diagnoses to confirm that the biomarkers and apps predicted
suicidal ideation, and also examined their ability to predict
future hospitalizations for suicidality in the first year
following testing.
The app-based questionnaires were developed separately, said Dr.
Niculescu, director of the Laboratory of Neurophenomics at the
Institute of Psychiatric Research at the IU School of Medicine.
One of the apps assesses measures of mood and anxiety; the other
asks questions related to life issues including physical and
mental health, addictions, cultural factors and environmental
stress.
Neither app, he emphasized, asks
whether the individual is thinking of committing suicide.
Dr. Niculescu said he believes the apps are ready to be deployed
and tested by medical professionals, particularly in emergency
department settings. The biomarkers could also be more widely
tested for in the near future he said.
However, he noted two limitations that require additional
research.
-
First, all of the
participants in this study were men.
-
Studies in women are
currently being conducted and are showing promising
preliminary results. In addition, the research was based
on work with people with psychiatric diagnoses.
How well the biomarkers would work
among people who have not been diagnosed with a psychiatric
disease is not known.
Source
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