Screening and Measurement

Primary care clinicians are taught to engage in a complex process of clinical reasoning to identify illness. This process is no different for mental health conditions.

In the clinical assessment tool kit is an understanding of the epidemiology of diagnoses, awarenss of the range of diagnostic candidates, and a host of available tests and knowledge of test characteristics. 

Screening tools improve both the efficiency and comprehensiveness of the clinical encounter and are increasingly linked to value-based care. In this section we cover formalized screening procedures and tools used for specific disorders. 


Evidence Based Assessment

Pediatricians think statistically and sequentially, adding assessment information, weighing dynamic factors, and applying a clinical decision making model. 


The Evidence Based Assessment model provides clear steps to the process of prediciting, prescribing treatment, and tracking the progress.


Steps 1 and 2 in Evidence Based assessment is identifying the prevelance or base rate of disorders. This graph includes the common disorders, with data compiled from multiple sources (Breslau et al., 2017; Francés et al., 2022; Kessler et al., 2005; Merikangas et al., 2010; Patel et al., 2018; Solmi et al., 2021). 


Step 3 of the Evidence Based Assessment Model should include weighing known risk factors that migth increase the liklihood of disorder. Family mental history is very important to ask about because of elevated genetic and correlated enviormental factors.

Parental history of any psychiatric diagnosis is associated with increased incidence rates of mental illness. Odds Ratios (OR) indicate elevated risk of disorder in youth with parents with history of illness. Reported OR for common disorders include ADHD (4-9 OR), Anxiety Disorder (2-6 +OR), and Depression (3-13 +OR) (Martin et al. 2018; Rappe et al 2012; Telman et al. 2017; Rice et al. 2012).


Step 4, 5, and 6 Typically, our team recommends using a broad mental health measure built to detect multiple conditions. If there is elevated concern, a targeted measure for a specific condition (e.g. anxiety, depression) would be employed. This is called sequential screening and it essentially zeros in on a subgroup of a population through a brief set of consecutive screens, reducing the likelihood of false positives and false negatives. 

Next we'll identify measures and psychometric properties to support implementation in the pediatric practice. 


Broad Measures

Broad measures screen for multiple mental health symptoms and are optimally employed as an initial measure that might detect possible concerns. Positive results should received subsequent targeted screening related to specific concerns. 

Measure Informant Cut-offs Sensitivity/Specificity

Patient Symptom Checklist – 17
Age 4-17
Items 17

Total Score:    ≥ 15
Internalizing:  ≥ 5
Externalizing:  ≥ 7
Attention:       ≥ 7
Total Score:     73%/74%
Internalizing:   52%/74%
Externalizing:   62%/89%
Attention:        59%/91%

Strengths and Difficulties Questionnaire (SDQ) 
Age 2-18+
Items 25

Total Score:        ≥ 15
Emotional (Anx): ≥ 5
Conduct (ODD):  ≥ 3
Conduct (CD):    ≥ 4
Inattention/HI:   ≥ 6
Total Score:         81%/42%
Emotional (Anx):  75%/51%
Conduct (ODD):   84%/66%
Conduct (CD):     89%/63%
Inattention/HI:    95%/32%

ADHD Tools

Here are freely available targeted measures developed to assess ADHD and Oppositional Defiant Disorder/Conduct Disorder

Measure Informant Cut-offs Sensitivity/Specificity
SNAP-IV
Items: 26
Age: 6-18

Parent or Teacher

ADHD IN:  Parent > 2.56; Teacher > 1.78

ADHD H/I: Parent > 1.78; Teacher > 1.44

ADHD CT:  Parent > 2.00; Teacher > 1.67

ODD:        Parent > 1.38; Teacher > 1.88

Summed scale score, divided number of items in scale

 
NICHQ Vanderbilt
Items: 55 (P), 44 (T)
Age: 6-12

Parent

Teacher

ADHD Combined: > 6

ODD Total: > 10

ADHD Combined: 67%/86%

ODD Total:          88%/85%

Note: NICHQ Parent Vanderbilt positive cutoff requires 6 of 18 items on the Combined Inattention/Hyperactivity scale be recorded as 2 or 3 and at least one 4 or 5 rating on the performance scale

Anxiety Tools

Targeted anxiety measures free for use. 

Measure Informant Cut-offs Sensitivity
Screen for Child Anxiety and Related Disorders (SCARED)
Items: 41
Age: 8-17
Total Score:  ≥ 25
Panic:  ≥ 7
GAD:  ≥ 9
Separation Anx:  ≥ 5
Social Anx: ≥ 8
School Avoidance: ≥ 3

Parent Total:  65%/99%
Parent GAD:   77%/90%
Parent Social: 79%/92%

Youth Total:   64%/92%
Youth GAD:   54%/91%
Youth Social: 64%/84%

SPENCE Child Anxiety
Items: 44
Age: 3-6; 8-15
T Score:  ≥ 60
(T-Score, M = 50; SD 10)
 
Generalized Anxiety Disorder (GAD-7)
Items: 7
Age: 12+
Total Score: ≥ 10  
Patient Reported Outcomes Measurement System - Fixed Length Short Form (V2)
Items:
Age: 5-17
Parent T-Score:  ≥ 62
Youth T-Score:    ≥ 63
(T-Score, M = 50; SD 10)
 

Depression Tools

Here are targeted depression measures that are free for use. 

Measure Informant Cut-offs Sensitivity/Specificity

Short Moods & Feelings Questionnaire (SMFQ)

Items: 13 
Age: 8-18

Total Score: ≥ 11 Parent Total: 65%/99%
Youth Total:  64%/92%

Patient Health Questionnaire
(PHQ-9)

Items: 9
Age: 11+

T Score: ≥11 89.5%/77.5%

Patient Reported Outcomes Measurement System (PROMIS - Depression)

Items: 8 (6)
Age: 5-17

Parent T-Score:  ≥ 60.5
Youth T-Score:    ≥ 62.5

(T-Score, M = 50; SD 10)

 

Other Targeted Tools

Freely available targeted screening for primary care.

Measure Informant Domain Cut-offs Sensitivity/
Specificity

Ask Suicide Questionnaire (ASQ -4)

Items: 4
Age: 10-18

Suicidality Any "Yes" response results in further assessment  100%/87.9%

Columbia Suicide Severity Risk Scale (Primary Care)

Items: 2+
Age: 10-18

Suicidality  Any "Yes" response results in further assessment   

CRAFFT 2.1

Items: 9
Age: 12-21

Substance Use/
Abuse
T Score : ≥2 Any substance use disorder: 76%/94%

Screening to Brief Intervention (S2BI)

Items: 9
Age: 12-17

Substance Use/
Abuse
Affirmative response to frequency in past year Any substance use disorder: 90%/94%

Brief Screener for Tobacco, Alcohol, and other Drugs (BSTAD)

Items: 5+
Age: 12-17

Substance Use/Abuse Risk of use of alcohol, tobacco, and marijuana 

≥6 days of tobacco use 95%/97%
≥2 days of alcohol use 96%/85%
≥2 days of marijuana use 80%/93%

Eating Attitudes Test-26

Items: 26
Age: 8-13

Disordered Eating Total Score: ≥20  

References

  • Bard, D. E., Wolraich, M. L., Neas, B., Doffing, M., & Beck, L. (2013). The psychometric properties of the Vanderbilt attention-deficit hyperactivity disorder diagnostic parent rating scale in a community population. Journal of Developmental and Behavioral Pediatrics: JDBP, 34(2), 72–82. https://doi.org/10.1097/DBP.0b013e31827a3a22
  • Becker, S. P., Langberg, J. M., Vaughn, A. J., & Epstein, J. N. (2012). Clinical Utility of the Vanderbilt ADHD Diagnostic Parent Rating Scale Comorbidity Screening Scales. Journal of Developmental and Behavioral Pediatrics, 33(3), 221–228. https://doi.org/10.1097/DBP.0b013e318245615b
  • Birmaher, B., Khetarpal, S., Brent, D., Cully, M., Balach, L., Kaufman, J., & Neer, S. M. (1997). The Screen for Child Anxiety Related Emotional Disorders (SCARED): Scale construction and psychometric characteristics. Journal of the American Academy of Child and Adolescent Psychiatry, 36(4), 545–553. https://doi.org/10.1097/00004583-199704000-00018
  • Breslau, J., Gilman, S. E., Stein, B. D., Ruder, T., Gmelin, T., & Miller, E. (2017). Sex differences in recent first-onset depression in an epidemiological sample of adolescents. Translational Psychiatry, 7(5), e1139. https://doi.org/10.1038/tp.2017.105
  • Costello, E. J. (2016). Early Detection and Prevention of Mental Health Problems: Developmental Epidemiology and Systems of Support. Journal of Clinical Child & Adolescent Psychology, 45(6), 710–717.
  • Francés, L., Quintero, J., Fernández, A., Ruiz, A., Caules, J., Fillon, G., Hervás, A., & Soler, C. V. (2022). Current state of knowledge on the prevalence of neurodevelopmental disorders in childhood according to the DSM-5: A systematic review in accordance with the PRISMA criteria. Child and Adolescent Psychiatry and Mental Health, 16(1), 1–15. https://doi.org/10.1186/s13034-022-00462-1
  • Kelly, S. M., Gryczynski, J., Mitchell, S. G., Kirk A., O'Grady, K. E., Schwartz, R. P.. (2014) Validity of brief screening instrument for adolescent tobacco, alcohol, and drug use. Pediatrics. 133(5):819-26. doi: 10.1542/peds.2013-2346. PMID: 24753528; PMCID: PMC4006430.
  • Kessler, R. C., Coccaro, E. F., Fava, M., Jaeger, S., Jin, R., & Walters, E. (2006). The Prevalence and Correlates of DSM-IV Intermittent Explosive Disorder in the National Comorbidity Survey Replication. Archives of General Psychiatry, 63(6), 669–678. https://doi.org/10.1001/archpsyc.63.6.669
  • Knight, J. R., Sherritt, L., Shrier, L. A., Harris, S. K., & Chang, G. (2002). Validity of the CRAFFT Substance Abuse Screening Test Among Adolescent Clinic Patients. Archives of Pediatrics & Adolescent Medicine, 156(6), 607–614. https://doi.org/10.1001/archpedi.156.6.607
  • Levy, S., Weiss, R., Sherritt, L., Ziemnik, R., Spalding, A., Van Hook, S., & Shrier, L. A. (2014). An electronic screen for triaging adolescent substance use by risk levels. JAMA Pediatrics. 168(9), 822-828.
  • Martin, J., Walters, R. K., Demontis, D., Mattheisen, M., Lee, S. H., Robinson, E., Brikell, I., Ghirardi, L., Larsson, H., Lichtenstein, P., Eriksson, N., Werge, T., Mortensen, P. B., Pedersen, M. G., Mors, O., Nordentoft, M., Hougaard, D. M., Bybjerg-Grauholm, J., Wray, N. R., … Neale, B. M. (2018). A Genetic Investigation of Sex Bias in the Prevalence of Attention-Deficit/Hyperactivity Disorder. Biological Psychiatry, 83(12), 1044–1053. https://doi.org/10.1016/j.biopsych.2017.11.026
  • Meehl, P. E. (1954). Clinical versus statistical prediction: A theoretical analysis and a review of the evidence (pp. x, 149). University of Minnesota Press.
  • Merikangas, K. R., He, J.-P., Burstein, M., Swanson, S. A., Avenevoli, S., Cui, L., Benjet, C., Georgiades, K., & Swendsen, J. (2010). Lifetime prevalence of mental disorders in U.S. adolescents: Results from the National Comorbidity Survey Replication--Adolescent Supplement (NCS-A). Journal of the American Academy of Child and Adolescent Psychiatry, 49(10), 980–989. https://doi.org/10.1016/j.jaac.2010.05.017
  • Murphy, J. M., Bergmann, P., Chiang, C., Sturner, R., Howard, B., Abel, M. R., & Jellinek, M. (2016). The PSC-17: Subscale Scores, Reliability, and Factor Structure in a New National Sample. Pediatrics, 138(3). https://doi.org/10.1542/peds.2016-0038
  • Rhew, I. C., Simpson, K., Tracy, M., Lymp, J., McCauley, E., Tsuang, D., & Stoep, A. V. (2010). Criterion validity of the Short Mood and Feelings Questionnaire and one- and two-item depression screens in young adolescents. Child and Adolescent Psychiatry and Mental Health, 4(1), 8. https://doi.org/10.1186/1753-2000-4-8
  • Richardson, L. P., McCauley, E., Grossman, D. C., McCarty, C. A., Richards, J., Russo, J. E., Rockhill, C., & Katon, W. (2010). Evaluation of the Patient Health Questionnaire (PHQ-9) for Detecting Major Depression among Adolescents. Pediatrics, 126(6), 1117–1123. https://doi.org/10.1542/peds.2010-0852
  • Solmi, M., Radua, J., Olivola, M., Croce, E., Soardo, L., Salazar de Pablo, G., Il Shin, J., Kirkbride, J. B., Jones, P., Kim, J. H., Kim, J. Y., Carvalho, A. F., Seeman, M. V., Correll, C. U., & Fusar-Poli, P. (2021). Age at onset of mental disorders worldwide: Large-scale meta-analysis of 192 epidemiological studies. Molecular Psychiatry, 1–15. https://doi.org/10.1038/s41380-021-01161-7
  • Spence, S. H., Rapee, R., McDonald, C., & Ingram, M. (2001). The structure of anxiety symptoms among preschoolers. Behaviour Research and Therapy, 39(11), 1293–1316. https://doi.org/10.1016/s0005-7967(00)00098-x
  • Telman, L. G. E., van Steensel, F. J. A., Maric, M., & Bögels, S. M. (2018). What are the odds of anxiety disorders running in families? A family study of anxiety disorders in mothers, fathers, and siblings of children with anxiety disorders. European Child & Adolescent Psychiatry, 27(5), 615–624. https://doi.org/10.1007/s00787-017-1076-x
  • Wolraich, M. L., Bard, D. E., Neas, B., Doffing, M., & Beck, L. (2013). The psychometric properties of the Vanderbilt attention-deficit hyperactivity disorder diagnostic teacher rating scale in a community population. Journal of Developmental and Behavioral Pediatrics: JDBP, 34(2), 83–93. https://doi.org/10.1097/DBP.0b013e31827d55c3
  • Youngstrom, E. A., & Van Meter, A. (2016). Empirically supported assessment of children and adolescents. Clinical Psychology: Science and Practice, 23(4), 327–347. https://doi.org/10.1037/h0101738