In these analyses, families are considered to be a low-income household if their reported annual income is less than 2 times the Federal Poverty Level for a household of their size. Household size is calculated as the number of children in the household plus one (if the caregiver reports being singled, divorced, widowed, romantically involved but living papart, or not in any kind of relationship) or plus two otherwise.

Analyses May 7

Pre-panedemic well-being

** Comparison of income groups at baseline**

emotion test

Well-being during shelter-in-place

Caregiver anxiety

Plots

Test of slope

Weeks 1+

Baseline model

Term Coef SE t p
Fixed effects
(Intercept) 46.50 2.91 15.96 0.000
Week -3.05 1.37 -2.22 0.026
poverty -1.16 5.01 -0.23 0.816
Week:poverty 2.53 2.42 1.04 0.296
Random effects
sd__(Intercept) 27.63
sd__Observation 15.79

Can we explain the effect?

Mediator Coefficient (Income) Coefficient of mediator
access_online 0.71 2.66
black 2.94 2.33
child_insurance -0.20 2.57
decrease_nonfamilyCC 5.71* 3.42
difficulty_basics -1.58 3.21
employment_decreased 2.29 4.51
free_food 3.49 0.91
income_decreaed 0.01 2.95
insurance -0.62 2.61
latinx -2.13 3.24
losejob_sickleave -7.43* 4.49
lost_free_lunch -0.67 2.53
minority 0.72 2.43
support_decrease -1.37 2.46
Week 0 to first response

Baseline model

Term Coef SE t p
(Intercept) 17.61 0.95 18.63 0.000
poverty -2.90 1.66 -1.75 0.081

Can we explain the effect?

Mediator Coefficient (Income) Coefficient of mediator
access_online 6.21* -2.25
black -2.15 -2.76
child_insurance 4.73 -2.62
decrease_nonfamilyCC 4.68* -2.14
difficulty_basics -0.17 -2.86
employment_decreased 3.85* -4.83*
free_food -4.56* -1.21
income_decreaed 3.05 -3.54*
insurance 2.87 -2.58
latinx 1.34 -2.84
losejob_sickleave 1.93 -4.82*
lost_free_lunch 5.04* -3.29*
minority -0.80 -2.81
support_decrease 14.27* -2.19

Caregiver depression

Plots

Test of slope

Weeks 1+

Baseline model

Term Coef SE t p
Fixed effects
(Intercept) 28.35 2.67 10.61 0.000
Week -0.46 1.26 -0.37 0.713
poverty 1.40 4.59 0.31 0.760
Week:poverty 4.13 2.22 1.86 0.063
Random effects
sd__(Intercept) 25.32
sd__Observation 14.47

Can we explain the effect?

Mediator Coefficient (Income) Coefficient of mediator
access_online 0.02 4.18
black 0.48 4.04
child_insurance 0.58 4.13
decrease_nonfamilyCC 5.35* 5.04*
difficulty_basics 1.18 4.23
employment_decreased 0.61 6.11*
free_food 0.63 3.56
income_decreaed 0.45 4.53*
insurance 1.87 4.13
latinx -2.07 4.71*
losejob_sickleave -2.63 4.49
lost_free_lunch 0.23 4.08
minority 1.97 3.89
support_decrease -1.59 3.73
Week 0 to first response

Baseline model

Term Coef SE t p
(Intercept) 13.33 0.81 16.37 0.000
poverty -1.34 1.43 -0.94 0.349

Can we explain the effect?

Mediator Coefficient (Income) Coefficient of mediator
access_online 3.56* -0.97
black -2.43 -1.21
child_insurance 2.52 -1.17
decrease_nonfamilyCC 3.29* -0.80
difficulty_basics 4.69* -2.48
employment_decreased 6.19* -2.67
free_food -0.80 -1.05
income_decreaed 6.43* -2.42
insurance -0.77 -1.40
latinx 0.48 -1.25
losejob_sickleave 5.41* -1.74
lost_free_lunch 2.49 -1.53
minority -0.66 -1.28
support_decrease 14.60* -0.79

Caregiver stress

Plots

Test of slope

Weeks 1+

Baseline model

Term Coef SE t p
Fixed effects
(Intercept) 59.42 2.98 19.92 0.000
Week -2.71 1.41 -1.93 0.054
poverty -0.84 5.13 -0.16 0.870
Week:poverty 3.04 2.48 1.23 0.220
Random effects
sd__(Intercept) 28.30
sd__Observation 16.17

Can we explain the effect?

Mediator Coefficient (Income) Coefficient of mediator
access_online -2.42 2.83
black 1.00 2.94
child_insurance -0.54 3.20
decrease_nonfamilyCC 4.43 3.57
difficulty_basics 0.11 3.35
employment_decreased -2.53 5.47*
free_food 7.41* -0.43
income_decreaed -1.32 3.98
insurance -2.17 2.99
latinx -2.50 3.40
losejob_sickleave -7.80* 4.97
lost_free_lunch -1.08 3.06
minority 1.01 2.90
support_decrease -0.20 2.97
Week 0 to first response

Baseline model

Term Coef SE t p
(Intercept) 24.73 1.01 24.53 0.000
poverty -2.49 1.77 -1.40 0.161

Can we explain the effect?

Mediator Coefficient (Income) Coefficient of mediator
access_online 3.48 -2.12
black -3.75 -2.22
child_insurance 4.91 -2.19
decrease_nonfamilyCC 4.59* -1.73
difficulty_basics 5.19* -3.74*
employment_decreased 6.14* -4.77*
free_food -2.56 -1.54
income_decreaed 7.25* -3.76*
insurance 6.28* -1.75
latinx 2.25 -2.81
losejob_sickleave 4.86* -4.03
lost_free_lunch 7.56* -3.07
minority 0.66 -2.45
support_decrease 18.55* -1.78

Caregiver loneliness

Plots

Test of slope

Weeks 1+

Baseline model

Term Coef SE t p
Fixed effects
(Intercept) 42.84 2.79 15.37 0.000
Week -1.37 1.31 -1.04 0.298
poverty -0.62 4.79 -0.13 0.897
Week:poverty 3.78 2.32 1.63 0.103
Random effects
sd__(Intercept) 26.44
sd__Observation 15.11

Can we explain the effect?

Mediator Coefficient (Income) Coefficient of mediator
access_online -4.53 3.33
black -6.52 4.23
child_insurance 2.14 4.06
decrease_nonfamilyCC 1.34 3.94
difficulty_basics -0.30 4.10
employment_decreased 1.83 5.48*
free_food 3.12 2.26
income_decreaed -0.83 4.62*
insurance 4.10 4.34
latinx 3.20 3.90
losejob_sickleave -0.72 4.97
lost_free_lunch 2.01 3.60
minority -2.76 4.13
support_decrease -1.03 3.91
Week 0 to first response

Baseline model

Term Coef SE t p
(Intercept) 14.49 0.89 16.21 0.000
poverty -2.02 1.57 -1.29 0.199

Can we explain the effect?

Mediator Coefficient (Income) Coefficient of mediator
access_online 2.74 -1.74
black 1.75 -2.04
child_insurance -1.89 -2.12
decrease_nonfamilyCC 1.13 -1.84
difficulty_basics -0.60 -1.88
employment_decreased 4.48* -3.27
free_food -3.36 -0.78
income_decreaed 5.09* -3.03
insurance 1.62 -1.82
latinx -3.79 -1.50
losejob_sickleave 1.35 -2.71
lost_free_lunch 2.12 -2.19
minority -1.40 -1.85
support_decrease 18.23* -1.28

Child Externalizing

Plots

Test of slope

Weeks 1+

Baseline model

Term Coef SE t p
Fixed effects
(Intercept) 53.33 3.28 16.27 0.000
Week -2.62 1.54 -1.69 0.091
poverty -1.68 5.66 -0.30 0.766
Week:poverty 3.70 2.73 1.35 0.176
Random effects
sd__(Intercept) 31.06
sd__Observation 17.75

Can we explain the effect?

Mediator Coefficient (Income) Coefficient of mediator
access_online -2.06 3.57
black -2.90 3.92
child_insurance -5.24 3.70
decrease_nonfamilyCC -1.01 2.93
difficulty_basics 7.43* 2.08
employment_decreased 3.76 4.30
free_food 5.82 0.80
income_decreaed -2.34 4.87
insurance 1.67 4.38
latinx 1.02 3.90
losejob_sickleave -2.58 3.84
lost_free_lunch -0.02 3.64
minority 0.34 3.69
support_decrease 0.98 4.37
Week 0 to first response

Baseline model

Term Coef SE t p
(Intercept) 16.33 1.03 15.84 0.000
poverty 0.51 1.82 0.28 0.779

Can we explain the effect?

Mediator Coefficient (Income) Coefficient of mediator
access_online 3.79 0.90
black -6.60* 0.90
child_insurance 5.14 0.81
decrease_nonfamilyCC 5.32* 1.37
difficulty_basics 2.96 -0.18
employment_decreased 6.67* -1.93
free_food 3.60 -0.80
income_decreaed 7.98* -0.92
insurance 5.33 1.16
latinx 7.06* 0.17
losejob_sickleave 4.04 -0.65
lost_free_lunch 10.88* -0.34
minority -0.49 0.61
support_decrease 13.41* 1.22

Child Internalizing

Plots

Test of slope

Weeks 1+

Baseline model

Term Coef SE t p
Fixed effects
(Intercept) 24.15 2.99 8.08 0.000
Week -0.79 1.41 -0.56 0.576
poverty 1.47 5.19 0.28 0.776
Week:poverty 2.30 2.50 0.92 0.359
Random effects
sd__(Intercept) 28.28
sd__Observation 16.16

Can we explain the effect?

Mediator Coefficient (Income) Coefficient of mediator
access_online 1.77 2.56
black -2.89 2.49
child_insurance -2.66 1.93
decrease_nonfamilyCC 1.39 2.33
difficulty_basics 7.40* 0.73
employment_decreased 1.70 3.91
free_food 1.47 1.33
income_decreaed -1.95 3.19
insurance 2.14 2.29
latinx 2.14 2.76
losejob_sickleave -2.96 1.01
lost_free_lunch 5.31 1.82
minority 2.54 2.11
support_decrease -1.50 2.66
Week 0 to first response

Baseline model

Term Coef SE t p
(Intercept) 9.83 0.99 9.93 0.00
poverty 1.41 1.75 0.81 0.42

Can we explain the effect?

Mediator Coefficient (Income) Coefficient of mediator
access_online 3.91 1.79
black -0.36 1.46
child_insurance 2.13 1.43
decrease_nonfamilyCC 3.79* 2.03
difficulty_basics 4.51 0.35
employment_decreased 4.73* -0.20
free_food 0.40 1.26
income_decreaed 5.69* 0.36
insurance 1.85 1.60
latinx -3.44 1.95
losejob_sickleave 2.34 -0.17
lost_free_lunch 5.94* 0.93
minority -1.31 1.54
support_decrease 9.38* 1.88

Analyses May 6

Well-being during shelter-in-place

Compared to general population

Caregiver anxiety

Caregiver depression

Caregiver stress

Caregiver loneliness

Child externalizing

Child internalizing

By geographic region

Caregiver anxiety

Caregiver depression

Caregiver stress

Child externalizing

Child internalizing

By childcare

Of these caregivers, 40 have non-family childcare and 359 do not.

Of these caregivers, 208 have family childcare and 191 do not.

By use of online resources

Education

Compared to general population

Parent education interrupted

Child education interrupted

By geographic region

By childcare

Of these caregivers, 40 have non-family childcare and 359 do not.

Of these caregivers, 208 have family childcare and 191 do not.

By use of online resources

Differences

Lost income

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  week1$poverty and week1$income_decreaed
## X-squared = 29.59, df = 1, p-value = 5.337e-08
## # A tibble: 2 x 4
##   poverty     n decreased_income percent
##     <dbl> <int>            <dbl>   <dbl>
## 1       0   835              343   0.411
## 2       1   399              230   0.576

Lost non-family childcare

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  week1$poverty and week1$decrease_nonfamilyCC
## X-squared = 28.414, df = 1, p-value = 9.796e-08
## # A tibble: 2 x 4
##   poverty     n decrease_nonfamilyCC percent
##     <dbl> <int>                <dbl>   <dbl>
## 1       0   835                  478   0.572
## 2       1   399                  163   0.409

Trouble paying for basics

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  week1$poverty and week1$difficulty_basics
## X-squared = 112.15, df = 1, p-value < 2.2e-16
## # A tibble: 2 x 4
##   poverty     n difficulty_basics percent
##     <dbl> <int>             <dbl>   <dbl>
## 1       0   835                74  0.0886
## 2       1   399               132  0.331

Delayed healthcare

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  week1$poverty and week1$delay_healthcare
## X-squared = 5.6987, df = 1, p-value = 0.01698
## # A tibble: 2 x 4
##   poverty     n delay_healthcare percent
##     <dbl> <int>            <dbl>   <dbl>
## 1       0   835              494   0.592
## 2       1   399              265   0.664

Lost free lunch

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  week1$poverty and week1$lost_free_lunch
## X-squared = 16.46, df = 1, p-value = 4.968e-05
## # A tibble: 2 x 4
##   poverty     n lost_free_lunch percent
##     <dbl> <int>           <dbl>   <dbl>
## 1       0   835              67  0.0802
## 2       1   399              63  0.158

Access to telehealth

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  week1$poverty and week1$access_telehealth
## X-squared = 2.2319, df = 1, p-value = 0.1352
## # A tibble: 2 x 4
##   poverty     n access_telehealth percent
##     <dbl> <int>             <dbl>   <dbl>
## 1       0   835               325   0.389
## 2       1   399               137   0.343

Caregiver insurance

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  week1$poverty and week1$insurance
## X-squared = 41.121, df = 1, p-value = 1.431e-10
## # A tibble: 2 x 4
##   poverty     n insurance percent
##     <dbl> <int>     <dbl>   <dbl>
## 1       0   835       777   0.931
## 2       1   399       324   0.812

Child insurance

## 
##  Pearson's Chi-squared test with Yates' continuity correction
## 
## data:  week1$poverty and week1$child_insurance
## X-squared = 9.0795, df = 1, p-value = 0.002585
## # A tibble: 2 x 4
##   poverty     n child_insurance percent
##     <dbl> <int>           <dbl>   <dbl>
## 1       0   835             752   0.901
## 2       1   399             337   0.845

Testing predictors of well-being in this demo

Outcome Coefficient Estimate Std. Error p-value Corrected p-value
Lost income since pandemic (N = 230)
Caregiver anxiety 4.15 3.24 0.201 1.000
Caregiver depression 8.99 3.22 0.006 0.304
Caregiver stress 9.84 3.39 0.004 0.230
Child externalzing 5.64 3.60 0.118 1.000
Child internalizing 0.96 3.53 0.787 1.000
Lost employment since pandemic (N = 180)
Caregiver anxiety 8.62 3.46 0.013 0.688
Caregiver depression 11.17 3.46 0.001 0.085
Caregiver stress 7.87 3.71 0.035 1.000
Child externalzing 3.93 3.94 0.319 1.000
Child internalizing 2.00 3.90 0.609 1.000
Have difficulty paying for basics (N = 132)
Caregiver anxiety 14.65 3.32 0.000 0.001
Caregiver depression 16.77 3.30 0.000 0.000
Caregiver stress 17.37 3.49 0.000 0.000
Child externalzing 8.43 3.78 0.026 1.000
Child internalizing 12.28 3.69 0.001 0.062
Two or more children in household (N = 222)
Caregiver anxiety 1.37 3.22 0.671 1.000
Caregiver depression 3.39 3.22 0.293 1.000
Caregiver stress 4.88 3.40 0.152 1.000
Child externalzing 9.23 3.55 0.010 0.527
Child internalizing 3.64 3.51 0.301 1.000
Three or more children in household (N = 116)
Caregiver anxiety 0.46 3.53 0.897 1.000
Caregiver depression 0.61 3.53 0.862 1.000
Caregiver stress 5.85 3.71 0.116 1.000
Child externalzing 9.63 3.89 0.014 0.702
Child internalizing 11.01 3.81 0.004 0.233
Can access online serivices (N = 287)
Caregiver anxiety 11.81 3.52 0.001 0.057
Caregiver depression 12.24 3.51 0.001 0.038
Caregiver stress 9.39 3.73 0.013 0.651
Child externalzing 9.55 3.95 0.016 0.782
Child internalizing 14.52 3.85 0.000 0.014
Can access telehealth serivices (N = 137)
Caregiver anxiety 13.75 3.31 0.000 0.003
Caregiver depression 14.43 3.30 0.000 0.001
Caregiver stress 8.46 3.54 0.018 0.832
Child externalzing 3.34 3.75 0.373 1.000
Child internalizing 11.73 3.62 0.001 0.083
Single parents (N = 119)
Caregiver anxiety 2.85 3.50 0.417 1.000
Caregiver depression 4.68 3.49 0.182 1.000
Caregiver stress 6.03 3.68 0.103 1.000
Child externalzing -1.57 3.90 0.689 1.000
Child internalizing 6.49 3.81 0.090 1.000
Child education interrupted (N = 159)
Caregiver anxiety 0.66 3.27 0.840 1.000
Caregiver depression 1.83 3.27 0.575 1.000
Caregiver stress 1.16 3.45 0.738 1.000
Child externalzing 1.81 3.63 0.619 1.000
Child internalizing 10.38 3.53 0.004 0.210
Parent education interrupted (N = 37)
Caregiver anxiety 8.70 5.51 0.115 1.000
Caregiver depression 8.78 5.50 0.112 1.000
Caregiver stress 6.23 5.82 0.285 1.000
Child externalzing 9.35 6.08 0.125 1.000
Child internalizing 5.86 5.95 0.325 1.000
Have delayed healthcare (N = 265)
Caregiver anxiety 11.36 3.34 0.001 0.051
Caregiver depression 10.59 3.35 0.002 0.104
Caregiver stress 12.46 3.53 0.000 0.033
Child externalzing 10.69 3.72 0.004 0.244
Child internalizing 12.46 3.64 0.001 0.048
African American (N = 54)
Caregiver anxiety -5.97 4.67 0.202 1.000
Caregiver depression 0.82 4.68 0.860 1.000
Caregiver stress 1.66 4.94 0.737 1.000
Child externalzing -2.13 5.17 0.681 1.000
Child internalizing 5.98 5.12 0.245 1.000
Latinx (N = 87)
Caregiver anxiety 1.98 3.88 0.610 1.000
Caregiver depression -3.40 3.88 0.382 1.000
Caregiver stress -1.54 4.09 0.708 1.000
Child externalzing 4.81 4.34 0.268 1.000
Child internalizing -0.05 4.27 0.991 1.000
Caregivers of children with disabilities (N = 64)
Caregiver anxiety 8.29 4.34 0.057 1.000
Caregiver depression 14.78 4.30 0.001 0.046
Caregiver stress 11.30 4.59 0.014 0.709
Child externalzing 8.04 4.86 0.099 1.000
Child internalizing 22.58 4.71 0.000 0.000
Essential employees (N = 116)
Caregiver anxiety 0.82 3.53 0.816 1.000
Caregiver depression -0.73 3.53 0.836 1.000
Caregiver stress -3.08 3.72 0.408 1.000
Child externalzing 0.45 3.95 0.910 1.000
Child internalizing -2.14 3.87 0.581 1.000
Note:
Coefficients estimated using a multi-level model in which responses are nested within caregivers. In the case of binary predictors, we report the number (N) of participants who fall into the category listed. p-values are adjusted using a Holm correction

Child Internalizing

Plots

Test of slope

Weeks 1+

Baseline model

Term Coef SE t p
Fixed effects
(Intercept) 24.15 2.99 8.08 0.000
Week -0.79 1.41 -0.56 0.576
poverty 1.47 5.19 0.28 0.776
Week:poverty 2.30 2.50 0.92 0.359
Random effects
sd__(Intercept) 28.28
sd__Observation 16.16

Can we explain the effect?

Mediator Coefficient (Income) Coefficient of mediator
access_online 1.77 2.56
black -2.89 2.49
child_insurance -2.66 1.93
decrease_nonfamilyCC 1.39 2.33
difficulty_basics 7.40* 0.73
employment_decreased 1.70 3.91
free_food 1.47 1.33
income_decreaed -1.95 3.19
insurance 2.14 2.29
latinx 2.14 2.76
losejob_sickleave -2.96 1.01
lost_free_lunch 5.31 1.82
minority 2.54 2.11
support_decrease -1.50 2.66
Week 0 to first response

Baseline model

Term Coef SE t p
(Intercept) 9.83 0.99 9.93 0.00
poverty 1.41 1.75 0.81 0.42

Can we explain the effect?

Mediator Coefficient (Income) Coefficient of mediator
access_online 3.91 1.79
black -0.36 1.46
child_insurance 2.13 1.43
decrease_nonfamilyCC 3.79* 2.03
difficulty_basics 4.51 0.35
employment_decreased 4.73* -0.20
free_food 0.40 1.26
income_decreaed 5.69* 0.36
insurance 1.85 1.60
latinx -3.44 1.95
losejob_sickleave 2.34 -0.17
lost_free_lunch 5.94* 0.93
minority -1.31 1.54
support_decrease 9.38* 1.88