Assessing Bias in Substance Withdrawal Symptom Measurement and Treatment: How The OAD Clinic Personalises Patient Care
- The OAD Clinic
- 2 days ago
- 9 min read
The Diagnostic and Statistical Manual of Mental Disorders (DSM-5) treats all substance withdrawal symptoms as equal. Clinicians routinely tally present symptoms to determine the presence or severity of withdrawal, operating on the assumption that every clinical criterion holds identical weight for all patients.
A new paper published in Drug and Alcohol Dependence (2026), led by Dr Christal Davis and a team of addiction researchers offers a fresh, evidence-based perspective for more detailed symptom severity assessment. By tracking genetics and childhood adversity when measuring substance withdrawal symptom severity, the research findings reveal that the same symptom may represent a different level of severity among different individuals, and withdrawal severity may present with different symptoms in different patients depending on childhood background and genetics.
Therefore, treating a withdrawal symptom as an isolated, mechanical event does not provide comprehensive understanding of the patient’s withdrawal experience. The research clearly suggests that individual variations dictate how a patient experiences distress.
What the Research Tells Us About Withdrawal Measurement Bias
The groundbreaking 2026 study published in Drug and Alcohol Dependence, titled ‘Assessing measurement bias in substance withdrawal symptoms attributable to childhood adversity and genetic liability’ exposes major flaws in standard diagnostic frameworks. Led by Dr. Christal Davis and a team of research experts, the Item Response Theory (IRT) was used as a group of mathematical models to evaluate tobacco, alcohol, and opioid withdrawal criteria.
Symptoms are Not Created Equal When Measuring Withdrawal Severity
To explore further diagnostic precision for withdrawal symptom severity, Dr. Davis measured two core parameters for every symptom:
difficulty - how severe a withdrawal state must be for the symptom to appear (from low to high), and
discrimination - how precisely the symptom differentiates between mild (low) and severe (high) withdrawal phases.
Their findings reveal a highly uneven clinical landscape:
Tobacco Withdrawal - A decreased heart rate carries the highest severe state when it appears, occurring almost exclusively in advanced dependency, while irritability and restlessness show the highest discrimination values to precisely discriminate how severe the withdrawal is. For a success story about treatment for irritability caused by cannabis and tobacco addiction, read Jake's story.
Alcohol Withdrawal - Hallucinations demonstrate extremely high difficulty, appearing in severe withdrawal cases, but low discrimination in terms of severity of withdrawal phase, acting as a late-stage marker associated with profound neuropsychiatric disruptions like delirium tremens.
Opioid Withdrawal - the findings suggest that the most highly discriminating symptoms are strictly physiological—specifically a runny nose, chills, and sweating—which offer the greatest statistical precision for plotting latent severity of withdrawal symptoms.
Trauma- and medical history-Informed Care, and the Link Between Genetics and Environment
From a clinical standpoint, when clinicians fail to account for a patient’s trauma, PTSD history or genetic liability, they are highly prone to misjudging the true clinical severity of withdrawal symptoms. This can result in:
Poorly matched levels of acute care
Inadequate detoxification support, and
A higher risk of immediate return to substance use.
It is for these reasons that the research supports a trauma- and medical history-informed, integrated care approach as being vital to withdrawal symptom treatment.
The OAD Practice
The OAD Clinic’s clinical model treats addiction and withdrawal as deeply interconnected with a patient's psychiatric and medical history. Our medical protocols incorporate a holistic look at trauma histories, mental health variables and medical records, allowing clinicians to accurately manage withdrawal symptom variations without over-relying just on standard diagnostic symptom counts such as DSM-5.
The Role of Trauma and Genetics in Emotional Response to Withdrawal Symptoms
The true clinical impact of these research findings lies in their exploration of what happens when individuals experiencing identical levels of withdrawal severity report entirely different symptom profiles due to underlying genetic or environmental variables:
The Trauma Factor: patients with significant histories of childhood trauma, PTSD or instability show a lower overall likelihood of showing basic cravings or physical withdrawal symptoms at expected severity thresholds. Early-life trauma also amplifies the body's baseline stress reactivity, changing how symptoms perform. For example, a symptom like a runny nose becomes significantly more discriminating of severe opioid withdrawal in individuals with high adverse childhood exposures, highlighting a heightened autonomic response system.
Patients with an elevated genetic liability are also far more likely to display affective symptoms, such as restlessness or a depressed mood, at identical levels of physiological withdrawal severity when compared to other patients.
This means one patient may report a runny nose, and another a depressed mood, however the withdrawal severity may be identical in both cases. Dr Davis emphasises that this is particularly the case when treating opioid use disorder:
"Our findings suggest that physiological symptoms may be especially useful for accurately assessing opioid withdrawal severity, but we also found that their usefulness was not the same for every patient. Some symptoms clearly functioned differently depending on the patient’s genetic liability and history of childhood adversity. For example, a runny nose was better able to distinguish between levels of opioid withdrawal severity among individuals who had greater exposure to childhood adversity, while depressed mood was more likely to be reported by individuals with higher genetic liability for opioid use disorder even when their underlying withdrawal severity was the same as a patient with lower genetic liability."
Beyond Symptom Counts: Meeting Patients Where They Are
A crucial clinical takeaway from this data is that achieving true precision does not mean prioritising physical traits over emotional ones, particularly when it comes to opioid addiction treatment. Instead, clinicians must evaluate symptom sets alongside individual patient backgrounds. Dr Davis' position in this regard is clear:
"[...] greater precision may not come simply from prioritizing physiological over affective opioid withdrawal symptoms, but from considering which symptoms are most informative in combination with the patient's individual characteristics."
One of the most immediately actionable recommendations in the research is the routine adoption of tools that consider childhood trauma or PTSD, and potential genetic predisposition to addiction and/or mental health in order to assess withdrawal symptoms more accurately. For example, the more accurate severity measure for opioid withdrawal for patients with childhood trauma was a runny nose, while for patients with and without genetic predisposition to become addicted to opioids, it was a depressed mood.
Dr Davis emphasises that both biological predisposition and childhood trauma should be looked at in combination with the reported withdrawal symptoms.
At The OAD Clinic, the medical team bypasses the limitations of unweighted binary checklists with the use of more dynamic tools such as the Clinical Opiate Withdrawal Scale (COWS) to measure actual symptom intensity. Combining clinical grading scales with person-centred care pathways ensures that patients at The OAD Clinic remain safely engaged with treatment throughout recovery as withdrawal symptoms are managed more effectively.
The OAD Practice
The clinical team at The OAD Clinic combines individual patient profiles including mental health and medical history with advanced, intensity-graded assessment tools to adjust detoxification tracking and clinical monitoring in real time.
How The OAD Clinic Puts Dynamic Withdrawal Assessment Into Action
The clinical workflows implemented at The OAD Clinic translate this cutting-edge psychometric research directly to our treatment approach:
Comprehensive Baselines: Every patient undergoes an integrated review exploring medical risks, childhood adversity markers or PTSD, and psychiatric vulnerabilities from day one. For example, medical history is a mandatory piece of data during assessment in order to determine any predisposition to opioid dependence, and whether trauma or adversity earlier in life forms part of a patient’s background. This information provides valuable insights to contextualise severity of symptoms by symptom type in order to manage withdrawals as effectively and accurately as possible.
Weighted Interpretations: The OAD Clinic does not treat a single symptom count as a definitive measure of severity. Our clinicians explicitly adjust detoxification and monitoring protocols based on individual patient traits identified at assessment stage and how withdrawal symptoms develop throughout treatment.
Autonomic & Affective Balance: Medical staff are trained to judge whether a patient's emotional distress reflects trait-level vulnerabilities or an acute physiological emergency to provide appropriate treatment.
Dynamic Monitoring: We use sophisticated, intensity-graded assessment tools as well as simple binary present-or-absent frameworks such as DSM-5 to adjust patient treatment plans in real time.
Key Takeaways
Symptom Counts Mislead: Standard symptom tallies fail to measure equivalent underlying severity across different patients, creating risks of misdiagnosis.
Childhood adversity frequently reduces physical awareness, causing patients to underreport classic withdrawal symptoms.
Genetics Bias Mood Reporting: following research findings, patients with a high genetic risk for addiction report anxiety and depressed mood more frequently, even during mild withdrawal phases.
Autonomic Precision Treatment: In alignment with latest research, we consider that physiological signs (chills, sweating, runny nose) offer the highest statistical precision for determining the baseline trajectory of opioid withdrawal.
Integrated Care is Mandatory: Managing withdrawal safely requires combining clinical tracking scales with an individual's personal history rather than checking boxes.
Frequently Asked Questions
What is measurement bias in substance withdrawal, and why does it matter?
Measurement bias occurs when diagnostic systems assume all symptoms are equal indicators of condition severity. It matters because individual factors cause symptoms to present differently, meaning unweighted checklist counts can easily misjudge a patient's actual distress. This structural oversight can lead to inappropriate treatment planning or poorly matched levels of clinical detoxification support.
Does The OAD Clinic rely on the standard DSM-5 symptom checklists?
No. While The OAD Clinic uses standard frameworks for diagnostic tracking, our clinical teams use advanced, intensity-graded assessment tools like COWS alongside a patient's personal and medical history to guide detoxification adjustments.
How do adverse childhood experiences affect withdrawal symptoms?
Adverse childhood experiences can decrease a person's physiological self-awareness, making it harder to recognise internal bodily changes like cravings. In fact, early trauma can sensitise the nervous system, which makes physiological signs like a runny nose much more reflective of underlying distress during opioid withdrawal.
Does The OAD Clinic look beyond standard diagnostic checklists to manage withdrawal?
Yes. The OAD Clinic's assessment protocols explicitly bypass unweighted diagnostic counts by evaluating a patient's medical liabilities and adverse childhood history alongside their presenting symptoms. The clinical team combines individual patient profiles with advanced, intensity-graded assessment tools to adjust detoxification tracking and clinical monitoring in real time.
About the Research
This article draws on findings from the following peer-reviewed publication:
Davis, C. N., Han, A., Jackson, S., Gelernter, J., Feinn, R.,Kranzler, H.R. (2026): Assessing measurement bias in substance withdrawal symptoms attributable to childhood adversity and genetic liability, Drug and Alcohol Dependence Journal, Vol. 286, 113261, DOI: https://doi.org/10.1016/j.drugalcdep.2026.113261.
About Dr Christal Davis
Dr. Christal N. Davis is a psychologist, clinician-investigator and instructor at the University of Pennsylvania and the Philadelphia VA Medical Center. She is a lead author of Assessing measurement bias in substance withdrawal symptoms attributable to childhood adversity and genetic liability published in the Drug and Alcohol Dependence Journal (September 2026), which examines how genetic predisposition and early life exposure to trauma or adversity shape withdrawal symptom severity presentation.
Dr Davis contributes her clinical and research expertise to The OAD Clinic as an expert voice on opioid addiction psychiatry and the evidence base for the use of non-linear, dynamic testing of withdrawal symptomatology in combination with a patient’s medical history and early life experiences. Read Dr Davis' full profile at The OAD Clinic.
Expert Q&A: Dr Davis on addiction withdrawal symptom bias
This Q&A draws on findings from: Dr Christal Davis et al. (2026): Assessing measurement bias in substance withdrawal symptoms attributable to childhood adversity and genetic liability, Drug and Alcohol Dependence Journal, Vol. 286, 113261, DOI: https://doi.org/10.1016/j.drugalcdep.2026.113261.
Question: The findings reveal that the most highly discriminating symptoms for opioid withdrawal are primarily autonomic and physiological (such as a runny nose, chills, and sweating) rather than mood-related. In such cases, would the absence of affective symptoms indicate that physiological symptoms are more relevant for achieving better diagnostic precision?
Our findings suggest that physiological symptoms may be especially useful for accurately assessing opioid withdrawal severity, but we also found that their usefulness was not the same for every patient. Some symptoms clearly functioned differently depending on the patient’s genetic liability and history of childhood adversity. For example, a runny nose was better able to distinguish between levels of opioid withdrawal severity among individuals who had greater exposure to childhood adversity, while depressed mood was more likely to be reported by individuals with higher genetic liability for opioid use disorder even when their underlying withdrawal severity was the same as a patient with lower genetic liability. Clinically, this suggests that greater precision may not come simply from prioritizing physiological over affective opioid withdrawal symptoms, but from considering which symptoms are most informative in combination with the patient’s individual characteristics.
Dr Davis
Question: Given that the DSM-5 currently treats all opioid withdrawal symptoms equally, but this study proves they vary significantly in difficulty and discrimination, what would a more effective scoring system consist of?
The DSM provides an important framework for identifying the presence or absence of opioid withdrawal syndrome, but diagnosis is only one part of clinical assessment and withdrawal management. Measures like the Clinical Opiate Withdrawal Scale (COWS) complement the DSM by assessing the intensity of different signs and symptoms to provide a more detailed picture of withdrawal severity. Our findings suggest that there may be opportunities to make these assessments even more precise. For example, future approaches could consider that some symptoms better distinguish between levels of withdrawal severity and that different symptoms tend to occur at different points along the severity spectrum. Although likely more intensive to implement in a structured assessment, clinicians may also consider how patient characteristics (i.e., childhood adversity and genetic risk) influence symptom presentation. An important next step will be to determine whether incorporating this information could improve clinical decision making and outcomes.
Dr Davis
About the Author
This article was written and reviewed by Luciana D'Agnone BA, MSc, Director and Editorial Lead at The OAD Clinic. Luciana oversees all clinical content published on the The OAD Clinic website, ensuring it reflects current evidence, clinical experience, and a commitment to person-centred addiction care.
¹ Davis, C. N., Han, A., Jackson, S., Gelernter, J., Feinn, R.,Kranzler, H.R. (2026): Assessing measurement bias in substance withdrawal symptoms attributable to childhood adversity and genetic liability, Drug and Alcohol Dependence Journal, Vol. 286, 113261, DOI: https://doi.org/10.1016/j.drugalcdep.2026.113261.
