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Dana L Rofey PhD University of Pittsburgh Department of Pediatrics (Children

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Healthy Bodies, Healthy Minds: Helping Adolescents with Polycystic Ovary Syndrome Dana L Rofey PhD University of Pittsburgh Department of Pediatrics (Children s ... – PowerPoint PPT presentation

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Title: Dana L Rofey PhD University of Pittsburgh Department of Pediatrics (Children


1
Dana L Rofey PhDUniversity of PittsburghDepartme
nt of Pediatrics (Childrens Hospital),
Psychiatry (Western Psychiatric Institute), and
PsychologyDivision of Weight Management and
Wellness
Healthy Bodies, Healthy Minds Helping
Adolescents with Polycystic Ovary Syndrome
Western Psychiatric Institute Clinic
2
Reviewed Articles
  • Rofey, D.L., Szigethy, E., Noll, R., Iobst, E.,
    Dahl, R., Arslanian, S. (2008). Cognitive
    Behavioral Therapy for adolescents with
    Polycystic Ovary Syndrome A pilot study. Journal
    of Pediatric Psychology.
  • Rofey, D.L., Hull, E.E., Phillips, J., Vogt, K.,
    Silk, J.S., Dahl, R.E. (in press). Utilizing
    EMA in pediatric obesity to quantify behavior,
    emotion, and sleep. Obesity.

3
Overview
  • Brief background and rationale
  • Present studies
  • Future directions
  • Questions/thoughts from the group

4
Background PCOS
  • 10 of women
  • Comorbidities
  • Obesity
  • Depression
  • Sleep
  • PCOS A model physical illness

5
Behavioral Intervention Why
  • Obesity
  • Depression
  • Sleep
  • Endocrine/Metabolic Functioning
  • Role of puberty

6
CBT and Functioning
  • Weight
  • Family-based
  • Different approach
  • Depression
  • Multiple sources of information
  • New technology
  • Sleep (future direction)
  • Diaries
  • Actigraphy

7
Aims
  • Aim 1 Behavioral
  • Change in weight (kg)
  • Increase in energy expenditure
  • Aim 2 Emotional
  • Change in depression (CDI KSADS)
  • Aim 3 Physiological
  • Sleep
  • Metabolic parameters

8
Screening Process
Step 1 Participants are screened for depression
(10 on the CDI) ? Step 2a Participants meet
other inclusion criteria PCOS (hyperandrogenism
oligo-ovulation exclusion of other endocrine
disorders) and are between the ages of 11 and 21
? ? Step 2b Participants complete a
semi-structured clinical interview, K-SADS
? Step 2c Participants meet DSM-IV criteria for
minor/major depressive disorder ? Step
3 Participants sign the consent to participate in
the intervention (11 sessions)
9
Method
Weight Management Solution Armband and Feedback
Device
Answer-only cellular phone
Total caloric intake
Total physical activity Number of steps Sleep
duration/efficiency
10
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11
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12
Results
Paired T-Tests Documenting Behavioral, Emotional,
and Physiological Parameters in Adolescents with
PCOS Pre- and Post-Intervention __________________
______________________________________ Variables
Pre-Tx Post-Tx t Value
Effect Mean (SD) Mean
(SD) Size ____________________________________
____________________ Depressive Symptoms
CDI 14.1(8) 8.3(7)
4.5 .39 Weight Kilograms
106(26) 99(29) 2.5
.13 Sleep PSQ 1.24(.77)
.62(.74) 2.9 .30
_________________________________________________
_______ Note N44 CDI Childrens Depression
Inventory PSQ Pediatric Sleep Questionnaire,
Sleepiness p lt .05, p lt .01 _________________
_______________________________________
13
Behavioral, Emotional, and Physiological Outcomes
Over Time
14
EMA Results
  • Ecological Momentary Assessment Pilot Data
  • Compliance rate for armband 74.7.3
  • Compliance rate for phone calls 64.2 .3
  • Higher BMIs were more likely to be compliant with
    EMA methods, rho.78, plt.01.
  • No association between compliance rates for EMA
    and level of depressive symptoms.

15
EMA Results
  • Mixed effect model
  • Significant interaction between group and
    physical activity, F (1,111) 6.17 p lt .05 in
    predicting positive mood.
  • For obese, depressed girls, physical activity
    predicts positive affect, mean 3.1
  • For controls, physical activity does not
    significantly predict positive affect, mean
    2.8.
  • SIDENOTE For controls, physical activity does
    not affect positive affect.

16
EMA Output Sample Participant
17
EMA Output Sample Scientific
18
Discussion
  • Similar underlying processes maintaining these
    changes
  • Targeting overlapping regulatory processes
  • Underlying neurobiological and genetic factors

19
Discussion
  • Neurobiological underpinnings
  • Sleep as an effective window into the brain
  • Cognitive functioning (Hannon/Rofey, Hull, Kolko,
    Chakravorty, Arslanian, to be submitted)
  • fMRI
  • BRAIN IMPLICATIONS
  • Hypothalamus Regulating intake and homeostasis
  • Anterior (amygdala, Initiation of eating
  • striatum, insula)
  • Anterior cortex (orbito- Termination of eating
  • frontal, dorsolateral)

20
Discussion
  • Genetic (chromosomes 2p, 3q, 5p, 6p, 7q, 10p,
    11q, 17p and 20q)
  • GENE ASSOCIATED PHENOTYPE
  • Leptin Satiation, metabolism
  • Ghrelin Appetite stimulation
  • PROP Taste preference
  • PPAR Fat metabolism
  • Mitochondrial
  • uncoupling proteins Energy expenditure

21
Future Directions
  • Temporal relationship Eating, physical activity,
    mood, and sleep
  • Role of physiology in depression
  • Remaining sleep disturbances
  • Behavioral impact of intervention on
  • Activation areas of the brain
  • Physiological data

22
  • Thank you Mentors
  • Ronald Dahl, MD
  • Silva Arslanian, MD
  • Thank you Collaborators
  • Robert Noll, PhD
  • Eva Szigethy, MD, PhD
  • Ronette Blake, MS
  • Ethan Hull, PhD
  • Tamara Hannon, MD
  • Pamela Murray, MD
  • Hala Tfayli, MD
  • Julie Byrne, CRNP
  • Marsha Marcus, PhD
  • Anne Marie Kuchera, RD, MA
  • Joseph Sanfilippo, MD, MBA
  • Jennifer Silk, PhD
  • KayLoni Olson, Angela Vincent, Kelly Rabenstein,
    Katherine Belendiuk, Britney Brinkman, Emily
    Hogan, Erica Stein, Glory Ojiere, Amy Gillio,
    Jenn Jones, Jill Matlock, Brittany Musselman,
    Meaghan Beckner, Rachel Metz, Megan Barna, Ashley
    Rowden, Brian Thoma
  • Weight Management Wellness Center

23
Questions to the group
  • Is an 11-session intervention enough?
  • What about weight maintenance?
  • Are children who are obese with a medical
    diagnosis qualitatively different than obese
    adolescents without a medical diagnosis?
  • Challenges with actigraphy data
  • Data analysis
  • Participant and laboratory burden
  • Is it worthwhile to scan?
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