# Archiving parent-child, marital, and family social Interaction videotapes from a 33 year prospective study of the development of risk and resilience in a high risk population

> **NIH NIH R03** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2022 · $78,000

## Abstract

ABSTRACT
The Michigan Longitudinal Study (MLS) is unique for a number of reasons: (1) the study is the earliest
beginning (age 3-5 for the proband group) high risk yet also population based family study (N= 460 families) of
the emergence of substance abuse and other externalizing behaviors currently extant, (2) it is also the longest
running, having involved continuous assessment for 33 years; (3) the behavior of both biological parents as
well as step-parent(s) (N=994) was assessed in parallel, and in overlapping domains with those assessed in
the offspring (N=1091), (4) genetic data have also been collected; (5) for a substantial portion of the sample
(N= 340), neuroimaging (structural and functional MRI) has been carried out at multiple time points. (6)
Assessment involved 95 measures covering 6 domains for the offspring and 6 for parents, with data collected
at 3-year intervals for all participants, and also annually for the youth between ages 11 and 26. Data collection
formally ended in April of 2018. (7) In addition to questionnaires and ratings, in the early assessment waves
real-time observation of parental, marital, and family interaction during standardized social interaction tasks
was carried out and recorded by VHS videotape.
 This multi-level, multi-domain dataset permits characterization of risk at levels of analysis ranging from
genes to brain to behavior to environment as participants have transitioned from childhood, to adolescence, to
early adulthood. Assessment of fathers is another special feature. Publication output to date has included 180
refereed papers and 28 chapters, and has also involved collaboration with numerous non-University of
Michigan investigators who have joined us in using the data to examine their own hypotheses. To enable long
term and much broader access, the study has established an agreement to archive all data at the Inter-
university Consortium for Political and Social Research (ICPSR). Non-video data cleaning and curating have
been funded by close-out funds of the long-term MLS R01, aided by a small grant from ICPSR. Complete
transfer of the curated database is projected for this July. However, resources are insufficient to digitize and
store the 1500 social interactional videotapes involving a) the Eyberg Parent-Child interaction task (carried out
separately with each parent), (b) a standardized marital interaction problem solving task, and (c) a
standardized family interaction task. The proposed grant would provide funds to digitize the videotapes, allow
the digitized data to be stored at ICPSR, and create the ability for linkage with the remainder of the MLS
archive. Although these social/behavioral data are only a small part of the MLS database, they are unique
within the study and also to the field, in permitting analysis of microlevel social interaction (including
facial/emotional display characteristics), examining its long term predictive power, and its relationship to the
more traditional but...

## Key facts

- **NIH application ID:** 10380109
- **Project number:** 5R03HD100814-02
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** ROBERT ALPERT ZUCKER
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $78,000
- **Award type:** 5
- **Project period:** 2021-04-01 → 2024-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10380109

## Citation

> US National Institutes of Health, RePORTER application 10380109, Archiving parent-child, marital, and family social Interaction videotapes from a 33 year prospective study of the development of risk and resilience in a high risk population (5R03HD100814-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10380109. Licensed CC0.

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