Optimizing screening for depression, anxiety disorders, and post-traumatic stress disorder in inpatient addiction treatment: A preliminary investigation
Open accessAbstract
Objective Substance use disorders (SUD) are frequently comorbid with other psychiatric conditions, but a comprehensive diagnostic assessment is often not feasible clinically. Efficient psychometrically-validated screening tools exist for commonly comorbid conditions, but cutoff accuracies have typically not been evaluated in addiction treatment settings. This study examined the performance of several widely-used screening measures in relation to diagnostic status from a clinical interview to identify and validate cutoff scores in an inpatient SUD treatment setting.Method Participants were 99 patients in a large residential SUD treatment program in Ontario, Canada. Participants completed a screening battery, including the Patient Health Questionnaire - 9 (PHQ-9), Generalized Anxiety Disorder - 7 (GAD-7), and Post-Traumatic Stress Disorder Checklist-5 (PCL-5), and underwent a semi-structured diagnostic clinical interview. Receiver operating characteristic curves were used to determine optimal cutoff scores on the screening tool against the interview-based diagnosis.Results Area under the curve (AUC) was statistically significant for all screens and were as follows: PHQ-9 = 0.70 (95% CI = 0.59-0.80), GAD-7 = 0.74 (95% CI = 0.63-0.84), and PCL-5 = 0.79 (95% CI = 0.66-0.91). The optimal accuracy cutoff scores based on sensitivity and specificity were: PHQ-9 ≥ 16, GAD-7 ≥ 9, the PCL-5 ≥ 42.Conclusions In general, the candidate screeners performed acceptably in this population. However, the optimal cutoff scores were notably higher than existing guidelines for depression and PTSD, potentially due to the general elevations in negative affectivity among individuals initiating SUD treatment. Further validation of these cutoff values is warranted.Public health significance This study provides modified screening cutoff scores for major depression, anxiety disorders, and post-traumatic stress disorder in addiction treatment settings.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
0 of 13 cited sources checked · 0 supported · 0 flagged
- Findingown data
All screening measures performed significantly better than chance.
“The AUCs suggest that all measures performed significantly better than chance, discerning between participants with and without the disorders.”
Quote in the paperSubstantial claim - Findingown data
Kappa values indicated substantial to almost perfect agreement between alcohol, cocaine, and opioid use symptom checklists and their corresponding diagnoses.
“For the current study, the Kappa values indicate that there was fair agreement between the PHQ-9 and a diagnosis of MDD; moderate agreement between the GAD-7, PCL-5, and Cannabis Symptom Checklist, and a diagnosis of anxiety, PTSD, and cannabis use disorder, respectively; and substantial agreement to almost perfect agreement between alcohol use, cocaine use, and opioid use symptom checklists, and”
Quote in the paperSubstantial claim - Findingown data
Accuracy was fair for major depressive disorder, anxiety disorders, and PTSD.
“For MDD, anxiety disorders, and PTSD the accuracy was fair.”
Quote in the paperSubstantial claim - Findingown data
The anxiety screen's positive predictive power captured three-quarters of individuals who actually had the diagnosis.
“The positive predictive power for anxiety was slightly better, capturing three-quarters of individuals who actually had the diagnosis.”
Quote in the paperNot a substantial claim - Findingown data
Kappa values indicated moderate agreement between the PCL-5 and PTSD diagnosis.
“For the current study, the Kappa values indicate that there was fair agreement between the PHQ-9 and a diagnosis of MDD; moderate agreement between the GAD-7, PCL-5, and Cannabis Symptom Checklist, and a diagnosis of anxiety, PTSD, and cannabis use disorder, respectively; and substantial agreement to almost perfect agreement between alcohol use, cocaine use, and opioid use symptom checklists, and”
Quote in the paperSubstantial claim
- Findingown data
The GAD-7 had a statistically significant AUC of 0.74 (95% CI 0.63-0.84).
“Area under the curve (AUC) was statistically significant for all screens and were as follows: PHQ-9 = 0.70 (95% CI = 0.59–0.80), GAD-7 = 0.74 (95% CI = 0.63–0.84), and PCL-5 = 0.79 (95% CI = 0.66–0.91).”
Quote in the paperSubstantial claim - Findingown data
The PCL-5 had a statistically significant AUC of 0.79 (95% CI 0.66-0.91).
“Area under the curve (AUC) was statistically significant for all screens and were as follows: PHQ-9 = 0.70 (95% CI = 0.59–0.80), GAD-7 = 0.74 (95% CI = 0.63–0.84), and PCL-5 = 0.79 (95% CI = 0.66–0.91).”
Quote in the paperSubstantial claim - Findingreasoning
The optimal cut-off scores were notably higher than existing guidelines for depression and PTSD.
“However, the optimal cut-off scores were notably higher than existing guidelines for depression and PTSD, potentially due to the general elevations in negative affectivity among individuals initiating SUD treatment.”
Quote in the paperSubstantial claim - Findingown data
The optimal PHQ-9 cut-off was 16 or higher.
“The optimal accuracy cut-off scores based on sensitivity and specificity were: PHQ-9 ≥16, GAD-7 ≥ 9, the PCL-5 ≥ 42.”
- Also stated in: § Results · plain
“For the PHQ-9, a cut-off of 16 yielded the optimal accuracy, correctly identifying 72% of individuals with MDD and correctly identifying 64% of individuals without MDD.”
Quote in the paperSubstantial claim - Also stated in: § Results · plain
- Findingown data
The optimal PCL-5 cut-off was 42 or higher.
“The optimal accuracy cut-off scores based on sensitivity and specificity were: PHQ-9 ≥16, GAD-7 ≥ 9, the PCL-5 ≥ 42.”
- Also stated in: § Results · plain
“For the PCL-5, a cut-off of 42 would correctly identify 81% of individuals with PTSD and correctly identify 77% of individuals without PTSD.”
Quote in the paperSubstantial claim - Also stated in: § Results · plain
- Findingown data
The PHQ-9 had a statistically significant AUC of 0.70 (95% CI 0.59-0.80).
“Area under the curve (AUC) was statistically significant for all screens and were as follows: PHQ-9 = 0.70 (95% CI = 0.59–0.80), GAD-7 = 0.74 (95% CI = 0.63–0.84), and PCL-5 = 0.79 (95% CI = 0.66–0.91).”
Quote in the paperSubstantial claim - Findingown data
The GAD-7 optimal cut-off was 10 or greater.
“The GAD-7 in this study had an optimal cut off score of 10 or greater, similar to the previously validated cut-off of nine and above in general psychiatry (Löwe et al., 2008) and nine and above in a substance use disorder specific population (Delgadillo et al., 2012).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Löwe et al., 2008
Not checked in the free run.
- cites Delgadillo et al., 2012 source
Not checked in the free run.
- Findingown data
SUD screening instruments had good to excellent sensitivity (86-92%) and specificity (80-95%).
“With regards to the secondary focus, the SUD screening instruments, the cut-off scores were at or around the validated cut-off scores, and had good to excellent sensitivity (86–92%) and specificity (80–95%).”
Quote in the paperSubstantial claim- The authors state this as an assumption: The presence of a substance use disorder was assumed for participants because of the clinical setting.
- Findingown data
Kappa values indicated moderate agreement between the Cannabis Symptom Checklist and cannabis use disorder diagnosis.
“For the current study, the Kappa values indicate that there was fair agreement between the PHQ-9 and a diagnosis of MDD; moderate agreement between the GAD-7, PCL-5, and Cannabis Symptom Checklist, and a diagnosis of anxiety, PTSD, and cannabis use disorder, respectively; and substantial agreement to almost perfect agreement between alcohol use, cocaine use, and opioid use symptom checklists, and”
Quote in the paperNot a substantial claim - Findingown data
The anxiety screen's negative predictive power captured two-thirds of individuals who did not have the diagnosis.
“Negative predictive power for anxiety disorders, however, tended to only capture two-thirds of individuals who did not have the diagnosis.”
Quote in the paperNot a substantial claim - Findingown data
Kappa values indicated fair agreement between the PHQ-9 and MDD diagnosis.
“For the current study, the Kappa values indicate that there was fair agreement between the PHQ-9 and a diagnosis of MDD; moderate agreement between the GAD-7, PCL-5, and Cannabis Symptom Checklist, and a diagnosis of anxiety, PTSD, and cannabis use disorder, respectively; and substantial agreement to almost perfect agreement between alcohol use, cocaine use, and opioid use symptom checklists, and”
Quote in the paperSubstantial claim - Findingown data
The depression and PTSD screens had negative predictive powers above 80%.
“However, the depression and PTSD screens had negative predictive powers above 80%, meaning four out of five who screened negative were indeed negative for the disorders.”
Quote in the paperSubstantial claim - Findingown data
Kappa values indicated moderate agreement between the GAD-7 and anxiety diagnosis.
“For the current study, the Kappa values indicate that there was fair agreement between the PHQ-9 and a diagnosis of MDD; moderate agreement between the GAD-7, PCL-5, and Cannabis Symptom Checklist, and a diagnosis of anxiety, PTSD, and cannabis use disorder, respectively; and substantial agreement to almost perfect agreement between alcohol use, cocaine use, and opioid use symptom checklists, and”
Quote in the paperSubstantial claim - Findingown data
The optimal GAD-7 cut-off was 9 or higher.
“The optimal accuracy cut-off scores based on sensitivity and specificity were: PHQ-9 ≥16, GAD-7 ≥ 9, the PCL-5 ≥ 42.”
Quote in the paperSubstantial claim - Findingown data
The depression and PTSD screens had positive predictive powers below 50%.
“Both the depression and PTSD screens had positive predictive powers below 50%, meaning that fewer than half who screened positive were actually determined to meet diagnosis.”
Quote in the paperSubstantial claim - Findingown data
The established PHQ-9 cut-off scores over-identified patients as MDD+.
“In other words, the established cut off scores for the PHQ-9 over-identified patients as being MDD+.”
Quote in the paperSubstantial claim - Findingown data
The GAD-7 demonstrated good specificity (78%).
“This screening tool demonstrated good specificity (78%), suggesting it performed well in correctly classifying patients who did not meet criteria for an anxiety disorder.”
Quote in the paperSubstantial claim - Findingown data
The validated GAD-7 cut-off scores performed almost identically to the cut-off scores obtained in this sample.
“Interestingly, the validated cut-off scores for the GAD-7 preformed almost identically to the cut-off scores obtained in this sample, suggesting it may be a problem with the screening measure itself in assessing anxiety disorders in this population.”
Quote in the paperSubstantial claim - Findingown data
SUD screening cut-off scores were at or around validated cut-off scores.
“With regards to the secondary focus, the SUD screening instruments, the cut-off scores were at or around the validated cut-off scores, and had good to excellent sensitivity (86–92%) and specificity (80–95%).”
Quote in the paperSubstantial claim- The authors state this as an assumption: The presence of a substance use disorder was assumed for participants because of the clinical setting.
- Findingown data
Fully 66% of patients met criteria for at least one target non-SUD condition in this sample.
“Fully 66% of patients met criteria for at least one target non-SUD condition in this sample, with the most common comorbidity being anxiety disorders (i.e. GAD and/or SAD).”
Quote in the paperSubstantial claim - Findingown data
The most common comorbidity was anxiety disorders (GAD and/or SAD).
“Fully 66% of patients met criteria for at least one target non-SUD condition in this sample, with the most common comorbidity being anxiety disorders (i.e. GAD and/or SAD).”
Quote in the paperNot a substantial claim - Premisecitation
Substance use disorders frequently co-occur with other psychiatric conditions, especially depression, anxiety, and PTSD.
“Substance use disorders (SUD) tend to co-occur with other psychiatric conditions, particularly depression, anxiety, and posttraumatic stress disorder (PTSD) (Strathdee et al., 2005; Compton et al., 2007; MacKillop et al., 2016).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Strathdee et al., 2005
Not checked in the free run.
- cites Compton et al., 2007 source
Not checked in the free run.
- cites MacKillop et al., 2016
Not checked in the free run.
- Interpretationown data
The candidate screeners performed acceptably in this population.
“In general, the candidate screeners performed acceptably in this population.”
Quote in the paperSubstantial claim - Interpretationreasoning
Typical cut-off scores may lack accuracy or validity if they have not been validated in a substance use disorder treatment sample.
“Without validation of these screening questionnaires within a SUD treatment population, typical cut off scores for identification may not be as accurate or valid.”
Quote in the paperSubstantial claim - Interpretationreasoning
A substance use disorder may raise the false positive rate on psychiatric screening.
“Second, the presence of a SUD may result in a higher false positive rate.”
Quote in the paperSubstantial claim - Interpretationreasoning
Elevated negative affectivity tied to substance misuse may produce psychiatric false positives.
“As such, high negative affectivity resulting from the substance misuse may contribute to false positives from a psychiatric standpoint.”
Quote in the paperSubstantial claim - Interpretationreasoning
The higher cut-offs may be due to general elevations in negative affectivity among individuals initiating SUD treatment.
“However, the optimal cut-off scores were notably higher than existing guidelines for depression and PTSD, potentially due to the general elevations in negative affectivity among individuals initiating SUD treatment.”
Quote in the paperSubstantial claim - Interpretationown data
The cut-off scores generated in this sample are substantively accurate.
“For example, based on the optimal cut-offs in this sample, the PHQ-9 demonstrated good sensitivity and adequate specificity, and the PCL-5 demonstrated good sensitivity and excellent specificity, suggesting the cut-off scores generated in this sample are substantively accurate.”
Quote in the paperSubstantial claim - Premisecitation
Comprehensive diagnostic assessment is frequently impractical in clinical settings.
“While these interviews are considered the most clinically accurate, they are typically resource- and time-intensive, and are not feasible in high volume clinical settings (Eack, Singer & Greeno, 2008).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Eack, Singer & Greeno, 2008
Not checked in the free run.
- Study design and conductcitation
Prevalence rates of comorbid conditions in this sample were similar to those in other studies.
“However, the prevalence rates of comorbid conditions in this sample were similar to those obtained in other studies (for a meta-analysis, see Lai et al., 2015), somewhat mitigating this concern.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Lai et al., 2015 source
Not checked in the free run.
- Interpretationown data
The screening measures did not offer sufficient accuracy to serve in a diagnostic capacity.
“While these screening measures functioned well in general, they did not offer sufficient accuracy to serve in a diagnostic capacity.”
Quote in the paperSubstantial claim - Study design and conductown data
The PHQ-9 demonstrated good internal consistency (α = .87) in this sample.
“The PHQ-9 demonstrated good internal consistency (α = .87).”
Quote in the paperNot a substantial claim - Interpretationown data
Existing screening tools appear to operate adequately in an inpatient SUD treatment setting.
“Taken together, these results offer evidence that existing screening tools appear to operate adequately in an inpatient SUD treatment setting, but particularly emphasize the need for their optimization.”
Quote in the paperSubstantial claim - Study design and conductown data
ICD-10 SUD checklist internal consistency was good to excellent across substances (α's = .87 −.92).
“Internal consistency was good to excellent across substances (α’s = .87 −.92).”
Quote in the paperNot a substantial claim - Study design and conductcitation
The current sample size is not substantially below typical sample sizes for developing ranges for laboratory tests.
“In addition, the current sample size is not substantially below typical sample sizes for developing ranges for laboratory tests (Manrai, Patel, & Ioannidis, 2018).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Manrai, Patel, & Ioannidis, 2018
Not checked in the free run.
- Interpretationreasoning
The overall prevalence rates of comorbid conditions indicate that SUD treatment services not deliberately targeting comorbid conditions are in fact typically doing so.
“Thus, the overall prevalence rates of comorbid conditions indicate that even SUD treatment services that are not deliberately providing services targeting patients with SUDs and other psychiatric comorbidities (populations typically referred to as concurrent disorders or dual diagnosis patients) are in fact typically doing so.”
Quote in the paperSubstantial claim - Interpretationreasoning
Inpatient SUD treatment is de facto concurrent disorders programs.
“In other words, the high rates of comorbidity between SUD and other conditions, in general and probably even more so in high severity clinical settings, make inpatient SUD treatment de facto concurrent disorders programs, regardless of whether they are designed as such.”
Quote in the paperSubstantial claim
- Borderline: one of the tests for a substantial claim is unclear. 1
- May combine two claims. 22
- Classified as probably not a substantial claim. 8
Borderline on S1 (asserted), S4 (based): unclear from the text. May combine two claims.
Findingnone givenThe previously validated PCL-5 cut-off of 31 would over-identify individuals, with specificity of 51%.
“Again, the previously validated cut-off of 31 would over-identify individuals, with specificity of 51%.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S1 (asserted), S4 (based).
Findingnone givenThe previously validated PHQ-9 cut-off of 10 would over-identify individuals with MDD.
“In contrast, the previously validated score of 10 would over-identify individuals with MDD.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataA PCL-5 cut-off of 42 correctly identified 81% of individuals with PTSD and 77% of those without PTSD.
“For the PCL-5, a cut-off of 42 would correctly identify 81% of individuals with PTSD and correctly identify 77% of individuals without PTSD.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe PCL-5 demonstrated good sensitivity and excellent specificity.
“For example, based on the optimal cut-offs in this sample, the PHQ-9 demonstrated good sensitivity and adequate specificity, and the PCL-5 demonstrated good sensitivity and excellent specificity, suggesting the cut-off scores generated in this sample are substantively accurate.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataKappa values for validated cut-offs were lower than or equal to those for optimal cut-offs for PHQ-9 and PCL-5, slightly lower for GAD-7, and almost identical for substance use checklists.
“The κ values calculated for the validated cut off values were lower than or equal to those calculated using the optimal cut off score for the PHQ-9, and PCL-5, slightly lower for the GAD-7, and almost identical for the substance use checklists.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataOptimal cut-off scores were considerably higher than validated cut-off scores, with PHQ-9 five points higher and PCL-5 ten points higher.
“However, the optimal cut-off scores were considerably higher than the validated cut off scores, with the PHQ-9 being five points higher and the PCL-5, ten points higher.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataA PHQ-9 cut-off of 16 correctly identified 72% of individuals with MDD and 64% of those without MDD.
“For the PHQ-9, a cut-off of 16 yielded the optimal accuracy, correctly identifying 72% of individuals with MDD and correctly identifying 64% of individuals without MDD.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe PHQ-9 demonstrated good sensitivity and adequate specificity.
“For example, based on the optimal cut-offs in this sample, the PHQ-9 demonstrated good sensitivity and adequate specificity, and the PCL-5 demonstrated good sensitivity and excellent specificity, suggesting the cut-off scores generated in this sample are substantively accurate.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataSUD screens had positive predictive powers between 89% and 100% and negative predictive powers between 71% and 88%.
“As expected, the screens for SUD had stronger predictive power, with positive predictive powers between 89–100%, and negative predictive powers between 71–88%.”
Quote in the paperSubstantial claim- The authors state this as an assumption: The presence of a substance use disorder was assumed for participants because of the clinical setting.
May combine two claims.
Findingown dataWhen the previously validated PHQ-9 cut-off was applied, sensitivity increased to 100% and specificity decreased to 29%.
“Additionally, in the current study, when the previously validated cut-off score for the PHQ-9 was applied in this sample, sensitivity increased to 100%, but specificity decreased to 29%.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataFor the PCL-5, sensitivity did not increase with a higher cut-off, but correct identification of individuals who truly did not have the disorder improved.
“For the PCL-5, the situation was somewhat different, insofar as sensitivity did not increase with a higher cut-off, but correct identification of individuals who truly did not have the disorder improved.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe GAD-7 sensitivity was adequate but suboptimal (66%).
“However, similar to the PHQ-9, sensitivity was adequate but suboptimal (66%), suggesting it only correctly identified two-thirds of those who were subsequently determined to have an anxiety disorder.”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataBoth PHQ-9 and PCL-5 had substantially higher cut-off scores in this study.
“Both the PHQ-9 and PCL-5 in this study had substantially higher cut off scores and, as depression and PTSD are commonly comorbid with substance use, it is critical to establish valid screening values to correctly identify the need for more in depth diagnostic assessment and also guide treatment planning.”
Quote in the paperSubstantial claimMay combine two claims.
FindingcitationWhen using the Delgadillo et al. (2011) cut-off with SUD outpatients, sensitivity was 90% and specificity was 37%.
“Similarly, when using the cut off scores obtained by Delgadillo et al. (2011) with SUD outpatients, sensitivity was 90%, and specificity was 37%.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Delgadillo et al., 2011 source
Not checked in the free run.
May combine two claims.
PremisecitationOnly one prior validation of the PHQ-9 and GAD-7 exists in a substance use disorder sample, and it was outpatient.
“In fact, to our knowledge the PHQ-9 and the GAD-7 have only been validated once in a SUD population and that was in an outpatient setting (Delgadillo et al., 2011; Delgadillo et al., 2012).”
Quote in the paperSubstantial claim0 of 2 sources checkedMay combine two claims.
InterpretationreasoningPeople entering addiction treatment may have had a recent negative life event that led to admission and may therefore have elevated general negative affectivity.
“Specifically, individuals in addiction treatment may have recently experienced a negative life event that precipitated admission to treatment, which may increase general negative affectivity.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Premisenone givenMany commonly used screening questionnaires have strong validation in general psychiatric populations.
“Although certain widely used screening questionnaires, have been well validated in general psychiatric settings, they have not been well established among people with SUD.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductnone givenDiagnostic interviews were audiotaped and checked for accuracy by a second reviewer, with discrepancies resolved by a licensed clinical psychologist.
“All diagnostic interviews were audiotaped and checked for accuracy by a second reviewer. Where discrepancies were present between the interviewer and the reviewer, the final disposition was made by a licensed clinical psychologist (JM).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductreasoningOther disorders outside the scope of this study are also comorbid with SUDs and could not be addressed.
“Furthermore, it is certainly the case that other disorders outside the scope of this study are also comorbid with SUDs (e.g., borderline personality disorder, antisocial personality disorder) and could not be addressed.”
Quote in the paperNot a substantial claimMay combine two claims.
Study design and conductnone givenThe study may be representative of inpatient addiction services but not necessarily public inpatient SUD treatment programs or lower acuity settings.
“Second, although this study may be representative of inpatient addiction services, they are not necessarily representative of public inpatient SUD treatment programs or lower acuity settings, such as outpatient SUD treatment clinics or general psychiatry programs.”
Quote in the paperNot a substantial claimMay combine two claims.
Study design and conductnone givenThe sample size was modest, reducing statistical power and representativeness.
“With regard to limitations, it is important to consider that the sample size was modest, reducing statistical power and reducing the representativeness of the sample.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenThe GAD-7 demonstrated high internal consistency (α = .92).
“The GAD-7 demonstrated high internal consistency (α = .92).”
Quote in the paperNot a substantial claimMay combine two claims.
Study design and conductown dataThe PCL-5 demonstrated good internal consistency (α = .83), and each subscale good to excellent (α's = .81 −.91).
“The PCL-5 as a whole demonstrated good internal consistency (α = .83), and each subscale exhibited good to excellent internal consistency (α’s = .81 −.91).”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Study design and conductreasoningThe results should not be considered definitive, particularly the specific cut-off scores.
“Nonetheless, the results should not be considered definitive, particularly in terms of the specific cut-off scores.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductnone givenThe GAD-7 is a global screen for anxiety disorders and does not reflect individual categories within anxiety disorders.
“Third, the GAD-7 is a global screen for anxiety disorders, and therefore does not reflect individual categories within anxiety disorders (e.g. social anxiety, generalized anxiety, and panic disorder).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningThis study supports calls for a more integrated treatment system.
“Consistent with these trends, this study clearly supports calls for a more integrated treatment system, where programs are focussed on SUD and co-occurring conditions, and clinicians are cross-trained on management of concurrent disorders (McGovern et al., 2014; Drake et al., 2010).”
Quote in the paperNot a substantial claim0 of 2 sources checkedMay combine two claims.
Interpretationown dataSUD screening instruments provide confirmatory evidence that efficient, low-burden screening measures accurately classify individuals diagnostically.
“However, they provide confirmatory evidence that efficient, low-burden screening measures do indeed accurately classify individuals diagnostically.”
Quote in the paperSubstantial claim- The authors state this as an assumption: The presence of a substance use disorder was assumed for participants because of the clinical setting.
The authors state this as an assumption.
The presence of a substance use disorder was assumed for participants because of the clinical setting.
“Although the presence of an SUD was assumed given the clinical setting, a secondary objective of the study was to also examine SUD screening in terms of its accuracy.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The YA-SUP assessment (called the 'battery') evolved through literature reviews, discussion of clinically important outcomes with stakeholders, and previous batteries that have been successfully deployed in similar clinical settings.
“The YA-SUP assessment (called the 'battery') evolved through literature reviews, discussion of clinically important outcomes with stakeholders, and previous batteries that have been successfully deployed in similar clinical settings (71-73).”
From Initial insights from a quality improvement initiative to develop an evidence-informed young adult substance use program (2022) · cites this paper as [72]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
GAD-7 optimal cutoff conflicts between abstract and discussion
MajorThe abstract states the optimal GAD-7 cutoff was 9, but the discussion later says the study's optimal cutoff was 10 or greater. These two statements describe different optimal thresholds for the same result.
“The optimal accuracy cut-off scores based on sensitivity and specificity were: PHQ-9 ≥16, GAD-7 ≥ 9, the PCL-5 ≥ 42.”
“The GAD-7 in this study had an optimal cut off score of 10 or greater, similar to the previously validated cut-off of nine and above in general psychiatry (Löwe et al., 2008) and nine and above in a substance use disorder specific population (Delgadillo et al., 2012).”
Two different optimal GAD-7 cut-offs are reported
MajorThe abstract gives an optimal GAD-7 cut-off of 9 or greater, while the discussion gives 10 or greater. This changes which patients would screen positive.
“The optimal accuracy cut-off scores based on sensitivity and specificity were: PHQ-9 ≥16, GAD-7 ≥ 9, the PCL-5 ≥ 42.”
“The GAD-7 in this study had an optimal cut off score of 10 or greater”
Previously validated GAD-7 cut-off changes between sections
MinorThe measures section states that the validated GAD-7 cut-off in nonclinical settings is 10 or above, but the discussion describes the previously validated general-psychiatry cut-off as nine and above.
“The validated cut off score for this screening instrument in nonclinical settings is 10 or above (Löwe et al., 2008)”
“the previously validated cut-off of nine and above in general psychiatry (Löwe et al., 2008)”
Cites
Diagnostic and Statistical Manual of Mental Disorders
Williams, J. B. W., & First, M. B. (2013) · Oxford University Press eBooks · doi:10.1093/acrefore/9780199975839.013.104 · Cited by 109,841 · see citing works
A Coefficient of Agreement for Nominal Scales
Cohen, J. (1960) · Educational and Psychological Measurement · doi:10.1177/001316446002000104 · Cited by 42,398 · see citing works
A Brief Measure for Assessing Generalized Anxiety Disorder: The GAD-7
Spitzer, R. L., Kroenke, K., Williams, J. B. W., & Löwe, B. (2006) · Archives of Internal Medicine · doi:10.1001/archinte.166.10.1092 · Cited by 31,765 · see citing works
Diagnostic and Statistical Manual of Mental Disorders
(2012) · Springer eBooks · doi:10.1007/springerreference_121117 · Cited by 20,769 · see citing works
Spitzer, R. L. (1999) · JAMA · doi:10.1001/jama.282.18.1737 · Cited by 9,802 · see citing works
Löwe, B., Decker, O., Müller, S., Brähler, E., Schellberg, D., Herzog, W., & Herzberg, P. Y. (2008) · Medical Care · doi:10.1097/mlr.0b013e318160d093 · Cited by 4,527 · see citing works
Hasin, D. S., Stinson, F. S., Ogburn, E., & Grant, B. F. (2007) · Archives of General Psychiatry · doi:10.1001/archpsyc.64.7.830 · Cited by 2,908 · see citing works
Grant, B. F., Stinson, F. S., Dawson, D. A., Chou, S. P., Dufour, M. C., Compton, W., Pickering, R. P., & Kaplan, K. (2004) · Archives of General Psychiatry · doi:10.1001/archpsyc.61.8.807 · Cited by 2,889 · see citing works
Grant, B. F., Goldstein, R. B., Saha, T. D., Chou, S. P., Jung, J., Zhang, H., Pickering, R. P., Ruan, W. J., Smith, S. M., Huang, B., et al. (2015) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2015.0584 · Cited by 2,556 · see citing works
Bovin, M. J., Marx, B. P., Weathers, F. W., Gallagher, M. W., Rodriguez, P., Schnurr, P. P., & Keane, T. M. (2016) · Psychological Assessment · doi:10.1037/pas0000254 · Cited by 2,532 · see citing works
Compton, W. M., Thomas, Y. F., Stinson, F. S., & Grant, B. F. (2007) · Archives of General Psychiatry · doi:10.1001/archpsyc.64.5.566 · Cited by 1,152 · see citing works
Lai, H. M. X., Cleary, M., Sitharthan, T., & Hunt, G. E. (2015) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2015.05.031 · Cited by 941 · see citing works
Grant, B. F., Saha, T. D., Ruan, W. J., Goldstein, R. B., Chou, S. P., Jung, J., Zhang, H., Smith, S. M., Pickering, R. P., Huang, B., et al. (2016) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2015.2132 · Cited by 877 · see citing works
Kocalevent, R.-D., Hinz, A., & Brähler, E. (2013) · General Hospital Psychiatry · doi:10.1016/j.genhosppsych.2013.04.006 · Cited by 748 · see citing works
The comorbidity of depression and substance use disorders
Swendsen, J. (2000) · Clinical Psychology Review · doi:10.1016/s0272-7358(99)00026-4 · Cited by 632 · see citing works
The epidemiology of dual diagnosis
Kessler, R. C. (2004) · Biological Psychiatry · doi:10.1016/j.biopsych.2004.06.034 · Cited by 588 · see citing works
Draine, J., Salzer, M. S., Culhane, D. P., & Hadley, T. R. (2002) · Psychiatric Services · doi:10.1176/appi.ps.53.5.565 · Cited by 480 · see citing works
Medical Morbidity, Mental Illness, and Substance Use Disorders
Dickey, B., Normand, S. T., Weiss, R. D., Drake, R. E., & Azeni, H. (2002) · Psychiatric Services · doi:10.1176/appi.ps.53.7.861 · Cited by 400 · see citing works
Co-occurring disorders in substance abuse treatment: Issues and prospects
Flynn, P. M., & Brown, B. S. (2007) · Journal of Substance Abuse Treatment · doi:10.1016/j.jsat.2006.11.013 · Cited by 180 · see citing works
O’Brien, C. P., Charney, D. S., Lewis, L., Cornish, J., Post, R. M., WOODY, G. E., Zubieta, J., Anthony, J. C., BLAINE, J. D., Bowden, C. L., et al. (2004) · Biological Psychiatry · doi:10.1016/j.biopsych.2004.10.002 · Cited by 139 · see citing works
Chen, K. W., Banducci, A. N., Guller, L., Macatee, R. J., Lavelle, A., Daughters, S. B., & Lejuez, C. W. (2011) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2011.03.003 · Cited by 139 · see citing works
Concurrent Treatment of Substance Use and PTSD
Flanagan, J. C., Korte, K. J., Killeen, T. K., & Back, S. E. (2016) · Current Psychiatry Reports · doi:10.1007/s11920-016-0709-y · Cited by 131 · see citing works
McGovern, M. P., Lambert-Harris, C., Gotham, H. J., Claus, R. E., & Xie, H. (2014) · Administration and Policy in Mental Health and Mental Health Services Research · doi:10.1007/s10488-012-0449-1 · Cited by 126 · see citing works
Delgadillo, J., Payne, S., Gilbody, S., Godfrey, C., Gore, S., Jessop, D., & Dale, V. (2012) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2012.03.011 · Cited by 106 · see citing works
Evaluating the South Oaks Gambling Screen With DSM-IV and DSM-5 Criteria
Goodie, A. S., MacKillop, J., Miller, J. D., Fortune, E. E., Maples, J. L., Lance, C. E., & Campbell, W. K. (2013) · Assessment · doi:10.1177/1073191113500522 · Cited by 78 · see citing works
Self-citationMental health screening in addiction, corrections and social service settings: Validating the MMS
Alexander, M. J., Haugland, G., Lin, S. P., Bertollo, D. N., & McCorry, F. A. (2008) · International Journal of Mental Health and Addiction · doi:10.1007/s11469-007-9100-x · Cited by 71 · see citing works
Symptoms of depression and PTSD are associated with elevated alcohol demand
Murphy, J. G., Yurasek, A. M., Dennhardt, A. A., Skidmore, J. R., McDevitt‐Murphy, M. E., MacKillop, J. M., & Martens, M. P. (2012) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2012.06.022 · Cited by 66 · see citing works
Self-citationTreatment for Substance Use Disorder with Co-Occurring Mental Illness
Iqbal, M. N., Levin, C. J., & Levin, F. R. (2019) · Focus · doi:10.1176/appi.focus.20180042 · Cited by 66 · see citing works
Delgadillo, J., Payne, S., Gilbody, S., Godfrey, C., Gore, S., Jessop, D., & Dale, V. (2011) · Journal of Affective Disorders · doi:10.1016/j.jad.2011.06.017 · Cited by 62 · see citing works
Rush, B. R., Castel, S., Brands, B., Toneatto, T., & Veldhuizen, S. (2012) · Journal of Substance Abuse Treatment · doi:10.1016/j.jsat.2012.08.221 · Cited by 49 · see citing works
Self-citationEack, S. M., Singer, J. B., & Greeno, C. G. (2008) · Community Mental Health Journal · doi:10.1007/s10597-008-9150-y · Cited by 48 · see citing works
Implementing integrated mental health and substance abuse services
Drake, R. E., & Bond, G. R. (2010) · Journal of Dual Diagnosis · doi:10.1080/15504263.2010.540772 · Cited by 37 · see citing works
Unrecognised dual diagnosis—A risk factor for dropout of addiction treatment
Schulte, S. J., Meier, P. S., Stirling, J., & Berry, M. (2010) · Mental Health and Substance Use · doi:10.1080/17523281003705199 · Cited by 25 · see citing works
Strathdee, G., Manning, V., Best, D. W., Keaney, F., Bhui, K. S., Witton, J., Wall, S., McGillivray, L., Marsden, J., Johnson, F., et al. (2005) · Research Portal (King's College London) · Cited by 22 · see citing works
Comorbidity and “Self-Medication”
DuPont, R. L., & Gold, M. S. (2007) · Journal of Addictive Diseases · doi:10.1300/j069v26s01_03 · Cited by 14 · see citing works
Castel, S., Rush, B. R., & Scalco, M. Z. (2007) · International Journal of Mental Health and Addiction · doi:10.1007/s11469-007-9096-2 · Cited by 9 · see citing works
Self-citationUsing Big Data to Determine Reference Values for Laboratory Tests—Reply
Manrai, A. K., Patel, C. J., & Ioannidis, J. P. A. (2018) · JAMA · doi:10.1001/jama.2018.10956 · Cited by 3 · see citing works
Addiction Assessment and Treatment Planning: Developing Countries
Clark, N. C., & Uchtenhagen, A. (2015) · Zurich Open Repository and Archive (University of Zurich) · doi:10.5167/uzh-108923 · Cited by 2 · see citing works
Addiction Assessment and Treatment Planning: Developing Countries
Clark, N. C., & Uchtenhagen, A. (2014) · Springer eBooks · doi:10.1007/978-88-470-5322-9_139 · Cited by 2 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- MacKillop, 2016, Concurrent substance use disorders and PTSD in an inpatient addiction treatment program in Canada, Canadian Journal of Addiction, 7, 33
Cited by
Sorted by citations
Forkus, S. R., Raudales, A. M., Rafiuddin, H. S., Weiss, N. H., Messman, B. A., & Contractor, A. A. (2023) · Clinical Psychology: Science and Practice · doi:10.1037/cps0000111 · Cited by 262 · see citing works
Hazardous drinking and alcohol use disorders
MacKillop, J. M., Agabio, R., Ewing, S. W. F., Heilig, M. A., Kelly, J. F., Leggio, L., Lingford-Hughes, A. R., Palmer, A. A., Parry, C. D. H., Ray, L. A., et al. (2022) · Nature Reviews Disease Primers · doi:10.1038/s41572-022-00406-1 · Cited by 235 · see citing works
Self-citationBentley, K. H., Sakurai, H., Lowman, K. L., Rines-Toth, L., McKowen, J. W., Pedrelli, P., Evins, A. E., & Yule, A. M. (2021) · Journal of Affective Disorders · doi:10.1016/j.jad.2021.01.005 · Cited by 51 · see citing works
Aktürk, Z., Hapfelmeier, A., Fomenko, A., Dümmler, D., Eck, S., Olm, M., Gehrmann, J., von Schrottenberg, V., Rehder, R., Dawson, S., et al. (2025) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd015455 · Cited by 50 · see citing works
Beyond one-cutoff-fits-all: determining cutoff values for the PTSD checklist for DSM-5 (PCL-5)
Pettrich, A., Schellong, J., Dyer, A., Ehring, T. W., Knaevelsrud, C., Krüger-Gottschalk, A., Nesterko, Y., Schäfer, I., & Glaesmer, H. (2025) · European Journal of Psychotraumatology · doi:10.1080/20008066.2025.2514878 · Cited by 20 · see citing works
Park, S., & Park, S. K. (2025) · Journal of Affective Disorders · doi:10.1016/j.jad.2025.119913 · Cited by 19 · see citing works
Gendy, M. N. S., Taisir, R., Sousa, S., Costello, M. J., Rush, B. R., Busse, J. W., & MacKillop, J. M. (2023) · Addictive Behaviors · doi:10.1016/j.addbeh.2023.107667 · Cited by 19 · see citing works
Self-citationWalji, A., Romano, I., Levitt, E. E., Sousa, S., Rush, B. R., MacKillop, J. M., Urbanoski, K. A., & Costello, M. J. (2021) · Drug and Alcohol Dependence Reports · doi:10.1016/j.dadr.2021.100014 · Cited by 10 · see citing works
Self-citationOddo, L. E., Acuff, S. F., Arenson, M. B., Oshri, A., Chronis-Tuscano, A. M., MacKillop, J. M., & Murphy, J. G. (2021) · Alcohol and Alcoholism · doi:10.1093/alcalc/agab070 · Cited by 9 · see citing works
Self-citationMinhas, M., Cooper, A., Sousa, S., Costello, M. J., & MacKillop, J. M. (2022) · Substance Abuse Research and Treatment · doi:10.1177/11782218221126977 · Cited by 9 · see citing works
Self-citationUsing Measurement-Based Care as a Precision Medicine Strategy for Substance Use Disorders
Samokhvalov, A. V., Levitt, E. E., & MacKillop, J. M. (2024) · Current Psychiatry Reports · doi:10.1007/s11920-024-01495-3 · Cited by 8 · see citing works
Self-citationWalter, Z. C., Carlyle, M., Mefodeva, V., Glasgow, S., Newland, G., Nixon, R. D. V., Cobham, V. E., & Hides, L. M. (2024) · Journal of Substance Use and Addiction Treatment · doi:10.1016/j.josat.2024.209571 · Cited by 7 · see citing works
Halladay, J., Stead, V., McCarron, C., Kennedy, M., King, K., Venantius, M., Carter, A., Syan, S., Matthews, M., Khoshroo, S., et al. (2022) · medRxiv · doi:10.1101/2022.10.21.22281362 · Cited by 5 · see citing works
“that have been successfully deployed in similar clinical settings (71-73).”
Self-citationCoeur, E., Giaufer, C., Robert, P. H., & Corveleyn, X. (2025) · Journal of Affective Disorders · doi:10.1016/j.jad.2025.120484 · Cited by 5 · see citing works
Andersson, H. W., Nordfjærn, T., & Mosti, M. P. (2024) · Nordic Journal of Psychiatry · doi:10.1080/08039488.2024.2323124 · Cited by 4 · see citing works
Hazardous drinking and alcohol use disorders
(2022) · Nature Reviews Disease Primers · doi:10.1038/s41572-022-00414-1 · Cited by 4 · see citing works
Sistad, R. E., Kimerling, R. E., Schnurr, P. P., & Bovin, M. J. (2023) · Journal of Traumatic Stress · doi:10.1002/jts.22999 · Cited by 3 · see citing works
Faridi, A., Taremian, F., & Thatcher, R. W. (2024) · Clinical EEG and Neuroscience · doi:10.1177/15500594241229194 · Cited by 3 · see citing works
Ath-Thulab Al-Qulqun li Ta'allum Al-Lughat Al-Ajnabiyah fi Indonesia
Fakhrurrozy, M. I., Amrullah, M. K., & Dey, M. (2023) · An-Nabighoh Jurnal Pendidikan dan Pembelajaran Bahasa Arab · doi:10.32332/an-nabighoh.v25i1.5834 · Cited by 2 · see citing works
Britton, E. M., Taisir, R., Cooper, A., Remers, S., Chorny, Y., LaBelle, O. P., Rush, B. R., MacKillop, J. M., & Costello, M. J. (2023) · Assessment · doi:10.1177/10731911231217478 · Cited by 2 · see citing works
Self-citationGarber, M. L., Samokhvalov, A. V., Chorny, Y., LaBelle, O. P., Rush, B. R., Costello, M. J., & MacKillop, J. M. (2025) · Addiction · doi:10.1111/add.70037 · Cited by 2 · see citing works
Self-citationGendy, M. N. S., Remers, S., Samokhvalov, A. V., Sousa, S., Rush, B. R., Costello, M. J., & MacKillop, J. (2024) · Substance Use & Misuse · doi:10.1080/10826084.2024.2352604 · Cited by 1 · see citing works
Self-citationRasch analysis of DSM ‐5 alcohol use disorder in a large inpatient sample
Britton, E. M., Taisir, R., Remers, S., Chorny, Y., Gendy, M. N. S., Costello, M. J., Rush, B. R., & MacKillop, J. M. (2025) · Alcoholism Clinical and Experimental Research · doi:10.1111/acer.70029 · Cited by 1 · see citing works
Self-citationHowry, S. K., Vogt, M. L., Kim, B. L., Bennett, E., IV, Cain, M. D., & Thyer, B. A. (2025) · Journal of Human Behavior in the Social Environment · doi:10.1080/10911359.2025.2499657 · Cited by 1 · see citing works
Pejic, S. R., Snaychuk, L. A., Swan, S., Thulin, M. C., Basedow, C. A., & Ornstein, T. J. (2026) · Substance Use & Misuse · doi:10.1080/10826084.2026.2648153 · Cited by 1 · see citing works
Gendy, M. N. S., Remers, S., Costello, M. J., Rush, B. R., & MacKillop, J. M. (2024) · PLOS mental health. · doi:10.1371/journal.pmen.0000074 · Cited by 1 · see citing works
Self-citationBritton, E. M., Taisir, R., Cooper, A., Li, Y., Sousa, S., Chorny, Y., MacKillop, J. M., & Costello, M. J. (2024) · Cannabis · doi:10.26828/cannabis/2024/000260
Self-citationSunderland, M., Halladay, J. E., & Chapman, C. (2024) · Journal of Psychopathology and Behavioral Assessment · doi:10.1007/s10862-024-10181-w
Adhikari, A. A. D. N. W., Bhatta, K., Parajuli, S., & Kaphle, H. P. (2025) · Mental Illness · doi:10.1155/mij/4778500
Courchesne‐Krak, N. S., Chandrasekaran, A. R., Gonzalez, J., Bianchi, S. B., Tran, V., Johnson, E. O., Troiani, V., Hettema, J. M., Stein, M. B., Coon, H. H., et al. (2025) · Complex Psychiatry · doi:10.1159/000546389
Self-citationPérez-Gutiérrez, A. M., Flórez, G., Blanco, V., Vázquez, F. L., Abellí‐Deulofeu, E., Ortega, L., Serrano, A., Árias, F., Navarrete, F., Fonseca, F., et al. (2025) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2025.112877
MacKillop, J. M., McIntyre‐Wood, C., Vandehei, E., Yaya, H., Passa, A.-M. D., Prokop-Millar, S., Fein, A. J., Yang, A., Elsayed, M., Schwartzmann, B., et al. (2026) · Neuromodulation Technology at the Neural Interface · doi:10.1016/j.neurom.2026.01.003
Self-citationHuang, Y., Chong, Z. Y., Dou, Z., Lo, H., Wang, S., & Xu, W. (2026) · Behaviour Research and Therapy · doi:10.1016/j.brat.2026.105020
Kokatnur, V. M., Dawood, T., Pais, K. P., Malik, Y. R., Muddebihal, F., Preethanath, R. S., Babu, J. S., Swarnalatha, C., & Nayyar, A. S. (2026) · International Journal of Preventive Medicine · doi:10.4103/ijpvm.ijpvm_94_25
Halladay, J. E., Gendy, M. N. S., Little, Hira, V., Taisir, R., Rahman, L., Britton, E. M., Shantz, R. N., Levitt, E. E., Amlung, M. T., et al. (2026) · Substance Use & Misuse · doi:10.1080/10826084.2026.2670633
Self-citation
- Authors
- Levitt, E. E., Syan, S. K., Sousa, S., Costello, M. J., Rush, B., Samokhvalov, A. V., McCabe, R. E., Kelly, J., & MacKillop, J.
- Affiliations
- Homewood Research Institute (CA)
- Centre for Addiction and Mental Health (CA)
- Peter Boris Centre for Addictions Research (CA)
- Massachusetts General Hospital (US)
- Corresponding author
- MacKillop, J.
- ORCID
- Venue
- Addictive Behaviors
- Publisher
- Elsevier BV
- Published
- 2021-01
- Volume
- 112
- Pages
- 106649
- ISSN
- 0306-4603 (ISSN-L)
- PMC
- PMC11381827
- OpenAlex
- W3084264499
- Cited by
- 35
- References
- 40
- Citations by year
- 2026: 5 · 2025: 10 · 2024: 8 · 2023: 4 · 2022: 5 · 2021: 3
- FWCI
- 2.90
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Addictive Behaviors (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Alcohol Abuse and Alcoholism
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Health Sciences › Medicine › Epidemiology › Substance Abuse Treatment and Outcomes
- Social Sciences › Psychology › Social Psychology › Mental Health Treatment and Access
- Keywords
- depression screening, substance use disorders, inpatient addiction treatment, screening cut-off values, PHQ-9, GAD-7, PCL-5, comorbidities, diagnostic accuracy, negative affectivity
- MeSH terms
- Anxiety Disorders, Depression, Humans, Inpatients, Mass Screening, Ontario, Psychometrics, Sensitivity and Specificity, Stress Disorders, Post-Traumatic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read under definition version 3 (extract-v3) on 2026-09-28.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-09-28.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review