Introduction: Adults living with sickle cell disease (SCD) most frequently seek medical care due to pain. To determine the most efficacious treatment plan for patients presenting with pain, providers must first accurately assess and diagnose the pain. Unfortunately, the current approaches for assessing pain are inadequate. Combined with medical provider biases, patients can often have their pain symptoms misinterpreted, ignored, or blatantly dismissed. To address this issue, we partnered with stakeholders, human-centered designers, and software engineers to design a novel pain assessment tool, called Painimation. Painimation allows patients to communicate their pain quality, intensity, and location using abstract animations and a paintable body image. Painimation has been validated in a general population with chronic pain, but there is limited data validating this approach in SCD. Preliminary data on the use of Painimation by adults with SCD (N = 67) found that those who described their pain using the “throbbing” animation had less severe pain symptoms than those endorsing the “shooting” animation. Objective: To replicate and extend prior findings by determining whether pain animations and body image data are associated with pain outcomes in a large cohort of adults with SCD. We hypothesized that the presence of shooting pain and greater body surface areas affected by pain would be associated with more severe pain outcomes and mental health symptoms. Methods: We performed a secondary analysis on baseline data from the “Cognitive Behavioral Therapy and Real-Time Pain Management Intervention for Sickle Cell via Mobile Application (CaRISMA)” Trial-a multisite randomized, controlled trial in adults with SCD and chronic pain. Eligible patients were randomized 1:1 to either digital cognitive behavioral therapy or digital education; in addition, both arms received at least 12 weeks of health coach support. At baseline, participants completed a battery of questionnaires and tracked their pain intensity (0-10) by the Visual Analog Scale (VAS) and mood daily via a mobile app. The Painimation app presents a front and back 2-dimensional body image that is paintable to indicate areas affected by pain. Users choose from abstract animations intended to represent different pain qualities; the intensity of the animations can be adjusted, and up to three can be selected. For the purpose of the analyses, participants were categorized into “Shooting Pain” vs “No Shooting Pain” and “Throbbing with Shooting and Stabbing” vs “Throbbing Alone,” based on our prior study. Participants were also split into groups based on whether the proportion of the body image painted was less than the median (<9.8% vs >=9.8%). Baseline characteristics and demographics were compared between groups, and multivariable regressions were used to estimate covariate-adjusted associations with the following outcomes at baseline: daily pain, Patient Reported Outcomes Measurement Information System (PROMIS) pain interference scale, Pain Catastrophizing Scale (PCS), Current Opioid Misuse Measure (COMM-9), and Adults Sickle Cell Quality of Life Measurement Information System (ASCQ-Me) pain severity and frequency. Results: The trial enrolled 359 adults, mean age 36.3 (SD = 10.5), 66% female, 93% Black race. The “Shooting” painimation and greater body image scores were associated with all outcomes in univariate analyses (all p<0.01; Table 1) except for the proportion of “happy” mood days and anxiety scores. After controlling for age, depression, anxiety, % body image, and site, the shooting animations were independently associated with greater daily pain intensity (beta = 0.64; p = 0.046). After controlling for age, depression, and site, greater body image score was associated with daily pain intensity (beta = 1.18; p < 0.001), pain interference (beta = 2.87; p < 0.001), ASCQ-Me pain frequency (beta = 3.91; p =< 0.005), and ASCQ-Me pain severity (beta = 4.50; p = 0.002). Conclusion: Both the “shooting” animation and body image measures were associated with more severe pain outcomes. This study demonstrates that animations and body image data can be used to assess pain severity in SCD, more objectively than the 0-10 numeric VAS scale. Future studies should explore whether pain location and specific animation selected are associated with pain etiology, and determine whether this approach can differentiate different types of pain in SCD.