Control
BehavioralBrief 4-slide presentation without a separate session for questions and answers
NCT Number: NCT06630676
The investigative team will provide 27 slides with bullet points and images of pain referral patterns for different causes (e.g., herniated disc, facet joint arthritis) for patients seen for a new visit with a chief complaint of chronic low back pain. This material is all publicly available but has been compiled in presentation form. This will have educational benefit for patients, discussing clinical signs and symptoms, risk factors and basic treatments. There will also be a smaller control group of that gets a condensed 4-slide presentation. After review of the slides, an independent observer will ask the patient what they think are the 2 most likely causes of their LBP (in order of likelihood) and match that with the attending physician and trainee, who will independently do the same. The investigative team will then determine how concordant the patient's answers are with the physicians and also record outcomes.
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Notify Me18 year and older
All sexes
Interventional
Not applicable
Northwestern University Pain Management Center, Chicago, Illinois, United States
Artificial intelligence (AI), the growth of the internet and internet access, direct-to-patient advertising, and more recently the COVID-19 pandemic with a proliferation of telehealth visits has transformed medicine. Patients come in with a wealth of information, some accurate but some inaccurate, about their condition, often with preconceived notions about what condition they have and how they want to be treated. For conditions such as chronic pain with a high prevalence rate of abnormal imaging findings in asymptomatic individuals, the absence of biomarkers for clear-cut diagnoses, and subjective outcome measures, this has led to unnecessary tests and treatment, doctor shopping, high rates of burnout among providers and low success rates.
The COVID-19 pandemic shed light on accuracy of diagnoses via telehealth, with studies finding a high concordance rate between telehealth visits without the benefit of a physical exam, and in-person pain management consultant, which is similar to that found in other specialties. The proliferation of AI in electronic medical record systems that confer diagnoses based on patient and physician input of symptoms and signs suggests that in the future, patients with access to the information will be able to self-diagnose their chronic pain and other conditions. Many guidelines also recommend education and self-care in their back pain treatment algorithms, though the effect of education on outcomes is not well-known.
With this in mind, the purpose of this study is to determine how accurate patient diagnoses are when they are furnished with readily available information on the different etiologies for chronic low back pain (LBP), the leading cause of disability worldwide.
The plan is to enroll 269 patients in a 3:1 allocation ratio to either the 27-slide educational group or a condensed 4-slide control group. The patient will have the opportunity to ask questions, after which they will rate their top 2 diagnoses, in order. A trainee (resident or fellow) and the attending will do then do the same. Outcomes will be recorded at 4 weeks (e.g., for simple injections such as epidural steroids and sacroiliac joint injections, medications, physical therapy) or at 12 weeks for more invasive procedures such as spinal cord stimulation, radiofrequency ablation, or vertebral augmentation.
Analyses will be performed to: 1) Determine whether the educational program improves the likelihood that the patient correctly self-diagnoses the cause of their back pain using the attending physician as the reference standard compared to the control group; and 2) Whether the educational program improves treatment outcomes.
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Brief 4-slide presentation without a separate session for questions and answers
Patients will review 28 slides that discuss the different etiologies (causes) of back pain, how common they are, what causes them (e.g., wear and tear, trauma), factors that exacerbate and alleviate the pain, how they are diagnosed and treated, and have an opportunity to ask questions.
Time frame: Day 0 (enrollment date)
Concordance (overlap) between the patient's guess at their top 2 diagnoses, and those rendered by the attending physician. The patient's choices include 12 diagnoses (e.g., discogenic pain, spinal stenosis, piriformis syndrome) while the physician's includes 13 (secondary gain).
Time frame: Day 0
Concordance (overlap) between the patient's guess at their top 2 diagnoses, and those rendered by the trainee. The patient's choices include 12 diagnoses (e.g., discogenic pain, spinal stenosis, piriformis syndrome) while the physician's includes 13 (secondary gain). The intended scale is:
Time frame: 4 weeks
Average back pain score over past week on a 0-10 numerical rating scale (higher scores indicating greater pain)
Time frame: 4 weeks
Worst back pain score over past week on a 0-10 numerical rating scale (higher scores indicating greater pain)
Time frame: 4 weeks
Average leg pain score over past week on a 0-10 numerical rating scale (higher scores indicating greater pain)
Time frame: 4 weeks
Worst leg pain score over past week on a 0-10 numerical rating scale (higher scores indicating greater pain)
Time frame: 4 weeks
7-point Likert scale (7 is best outcome) in which patient rates their improvement as: no change or worse (1); almost the same (2); a little better (3); somewhat better (4); moderately better (5); better (6); a great deal better (7)
Time frame: 4 weeks
Greater or equal to 30% decrease in average back or leg (for sciatica) pain score coupled with a score >4 out of 7 on the Patient Global Impression of Change (PGIC) scale. For patients with <4 average pain score, we will use "worst" pain score as the baseline reference.
Time frame: 4 weeks
14-question survey (7 each for anxiety and depression) that measures anxiety and depression, each scored from 0 (no symptoms) to 21 (severe anxiety or depression)
Time frame: 4 weeks
10-question survey that assesses back pain-related disability, scored from 0 (no disability) to 50 (incapacitated), but usually expressed as a percentage (0-100%).
Northwestern University
Other
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View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
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