Troubles with Trajectories: Challenges to Longitudinal Research on

Mental Health

William R. Avison, PhD, FCAHS

Departments of Sociology, Paediatrics,and Epidemiology and Biostatistics

Western University

Chair, Division of Children’s Health & TherapeuticsChildren’s Health Research Institute

Assistant Director Lawson Health Research Institute

London Health Sciences Centre/St. Joseph’s Health Care

SURVEY RESEARCH IN MENTAL HEALTH RESEARCH

Multi-wave, multi-level longitudinal surveys

Multiple informants

Dimensional and categorical measures of mental health

Social, economic, family, school, and neighborhood contexts

Data linkage

Biological samples

Have technical advances in longitudinal data collection and analyses overtaken conceptual models of change?

“If all you have is a hammer, everything looks like a nail” Abraham Kaplan, 1964; Abraham Maslow, 1966: The Law of the Instrument

Scientists from all disciplines who use multivariate techniques have been guilty of:

- spray and pray analyses- capitalizing on chance - kitchen sink analyses- dredge and hedge

“If you torture the data long enough, sooner or later they will confess” Ronald Coase, 1960s; Peter Rossi, 1980s

A FRAMEWORK

Jacob Cohen (1990) “Things I Have Learned (So Far).”American Psychologist 45:1304-12

less is more simple is better some things you learn aren’t so

Carol S. Aneshensel (2013). Theory-Based Data Analysis for the Social Sciences. Second Edition

CONCEPTUAL FRAMEWORKS Developmental Origins of Health and Disease (DOHaD)

evidence of perinatal influences is mixedproblem of G-E correlationsalternative explanationsDonofrio et al. (2014), Child Development Perspectives

The neuroinflammation hypothesis Miller, Chen, and Parker (2011), Psychological Bulletin childhood maltreatment low SES biological embedding of childhood adversity

LBWSGAIUGR

Childhood Onset of Elevated

Inflammatory Response

Social Structure in Adulthood

Mental Health

Problems in Adulthood

Parental SES

AdversitiesStress

Elevated Inflammatory Response in Adulthood

AdversitiesStress

WHAT IS THE GOAL?

ADVERSITIES

DISADVANTAGES

MENTAL HEALTH

PROBLEMSNeuroinflammation Processes

Identification of risk factors Explanation of how disadvantage “gets under the skin”

LIFE COURSE PERSPECTIVES Life course epidemiology

critical period modelsaccumulation of risk models

Eco-social or multi-level developmental models Bronfenbrenner Hertzman

WHAT CAN A SOCIOLOGICAL PERSPECTIVE CONTRIBUTE? The stress process across the life course

the stress process paradigm (Leonard Pearlin) what are the consequences of social structure for individuals’

mental health?

STRESSORSSTRESSORS

MEDIATORSMEDIATORS

MENTAL HEALTHMENTAL HEALTH

SOCIAL AND ECONOMIC STATUSESSOCIAL AND ECONOMIC STATUSES

STRESS AND THE LIFE COURSE Status and role changes over the life course generate different

stressors and condition differential access to mediating resources (Pearlin and Skaff 1996)

The life course perspective in the sociology of mental health Interplay of individual lives and historical times The timing of lives (transitions) Linked lives Human agency

The long arm of childhood (Hayward and Gorman, 2004) cumulative burden of adversity the impact of early mental illness

Turning points or transitions in children’s lives school entry changing schools moving to a different neighborhood addition and subtraction to the household parental job loss poverty child care

Linked lives parental mental health parenting parents’ jobs and children’s lives

TRAJECTORIES IN MENTAL HEALTH RESEARCH Trajectories of symptoms Trajectories of diagnosed episodes Trajectories of social experiences Trajectories of psychosocial resources Trajectory of mastery, agency

CAUTIONS ABOUT TRAJECTORIES Limited number of data points

data points may not correspond to role transitionsSample acquisition bias and attrition bias

who volunteers? who persistently participates?Source of reports about children’s lives change over the life courseSparse data for analyses of trajectories of diagnosed illness

Eaton et al. (2008) – 1071 participants in 1993 Baltimore ECA 23 year prospective study only 92 had a first episode of MDD 50% recovered with no remission 35% had at least one recurrent episode 15% had unremitting depression

The high prevalence of flat trajectories of continuous measures and sparse trajectories of change

GROWTH CURVE ANALYSES or

GROWTH MIXTURE MODELS WITH LATENT CLASSES Wickrama et al. (2008), Family Transition Project

485 adolescents over 10 years (1989 – 2001) depression subscale from SCL-90-R (range 13 – 65) comparison of traditional growth curve analysis of

entire sample with latent class clusters derived from growth mixture models

Lessons we can learn both GCA and GMM with latent clusters are

wholesale data reduction techniques latent cluster approaches may help us reduce

massive heterogeneity of change over time into meaningful trajectories

we can then estimate how these trajectories are associated with

antecedent transitions consequent social outcomes other concomitant trajectories

5

10

15

20

25

T1 T2 T3Early Onset

5%

10%

15%

20%

25% MDD CES-D

16%

31%

32%

21%

More progress with conceptually or theoretically driven research on trajectories

DOHaD the neuroinflammation hypothesis ecological or multilevel developmental models life course epidemiology life course sociology

Enables the testing of alternative hypotheses which is the goal of good science

THANK YOU!