OBSERVED CONFLICT AND ASTHMA
Supplementary Online Material (SOM) for
Naturalistically-Observed Conflict and Youth Asthma Symptoms
[MASKED AUTHOR INFORMATION]
This file includes:
Supplementary Methods
Supplementary Results
Table S1
Table S2
Table S3
Supplementary References
1
Supplementary Methods
Multiple Imputation
Multiple imputation was applied to account for the missing data and to improve statistical
power (Graham, 2009; Graham, Cumsille, & Elek‐Fisk, 2003). We used a multiple imputation
approach under a model that assumes values are missing at random meaning that the missing
values do not depend on unobserved data, given the availability of observed outcome data and
covariates (Little & Rubin, 1989). Thirty imputations were completed as recommended by
Graham et al. (2007) to prevent a falloff of statistical power. All analyses were carried out using
SPSS version 22 software.
Supplementary Results
Naturalistically-Observed and Self-Reported Conflict
We first examined bivariate correlations between caregiver-reported, youth-reported, and
EAR-observed measures of conflict. Table S1 presents bivariate correlations between all study
measures using imputed data. Notably, there were no associations between EAR-observed
conflict composites and the baseline self-reported measures of conflict (e.g., caregiver and youth
PEQ conflict). However, daily diary reports of negative interactions from the caregiver were
significantly associated with baseline caregiver-reported conflict (e.g., caregiver-PEQ), youth
daily reports of negative interactions, EAR-observed measures of interpersonal conflict, and
EAR-observed caregiver-youth conflict. Additionally, youth daily diary reports of negative
interactions were significantly correlated with baseline youth-reported conflict (e.g., youthPEQ). Further, EAR-observed interpersonal conflict and EAR-observed caregiver-youth conflict
were strongly associated, as would be expected given the composite codes share overlap (e.g.,
yelling by the mother and yelling by the youth).
Conflict and Asthma Symptoms
We next explored the associations between the measures of conflict and asthma
symptoms (See Table S2). Notably, there were no significant relationships between caregiverPEQ, youth-PEQ, and self- or daily reported asthma symptoms or EAR-observed wheezing.
However, with the daily diary reports of negative interactions, a relationship emerged. Daily
youth reports of negative caregiver-youth interactions were significantly associated with greater
daily asthma symptoms and marginally related with greater self-reported asthma symptoms.
EAR-observed interpersonal conflict was significantly associated with greater baseline selfreported asthma symptoms and daily asthma symptoms and marginally related with greater
EAR-observed wheezing. EAR-observed caregiver-youth conflict was significantly associated
with greater EAR-observed wheezing and marginally related to baseline self-reported asthma
symptoms.
Interpersonal Conflict and Asthma Symptoms
We next conducted several hierarchical multiple regression analyses to examine the
independent effects of EAR-observed interpersonal conflict and daily diary measures of conflict
on asthma symptoms. As displayed in Table S2, EAR-observed interpersonal conflict and the
daily diary indices of conflict (e.g., youth-reported negative caregiver-youth interactions and
caregiver-reported negative interactions) were entered as predictors. EAR-observed
interpersonal conflict significantly predicted increased baseline self-reported asthma symptoms
and, when daily reports of conflict where added to the regression, significantly predicted
increased self-reported asthma symptoms.
EAR-observed interpersonal conflict also significantly predicted increased asthma
symptoms reported via daily diary and when daily reports of conflict where added to the
regression equation, the relationship was marginally significant. Notably, when entering daily
reports of conflict, youth daily ratings of caregiver-youth conflict significantly predicted daily
reported asthma symptoms.
EAR-observed interpersonal conflict marginally predicted increased EAR-observed
wheezing. When including daily reports of caregiver-youth conflict in the regression, EARobserved interpersonal conflict and youth daily ratings of caregiver-youth conflict were both
marginally significant. After the addition of youth ethnicity, the relationship between EARinterpersonal conflict and EAR-observed wheezing remained marginally significant.
Caregiver-Youth Conflict and Asthma Symptoms
We then conducted several hierarchical multiple regression analyses to examine the
independent effects of EAR-observed caregiver-youth conflict and daily diary measures of
conflict on asthma symptoms. As displayed in Table S3, EAR-observed caregiver-youth conflict
and the daily diary indices of conflict (e.g., youth-reported negative caregiver-youth interactions
and caregiver-reported negative interactions) were entered as predictors. EAR-observed
caregiver-youth conflict was marginally associated with increased self-reported asthma
symptoms. When adding daily measures of conflict into the regression equation, EAR-observed
caregiver-youth conflict and youth daily ratings of caregiver-youth conflict marginally predicted
increased self-reported asthma symptoms.
EAR-observed caregiver-youth conflict was not associated with daily reported asthma
symptoms. When including daily diary reports of conflict, youth reports of negative interactions
emerged as a significant predictor of daily reported asthma symptoms and not EAR-observed
caregiver-youth conflict.
Finally, EAR-observed caregiver-youth conflict significantly predicted EAR-observed
wheezing. When including daily reports of caregiver-youth conflict in the regression, EARobserved caregiver-youth conflict remained significant. After the addition youth ethnicity, the
relationship between EAR-observed caregiver-youth conflict and EAR-observed wheezing
remained significant.
OBSERVED CONFLICT AND ASTHMA
6
Table S1
Bivariate Correlations between Study Variables using Imputed Data
1. Y-Age
2. Y-Ethnicity
3. Y-PEQ
4. C-PEQ
5. Y-NG
6. C-NG
7. EAR-Observed
Interpersonal Conflict
8. EAR-Observed
Caregiver-Youth Conflict
9. Self-Report Asthma
Symptom Questionnaire
10. Daily Diary Asthma
Symptom Composite
11. EAR-Observed
Wheezing
2
3
.08
.06
-.10
4
.04
.06
.38**
5
.12
-.11
.44**
.34**
6
.01
.01
.12
.42**
.38**
7
-.07
.01
-.03
.13
.24
.43**
8
.05
.07
-.01
.09
.24
.44**
.80**
9
-.02
.06
.07
-.10
.23+
.03
.28*
.25+
10
.07
-.04
.21
-.01
.40**
.10
.28*
11
.01
.21
-.27
-.16
-.07
.08
.30+
.18
.34*
.49**
.15
-.08
Note. + p < .10. * p < .05. ** p < .01. Y = Youth-Reported. C = Caregiver-Reported. PEQ = Parental Environment Questionnaire.
NG = Daily Negative Caregiver-Youth Interactions. EAR = Electronically Activated Recorder.
Table S2
Multiple Regression Analyses Pooled Coefficients after Multiple Imputation with EAR
Interpersonal Conflict and Daily Caregiver- and Youth-Reports Predicting Asthma Symptoms
Predictor Variables
Step 1
EAR-Observed
Interpersonal
Conflict
Step 2
EAR-Observed
Interpersonal
Conflict
Y-NG
C-NG
Step 3
EAR-Observed
Interpersonal
Conflict
Y-NG
C-NG
Y-Ethnicity
Self-Reported Asthma
Symptoms
Daily Diary Reported
Asthma Symptoms
EAR-Observed
Wheezing
b-weight (SE)
b-weight (SE)
b-weight (SE)
.42 (.19)*
.46 (.21)*
2.47 (1.46) +
-.28 (.21)
.04 (.02)*
.04 (.02)+
.46 (.14) **
-.03 (.02)
.30 (.15) +
.35 (.18) +
-1.08 (1.59) +
-.02 (.19)
.34 (.17) +
-.89 (1.57)
-.03 (.19)
.26 (.16)
Note. + p < .10. * p < .05. ** p < .01. Y = Youth-Reported. C = Caregiver-Reported.
NG = Daily Negative Caregiver-Youth Interactions.
Table S3
Multiple Regression Analyses Pooled Coefficients after Multiple Imputation with EAR
Caregiver-Youth Conflict and Daily Caregiver- and Youth-Reports Predicting Asthma
Symptoms
Predictor Variables
Step 1
EAR-Observed
Caregiver-Youth
Conflict
Step 2
EAR-Observed
Caregiver-Youth
Conflict
Y-NG
C-NG
Step 3
EAR-Observed
Caregiver-Youth
Conflict
Y-NG
C-NG
Y-Ethnicity
Self-Reported Asthma
Symptoms
Daily Diary Reported
Asthma Symptoms
EAR-Observed Wheezing
b-weight
b-weight
b-weight
.35 (.19) +
.38 (.21) +
2.52 (1.47) +
-.27 (.21)
.03 (.02)
.02 (.02)
.48 (.14)**
-.02 (.02)
.31 (.13)*
.36 (.15)*
-1.08 (1.52)
-.05 (.19)
.35 (.15)*
-.91 (1.50)
-.05 (.19)
.23 (.16)
Note. + p < .10. * p < .05. ** p < .01. Y = Youth-Reported. C = Caregiver-Reported.
NG = Daily Negative Caregiver-Youth Interactions.
Supplementary References
Graham, J. W. (2009). Missing data analysis: Making it work in the real world. Annual
review of psychology, 60, 549-576.
Graham, J. W., Cumsille, P. E., & Elek‐ Fisk, E. (2003). Methods for handling missing
data. Handbook of psychology.
Graham, J. W., Olchowski, A. E., & Gilreath, T. D. (2007). How many imputations are
really needed? Some practical clarifications of multiple imputation theory.
Prevention Science, 8(3), 206-213.
Little, R. J., & Rubin, D. B. (1989). The analysis of social science data with missing
values. Sociological Methods & Research, 18(2-3), 292-326.