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Technology & Psychopathology Lab


Mission: To ignite large-scale reductions in mental illness by harmonizing advances in technology with advances in psychology

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Technology & Psychopathology Lab


Mission: To ignite large-scale reductions in mental illness by harmonizing advances in technology with advances in psychology

Over the past several decades:

Rates of suicide and suicidal behaviors have not declined

Rates of most major mental illnesses have not declined

Technology has become exponentially more powerful and pervasive


Our work aims to provide new insights into psychopathology (especially suicidal behaviors) and to leverage technology to transform these insights into major declines in mental illness

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Meta-Analyses


Meta-Analyses of Risk Factors for Self-Injurious Thoughts and Behaviors (1965-Present)

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Meta-Analyses


Meta-Analyses of Risk Factors for Self-Injurious Thoughts and Behaviors (1965-Present)

it's hard to advance knowledge if you don't know what's known

Our first step is to try to figure out what science currently knows about our phenomena of interest. Meta-analyses are a great way to summarize and understand current knowledge. We have an ongoing project that collects all information on risk factors (i.e., longitudinal predictors) for our primary interest -- self-injurious thoughts and behaviors (SITBs). This project has produced many surprising and sobering findings. As we publish papers from this project, we will include detailed information about specific findings (all pictures below represent submitted papers and will become active links once published).

For now, we note three overarching findings from this project:

  • Science's ability to predict SITBs is only slightly better than chance
  • Science's ability to predict SITBs has not improved across 50 years of research and several hundred papers
  • Researchers have essentially conducted the same studies over and over again for the last several decades

 

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Experimental Work


Laboratory-Based Work on the Mechanisms that Drive Self-Injurious Behaviors

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Experimental Work


Laboratory-Based Work on the Mechanisms that Drive Self-Injurious Behaviors

Testing new ideas about how self-injurious thoughts and behaviors work

A major takeaway from our meta-analytic work is that science currently knows little about how self-injurious thoughts and behaviors (SITBs) work. We've accordingly done away with old assumptions and have conducted several projects aimed at testing new ideas about SITBs. Several projects are ongoing, but below we describe and provide links to our published/completed work on these topics (click on each picture for more information).

SITB Benefits & Barriers

Most of our early published work in this area centered on questions like "Why do so many people engage in behaviors like self-cutting?" One major answer to this turned out to be something that we call Pain Offset Relief -- a natural physiological mechanism that makes everyone feel good after the removal (or offset) of pain. Given that such benefits seemed universal, we've more recently been asking questions like, "What keeps the rest of us from engaging in behaviors like self-cutting?" The answer to this seems to be that there are many important barriers that prevent most people from accessing pain offset relief in this way. These barriers include things like pain itself (vs. offset), the natural aversion to mutilation/blood/death images, and social norms. Our work shows that people who engage in SITBs overcome these barriers.

Eroding and re-building SITB Barriers

Once key factors involved in SITBs have been identified, it is crucial to figure how these factors work. Our recent work in this area has focused on determining how the SITB barriers become eroded for some people and how to best re-build these barriers. This knowledge can give us insight into who is at risk for future SITBs, how SITBs develop, and how to best treat and prevent SITBs. So far, much of our work on this topic has centered on figuring out why some people who engage in SITBs enjoy stimuli related to mutilation, injury, and death, and determining how to best change this. Once this work is published, the picture above will become an active link describing this work in detail.

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Prediction


Short-Term Prediction of Self-Injurious Thoughts and Behaviors

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Prediction


Short-Term Prediction of Self-Injurious Thoughts and Behaviors

Improving prediction with novel methods and strategies

As our meta-analytic work has shown, science can only predict self-injurious thoughts and behaviors slightly better than random guessing. We believe that a few fundamental changes in study methods and strategies will dramatically improve predictive accuracy. Specifically, our projects aim to predict over extremely short intervals, measure dynamic shifts in risk factors, and combine large numbers of risk factors with machine learning algorithms. We have just completed one set of projects relevant these aims, and we have just begun another exciting set of projects involving Twitter. Once this work is published (multiple papers currently under review), the pictures below will become active links describing results in detail.

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Mobile Treatment Apps


Our Game-Like Mobile Treatment Apps for Self-Injury, Suicidal Behaviors, and Other Phenomena

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Mobile Treatment Apps


Our Game-Like Mobile Treatment Apps for Self-Injury, Suicidal Behaviors, and Other Phenomena

Novel treatments designed to reach all in need

Few treatments are effective at reducing self-injurious thoughts and behaviors (SITBs) and most existing treatments can only reach a very small proportion of people in need. Recently, there have been many attempts to retrofit old treatments into new technologies, but much therapeutic power is lost in these technological translations and once again, even in their ideal in-person formats, most treatments are not very effective at reducing SITBs.

Our approach is different. We aim to combine basic psychological science, the newest information about how SITBs work, and the latest technologies to grow completely new forms of treatment. Our ultimate goals are to create treatments that are (a) far more powerful than in-person treatments and (b) freely available to everyone with internet access. As described in greater detail via the image links below, we have taken the initial steps toward these goals. Three randomized control trials have now shown that one of our first mobile treatment apps - therapeutic evaluative conditioning (TEC) - powerfully reduces SITBs. Much of our ongoing work is aimed at improving TEC, expanding TEC to non-SITB issues, and creating totally new mobile treatment apps.

Our initial work on TEC for nonsuicidal and suicidal self-injury were recently published (click on pictures below); once our additional TEC work is published, other links will be activated. 

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People


Who are we?

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People


Who are we?

our team

Our team started at Florida State University in August of 2016. Members include Dr. Joseph C. Franklin (Lab Director), and Irene Huang and Katherine Musacchio  (Graduate Students). In addition, we have many invaluable collaborators and volunteers. Please click on the image links below for more information about lab members and collaborators.