New research| Volume 60, ISSUE 4, P513-523, April 01, 2021

Change in Youth Mental Health During the COVID-19 Pandemic in a Majority Hispanic/Latinx US Sample

Published:December 24, 2020

Objective

Children and adolescents, individuals from racial and ethnic minority groups, and those with mental health conditions may be at greater risk for worsened mental health because of the COVID-19 pandemic. This study examined change in mental health from before to during the pandemic among predominantly Hispanic/Latinx adolescents.

Method

A total of 322 young adolescents (mean age = 11.99 years, 55% female and 45% male), with a racial/ethnic composition of 72.7% Hispanic/Latinx, 9.3% Black or African American, 5.9% multiple races, 5.0% Asian, 1.6% White, and 1.2% American Indian, completed a mental health screening measure prior to the COVID-19 pandemic and at 3 time-points beginning 1 month after COVID-19 stay-at-home measures were implemented. A subsample also completed a survey about their experience at home during COVID-19. Repeated-measures mixed analysis of covariance was used to evaluate change in each mental health domain, and whether youths who had elevated symptoms at baseline differed in their level of change, controlling for age and gender.

Results

For youths who had elevated levels of mental health problems before the pandemic, symptoms were significantly reduced across domains during the pandemic. Reductions in internalizing, externalizing, and total problems were clinically significant. For other youths, there were statistically significant reductions in internalizing and total problems, and no change in attention or externalizing problems. Post hoc analyses revealed that better family functioning was consistently related to lower mental health symptoms in youths during COVID-19 follow-ups.

Conclusion

COVID-19 stay-at-home regulations may offer protective effects for youth mental health. Study results may be specific to this population of predominantly Hispanic/Latinx youths from a large city in the southwestern United States.

Key Words

The 2019 novel coronavirus disease (COVID-19) was characterized as a pandemic by the World Health Organization (WHO) on March 11, 2020.
WHO Director-General's opening remarks at the media briefing on COVID-19, 11 March 2020. World Health Organization.
Widespread lockdown or stay-at-home measures were put in place in order to reduce transmission. These measures also led to detrimental impacts on the global economy, financial burden for many families, and the closing of in-person schooling in spring 2020. The combination of virus-related fears, confinement and social isolation, and financial stress has understandably led to concern over the consequences of the pandemic on mental health, including the mental health of children and adolescents.
• Cluver L.
• Lachman J.M.
• Sherr L.
• et al.
Parenting in a time of COVID-19.
,
• Prime H.
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Risk and resilience in family well-being during the COVID-19 pandemic.
Youths are thought to be more vulnerable to mental health problems during the pandemic, because many mental health disorders begin during childhood and adolescence.
• Golberstein E.
• Wen H.
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Coronavirus disease 2019 (COVID-19) and mental health for children and adolescents.
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• Zhou X.
Managing psychological distress in children and adolescents following the COVID-19 epidemic: a cooperative approach.
Researchers have pointed to the disruption in daily routines,
• Lee J.
Mental health effects of school closures during COVID-19.
reduction in physical activity, increase in screen time,
• Wang G.
• Zhang Y.
• Zhao J.
• Zhang J.
• Jiang F.
Mitigate the effects of home confinement on children during the COVID-19 outbreak.
reduction in play and time with peers,
WHO–UNICEF–Lancet Commissioners
After COVID-19, a future for the world's children?.
media hype,
• Cluver L.
• Lachman J.M.
• Sherr L.
• et al.
Parenting in a time of COVID-19.
families sharing restricted spaces,
• Clemens V.
• Deschamps P.
• Fegert J.M.
• et al.
Potential effects of "social" distancing measures and school lockdown on child and adolescent mental health.
caregiver burden,
• Prime H.
• Browne D.T.
Risk and resilience in family well-being during the COVID-19 pandemic.
and increased reports of maltreatment and other adverse childhood experiences during the pandemic
• Bryant D.J.
• Oo M.
• Damian A.J.
The rise of adverse childhood experiences during the COVID-19 pandemic.
,
• Cuartas J.
Heightened risk of child maltreatment amid the COVID-19 pandemic can exacerbate mental health problems for the next generation.
as additional risk factors for mental health problems in children and adolescents during COVID-19. In particular, young adolescents may have an exacerbated risk of mental health concerns related to the pandemic, due to the combination of pubertal development and social reorientation during the early adolescent period (beginning at age 10 years), combined with social deprivation from peers because of social distancing.
• Orben A.
• Tomova L.
• Blakemore S.-J.
The effects of social deprivation on adolescent development and mental health.
Youths from racial and ethnic minority groups are also thought to be at heightened risk for experiencing adverse mental health consequences related to COVID-19.
WHO–UNICEF–Lancet Commissioners
After COVID-19, a future for the world's children?.
,
Centers for Disease Control and Prevention
Mental health and coping during COVID-19.
These youths are already negatively affected by health disparities, which have been exacerbated further by the pandemic.

Stark AM, White AE, Rotter NS, Basu A, Shifting from survival to supporting resilience in children and families in the COVID-19 pandemic: lessons for informing U.S. mental health priorities. Psychol Trauma. 2020;2:S133-S135.

There has also been a higher burden of COVID-19 illness and death among racial and ethnic minority groups in the United States.
Centers for Disease Control and Prevention
Coronavirus Disease 2019 (COVID-19).
Another group who may have heightened mental health risk during COVID-19 are youths who had pre-existing mental health conditions, due to increased stress during COVID-19 as well as potential disruptions in mental health care.
• Golberstein E.
• Wen H.
• Miller B.F.
Coronavirus disease 2019 (COVID-19) and mental health for children and adolescents.
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• Lee J.
Mental health effects of school closures during COVID-19.
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Centers for Disease Control and Prevention
Mental health and coping during COVID-19.
,
• Cui Y.
• Li Y.
• Zheng Y.
Chinese Society of Child & Adolescent Psychiatry Mental health services for children in China during the COVID-19 pandemic: results of an expert-basednational survey among child and adolescent psychiatric hospitals.
Research conducted this far has found elevated mental health concerns among adults during COVID-19 compared to time-points prior to the pandemic,
• Daly M.
• Sutin A.R.
• Robinson E.
Depression reported by US adults in 2017-2018 and March and April 2020.
,
• Pierce M.
• Hope H.
• Ford T.
• et al.
Mental health before and during the COVID-19 pandemic: a longitudinal probability sample survey of the UK population.
and has also shown that Hispanic/Latinx adults have reported higher psychological distress relative to other racial/ethnic groups during COVID-19.
• Fitzpatrick K.M.
• Harris C.
• Drawve G.
Fear of COVID-19 and the mental health consequences in America.
,
• McGinty E.E.
• Presskreischer R.
• Han H.
• Barry C.L.
Psychological distress and loneliness reported by US Adults in 2018 and April 2020.
However, there is less research among youth samples. Liang et al.
• Liang L.
• Ren H.
• Cao R.
• et al.
The effect of COVID-19 on youth mental health.
showed that 40.4% of children reported psychological problems 2 weeks after the outbreak of COVID-19 in China. Zhang et al.
• Zhang J.
• Shuai L.
• Yu H.
• et al.
Acute stress, behavioural symptoms and mood states among school-age children with attention-deficit/hyperactive disorder during the COVID-19 outbreak.
found that, for children in China with an existing diagnosis of attention-deficit/hyperactivity disorder, there were higher behavior symptoms during the COVID-19 outbreak than typical. Orgiles et al.

Orgilés M, Morales A, Delvecchio E, Mazzeschi C, Espada JP. Immediate psychological effects of the COVID-19 quarantine in youth from Italy and Spain, Front Psychol. 2020;11:579038.

found that caregivers in Spain and Italy reported negative emotional and behavioral changes in their children aged 3 to 18 years. Secer and Ulas

Seçer İ, Ulaş S. An investigation of the effect of COVID-19 on OCD in youth in the context of emotional reactivity, experiential avoidance, depression and anxiety. Int J Ment Health Addict. 2020;1-14.

showed that among adolescents in Turkey, fear of COVID-19 predicted increased obsessive-compulsive, depression, and anxiety symptoms. Zhou et al.
• Zhou S.J.
• Zhang L.G.
• Wang L.L.
• et al.
Prevalence and socio-demographic correlates of psychological health problems in Chinese adolescents during the outbreak of COVID-19.
found rates of depressive and anxiety symptoms of 43.7% and 37.4%, respectively, among 12- to 18-year-olds in China during COVID-19. In Austria, adolescent psychiatric outpatients showed worsened psychosocial functioning during the pandemic after switching from in-person to teletherapy.

Huscsava MM, Scharinger C, Plener PL, Kothgassner OD. “Bridge over troubled water”: a first look at adolescent psychiatric outpatients transited from regular care to teletherapy during the COVID-19 outbreak using quantitative and qualitative analyses. Published online July 9, 2020. https://doi.org/10.21203/rs.3.rs-40679/v1.

In summary, studies thus far suggest that there may be worsened mental health in children and adolescents due to the pandemic.
However, there is a need for more research. There is a lack of research from samples in the United States, where the outbreak timing and response differed from those of many Asian and European countries. In addition, studies have tended to examine mental health in specific domains, preventing a broad picture of mental health consequences of the pandemic in youths. Finally, studies have generally been cross-sectional in nature, and longitudinal studies are needed.
• Prime H.
• Browne D.T.
Why we need longitudinal mental health research with children and youth during (and after) the COVID-19 pandemic.
The current study seeks to address these gaps by reporting on longitudinal change in mental health across multiple domains, from before and during the COVID-19 pandemic, in a sample of US adolescents. Specifically, in this study, we examine mental health change in a sample of 10- to 14-year-old youths who are majority Hispanic/Latinx, and test whether change over time was different for youths with pre-existing mental health problems.
The aims of the current study are as follows: (1) to provide descriptive data on the impact of COVID-19 one month after stay-at-home measures were put in place, in a subsample of youth who completed a COVID-19 survey; and (2) to examine change in mental health, including internalizing, attention, externalizing, and total mental health problems, from before the pandemic (January 2020, when COVID-19 had been identified in only 1 US patient) to during the outbreak (at 3 follow-up time-points in April/May 2020); and finally (3) to conduct, in the COVID-19 survey subsample, further post hoc analyses to test whether job loss or family functioning influenced change in youth mental health.

Method

Participants and Procedure

Participants were individuals 10- to 14 years of age in grades 5 to 8 who were attending a public charter middle school in a large city in the southwestern United States. The demographics of the school reflect the surrounding neighborhood, which is the city’s most densely populated neighborhood, with over 90% of residents living in large apartment complexes and 71% Latinx/Hispanic residents. Many of the area residents have immigrated from Mexico and Central America. Most residents in the area are employed in the service sector, and the area had a median family income of $29,124 in 2017,$20,000 less than the city average. Although immigration issues are significant issues for this population, immigration status of this sample was not assessed.
Students completed baseline assessments as part of a larger study in January 2020, prior to the spread of COVID-19 in the United States. All students attending the school had the opportunity to complete baseline assessments. Surveys were completed by students during school using Qualtrics survey software. Because of the COVID-19 pandemic, schools in the local district were closed beginning on March 13, 2020, with school conducted online through the end of the school year. Beginning 1 month after in-person school closure (mid-April 2020), follow-up assessments were sent electronically to students at the school on a bi-weekly basis to evaluate students’ mental health during the COVID-19 pandemic and the effects of the pandemic for students at home. Institutional review board approval was obtained for all study procedures. Students were included in current analysis if they completed baseline assessments and at least 1 of the Brief Problem Monitor (BPM; see later here) follow-up assessments.
Table 1 provides a summary of sample demographics for the baseline sample, main study (BPM) sample, and subsample that completed the COVID-19 survey. Of 464 students enrolled at the school, a total of 424 (91.4%) were present the day of the survey, assented, and completed the baseline study in January 2020. Of these 424 students, 389 (91.7%) had BPM data at baseline, and 322 of 389 (82.8%) completed the BPM during at least 1 follow-up and were included in the main study sample. Significantly more girls than boys completed at least 1 follow-up [χ2(1) = 6.80, p = .009]. Students who completed at least 1 follow-up were also significantly older than those who did not [t(388) = −2.45, p = .02]. There were no differences between those who completed at least 1 follow-up and those who did not in terms of grade level, ethnicity/race, or clinical group membership (all p > .07).
Table 1Sample Demographics
Baseline sample (N = 389, %)Main study (BPM) sample

(N = 322, %)
COVID-19 survey subsample (n = 185, %)
Gender
Female51.955.056.2
Male47.044.142.7
Ethnicity
Hispanic/Latinx72.872.771.9
Black/African American9.09.39.7
Asian5.45.05.4
White1.51.61.1
American Indian1.01.21.1
Multiple races5.95.95.4
Other3.94.35.4
BPM internalizing “high scorers”20.121.421.1
BPM attention “high scorers”19.821.723.2
BPM externalizing “high scorers”18.519.622.2
BPM total “high scorers”20.322.024.9
Fifth26.524.828.1
Sixth28.026.74.9
Seventh25.426.134.6
Eighth20.122.432.4
Age, mean (SD)11.91 (1.16)11.99 (1.16)12.21 (1.31)
Note: “High scorers” = highest 20% of scorers on BPM scale at baseline (ie, youth with elevated mental health problems at baseline). BPM = Brief Problem Monitor.
The sample of 322 students for the main analyses was 55.0% female (44.1% male) and had a mean age of 11.99 years (SD = 1.16). Among the students, 24.8% (80) were in 5th grade, 26.7% (86) were in 6th grade, 26.1% (84) were in 7th grade, and 22.4% (72) were in 8th grade. Students self-identified as 72.7% (234) Hispanic/Latinx, 9.3% (30) Black or African American, 5.9% (19) Multiple Races, 5.0% (16) Asian, 1.6% (5) White, 1.2% (4) American Indian, and 4.3% (14) self-identified their ethnicity or race as “other.”
A smaller subsample (n = 185) completed the survey on COVID-19 effects at home, in mid-April 2020. The smaller number for this sample likely occurred because the survey was sent on its own and was the first survey sent out by the school during COVID-19. There was also a small response rate from 6th graders, which suggests that they may have received the survey link differently from students in other grades. This sample did not differ from the main study sample in terms of gender, ethnicity, or clinical group membership (all p ≥ .16), but significantly differed in terms of grade level [χ2(3) = 108.95, p < .001] and age [t(312.92) = −4.37, p < .001].

Measures

Effects of the COVID-19 Pandemic at Home

One month into the stay-at-home period (mid-April 2020), students were sent a self-report survey about their experiences at home during the COVID-19 pandemic. The survey used items from a recently developed COVID-19 survey for youths,
• Temple J.R.
• Wood L.
• Guillot-Wright S.
• Baumler E.
• Thiel M.
• Torres E.
Coronavirus (COVID-19) Pandemic Questionnaire for Youth and Young Adults.
which was adapted for this study by adding additional questions related to family functioning. The 18 questions assessed physical contact with other people, family finances and access to food, family loss of work, media exposure, loneliness, contact with friends, and parent and child stress, in addition to several family functioning items, over the previous 2 weeks. The family functioning items were added for the purpose of this study and included items such as “Since the coronavirus pandemic, have you gotten into more conflicts with your parents?” This survey has not yet been used in published research, and evidence on reliability and validity is not yet available.

Youth Mental Health

Students completed the Brief Problem Monitor (BPM),
• Achenbach T.M.
• McConaughy S.H.
• Ivanovaa M.
• Rescorla L.A.
Manual for the ASEBA Brief Problem Monitor (BPM).
a 19-item mental health screening measure. The BPM was developed using items from the Youth Self Report,
• Achenbach T.M.
• Rescorla L.A.
Manual for the ASEBA School-Age Forms and Profiles.
a widely used measure of youth emotional and behavioral problems. The measure asks about problems over a specified period (previous 30 days was used in this study) using a response scale from 0 to 2 (0 = not true, 1 = somewhat true, 2 = very true). Raw scores from each of the 4 BPM scales (internalizing problems, attention problems, externalizing problems, and total problems) were used. Internal consistency, test−retest reliability, and construct validity evidence have been demonstrated for the BPM in a large, nationally representative sample of youths that included 14% Hispanic/Latinx youths.
• Achenbach T.M.
• McConaughy S.H.
• Ivanovaa M.
• Rescorla L.A.
Manual for the ASEBA Brief Problem Monitor (BPM).
,
• Achenbach T.M.
• Rescorla L.A.
Manual for the ASEBA School-Age Forms and Profiles.
Students completed the BPM at baseline (January 2020, pre-pandemic) and at 3 bi-weekly follow-up time-points in April and May 2020.
For each of the 4 BPM scales, an additional dichotomous variable (“high scorers”) was created to denote whether students had high levels of mental health problems at baseline, with students receiving a “1” if they were in the highest 20% of scores on that scale at baseline, and a “0” if they were in the lower 80% of scores at baseline.

Data Analytic Strategy

SPSS Version 26
IBM Corp
IBM SPSS Statistics for Windows, Version 26.0.
was used for all analyses. Descriptive statistics were first computed. BPM scores had skew and kurtosis values within range of −1 to 1 and were therefore assumed to be normally distributed. Repeated-measures mixed analysis of covariance was used to test 4 separate models, 1 for each of the BPM scales. BPM scores were entered as the within-subjects variable, with 4 levels (time-points). Group (“high scorers” or “low scorers” on each BPM scale) served as the between-subjects variable. Gender and age were included as covariates. A full factorial model was used. Significant interactions between time and group were explored further using the EMMEANS procedure in SPSS and by examining interaction graphs.
Of 322 students who completed at least 1 follow-up time-point, 252 students participated at follow-up 1, 182 at follow-up 2, and 261 at follow-up 3. There were significant differences between students who participated in follow-up 1 and those who did not based on gender (χ2 = 6.46, p = .01) and grade (χ2 = 9.94, p = .02), and significant differences in grade (χ2 = 115.76, p < .001) and age (t(319.37) = −3.94, p < .001) for students who participated in follow-up 2 and those who did not. Because of these differences, we could not assume that data were missing at random. We accounted for missing data at follow-up time-points using Last Observation Carried Forward (LOCF) or Next Observation Carried Backward (NOCB).

Results

Descriptive Statistics

Descriptive data on students’ experiences at home (completed by a subsample of 185 students) during COVID-19 are shown in Table 2. Of note, 48.1% of students reported that 1 of their immediate family members had lost a job or employment hours because of the pandemic. There was a significant difference in student-reported family finances before and after the pandemic (χ2 = 60.89, p < .001), with more students reporting having “rarely enough” or “enough with no extra” compared to before the pandemic. The majority of youths reported only “a little” or “not at all” for difficult family relationships, loneliness, stress, parent stress, conflict with parents, worsened relationships with parents, and parent impatience during the pandemic. Furthermore, roughly 80% of students reported “a little,” “a lot,” or “a whole lot” for parents’ level of understanding, ability to make the child feel better, and ability to help the child manage stress during the pandemic.
Table 2Descriptive Data on COVID-19 Effects at Home in Mid-April 2020, 1 Month After School In-Person Closure, Reported by Sub-sample of Students (n = 185)
 Almost none Little Some Normal In-person contact with people outside immediate family since pandemic, % 39.5 36.8 19.5 4.3 Worse Same Better Treatment compared to people of other races since pandemic, % 3.8 91.9 4.3 Comfortable with extra Enough with no extra Rarely enough Financial situation in family before pandemic, % 57.3 37.3 5.4 Financial situation in family current, % 34.1 49.7 16.2 Did not use Used the same as before Sometimes (≤1/wk) Often (1/wk) Use of food bank, church, or school for food in last 2 wk, % 64.3 12.4 17.3 5.9 Yes No Immediate family member lost job/hours due to pandemic, % 48.1 51.9 Not at all A little A lot A whole lot Exposure to COVID-19 media coverage, % 9.2 47.6 31.4 11.9 More difficult relationship with family since pandemic, %aItems included in family functioning scale for post-hoc analysis. Items were recoded for the scale so that higher scores indicated better family functioning. Scale mean = 3.06, SD = 0.57, α = .079. 57.8 33.0 6.5 2.7 Felt lonely because of pandemic, % 38.4 35.7 16.8 9.2 Contact with friends during pandemic (video, social media), % 20.0 30.8 28.1 21.1 Stress during pandemic, % 28.6 45.9 18.9 6.5 Parent stress during pandemic, % 16.2 55.7 21.6 6.5 Conflict with parents during pandemic, %aItems included in family functioning scale for post-hoc analysis. Items were recoded for the scale so that higher scores indicated better family functioning. Scale mean = 3.06, SD = 0.57, α = .079. 61.1 26.5 8.1 4.3 Parents are understanding of child’s problems during pandemic, %aItems included in family functioning scale for post-hoc analysis. Items were recoded for the scale so that higher scores indicated better family functioning. Scale mean = 3.06, SD = 0.57, α = .079. 20.0 37.8 25.9 16.2 Relationship with parents has worsened, %aItems included in family functioning scale for post-hoc analysis. Items were recoded for the scale so that higher scores indicated better family functioning. Scale mean = 3.06, SD = 0.57, α = .079. 86.5 10.8 1.6 1.1 Parents have become more impatient, %aItems included in family functioning scale for post-hoc analysis. Items were recoded for the scale so that higher scores indicated better family functioning. Scale mean = 3.06, SD = 0.57, α = .079. 60.5 23.8 11.4 4.3 Parents able to make child feel better when upset, %aItems included in family functioning scale for post-hoc analysis. Items were recoded for the scale so that higher scores indicated better family functioning. Scale mean = 3.06, SD = 0.57, α = .079. 20.5 31.4 29.2 18.9 Parents able to help child manage stress, %aItems included in family functioning scale for post-hoc analysis. Items were recoded for the scale so that higher scores indicated better family functioning. Scale mean = 3.06, SD = 0.57, α = .079. 21.6 29.7 33.5 15.1
Note:
a Items included in family functioning scale for post-hoc analysis. Items were recoded for the scale so that higher scores indicated better family functioning. Scale mean = 3.06, SD = 0.57, α = .079.
Means for each BPM scale, for the whole sample and by group at each time-point, are shown in Table 3. Of the students, 59.6% (n = 192) were not a high scorer for any BPM domain; 16.1% (n = 52) of students were high scorers in 1 domain, 9.3% (n = 30) in 2 domains, 9.6% (n = 31) in 3 domains, and 5.3% (n = 17) in all 4 domains. Means for the “high scorer” groups were in the clinical range on the BPM
ASEBA BPM/6-18. Achenbach System for Empirically Based Assessment (ASEBA).
across domains at baseline, and below the clinical range at follow-ups in all domains except attention problems. “Low scorer” means were below clinical cutoff in all domains at baseline and follow-up time-points.
ASEBA BPM/6-18. Achenbach System for Empirically Based Assessment (ASEBA).
Table 3Brief Problem Monitor Means at Baseline and Follow-up Time-Points, by Group
BPM internalizingBPM attentionBPM externalizingBPM total problems
MeanSDMeanSDMeanSDMeanSD
January 2020
Low scorers3.272.303.902.082.792.0910.535.61
High scorers9.511.258.991.138.321.7223.623.65
Full sample4.593.324.982.833.852.9713.427.55
Mid-April 2020
Low scorers2.682.333.902.472.532.219.505.72
High scorers5.692.977.262.715.482.6716.456.28
Full sample3.322.764.612.873.102.5811.036.51
Early May 2020
Low scorers2.722.393.752.512.412.309.275.93
High scorers5.583.127.282.755.202.4616.096.17
Full sample3.322.814.502.942.952.5710.776.61
Late May 2020
Low scorers2.592.393.622.562.402.359.005.86
High scorers5.453.247.212.685.072.6415.836.49
Full sample3.202.844.392.972.912.6310.506.63
Note: N = 322. Baseline occurred in January 2020, follow-up 1 in mid-April 2020, follow-up 2 in early May 2020, and follow-up 3 in late May 2020. Low scorers = lower 80% of scorers on BPM scale at baseline; High scorers = highest 20% of scorers on BPM scale at baseline (ie, youth with elevated mental health problems at baseline).
BPM = Brief Problem Monitor.

Change in Mental Health

Analysis of covariance results are shown in Table 4. For each model, the sphericity assumption was violated, based on significant values from the Mauchly test of sphericity (all p < .001). Therefore, the Greenhouse−Geisser estimate was used for each F test.
• Field A.
Discovering Statistics Using SPSS (4th ed).
In all 4 models, there were significant main effects of group and significant interactions between time and group, over and above the effects of gender and age.
Table 4Repeated-Measures Mixed Analysis of Covariance Results for Change in Brief Problem Monitor Scores Over Time, Moderated by Group and Controlling for Gender and Age
 BPM internalizing problems F df p Partial eta squared Time 1.21 1.82; 569.08 .30 .004 Time × group 64.72 1.82; 569.08 <.001 .17 Time × gender .711 1.82; 569.08 .48 .002 Time × age .42 1.82; 569.08 .64 .001 Group 157.51 1; 313 <.001 .34 Gender 13.18 1; 313 <.001 .04 Age .09 1; 313 .77 .000 BPM attention problems F df p Partial eta squared Time 2.33 1.81; 568.50 .10 .01 Time × group 18.60 1.81; 568.50 <.001 .06 Time × gender 4.61 1.81; 568.50 .01 .01 Time × age .73 1.81; 568.50 .47 .002 Group 181.91 1; 315 <.001 .37 Gender 1.44 1; 315 .23 .01 Age .20 1; 315 .66 .001 BPM externalizing problems F df p Partial eta squared Time 2.69 1.84; 568.70 .07 .01 Time × group 58.71 1.84; 568.70 <.001 .16 Time × gender .26 1.84; 568.70 .76 .001 Time × age .57 1.84; 568.70 .55 .002 Group 141.02 1; 309 <.001 .31 Gender .01 1; 309 .92 .000 Age 1.58 1; 309 .21 .01 BPM total problems F df p Partial eta squared Time 2.36 1.68; 519.66 .11 .01 Time × group 53.02 1.68; 519.66 <.001 .15 Time × gender 1.52 1.68; 519.66 .22 .01 Time × age .22 1.68; 519.66 .76 .001 Group 139.17 1; 309 <.001 .31 Gender 1.65 1; 309 .20 .01 Age .66 1; 309 .42 .002
Note: N = 322. Within-subjects effects: time, time × group, time × gender, time × age. Between-subjects effects: group, gender, age. Degrees of freedom values for within-subjects effects were calculated using the Greenhouse−Geisser estimate due to violation of the sphericity assumption. BPM = Brief Problem Monitor.
We focused interpretation of interactions on those between time and group, because gender and age were control variables. Within-subject contrasts, in combination with interaction graphs (Figure 1), suggest that the time by group interaction was significant for contrasts between baseline and all follow-up time-points, for all BPM scales. There was a decrease from baseline to follow-up 1 that appears to stagnate thereafter. Significant interaction effects and effect sizes from baseline to follow-up 1 were F1,313 = 84.32, p < .001, ηp2 = 0.21 for internalizing problems, F1,315 = 27.15, p < .001, ηp2 = 0.08 for attention problems, F1,309 = 72.04, p < .001, ηp2 = 0.19 for externalizing problems, and F1,309 = 65.89, p < .001, ηp2 = 0.18 for total problems. Results of simple effects analysis, using the Bonferroni adjustment in SPSS to reduce likelihood of type I error, revealed that for internalizing, both the low scorers (mean difference = 0.58, p = .003) and the high scorers (mean difference = 3.87, p < .001) had significantly lower scores at follow-up 1 relative to baseline. For attention problems and for externalizing problems, only the high scorers had a significant reduction in scores at follow-up 1 (Attention mean difference = 1.76, p < .001; Externalizing mean difference = 2.85, p < .001). For total problems, both the high scorers (mean difference = 7.18, p < .001) and the low scorers (mean difference = 1.03, p = .02) reported reduced problems from baseline to follow-up 1.
We conducted 2 post hoc analyses using the subsample who had completed the survey on COVID-19 effects at home (n = 185). First, we evaluated whether the loss of employment by someone in the immediate family significantly affected mental health changes for youths. We followed the same analysis of covariance procedures as above, and added the variable indicating whether someone in the immediate family had lost employment or hours of employment as an additional between-subjects variable. The 3-way interaction amog time, group, and job loss was not significant in any model, and the 2-way interaction between time and job loss was significant only for BPM total problems (F1.81,315.45 = 3.54, p = .03). Pairwise comparisons, which were conducted using the Bonferroni correction, suggested there was a significant difference at follow-up 1, with total mental health problems higher for those whose parents lost employment relative to those whose parents did not; differences were not significant at later follow-ups.
For the second post hoc analysis, we evaluated whether family functioning during COVID-19 significantly affected mental health changes for youths. We created a family functioning variable by calculating the mean of the 7 family functioning items in the COVID-19 survey (items are listed in Table 3; the scale had an internal consistency reliability of α = 0.79), and dichotomized this variable for between-subjects analysis using a median split. This dichotomous variable was added as a between-subjects variable to the 4 models described in main analyses. The 3-way interaction between time, group, and family functioning, and the 2-way interactions between time and family functioning, were not significant for internalizing, attention problems, or total problems (all p > .17). For externalizing, the 3-way interaction was not significant; however, the 2-way interaction between family functioning and time was significant (F0.98,343.74 = 3.47, p = .03). Pairwise comparisons, using the Bonferroni correction, revealed that both low and high family functioning groups reported significant reductions in externalizing between baseline and follow-up time-points; however, the higher family functioning group had significantly lower externalizing scores at follow-ups 1 to 3 relative to the lower family functioning group, suggesting a faster rate of change for this group.
We also calculated Pearson correlations between the continuous 7-item COVID-19 family-functioning variable and BPM scores across domains at the 3 COVID-19 follow-up time-points, adjusting the p value using the Bonferroni correction. All correlations were significant at the level of p < .004, with medium correlations from r = −0.29 to r = −0.44, demonstrating that there were consistent relationships between better family functioning and lower mental health concerns for youths during COVID-19.

Discussion

The goals of this study were to add to epidemiological knowledge of consequences of the COVID-19 pandemic for youth mental health in the United States, and to potentially identify risk or protective factors for youth mental health during the COVID-19 pandemic. Findings revealed that there was a significant reduction in mental health problems for youths who had elevated levels of internalizing, attention, externalizing, or total problems before the pandemic from baseline to follow-up 1, controlling for age and gender. This reduction was clinically significant for internalizing, externalizing, and total problems. For youths who did not have elevated mental health problems at baseline, there were statistically (but not clinically) significant reductions in internalizing and total problems at follow-up 1. In a subsample, youths reported a significant change in family finances due to the pandemic, and 48.1% reported that a family member had lost employment. The majority of youths reported no or little stress, parent stress, or difficult family relationships during the pandemic, and endorsed “a little” or greater level of parental ability to help them cope and feel better during the pandemic. Post hoc analyses did not indicate that family job loss or family functioning were consistently related to youth mental health changes from before to during the pandemic, although there were significant effects for job loss on total problems at follow-up 1 and for family functioning on externalizing at follow-ups 1 to 3. Better family functioning during the COVID-19 follow-up period was related to lower levels of youth mental health problems across domains at all follow-up time-points.
Reductions in mental health problems were somewhat unexpected, given research that has suggested that the pandemic is associated with worsened mental health. However, this result aligns with declining suicide rates that were noted in some countries during lockdown,
• Hoekstra P.J.
Suicidality in children and adolescents: lessons to be learned from the COVID-19 crisis.
suggesting that there may be protective aspects of stay-at-home measures, for some groups. In addition, research among adults in China found that there was peak in mental health concerns at the beginning of the pandemic, which had improved by 4 weeks later,
• Wang C.
• Pan R.
• Wan X.
• et al.
A longitudinal study on the mental health of general population during the COVID-19 epidemic in China.
suggesting that there may have been declines in mental health symptoms after the initial shock of the pandemic. Furthermore, US parents have reported higher rates of mental health problems for themselves than for their children during the pandemic,

Patrick SW, Henkhaus LE, Zickafoose JS, et al. Well-being of parents and children during the COVID-19 pandemic: a national survey. Pediatrics. Published online August 1, 2020. https://doi.org/10.1542/peds.2020-016824

suggesting that the mental health impact of COVID-19 may differ between adults and youths, or that parents may be able to protect their children’s mental health but less so their own.
There are several reasons that this finding may have occurred. First, stay-at-home measures may provide an opportunity for increased family time and relationship building,
• Cluver L.
• Lachman J.M.
• Sherr L.
• et al.
Parenting in a time of COVID-19.
,
• Prime H.
• Browne D.T.
Risk and resilience in family well-being during the COVID-19 pandemic.
,
• Cui Y.
• Li Y.
• Zheng Y.
Chinese Society of Child & Adolescent Psychiatry Mental health services for children in China during the COVID-19 pandemic: results of an expert-basednational survey among child and adolescent psychiatric hospitals.
Decades of resilience research has suggested that children’s coping is largely buffered by the quality of their family relationships.
• Masten A.S.
• Narayan A.J.
Child development in the context of disaster, war, and terrorism: pathways of risk and resilience.
The protective effect of increased family time may be particularly true for youths from Latinx backgrounds due to familism, an important Latino cultural construct that puts family as central and prioritizes family as a main source of support and comfort,
• Hernández M.M.
• Bámaca–Colbert M.Y.
A behavioral process model of familism.
and that has been shown to be a protective influence for many adolescent outcomes.
• Stein G.L.
• Cupito A.M.
• Mendez J.L.
• Prandoni J.
• Huq N.
• Westerberg D.
Familism through a developmental lens.
Our finding that higher levels of family functioning were consistently associated with lower mental health problems in youths during the COVID-19 period also supports this idea, and aligns with a recent study with adults showing that better relationship quality during COVID-19 is associated with lower levels of psychological symptoms.
• Pieh C.
• ÓRourke T.
• Budimir S.
• Probst T.
Relationship quality and mental health during COVID-19 lockdown.
Second, it is possible that being removed from the in-person school environment led to improved mental health due to a reduction in peer stressors.
• Hoekstra P.J.
Suicidality in children and adolescents: lessons to be learned from the COVID-19 crisis.
,
• Becker S.P.
• Gregory A.M.
Editorial perspective: perils and promise for child and adolescent sleep and associated psychopathology during the COVID-19 pandemic.
Middle schoolers confined at home suddenly do not have to deal with the complexities of an expanded social network, which may relieve stress.
• Zimmer-Gembeck M.J.
Peer rejection, victimization, and relational self-system processes in adolescence: toward a transactional model of stress, coping, and developing sensitivities.
At the same time, it is likely important for adaptive socio-emotional development that normative levels of peer stress occur so that youths can learn to navigate the complexities of social interaction.
Third, academic pressures may also have been reduced once in-person school was closed.
• Hoekstra P.J.
Suicidality in children and adolescents: lessons to be learned from the COVID-19 crisis.
,
• Becker S.P.
• Gregory A.M.
Editorial perspective: perils and promise for child and adolescent sleep and associated psychopathology during the COVID-19 pandemic.
Although students in our sample continued instruction online, it is possible that not having to attend school in-person inherently lowered academic pressures, by allowing students more time and flexibility to complete schoolwork, fewer distractions, or fewer academic demands.
Fourth, it is possible that lack of in-person schooling led to more flexible routines that allowed adolescents to get more sleep. There is considerable evidence that early school start times have an adverse impact on adolescent functioning by contributing to insufficient sleep time and disrupting circadian rhythm, which in turn can have a negative impact on mental health.
Becker and Gregory
• Becker S.P.
• Gregory A.M.
Editorial perspective: perils and promise for child and adolescent sleep and associated psychopathology during the COVID-19 pandemic.
point out that improved sleep may be a “silver lining” for adolescents during the COVID-19 pandemic.
Fifth, there may have been unique factors associated with this sample that influenced results. The context of this particular school, which provided students with laptops and mobile hotspots for online learning if needed, continued to provide face-to-face instruction through video, and has a focus on the whole child, including the provision of socio-emotional learning instruction which continued through the COVID-19 period, may be important to consider as potential beneficial factors for students during the COVID-19 pandemic. The surrounding neighborhood is also home to a longstanding nonprofit organization offering services to recently immigrated families, which continued to operate during COVID-19. Our findings tentatively suggest that community characteristics such as these may offer important buffering during the COVID-19 pandemic and may serve as a model for future community resilience development. That this community found ways to be resilient amid the impact of COVID-19 is striking when one takes into account the high number of immigrants (an index of vulnerability) and the fact that 40% of students were “high scorers” in at least 1 mental health domain at baseline, suggesting higher levels of vulnerability than is seen in typical community samples.
Finally, these results may have occurred due to the timing of follow-up assessments. Assessments were completed while the academic year was still in session, and the COVID-19 outbreak worsened in the school’s region after that time. Mental health may have declined later, as the spread increased in the area or as stay-at-home measures continued. The window of time when this study was conducted may present a unique “natural experiment” with the combination of increased time at home while stress related to COVID-19 in this particular region was not yet at its peak. Similarly, families who were financially affected by COVID-19 may have had worsening stress that had not yet manifested during the follow-up time-points. Our post hoc analysis indicated that in families in which job loss occurred, children did not experience the same level of reduction in total mental health problems at the first follow-up, compared to children in families in which no job loss occurred. Differences were not significant at later follow-ups, suggesting that families may have adapted to the initial shock of job loss.
Our findings underline the importance of the family environment for promoting child resilience. This may not be true for all families, and the resilience demonstrated here should be harnessed and understood in order to assist other families and communities. Current results also bring into stark focus the possibility that school environments may exacerbate mental health difficulties, such that removal from that context into a less pressured environment immediately and positively impacts mental health. Finally, results highlight that there may be protective aspects of Hispanic and Latinx culture for youth mental health, not only due to the valuing of familism, but also due to the collectivistic nature of Hispanic and Latinx culture.
• Oyserman D.
• Coon H.M.
• Kemmelmeier M.
Rethinking individualism and collectivism: evaluation of theoretical assumptions and meta-analyses.
A recent opinion piece, “Now Is a Time to Learn from Hispanic Americans,”
• Kristof N.
Now is a time to learn from Hispanic Americans. The New York Times, June 27, 2020.
underlined that social ties and the tendency to help others in Hispanic and Latinx communities, even those hard-hit by COVID-19, appear to offer a protection that may not be felt in more individualistic cultures. Indeed, higher levels of collectivism in adults have been associated with psychological well-being during COVID-19.

Ahuja KK, Banerjee D, Chaudhary K, Gidwani C. Fear, xenophobia and collectivism as predictors of well-being during coronavirus disease 2019: an empirical study from India. Int J Soc Psychiatry. 2020;20764020936323.

,
• Germani A.
• Buratta L.
• Delvecchio E.
• Mazzeschi C.
Emerging Adults and COVID-19: the role of individualism-collectivism on perceived risks and psychological maladjustment.
In addition, adolescent engagement in social distancing for motivations such as not wanting to be judged or to become sick, consistent with individualistic values, have been associated with higher anxiety compared to engagement in social distancing for other motivating factors.
• Oosterhoff B.
• Palmer C.A.
• Wilson J.
• Shook N.
Adolescents' motivations to engage in social distancing during the COVID-19 pandemic: associations with mental and social health.
It is possible that increasing collectivistic behavior in communities may promote mental health for children, even in times of crisis.
Study limitations include that the sample was collected from 1 school, which may limit the generalizability of our findings. Despite this, we believe that this sample is valuable because it represents an important population in the United States for whom to understand mental health risk during the COVID-19 pandemic. Second, measures were all collected via self-report. Multi-method assessment would be ideal for understanding youth mental health functioning during the COVID-19 pandemic. Third, the BPM is designed for use with individuals 11 to 18 years of age for self-report purposes; our sample started at age 10 years. Fourth, youths were sent measures electronically during the stay-at-home period, which changed the context of assessment relative to baseline. It may have been the influence of other factors, including the change in context of assessment, rather than the influence of COVID-19 or stay-at-home practices, that led to the changes in mental health. Finally, post hoc analyses in the subsample were likely underpowered. Research with larger samples is needed to fully evaluate questions addressed in post hoc analyses. It will be important for researchers to continue to examine youth mental health longitudinally as the pandemic continues, including mental health trends among older adolescents.
Mental health consequences of the COVID-19 pandemic, particularly for vulnerable groups such as children and adolescents, individuals from racial and ethnic minority groups, and persons with existing mental health conditions, are not yet fully known. This study provides data demonstrating that in a predominantly Hispanic/Latinx group of adolescents from the southwestern United States, there were reductions in mental health problems from before the pandemic to 1 month into the stay-at-home period, which stayed consistent for 4 weeks thereafter. Reductions in internalizing, externalizing, and total problems were clinically significant for youths who had elevated mental health symptoms before the pandemic. Possible reasons for this finding include increased family time, cultural factors, reduced peer stress, school- or community-level factors, and more flexible routines enabled by stay-at-home policies.
The authors wish to thank Mirella Sales, BS, and Ryan Villarreal, MA, of Connect Community, for facilitating data collection, serving as a source of knowledge about the neighborhood where data collection took place, and reviewing the manuscript before submission.

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