Tag: Charity / nonprofit

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Digital Reassurance Seeking in OCD

– by Jordan Karr, PhD

We all need reassurance once in a while. Receiving reassurance from a friend, loved one, or expert can reduce short-term distress, foster a sense of connection, and help us move forward in a productive way. On the other hand, excessive reassurance seeking can lead to a painful cycle of stress and doubt. For individuals with obsessive-compulsive disorder (OCD), reassurance is fleeting and is quickly followed by a resurgence of perceived threat and a compelling drive to seek additional reassurance.

As an OCD and anxiety specialist, I am no stranger to reassurance traps. I see them in the patient who repeatedly consults doctors but never fully trusts their answers; the partner who keeps asking, “Do you still love me?” while scrutinizing every response; and the teenager who needs her homework checked repeatedly but does not learn to tolerate uncertainty. While the content of excessive reassurance seeking may vary, its function remains the same, relieving anxiety momentarily while allowing obsessions to rebound more strongly in the long run. In each example, we see an individual desperately trying to protect something they hold dear while being misled by one of OCD’s most convincing lines: “What if this time the reassurance sticks?”

Psychologists have long argued that excessive reassurance seeking helps maintain OCD, anxiety, and depression (Abramowitz et al., 2002; Burns et al., 2006). What is new is the landscape. Today, reassurance is available instantly and endlessly through search engines, medical websites, social media, and artificial intelligence tools. Emerging research suggests that online reassurance seeking may be as prevalent as interpersonal reassurance seeking (Parsons & Alden, 2022). These digital reassurance traps present in a variety of forms, including:

  • Excessive symptom-checking on WebMD
  • Checking a loved one’s location on Find My Friends to make sure they are still alive or where they promised they would be
  • Asking Google Gemini whether an intrusive thought makes you a monster, a pedophile, or a bad Christian, Muslim, or Jew
  • Analyzing the contents of a partner’s Instagram to see whether their feelings have changed
  • Endlessly searching Reddit for answers to existential questions
  • Obsessively checking likes and read receipts to monitor the durability of a relationship
  • Finding creative ways to ask ChatGPT whether you might be responsible for spreading a virus or causing someone harm
  • Compulsively checking the news to confirm whether a feared event has taken place

Why do some individuals seek reassurance primarily from others in face-to-face contexts while others turn to the internet? Findings from one study suggest that individuals may be more likely to seek interpersonal reassurance when they desire emotional support, whereas online reassurance seeking is more likely when individuals feel ashamed or fear judgment from others (Parsons et al., 2025). In the same study, shame was reported more frequently among individuals with OCD. The perceived anonymity of the internet creates a compelling environment for seeking reassurance about our most distressing fears and the fears we feel ashamed to have.

Wait, hold on… shouldn’t having access to all the information on the internet be empowering? After all, there’s that famous saying, “Knowledge is Power.” Well I’m not sure what Francis Bacon would say if he could scroll on TikTok, but in the age of the internet, more information does not always mean more power or knowledge. In fact, information overload seems to trigger excessive reassurance seeking online (Yang & Luo, 2024). Once digital algorithms detect health-related concerns, users may be exposed to increasingly frequent and targeted content, further amplifying health anxiety and driving additional reassurance seeking online (Zhang et al., 2024).

Despite these challenges, evidence-based treatments offer hope. Exposure and response prevention (ERP), the gold-standard treatment for OCD, helps individuals tolerate uncertainty and break free from compulsive behaviors. ERP therapists are prepared to respond to clients who compulsively seek reassurance while taking care to avoid reinforcing a client’s anxiety and setting boundaries when appropriate. On the other hand, AI chatbots are available 24/7 and will continue to reassure users when it would be clear to a skilled therapist that more reassurance is harmful. Some helpful activities I have encouraged clients to try include:

  • Going for a walk and leaving your phone behind
  • When you have the urge to seek reassurance, use a timer to delay. Start with 5 minutes and gradually increase the time as you go.
  • Imaginal exposure: Writing out OCD’s worst case scenario while refraining from seeking reassurance.
  • Embracing the uncertainty: When you have the urge to seek reassurance, lean into the uncertainty by responding “maybe that will happen, maybe not.”
  • Watch a movie that triggers obsessions but leave your phone in the other room
  • Try a fast from social media. Start with a short fast and increase the length of each fast as you gain confidence.
  • Agreeing with the obsessions: Whatever your OCD throws at you, respond by saying “Sure, that is true!”

Clinicians working with youth should also attend to parental accommodations that inadvertently facilitate online reassurance seeking. Supportive Parenting for Anxious Childhood Emotions (SPACE) is an evidence-based, parent-focused intervention that emphasizes increasing supportive statements while reducing unhelpful accommodations. Setting reasonable limits on smartphone use while responding with empathy and confidence can help youth build resilience and independence (i.e. “I know it’s tough to be away from your phone and I know you got this!”).

Finally, because shame plays a central role in digital reassurance traps, incorporating self-compassion practices may be beneficial. Compassion-focused exercises help individuals respond to their struggles with kindness rather than self-criticism, complementing ERP by fostering emotional resilience. I sometimes ask clients to imagine that a close friend or loved one is feeling ashamed because they are experiencing obsessions and are stuck in an OCD loop. Then, I invite them to write down how they would support this friend while paying special attention to how compassion feels in their body. By practicing compassion for others, we strengthen the same muscles in our brains that help us turn compassion inward.

If you are getting stuck in digital reassurance traps, you are not alone! Many of these technologies are brand new and we are learning how to integrate them into our lives in a healthy way. If you need help managing compulsive online habits, finding a therapist trained in ERP could be a useful step!

References

Abramowitz, J. S., Schwartz, S. A., & Whiteside, S. P. (2002). A contemporary conceptual model of hypochondriasis. Mayo Clinic Proceedings, 77(12), 1323–1330. https://doi.org/10.4065/77.12.1323

Burns, A. B., Brown, J. S., Plant, E. A., Sachs-Ericsson, N., & Joiner, T. E., Jr. (2006). On the specific depressotypic nature of excessive reassurance-seeking. Personality and Individual Differences, 40(1), 135–145. https://doi.org/10.1016/j.paid.2005.05.019

Parsons, C. A., & Alden, L. E. (2022). Online reassurance-seeking and relationships with obsessive-compulsive symptoms, shame, and fear of self. Journal of Obsessive-Compulsive and Related Disorders, 33, 100714. https://doi.org/10.1016/j.jocrd.2022.100714

Parsons, C. A., Kim, H. J., Singh, S., Lkhagva, T., Wang, J., & Alden, L. E. (2025). Covert or connected: Motivations for online and interpersonal reassurance-seeking in OCD. Journal of Anxiety Disorders, 115, 103057. https://doi.org/10.1016/j.janxdis.2025.103057

Yang, X., & Luo, X. (2024). Unpacking cyberchondria: The roles of online health information seeking, health information overload, and health misperceptions. Telematics and Informatics, 97, 102225.

Zhang, X., Zheng, H., Zeng, Y., Zou, J., & Zhao, L. (2024). Exploring how health-related advertising interference contributes to the development of cyberchondria: A stressor–strain–outcome approach. BMC Public Health, 24, 534.

Jordan Karr, PhD, is the owner of River Falls Therapy in Portland, OR. He is a licensed psychologist in Oregon and Virginia, and specializes in evidence-based therapies for OCD and anxiety disorders. Dr. Karr has experience working in outpatient, community-based, and school-based settings.

The post Digital Reassurance Seeking in OCD appeared first on International OCD Foundation.

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Revvity Creates Program to Equip Young Biotechs with Scalable Informatics Capabilities Sooner than Later

Revvity reports that its Signals Software business is launching Signals for Startups, a new program designed to help emerging biotech companies adopt scalable informatics capabilities earlier in their growth journey.

Built for early-stage biotechs, the program combines access to Signals software with guided onboarding and best-practice configurations for smaller biotechs to help accelerate innovation, improve scientific productivity and shorten time-to-value, according to a company spokesperson.

Startup biotechs are often under pressure to move quickly with limited IT, informatics, and operational resources while managing increasingly complex discovery data. Signals for Startups addresses this challenge with a purpose-built, scalable Signals environment that helps teams focus on science while establishing a strong digital foundation from day one, explains Kevin Willoe, president of Revvity Signals Software, adding that out-of-the-box configurations for large and small molecules enable companies to accelerate adoption, standardize data, and enhance collaboration on a proven, scalable informatics infrastructure.

“Signals for Startups addresses a critical need for emerging biotech companies that want to move fast without creating data and workflow challenges that limit their ability to scale,” he continues. “By combining startup-friendly access with guided onboarding and scalable Signals workflows, we are helping early-stage teams build the digital foundation they need to advance discovery, support investor readiness and grow with confidence.”

Signals for Startups is expected to be available in the U.S., Europe, the Middle East, and Africa later this month.

 

The post Revvity Creates Program to Equip Young Biotechs with Scalable Informatics Capabilities Sooner than Later appeared first on GEN – Genetic Engineering and Biotechnology News.

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STAT+: Bristol Myers Squibb becomes latest company to claim it’s building pharma’s largest NVIDIA AI supercomputer

It’s officially a trend. For the third time in nine months, a pharma company has announced that it is assembling the largest AI supercomputer in the life sciences industry. This time, it is Bristol Myers Squibb. 

When the company began its partnership with NVIDIA three years ago with a smaller computing cluster, it was focusing on simpler problems with individual AI tools, like protein structure prediction. But “we actually consumed all the space we had,” said Greg Meyers, chief digital & technology officer at BMS.

Adding extra computing power is necessary for the company now that it’s “become more convinced” that computationally hungry foundation models can give the company valuable insight into how its drug candidates interact with both the body and with disease, Meyers said in an interview with STAT. He mentioned oncology and neurodegeneration as examples of areas where BMS has developed such models.

Continue to STAT+ to read the full story…

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Transition Care for FEP

Conditions: Schizoaffective Disorders; Bipolar Disorder With Psychotic Features; Schizophrenia Disorders; Major Depressive Disorder With Psychotic Features; Psychosis NOS

Interventions: Behavioral: Transition Care Team

Sponsors: University of Chicago; Sidney R. Baer, Jr. Foundation

Recruiting
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Circuit logic of oxytocin and vasopressin complementary actions

Oxytocin (OT) and vasopressin (VP) are evolutionarily conserved neuropeptides that regulate social behavior, emotional processing and physiological homeostasis. Although traditionally studied as individual modulators of affiliation, stress and autonomic function, emerging evidence indicates that their actions are best understood at the level of neural circuits. Advances in optogenetics, cell-type-specific electrophysiology and systems neuroscience have revealed that OT and VP act within distributed networks through receptor-defined microcircuits composed of excitatory and inhibitory neuronal populations, astrocytes and long-range projections. Within these circuits, OT and VP can exert complementary, synergistic or opposing effects depending on receptor localization, cellular identity and network state. Here, we synthesize recent circuit-level and electrophysiological evidence to propose a framework in which OT and VP operate as a coordinated neuromodulatory axis. We argue that the functional consequences of OT/VP signaling emerge not from peptide identity alone, but from their engagement of recurrent circuit motifs that redistribute excitation and inhibition across neural networks. These motifs provide a mechanistic substrate for regulating transitions between competing behavioral and physiological states, including social safety vs. threat, affiliation vs. avoidance, and parasympathetic vs. sympathetic dominance. We further discuss how disruption of receptor topology, synaptic integration and circuit architecture may contribute to neurodevelopmental, psychiatric and stress-related disorders. By shifting the focus from peptide-centric models to circuit-level mechanisms, this framework reconciles seemingly contradictory findings across brain regions and behavioral paradigms, and provides a foundation for the development of next-generation circuit-based therapeutic strategies targeting the oxytocin-vasopressin axis.
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The risk of weather data sabotage is rising

Every morning, airline dispatchers, grid operators, and farmers around the world make decisions based on the same thing: a weather forecast.

While these forecasts are something that most people glance at for two seconds, weather predictions influence major strategic decisions in many industries, with real money, livelihoods, and even actual lives at stake. Farmers use them to determine which crop variety to sow, when to fertilize, how much to invest in irrigation infrastructure, and how long livestock should graze. Utilities use them to decide where to build solar and wind farms, as well as how to price wholesale electricity. Predictions are used to warn people about extreme weather and to trigger emergency response measures. More recently, weather predictions have become relevant for an emerging industry: prediction markets, where people bet money on all kinds of real-world events, including the weather.

However, the temptation to manipulate weather data to get an edge in these markets, combined with a collective move toward data-driven AI weather forecasting, is starting to put the accuracy of weather predictions at risk. These risks are relatively manageable for now, but as experts in the field, we can foresee scenarios where they snowball into far bigger, more systemic problems. 

To develop weather predictions, we need accurate observations of current conditions. These are collected from several sources, including weather stations at airports, utilities, or transport services. Traditional operational systems like the Weather Research and Forecasting model or the European Centre for Medium-Range Weather Forecast (ECMWF) Integrated Forecasting System combine these observations with numerical approximations in order to estimate future weather patterns. 

Sometimes, weather stations have issues because of, for example, instrument failures or upgrades in equipment. These can be caught either in real time (through checking and correction) or retroactively. Traditional forecasting systems also have a built-in safeguard called data assimilation: Every incoming measurement is weighed against what the physical model says should be happening and against readings from nearby stations.

Together, these mechanisms help keep weather observations reliable and predictions robust. However, new threats are putting observational accuracy at risk. Earlier this year, news outlets reported that the weather station at Paris Charles de Gaulle Airport (CDG) had been manipulated to record suspicious temperature spikes on April 6 and April 15, 2026. Authorities speculate that a hand-held hairdryer or lighter might have come into play. Either way, it led to some big payouts for online prediction-market gamblers who had bet it would hit 22 °C (71.6 °F) on days when the actual average was around 18°C (64.4°F). One individual won $20,000.  

Fortunately, tampering with a single station like this can usually be caught by human monitoring or current statistical methods. In this case, members of a French climate nonprofit association noticed the anomalies by chance and raised the alarm.

But what if there are no human monitoring systems in place? And what about other types of manipulation? What if, instead of tampering with one station, someone remotely nudged the readings at many stations at once—making each change small enough to look plausible on its own? Existing quality controls struggle to catch this kind of coordinated manipulation. And time works against us; careful checks of data and metadata take hours or days, but forecasts have to go out on schedule, whatever the weather is doing.

The shift toward artificial intelligence in weather prediction raises the stakes. These methods are even more dependent on accurate, reliable weather observations; in fact, they are known as “data-driven models.” For example, researchers at ECMWF are exploring whether high-quality weather forecasts can be produced directly from raw observations, skipping the assimilation step that currently acts as a quality filter. Other researchers are going one step further; combining geospatial data (including weather station data) with large language models and agentic AI to support real-time, autonomous decision-making during extreme events such as storms. 

Possible benefits are improvements in accuracy, efficiency, and speed. But removing humans from the equation introduces a vast range of new risks.

At the low end of the risk scale, an individual speculator manipulates a weather station for personal gain—that is the CDG Airport case. One step up: A group of traders could coordinate to bias forecasts of renewable energy output, moving wholesale electricity prices and leaving whoever is on the other side of the trade holding the loss. And at the far end, a state actor or saboteur could manipulate one or many stations to set off an early warning system or even keep one silent when it should sound. Step by step, the risk grows, from fraud to compromised disaster preparedness to a matter of national security.  

As long as there are financial (or other) incentives to manipulate observational data, adversaries will search for new opportunities, and it is our task to stay one step ahead. Here are three ways.

1. Watch the stations. Data quality controls should include station security, anomaly detection and correction, and human oversight. Weather stations should be monitored continuously to deter tampering. Data homogenization methods that clean up weather records also need to get faster, with the goal of catching problems in real time. This will become increasingly important as agentic AI systems use these data to deliver real-time decisions. Finally, human oversight is needed to flag questionable data and model outcomes. After all, it was humans who caught the CDG Airport manipulation.

2. Protect the data to safeguard the AI. Data defense mechanisms must be positioned throughout the AI pipeline. AI explainability and adversarial robustness tools can help us understand the underlying data and the AI model outputs, help us identify data- or model-related issues, and potentially  make us more resilient to adversarial attacks. 

3. Ensure continuous accountability along the chain. Observational data passes through many hands: the operators who run the stations, the national weather services that steward the records, and the forecasting centers that turn them into predictions. No single one of them can protect data integrity alone—each guards its own link, and any anomaly needs to be communicated along the whole chain, from station operators to the people acting on the forecast.

It is fortunate that the situation at CDG Airport was caught, but it should serve as a wake-up call. As the role of observational data grows in weather forecasting, we need to adapt to evolving threats. This means protecting our data and models by strengthening existing oversight and accountability structures, and improving coordination among key partners.

This op-ed was written by:

  • Monique Kuglitsch — Innovation Manager at Fraunhofer Heinrich Hertz Institute and Chair of the UN Global Initiative on Resilience to Natural Hazards through AI Solutions
  • Jesper Dramsch — Scientist for Machine Learning at the European Centre for Medium-Range Weather Forecasts (ECMWF), where they work on AIFS (Artificial Intelligence Forecasting System), ECMWF’s data-driven weather prediction model
  • Franz G. Kuglitsch — Climate Scientist and Executive Secretary of the International Union of Geodesy and Geophysics (IUGG) at the GFZ Helmholtz Centre for Geosciences in Potsdam
  • Andrea Toreti — Senior Scientist at the European Commission’s Joint Research Centre (JRC), where he coordinates the European and Global Drought Observatory under the Copernicus Emergency Management Service
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Comparing Two Moral Injury Treatments

Conditions: Moral Injury

Interventions: Behavioral: Acceptance and Commitment Therapy for Moral Injury (ACT-MI); Behavioral: Present Centered Therapy for Moral Injury (PCT-MI)

Sponsors: VA Eastern Colorado Health Care System; Denver Research Institute; Northern California Institute of Research and Education; Henry M. Jackson Foundation for the Advancement of Military Medicine; Palo Alto Veterans Institute for Research

Not yet recruiting
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HelloType1 Digital Education Platform for Individuals With Type 1 Diabetes in Southeast Asia: Data Analytics Study

Background: Type 1 diabetes remains an underrecognized and challenging condition across Southeast Asia, where many countries face limited health care infrastructure, shortages of trained health care professionals, inconsistent access to diabetes education, and a lack of culturally appropriate resources in local languages. These barriers contribute to delayed diagnosis, suboptimal self-management, high rates of diabetic ketoacidosis, and inequities in care. During the COVID-19 pandemic, Action4Diabetes, a nonprofit organization working with local health care professionals and diabetes associations across Southeast Asia, developed HelloType1, a multilingual digital educational platform designed to improve awareness, education, and access to credible type 1 diabetes information. The platform was launched sequentially in Cambodia in 2021, Vietnam and Thailand in 2022, and Malaysia in 2023 through formal memorandums of understanding with local partners. Objective: This study aimed to evaluate the reach, platform usage, and online engagement of the HelloType1 digital educational platform across Southeast Asia between 2021 and 2024. Methods: Website analytics from Google Analytics 4 and Meta Business Suite metrics were descriptively analyzed to assess digital reach and engagement across countries. Metrics were compared over time and by country to examine patterns of platform uptake and user engagement. Results: HelloType1 demonstrated substantial growth between 2021 and 2024. Total unique website users increased from 1178 in 2021 to 40,361 in 2024, representing a marked expansion in regional reach. Pageviews rose from 4644 in 2021 to 83,689 in 2024, suggesting increasing content use and user platform engagement. By 2024, most website visits originated from organic search engines. Platform use was predominantly mobile-based, particularly in Vietnam, Thailand, and Malaysia, with the strongest engagement among adults aged 25 to 54 years. Facebook followers increased from 940 to 4553, and average engagement rates rose between 2022 and 2024. Cambodia achieved the highest number of Facebook interactions, whereas Thailand demonstrated the highest engagement rate. Content-level analysis showed that practical self-management topics, including blood glucose monitoring, insulin treatment, nutrition and exercise, complications, and emotional support, generated high levels of reach and interaction. Conclusions: HelloType1 demonstrates strong growth, mobile-first use, search-driven visibility, and engagement with practical self-management content. These findings support the feasibility and potential utility of a low-cost, multilingual digital education model, while future studies should evaluate its effects on knowledge, behavior, and clinical outcomes.
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