research thesis proposal written and oral.
Aayushi.Potla
Example1OralResearchProposal.pptxFemale Energy Deficiency Questionnaire – FED-Q: Development and Validation
Ana Carla Chierighini Salamunes
Advisor: Dr Mary Jane De Souza
Introduction to the Problem
Exercising women
Risk of energy deficiency
Risk of Female Athlete Triad
How to detect energy deficiency?
Key background
Energy availability (EA):
(DEI-EEE)/kg FFM/day
Low EA: < 30 kcal/kg FFM/day
Energy deficiency (ED):
Triiodothyronine < 80 ng/dL
Resting metabolic rate ratio < 0.9 (Strock et al., 2020a)
Higher sensitivity to change than EA (Strock et al., 2020b)
Female athlete triad (De Souza et al., 2014)
Menstrual dysfunction
Impaired growth
Low bone mineral density
Key background
Measurements of ED might not be feasible or accessible tool for clinical/large scale use is needed
Low Energy Availability in Females – LEAF-Q (Melin et al., 2014)
Validated to detect risk of developing the Triad
Did not detect differences in EA
Did not account for EEE
High sensitivity, but low specificity low positive predictive value (Rogers et al., 2021)
Specific aims and hypotheses
The aim of this study is to develop and validate the Female Energy Deficiency Questionnaire (FED-Q), a tool to assess energy deficiency in exercising women.
H0: A questionnaire that screens for the presence of menstrual dysfunction, impaired bone health, exercise level, dietary habits, and eating disorders and disordered eating is not an accurate predictor of energy deficiency in exercising women.
H1: Energy deficiency (ED) in exercising women can be predicted with 90% sensitivity by the Female Energy Deficiency Questionnaire – FED-Q, a questionnaire that screens for: the presence of menstrual dysfunction; impaired bone health; exercise level; dietary habits; and eating disorders and disordered eating.
H2: The total score in the FED-Q will correlate with resting metabolic rate ratio and total triiodothyronine concentration.
H3: The specific scores for menstrual dysfunction and bone health will be associated and correlated, respectively, with menstrual status and bone mineral density.
General study design
Questionnaire:
Feasibility
Reliability
Validity:
TT3
RMRratio
Menstrual status
Bone mineral density
Dietary energy intake
Exercise energy expenditure
Sensitivity and specificity: low TT3 and RMRratio
Subjects
Inclusion criteria:
Women 18-35 years old
Minimum 150 min of exercise/week in the last 12 months
Athlete or non-athlete
Good health, free of chronic diseases
Exclusion criteria:
Pregnant or lactating
Hormonal contraceptives or medication that can alter calcium metabolism
Recovering from bone injury
Recruitment:
Flyers, emails, Study Finder, laboratory website
Methods
Questionnaire development and validation (Boparai et al., 2018; Tsang et al., 2017):
Menstrual status, bone health, exercise level, dietary habits, and disordered eating/eating disorders
Self-administered, ~20 close ended questions, Likert scale or yes/no answers
Demographics: age, height, weight, and age of menarche
Methods
First draft:
~60 items
Feasibility: pilot-testing in ~30 subjects
Modifications
Content validity: expert committee CVI
Modifications: final draft
Scoring system
Data collection
Expert committee discussion
Modifications
Construct validity and reliability
methods
First visit
FED-Q, RMR, DXA, TT3, urine
8-10 days interval
Wearable exercise monitor, nutrition logs, urine collection
Second visit
FED-Q, exercise and nutrition data, urine samples
Reliability
Data of first and second visits
Construct validity
FED-Q of first visit and physiological data
Stability
Correlation coefficient of first and second visit
Internal consistency
Split-half method
Analytical approach
Content validity
Expert committee
Content Validity Index (CVI)
Construct validity
Normal distribution/ transformation
Pearson’s correlation or
Spearman’s rho with physiological data
Reliability
I-CVI and S-CVIAve
Sensitivity and specificity, and T-test or Mann-Whitey test
Stability: test-retest method, correlation
Internal consistency: split-half method, correlation
Sample size calculations
Questionnaire:
5:1 100 participants for a 20-item questionnaire
n=132
95% confidence interval, standard deviation of 11.6 ng/dL TT3, margin of error of 2 ng/dL
n=165, with drop-out rate of 20%
n=195, of which 30 subjects in pilot testing
Timeline and Milestones for Success
Anticipated Results
FED-Q: feasible, reliable, and repeatable survey to assess ED in exercising women
Cut-off point will predict low TT3 and/or low RMRratio with 90% sensitivity
Scores on menstrual status menstrual dysfunction
Scores on bone health BMD
FED-Q will be a tool that is accessible, rapid, simple to use, and easy to interpret
Potential Pitfalls and Alternative Approaches to Consider
Concerns referring to feasibility, reliability, and/or validity
Minor inconsistencies reformulation of specific items
Major inconsistencies complete reformulation or investigation of a different tool
references
De Souza, M. J., Miller, B. E., Loucks, A. B., Luciano, A. A., Pescatello, L. S., Campbell, C. G., & Lasley, B. L. (1998). High frequency of luteal phase deficiency and anovulation in recreational women runners: blunted elevation in follicle-stimulating hormone observed during luteal-follicular transition. The Journal of Clinical Endocrinology & Metabolism, 83(12), 4220-4232.
De Souza, M. J., Nattiv, A., Joy, E., Misra, M., Williams, N. I., Mallinson, R. J., Gibbs, J.C., Olmsted, M., Goolsby, M., Matheson, G. (2014). 2014 Female Athlete Triad Coalition Consensus Statement on treatment and return to play of the female athlete triad: 1st International Conference held in San Francisco, California, May 2012 and 2nd International Conference held in Indianapolis, Indiana, May 2013. British journal of sports medicine, 48(4), 289-289.
De Souza, M. J., Toombs, R. J., Scheid, J. L., O'Donnell, E., West, S. L., & Williams, N. I. (2010). High prevalence of subtle and severe menstrual disturbances in exercising women: confirmation using daily hormone measures. Human reproduction, 25(2), 491-503.
Melin, A., Tornberg, Å. B., Skouby, S., Faber, J., Ritz, C., Sjödin, A., & Sundgot-Borgen, J. (2014). The LEAF questionnaire: a screening tool for the identification of female athletes at risk for the female athlete triad. British journal of sports medicine, 48(7), 540-545.
Rogers, M. A., Drew, M. K., Appaneal, R., Lovell, G., Lundy, B., Hughes, D., Vlahovich, N., Waddington, G., Burke, L. M. (2021). The Utility of the Low Energy Availability in Females Questionnaire to Detect Markers Consistent With Low Energy Availability-Related Conditions in a Mixed-Sport Cohort. International Journal of Sport Nutrition and Exercise Metabolism, 31(5), 427-437.
Sim, A., & Burns, S. F. (2021). questionnaires as measures for low energy availability (LEA) and relative energy deficiency in sport (RED-S) in athletes. Journal of Eating Disorders, 9(1), 1-13.
Strock, N. C., De Souza, M. J., & Williams, N. I. (2020b). Eating behaviours related to psychological stress are associated with functional hypothalamic amenorrhoea in exercising women. Journal of Sports Sciences, 38(21), 2396-2406.
Strock, N. C., Koltun, K. J., Mallinson, R. J., Williams, N. I., & De Souza, M. J. (2020a). Characterizing the resting metabolic rate ratio in ovulatory exercising women over 12 months. Scandinavian journal of medicine & science in sports, 30(8), 1337-1347.
Tsang, S., Royse, C. F., & Terkawi, A. S. (2017). Guidelines for developing, translating, and validating a questionnaire in perioperative and pain medicine. Saudi journal of anaesthesia, 11(Suppl 1), S80.
