Validation of the Observational Assessment Tool for Tailoring (OATT)

Individually tailored interventions can address the myriad multi-level determinants of chronic health conditions. Limited measurement modalities to quantify tailoring disallow examining "active ingredient" effects on outcomes and implementation fidelity. The objective of this study is to develop and validate the Observational Assessment Tool for Tailoring (OATT) for behavioral prevention interventions. We developed the OATT and coded n = 172 videorecorded sessions from two trials of the Family Check-Up® 4 Health (FCU4Health), an individually tailored prevention and management program for behavioral health and obesogenic behaviors with English and Spanish-speaking participants. The sample was culturally diverse (> 65% Hispanic/Latino). Confirmatory factor analysis (CFA) tested the two-factor model. McDonald's Omega estimated internal consistency. Discriminant and predictive validity tests were conducted with FCU4Health fidelity, engagement, and health behavior outcomes, informed by the Implementation Cascade Model. CFA confirmed a two-factor structure for both trials (i.e., RMSEA ≤ 0.06, CFI and TLI of ≥ 0.95, SRMR < 0.08 chi-square p ≥ 0.05). Reliability and inter-rater reliability were good (ICC > 0.77) for both trials and English and Spanish videos. The OATT was not correlated (p > 0.05) with discriminant validity variables. Path analysis for predictive validity indicated that fidelity to the Individualized Treatment Planning factor directly predicts improvements in participant engagement (B = 0.16, p = 0.01, 95% CI [0.03-0.29]), which directly predicts improvements in parent health behaviors 12 months post-baseline (B = 0.18, p = 0.01, 95% CI [0.02-0.34]). The development of the OATT is a critical step to measure and guide tailored intervention development, implementation, and evaluation. Future studies are needed to replicate predictive validity findings and test the OATT factor structure with larger samples and different prevention initiatives.

Authors

Institutions

Publication Details

Journal
Prevention Science
Published
2026-01-30
DOI
https://doi.org/10.1007/s11121-026-01879-2
Primary Topic
Health Policy Implementation Science
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Validation of the Observational Assessment Tool for Tailoring (OATT)

James L. Merle, Justin D. Smith, Yiqing Fan, Jenna L. McGinnis et al.
Prevention Science
Health Policy Implementation Science
article

Validation of the Observational Assessment Tool for Tailoring (OATT)

James L. Merle, Justin D. Smith, Yiqing Fan, Jenna L. McGinnis, Sarah Philbin, Emily S. Fu, Janeth Litchey, C. Hendricks Brown, Cady Berkel, Ariana DiGregorio, Dania Demauro
article en

Abstract

Individually tailored interventions can address the myriad multi-level determinants of chronic health conditions. Limited measurement modalities to quantify tailoring disallow examining "active ingredient" effects on outcomes and implementation fidelity. The objective of this study is to develop and validate the Observational Assessment Tool for Tailoring (OATT) for behavioral prevention interventions. We developed the OATT and coded n = 172 videorecorded sessions from two trials of the Family Check-Up® 4 Health (FCU4Health), an individually tailored prevention and management program for behavioral health and obesogenic behaviors with English and Spanish-speaking participants. The sample was culturally diverse (> 65% Hispanic/Latino). Confirmatory factor analysis (CFA) tested the two-factor model. McDonald's Omega estimated internal consistency. Discriminant and predictive validity tests were conducted with FCU4Health fidelity, engagement, and health behavior outcomes, informed by the Implementation Cascade Model. CFA confirmed a two-factor structure for both trials (i.e., RMSEA ≤ 0.06, CFI and TLI of ≥ 0.95, SRMR < 0.08 chi-square p ≥ 0.05). Reliability and inter-rater reliability were good (ICC > 0.77) for both trials and English and Spanish videos. The OATT was not correlated (p > 0.05) with discriminant validity variables. Path analysis for predictive validity indicated that fidelity to the Individualized Treatment Planning factor directly predicts improvements in participant engagement (B = 0.16, p = 0.01, 95% CI [0.03-0.29]), which directly predicts improvements in parent health behaviors 12 months post-baseline (B = 0.18, p = 0.01, 95% CI [0.02-0.34]). The development of the OATT is a critical step to measure and guide tailored intervention development, implementation, and evaluation. Future studies are needed to replicate predictive validity findings and test the OATT factor structure with larger samples and different prevention initiatives.

Prevention ScienceVol. 27(2)
Northwestern University (US), American University (US), University of Utah (US), University of Chicago (US), Arizona State University (US)
U.S. Department of Agriculture, Centers for Disease Control and Prevention, Health Resources and Services Administration, National Heart, Lung, and Blood Institute, National Institute on Minority Health and Health Disparities
Reduced inequalities
Openalex Percentile: Top 75%
Health Policy Implementation Science
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.