Not Sure If You Are Depressed? Just Ask Your Smartphone


By Nicholas West

Predictive technology is exploding across the virtual landscape. 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. 
  • 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. 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.” 

Full press release available HERE

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 is now proclaiming that the standard smartphone can accurately detect general depression with nearly 90% accuracy, merely based on GPS location data and usage information. Researchers seem preliminarily overjoyed from the results obtained from just 40 participants, but it is worth noting what their objective and conclusions state:

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.

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. (emphasis added)

Source and full release HERE

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.

Did you know that the average smartphone user time for a depressed person is 68 minutes? Did you know that 17 minutes makes you normal?

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? 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. (emphasis added)

Source: “More Data in Health Care Will Enable Predictive Modeling Advances.” Managed Care

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.

What a dream – effortless transmission of what makes you tick … all you have to do is wait for the Intervention Team to arrive.

Hat Tip: Zen Gardner

Nicholas West writes for Activist Post and TechSwarm

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3 Comments on "Not Sure If You Are Depressed? Just Ask Your Smartphone"

  1. who’s zooming who ???

    from WAAAAAY back in the day (c. 2011) psychology today no less – LOL for crying out loud!!!

    another great example of TECHNOCRACY RISING, Nick. depressing post – will share far and wide – thanks for posting


    “One of the oldest metaphors for human interaction with technology is the relationship of master and slave. Aristotle imagined that technology could replace slavery if devices like the loom became automated. In the 19th century, Oscar Wilde foresaw a future when machines performed all dull and unpleasant labor, freeing humanity to amuse itself by “making beautiful things,” or simply “contemplating the world with admiration and delight.” Marx and Engels saw things differently. “Masses of laborers are daily and hourly enslaved by the machine,” they wrote in the Communist Manifesto. Machines had not saved us from slavery; they had become a means of enslavement……….”

  3. Normal?

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