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Open AccessOriginal Article

The Mental Well-Being of Young Children and Families at the Beginning of the COVID-19 Pandemic in Germany

Published Online:https://doi.org/10.1026/0049-8637/a000253

Abstract

Abstract. During the spring of 2020, the lockdown in Europe, enacted as a countermeasure to the COVID-19 pandemic, dramatically changed the social and daily life of young families. This online study explored the potential consequences of these unprecedented circumstances for the well-being of young German families. Caregivers completed a standardized questionnaire on their positive mental well-being and open-ended questions referring to their family situation and children. Although there is an emerging body of research describing pandemic-related outcomes in older children, little is known about its impact during early development. Hence, our analyses focused on a subset of caregivers of N = 798 children aged 0 to 23 months. Answers to open-ended questions revealed predominantly negative changes in their children and family life as a whole. During the lockdown, the well-being of the caregivers decreased. Taken together, the data show that social changes caused by the lockdown affected the well-being of young families. Potential mechanisms of stress transmission between parents and children are discussed.

Psychisches Wohlbefinden junger Kinder und Familien zu Beginn der COVID-19 Pandemie in Deutschland

Zusammenfassung. Der europäische Lockdown zur Bekämpfung der COVID-19 Pandemie im Frühjahr 2020 führte zu dramatischen Veränderungen im Sozialleben und im Alltag junger Familien. Die vorliegende Online-Studie untersuchte potentielle Folgen dieser Begleitumstände für das Wohlbefinden junger Familien in Deutschland. Bezugspersonen bearbeiteten einen standardisierten Fragebogen zu ihrem positiven mentalen Wohlbefinden sowie offene Fragen zur aktuellen Familiensituation und zu ihren Kindern. Während sich viele Forschungsarbeiten mit pandemie-bezogenen Folgen für ältere Kinder befassen, ist noch wenig über die Bedeutung der Pandemie in frühen Entwicklungsphasen bekannt. Die Analysen fokussieren sich daher auf eine Teilgruppe von Bezugspersonen von N = 798 Kindern im Alter zwischen 0 und 23 Monaten. Antworten auf offene Fragen zeigten überwiegend negative Veränderungen bei Kindern und im Familienleben. Während des Lockdowns sank das Wohlbefinden der Bezugspersonen. Insgesamt zeigten die Daten, dass das Wohlbefinden junger Familien von sozialen Veränderungen im Lockdown betroffen war. Potenzielle Mechanismen der Stress-Übertragung zwischen Eltern und Kindern werden diskutiert.

The COVID-19 pandemic has profoundly affected human lives around the globe. In Germany, multiple nationwide lockdown measures were enacted for the first time in mid-March 2020 (cf. Steinmetz et al., 2020). As in many other countries, citizens in Germany experienced severe restrictions of public life and social activities. In addition to schools, daycare centers for children were closed as were playgrounds – measures that specifically affected families with young children, and that were potential sources of severe stress in addition to the threat posed by the virus.

Based on existing models of human development and family functioning (e. g., Conger et al., 2002), Prime et al. (2020) proposed a conceptual framework to explain links between COVID-19-related stressors and children’s adjustment in terms of their behavioral functioning, emotional problems, academic progress, and peer relations. The model assumes that social disruptions from the pandemic, such as job loss and social distancing, affect both family well-being and child adjustment via impairment of caregiver well-being (Prime et al., 2020). Thus, child adjustment depends on both proximal factors like reciprocal face-to-face interactions and distal factors like family socioeconomic status (see Bronfenbrenner & Morris, 2007). Prime et al. (2020) concluded that pandemic-related disturbances affect both caregiver well-being and – as distal factors – relationships within the family, which in turn are linked to child adjustment.

Empirical evidence for the model is growing. For instance, a German study with 7- to 17-year-olds (Ravens-Sieberer et al., 2021) suggested that children were more likely to suffer from mental health problems and higher anxiety levels during than before the pandemic. Carroll et al. (2020) identified some key factors for parents’ COVID-19-related stress: Parental stress levels were traced back to factors like the challenge to balance work with increased childcare and homeschooling and financial instability. Moreover, Davidson et al. (2021) found that higher pandemic-related everyday stress and current mental health were linked to caregivers’ lower confidence in meeting their family’s needs. Children’s psychosocial problems predicted lower caregiver mental health (Davidson et al., 2021), supporting the interdependence between parental and children’s well-being proposed by Prime et al. (2020). Likewise, the role of social disruption, elicited, for example, by pandemic-related job loss, was recently demonstrated (e. g., Lawson et al., 2020). Furthermore, Ravens-Sieberer et al. (2021) found that children of families with a low socioeconomic status felt more burdened by the pandemic.

Although experiences in infancy form the foundation of the future development of children, only a few studies have focused on parental stress and infant adjustment to COVID-19-related stress (e. g., Vardi et al., 2022). Given their strong dependence on caregivers, and given that stress transmission from caregivers to infants can occur quickly (Waters et al., 2014), infants might be particularly receptive to pandemic-related changes in caregiver well-being and behavior. Taubman–Ben-Ari et al. (2021) emphasized that parents of young infants are particularly vulnerable to parenting stress, and that, for example, preserving marital satisfaction can protect against parenting stress in such times. In accordance with calls for research on infant well-being in the context of the pandemic (e. g., Erdei & Liu, 2020), the current study, conducted in Germany, focused on families with 0- to 23-month-old infants.

To explore how the pandemic and its associated countermeasures affected families, and in particular how it affected infants and young children, we conducted a nationwide online survey after the lockdown measures had been in place for 3 to 4 weeks.

Conceptually related to Prime et al.’s (2020) model, we examined associations between caregivers’ well-being during the COVID-19 pandemic, changes and challenges for the whole family, and the valence of infants’ behavioral and emotional changes. Both the health threats of the COVID-19 pandemic as well as the sudden and pervasive changes to family life as a result of the lockdown were uncontrollable factors in the livelihoods of young families, likely causing enduring psychological stress, and/or perception of threat (Sheridan & McLaughlin, 2014). First, we predicted caregivers’ positive mental health (PMH) to be lower during lockdown than before lockdown, indicating a potential link between social disruption and caregiver well-being. In addition, we examined such a link by measuring caregivers’ perceived COVID-19-related threat. Besides a direct and bidirectional relationship between caregiver well-being and child adjustment, Prime et al. (2020) also found an indirect link via the family system: Heightened stress levels of caregivers can impact the relationship quality among family members, and destabilized relationships may, in turn, endanger child adjustment (Prime et al., 2020). As a second study goal, we examined associations between caregiver well-being, on the one hand, and family well-being and child adjustment, on the other hand. Prime et al. (2020) suggested a link between family well-being and child adjustment. Investigating this link presented the third goal of the current study. We did not formulate directed hypotheses for study goals two and three because of the unprecedented situation and hence the lack of relevant models and existing data at the time the study was set up.

Method

Participants

The final sample of N = 798 caregivers was a subsample from a more comprehensive study of caregivers of children from newborn to 6 years (in months: M = 37.2, SD = 18.1), living in Germany. The sample from the more comprehensive study consisted of N = 3,067 caregivers. Both in the current sample (69 %) and the more comprehensive sample (54 %), caregivers with a university or higher academic degree accounted for the largest proportion. In the present study, the children’s age varied from newborn to 23 months (M = 15.6, SD = 5.8). Because of inconclusive data on the child’s exact age, n = 1 participant was excluded from age group-related analyses. Demographic information on the final sample is presented in Appendix A (Table A1 for children and Table A2 for caregivers).

If more than one child within the targeted age range lived in the caregiver’s household, the caregiver was requested to answer the questionnaire referring to their youngest child. All participants provided informed consent before participation. Ethics approval was obtained from the local Ethics Committee.

Measures

Family Well-Being

To assess their family well-being, caregivers indicated their perception of the current family situation on a 7-point scale from –3 (very negative) over 0 to +3 (very positive). To perform analyses with this measure, we converted the reported scores into values of 1 (very negative) to 7 (very positive).

To capture individual perspectives on family life during the lockdown, we asked three open-ended questions. Caregivers were asked to briefly describe (a) the three greatest changes in the family, (b) the three greatest difficulties, and (c) the three aspects that were most helpful for the family in the current situation. Statements were categorized in terms of content and valence (see Coding of Caregiver Statements).

For the present purposes, we focused on the valence of statements regarding the greatest changes in the family and perception of family situation as indicators of family well-being.

Caregiver Well-Being

The Positive Mental Health Scale (PMH-scale; Lukat et al., 2016) was used to assess caregivers’ well-being (e. g., “I manage well to fulfill my needs”). The unidimensional, 9-Likert-type item scale has shown good psychometric properties in a student, a patient, and a general population (Lukat et al., 2016). The scale, as used by Lukat et al. (2016), ranges from 1 = I do not agree to 4= I agree. Because our main aim was to capture the potential impact of the COVID-19 pandemic, participants were required to respond twice to the PMH-scale, referring to before and during the pandemic: Specifically, we asked caregivers to consider the time before the COVID-19 pandemic as the period before the closure of schools and daycare centers. Scores were calculated by averaging participants sum scores, with higher scores indicating stronger PMH (before lockdown: M = 3.22, SD = 0.47; during lockdown: M = 3.01, SD = 0.52). The internal consistency was acceptable for the time before (α = .79) and high for the time during the COVID-19 pandemic (α = .82). Furthermore, caregivers indicated how much they perceived the COVID-19 pandemic as a threat on a 5-point scale from 0 (not at all) to 4 (very strongly).

Child Adjustment

Given the lack of standardized questionnaires to capture well-being and adjustment in children aged 0 to 23 months, caregivers answered an open-ended question referring to potential changes in their children’s adjustment during the COVID-19 pandemic. They indicated up to three main changes that they had noticed in their child since the start of the lockdown. As for the other open-ended questions, we categorized the content and valence of reported changes.

Procedure

The online questionnaire was created using the survey platform Qualtrics (Qualtrics, Provo, UT) and nationally distributed via social media and a press release. We also contacted family magazines and social-media groups for parents of young children to promote and hyperlink the questionnaire within their respective online presence. Participants completed the questions using web-enabled electronic devices and were allowed to take breaks during completion.

Caregivers also responded to questions concerning the child’s sleeping behavior and media use, both of which were not relevant to the purpose of the present study. Pretests revealed an average duration of 20 minutes to complete the entire survey.

Coding of Caregiver Statements

There were four open-ended questions overall, asking for main changes in 0- to 23-month-old children, greatest changes in family life, greatest difficulties in family life, and most helpful aspects. Categories were generated in a 5-step process by combining top-down and inductive approaches following qualitative content analysis (Mayring, 2000). First, before inspecting the data, we generated content-related categories for each of the four open-ended questions. Second, we tested categories of each question with the first 100 entries by two of the authors. Third, we discussed proposed modifications and agreed upon four lists of preliminary categories. Fourth, two research assistants classified the first 100 entries of each question based on these categories. Fifth, we integrated feedback arising from coding of this subset, defined the final categories (Appendix B, Tables B1-B4), and added a valence-related category (neutral, positive, or negative) for the main changes in infants and family life. A statement was only classified as valent (positive or negative) if it contained evaluative wording or if the valence was clearly recognizable from the language used. Each research assistant manually categorized participants’ answers to two of the open-ended questions. The interrater reliability was determined by using Cohen’s κ. For the first 300 participants of the full sample, each research assistant independently coded the answers to the other two questions as well. According to Landis and Koch (1977), interrater reliabilities for the four open questions were almost perfect for the valence-related coding (κ = .76–.95), and substantial to almost perfect for the content-related coding (κ = .64–.88).

Composite Score for Negative, Positive, and Neutral Changes

We summed up the frequency of negative child- and family-related changes for every participant. Then, we divided this sum by the sum of all reported child- and family-related changes per participant and multiplied the result by 100 to gain a percentage score. This procedure was repeated for positive and neutral statements. For example, the composite score for negative changes describes the percentage of a participant’s reported negative child-related and negative family-related changes in all reported child-related and family-related changes of that participant.

Analytic Strategy

First, we assessed the relations between our outcome measures and caregiver educational level, presence of a sibling, and daycare attendance of the youngest child. Parents who took care of more than one child or who depended on daycare offers might have perceived more stress than parents of only one child or with capacities to provide for complete daycare on their own. If the factors were significant in the preliminary analyses, we included them in further analyses on the respective outcome measures. To examine potential lockdown-dependent differences in caregiver well-being and to investigate the role of infant age, we performed an analysis of variance (ANOVA) on caregivers’ PMH. We included infant age as a grouping factor to examine whether caregivers of infants 12 months of age and older indicated lower scores than caregivers of infants younger than 12 months, perhaps because of the closure of daycare offers that were mostly attended by older infants. Caregiver statements on child adjustment required valence categorization (neutral, positive, negative) to analyze the statements quantitatively. Valence categories were entered as a factor in ANOVAs to analyze how child adjustment related to caregiver well-being (PMH during lockdown, threat perception) and family well-being (perception of family situation). The valence of the first child-related change that parents mentioned was used for group formation in ANOVAs on caregiver and family well-being. As it was most accessible to caregivers, the first out of three possible mentions probably indicates the most noticeably change and therefore deserves particular attention (Fishbein, 1963; Ajzen & Fishbein, 2000).

We conducted correlational analyses between the composite score for negative changes and caregivers’ PMH and threat perception, respectively, to examine the link between caregiver well-being, on the one hand, and both family well-being and child adjustment, on the other hand.

For all statistical tests, we used an alpha level of .05. For all analyses, we used IBM SPSS Statistics (Version 26).

Results

Description of Caregiver-Reported Changes

Family-Related Changes During the COVID-19 Pandemic

Participants reported primarily negative (46 %) and neutral changes (40 %) in their family lives since the start of the lockdown. Table 1 presents the most frequently reported categories of changes in family life, difficulties, and helpful aspects during the COVID-19 pandemic. An overview of the valence categories regarding changes in family life is available in Appendix C (Table C1).

On average, caregivers described their perception of their current family situation as rather neutral (M = 4.57, SD = 1.48). There was no difference in caregivers’ perception of the current family situation as a function of the child’s age group, t‍(795) = 1.12, p = .26.

Child’s age group was not associated with valence of the primary family-related change, χ² (2, N = 639) = 0.06, p = .97.

Table 1 Most frequent response categories for COVID-19-related open-ended questions

Child-Related Changes During the COVID-19 Pandemic

Classification of caregivers’ statements revealed that they perceived mainly negative changes in their children (48 %). Positive and neutral changes were reported by 19 % and 33 %, respectively. The two most commonly described changes referred to behavioral change in activity (18 %) and emotional state (17 %), and these changes were mostly classified as negative (77 % and 66 %, respectively). For example, caregivers described children as “restless” or “more unbalanced” (negative behavioral change) and as “unmotivated,” “unhappy,” or “crotchety” (emotional state). Child’s age group was not associated with valence of the primary child-related change, χ² (2, N = 464) = 0.29, p = .87. Table 2 contains the most frequent categories of 0- to 23-month-olds’ main changes, as described by their caregivers.

Table 2 Most frequent response and valence categories referring to main changes in 0- to 23-month-old children

Composite Scores for Negative, Positive, and Neutral Changes

On average, 45 % of all reported changes in infants and in family life were classified as negative, 16 % as positive, and 39 % as neutral. Families with 0- to 11-month-olds did not differ from families with 12- to 23-month-olds in their composite scores for either negative changes, Welch’s t‍(286.6) = 0.32, p = .75, for positive changes, t‍(702) = -1.13, p = .26, or for neutral changes t‍(702) = 0.56, p = .58.

Preliminary Analyses

Following the procedure by Bérubé et al. (2021), we formed two groups for educational level (secondary school 1 to high-school diploma vs. university or doctoral degree) and performed t-tests on the outcome variables of the planned ANOVAs (caregiver well-being: PMH during lockdown, threat perception; perception of family situation) to examine education as a potentially confounding variable. Neither PMH, t‍(795) = -0.29, p = .77, nor threat perception, t‍(795) = -0.16, p = .87, nor perception of the family situation, t‍(795) = -0.71, p = .48, differed significantly between the two groups. Therefore, educational level was not included in further analyses. Appendix D presents test statistics and Bonferroni-Holm corrected p-values of the control analyses for the outcome variables (PMH before lockdown, PMH during lockdown, threat perception, perception of family situation, composite score for negative changes) with the presence of a sibling (Table D1) and daycare attendance (Table D2) as grouping variables. Presence of a sibling was associated with valence of the primary child-related change, χ² (2, N = 468) = 18.35, p < .001, but daycare attendance was not, χ² (2, N = 468) = 0.80, p = .67. Based on t-tests results (Appendix D), daycare attendance and the presence of a sibling entered the following analyses on PMH before and during lockdown as factors. Further, we performed separate analyses for daycare status (yes/no) in analyses on the perception of family situation, and for the manifestation of sibling status (yes/no) in analyses on the valence of primary child-related change.

Research Question 1: Caregiver Well-Being During the COVID-19 Pandemic

A 2 (Time: before, during lockdown) x 2 (Infant age: 0 – 11, 12 – 23 months) mixed-model ANOVA on PMH scores revealed a main effect of time, F‍(1, 795) = 264.08, p < .001, ηp² = .25, indicating significantly higher parental positive mental health before than during lockdown. A main effect of infants’ age, F‍(1, 795) = 6.96, p = .01, ηp² = .01, indicated higher PMH for parents of 0- to 11-month-old infants (M = 3.07, SD = 0.52) than for 12- to 23-month-old infants (M = 2.99, SD = 0.52). However, effect size was negligible. The interaction term did not reach significance, F‍(1, 795) = 1.63, p = .20. A 2 (Time: before, during lockdown) x 2 (Daycare: attendance, no attendance) x 2 (Sibling: sibling, no sibling) mixed-model ANOVA on PMH scores also revealed a main effect of time, F‍(1, 794) = 305.75, p < .001, ηp² = .28. A main effect of daycare, F‍(1, 794) = 10.18, p < .01, ηp² = .01, indicated higher PMH for parents whose children did not attend daycare before lockdown than for parents of children in daycare. Further, a main effect of presence of a sibling indicated higher PMH for parents of only one child than for parents of two or more children, F‍(1, 794) = 17.43, p < .01, ηp² = .02. The effect sizes of daycare attendance and presence of sibling‍(s) were negligible. None of the interactions reached significance, all ps > .12. Results of the three-way ANOVA are shown in Table D3. Overall, parents perceived a decrease in their PMH during lockdown.

Caregivers perceived the COVID-19 pandemic as moderately threatening (M = 2.15, SD = 0.94). There was no difference in threat perception as a function of the child’s age group, t‍(795) = 1.20, p = .23.

Research Question 2.1: Caregiver Well-Being and Child Adjustment

A one-way (Valence of primary child-related change: neutral, positive, negative) ANOVA on PMH scores during lockdown revealed a significant effect of valence, F(2, 465) = 14.82, p < .001, ηp² = .06. Planned contrasts revealed that PMH was lower for parents reporting a negative primary change in their children (M = 2.88, SD = 0.45) compared to those reporting a positive primary change (M = 3.19, SD = 0.50), t(465) = 5.25, p < .001, d = 0.66, but not compared to those reporting a neutral primary change (M = 2.90, SD = 0.49), t(465) = 0.47, p = .64.

A one-way (Valence of primary child-related change: neutral, positive, negative) ANOVA on threat perception during lockdown yielded a marginally significant effect of valence, F(2, 465) = 2.78, p = .06. Planned contrasts indicated that parents who first reported a negative change (M = 2.25, SD = 0.90) perceived more threat compared to those who reported a neutral primary change (M = 2.05, SD = 0.93), t(465) = -2.12, p < .05, d = -0.22. The difference in threat perception between parents who reported a negative and those who reported a positive primary change (M = 2.06, SD = 0.97) was marginally significant, t(465) = -1.71, p = .09.

Both one-way ANOVAs were repeated for each subgroup concerning daycare attendance and the presence of sibling(s) (see Appendix D, Table D4). Planned contrasts for significant PMH score differences did not differ considerably from analyses of the whole group of 0- to 23-month-olds. However, planned contrasts for significant differences in threat perception revealed that the marginally significant effect of valence was mainly driven by families with more than one child.1

Research Question 2.2: Caregiver and Family Well-Being

The composite score for negative changes correlated moderately with parents’ PMH during lockdown, r = –.29, n = 704, p < .001, and weakly with the difference between parents’ PMH before and during lockdown, r = –.13, n = 704, p < .001. Hence, the more negative family- and child-related aspects parents reported, the lower they perceived their mental well-being and the more their well-being had decreased during lockdown. The composite score for negative changes was weakly correlated with caregivers’ threat perception, r = .10, n = 704, p = .01. To account for daycare attendance and the presence of sibling(s), we repeated the correlations including PMH scores for the respective subgroups. Correlations in the subgroup analyses were of similar magnitude as correlations for the entire sample, –.26 ≤ r ≤ .34, and –.11 ≤ r ≤ –.14.

Research Question 3: Family Well-Being and Child Adjustment

A one-way ANOVA on perception of family situation during lockdown revealed a significant effect of valence of primary child-related change, F‍(2, 465) = 33.83, p < .001, ηp² = .13. Planned contrasts showed that parents reporting a negative primary change in their children perceived the family situation as more negative (M = 4.00, SD = 1.43) than those reporting a positive primary change (M = 5.44, SD = 1.27), t‍(465) = 8.20, p < .001, d = 1.03, and those starting with a neutral change (M = 4.31, SD = 1.44), t‍(465) = 2.19, p = .03, d = 0.23.

Again, the ANOVA was repeated for each subgroup concerning daycare attendance and the presence of sibling‍(s) (see Appendix D, Table D4). Planned contrasts did not differ considerably from analyses of the whole subsample of 0- to 23-month-olds (see Footnote 1).

Discussion

The purpose of this study was to explore how the COVID-19 pandemic and countermeasures during the first German lockdown shaped family well-being. Caregivers’ PMH was lower during than before lockdown. Caregivers perceived predominantly negative child-related changes, indicating a decrease in infants’ well-being during lockdown. Both caregiver and family well-being were related to child adjustment: Parents who perceived their child’s primary change as negative reported lower PMH and a more negative perception of the current family situation than parents who perceived their child’s salient change as positive. Furthermore, caregiver well-being and negative changes in children and family lives were associated. Thus, the results of the current study support the proposed relations within Prime et al.’s (2020) framework. In terms of caregiver well-being, it is noteworthy that high PMH does not automatically imply the absence of mental disorder (Lukat et al., 2016), and that positive mental health and psychopathology are correlated but distinct concepts. Therefore, the reported reduction in PMH scores is not necessarily equal to an increase in mental health problems. The overall pattern of responses, however, does suggest that during lockdown children’s behavior and emotional state changed, and that families’ well-being decreased to a noticeable extent. PMH before and during lockdown and perception of the family situation were higher in parents whose children did not attend daycare offers before lockdown and who had an only child. It is highly probable that using daycare offers relieved employed parents. The discontinuation of daycare offers during lockdown and the need to balance out childcare and job performance might have contributed to a decrease in parents’ well-being. Additionally, meeting the needs of multiple children during lockdown could have reduced positive mental health. However, daycare and sibling status interacted neither with each other nor with time, and did not noticeably affect our main results, for example, concerning changes in perceived stress.

The effects of stress on child development, for example, on emotion regulation (e. g., Hoffman et al., 2006) and cognition (e. g., Kingston et al., 2015), have been widely studied. Recent COVID-19 research highlighted that the pandemic represents a stressful situation for parents (e. g., Carroll et al., 2020). In our study, the most frequently mentioned difficulty in family life was strain through work and the childcare situation, which was also a key stress factor identified by Carroll et al. (2020). Hence, parents may feel stressed because they must try to simultaneously work and care for their child. From a very young age, children respond to parental interactive bids (Kochanska & Aksan, 2004) and experience direct affection contagion (Waters et al., 2014). Thus, on the one hand, it is indeed possible that parents’ negative changes in well-being or stress perception directly affected their children. On the other hand, links between external circumstances like the pandemic, caregiver and family well-being as well as child adjustment can be multidirectional, as Prime et al. (2020) suggested. That is, negative child-related changes can leave a trace in their caregivers’ well-being, too.

Studying the nature and valence of child-related changes extends current research on children’s well-being during the pandemic (e. g., Ravens-Sieberer et al., 2021) by focusing on 0- to 23-month-old infants. Caregivers reported restlessness and boredom as some of the main changes in infants (categorized as “behavioral change: activity”). Additionally, limitations of social contacts and keeping the child occupied belonged to the most frequent difficulties mentioned by participants. Overall, these aspects suggest that infants are confronted with a more deprived environment during than before lockdown. Previous studies suggest that ongoing deprivation, characterized by a lack of cognitive and social learning experiences, can have long-term cognitive and emotional consequences (e. g., Machlin et al., 2019; Carrera et al., 2020). Ongoing longitudinal studies will reveal how children’s cognitive and emotional abilities develop throughout the pandemic and beyond (e. g., Deoni et al., 2021).

Participants perceived the situation during the first wave of the COVID-19 pandemic as moderately threatening. This finding roughly mirrored how people in Germany perceived the risks of COVID-19 during the time of data collection (Dryhurst et al., 2020). However, our analyses indicated that threat perception was limited in its relevance for reported family well-being. It will be informative to study threat perception over time and in different places of the world, affected by the pandemic to a different degree. In this context, the Fear of COVID-19 Scale (Ahorsu et al., 2020) has already proven to be a useful tool showing robust psychometric properties across validation studies in many countries (e. g., Bitan et al., 2020; Haktanir et al., 2020). Moreover, to capture threat perception during the pandemic, one has to be aware of individual experiences with COVID-19, personal values, trust in national institutions and the health system, and risk communication – factors shown to relate to risk perception (e. g., Dryhurst et al., 2020; Margraf et al., 2020). Future studies could investigate how threat perception of COVID-19 and its consequences develop over time and how this relates to daily life in young families.

Limitations and Future Directions

The present study has several limitations. First, the objectivity of measurement was reduced. Because we conducted the survey online, we were unable to control the external circumstances of participation. Second, the data were provided by self-report, so the study provides only indirect insights into family life during the lockdown. Third, the study was cross-sectional, so participants had to recall their own and their children’s mental health and behavior, respectively, over a period of time when indicating changes from “before” to “during” lockdown. Hence, we cannot exclude recall bias in participants’ answers. Fourth, the correlational design does not allow for causal interpretations. Fifth, the results including caregiver statements might be limited in their explanatory power because they were further categorized by independent raters (as expressing positive, neutral, or negative contents). Hence, raters inferred the valence of caregiver statements rather than caregivers providing direct ratings. Sixth, the validity of reported child-related changes might be limited for infants born a few months before lockdown as it might be difficult for new parents to disentangle rapid developmental changes from changes because of pandemic disruptions. Seventh, participants with a middle and higher socioeconomic background were likely overrepresented in our sample, with 69 % of participants having a university entrance degree or a higher educational level. The sample was hence not representative of the whole of the population. However, families with a higher social status might have been able to offer their children comparatively more cognitively stimulating and enriching environments (e. g., Rosen et al., 2020). Thus, the present findings might be a conservative estimate of self-reported changes in parental and children’s well-being and family change during lockdown.

To get a more precise estimate of the links within Prime et al.’s (2020) framework, future research should include more direct measures of families’ and children’s well-being. For instance, daily web diaries, an experience sampling method, can systematically capture daily hassles and coping strategies (e. g., Almeida, 2005). In this respect, a promising approach might be to focus on the particular subsystems in Prime et al.’s (2020) framework, for example, the marital subsystem. By applying a broad subdivision into neutral, positive, and negative child-related changes, the current study provided empirical support for Prime et al.‘s (2020) model on a superordinate level. To assess the applicability of the model in more depth, we recommend examining specific aspects of caregiver well-being (e. g., parenting stress) and their relationship to specific aspects of child adjustment (e. g., emotional problems). This approach might help to generate specific advice for effective coping in a lockdown situation.

Conclusions

The present study provides a rich descriptive database of the changes, difficulties, and resources of young families during an unprecedented lockdown situation. Although generalization of results regarding children’s changes is limited, the method of open-ended questioning might have captured the individual needs of young families in this exceptional situation in a person-centered way. Because of the critical social and environmental changes caused by the COVID-19 pandemic, both parents and young children’s well-being appeared to suffer. Given the realistic and unprecedented threat caused by the COVID-19 pandemic, this is perhaps not surprising. The situation of young families will require careful monitoring and, if needed, tailored help to support them through the ongoing crisis and beyond.

We would like to thank all caregivers who participated in this research. We thank Julia Holewa and Vanessa Vogel for help with data coding as well as Janina Stecker and Nele Tatarevic for help with data management.

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1Reports of planned contrasts in the subgroups daycare attendance and presence of sibling‍(s) lie beyond the scope of this article. Detailed results can be requested from the first author.

Appendix A

Demographic Information on the Final Sample

Table A1 Children’s demographic characteristics

Table A2 Caregivers’ demographic characteristics

Appendix B

Content-Related Categories for the Open-Ended Questions

Table B1 List of content-related categories for caregiver-reported main changes of 0- to 2-year-old children
Table B2 List of content-related categories for caregiver-reported greatest difficulties in family life
Table B3 List of content-related categories for caregiver-reported greatest changes in family life
Table B4 List of content-related categories for caregiver-reported most helpful aspects for the family

Appendix C

Table C1 Most frequent responses and valence categories referring to changes in family life

Appendix D

Descriptive and Inferential Statistics of the Control Variables, Daycare Attendance (Youngest Child), and Presence of Sibling‍(s)

Table D1 Descriptive statistics of outcome variables and results of control analyses examining differences as a function of presence of sibling‍(s)
Table D2 Descriptive statistics of outcome variables and results of control analyses examining differences according to daycare attendance of the youngest child
Table D3 Results of the three-way ANOVA on PMH scores before and during lockdown (time) according to presence of sibling‍(s) and daycare attendance of the youngest child
Table D4 Results of one-way ANOVAs with the valence of primary child-related change as between-subject factor, controlled for the presence of sibling‍(s)