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Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Not all that blows up is bipolar (but some of it is!) Evidence-based assessment and treatment for bipolar disorders in youths and young adults

Eric Youngstrom, Ph.D.

UNC Chapel Hill USA

Disclosures

 NIH R01 MH066647 (PI: E. Youngstrom)  NIH R01 MH073967 (PI: R.L. Findling)  E. Youngstrom has consulted with Pearson,

Lundbeck, Otsuka, Janssen, Western Psychological Services about assessment

 Chief Scientific Officer for Joe Startup

Technologies, LLC

 No speakers bureaus, pharma supported

talks, stock ownership, test sales….

Objectives

 Learn base rates in different settings, such as public

schools, outpatient services, forensic settings, and inpatient units; and how to use these benchmarks to evaluate efficiently

 Use assessment procedures to aid in differential

diagnosis and measuring response to treatment

 Apply new methods for interpreting test results,

including methods taking into account clinical settings where we work

Shortcuts to work faster! Be more accurate! Get better results!

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Handout Handout What do you think is going on?

 Diagnosis?  What’s your assessment plan?  Treatment options?

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Teasers

 One will have “classic” bipolar I  One won’t have any mood disorder

(and we won’t discuss a lot further)

 One will die over the course of the

history we know

Lea

Stressed out senior?

 18 yo WF  Middle of senior year  Coming to outpatient clinic  Presenting problem:

 Trouble with attention

 Can’t stay focused  Grades dropping

 Getting anxious and stressed about graduating

(and if she’ll graduate)

Christopher

Going off the rails?

 14 year old white male  Smart, skipped grade, popular  Changed clothes, music  Started “hooking up” with older brother’s

female friends

 Now tired, missing school for weeks at a time

What’s you diagnostic hypothesis at this point?

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

DeShawn

The Boy Who Blows Up

 7 year old black male  referred because of extreme

aggression and distractibility, motor agitation at school

 Dad has been diagnosed with Bipolar I and

treated for several years with lithium and divalproex. What’s you diagnostic hypothesis at this point? Chances of bipolar?

Tamika

From Grouchy to Kaboom!

 11 y.o. black female, regular ed.  Increased anger, aggression, being “hyper,” having

trouble sleeping, lying, talking to herself, and stealing.

 Tantrums: screamed, threw things, broke a plate

and some toys… mom worried she might hurt someone.

 Now lower grades and disruptive in class - talking

• ut, easily distracted, arguing with peers & teachers.

Overwhelming amounts

• f new data

 Medical information now

doubles every 5 years

 Cochrane estimates that

<20% of clinical decisions evidence based

 IBM estimates that <20% of

information guiding decisions is evidence based

 81% of physicians report

<=5 hours per month reading journals <2% of published data are both reliable and would change clinical care

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Leaky Pipeline

Aware Accept Target Doable Recall Agree Done Valid Research

If 80% achieved at each stage then .8 x .8 x .8 x .8 x .8 x .8 x .8 = 21% delivered!

Early 1990s

 Where were you?  (Working on master’s thesis)  First modern “sightings” of pediatric bipolar  Geller 1993 Depression Trial  Wozniak 1995 JAACAP paper

(ADHD sample)

 1999 Papolos book

Pediatric Bipolar: More than 10,000 articles (590 in 2014 alone)

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

The Evidence Base May 2018

100 200 300 400 500 600

1950 1970 1990 2010 Count of PubMed Indexed Citations

PBD DMDD/SMD

• Poly. (PBD)

SMD/DMDD 147 hits Pediatric Bipolar 10,361 hits

500+ new articles each year: textbooks are out of date as soon as they are published

Comparing the Evidence Base October 2013 (~DSM-5)

MeSH Filter Pediatric Bipolar SMD/DMDD Total Citations

7606 56

“Clinical Trial”

729 7

Free Full Text

784 3

Review

811 4

Meta-analysis

48

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Revolutionary changes in knowledge of bipolar

What we used to think:

 Rare (~1% of adults)  R-Rated (onset after 18)  Severe  Treatment is medication  Incurable

What we are learning:

 More common (~4% of adults  More than 50% have mood

• nset in childhood &

adolescence

 Spectrum of presentations  Full range of treatments  Survivable and “thrivable”

Conventional Wisdom

 Adult disorder, with median age of

• nset around 18-20 years

 Distinct mood episodes  Good functioning before illness and

between episodes

 “Touched with Fire” – creativity and

productivity during hypomania

The Gift

 Many famous artists, musicians, and

politicians are likely to have had bipolar disorder

 Composers: Handel, Schumann, Schubert;

Charlie Mingus, Charlie Parker, Bud Powell…

 Artists: Jackson Pollak…  Poets: Sylvia Plath, Anne Sexton, Dylan

Thomas…

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

The cost:

 7th leading cause of disability in the world,

ahead of all other mental illnesses except depression (Murray & Lopez, 1996; Lopez et al., 2006)

 Increased substance abuse  Increased incarceration  One of the leading causes of suicide

 18% of adults with bipolar end own life

Changes in Rate of Mood, Schizophrenia Diagnoses

Stoll, A., Tohen, M., et al. (1993) AJP

DSM-III DSM-II DSM-III-R

Increase in diagnosis of BD in youth

Moreno et al., 2007 40-fold increase in rate of dx DSM-III-R DSM-IV (adds II, NOS) DSM-5 ?????

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

1% 32% 42% 78%

Risk factors may vary by region: DRD4 Gene Genetic “Iceberg”

Recognized (Bipolar I, II) Spectrum (missed bipolar I & II; Cyclothymia, NOS) Unimpaired (low loading, high functioning family members, “hyperthymic”)

Challenges to “Adults Only” Rating

 Age of onset appears to be earlier than

previously thought (median of 18 means 50% were 18 or younger)

 Some data suggest progressively earlier age

• f onset since WW II (genetic anticipation?)

 Epidemiological studies appear to be

underestimating prevalence in adults, especially for “softer spectrum” bipolar

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Obesity and bipolar disorder

 Obesity associated with bipolar

independent of medication effects

 Inflammatory response  Obesity driving down age of puberty

 20% of 8 year old girls in USA

 Hormonal changes associated with

mood now happening out of step with brain development

Other reasons for changes in rate of bipolar

 Better assessment  Greater awareness  …but could be expansion of category

 Diagnostic stretch (“use drug before it

stops working”)

 Disease mongering

Meta-Analysis of Child Epidemiological Studies

 How common is the bipolar spectrum in

youths around the world?

 Is the rate increasing in the community

• ver the same time frame that clinical

diagnosis has changed?

 Is it more common in the USA than the

rest of the world?

Van Meter, Moreira, & Youngstrom (2011) J Clin Psychiatry

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

No increase in rate of bipolar in community samples

Prevalence

• f Bipolar

Spectrum

Van Meter, Moreira, & Youngstrom, 2011, J Clin Psychiatry

No difference USA rate

• vs. World

Non-USA USA

USA not driving increase

• f PBD

1.9% 1.8% 2.8% 2.4% 0% 1.2% 2.5%

DSM Bipolar I is most heavily researched, greatest validity

“Narrow” BP-I (DSM-IV) BP-II Cyclothymia??? Bipolar NOS Only if elated or grandiose “Intermediate” “Broad” Severe Mood Dysreg. (SMD) Youngstrom (2009) CP:SP

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Anxiety Depression Mania ADHD CD/APD Substances Psychoses Dysthymia OCD Eating D/O Impulse D/O Childhood Environ Pre- & Peri-Natal TBI Sleep Genes Mood Genes Acute Trauma Stress

Bipolar: Many roots, many branches Review of Bipolar Diagnoses

 Two stage process:

 Diagnose mood episodes first  Then make mood disorder diagnosis

“Life time mood Bingo!”

Difficulties in Diagnosis – All Ages

 Complicated criteria – mood states +

diagnostic categories

 Symptom overlap with more common

diagnoses

 Moving target – changing mood states  Hypomania feels good

(not going to seek treatment)

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Mood States

 Depression  Euthymia  Hypomania  Mania  Mixed States* * DSM-5 proposes to change this to a specifier

Euthymia

 Not a mood episode  Mood functioning is “within normal

limits”

 May characterize functioning before or

between mood episodes

Depression

 2+ week duration  5 or more of:

 Depressed mood (can be irritable mood in youths),

loss of interest, sig. weight loss/gain, sleep disturbance, psychomotor agitation/retardation, fatigue/loss of energy, worthlessness/excessive guilt, poor concentration, thoughts of suicide/death

 Causes impairment & distress  Rule out bereavement, mixed state, substance

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Mania

 A distinct period of abnormally & persistently

elevated, expansive, or irritable mood [and goal directed activity or energy]

 Must last at least one week

[most of day, nearly every day]

 …unless psychiatrically hospitalized for behavior

 Rule out mixed episode, substance induced,

general medical condition

 Must cause marked impairment

Symptoms of Mania (cont.)

 3 of following (4 if mood is only irritable):

 inflated self-esteem/grandiosity,  decreased need for sleep,  pressured speech,  racing thoughts,  distractibility,  increased goal-directed activity,  excessive risky [but fun] activity

DSM-5 changes: Mania

 Emphasizes change in energy in A criterion

 “abnormally and persistently increased goal-

directed activity or energy”

 Clarifications:

 “Most of the day, nearly every day” – doesn’t

need to be 24/7

 “Noticeable change” applies to all symptoms  Deleted “pleasurable”  Emphasize episodicity

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Hypomania

 Distinct period of elevated, expansive, or

irritable mood [and energy/activity] – clearly different from normal for that person

 Duration at least 4 days  3 or more (4 if only irritable mood) manic sx  Unequivocal change in functioning

• bservable by others

 NOT severe enough to cause marked

impairment (no hospitalization, no psychosis)

DSM-5 changes: Hypomania

 Same as for mania  Continued debate about duration of 4 days

• vs. 2 days

 Now can use mixed specifier  Clarifies that psychosis automatically

upgrades to mania

Mixed [Episodes]

 Meet criteria for both manic and depressed

episodes

 Except duration of depression need only be

• ne week

 Severe, causing marked impairment  Rule out substance induced, general

medical condition, etc.

 DSM-5 dropped “episode” and made

“mixed” a specifier

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

DSM5 “Mixed Specifier”

 Meet criteria for both hypomanic and

depressed episodes

 Exact criteria attempt to emphasize non-

shared symptoms

 Rule out substance induced, general

medical condition, etc.

Other DSM-5 Specifiers

 With anxious distress  With mixed features  With rapid cycling  With melancholic features  With atypical features  With mood-congruent psychotic features  With mood-incongruent psychotic features  With catatonia  With peripartum onset  With seasonal pattern

Mixed State

 “Black Mania” (Kay Redfield Jamison)  Depression plus energy and agitation

and intensity

 Can also be volatile & shifting

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Chocolate Milk vs. Fudge Ripple “Mixed”

Distinct State Ultradian Cycling

Which episodes has DeShawn had?

 Manic episode  Hypomanic episode  Major depressive episode  Euthymia  Cyclothymic episode?

DSM-IV & 5 Diagnoses

 Bipolar I  Bipolar II  Cyclothymia  Bipolar Not Otherwise Specified

 [=“Other Specified” in DSM-5]

 Substance Induced Mania

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Bipolar I

 Considered most serious diagnosis  Only requires manic or mixed episode

(can diagnose even if never depressed)

 “Rapid cycling”:

four or more mood episodes per year

Bipolar II – a type of depression

 Requires combination of hypomania +

a major depressive episode

 No history of mania or mixed episodes

(these change dx to bipolar I)

 Appears less common than Bipolar I

 But likely to be under-reported,  And not always assessed in research or

clinical work

Cyclothymic Disorder

 For at least 2 years (1 year in youths),

numerous episodes of hypomanic & depressive symptoms

 Cannot meet criteria for mania, mixed

• r major depressive episode during first

2 years (1 year for kids)

 Rule out schizophrenia, substance

induced, general medical…

 Must cause impairment

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Bipolar NOS (DSM-IV) Other Specified Bipolar & Related Disorder (DSM-5)

 Manic symptoms that don’t fit into any of the

previous diagnostic categories

 Some ways to earn a residual diagnosis

 Manic or hypomanic sx of insufficient duration

(including very rapid cycling)

 Repeated hypomania without a depressive episode  Manic symptoms,

but insufficient number co-occurring

 [brief cyclothymic disorder]

For which diagnosis would DeShawn meet criteria?

a) Bipolar I? b) Bipolar II? c) Cyclothymic Disorder? d) Other Specified Bipolar and Related

Disorder?

e) Substance Induced? f)

Disruptive Mood Disorder with Dysphoria?

g) None of the above?

Including “NOS” increases the amount of bipolar

 Cyclothymic & NOS

3x as common as bipolar I, II

 Including the “soft spectrum” would

triple the amount of bipolar

 Are they impaired?  Should we take a “wait & see”

approach?

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

BP NOS still a serious threat

Proband diagnostic group (%)

Characteristic

Bipolar NOS MDD No disorder Received treatment 55.6a 39.2a 33.2a 3.4b Attempted suicide 44.4a 14.4b 22.2ab 1.2c Social impairment 66.7 48.5 54.7

• Family impairment

55.6 53.6 64.9

• School impairment

83.3a 52.6b 66.1ab

• Lewinsohn et al., 2000. Different subscripts differ at p<.05

Similar patterns of impairment found in adult data with ECA reanalysis (Judd & Akiskal, 2003)

NOS impairing in adults, community sample, too (ECA)

Judd & Akiskal (2003) J Affect Disord

Odds Ratios comparing Subsyndromal Manic/Hypomanic (n=940)

• vs. No Mental Disorder (n=16,437)

All p <.001

What Happens to NOS?

Birmaher et al., 2006, Archives

N = 92 32 remain NOS 33 recover 27 progress (9 BP II, 18 BP I)

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Five year follow-up…

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Baseline 95 Weeks 4 year ??? BP I BP II BP NOS Remitted

Birmaher et al., 2009, Am J Psychiatry; Axelson et al., 2011, JAACAP

N = 141

What Happens to NOS?

N = 92

Continued progression? Birmaher et al., 2009, Am J Psychiatry; Axelson et al., 2011, JAACAP

What Happens to NOS?

N = 92

Stable subtype? (or different condition?) Birmaher et al., 2009, Am J Psychiatry; Axelson et al., 2011, JAACAP

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

What Happens to NOS?

N = 92

Remission? (NOS as developmental delay of emotion regulation?) Birmaher et al., 2009, Am J Psychiatry; Axelson et al., 2011, JAACAP

BP NOS takes longer to remit

Birmaher et al., 2009, Am J Psychiatry Median Median =180 weeks

BP NOS more days ill per year

Birmaher et al., 2009, Am J Psychiatry

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

NOS/OS-BRD: Difficult to Treat

 Less good treatment response to mood

stabilizers

 No RCT for psychotherapy yet  Findling et al. 2005 – high rate of

progression

 Suicide ideation, attempts at same rate as

bipolar II (Goldstein et al., 2005)

Substance Induced Mania

 Manic symptoms could be caused by

street drugs

 Concern that stimulants or antidepressants

might trigger mania

 Conflicting evidence (stimulants may be lower risk)  Unknown whether this is “uncovering” latent

bipolar disorder, or is a side effect

 DSM-5 states that these count as bipolar if the

mood disturbance persists after substance is gone

Bipolar I DSM is most heavily researched, greatest validity

“Narrow” BP-I (DSM-IV) BP-II Cyclothymia??? Bipolar NOS Only if elated or grandiose “Intermediate” “Broad” Severe Mood Dysreg. (SMD)

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Boundary Between ODD and DMDD?

 The symptoms of TDD-D overlap almost

completely with ODD

 ~15% of extreme ODD meet TDD-D criteria per

DSM5 analyses

ODD

SMD/TDD- DMDD (~15%)

For which diagnosis would DeShawn meet criteria?

a) Something bipolar? b) Disruptive Mood Disorder with Dysphoria? c) Oppositional Defiant Disorder d) Early onset conduct disorder

Treatment hinges on formulation

a) Something bipolar? b) Disruptive Mood Disorder with Dysphoria? c) Oppositional Defiant Disorder d) Early onset conduct disorder

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

What did DeShawn’s family try?

 Helping noncompliant child

(Forehand & McMahon)

 Augmentation with methylphenidate and

careful follow-up

 No treatment emergent mania

 Carlson (2003) J Ch Adol Psychopharm  Scheffer (2005) Am J Psychiat

 Lithium, DVPX in reserve

 Balancing dad’s response with Deshawn’s age

Attack Types at Different Ages

10 20 30 40 50 60 70 80 90 100 15 Years 20 25 30 35 40 45 50 55 60 65

Manic Attack Mixed Attack Melancholic Attack Percentage

• Kraepelin. Manic Depressive Insanity and Paranoia.

Edinburgh: E&S Livingstone; 1921:169.

Mixed

ICD-11

 Not planning to add DMDD as diagnosis  Planning to add subtype of ODD

 With mood

 Decisions for clinician:

 Follow DSM or ICD?  What is front line treatment for ODD-Mood

subtype?

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

What is different in clinical picture in youth vs. adult?

 More likely to see mixed mood  Otherwise, not much!

 Similar comorbidities  Similar rates of elated, irritable (if you ask)  Similar rates of “rapid relapse” or episodes

Part II. Evidence Based Assessment in a Nutshell General model of Evidence Based Assessment (EBA)

Journal of Clinical Child & Adolescent Psychology (2013)

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Applying EBA model to pediatric bipolar disorder Installing model in clinic; applying to cases

Cognitive and Behavioral Practice (2014)

Evidence Based Algorithm

High score + Low risk Low score + High risk High score + High risk High score, Replace with mania measure Low score, No risk factors Yes, risk factors No Risk Factors? Know Base Rate

• f Bipolar

Broad Band Scale Mania Specific Scale Test-Wait Threshold Treat-Test Threshold High Risk Severe Mood Medium Risk Moderate Mood Low Risk Mild Mood Treatment: Aggressive Interventions (medication, hospitalization) Assessment: Switch to Process (life chart, CBT 3 & 5 column charts) and Outcome measures Treatment: Secondary interventions and non-specific + low risk treatments Assessment: Intensive assessment-- including semi-structured interviews, collateral informants, additional treatment history, prospective life charting Continue assessment until probability crosses the Treat or Wait Thresholds Treatment: No intervention for bipolar; treat any other conditions Assessment: No further assessment for bipolar disorder unless there is a new risk factor or change

Road Map to Better Assessment Decision Thresholds (EBM) Graded Treatment Options

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Evidence Based Algorithm

High score + Low risk Low score + High risk High score + High risk High score, Replace with mania measure Low score, No risk factors Yes, risk factors No Risk Factors? Know Base Rate

• f Bipolar

Broad Band Scale Mania Specific Scale Test-Wait Threshold Treat-Test Threshold High Risk Severe Mood Medium Risk Moderate Mood Low Risk Mild Mood Treatment: Aggressive Interventions (medication, hospitalization) Assessment: Switch to Process (life chart, CBT 3 & 5 column charts) and Outcome measures Treatment: Secondary interventions and non-specific + low risk treatments Assessment: Intensive assessment-- including semi-structured interviews, collateral informants, additional treatment history, prospective life charting Continue assessment until probability crosses the Treat or Wait Thresholds Treatment: No intervention for bipolar; treat any other conditions Assessment: No further assessment for bipolar disorder unless there is a new risk factor or change

The Worst of Both Worlds

Actually Have Bipolar Disorder Diagnosed with Bipolar Disorder We miss many that truly have a bipolar disorder Many “diagnosed” may not actually have bipolar disorder

How to Choose from Options?

 Availability

 Public domain vs. commercial  Language issues & translation

 Convention (“popularity”)  Advertising claims  Ease of use

 Burden on respondent  Scoring & interpretation

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

More Clinically Oriented Statistics

 Receiver Operating Characteristic

(ROC) analysis

 Signal detection theory  ROC Curve plots sensitivity and

specificity

 Comparing two crucial aspects of test

performance

Diagnostic Efficiency

 Sensitivity – Percentage of cases that truly

have bipolar disorder correctly identified

 Specificity – Percentage of those without

bipolar disorder correctly identified

 False Alarm Rate – Percentage of those

without bipolar disorder misdiagnosed as bipolar

 ROC Analyses look at “trade-off” between

sensitivity and false alarms

Evaluating Diagnostic Efficiency:

Receiver Operating Characteristics (ROC)

• V. High

Medium Low

Test Scores

False Alarm Rate (1 – Specificity) Sensitivity

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

A Visual Comparison of Diagnostic Efficiency

ROC Curve

1 - Specificity

1.00 .75 .50 .25 0.00

Sensitivity

1.00 .75 .50 .25 0.00

Source of the Curve

Reference Line Measure 2 Measure 1

Measure 1 clearly performs better across a wide range

• f scores.

AUC #1 = .94 AUC #2 = .79 (Measure 1 is better, p < .0005)

Areas Under the Curve (AUC)

 Excellent: .90 +  Good: .70 to .89  Fair: .60 to .69  Poor: < .60  Chance: .50

(If you get a number significantly below .50, you are using a good test backwards!)

Be suspicious!

Other Strategies Not Ready for Clinical Use vis Bipolar

 fMRI and other imaging techniques

 Expensive  Findings not specific to bipolar disorder

 Neuropsychological batteries

 Again, findings not specific, or not validated

against clinically meaningful comparison groups yet

 MMPI-A or Personality Inventory for Children

 Conceptually promising, but not validated yet

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

fMRI

Planning has biggest difference between bipolar, ADHD

Walshaw et al., 2010, Neuropsychol Rev

Largest difference d ~.6 (AUC of ~.66)

Most discriminating neuropsych test not helpful diagnostically

.0 .2 .4 .6 .8 1.0 .0 .2 .4 .6 .8 1.0 Sensitivity Specificity

d AUC .2 .56 .5 .64 .8 .71 2.0 .92

Best case neuropsych testing would be d ~.6, AUC = .66

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Christopher

 14 year old white male  Smart, skipped grade, popular  Changed clothes, music  Started “hooking up” with older brother’s

female friends

 Now tired, missing school for weeks at a time

What’s you diagnostic hypothesis at this point?

a) Worried mom, normal teenager b) “Axis III” medical issue

(mononucleosis, etc.)

c) Bipolar II d) Unipolar depression e) Substance misuse

Family Index of Risk for Mood (FIRM)

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Christopher’s FIRM

Perez Algorta et al., 2012, Psych Assess

     Christopher’s family has a lot of alcohol use, Multiple relatives with bipolar disorder; Drinking heavily  

What’s you diagnostic hypothesis at this point?

a) Worried mom, normal teenager b) “Axis III” medical issue

(mononucleosis, etc.)

c) Bipolar II with self-medication d) Unipolar depression e) Substance misuse leading to

moodiness

Case Example

 7 year old black male  referred because of extreme aggression

and distractibility, motor agitation at school

 Dad has been diagnosed with Bipolar I

and treated for several years with lithium and divalproex. What’s you diagnosis at this point? How confident are you?

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Audience Participation Add a Test

 Mom completes CBCL, and he earns an

Externalizing T = 84

 What do you think likelihood is of

bipolar now?

Audience Participation

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Estimated Probability of Bipolar Diagnosis

100 80 60 40 20

Frequency

120 100 80 60 40 20 100 80 60 40 20 120 100 80 60 40 20

Nomogram Clinical Judgment

Wide Range of Clinical Opinion

Decision-Making: Rare + Red Flag + High Test Score =???? N = 610 clinicians, 13 sites

• 2. Risk Factors

 Tsuchiya et al. (2004) review the

literature on risk factors

 They conclude that only family history

• f mood disorder (esp. bipolar disorder)

is robust enough to be clinically useful at present

Recommended rules of thumb

 Clear bipolar in one parent = 5x risk

 Studies including adult offspring estimate 6.1x

lifetime risk (Zuckerman, 1999, p. 164)

 (more liberal estimate would be 9x risk =

5.4% in offspring / 0.6% epidemiological rate)

 Bipolar in bio grandparent, aunt, uncle =

2.5x risk (~50% shared genes * 5x = 2.5)

 “Fuzzy” bipolar or clear mood history in

parents = up to 2x risk

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Risk Factors triggering assessment

 Family history of bipolar disorder  Early onset depression

 (1/3 of adolescent depression may be bipolar)

 Psychotic features

 (bipolar much more common than early

schizophrenia)

 Episodic aggression & mood dysregulation

 Episodicity suggests mood disorder

 Medication coincident mania

Ask about Past Episodes, Not just presenting problem

Present Episode Past Episode No Mood Major Depress Dysthymic Hypomanic Manic No Mood

No mood MDD Dysthymia BP NOS? BP-I

Major Depression

Remitted MDD Recurrent MDD MDD, partial remission BP-II BP-I

Dysthymic

Past dysthymia “Double Depression” Recurrent dysthymia Cyclothymia BP-I

Hypomanic

No mood Bipolar II Cyclothymia BP NOS BP-I

Manic

BP-I BP-I (depressed) BP-I BP-I BP-I

(Youngstrom, Freeman, & Jenkins, 2009)

Evidence Based Algorithm

High score + Low risk Low score + High risk High score + High risk High score, Replace with mania measure Low score, No risk factors Yes, risk factors No Risk Factors? Know Base Rate

• f Bipolar

Broad Band Scale Mania Specific Scale Test-Wait Threshold Treat-Test Threshold High Risk Severe Mood Medium Risk Moderate Mood Low Risk Mild Mood Treatment: Aggressive Interventions (medication, hospitalization) Assessment: Switch to Process (life chart, CBT 3 & 5 column charts) and Outcome measures Treatment: Secondary interventions and non-specific + low risk treatments Assessment: Intensive assessment-- including semi-structured interviews, collateral informants, additional treatment history, prospective life charting Continue assessment until probability crosses the Treat or Wait Thresholds Treatment: No intervention for bipolar; treat any other conditions Assessment: No further assessment for bipolar disorder unless there is a new risk factor or change

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Using a Nomogram

Parent with Bipolar (LR+ 5.0)

Pre-test Prob. Likelihood Ratio Post-test Prob.

.1% 1% 25% 99% 99% 1% .1% 1000 100 10 1 .1 .01 .001 68%

Find pre-test prob. Find LR+ (5.0) Connect dots and read post- test prob.

6%

• utpatient

base rate ??? Box #3

Audience Participation Step 3. Add Test Result

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Evidence Based Algorithm

High score + Low risk Low score + High risk High score + High risk High score, Replace with mania measure Low score, No risk factors Yes, risk factors No Risk Factors? Know Base Rate

• f Bipolar

Broad Band Scale Mania Specific Scale Test-Wait Threshold Treat-Test Threshold High Risk Severe Mood Medium Risk Moderate Mood Low Risk Mild Mood Treatment: Aggressive Interventions (medication, hospitalization) Assessment: Switch to Process (life chart, CBT 3 & 5 column charts) and Outcome measures Treatment: Secondary interventions and non-specific + low risk treatments Assessment: Intensive assessment-- including semi-structured interviews, collateral informants, additional treatment history, prospective life charting Continue assessment until probability crosses the Treat or Wait Thresholds Treatment: No intervention for bipolar; treat any other conditions Assessment: No further assessment for bipolar disorder unless there is a new risk factor or change

• 3. Use Broad Band

Rating Scales

 Achenbach CBCL most widely researched  Expect similar performance by BASC,

Conners, CASI

 Parent report validity > teacher, youth

 True even if parent is depressed  Spouse/partner perspective important

 Can focus on Externalizing score

 No value added by looking at “bipolar profile”

EBM – Find Likelihood Ratios associated with test result

 More than 9 studies on 3 continents

show association between CBCL and bipolar disorder

 Youngstrom et al., 2004 report

likelihood ratios associated with scores

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

LR+ = 3.9

73+ 3.91

Externalizing Scores

 Low parent Externalizing rules bipolar out

 No further need to evaluate bipolar unless

new risk factors develop

 Powerful enough to reduce concerns due

to family history or other risk factors

 Moderate elevations (60-70) don’t change

diagnostic impression

 Could happen for lots of reasons besides

bipolar

The Signal and the Noise: Deshawn meets Bayes (again)

 Mom completes CBCL, and he earns an

Externalizing T = 84

 What do you think likelihood is of

bipolar now?

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Using a Nomogram

Add a CBCL Test Result

Pre-test Prob. Likelihood Ratio Post-test Prob.

.1% 1% 99% 99% 1% .1% 1000 100 10 1 .1 .01 .001 68%

LR+ (3.9) Connect dots and read post- test prob. Box #3

??? Box #4

Audience Participation

Estimated Probability of Bipolar Diagnosis

100 80 60 40 20

Frequency

120 100 80 60 40 20 100 80 60 40 20 120 100 80 60 40 20

Nomogram Clinical Judgment

Is the Nomogram Worth Using?

55% Probability (Adding Test Result)

N = 610 clinicians, 13 sites Still extreme range of opinion Most tend to

• verdiagnose

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Estimated Probability of Bipolar Diagnosis

100 80 60 40 20

Frequency

120 100 80 60 40 20 100 80 60 40 20 120 100 80 60 40 20

Nomogram Clinical Judgment

Is the Nomogram Worth Using?

55% Probability (Adding Test Result)

N = 610 clinicians, 13 sites Much more accurate Much less range of

• pinion

Reduces

• verdiagnosis

Evidence Based Algorithm

High score + Low risk Low score + High risk High score + High risk High score, Replace with mania measure Low score, No risk factors Yes, risk factors No Risk Factors? Know Base Rate

• f Bipolar

Broad Band Scale Mania Specific Scale Test-Wait Threshold Treat-Test Threshold High Risk Severe Mood Medium Risk Moderate Mood Low Risk Mild Mood Treatment: Aggressive Interventions (medication, hospitalization) Assessment: Switch to Process (life chart, CBT 3 & 5 column charts) and Outcome measures Treatment: Secondary interventions and non-specific + low risk treatments Assessment: Intensive assessment-- including semi-structured interviews, collateral informants, additional treatment history, prospective life charting Continue assessment until probability crosses the Treat or Wait Thresholds Treatment: No intervention for bipolar; treat any other conditions Assessment: No further assessment for bipolar disorder unless there is a new risk factor or change

Which Mania Scales to Use?

 More than 30 available, more than 12

validated in youths, 20+ in adults

 Youth leaders:

 Parent MDQ (Wagner et al., 2006)

 Easiest reading level, most translations

 Parent CMRS-10 (Henry et al., 2008)  Parent GBI 10M (Youngstrom et al., 2006)

 Most data; sensitive to treatment effects  But difficult reading level

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Consumer Reports style review of rating scales or checklists

4094 hits 27 samples from 25 sources 10,232 youths (1,719 with bipolar spectrum) 8 measures

Youngstrom, Genzlinger, Egerton, Van Meter (2015) Arch Sci Psych 63 effect sizes: 38 caregiver, 14 youth, 11 teacher 8 scales with multiple samples

• 1.00

0.00 1.00 2.00 3.00 Hedge's g

• 0.02 [ -0.30 , 0.25 ]

g [95% CI] Measure Study

Youth Report (medium) Teacher Report (small) Caregiver Report (very large) Youngstrom, Genzlinger, Egerton, Van Meter (2015) Arch Sci Psychol

• 1.00

0.00 1.00 2.00 3.00 Hedge's g

1.11 [ 0.93 , 1.28 ] Caregiver random effect model 0.32 [ 0.15 , 0.49 ] Teacher random effect model 0.49 [ 0.38 , 0.61 ] Youth random effect model 1.05 [ 0.83 , 1.27 ] Overall random effect model

Youngstrom, Genzlinger, Egerton, Van Meter (2015) Arch Sci Psychol

• 1.00

• 0.02 [ -0.30 , 0.25 ]

Mother knows best about mania

S M L

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Lessons Learned from Mom

 Onion versus Garlic symptoms

 Clinician can use nonverbals  Look from their perspective

 Compromised insight with hypomania

Moms still accurate even if they have mood disorder

Parent Mood History

.0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1.0 .0 .2 .4 .6 .8 1.0 Specificity Sensitivity Bipolar Unipolar No Mood Chance

.90 .85 .88 No significant differences

Implications for Assessment

 Parents, collaterals should routinely be involved

in assessment for bipolar (even for teens)

 Teacher report on TRF not useful for bipolar  Involving collateral informant may be helpful

with adults

 Low scores on any good instrument effectively

rule out bipolar in low base rate settings

 E.g., If already have low CBCL and no obvious risk

factors, don’t need to give any other instruments

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Which Mania Scales to Use?

 Adult Leaders:

 MDQ (Hirschfeld et al., 2000, AJP)

 Easiest reading level, most translations  Now commercially distributed

 BSDS (Ghaemi et al., 2005, JAD)

 Designed as a new, public domain alternative to MDQ  Included in “care package”

 Hypomanic Checklist (HCL-32)  TEMPS widely used in research,

less developed clinically

Second meta-analysis – adult mania scales

3852 hits 127 effects from 103 sources

37,749 people (11,985 with

bipolar spectrum)

14 measures

Youngstrom, Egerton, Genzlinger, & Van Meter (2017) Psychological Bulletin

14 measures 17 languages 24 countries 6 continents

Meta-analysis of mania scales in adults

Youngstrom, Egerton, et al. (2017) Psych Bull

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Using any top tier scale would substantially improve practice UNC Translations Project

Archived by Stephanie Salcedo & team

https://trello.com/b/dYUKlNRP/translated-measures-dashboard

Tamika plot twist

 Saved by a

semi-structured interview

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Lea

 18 yo WF  Middle of senior year  Coming to outpatient clinic  Presenting problem:

 Trouble with attention

 Can’t stay focused  Grades dropping

 Getting anxious and stressed about graduating

(and if she’ll graduate)

What do you think is going on?

 Diagnosis?  What’s your assessment plan?  Treatment options?  How many comorbidities?

 How many that change treatment?

Detective Work: Evidence-Based Assessment

EBA

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

DSM‐5

Expanding number of diagnoses

More than 365 diagnoses – One for every day of the year!

How long would it take to consider all of them?

Pareto’s 80:20 Law “Law of the vital few”

 20% of diagnoses will cover more than

80% of the cases we see

 Concentrate on the common problems  Have a good plan for assessing,

treating them

Rates of common diagnoses

5 10 15 20 25 30 35 40 General Anxiety Disorder PTSD Conduct Depression Substance Use ADHD ODD Structured Clinicians

Rettew et al., 2009

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Probabilities:

Thinking like the weather forecast

The weather meets clinical decision-making

0% 100%

?

Treatment Zone

(this becomes a treatment target)

Assessment Zone

(we need more information)

“Wait” Zone

(ruled out, prevention, remission…)

The weather meets clinical decision-making

0% 100%

Treatment Zone

(this becomes a treatment target)

Assessment Zone

(we need more information)

“Wait” Zone

(ruled out, prevention, remission…) Test-Treat threshold Wait-Test threshold

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Where to start?

Epidemiological Clinical

Rates of common diagnoses

• -we underestimate them!

5 10 15 20 25 30 35 40 General Anxiety Disorder PTSD Conduct Depression Substance Use ADHD ODD Structured Clinicians

Rettew et al., 2009 Rates higher when using structured approach with same person

Why the gap?

 Our brain is wired to:

 React quickly  Make a hypothesis  Look for confirming evidence  Discount contradictory evidence

 One diagnosis is enough for billing

 No push to find all comorbidities

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Quick Solutions

 Always consider the common issues (A,B)

 Look for evidence to rule them out  Don’t wait to be reminded

 Always list more than one hypothesis (C)

 Look for evidence for each  Don’t play “favorites” at beginning

Think about where you are working (“Bet the base rate”)

0% 100%

Treatment Zone Assessment Zone “Wait” Zone

Test-Treat threshold Wait-Test threshold ADHD Depression Anxiety Substance Bipolar Conduct PTSD ODD

Learn good thinking habits

 Debiasing strategies:

 Competing hypotheses  Look for disconfirming evidence  Don’t call off search when find one

plausible suspect

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

 Randomized control trial, 2-arm  N = 137 clinician participants  Case vignette methodology  Web administration via Qualtrics software

 Randomized:

 Treatment or Control group  Race/ethnicity of vignette characters

Jenkins & Youngstrom (2016) JCCP

Cognitive Strategies vs. Diagnosis As Usual

 20 minutes  Web tutorial  Four cognitive debiasing strategies  Treatment group more accurate across

all four vignettes:

 Accuracy F =10.37, p <.0005, R2 =.22  Fewer Errors F =10.86, p <.0005, R2 =.23

Intervention

Jenkins & Youngstrom (2016) JCCP

Cognitive de-biasing increases accuracy

Estimated Probability of Bipolar Diagnosis

Diagnosis As Usual Treatment Group Accurate Estimate

Treatment group more accurate Diagnosis As Usual over- estimates bipolar risk

Jenkins & Youngstrom (2016) JCCP

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

 Presenting problem: Attention, grades, stress

 Sounds like ADHD?

 Common conditions at clinic (Pareto 80:20):

 ODD, Anxiety, ADHD, Depression, Substance

 Could these other diagnoses also explain

presenting problem?

 …Better check all of them!

 What would help rule them out?

Applying these to Lea Another Solution: Checklists

 Checklists as a simple way of

eliminating human error

 Used in medicine, engineering, arena

rock, other complex endeavors

 Atul Gawande –

The Checklist Manifesto

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Possible Checklists

 DSM Diagnostic Criteria  Rule-outs or other diagnoses to consider

 General medical condition  Medication induced  Due to some other disorder  Environmental factors  Cultural factors

 Side effects, treatment response  Could be “notes to self” about treatment planning

Use a broad measure to get data about several issues quickly

 Achenbach System of Empirically Based

Assessment (ASEBA)

 Youth Self Report – How does Lea’s report

compare to 11-18 year old females?

 Child Behavior Checklist – caregiver report

 Strengths & Difficulties Questionnaire (SDQ)

 Free alternative

Reading the Achenbach

T Scores Average +1 SD +2 SD +3 SD Broad Bands Clinical Syndrome Scales

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Lea’s Youth Self Report scores

T Scores

Check the details & probes

(Drotar, Stein, & Perrin, 1995)

Substance issues Sleep problems – bipolar clue?

YSR

Lea’s updated probabilities

0% 100%

Treatment Zone Assessment Zone “Wait” Zone

Test-Treat threshold Wait-Test threshold ADHD 21% Depression 39% Anxiety 49% Substance 37% Bipolar 9% Conduct 2% PTSD 2% ODD 6%

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Next step: Get another perspective (E)

 Routine with children and adolescents

to get caregiver; often teacher ratings

 Lea “on the bubble”

 18 years old  Has left home  Now living with older sister

 Choice point:

Older sister or bio mom’s perspective?

Lea’s CBCL Scores (Big sister!)

T Scores

Check the details & probes

(Drotar, Stein, & Perrin, 1995)

CBCL

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Check the details & probes

(Drotar, Stein, & Perrin, 1995)

More substance issues Sleep problems – bipolar clue?

CBCL

Another Step: Ask about risk factors (c)

 Why did Lea move in with sister?

Lea’s FIRM

Perez Algorta et al., 2012, Psych Assess

       Lea’s dad has bipolar disorder, inconsistent with treatment; Drinking heavily

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Another Step: Ask about risk factors

 Why did Lea move in with sister?  Dad has bipolar and history of

substance problems

 Bipolar is highly heritable

 How much does this change Lea’s risk?  First degree relative – 5x more risk

 Any other bipolar risk factors?

 Early onset depression – 1/3 becomes bipolar  Sleep disturbance

Lea’s re-updated probabilities

0% 100%

Treatment Zone Assessment Zone “Wait” Zone

Test-Treat threshold Wait-Test threshold ADHD 21% Depression 39% Anxiety 49% Substance 37% Bipolar 9% Conduct 2% PTSD 2% ODD 6%

Adding more information (G)

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Evidence Based Algorithm

High score + Low risk Low score + High risk High score + High risk High score, Replace with mania measure Low score, No risk factors Yes, risk factors No Risk Factors? Know Base Rate

• f Bipolar

Broad Band Scale Mania Specific Scale Test-Wait Threshold Treat-Test Threshold High Risk Severe Mood Medium Risk Moderate Mood Low Risk Mild Mood Treatment: Aggressive Interventions (medication, hospitalization) Assessment: Switch to Process (life chart, CBT 3 & 5 column charts) and Outcome measures Treatment: Secondary interventions and non-specific + low risk treatments Assessment: Intensive assessment-- including semi-structured interviews, collateral informants, additional treatment history, prospective life charting Continue assessment until probability crosses the Treat or Wait Thresholds Treatment: No intervention for bipolar; treat any other conditions Assessment: No further assessment for bipolar disorder unless there is a new risk factor or change

Road Map to Better Assessment Decision Thresholds (EBM) Graded Treatment Options

Evidence Based Algorithm

High score + Low risk Low score + High risk High score + High risk High score, Replace with mania measure Low score, No risk factors Yes, risk factors No Risk Factors? Know Base Rate

• f Bipolar

Broad Band Scale Mania Specific Scale Test-Wait Threshold Treat-Test Threshold High Risk Severe Mood Medium Risk Moderate Mood Low Risk Mild Mood Treatment: Aggressive Interventions (medication, hospitalization) Assessment: Switch to Process (life chart, CBT 3 & 5 column charts) and Outcome measures Treatment: Secondary interventions and non-specific + low risk treatments Assessment: Intensive assessment-- including semi-structured interviews, collateral informants, additional treatment history, prospective life charting Continue assessment until probability crosses the Treat or Wait Thresholds Treatment: No intervention for bipolar; treat any other conditions Assessment: No further assessment for bipolar disorder unless there is a new risk factor or change

Time and costs so far:

 Could use checklists (YSR, CBCL, FIRM)

as part of intake

 0 min in session to complete; 0-10 min to

discuss

 Achenbach costs $1.25; free alternatives

 Base rates: Know ahead of time

 0 session minutes; 0 cost

 Debiasing strategies

 0 added session minutes, 0 cost

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

• Natural language,

unlike chess

• Better approximates clinical

interview

• Medical decision‐making

IBM Watson wins on Jeopardy!

14 February, 2011

Symptoms UTI Diabetes Influenza Hypokalemia Renal Failure

no abdominal pain no back pain no cough no diarrhea (Thyroid Autoimmune)

Esophagitis

pravastatin Alendronate levothyroxin e hydroxychloroquine

Diagnosis Models

frequent UTI cutaneous lupus hyperlipidemia

• steoporosis

hypothyroidism

Confidence

difficulty swallowing dizziness anorexia fever dry mouth thirst frequent urination

Family History

Graves’ Disease Oral cancer Bladder cancer Hemochromatosis Purpura

Patient History Medications

Findings

supine 120/80 mm HG urine dipstick: leukocyte esterase urine culture: E. Coli heart rate: 88 bpm

Symptoms Family History Patient History Medications Findings

Putting the proper pieces together at the point of impact can be life changing

Kohn, 2012, IBM

Example of Watson Decision-support

Compare these to old “Tested Positive” idea

 37% chance of bipolar

 If called everyone who tested positive

bipolar, wrong more often than right

 “Based on this result, we should talk

more about possible bipolar…”

 Yellow zone phrasing  Avoid overinterpreting  Not ignoring, either

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Next step:

Semi-structured diagnostic interview

 Structured: Make sure you cover the

key symptoms, and the contending hypotheses

 Semi:

 Use language you and client understand  Scratch & sniff

 Options: MINI, SCID, KSADS...

Practical issues with semi-structured

 Hurt rapport?

 No, patients prefer them

(Bruchmuller et al., 2011)

 Take long?

 Not if targeted, or use skip outs

 Not reimbursed

 MedicAid, insurance will pay if show

“medical necessity”

 Working earlier steps counts as “yes”!

Lea after MINI

 Bipolar II (depression + hypomania)  Substance abuse  ADHD Predominantly inattentive

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

What is bipolar II?

 Major depression + hypomania

 Could be mixed depression, mixed hypomania

 How different from ordinary depression?

 Poor response to antidepressants  Higher risk of suicide and NSSI  Higher risk of substance misuse  Often more atypical features

 Hypersomnia, increased appetite

 Changes prognosis, and treatment

“Moodquakes”

Pick treatment goals

 Lea not on board with substance as

focus of treatment

 Would fight “diagnosis” (Step L!)

 Lea agreed with depression as

focus of treatment

 Bipolar II as a way of describing

type of depression

 Focusing on stability versus activation  Agreed to be honest about substance use,

see if it changed as depression went down

Setting Goals (H)

 Severity measures

can help define goals

 Some have norms  Benchmarks for comparison

 Get client input (L)

 Goals should be motivating  Measurable

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Parent report as sensitive to treatment effects as clinician ratings

Brief parent checklists as effective as 30-40 minute interview with family

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 CGI- BPO YMRS CGI- BPM pGBI- M10 sGBI- M10 CGI- BPD pGBI- D10 sGBI- D10

Effect Size (Cohen’s d) Manic Sx Depressive Sx Youngstrom, Zhao et al. (2013) JCAP N = 296

Nomothetic benchmarking

(~Jacobson & Truax, 1991)

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Progress measures (I,J)

 Need to be short

(asking client to repeat them)

 Focus on goals  Can check progress quickly

 Like bathroom scale for diet

Assessment During Treatment

 Process measures: response to treatment  Outcome measures:

 Parent report sensitive to treatment effects

 Less time, expense, training than clinician ratings  Excellent complement to clinician-rated

 Also measure comorbid issues

 May require adjunctive treatment for ADHD,

anxiety

 Measure quality of life

Idiographic goal assessment

(~Y-TOPS)

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Progress measures for Lea

 Mood: Smartphone mood app

(daily use; $3.99 at App Store)

 Attention problems: CAARS or other

rating scale, every other session

 Substance: ask about drinks and tokes

each session (brief and low key; just charting trends)

Typical improvement?

 Treatment as usual: d ~.2  Tracking progress: d ~.4-.6

 Imagine going on a diet where you never

stepped on a scale?!

 Measuring more than doubles the outcome

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Evidence Based Assessment is fast and frugal

 Time added per patient:

 < 5 minutes for first 6 steps  Remaining steps may already be part of typical

assessment or treatment

 No delay in initiating “Green” or

“Yellow” zone treatments

 Expense added:

 $5 if use life charting app on smartphone  All else in public domain, and billable time

Youngstrom et al. (2012) Israel J Psychiatry

Wikipedia: “Best of the Free” Assessments

 Write pages for free use tools that have good score

psychometrics across samples

 Link to copies of measures  Solves Awareness and Access issues  Supported by grants from SCCAP, APS, SSCP, APA CODAPAR

& D12

 Now a 501c3! https://HGAPS.org

Wikiversity:

EBA, Teaching and Clinical Application

 Evidence-Based

Assessment (EBA)

• verview and

concepts

 Disorder-specific

assessment toolkits

 Teaching Vignettes  Research: Toolkit for

EBA statistics

 Ready to ROC

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Free Evidence-based Assessments

 Also on Wikipedia &

Wikiversity

 Can help us frame the

feedback & suggest resources:

 DBSA/screeningcenter

Want to support HGAPS?

Method 1: Online Donation

 How to donate online-

 Go to hgaps.org  Scroll to the bottom  Under “donate” select or enter an amount

and choose whether you’d like to make an

• ne-time or recurring gift

 Enter your information and click “Donate”

Want to support HGAPS?

Method 2: Amazon Smile

 What is Amazon Smile?

 The Amazon you know and love with a different

URL that will donate a percentage of your purchases to a charity

 How do you do it?

 There are two methods:  1. Just type in tinyurl.com/supportHGAPS and

login

 2. Go to smile.amazon.com and search for

Helping Give Away Psychological Science

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Evidence Based Assessment produces large effects

 Increased consistency &

accuracy of diagnoses

 Greater agreement about next action  Avoids cultural biases  Need not reduce clinical control of treatment  Makes it possible to treat more specifically

and use lower “doses” of intervention

For Lea, EBA…

 Found a problem she didn’t know she had

 (limitation of describing the presenting problem)

 Caught a diagnosis not on our radar  Developed a plan for treatment goals

 And how to tell if treatment was helping

 Working faster

 Using base rates, cognitive debiasing  Checklists & focused interviewing

 More accurate, and better outcomes

Your next client

 Circle the steps you are confident you’ll

be able to use – twice

 Circle the “stretch goals” once  Ask supervisor for support

 What are common diagnoses?  What tools are available to assess?

 Commit to try one step this week…  Share with your team! (many hands…)s

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

FIRM Slides, records,

• r supervisor

Have some go-to checklists (& know what results mean at your clinic) Semi-structured interview Progress, outcome tools & benchmarks Keep talking with client!

Thank You!

Questions, Suggestions, and Comments

 Please send to:

Eric Youngstrom, Ph.D. Department of Psychology & Neuroscience University of North Carolina at Chapel Hill, Psychology, Davie Hall, CB3270 Chapel Hill, NC 27599-3270 Eay@unc.edu

Nebraska Psychological Association June 8, 2018 Eric Youngstrom, Ph.D. University of North Carolina at Chapel Hill Davie Hall, Chapel Hill, NC 27599-3270 eay@unc.edu

Arlene 2.0