INDIVIDUAL DIFFERENCES IN MEMORY FUNCTION Richard N. Jones, John N. Morris, Adrienne Rosenberg, Paul Malloy HRCA Research and Training Institute, Boston Ken Kleinman Harvard Medical School, Boston MA Jason Allaire Wayne State University, Institute of Gerontology, Detroit MI Michael Marsiske University of Florida, Institute on Aging, Gainesville

ACTIVE Advanced Cognitive Training for Vital and Independent Elderly funded as a cooperative agreement with the National Institute on Aging and the National Institute of Nursing Research. Participating Institutions & Principal Investigators: Hebrew Rehabilitation Center for AgedJohn Morris, Ph.D. Indiana University David Smith, M.D. Johns Hopkins University George Rebok, Ph.D. Pennsylvania State UniversitySherry Willis, Ph.D. University of Alabama at BirminghamKarolin Ball, Ph.D. Wayne State University Michael Marsiske, Ph.D. Coordinating Center New England Research InstitutesSharon Tennstedt, Ph.D.

Objectives Characterize performance on memory task in cognitively normal older adults Use Latent Growth Curve Modeling (LGM) techniques Separately model initial recall and learning Explore association of background variables and recall, learning

Rey AVLT Auditory Verbal Learning Test (Lezak, 1983; Rey, 1964) 15 unrelated word list, read at 2 sec. intervals Participants asked to recall words List re-read four times Repeated recall trials Intrusion list Delayed Recall and Recognition task

Latent Growth Modeling Psychometric approach to repeated measures data Individual differences in intercept and slope over time captured in latent variables (initial recall, learning) Certain parameterizations equivalent to random coefficient models, mixed models, hierarchical linear models

Methods: Participants HRCA –elder housing IU –community centers UAB –drivers licenses, ID cards –eye clinic attendees WSU –community organizations –urban residential settings JHU –in and around urban geriatric center –urban senior high-rise housing –suburban retirement community –urban & rural medical centers PSU –PACE enrollees

Eligibility and Exclusion Criteria Eligibility Criteria –age  65 –living in non-institutional setting –available for duration of trial Exclusion Criteria –vision impairment –hearing loss –impaired communication –reported disability –Alzheimer’s dx or MMSE<23 –cancer dx w/ limited life expectancy –current chemo/radiation –CVA in previous 12 months –in other cognitive training –high level depressive sx (CESD>16)

Background Variables Demographics –Age –Sex –Ethnicity –Education Cognitive Functioning –General (MMSE) –Reasoning ability (STAMAT) –Vocabulary (Kit) –Digit symbol substitution (WAIS)

LGM Parameterization without Background Variables

Alternative Functional Forms of AVLT Growth

Logarithmic Growth Function

Model implied trajectories

LGM Parameterization with Background Variables

Conclusion LGM provides a comprehensible model of initial recall and learning performance on the AVLT task Alternative summary measures are suggested by considering effect of background variables on initial recall and rate learning

LGM Alternative Parameterization without Background Variables

Word List Used in ACTIVE Drum Curtain Bell Coffee School Parent Moon Garden Hat Farmer Nose Turkey Color House River