Study Results: Methods
Browse studies focused on the design and methodology behind AOF’s long-term research.
Developing non-response weights to account for attrition-related bias in a longitudinal pregnancy cohort
Prospective cohorts may be vulnerable to bias due to attrition. Inverse probability weights have been proposed as a method to help mitigate this bias. The current study used the “All Our Families” longitudinal pregnancy cohort of 3351 maternal-infant pairs and aimed to develop inverse probability weights using logistic regression models to predict study continuation versus drop-out from baseline to the three-year data collection wave.
Conclusion The LASSO variable selection approach produced robust weights that addressed non-response bias more than the knowledge-driven approach. These weights can be applied to analyses across multiple longitudinal waves of data collection to reduce bias.
Data harmonization and data pooling from cohort studies: a practical approach for data management
Data pooling from pre-existing datasets can be useful to increase study sample size and statistical power in order to answer a research question. However, individual datasets may contain variables that measure the same construct differently, posing challenges for data pooling. Variable harmonization, an approach that can generate comparable datasets from heterogeneous sources, can address this issue in some circumstances. As an illustrative example, this paper describes the data harmonization strategies that helped generate comparable datasets across two Canadian pregnancy cohort studies: All Our Families; and the Alberta Pregnancy Outcomes and Nutrition.
2023
Pitt TM*, Hetherington E., Adhikari K*, Premji S*, Racine N, Tough SC, McDonald S. Developing non-response weights to account for attrition-related bias in a longitudinal pregnancy cohort. BMC Medical Research Methodology, 23, 295 (Dec 2023). https://doi.org/10.1186/s12874-023-02121-1
2021
Adhikari K, Patten SB, Patel AB, Premji S, Tough S, Letourneau N, Giesbrecht G, Metcalfe A. Data harmonization and data pooling from cohort studies: a practical approach for data management. International Journal of Population Data Science. 2021 Nov 30;6(1):1680. DOI: 10.23889/ijpds.v6i1.1680
2020
Stephenson NL*, Hornaday KK, Doktorchik CTA, Lyon AW, Tough SC, Slater DM. Quality assessment of RNA in long-term storage: The All Our Families biorepository. PLOS ONE. December 2020, 15(12): e0242404. DOI: 10.1371/journal.pone.0242404.
Adhikari K, Patten SB, Williamson T, Patel AB, Premji S, Tough S, Letourneau N, Giesbrecht G, Metcalfe A. Assessment of anxiety during pregnancy: Are existing multiple anxiety scales suitable and comparable in measuring anxiety during pregnancy? Journal of Psychosomatic Obstetrics & Gynecology. February 2020: 1-7. DOI: 10.1080/0167482X.2020.1725462.
2019
Stephenson N*, Hetherington E*, Dodd S*, Mathews A*, Tough S. Mitigation of participant loss to follow-up using Facebook: All Our Families Longitudinal Pregnancy Cohort. Journal of Medical Internet Research. February 2019, 21(2): e10441. DOI: 10.2196/10441.
Manhas KP*, Cui X, Tough SC. The experience of establishing data sharing & linkage platforms for administrative, research and community-service data. International Journal of Population Data Science. February 2019, 4(1): 1-8. DOI: 10.23889/ijpds.v4i1.465.
2018
Manhas K*, Dodd S*, Page S, Letourneau N, Adair CE, Cui X, Tough S. Sharing longitudinal, non-biologic birth cohort data: A cross-sectional analysis of parent consent preferences. BMC Medical Informatics and Decision Making. November 2018, 18(97): 1-11 DOI: 10.1186/s12911-018-0683-x.
2017
Dodd SX*, Manhas KP*, Page S, Letourneau N, Cui X, Tough SC. Governance and privacy in a provincial data repository: A cross-sectional analysis of longitudinal birth cohort parent participants’ perspectives on sharing adult vs. child research data. In Proceedings of the 6th International Conference on Data Science, Technology and Applications - Volume 1: DATA, Paper #30. August 2017. DOI: 10.5220/0006430802080215.
2016
Benediktsson I*, McDonald S, Tough S. Examining the psychometric properties of three standardized screening tools in a pregnant and parenting population. Maternal and Child Health Journal. July 2016, 21(2): 253-259. DOI: 10.1007/s10995-016-2128-4.
Manhas KP*, Page S, Dodd S*, Letourneau N, Ambrose A, Cui X, Tough S. Parental perspectives on consent for participation in large-scale, non-biological data repositories. Life Sciences, Society and Policy. January 2016, 12(1): 1-13. DOI: 10.1186/s40504-016-0034-6.
2015
Manhas KP*, Page S, Dodd S*, Letourneau N, Ambrose A, Cui X, Tough S. Parent perspectives on privacy and governance for a pediatric repository of non-biological, research data. Journal of Empirical Research on Human Research Ethics. February 2015, 10(1): 88-99. DOI: 10.1177/1556264614564970.
2014
McDonald SW*, Kingston D, Bayrampour H*, Dolan SM, Tough SC. Cumulative psychosocial stress, coping resources, and preterm birth. Archives of Women’s Mental Health. December 2014, 17(6):559-568. DOI: 10.1007/s00737-014-0436-5.
Bayrampour H*, McDonald S*, Fung T, Tough S. Reliability and validity of three shortened versions of the State Anxiety Inventory scale during the perinatal period. Journal of Psychosomatic Obstetrics and Gynecology. September 2014, 35(3): 101–107. DOI: 10.3109/0167482X.2014.950218.
2013
Leung BM*, McDonald SW*, Kaplan BJ, Giesbrecht GF, Tough SC. Comparison of sample characteristics in two pregnancy cohorts: community-based versus population-based recruitment methods. BMC Medical Research Methodology. December 2013, 13:149. DOI: 10.1186/1471-2288-13-149.
Bat-Erdene U*, Metcalfe A*, McDonald SW*, Tough SC. Validation of Canadian mothers’ recall of events in labour and delivery with electronic health records. BMC Pregnancy and Childbirth. January 2013, 13(Suppl 1):S3. DOI: 10.1186/1471-2393-13-S1-S3.
2012
McDonald SW*, Wall J*, Forbes K, Kingston D, Kehler H, Vekved M, Tough S. Development of a prenatal psychosocial screening tool for post-partum depression and anxiety. Paediatric and Perinatal Epidemiology. May 2012, 26(4): 316-327. DOI: 10.1111/j.1365-3016.2012.01286.x.
2010
Gracie SK*, Lyon AW, Kehler HL, Pennell CE, Dolan SM, McNeil DA, Siever JE, McDonald SW, Bocking AD, Lye SJ, Hegadoren KM, Olson DM, Tough SC. All Our Babies Cohort Study: Recruitment of a cohort to predict women at risk of preterm birth through the examination of gene expression profiles and the environment. BMC Pregnancy and Childbirth. December 2010, 10(87). DOI: 10.1186/1471-2393-10-87.