Research

PDA – Pain, Depression, Anxiety

Low back pain (LBP) is a global issue with a prevalence point of around 8% of the world population (~ 577.0 million people). Approximately 60% of patients with chronic pain suffer, in addition, from two or more psychological conditions like depression and anxiety. In nearly 52% of the cases, LBP patients also suffer from anxiety, depression, underdiagnosed, perpetuating the economic burden and the mental conditions.

Importantly, this synergy between pain and mental health conditions may change dynamically and not be well-understood. We are focusing on researching pain, depression and anxiety that usually change over time in daily life. We build an integrative system that will combine daily self-reported assessments, physiological and behavioral digital markers.

This Also, advanced computational approaches will be used for analysis of linguistic characteristics and behavioral markers of daily life activities over time, along with physiological measures, traced by the Fitbit smart watch device.

Better understanding of the compound mechanism that underlie chronic pain and mental health conditions will allow us to improve clinical approaches and prevent aggravation of these synergetic conditions.

The study is in collaboration with, Prof. Hagit Hel-Or (Department of Computer Science), Prof. Hadas Okon-Singer (Department of Psychology, Cognition Emotion Interaction Lab), Prof. Sigal Zilcha-Mano (Department of Psychology, Psychotherapy Research Lab) and Prof. Tzvi Reiss (Department of Statistics).

PainStory - pain detection based on facial expressions, voice and language content

Website: https://PainStory.science

The problem. Chronic pain, generally classified as pain that persists past normal healing time and lasts for longer than 3 to 6 months, affects almost 2.5 billion people, and is the main cause of the opioid crisis.1 Costs for treating and managing chronic pain conditions are greater than that for heart disease, cancer, and diabetes combined.2

While these facts are alarming, they paint an impersonal picture of the condition, detached from the actual daily suffering experienced by patients. As Kurt Tucholsky once said, “a single death is a tragedy, a million deaths are a statistic”, reflecting our protective tendency to simplify a harmful reality.

A critical challenge in pain management emerges from the fact that pain cannot be directly measured. Therefore, currently, the assessment of pain is based on a single 0-10 scale articulated by the patient with significant limitations especially for long-term usage: (1) being subjective and repetitive, it is biased and not sensitive enough, resulting in an unrealistic burden on the patient; (2) this oversimplified pain estimation does not capture the multiple aspects of chronic pain, such as its emotional and social impacts; and (3) shows low consistency with patients’ judgment about the severity of ongoing pain and its effects on daily life.3 As result, this easy-to-use approach to pain assessment means clinicians don’t have an accurate measurement tool for diagnosis or an evaluation of treatment efficacy. Therefore, objective measures of pain are needed to better inform pain management.

Our goals:

To develop an accurate objective pain assessment for clinical pain monitoring.
To reduce the stigma associated with chronic pain conditions and to increase awareness about chronic pain.

Our approach. We are developing a completely novel and intuitive digital platform, PainStory.science, that allows us to collect audio/video recordings from pain patients sharing their experiences of living with chronic pain. PainStory is a self-serving digital platform that uses advanced cybersecurity protocols to ensure participants’ privacy. The patients will be asked to describe their current symptoms, related emotions and suffering, the causes of the pain, and what makes the pain better or worse – by talking into their smartphone’s camera and microphone at home or in in their normal environment. In addition, they will rate their pain levels and complete a series of psychosocial surveys.

Using advanced machine learning approaches, the PainStory platform will “listen” and analyse patients’ narrative content, their vocal nuances and associated facial expressions to develop a personalised pain assessment. The PainStory assessment will be used for better clinical evaluation, and digital follow-up between the clinical visits. Relying on cheap and available sensing technology (microphone and camera), our solution will be easily scalable and adoptable. A select number of the pain narratives will be shared publicly (with patients’ approval) to empower others suffering from chronic pain.

PainRadar: Brain and skin-based fnirs fibromyalgia screening

We are developing a new biomarker for fibromyalgia with multi-modal techniques, including biochemical, brain-related, and physiological measures. Applying machine learning tools, we will attempt to classify fibromyalgia patients and their pain levels with neurophysiological and biochemical information. Further our model could be transformed into fully automated real-time detection of fibromyalgia and ongoing pain. The automated pain tracking has considerable potential to improve the efficacy of pain treatments, by providing just-in-time feedback and triggering interventions. Overall, the proposed project will contribute fundamental scientific knowledge about biochemical and neurophysiological signs of real-life pain and lay the groundwork for translational efforts to improve outcomes of pain self-management and reduce opioid use.This project is conducted in collaboration with Prof. Hossam Haick (Technion).

Alert Fatigue in Hospitals

Medication prescribing errors are among the most common and preventable types of errors in hospitalized patients, leading to significant morbidity, mortality, and healthcare costs. Computerized Physician Order Entry (CPOE) systems, combined with Clinical Decision Support Systems (CDSS), can reduce these errors by approximately 50%. CDSS provides alerts for drug-allergy checks, dosing adjustments, duplicate therapies, drug-drug interactions, and more, helping clinicians identify critical issues.

However, excessive alerts can lead to “alert fatigue,” where important warnings are overlooked due to an overwhelming number of notifications. Even 12 alerts per day in a busy clinic can cause clinicians to disregard over 90% of them, reducing CDSS effectiveness.

Relevance is key. When presented with irrelevant alerts, clinicians are more likely to ignore all alerts, including crucial ones. Customizing alerts to each hospital department’s needs can reduce unnecessary notifications and focus on actionable alerts that influence care.

Combatting alert fatigue requires thoughtful alert categorization:

Does an alert require immediate action?
Can the alert notify without disrupting workflow?
Are there valid reasons to override the alert?

Continuous review and optimization of CDSS, informed by data on alert trends, override rates, and clinician responses, are essential to maintaining their effectiveness. The goal is to balance safety and alert volume, ensuring CDSS supports clinical decisions while minimizing alert fatigue.

Our study focuses on the impact of CDSS customization and how it affects drug prescribing errors and alert fatigue, aiming to improve patient safety through effective alert management.

PDSR – Personalized Danger Signal Reprocessing

We are exploring a novel therapeutic approach for chronic low back pain, a condition affecting 18% of the population, often linked to persistent nociplastic pain without clear physical causes. Traditional treatments frequently fall short, prompting the development of Personalized Danger Signal Reprocessing (PDSR). PDSR combines neuroscience and clinical psychoeducation, sensory awareness and reprocessing, mindset reframing, using coaching to shape patients’ perceptions of pain and foster healing.

Importantly, we examine how nonverbal therapeutic dynamics, such as synchronized movements vocal pitch associated with the clinician-patient bond and treatment outcomes. By analyzing audio, video, and physiological data from the therapeutic sessions, we aim to uncover mechanisms that drive therapeutic success.

This project seeks to advance understanding of chronic pain treatment, offering a scalable, non-invasive model that could transform clinical care and improve patient outcomes.

Ukraine without chronic pain

Chronic pain is a significant problem in Ukraine, affecting more than 60% of the population. The physical and psychological trauma experienced by civilians and soldiers often triggers chronic pain and post-traumatic syndrome, leading to long-term suffering.

The Integrative Pain Laboratory (iPainLab) at the University of Haifa, in collaboration with Israeli methodologist Julia Zatulovsky has developed a therapeutic approach to help individuals suffering from chronic pain. This approach, which combines recent scientific discoveries with coaching tools to increase patient engagement, has been clinically validated and implemented at the rehabilitation unit of Hadassah Medical Center and two other scientific studies.

The first course was completed in collaboration with Ukrainian Community of Regional Analgesia and Pain Therapy this month with over 70 Ukrainian participants. Significant improvements were observed in pain symptoms (43%), post-traumatic symptoms (57%), depression (62%), and anxiety (47%).

https://www.israelhayom.com/2022/12/01/university-of-haifa-to-use-novel-methods-to-help-traumatized-ukraine-war-victims/

TrainPain - a new science based digital product designed to improve mental and emotional well-being for people living with neuropathic and fibromyalgia pain

Trainpain is a unique project aimed at examining the feasibility and effectiveness of a gamified sensory perceptual training programme for patients with fibromyalgia. Using a remote app-based somatosensorial training programme the project will examine changes in pain perception. The role of catastrophising, depression and anxiety will also be examined in relation to pain.

There is no known cure for fibromyalgia and pharmacological pain relief is only reported in a minority of patients. Perceptual training has been shown to reduce the impact of fibromyalgia along with other chronic pain conditions. Specifically, in fibromyalgia temporal discrimination may be altered; however, no study has examined training in this domain as a moderator for changes in pain.

There is a need for tools that fibromyalgia patients can use independently at home to manage their chronic pain and self-care. Thus, Trainpain offers a novel digital platform to enable patients to perform gamified perceptual training at home.