TY - JOUR
T1 - Conceptual comparison of constructs as first step in data harmonization
T2 - Parental sensitivity, child temperament, and social support as illustrations
AU - The Collaboration on Attachment Transmission Synthesis (CATS)
AU -
AU - Verhage, Marije L.
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 - Barone, Lavinia
AU - Behrens, Kazuko Y.
AU - Behringer, Johanna
AU - Bovenschen, Ina
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 - Mangelsdorf, Sarah
AU - Oosterman, Mirjam
AU - Pace, Cecilia S.
AU - Raby, K. Lee
AU - Crugnola, Cristina Riva
AU - Simonelli, Alessandra
AU - Spangler, Gottfried
AU - Tarabulsy, George M.
AU - Væver, Mette S.
AU - Arnott, Bronia
AU - Bailey, Heidi
AU - Brice, Patrick J.
AU - Brisch, Karl Heinz
AU - Castoro, Germana
AU - Costantino, Elisabetta
AU - Cyr, Chantal
AU - George, Carol
AU - Gloger-Tippelt, Gabriele
AU - Gojman, Sonia
AU - Harder, Susanne
AU - Howes, Carollee
AU - Teti, Doug M.
N1 - Funding Information:
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.
Publisher Copyright:
© 2022 The Author(s)
PY - 2022/1
Y1 - 2022/1
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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U2 - 10.1016/j.mex.2022.101889
DO - 10.1016/j.mex.2022.101889
M3 - Article
C2 - 36354308
AN - SCOPUS:85148687935
SN - 2215-0161
VL - 9
JO - MethodsX
JF - MethodsX
M1 - 101889
ER -