Being too smart for your own good: Issues in the cognitive ... · *CVLT-II: Tot1-5/SDFR/LDFR/d *Rey...
Transcript of Being too smart for your own good: Issues in the cognitive ... · *CVLT-II: Tot1-5/SDFR/LDFR/d *Rey...
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Being too smart for your own good:
Issues in the cognitive assessment of
high-functioning individuals
Greg Savage CCD & Department of Psychology, Macquarie University
Co-leader, Clinical & Cognitive Stream, AIBL
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Case : 72 year old CEO
referred by neurologist with 4 year history of
• word-finding difficulty, forgetfulness, spatial disorientation while driving
but
• well oriented and informed, ADL OK, still seeing clients, running company, driving to work
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Intelligence has a normal distribution
• this is true of most aspects of cognition we assess
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Intelligence has a normal distribution
• this is true of most aspects of cognition we assess
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For an average individual, scores placed here are clearly abnormal…
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But what about scores placed here?
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16%
-1 SD
But what about scores placed here?
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2%
-2 SDs
But what about scores placed here?
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7%
-1.5 SDs
But what about scores placed here?
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at least 1.5 SDs below normative mean
b/w 1.5 SDs below and above normative mean
at least 1.5 SDs above normative mean
*CVLT-II: Tot1-5/SDFR/LDFR/d’ *Rey figure copy *Category fluency/switching *Digit Symbol-Coding Brixton
*Digit Span *Rey figure recall *Letter fluency *Boston naming Digit Symbol-Copy Mental Control Picture Completion Similarities Faces-I
Faces-II
MCI : objective evidence of impairment
• 1.5 SDs below normative mean
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Impaired: at least 1.5 SDs below normative mean
Intact: ??? b/w 1.5 SDs below and above normative mean
Intact at least 1.5 SDs above normative mean
*CVLT-II: Tot1-5/SDFR/LDFR/d’ *Rey figure copy *Category fluency/switching *Digit Symbol-Coding Brixton
*Digit Span *Rey figure recall *Letter fluency *Boston naming Digit Symbol-Copy Mental Control Picture Completion Similarities Faces-I
Faces-II
MCI : objective evidence of impairment
• 1.5 SDs below normative mean
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Clinical judgments about cognitive deficits are based on normative data, which adjust for
• age (nearly always)
• sex (sometimes)
• education (sometimes)
These adjustments work well for the average person
“Our culture encodes a strong bias either to neglect or ignore variation. We tend to focus on measures of central tendency, and as a result we make some terrible mistakes, often with considerable practical import.” Gould (1996)
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Elephant in the room…
• research assumes everyone is average
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What about the rest of the population?
Need to adjust for case-specific expectations
• premorbid ability
How do we know what our expectations should be?
Neuropsychologists test for preserved abilities
• scores on tests resistant to brain damage
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WTAR : Wechsler Test of Adult Reading
50 words, simply read aloud
• can’t sound them out correctly (eg aisle)
• need to know them
• correlates highly with IQ
• word reading is preserved in most brain disorders
• a kind of fossil record…
Our case scored 48/50 : predicted IQ of 117
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-1.5 SDs
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-1.5 SDs premorbid
IQ=117
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case -1.5 SDs
premorbid IQ=117
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What if I had seen him 3 years ago, after a year of noted difficulties?
Worried well? Functioning adequately enough
• has it mattered?
In an era of disease-modifying therapy, it definitely would have mattered
• might have been considered unimpaired
• missed out on treatment
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How do high-functioning people ‘hold up’?
Cognitive Reserve : Stern (eg 2009, Neuropsychologia)
• no direct relationship between brain pathology and cognitive or functional consequences of pathology
• individual differences in susceptibility
• differences in how tasks are processed
• use your wits on assessment, in daily life
• my case : looked for distinctive features on faces
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IQ : a proxy for cognitive reserve
• high IQ would be protective against the impact of brain illness
• against the dementia in Alzheimer’s disease
• but not the disease itself
• cognition/function would remain intact for longer, but unravel very rapidly at some late time-point
• too late for intervention?
• too smart for their own good…
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Stern, Neuropsychologia 2009
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Back to the research context:
• for any case who normally thinks better than average, we will underestimate impairment using any criterion based on the normative mean
• the converse is also true
AIBL participants are high-performers
• cognitive test scores in HCs are ~0.7 SDs above average
• systematic under-representation of incidence of, and transition to, MCI
• in more than half our sample?
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My focus is on transition from healthy cognition to MCI
• it’s where the psychometrics count
• transition from MCI to AD has less reliance on psychometrics
• parallel issues : what counts as functional impairment for a high performer?
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AIBL -1.5 SDs (=-0.7)
AIBL HCs premorbid
IQ=112 (+0.8)
0 -1 -1.5 +1 +1.5
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Could use regression techniques to account for variation around the AIBL means for cognitive variables
Exploit bimodality revealed by latent class modeling:
• A+ : “slightly above average” cognition
• A++ : “well above average” cognition
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A+ (N=311) A++ (N=442)
58% female 45% female
70.7 years old 70.2 years old
56% tertiary educ’n 57% tertiary educ’n
WTAR-predicted IQ=110 (+0.67 SDs) WTAR-predicted IQ=114 (+0.93 SDs)
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Test A+ A++
CVLT-II delayed recall +0.34 +1.45
Rey figure delayed recall +0.12 +1.11
Category fluency +0.39 +1.40
Letter fluency +0.28 +1.28
Processing speed +0.36 +0.87
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0 -1 -1.5 +1 +1.5
A+ A++
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A+ (N=442) A++ (N=311)
58% female 45% female
70.7 years old 70.2 years old
56% tertiary educ’n 57% tertiary educ’n
WTAR-predicted IQ=110 (+0.67 SDs) WTAR-predicted IQ=114 (+0.93 SDs)
26% PiB+ (27/103) 34% PiB+ (25/74)
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-1.5
-1
-0.5
0
0.5
1
1.5
2
Baseline 18 mths 36 mths
A++ PiB- (N=49)
A+ PiB- (N=76)
Delayed recall
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-1.5
-1
-0.5
0
0.5
1
1.5
2
Baseline 18 mths 36 mths
A++ PiB- (N=49)
A++ PiB+ (N=25)
A+ PiB- (N=76)
A+ PiB+ (N=27)
Delayed recall
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-1.5
-1
-0.5
0
0.5
1
1.5
2
Baseline 18 mths 36 mths
Delayed recall
?
?
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-1.5
-1
-0.5
0
0.5
1
1.5
2
Baseline 18 mths 36 mths
Delayed recall
?
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Cognitive reserve is noise : remove from the equation
• WTAR is a good idea : deceptively simple, and impervious to strategic influence
• blunt instrument, low ceiling
• trivial difference between A+ and A++ groups
• doesn’t target those with nonverbal strengths • declining high-PIQ individuals will be missed
• look for intra-individual discrepancies
• early memory decline relative to non-memory cognition
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Use tests which are immune to the impact of CR?
• ‘harder’ tests with little apparent structure?
• no—that just narrows the field
• ‘easier’ tests which tap automatic, not strategic, processing
• reaction time and error rate on easy tasks?
• CogState
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With special thanks to:
Dr Petra Graham Department of Statistics, Macquarie University
CSIRO Mathematics, Informatics & Statistics
Dr Andrew Jones Department of Psychology, Macquarie University
CSIRO Mathematics, Informatics & Statistics