Evidence map›Paper›PMID 41615545›Full record

ArticlePrevention science : the official journal of the Society for Prevention Research2026

Validation of the Observational Assessment Tool for Tailoring (OATT).

Emily S Fu, James L Merle, Cady Berkel, C Hendricks Brown, Sarah Philbin, Yiqing Fan, Jenna L McGinnis, Dania Demauro, Ariana DiGregorio, Janeth Litchey and 1 more

Abstract readValidation Study
In one paragraph

Article in Prevention science : the official journal of the Society for Prevention Research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Emily S FuDepartments of Medicine & Psychiatry and Behavioral Neuroscience, The University of Chicago, Chicago, USA. efu@uchicago.edu.ORCID 0000-0002-9070-2975
James L MerleDepartment of Population Health Sciences, Division of Health System Innovation and Research, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, UT, USA.
Cady BerkelCollege of Health Solutions, Arizona State University, Phoenix, AZ, USA.ORCID 0000-0001-9664-9485
C Hendricks BrownDepartment of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Sarah PhilbinHealth Sciences Integrated PhD Program, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Yiqing FanDepartment of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
Jenna L McGinnisDepartment of Educational Psychology, University of Utah, Salt Lake City, UT, USA.
Dania DemauroCollege of Health Solutions, Arizona State University, Phoenix, AZ, USA.
Ariana DiGregorioCollege of Health Solutions, Arizona State University, Phoenix, AZ, USA.
Janeth LitcheyCollege of Health Solutions, Arizona State University, Phoenix, AZ, USA.
Justin D SmithDepartment of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.

Funding

Development and Validation of an Observational Rating System for Individual Tailoring in Family-Based Pediatric Obesity InterventionsF31HL160534 · NHLBI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI FU, EMILY SUZAN · 2021 to 2023
$66k
CDC HHS U18DP006255NCCDPHP CDC HHS U18 DP006255NHLBI Division of Intramural Research F31HL160534NHLBI NIH HHS F31 HL160534U.S. Department of Agriculture 2018-68001-27550
6 · The paper itself

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.

Indexed as

Health BehaviorHealth Impact AssessmentAdultFemaleHealth PromotionHumansMaleMiddle AgedRandomized Controlled Trials as TopicBehavior changeImplementation fidelityMeasurement developmentPediatric obesityTailoring

Identifiers

PMID41615545
PMCPMC12999605

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.