Conceptual comparison of constructs as first step in data harmonization: Parental sensitivity, child temperament, and social support as illustrations

Marije Verhage; Carlo Schuengel; Annaleena Holopainen; Marian J. Bakermans-Kranenburg; Annie Bernier; Geoffrey L. Brown; Sheri Madigan; Glenn I. Roisman; Mette S. Vaever; Maria S. Wong; Marian J. Bakermans-Kranenburg; Lavinia Barone; Kazuko Y. Behrens; Johanna Behringer; Annie Bernier; Ina Bovenschen; Geoffrey L. Brown; Rosalinda Cassibba; Jude Cassidy; Gabrielle Coppola; Alessandro Costantini; Mary Dozier; Karin Ensink; R. M. Pasco Fearon; Brent Finger; Airi Hautamaki; Nancy L. Hazen; Elena Ierardi; Inês Jongenelen; Simo Køppe; Francesca Lionetti; Sheri Madigan; Sarah Mangelsdorf; Mirjam Oosterman; Cecilia S. Pace; K. Lee Raby; Cristina Riva Crugnola; Glenn I. Roisman; Carlo Schuengel; Alessandra Simonelli; Gottfried Spangler; George M. Tarabulsy; Mette S. Væver; Marije Verhage; Maria S. Wong; Bronia Arnott; Heidi Bailey; Patrick J. Brice; Karl-Heinz Brisch; Germana Castoro; Elisabetta Costantino

doi:10.1016/j.mex.2022.101889

Conceptual comparison of constructs as first step in data harmonization: Parental sensitivity, child temperament, and social support as illustrations

Marije Verhage, Carlo Schuengel, Annaleena Holopainen, Marian J. Bakermans-Kranenburg, Annie Bernier, Geoffrey L. Brown, Sheri Madigan, Glenn I. Roisman, Mette S. Vaever, Maria S. Wong, Marian J. Bakermans-Kranenburg, Lavinia Barone, Kazuko Y. Behrens, Johanna Behringer, Annie Bernier, Ina Bovenschen, Geoffrey L. Brown, Rosalinda Cassibba, Jude Cassidy, Gabrielle CoppolaAlessandro Costantini, Mary Dozier, Karin Ensink, R. M. Pasco Fearon, Brent Finger, Airi Hautamaki, Nancy L. Hazen, Elena Ierardi, Inês Jongenelen, Simo Køppe, Francesca Lionetti, Sheri Madigan, Sarah Mangelsdorf, Mirjam Oosterman, Cecilia S. Pace, K. Lee Raby, Cristina Riva Crugnola, Glenn I. Roisman, Carlo Schuengel, Alessandra Simonelli, Gottfried Spangler, George M. Tarabulsy, Mette S. Væver, Marije Verhage, Maria S. Wong, Bronia Arnott, Heidi Bailey, Patrick J. Brice, Karl-Heinz Brisch, Germana Castoro, Elisabetta Costantino

Research output: Contribution to Journal › Article › Academic › peer-review

Abstract

This article presents a strategy for the initial step of data harmonization in Individual Participant Data syntheses, i.e., making decisions as to which measures operationalize the constructs of interest - and which do not. This step is vital in the process of data harmonization, because a study can only be as good as its measures. If the construct validity of the measures is in question, study results are questionable as well. Our proposed strategy for data harmonization consists of three steps. First, a unitary construct is defined based on the existing literature, preferably on the theoretical framework surrounding the construct. Second, the various instruments used to measure the construct are evaluated as operationalizations of this construct, and retained or excluded based on this evaluation. Third, the scores of the included measures are recoded on the same metric. We illustrate the use of this method with three example constructs focal to the Collaboration on Attachment Transmission Synthesis (CATS) study: parental sensitivity, child temperament, and social support. This process description may aid researchers in their data pooling studies, filling a gap in the literature on the first step of data harmonization.

•Data harmonization in studies using combined datasets is of vital importance for the validity of the study results.
•We have developed and illustrated a strategy on how to define a unitary construct and evaluate whether instruments are operationalizations of this construct as the initial step in the harmonization process.
•This strategy is a transferable and reproducible method to apply to the data harmonization process.

Original language	English
Article number	101889
Pages (from-to)	1-17
Number of pages	17
Journal	MethodsX
Volume	9
Early online date	26 Oct 2022
DOIs	https://doi.org/10.1016/j.mex.2022.101889
Publication status	Published - 2022

Funding

This work was supported by a grant from Stichting tot Steun Nederland to M. Oosterman and C. Schuengel, a grant from the Social Sciences and Humanities Research Council Canada (No. 430-2015-00989 ) to S. Madigan, a grant from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD; R01 HD102035 ) to G. I. Roisman, and a Veni grant by the Dutch Research Council (No. 451-17-010 ) to M. L. Verhage. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the grant agencies.

Funders	Funder number
Stichting tot Steun Nederland
Eunice Kennedy Shriver National Institute of Child Health and Human Development	R01 HD102035
Social Sciences and Humanities Research Council of Canada	430-2015-00989
Nederlandse Organisatie voor Wetenschappelijk Onderzoek	451-17-010

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Verhage, M., Schuengel, C., Holopainen, A., Bakermans-Kranenburg, M. J., Bernier, A., Brown, G. L., Madigan, S., Roisman, G. I., Vaever, M. S., Wong, M. S., Bakermans-Kranenburg, M. J., Barone, L., Behrens, K. Y., Behringer, J., Bernier, A., Bovenschen, I., Brown, G. L., Cassibba, R., Cassidy, J., ... Costantino, E. (2022). Conceptual comparison of constructs as first step in data harmonization: Parental sensitivity, child temperament, and social support as illustrations. MethodsX, 9, 1-17. Article 101889. https://doi.org/10.1016/j.mex.2022.101889

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title = "Conceptual comparison of constructs as first step in data harmonization: Parental sensitivity, child temperament, and social support as illustrations",

abstract = "This article presents a strategy for the initial step of data harmonization in Individual Participant Data syntheses, i.e., making decisions as to which measures operationalize the constructs of interest - and which do not. This step is vital in the process of data harmonization, because a study can only be as good as its measures. If the construct validity of the measures is in question, study results are questionable as well. Our proposed strategy for data harmonization consists of three steps. First, a unitary construct is defined based on the existing literature, preferably on the theoretical framework surrounding the construct. Second, the various instruments used to measure the construct are evaluated as operationalizations of this construct, and retained or excluded based on this evaluation. Third, the scores of the included measures are recoded on the same metric. We illustrate the use of this method with three example constructs focal to the Collaboration on Attachment Transmission Synthesis (CATS) study: parental sensitivity, child temperament, and social support. This process description may aid researchers in their data pooling studies, filling a gap in the literature on the first step of data harmonization. •Data harmonization in studies using combined datasets is of vital importance for the validity of the study results. •We have developed and illustrated a strategy on how to define a unitary construct and evaluate whether instruments are operationalizations of this construct as the initial step in the harmonization process. •This strategy is a transferable and reproducible method to apply to the data harmonization process.",

author = "Marije Verhage and Carlo Schuengel and Annaleena Holopainen and Bakermans-Kranenburg, \{Marian J.\} and Annie Bernier and Brown, \{Geoffrey L.\} and Sheri Madigan and Roisman, \{Glenn I.\} and Vaever, \{Mette S.\} and Wong, \{Maria S.\} and Bakermans-Kranenburg, \{Marian J.\} and Lavinia Barone and Behrens, \{Kazuko Y.\} and Johanna Behringer and Annie Bernier and Ina Bovenschen and Brown, \{Geoffrey L.\} and Rosalinda Cassibba and Jude Cassidy and Gabrielle Coppola and Alessandro Costantini and Mary Dozier and Karin Ensink and Fearon, \{R. M. Pasco\} and Brent Finger and Airi Hautamaki and Hazen, \{Nancy L.\} and Elena Ierardi and In{\^e}s Jongenelen and Simo K{\o}ppe and Francesca Lionetti and Sheri Madigan and Sarah Mangelsdorf and Mirjam Oosterman and Pace, \{Cecilia S.\} and Raby, \{K. Lee\} and Crugnola, \{Cristina Riva\} and Roisman, \{Glenn I.\} and Carlo Schuengel and Alessandra Simonelli and Gottfried Spangler and Tarabulsy, \{George M.\} and V{\ae}ver, \{Mette S.\} and Marije Verhage and Wong, \{Maria S.\} and Bronia Arnott and Heidi Bailey and Brice, \{Patrick J.\} and Karl-Heinz Brisch and Germana Castoro and Elisabetta Costantino",

year = "2022",

doi = "10.1016/j.mex.2022.101889",

language = "English",

volume = "9",

pages = "1--17",

journal = "MethodsX",

issn = "2215-0161",

publisher = "Elsevier",

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Verhage, M , Schuengel, C, Holopainen, A, Bakermans-Kranenburg, MJ, Bernier, A, Brown, GL, Madigan, S, Roisman, GI, Vaever, MS, Wong, MS, Bakermans-Kranenburg, MJ, Barone, L, Behrens, KY, Behringer, J, Bernier, A, Bovenschen, I, Brown, GL, Cassibba, R, Cassidy, J, Coppola, G, Costantini, A, Dozier, M, Ensink, K, Fearon, RMP, Finger, B, Hautamaki, A, Hazen, NL, Ierardi, E, Jongenelen, I, Køppe, S, Lionetti, F, Madigan, S, Mangelsdorf, S, Oosterman, M, Pace, CS, Raby, KL, Crugnola, CR, Roisman, GI, Schuengel, C, Simonelli, A, Spangler, G, Tarabulsy, GM, Væver, MS, Verhage, M, Wong, MS, Arnott, B, Bailey, H, Brice, PJ, Brisch, K-H, Castoro, G & Costantino, E 2022, 'Conceptual comparison of constructs as first step in data harmonization: Parental sensitivity, child temperament, and social support as illustrations', MethodsX, vol. 9, 101889, pp. 1-17. https://doi.org/10.1016/j.mex.2022.101889

TY - JOUR

T1 - Conceptual comparison of constructs as first step in data harmonization: Parental sensitivity, child temperament, and social support as illustrations

AU - Verhage, Marije

AU - Schuengel, Carlo

AU - Holopainen, Annaleena

AU - Bakermans-Kranenburg, Marian J.

AU - Bernier, Annie

AU - Brown, Geoffrey L.

AU - Madigan, Sheri

AU - Roisman, Glenn I.

AU - Vaever, Mette S.

AU - Wong, Maria S.

AU - Bakermans-Kranenburg, Marian J.

AU - Barone, Lavinia

AU - Behrens, Kazuko Y.

AU - Behringer, Johanna

AU - Bernier, Annie

AU - Bovenschen, Ina

AU - Brown, Geoffrey L.

AU - Cassibba, Rosalinda

AU - Cassidy, Jude

AU - Coppola, Gabrielle

AU - Costantini, Alessandro

AU - Dozier, Mary

AU - Ensink, Karin

AU - Fearon, R. M. Pasco

AU - Finger, Brent

AU - Hautamaki, Airi

AU - Hazen, Nancy L.

AU - Ierardi, Elena

AU - Jongenelen, Inês

AU - Køppe, Simo

AU - Lionetti, Francesca

AU - Madigan, Sheri

AU - Mangelsdorf, Sarah

AU - Oosterman, Mirjam

AU - Pace, Cecilia S.

AU - Raby, K. Lee

AU - Crugnola, Cristina Riva

AU - Roisman, Glenn I.

AU - Schuengel, Carlo

AU - Simonelli, Alessandra

AU - Spangler, Gottfried

AU - Tarabulsy, George M.

AU - Væver, Mette S.

AU - Verhage, Marije

AU - Wong, Maria S.

AU - Arnott, Bronia

AU - Bailey, Heidi

AU - Brice, Patrick J.

AU - Brisch, Karl-Heinz

AU - Castoro, Germana

AU - Costantino, Elisabetta

PY - 2022

Y1 - 2022

N2 - This article presents a strategy for the initial step of data harmonization in Individual Participant Data syntheses, i.e., making decisions as to which measures operationalize the constructs of interest - and which do not. This step is vital in the process of data harmonization, because a study can only be as good as its measures. If the construct validity of the measures is in question, study results are questionable as well. Our proposed strategy for data harmonization consists of three steps. First, a unitary construct is defined based on the existing literature, preferably on the theoretical framework surrounding the construct. Second, the various instruments used to measure the construct are evaluated as operationalizations of this construct, and retained or excluded based on this evaluation. Third, the scores of the included measures are recoded on the same metric. We illustrate the use of this method with three example constructs focal to the Collaboration on Attachment Transmission Synthesis (CATS) study: parental sensitivity, child temperament, and social support. This process description may aid researchers in their data pooling studies, filling a gap in the literature on the first step of data harmonization. •Data harmonization in studies using combined datasets is of vital importance for the validity of the study results. •We have developed and illustrated a strategy on how to define a unitary construct and evaluate whether instruments are operationalizations of this construct as the initial step in the harmonization process. •This strategy is a transferable and reproducible method to apply to the data harmonization process.

AB - This article presents a strategy for the initial step of data harmonization in Individual Participant Data syntheses, i.e., making decisions as to which measures operationalize the constructs of interest - and which do not. This step is vital in the process of data harmonization, because a study can only be as good as its measures. If the construct validity of the measures is in question, study results are questionable as well. Our proposed strategy for data harmonization consists of three steps. First, a unitary construct is defined based on the existing literature, preferably on the theoretical framework surrounding the construct. Second, the various instruments used to measure the construct are evaluated as operationalizations of this construct, and retained or excluded based on this evaluation. Third, the scores of the included measures are recoded on the same metric. We illustrate the use of this method with three example constructs focal to the Collaboration on Attachment Transmission Synthesis (CATS) study: parental sensitivity, child temperament, and social support. This process description may aid researchers in their data pooling studies, filling a gap in the literature on the first step of data harmonization. •Data harmonization in studies using combined datasets is of vital importance for the validity of the study results. •We have developed and illustrated a strategy on how to define a unitary construct and evaluate whether instruments are operationalizations of this construct as the initial step in the harmonization process. •This strategy is a transferable and reproducible method to apply to the data harmonization process.

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DO - 10.1016/j.mex.2022.101889

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JO - MethodsX

JF - MethodsX

M1 - 101889

ER -

Conceptual comparison of constructs as first step in data harmonization: Parental sensitivity, child temperament, and social support as illustrations

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