1. Introduction
With the onset of the COVID-19 pandemic, for many people, everyday life changed drastically. Accordingly, it quickly became apparent that mental health would likely be affected by the pandemic. In the course of the last years, this has been shown regarding the mental health of healthcare workers [1,2,3,4,5,6,7,8], patients suffering from COVID-19 [9,10,11], and those affected by quarantine and other restrictions aiming to protect the population from COVID-19 [12,13,14,15,16,17,18]. Children and adolescents infected with SARS-CoV-2 were only occasionally physically affected and rarely hospitalized [19,20,21]. At the same time, it became apparent early on that the psychosocial consequences resulting from the measures implemented to mitigate the spread of COVID-19, which resulted in school closures and severe contact restrictions, often had a negative impact on the everyday lives of children and young people [13,22,23,24,25,26].
A particularly strong influence of quarantine and isolation came from common mental health problems [27,28]. Studies from different countries worldwide examined the impact on the psychological well-being of children and adolescents and reported an increased prevalence of mental health problems such as depression, anxiety, and loneliness [29,30,31,32,33]. Studies also investigated behavioral disorders among young people and found an increase compared to pre-pandemic studies [34,35].
In Germany, children and adolescents reported a lower health-related quality of life (HRQoL) during the first months of the pandemic and showed a higher risk of suffering from anxiety disorders, depression, and poor mental health in general, compared to pre-pandemic data [36,37]. Studies investigating mental health in later phases of the pandemic (e.g., in January 2021, when very strict contact restrictions and other rules applied) described an increase in mental health problems in children and adolescents in Germany [36,37,38]. In contrast to these surveys in the early pandemic, studies conducted in September and October 2021 showed an improvement regarding the mental health situation of children and adolescents in Germany, as more surveyed children and adolescents indicated an average or high quality of life [39]. Correspondingly, the prevalence of symptoms of depression and anxiety, as well as psychosomatic complaints, also showed a slight decrease, which, however, was described as not statistically significant [39,40].
The period during which the measures implemented to contain the COVID-19 pandemic were less restrictive (e.g., easy access to COVID-19 vaccination (from the age of 12), travel to many countries was allowed again, no contact restrictions, no more strict quarantine regulations after travel, and in parts of Germany, the mask requirement no longer applied [41,42]) has, so far, been insufficiently considered in research. However, these results can provide important information on the experience of stress or depict the duration of the convalescence of the psychological stress experienced after the reduction in pandemic-related restrictions.
Research conducted prior to the COVID-19 pandemic has consistently highlighted various social determinants that affect the mental health of children and adolescents. Notably, subjective socioeconomic status has been identified as a critical factor influencing mental health outcomes in this demographic [43,44,45]. In addition to socioeconomic factors, physical health has also been recognized as a pivotal determinant of mental well-being among young individuals [46,47]. Moreover, sleep disturbances have been identified as a significant contributor to the mental health challenges faced by children and adolescents. Research indicates that inadequate or poor-quality sleep can severely impact mental health, leading to increased levels of anxiety, depression, and emotional instability [48,49,50,51,52].
We developed this study to investigate the two following research questions: First, we aimed to assess how children and adolescents experienced the period of the COVID-19 pandemic from June to July 2021. During this time, the early pandemic was still an important topic in media coverage and everyday conversations, but restrictions applying to children’s everyday lives were minimal. Second, we aimed to examine which factors were associated with children’s mental health situation during a time with more contact with peers and school attendance [53,54,55].
In addition to our main questions, this study aimed to examine which factors caused by the pandemic were perceived as being particularly stressful or positive by children and adolescents.
Furthermore, this study can be placed in context with other studies from this research area to develop hypotheses about the development of the mental health of children and adolescents during and after the COVID-19 pandemic.
2. Materials and Methods
2.1. Study Design and Sample
This study was conducted in Halle (Saale), Germany, and the surrounding districts between 14 June and 27 July 2021.
It used a cross-sectional design in the form of an anonymous online survey and was approved by the Ethics Committee of the Martin Luther University Halle-Wittenberg (Approval Number 2020-076). The study was conducted in accordance with the local legislation and institutional requirements. The participants’ guardians/next of kin provided their written informed consent to participate in this study. Included were children and adolescents between the ages of 10 and 18 years.
The study sample consisted of the two study populations. One study population was recruited via the DigiHero study (population 1) as follows: If parents were part of the DigiHero cohort and provided appropriate information about children in the appropriate age group, the DigiHero study invited them to participate in the Child and Adolescent Mental Health Survey. Details on DigiHero’s recruitment strategy are presented elsewhere [56]. The second study population (population 2) consisted of children and adolescents within the same age group who were recruited elsewhere (see below), and whose parents were not participants of the DigiHero study.
In order to be able to participate in the study, the parents of the respective children and adolescents of the second study population had to give their consent and register their child’s e-mail address on the study’s homepage. This way, the parents or legal guardian provided their consent for the children to participate in this study. Then, the access link for the study questionnaire was sent.
To ask parents for their children’s participation, all schools in Halle [29] were asked via the federal state’s school authority to pass on information about the study to the parents of their pupils. A reminder e-mail was sent to the schools two weeks later via the regional education authorities. In addition, posters and flyers were hung up in pediatric practices and our university’s pediatric outpatient department.
Since the participants in the DigiHero study had a rather high socio-economic status (SES) overall, we tried to recruit children and adolescents with a lower SES externally. An attempt was made to achieve oversampling by contacting youth centres and social institutions for children and distributing flyers and posters in districts with mostly low-income families. We distributed flyers and posters in social facilities and associations with a social pedagogical focus. Flyers and posters in Arabic were used in order to reach a wider audience. We decided to translate the flyers and posters into Arabic since it is the most commonly spoken language among migrants in Halle, hoping to better reach the parents of children with a migration background.
2.2. Questionnaire
We developed the questionnaire using established instruments. These instruments are all internationally established, validated, and considered to be easily comparable across studies. These instruments have also been used in large-scale studies carried out before the pandemic, enabling comparability with pre-pandemic conditions. The questionnaire consisted of 240 items in total. The instruments are described below in further detail and are listed in Table A1.
The first version of the questionnaire was piloted using the think-aloud method [57] with children and adolescents (both boys and girls, between 11 and 18 years of age). During the piloting, attention was paid to comprehensibility and processing time, as well as to substantive and formal comments and suggestions for change. Following the piloting, the questionnaire was revised again to make it easier to process and increase motivation to take part and complete the survey. Piloting did not lead to any substantial changes to the questionnaire.
2.3. Sociodemographic Variables
Regarding sociodemographic information, the survey included questions on the age and gender of the participants, parental occupational status, housing conditions, and migration background. In addition, variables related to lifestyle and living conditions were recorded, such as having a garden, a room of one’s own, and a good internet connection. Questions were also asked about the number of siblings, the relationship status of the parents, marital status, religious affiliation, and education.
Subjective socio-economic status was measured using the MacArthur Scale [58].
2.4. Impact and Burden of the COVID-19 Pandemic
In order to specifically examine the influence or the burden caused by the pandemic, we explored the difficulties that the children and adolescents were confronted with during the period in question.
This section used open-ended questions. The participants were asked to describe what the three biggest difficulties of the pandemic were for them. The questions were formulated as follows: “What stressed you most about the pandemic/still stresses you? What did you find worst/do you still find it very bad?”.
Similarly, the participants were also asked whether the pandemic and its associated restrictions had any positive effects on their lives.
2.5. Health-Related Quality of Life (HRQoL) and Mental Health
The instruments used in the study included the German version of the KIDSCREEN-10 to examine the HRQoL, which consists of 10 items providing a global HRQoL score that includes physical, psychological, and social components [59]. The evaluation of the KIDSCREEN-10 was based on the cut-off points for children/young adolescents (41.93 points) and older adolescents (40.26 points), as described by Hirschfeld et al. [60]. The KIDSCREEN-10 showed a good internal consistency and reliability (Cronbach’s alpha = 0.82) and a good test–retest reliability/stability (r = 0.73; ICC = 0.72) [61]. The German version of the CES-DC was used to measure depressive symptoms [62], which consists of 20 items in total with a response scale of four values [62]. Higher scores on the CES-DC indicate higher levels of depression [63]. The CES-DC showed a median internal consistency (Cronbach’s α) for all subscales and age groups of 0.67 [62]. The German version of the Strength and Difficulties Questionnaire (SDQ) used in this study assesses mental health problems in children and adolescents [64], focuses on 25 attributes, some positive and others negative, and is made up of five subscales [53,54]. Higher scores on the SDQ indicate a higher probability of abnormal behavior [64,65]. The internal consistency of the SDQ total score was α = 0.82 and showed only slight differences between genders. For the subscales, Cronbach’s alpha was between 0.58 (conduct problems) and 0.79 (hyperactivity) [66]. Certain common psychosomatic complaints (e.g., headaches, irritability, and feeling low) that had occurred within the previous six months were examined using the HBSC symptom checklist [67,68]. Regarding the HBSC symptom checklist, various studies conducted in Europe have shown an internal consistency between 0.75 and 0.81 [69,70,71,72]. The SCOFF Scale was used as a screening instrument for disordered eating [73]. The German version of the SCOFF Scale showed a test–retest reliability of 0.73 and a maximum accuracy of 82% (area under the ROC curve) [74]. The instruments are presented in more detail in Table A1.
In order to be able to summarize the individual health perceptions of the participants, the survey also contained a health scale in the form of a numerical rating scale. The respondents were asked how healthy they felt at the time they took part in the survey (0 = “very bad/sick” to 10 = “very good/healthy”).
Since existing studies indicate that sleep behavior is also influenced by the COVID-19 pandemic, the questionnaire covered some typical characteristics of sleep behavior, such as duration of sleep (e.g., “How many hours do you currently sleep on average every night?”), sleep problems, nightmares, and energy levels during the day [75,76,77].
Since studies from other countries show that the eating behavior of many was also influenced by the various pandemic-related measures, eating disorder symptoms were also examined in the questionnaire [78]. The most common symptoms of bulimia and anorexia nervosa, as well as indications of other eating disorders (e.g., “EDNOS” = eating disorder not otherwise specified), were measured using the SCOFF Scale [73]. Due to its brevity and simplicity in comparison to other screening instruments for eating disorders, we chose the SCOFF Scale, despite its low sensitivity, in order to obtain a rough overview of the prevalence of typical eating disorders in the corresponding age groups among the participants [79].
2.6. Physical Health and BMI
BMI was calculated from information on body weight and height. The values were evaluated based on the corresponding standard values of the Robert Koch Institute for the respective age groups [80]. Values between the 10th and the 90th percentile were rated as being in the normal range.
2.7. Data Analysis
Data were analyzed using descriptive statistics. We report absolute and relative frequencies and means and their respective standard deviations and 95% confidence intervals.
The percentages described below refer to the population of children and adolescents who answered the corresponding questions. An available case analysis was applied to all instruments and items, so that the populations might differ depending on the instrument. For the analysis of the open-ended questions, the respondents’ answers were coded using a qualitative content analysis [81]. In a second step, these codes were categorized and synthesized under broader categories. These categories were then used as categorical variables in further statistical analyses. For some analyses, the participants were divided into two subgroups according to their age (10 to 13 years and 14 to 18 years). To interpret the stratifications, we relied on the respective confidence intervals.
In accordance with the American Statistical Association guidelines for exploratory study designs, we did not calculate any statistical tests [82,83]. To further investigate the associations between socioeconomic characteristics, the extent to which the respondents’ were affected by the pandemic in terms of their sleeping and eating habits (independent variables), and the respective health outcomes (subjective health and health-related quality of life; dependent variables), we calculated six multivariable linear regression models. Model 1 measured the association between sociodemographic factors and health-related quality of life, while Model 2 measured the association between sociodemographic factors and subjective health. Model 3 calculated the associations between pandemic-related factors (such as number of quarantines, home schooling experience, and family/friends affected by COVID-19) and health-related quality of life, while Model 4 measured the relationship between the described pandemic-related variables and subjective health. Model 5 and Model 6 investigated the associations between disordered eating behavior and sleep problems with health-related quality of life and subjective health, respectively. We report regression coefficients and their 95% confidence intervals.
All analyses were performed in SAS, using the software version 9.4 as well as the SAS Studio version 2023.10.
2.8. Handling of Missing Data
Missing details were dealt with according to the specifications of the respective instruments. In the KIDSCREEN-10, all participants who left more than one item unanswered had to be excluded. Imputation was applied to the SDQ if no more than 2 items per subscale were left unanswered. Regarding the CES-DC, participants with missing data were completely excluded from the calculation.
2.9. Availability of Data and Materials
The datasets used and analysed during the current study are available from the corresponding author upon reasonable request.
3. Results
In total, 223 children and adolescents took part in the survey. In total, 111 children and adolescents participated in the survey as part of the DigiHero study, and 112 participants participated outside of the DigiHero study via their parents’ consent survey.
3.1. Sociodemographic Characteristics
The mean age was 14.3 years (range: 10–18 years). When asked about their gender, 55.4% (n = 93) of the participants identified themselves as girls, 41.7% (n = 70) as boys, and 2.9% (n = 5) as non-binary.
Most of the participants were born in Germany (n = 168 (99.4%)).
The majority of parents were married and most of the children stated that they lived in one household with both parents. Only 59.3% children answered the question on whether their parents were employed. Of those, 91.8% replied that their father was employed and 87.7% stated that their mother was employed. Of the 169 children who reported on their living conditions, 40.3% stated that they lived in a detached house and 59.7% affirmed that they lived in an apartment. The number of siblings who lived in the same household as the participants varied between zero and three. The corresponding mean was 0.96 siblings.
Almost all of the children (98.5%) who indicated that they lived in a detached house confirmed that there was a garden attached to it. Most of the participants who lived in an apartment also stated that the apartment had a garden, a terrace, or a backyard (69.7%).
Regarding the children’s rooms, 97.6% of the children confirmed that they had their own room and nearly all of them described having their own working space to study or complete homework. Almost all participants (97.0%) stated that they had their own computer, tablet, or a similar device at home. Slightly fewer households were equipped with a printer (86.3%). Regarding internet accessibility, 50.3% of the children and adolescents described generally having a good internet connection at home, while 45.6% defined their internet access as generally good, but not always working (e.g., being overloaded during home schooling). Further details are shown in Table A2.
Subjective social status, as measured on the MacArthur Scale, displayed a mean of 6.71 (95%CI: 6.51; 6.91) and a median of 7 with a range from 3 to 10.
3.2. Health Status
Information on general physical health was provided by 172 participants. The mean value was 7.3 (95%CI: 5.09; 9.55). The lowest value (0) was chosen by 1.7% (n = 3) of the children, and the highest value (10) by 12.8% (n = 22).
Information on BMI (weight and height) was provided by 165 children. The mean BMI was 20.37 (95%CI: 19.68; 21.03). A total of 16.4% (n= 27) of the participants were classified as being underweight (weight was below the 10th percentile according to Kromeyer–Hauschild), while 7.3% (n = 12) were overweight or obese (weight was over the 90th percentile according to Kromeyer–Hauschild).
3.3. Health-Related Quality of Life (KIDSCREEN-10)
In total, 85 children and adolescents completed the KIDSCREEN-10 questionnaire. Of those, 48.2% (n = 41, 95%CI: 37.39; 59.08)) reported a low HRQoL, while 51.8% (n = 44, 95%CI: 40.92; 62.61)) reported a high HRQoL.
3.4. Mental Health
3.4.1. Overall Mental Health (SDQ)
A total of 182 participants were included in the calculations regarding the SDQ. In total, 10.5% (n = 18) of the participants scored abnormal results in the overall assessment of the SDQ. In the additional subscale of prosocial behavior, which was not included in the overall assessment of the SDQ, 85.2% (n = 155) of participants scored normal values, 11.5% (n = 21) borderline values, and 3.3% (n = 6) abnormal values.
Stratified by gender, the overall assessment of the SDQ showed “abnormal” and “borderline” results slightly more often among female participants (n = 11 (12.2%) and n = 17 (18.9%)) than among male participants (n = 4 (6.2%), and n = 10 (15.4%)).
In addition, we stratified the SDQ by age group for the 162 children who provided the relevant information necessary for stratification. Overall, behavioral problems were more frequent among the older participants. In the overall assessment—which took emotional or conduct problems, difficulties in contact with peers, and hyperactivity into account—80.3% (n = 49) of the age group from 10 to 13 years showed no abnormalities. In contrast, among the 14- to 18-year-olds, 67.3% (n = 68) reached normal values. Further details regarding the SDQ subscales are shown in Table A3.
3.4.2. Depression (CES-DC)
The CES-DC was completed by 166 children and adolescents. The results of the CES-DC showed that 44.6% (n = 74) of the participating children and adolescents screened positive for depressive symptoms. When stratified by gender, we found that the female participants reported depressive symptoms considerably more frequently (n = 53 (59.6%), 95%CI: 49.4; 69.8) than the male participants (n = 14 (21.5%), 95%CI: 11.5; 31.5). Less than half of the girls exhibited no symptoms of depression (n = 32 (36.0%), 95%CI: 25.8; 46.2). In contrast, 75.4% of the boys reported no symptoms of depression (n = 49, 95%CI: 65.4; 85.4).
Also, there was a clear difference between the two age groups. Of the older adolescents, 52.0% (n = 51, 95%CI: 42.2; 61.2) screened positive for depressive symptoms and a further 7.1% (n = 7, 95%CI: 0.0; 17.0) scored borderline values for being depressed. In contrast, 31.8% (n = 20, 95%CI: 20.6; 43.9) in the younger age group scored positive for depressive symptoms, while 68.2% (n = 43, 95%CI: 56.1; 79.4) did not suffer from any corresponding symptoms.
3.4.3. (Psycho-)Somatic Health Complaints (HBSC Symptom Checklist)
Among all psychosomatic complaints, feeling irritable was named most often, with 58.9% (n = 109) of participants feeling the sensation of irritability almost every week or more frequently. Overall, the most rarely reported psychosomatic symptom was drowsiness (with 19.5% of all respondents reporting it “almost every week”, “several times a week”, or even “almost every day”).
In all the psychosomatic or physical complaints mentioned above, girls were affected considerably more frequently. Sleeping difficulties were least affected by this sex difference.
Also, psychosomatic complaints were reported by the older adolescents considerably more often compared to the children and younger adolescents. The details regarding the HBSC are shown in Table A4.
3.4.4. Disordered Eating According to the SCOFF Scale
In total, 19.2% (n = 33) of the participants screened positive for signs of an eating disorder. Girls reported signs of an eating disorder more often (n = 22 (23.7%), 95%CI: 15.02; 32.29) than boys (n = 9 (12.9%), 95%CI: 5.02; 20.70). Of the older adolescents, 20.2% (n = 21, 95%CI: 12.48; 27.91) of participants showed signs of an eating disorder compared to 16.9% (n = 11, 95%CI: 7.68; 25.66) in the younger age group.
3.4.5. Sleeping Habits
Questions regarding the duration of sleep at the time of the survey were answered by 162 participants. When asked “How many hours do you sleep each night at the moment?”, the answer with the shortest duration was 4 h and the longest sleep duration was 12 h. The participants reported a mean of 7.6 h per night (95%CI: 7.39; 7.82).
At this point, the results of the HBSC symptom checklist should be briefly referred to again. Regarding the question about sleep problems, 49.7% (n = 92) of the participants who completed the questionnaire stated that they experienced sleep problems “almost daily” to “almost every week”.
3.5. Worst Things during the Pandemic
A total of 402 responses regarding the worst things about the pandemic were given by the participants.
Most frequently (27.36%, n = 110) mentioned as the greatest burden during the COVID-19 pandemic first lockdown were the leisure and mobility restrictions. In second place, the lack of contact with friends and family members was commonly mentioned (18.66%, n = 75).
Almost as often as the contact restrictions, home schooling was named as a stressful factor (18.40%, n = 74). Emotional difficulties (10.95%, n = 44), arguments at home (7.21%, n =29), and fears of potential infections with COVID-19 among loved ones and the possible consequences (3.73%, n = 15) were often mentioned.
3.6. Positive Consequences
Overall, 28.25% (n = 63) of the participants described positive consequences that the pandemic had on their personal lives. Especially in terms of learning online and from home, these participants stated that they had become more independent and had found new ways of learning and improving their time management, as well as being enabled to develop their own daily structure (n = 16). Spending more time with family members was mentioned as an advantage of the pandemic as well (n = 10). Better handling of technology, digital networks, and computer programs was also reported (n = 9). In addition, some described that they had discovered new aspects of themselves or learned more about their weaknesses and, above all, their strengths (n = 8).
3.7. Further Stratifications
Further stratifications according to the variables of “Having a pet”, “Number of siblings”, “Internet quality”, “School performance”, “Type of school”, “Drug use”, “Religious affiliation”, and “Social media usage” were carried out for all outcomes, but did not show any relevant differences between groups. Stratifications according to social status were originally planned, but could not be carried out due to the small number of participants with a low socioeconomic status.
3.8. Regression Analyses
Model 1 showed that there were no associations between quality of life and socio-demographic characteristics. However, there was a notable association with subjective social status, as follows: children who perceived their social status to be higher tended to report a higher quality of life. Similarly, no significant associations were found between subjective health and socio-demographic characteristics, as measured by Model 2. Nonetheless, a strong association existed between subjective health and subjective social status, as follows: children who rated their social status higher also reported a better subjective health. For further details, see Table A5.
Additionally, none of the variables measuring the impact of the pandemic showed any significant association with subjective health or quality of life (measured by Models 3 and 4). Detailed information can be found in Table A6.
Model 5 showed that children who experienced daily sleep problems and those with abnormal eating behaviors, as indicated by the SCOFF Scale, reported a lower quality of life. Furthermore, children with daily sleep problems also tended to describe a poorer subjective health (Model 6). For further details, see Table A7.
4. Discussion
Overall, the participants in this study had an average to high socioeconomic status and reported a good general physical health. The pandemic was described as being stressful due to factors such as home schooling and contact restrictions, but about about one-third of the respondents also indicated experiencing positive consequences from the pandemic. Accordingly, the participants often reported a good health-related quality of life (HRQoL) and showed a low frequency of emotional problems.
Comparing these results with other German studies, such as the first two surveys of the German COPSY study and a study from Mecklenburg–Western Pomerania, the participants of our study scored similarly in terms of HRQoL [84,85]. A third survey of the COPSY study, conducted at the end of 2021, about three months after our study took place, indicated a trend towards a better HRQoL compared to earlier pandemic surveys, which was not reflected to the same extent in our data [39].
It is noteworthy that the evaluation of HRQoL using the KIDSCREEN-10 in the aforementioned studies was based on standard deviations, while our study was based on the cut-off point values from the corresponding publication by Hirschfeld et al. [60]. Despite this methological difference, the HRQoL among our participants was more often rated as low compared to the first COPSY survey and equally often as low as the second COPSY survey [37,38]. Compared to the third COPSY survey, a low HRQoL was more frequently mentioned in our study [39]. Pre-pandemic conditions were reached neither in our study nor in the third COPSY survey. In summary, at the time of our survey, the quality of life of children and young people was still visibly affected by the circumstances of the COVID-19 pandemic. A fourth survey of the COPSY study in February 2022 showed results similar to our data, with over 40% of the participants reporting a low HRQoL [86].
In our study, 10.5% of participants showed abnormalities concerning their general mental health, as assessed by the SDQ. This prevalence roughly equals the pre-pandemic prevalence assessed in the BELLA study [87,88,89]. In this regard, no relevant differences in the overall mental health situation of children and adolescents in Germany before the start of the pandemic could be identified. The results of the fifth wave of the COPSY study also showed an improvement in the mental health of children and young people based on the SDQ. Although the participants in our study did not reach pre-pandemic values on this scale, our results align with the noticeable downward trend in mental health problems on the SDQ, as presented in the COPSY study [90].
A considerably higher percentage of depressive symptoms was found in our study compared to the BELLA study, where depressive symptoms, assessed using the PHQ (Patient Health Questionnaire-9 for Young Adults), were below 10% [62,91]. In our study, 43.9% of the participants reached scores that exceeded the cut-off points for depression. This relatively high percentage of depressive symptoms correlates with the results of the KIDSCREEN-10, but contrasts with the lower percentage of mental health problems determined with the SDQ. However, other studies have also reported increased levels of depression during and after the COVID-19 pandemic, although not to the extent observed in our results [92,93,94]. Similar values to the CES-DC results in our study were found in a study from Italy, conducted earlier in the pandemic (May 2020), where 60% of children and adolescents of the general population reported scores above the cut-offs for clinically relevant symptoms on the CES-DC [95].
The high percentage of participants scoring positive for depression on the CES-DC can possibly be explained by the long-term restrictions to many hobbies and activities, as well as social interactions, which likely suppressed the mood of children and adolescents, since mental health and sleep were continuously influenced by the pandemic and its associated measures [31,96]. Pre-pandemic studies have shown that loneliness, defined as dissatisfaction with number of friends or frequency of social contact, can be a stressor and trigger for depressive symptoms in children and adolescents [97,98].
It has also been proven in various studies that there is a close correlation between HRQoL and depression, which can also be seen in our data [59,99,100,101,102,103]. A clear correlation between the KIDSCREEN-52 and the CES-DC was already determined by the BELLA study [104]. In the KIDSCREEN-10, there also seemed to be the highest correlation between the index total score and the items for the mood and emotions dimension, which also covers depressive symptoms, which could explain the corresponding correlation of our HRQoL results with the results of the CES-DC [105].
The low HRQoL determined from the KIDSCREEN-10 indicates that the participants felt “unhappy, unfit and dissatisfied with regards to family life, peers and school life” [61], enabling a correlation with the CES-DC, which measures subjectively experienced depressive symptoms. Although the SDQ can correlate with HRQoL [106], it also reflects other dimensions of mental health problems, such as hyperactivity, prosocial behavior, and conduct problems [64].
In addition, it should be noted that the KIDSCREEN-10 and CES-DC refer to the last week in terms of their items, while the SDQ asks about the previous 6 months [59,63,64].
The results concerning psychosomatic complaints were in line with previous studies among children and adolescents during the COVID-19 pandemic. It was particularly striking that emotional complaints such as “irritability” and “feeling low” were clearly the most frequently experienced, while physical symptoms such as “abdominal pain” or “back pain” were mentioned less often and about as often as pre-pandemic [67,107]. Children and adolescents in different countries reported experiencing irritability with a similarly high frequency (over 50% described this phenomenon) during the pandemic [108,109,110]. These emotional complaints, which can occur in the context of depressive moods, match the increased occurrence of high scores in the CES-DC [111,112,113,114].
Another common mental health problem in children and adolescents is eating disorders, which often appear in comorbidity with depression, anxiety, and other mental illnesses [115,116,117,118].
The prevalence of eating disorders recorded in this study was 19.2% and was not drastically higher than that recorded in the pre-pandemic BELLA study, in which the prevalence was 19.3% (baseline study) and 13.8% (follow-up study), respectively [119]. Stratified by age group, our study also showed that older adolescents showed a slightly higher prevalence of disordered eating [120]. However, other international studies indicate an increase in the number of cases of eating disorders since the beginning of the COVID-19 pandemic [121,122,123].
In children and adolescents with an overall high SES, which is often associated with a safe family situation, easy access to educational opportunities, and other circumstances identified as resilience factors, the impact of the pandemic on mental health could, therefore, be rather slight in the long term.
5. Conclusions
Our study revealed that, at the time of data collection, certain aspects of mental health among children and adolescents showed improvement compared to earlier points in the pandemic.
However, HRQoL remained comparatively low and a higher proportion of participants exceeded the cut-off points for depressive symptoms compared to pre-pandemic studies. This suggests that the COVID-19 pandemic had a major impact on the mental health of children and young people, while also indicating a gradual diminishment of these effects over time. Despite the extensive and far-reaching concequences of the COVID-19 pandemic, our findings align with other studies that suggest a visible trend of ongoing improvement in the mental health of children and adolescents. This trend also indicates the potential for further improvements in children and adolescents’ mental health over time.
The insights from our regression analyses emphasize the critical role of subjective social status in mental health outcomes.
The participants in our study identified restricted mobility, a lack of contact with friends, and the challenges of home schooling to be the most stressful collateral effects of the pandemic. These findings suggest that, in the event of another lockdown or similar situations in the future, it is crucial to address these stressors early on and identify measures to mitigate their effects on children and adolescents.
Additionally, our study highlights the importance of recognizing and leveraging children’s resources and the positive aspects of the pandemic experience, such as increased independence and enhanced family togetherness. These factors can be pivotal in providing better support to children and adolescents during extraordinary times.
In summary, this study makes an important contribution to the understanding of the multifaceted effects of the COVID-19 pandemic on youth mental health. It emphasizes the importance of subjective social status and specific behavioral factors, providing valuable insights that can inform future research and intervention strategies aimed at supporting the mental health and well-being of children and adolescents during crises.
Limitations
The main weakness of this study is its very homogeneous study population, as only a few participants with a migration background took part, the participants’ SES was comparatively high, and their living conditions were rather similar. As a result, the situation of structurally disadvantaged children, e.g., those with a migration background or those from families with a low SES, could not be shown, and important determinants affecting their mental health could not be assessed. The number of participants should be mentioned at this point as well, as it is relatively small, which means that some stratifications and subgroup analyses were not possible. Another weakness of this study is its cross-sectional design, since other studies had to be used in order to contextualize our study results. Pre-pandemic data were used for comparison, which means that conclusions concerning temporal trends can only be derived to a limited extent, since the study populations consisted of differently composed samples.
Due to the age range of the participants, a further limitation can be identified regarding the differences in the mental development and age-related cognitive abilities of the children and adolescents who carried out the survey.
Conceptualization, A.K., A.F., R.M. and K.R.; data curation, A.K. and A.F.; formal analysis, A.K. and A.F.; methodology, A.K., A.F. and K.R.; project administration, A.F. and K.R.; supervision, A.F., R.M. and K.R.; writing—original draft, A.K.; writing—review and editing, A.K., A.F., M.B., S.D., T.F., M.G. (Michael Gekle), M.G. (Matthias Girndt), C.G., J.H., B.K., K.K., I.M., J.R., D.S., J.-H.K., R.M. and K.R. All authors have read and agreed to the published version of the manuscript.
The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of Ethics Committee of the Martin Luther University Halle-Wittenberg for studies involving humans on 17 June 2021 and approval code is 2021-123.
Informed consent was obtained from all subjects involved in the study.
The datasets used and analysed during the current study are available from the corresponding author on reasonable request.
The authors would like to thank the research assistants of the DigiHero-team for their technical support, Mohammad Assaf for his help during recruitment and KIDSCREEN-Group for allowing us to use the KIDSCREEN-10 questionnaire as well as the HBSC-Study group for providing the HBSC symptom checklist. This publication was supported by the German Federal Ministry of Education and Research (BMBF) Network of University Medicine 2.0: “NUM 2.0”, Grant No. 01KX2121, Project: Collateral Effects in Pandemics—CollPan. We acknowledge the financial support of the Open Access Publication Fund of the Martin-Luther-University Halle-Wittenberg.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The authors declare that they have no competing interests. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
Footnotes
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
References
1. Sevinc, S.A.; Metin, S.; Basi, N.B.; Cinar, A.S.; Ozkan, M.T.; Oba, S. Anxiety and burnout in anesthetists and intensive care unit nurses during the COVID-19 pandemic: A cross-sectional study. Braz. J. Anesthesiol. Engl. Ed.; 2021; 72, pp. 169-175. [DOI: https://dx.doi.org/10.1016/j.bjane.2021.07.011]
2. Raoofi, S.; Kan, F.P.; Rafiei, S.; Khani, S.; Hosseinifard, H.; Tajik, F.; Masoumi, M.; Raoofi, N.; Ahmadi, S.; Aghalou, S. et al. Anxiety during the COVID-19 pandemic in hospital staff: Systematic review plus meta-analysis. BMJ Support. Palliat. Care; 2021; 13, pp. 127-135. [DOI: https://dx.doi.org/10.1136/bmjspcare-2021-003125] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/34312187]
3. Lu, M.-Y.; Ahorsu, D.K.; Kukreti, S.; Strong, C.; Lin, Y.-H.; Kuo, Y.-J.; Chen, Y.-P.; Lin, C.-Y.; Chen, P.-L.; Ko, N.-Y. et al. The Prevalence of Post-traumatic Stress Disorder Symptoms, Sleep Problems, and Psychological Distress among COVID-19 Frontline Healthcare Workers in Taiwan. Front. Psychiatry; 2021; 12, 705657. [DOI: https://dx.doi.org/10.3389/fpsyt.2021.705657] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/34322044]
4. Zhang, R.; Hou, T.; Kong, X.; Wang, G.; Wang, H.; Xu, S.; Xu, J.; He, J.; Xiao, L.; Wang, Y. et al. PTSD among Healthcare Workers During the COVID-19 Outbreak: A Study Raises Concern for Non-medical Staff in Low-Risk Areas. Front. Psychiatry; 2021; 12, 696200. [DOI: https://dx.doi.org/10.3389/fpsyt.2021.696200]
5. Lee, B.E.C.; Ling, M.; Boyd, L.; Olsson, C.; Sheen, J. The prevalence of probable mental health disorders among hospital healthcare workers during COVID-19: A systematic review and meta-analysis. J. Affect. Disord.; 2023; 330, pp. 329-345. [DOI: https://dx.doi.org/10.1016/j.jad.2023.03.012]
6. Ghahramani, S.; Kasraei, H.; Hayati, R.; Tabrizi, R.; Marzaleh, M.A. Health care workers’ mental health in the face of COVID-19: A systematic review and meta-analysis. Int. J. Psychiatry Clin. Pract.; 2023; 27, pp. 208-217. [DOI: https://dx.doi.org/10.1080/13651501.2022.2101927]
7. Dragioti, E.; Tsartsalis, D.; Mentis, M.; Mantzoukas, S.; Gouva, M. Impact of the COVID-19 pandemic on the mental health of hospital staff: An umbrella review of 44 meta-analyses. Int. J. Nurs. Stud.; 2022; 131, 104272. [DOI: https://dx.doi.org/10.1016/j.ijnurstu.2022.104272]
8. Hill, J.E.; Harris, C.; Danielle, L.C.; Boland, P.; Doherty, A.J.; Benedetto, V.; Gita, B.E.; Clegg, A.J. The prevalence of mental health conditions in healthcare workers during and after a pandemic: Systematic review and meta-analysis. J. Adv. Nurs.; 2022; 78, pp. 1551-1573. [DOI: https://dx.doi.org/10.1111/jan.15175]
9. Vindegaard, N.; Benros, M.E. COVID-19 pandemic and mental health consequences: Systematic review of the current evidence. Brain. Behav. Immun.; 2020; 89, pp. 531-542. [DOI: https://dx.doi.org/10.1016/j.bbi.2020.05.048]
10. Deng, J.; Zhou, F.; Hou, W.; Silver, Z.; Wong, C.Y.; Chang, O.; Huang, E.; Zuo, Q.K. The prevalence of depression, anxiety, and sleep disturbances in COVID-19 patients: A meta-analysis. Ann. N. Y. Acad. Sci.; 2021; 1486, pp. 90-111. [DOI: https://dx.doi.org/10.1111/nyas.14506]
11. Kang, E.; Lee, S.Y.; Kim, M.S.; Jung, H.; Kim, K.H.; Kim, K.-N.; Park, H.Y.; Lee, Y.J.; Cho, B.; Sohn, J.H. The Psychological Burden of COVID-19 Stigma: Evaluation of the Mental Health of Isolated Mild Condition COVID-19 Patients. J. Korean Med. Sci.; 2021; 36, e33. [DOI: https://dx.doi.org/10.3346/jkms.2021.36.e33] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33463098]
12. Hossain, M.M.; Tasnim, S.; Sultana, A.; Faizah, F.; Mazumder, H.; Zou, L.; McKyer, E.L.J.; Ahmed, H.U.; Ma, P. Epidemiology of mental health problems in COVID-19: A review. F1000Research; 2020; 9, 636. [DOI: https://dx.doi.org/10.12688/f1000research.24457.1] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33093946]
13. Brooks, S.K.; Webster, R.K.; Smith, L.E.; Woodland, L.; Wessely, S.; Greenberg, N.; Rubin, G.J. The psychological impact of quarantine and how to reduce it: Rapid review of the evidence. Lancet; 2020; 395, pp. 912-920. [DOI: https://dx.doi.org/10.1016/S0140-6736(20)30460-8] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32112714]
14. Torales, J.; O’Higgins, M.; Castaldelli-Maia, J.M.; Ventriglio, A. The outbreak of COVID-19 coronavirus and its impact on global mental health. Int. J. Soc. Psychiatry; 2020; 66, pp. 317-320. [DOI: https://dx.doi.org/10.1177/0020764020915212]
15. Lindert, J.; Jakubauskiene, M.; Bilsen, J. The COVID-19 disaster and mental health—Assessing, responding and recovering. Eur. J. Public Health; 2021; 31, (Suppl. S4), pp. iv31-iv35. [DOI: https://dx.doi.org/10.1093/eurpub/ckab153]
16. Ma, D.; Kuang, Y.; Lan, Z.; Zeng, S.; Li, Y.; Shang, M.; Zhang, R.-Y.; Zhao, B.; Li, W. The rapid change in mental health among college students after introduction of on-campus quarantine during the 2022 Shanghai COVID-19 lockdown. Front. Public Health; 2023; 11, 1132575. [DOI: https://dx.doi.org/10.3389/fpubh.2023.1132575]
17. Keller, F.M.; Derksen, C.; Kötting, L.; Dahmen, A.; Lippke, S. Distress, loneliness, and mental health during the COVID-19 pandemic: Test of the extension of the Evolutionary Theory of Loneliness. Appl. Psychol. Health Well-Being; 2022; 15, pp. 24-48. [DOI: https://dx.doi.org/10.1111/aphw.12352]
18. Wu, Y.; Chen, Z.; Jiang, D.; Shen, Z.; Zhu, S.; Wang, K.; Wang, Y. Repeated quarantine experiences are associated with increased mental health symptoms. Gen. Hosp. Psychiatry; 2023; 82, pp. 103-104. [DOI: https://dx.doi.org/10.1016/j.genhosppsych.2023.02.003]
19. Zimmermann, P.; Curtis, N. Why is COVID-19 less severe in children? A review of the proposed mechanisms underlying the age-related difference in severity of SARS-CoV-2 infections. Arch. Dis. Child.; 2021; 106, pp. 429-439. [DOI: https://dx.doi.org/10.1136/archdischild-2020-320338]
20. Swann, O.V.; Holden, K.A.; Turtle, L.; Pollock, L.; Fairfield, C.J.; Drake, T.M.; Seth, S.; Egan, C.; Hardwick, H.E.; Halpin, S. et al. Clinical characteristics of children and young people admitted to hospital with covid-19 in United Kingdom: Prospective multicentre observational cohort study. BMJ; 2020; 370, m3249. [DOI: https://dx.doi.org/10.1136/bmj.m3249]
21. Sinaei, R.; Pezeshki, S.; Parvaresh, S.; Sinaei, R. Why COVID-19 is less frequent and severe in children: A narrative review. World J. Pediatr.; 2021; 17, pp. 10-20. [DOI: https://dx.doi.org/10.1007/s12519-020-00392-y] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32978651]
22. Lee, J. Mental health effects of school closures during COVID-19. Lancet Child Adolesc. Health; 2020; 4, 421. [DOI: https://dx.doi.org/10.1016/S2352-4642(20)30109-7] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32302537]
23. Singh, S.; Roy, D.; Sinha, K.; Parveen, S.; Sharma, G.; Joshi, G. Impact of COVID-19 and lockdown on mental health of children and adolescents: A narrative review with recommendations. Psychiatry Res.; 2020; 293, 113429. [DOI: https://dx.doi.org/10.1016/j.psychres.2020.113429] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32882598]
24. Liang, L.; Ren, H.; Cao, R.; Hu, Y.; Qin, Z.; Li, C.; Mei, S. The Effect of COVID-19 on Youth Mental Health. Psychiatr. Q.; 2020; 91, pp. 841-852. [DOI: https://dx.doi.org/10.1007/s11126-020-09744-3] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32319041]
25. COVID-19 and School Closures: One Year of Education Disruption. UNICEF DATA. Available online: https://data.unicef.org/resources/one-year-of-covid-19-and-school-closures/ (accessed on 17 April 2022).
26. Cacchiarelli San Román, N.; Eymann, A.; Ferraris, J.R. Current impact and future consequences of the pandemic on children’s and adolescents’ health. Arch. Argent. Pediatr.; 2021; 119, pp. e594-e599. [DOI: https://dx.doi.org/10.5546/aap.2021.eng.e594]
27. Saurabh, K.; Ranjan, S. Compliance and Psychological Impact of Quarantine in Children and Adolescents due to Covid-19 Pandemic. Indian J. Pediatr.; 2020; 87, pp. 532-536. [DOI: https://dx.doi.org/10.1007/s12098-020-03347-3]
28. Zhang, L.; Zhang, D.; Fang, J.; Wan, Y.; Tao, F.; Sun, Y. Assessment of Mental Health of Chinese Primary School Students before and after School Closing and Opening during the COVID-19 Pandemic. JAMA Netw. Open; 2020; 3, e2021482. [DOI: https://dx.doi.org/10.1001/jamanetworkopen.2020.21482]
29. Hawes, M.T.; Szenczy, A.K.; Klein, D.N.; Hajcak, G.; Nelson, B.D. Increases in depression and anxiety symptoms in adolescents and young adults during the COVID-19 pandemic. Psychol. Med.; 2022; 52, pp. 3222-3230. [DOI: https://dx.doi.org/10.1017/S0033291720005358]
30. Lee, C.M.; Cadigan, J.M.; Rhew, I.C. Increases in Loneliness among Young Adults during the COVID-19 Pandemic and Association with Increases in Mental Health Problems. J. Adolesc. Health; 2020; 67, pp. 714-717. [DOI: https://dx.doi.org/10.1016/j.jadohealth.2020.08.009]
31. Loades, M.E.; Chatburn, E.; Higson-Sweeney, N.; Reynolds, S.; Shafran, R.; Brigden, A.; Linney, C.; McManus, M.N.; Borwick, C.; Crawley, E. Rapid Systematic Review: The Impact of Social Isolation and Loneliness on the Mental Health of Children and Adolescents in the Context of COVID-19. J. Am. Acad. Child Adolesc. Psychiatry; 2020; 59, pp. 1218-1239.e3. [DOI: https://dx.doi.org/10.1016/j.jaac.2020.05.009]
32. Orgilés, M.; Morales, A.; Delvecchio, E.; Mazzeschi, C.; Espada, J.P. Immediate Psychological Effects of the COVID-19 Quarantine in Youth from Italy and Spain. Front. Psychol.; 2020; 11, 579038. [DOI: https://dx.doi.org/10.3389/fpsyg.2020.579038] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33240167]
33. Chen, F.; Zheng, D.; Liu, J.; Gong, Y.; Guan, Z.; Lou, D. Depression and anxiety among adolescents during COVID-19: A cross-sectional study. Brain. Behav. Immun.; 2020; 88, pp. 36-38. [DOI: https://dx.doi.org/10.1016/j.bbi.2020.05.061] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32464156]
34. Jiao, W.Y.; Wang, L.N.; Liu, J.; Fang, S.F.; Jiao, F.Y.; Pettoello-Mantovani, M.; Somekh, E. Behavioral and Emotional Disorders in Children during the COVID-19 Epidemic. J. Pediatr.; 2020; 221, pp. 264-266.e1. [DOI: https://dx.doi.org/10.1016/j.jpeds.2020.03.013] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32248989]
35. de Figueiredo, C.S.; Sandre, P.C.; Portugal, L.C.L.; Mázala-de-Oliveira, T.; da Silva Chagas, L.; Raony, Í.; Ferreira, E.S.; Giestal-de-Araujo, E.; Dos Santos, A.A.; Bomfim, P.O.-S. COVID-19 pandemic impact on children and adolescents’ mental health: Biological, environmental, and social factors. Prog. Neuropsychopharmacol. Biol. Psychiatry; 2021; 106, 110171. [DOI: https://dx.doi.org/10.1016/j.pnpbp.2020.110171]
36. Ravens-Sieberer, U.; Kaman, A.; Otto, C.; Adedeji, A.; Napp, A.-K.; Becker, M.; Blanck-Stellmacher, U.; Löffler, C.; Schlack, R.; Hölling, H. et al. Seelische Gesundheit und psychische Belastungen von Kindern und Jugendlichen in der ersten Welle der COVID-19-Pandemie—Ergebnisse der COPSY-Studie. Bundesgesundheitsbl.—Gesundheitsforsch.—Gesundheitsschutz; 2021; 64, pp. 1512-1521. [DOI: https://dx.doi.org/10.1007/s00103-021-03291-3]
37. Ravens-Sieberer, U.; Kaman, A.; Otto, C.; Adedeji, A.; Devine, J.; Erhart, M.; Napp, A.-K.; Becker, M.; Blanck-Stellmacher, U.; Löffler, C. et al. Mental Health and Quality of Life in Children and Adolescents During the COVID-19 Pandemic—Results of the Copsy Study. Dtsch. Ärztebl. Int.; 2020; 117, pp. 828-829. [DOI: https://dx.doi.org/10.3238/arztebl.2020.0828]
38. Ravens-Sieberer, U.; Kaman, A.; Erhart, M.; Otto, C.; Devine, J.; Löffler, C.; Hurrelmann, K.; Bullinger, M.; Barkmann, C.; Siegel, N. et al. Quality of life and mental health in children and adolescents during the first year of the COVID-19 pandemic: Results of a two-wave nationwide population-based study. Eur. Child Adolesc. Psychiatry; 2021; 32, pp. 575-588. [DOI: https://dx.doi.org/10.1007/s00787-021-01889-1]
39. Ravens-Sieberer, U.; Erhart, M.; Devine, J.; Gilbert, M.; Reiss, F.; Barkmann, C.; Siegel, N.; Simon, A.; Hurrelmann, K.; Schlack, R. et al. Child and Adolescent Mental Health during the COVID-19 Pandemic: Results of the Three-Wave Longitudinal COPSY Study. J. Adolesc. Health; 2022; 71, pp. 570-578. [DOI: https://dx.doi.org/10.1016/j.jadohealth.2022.06.022]
40. Deutsches Ärzteblatt. Corona und Psyche: Kinder und Jugendliche Weiterhin Psychisch Belastet. Available online: https://www.aerzteblatt.de/nachrichten/131672/Corona-und-Psyche-Kinder-und-Jugendliche-weiterhin-psychisch-belastet (accessed on 17 April 2022).
41. Mdr. Chronik: Alle Nachrichten zur Corona-Krise 2021. Available online: https://www.mdr.de/nachrichten/jahresrueckblick/corona-nachrichten-jahresrueckblick-chronologie-100.html (accessed on 26 July 2023).
42. Bundesministerium für Gesundheit. Chronik zum Coronavirus SARS-CoV-2. Available online: https://www.bundesgesundheitsministerium.de/coronavirus/chronik-coronavirus.html (accessed on 26 July 2023).
43. Arroyo-Borrell, E.; Renart, G.; Saurina, C.; Saez, M. Influence maternal background has on children’s mental health. Int. J. Equity Health; 2017; 16, 63. [DOI: https://dx.doi.org/10.1186/s12939-017-0559-1]
44. Yang, P.; Hernandez, B.S.; Plastino, K.A. Social determinants of mental health and adolescent anxiety and depression: Findings from the 2018 to 2019 National Survey of Children’s Health. Int. J. Soc. Psychiatry; 2023; 69, pp. 795-798. [DOI: https://dx.doi.org/10.1177/00207640221119035]
45. Beutel, M.E.; Klein, E.M.; Brähler, E.; Reiner, I.; Jünger, C.; Michal, M.; Wiltink, J.; Wild, P.S.; Münzel, T.; Lackner, K.J. et al. Loneliness in the general population: Prevalence, determinants and relations to mental health. BMC Psychiatry; 2017; 17, 97. [DOI: https://dx.doi.org/10.1186/s12888-017-1262-x] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/28320380]
46. Cotton, N.K.; Shim, R.S. Social Determinants of Health, Structural Racism, and the Impact on Child and Adolescent Mental Health. J. Am. Acad. Child Adolesc. Psychiatry; 2022; 61, pp. 1385-1389. [DOI: https://dx.doi.org/10.1016/j.jaac.2022.04.020] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/35533798]
47. Wölfle, S.; Jost, D.; Oades, R.; Schlack, R.; Hölling, H.; Hebebrand, J. Somatic and mental health service use of children and adolescents in Germany (KiGGS-study). Eur. Child Adolesc. Psychiatry; 2014; 23, pp. 753-764. [DOI: https://dx.doi.org/10.1007/s00787-014-0525-z]
48. Xiao, Y.; Mann, J.J.; Chow, J.C.-C.; Brown, T.T.; Snowden, L.R.; Yip, P.S.-F.; Tsai, A.C.; Hou, Y.; Pathak, J.; Wang, F. et al. Patterns of Social Determinants of Health and Child Mental Health, Cognition, and Physical Health. JAMA Pediatr.; 2023; 177, pp. 1294-1305. [DOI: https://dx.doi.org/10.1001/jamapediatrics.2023.4218]
49. Owens, J.A.; Weiss, M.R. Insufficient sleep in adolescents: Causes and consequences. Minerva Pediatr.; 2017; 69, pp. 326-336. [DOI: https://dx.doi.org/10.23736/S0026-4946.17.04914-3]
50. Tarokh, L.; Saletin, J.M.; Carskadon, M.A. Sleep in adolescence: Physiology, cognition and mental health. Neurosci. Biobehav. Rev.; 2016; 70, pp. 182-188. [DOI: https://dx.doi.org/10.1016/j.neubiorev.2016.08.008]
51. Morales-Muñoz, I.; Gregory, A.M. Sleep and Mental Health Problems in Children and Adolescents. Sleep Med. Clin.; 2023; 18, pp. 245-254. [DOI: https://dx.doi.org/10.1016/j.jsmc.2023.01.006]
52. Chaput, J.-P.; Dutil, C.; Featherstone, R.; Ross, R.; Giangregorio, L.; Saunders, T.J.; Janssen, I.; Poitras, V.J.; Kho, M.E.; Ross-White, A. et al. Sleep timing, sleep consistency, and health in adults: A systematic review. Appl. Physiol. Nutr. Metab.; 2020; 45, (Suppl. S2), pp. S232-S247. [DOI: https://dx.doi.org/10.1139/apnm-2020-0032]
53. Tagesschau. Schulen Kehren Weitgehend in den Regelbetrieb zurück. Available online: https://www.tagesschau.de/inland/gesellschaft/coronavirus-schulen-regelbetrieb-101.html (accessed on 17 April 2022).
54. NDR. Corona-Chronologie: Mai 2021. Available online: https://www.ndr.de/nachrichten/info/Corona-Chronologie-Mai-2021,coronachronologie142.html (accessed on 17 April 2022).
55. Mdr. Das War der Mai 2021: Corona-Lockerungen, Raketenkrieg, Belarus und der Blogger. Available online: https://www.mdr.de/nachrichten/jahresrueckblick/chronik-mai-zweitausendeinundzwanzig-ereignisse-nachrichten-100.html (accessed on 17 April 2022).
56. Digi-Hero—Eine Populationsbasierte Studie zur Digitalen Gesundheitsforschung in Deutschland. Available online: https://webszh.uk-halle.de/digihero/ (accessed on 27 March 2022).
57. Wolcott, M.D.; Lobczowski, N.G. Using cognitive interviews and think-aloud protocols to understand thought processes. Curr. Pharm. Teach. Learn.; 2021; 13, pp. 181-188. [DOI: https://dx.doi.org/10.1016/j.cptl.2020.09.005]
58. Lampert, T.; Hoebel, J.; Kuntz, B.; Müters, S.; Kroll, L.E. Messung des sozioökonomischen Status und des subjektiven sozialen Status in KiGGS Welle 2. J. Health Monit.; 2018; [DOI: https://dx.doi.org/10.25646/2968]
59. Ravens-Sieberer, U.; Herdman, M.; Devine, J.; Otto, C.; Bullinger, M.; Rose, M.; Klasen, F. The European KIDSCREEN approach to measure quality of life and well-being in children: Development, current application, and future advances. Qual. Life Res.; 2014; 23, pp. 791-803. [DOI: https://dx.doi.org/10.1007/s11136-013-0428-3] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/23686556]
60. Hirschfeld, G.; von Brachel, R.; Thiele, C. Screening for health-related quality of lifein children and adolescents: Optimal cut points for the KIDSCREEN-10 for epidemiologicalstudies. Qual. Life Res.; 2020; 29, pp. 529-536. [DOI: https://dx.doi.org/10.1007/s11136-019-02324-4] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/31620984]
61. The KIDSCREEN Group Europe. The KIDSCREEN Questionnaires—Quality of Life Questionnaires for 697 Children and Adolescents: Handbook; Pabst Science Publishers: Lengerich, Germany, 2006.
62. Barkmann, C.; Erhart, M.; Schulte-Markwort, M. the BELLA Study Group. The German version of the Centre for Epidemiological Studies Depression Scale for Children: Psychometric evaluation in a population-based survey of 7 to 17 years old children and adolescents—Results of the BELLA study. Eur. Child Adolesc. Psychiatry; 2008; 17, pp. 116-124. [DOI: https://dx.doi.org/10.1007/s00787-008-1013-0] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/19132311]
63. Shahid, A.; Wilkinson, K.; Marcu, S.; Shapiro, C.M. Center for Epidemiological Studies Depression Scale for Children (CES-DC). STOP, THAT and One Hundred Other Sleep Scales; Shahid, A.; Wilkinson, K.; Marcu, S.; Shapiro, C.M. Springer: New York, NY, USA, 2011; pp. 93-96. [DOI: https://dx.doi.org/10.1007/978-1-4419-9893-4_16]
64. Theunissen, M.H.C.; de Wolff, M.S.; Reijneveld, S.A. The Strengths and Difficulties Questionnaire Self-Report: A Valid Instrument for the Identification of Emotional and Behavioral Problems. Acad. Pediatr.; 2019; 19, pp. 471-476. [DOI: https://dx.doi.org/10.1016/j.acap.2018.12.008]
65. Becker, A.; Wang, B.; Kunze, B.; Otto, C.; Schlack, R.; Hölling, H.; Ravens-Sieberer, U.; Klasen, F.; Rogge, J.; Isensee, C. et al. Normative Data of the Self-Report Version of the German Strengths and Difficulties Questionnaire in an Epidemiological Setting. Z. Kinder-Jugendpsychiatrie Psychother.; 2018; 46, pp. 523-533. [DOI: https://dx.doi.org/10.1024/1422-4917/a000589]
66. Rothenberger, A.; Becker, A.; Erhart, M.; Wille, N.; Ravens-Sieberer, U. the BELLA Study Group. Psychometric properties of the parent strengths and difficulties questionnaire in the general population of German children and adolescents: Results of the BELLA study. Eur. Child Adolesc. Psychiatry; 2008; 17, pp. 99-105. [DOI: https://dx.doi.org/10.1007/s00787-008-1011-2]
67. Ravens-Sieberer, U.; Erhart, M.; Torsheim, T.; Hetland, J.; Freeman, J.; Danielson, M.; Thomas, C. The HBSC Positive Health Group. An international scoring system for self-reported health complaints in adolescents. Eur. J. Public Health; 2008; 18, pp. 294-299. [DOI: https://dx.doi.org/10.1093/eurpub/ckn001]
68. Gariepy, G.; McKinnon, B.; Sentenac, M.; Elgar, F.J. Validity and Reliability of a Brief Symptom Checklist to Measure Psychological Health in School-Aged Children. Child Indic. Res.; 2016; 9, pp. 471-484. [DOI: https://dx.doi.org/10.1007/s12187-015-9326-2]
69. Heinz, A.; Sischka, P.E.; Catunda, C.; Cosma, A.; García-Moya, I.; Lyyra, N.; Kaman, A.; Ravens-Sieberer, U.; Pickett, W. Item response theory and differential test functioning analysis of the HBSC-Symptom-Checklist across 46 countries. BMC Med. Res. Methodol.; 2022; 22, 253. [DOI: https://dx.doi.org/10.1186/s12874-022-01698-3]
70. Petanidou, D.; Giannakopoulos, G.; Tzavara, C.; Dimitrakaki, C.; Kolaitis, G.; Tountas, Y. Adolescents’ multiple, recurrent subjective health complaints: Investigating associations with emotional/behavioural difficulties in a cross-sectional, school-based study. Child Adolesc. Psychiatry Ment. Health; 2014; 8, 3. [DOI: https://dx.doi.org/10.1186/1753-2000-8-3]
71. Haugland, S.; Wold, B.; Stevenson, J.; Aaroe, L.E.; Woynarowska, B. Subjective health complaints in adolescence: A cross-national comparison of prevalence and dimensionality. Eur. J. Public Health; 2001; 11, pp. 4-10. [DOI: https://dx.doi.org/10.1093/eurpub/11.1.4] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/11276570]
72. Cosma, A.; Stevens, G.; Martin, G.; Duinhof, E.L.; Walsh, S.D.; Garcia-Moya, I.; Költő, A.; Gobina, I.; Canale, N.; Catunda, C. et al. Cross-National Time Trends in Adolescent Mental Well-Being from 2002 to 2018 and the Explanatory Role of Schoolwork Pressure. J. Adolesc. Health; 2020; 66, pp. S50-S58. [DOI: https://dx.doi.org/10.1016/j.jadohealth.2020.02.010] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32446609]
73. Richter, F.; Strauss, B.; Braehler, E.; Adametz, L.; Berger, U. Screening disordered eating in a representative sample of the German population: Usefulness and psychometric properties of the German SCOFF questionnaire. Eat. Behav.; 2017; 25, pp. 81-88. [DOI: https://dx.doi.org/10.1016/j.eatbeh.2016.06.022] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/27354266]
74. Berger, U.; Wick, K.; Hölling, H.; Schlack, R.; Bormann, B.; Brix, C.; Sowa, M.; Schwartze, D.; Straub, B. Screening of disordered eating in 12-Year-old girls and boys: Psychometric analysis of the German versions of SCOFF and EAT-26. Psychother. Psychosom. Med. Psychol.; 2011; 61, pp. 311-318. [DOI: https://dx.doi.org/10.1055/s-0031-1271786] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/21432746]
75. Cellini, N.; Canale, N.; Mioni, G.; Costa, S. Changes in sleep pattern, sense of time and digital media use during COVID-19 lockdown in Italy. J. Sleep Res.; 2020; 29, e13074. [DOI: https://dx.doi.org/10.1111/jsr.13074]
76. Becker, S.P.; Gregory, A.M. Editorial Perspective: Perils and promise for child and adolescent sleep and associated psychopathology during the COVID-19 pandemic. J. Child Psychol. Psychiatry; 2020; 61, pp. 757-759. [DOI: https://dx.doi.org/10.1111/jcpp.13278]
77. Gruber, R.; Saha, S.; Somerville, G.; Boursier, J.; Wise, M.S. The impact of COVID-19 related school shutdown on sleep in adolescents: A natural experiment. Sleep Med.; 2020; 76, pp. 33-35. [DOI: https://dx.doi.org/10.1016/j.sleep.2020.09.015]
78. Ammar, A.; Brach, M.; Trabelsi, K.; Chtourou, H.; Boukhris, O.; Masmoudi, L.; Bouaziz, B.; Bentlage, E.; How, D.; Ahmed, M. et al. Effects of COVID-19 Home Confinement on Eating Behaviour and Physical Activity: Results of the ECLB-COVID19 International Online Survey. Nutrients; 2020; 12, 1583. [DOI: https://dx.doi.org/10.3390/nu12061583]
79. Solmi, F.; Hatch, S.L.; Hotopf, M.; Treasure, J.; Micali, N. Validation of the SCOFF questionnaire for eating disorders in a multiethnic general population sample. Int. J. Eat. Disord.; 2015; 48, pp. 312-316. [DOI: https://dx.doi.org/10.1002/eat.22373]
80. Neuhauser, H.; Schienkiewitz, A.; Schaffrath Rosario, A.; Dortschy, R.; Kurth, B. Referenzperzentile für 755 Anthropometrische Maßzahlen und Blutdruck aus der Studie zur Gesundheit von Kindern und Jugendlichen in Deutschland (KiGGS); Robert Koch-Institut: Berlin, Germany, 2013; Available online: https://edoc.rki.de/bitstream/handle/176904/3254/28jWMa04ZjppM.pdf?sequence=1&isAllowed=y (accessed on 26 September 2024).
81. Mayring, P. Qualitative Inhaltsanalyse. Handbuch Qualitative Forschung in der Psychologie; Mey, G.; Mruck, K. VS Verlag für Sozialwissenschaften: Wiesbaden, Germany, 2010; pp. 601-613. [DOI: https://dx.doi.org/10.1007/978-3-531-92052-8_42]
82. Wasserstein, R.L.; Lazar, N.A. The ASA Statement on p-Values: Context, Process, and Purpose. Am. Stat.; 2016; 70, pp. 129-133. [DOI: https://dx.doi.org/10.1080/00031305.2016.1154108]
83. Stang, A.; Poole, C.; Kuss, O. The ongoing tyranny of statistical significance testing in biomedical research. Eur. J. Epidemiol.; 2010; 25, pp. 225-230. [DOI: https://dx.doi.org/10.1007/s10654-010-9440-x] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/20339903]
84. Ravens-Sieberer, U.; Kaman, A.; Erhart, M.; Devine, J.; Schlack, R.; Otto, C. Impact of the COVID-19 pandemic on quality of life and mental health in children and adolescents in Germany. Eur. Child Adolesc. Psychiatry; 2021; 31, pp. 879-889. [DOI: https://dx.doi.org/10.1007/s00787-021-01726-5] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33492480]
85. Kästner, A.; Lücker, P.; Hannich, A.; Schmeyers, L.; Lücker, J.; Hoffmann, W. COVID-19-related future anxiety is associated with the health-related quality of life in school-aged children and adolescents—A cross-sectional study. Front. Public Health; 2022; 10, 1003876. [DOI: https://dx.doi.org/10.3389/fpubh.2022.1003876] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/36438295]
86. Ärzteblatt DÄG Redaktion Deutsches. Zwei Jahre Pandemie: Die Psychische Gesundheit und Lebensqualität von Kindern und Jugendlichen—Ergebnisse der COPSY-Längsschnittstudie. Available online: https://www.aerzteblatt.de/archiv/229355/Zwei-Jahre-Pandemie-Die-psychische-Gesundheit-und-Lebensqualitaet-von-Kindern-und-Jugendlichen-Ergebnisse-der-COPSY-Laengsschnittstudie (accessed on 18 May 2023).
87. Becker, A.; Rothenberger, A.; Sohn, A.; Ravens-Sieberer, U.; Klasen, F. the BELLA Study Group. Six years ahead: A longitudinal analysis regarding course and predictive value of the Strengths and Difficulties Questionnaire (SDQ) in children and adolescents. Eur. Child Adolesc. Psychiatry; 2015; 24, pp. 715-725. [DOI: https://dx.doi.org/10.1007/s00787-014-0640-x]
88. Ravens-Sieberer, U.; Otto, C.; Kriston, L.; Rothenberger, A.; Döpfner, M.; Herpertz-Dahlmann, B.; Barkmann, C.; Schön, G.; Hölling, H.; Schulte-Markwort, M. et al. The longitudinal BELLA study: Design, methods and first results on the course of mental health problems. Eur. Child Adolesc. Psychiatry; 2015; 24, pp. 651-663. [DOI: https://dx.doi.org/10.1007/s00787-014-0638-4]
89. Otto, C.; Reiss, F.; Voss, C.; Wüstner, A.; Meyrose, A.-K.; Hölling, H.; Ravens-Sieberer, U. Mental health and well-being from childhood to adulthood: Design, methods and results of the 11-year follow-up of the BELLA study. Eur. Child Adolesc. Psychiatry; 2020; 30, pp. 1559-1577. [DOI: https://dx.doi.org/10.1007/s00787-020-01630-4]
90. Ravens-Sieberer, U.; Devine, J.; Napp, A.-K.; Kaman, A.; Saftig, L.; Gilbert, M.; Reiß, F.; Löffler, C.; Simon, A.M.; Hurrelmann, K. et al. Three years into the pandemic: Results of the longitudinal German COPSY study on youth mental health and health-related quality of life. Front. Public Health; 2023; 11, 1129073. [DOI: https://dx.doi.org/10.3389/fpubh.2023.1129073]
91. Ravens-Sieberer, U.; Wille, N.; Bettge, S.; Erhart, M. Psychische Gesundheit von Kindern und Jugendlichen in Deutschland: Ergebnisse aus der BELLA-Studie im Kinder- und Jugendgesundheitssurvey (KiGGS). Bundesgesundheitsbl.—Gesundheitsforsch.—Gesundheitsschutz; 2007; 50, pp. 871-878. [DOI: https://dx.doi.org/10.1007/s00103-007-0250-6]
92. Wang, S.; Chen, L.; Ran, H.; Che, Y.; Fang, D.; Sun, H.; Peng, J.; Liang, X.; Xiao, Y. Depression and anxiety among children and adolescents pre and post COVID-19: A comparative meta-analysis. Front. Psychiatry; 2022; 13, 917552. [DOI: https://dx.doi.org/10.3389/fpsyt.2022.917552]
93. Theberath, M.; Bauer, D.; Chen, W.; Salinas, M.; Mohabbat, A.B.; Yang, J.; Chon, T.Y.; Bauer, B.A.; Wahner-Roedler, D.L. Effects of COVID-19 pandemic on mental health of children and adolescents: A systematic review of survey studies. SAGE Open Med.; 2022; 10, 20503121221086712. [DOI: https://dx.doi.org/10.1177/20503121221086712]
94. Kleine, R.; Galimov, A.; Hanewinkel, R.; Unger, J.; Sussman, S.; Hansen, J. Impact of the COVID-19 pandemic on young people with and without pre-existing mental health problems. Sci. Rep.; 2023; 13, 6111. [DOI: https://dx.doi.org/10.1038/s41598-023-32918-5]
95. Oliva, S.; Russo, G.; Gili, R.; Russo, L.; Di Mauro, A.; Spagnoli, A.; Alunni Fegatelli, D.; Romani, M.; Costa, A.; Veraldi, S. et al. Risks and Protective Factors Associated With Mental Health Symptoms During COVID-19 Home Confinement in Italian Children and Adolescents: The #Understandingkids Study. Front. Pediatr.; 2021; 9, 664702. [DOI: https://dx.doi.org/10.3389/fped.2021.664702]
96. Panda, P.K.; Gupta, J.; Chowdhury, S.R.; Kumar, R.; Meena, A.K.; Madaan, P.; Sharawat, I.K.; Gulati, S. Psychological and Behavioral Impact of Lockdown and Quarantine Measures for COVID-19 Pandemic on Children, Adolescents and Caregivers: A Systematic Review and Meta-Analysis. J. Trop. Pediatr.; 2020; 67, fmaa122. [DOI: https://dx.doi.org/10.1093/tropej/fmaa122]
97. Qualter, P.; Brown, S.L.; Munn, P.; Rotenberg, K.J. Childhood loneliness as a predictor of adolescent depressive symptoms: An 8-year longitudinal study. Eur. Child Adolesc. Psychiatry; 2010; 19, pp. 493-501. [DOI: https://dx.doi.org/10.1007/s00787-009-0059-y]
98. Maes, M.; Nelemans, S.A.; Danneel, S.; Fernández-Castilla, B.; Van den Noortgate, W.; Goossens, L.; Vanhalst, J. Loneliness and social anxiety across childhood and adolescence: Multilevel meta-analyses of cross-sectional and longitudinal associations. Dev. Psychol.; 2019; 55, pp. 1548-1565. [DOI: https://dx.doi.org/10.1037/dev0000719]
99. Marquez, J.; Katsantonis, I.; Sellers, R.; Knies, G. Life satisfaction and mental health from age 17 to 21 years in a general population sample. Curr. Psychol.; 2022; 42, pp. 27047-27057. [DOI: https://dx.doi.org/10.1007/s12144-022-03685-9]
100. Zisook, S.; Lesser, I.; Stewart, J.W.; Wisniewski, S.R.; Balasubramani, G.K.; Fava, M.; Gilmer, W.S.; Dresselhaus, T.R.; Thase, M.E.; Nierenberg, A.A. et al. Effect of Age at Onset on the Course of Major Depressive Disorder. Am. J. Psychiatry; 2007; 164, pp. 1539-1546. [DOI: https://dx.doi.org/10.1176/appi.ajp.2007.06101757]
101. Svedberg, P.; Eriksson, M.; Boman, E. Associations between scores of psychosomatic health symptoms and health-related quality of life in children and adolescents. Health Qual. Life Outcomes; 2013; 11, 176. [DOI: https://dx.doi.org/10.1186/1477-7525-11-176]
102. Martinsen, K.D.; Neumer, S.-P.; Holen, S.; Waaktaar, T.; Sund, A.M.; Kendall, P.C. Self-reported quality of life and self-esteem in sad and anxious school children. BMC Psychol.; 2016; 4, 45. [DOI: https://dx.doi.org/10.1186/s40359-016-0153-0]
103. Kenny, B.; Bowe, S.J.; Taylor, C.B.; Moodie, M.; Brown, V.; Hoban, E.; Williams, J. Longitudinal relationships between sub-clinical depression, sub-clinical eating disorders and health-related quality of life in early adolescence. Int. J. Eat. Disord.; 2023; 56, pp. 1114-1124. [DOI: https://dx.doi.org/10.1002/eat.23928]
104. Bettge, S.; Wille, N.; Barkmann, C.; Schulte-Markwort, M.; Ravens-Sieberer, U. the BELLA Study Group. Depressive symptoms of children and adolescents in a German representative sample: Results of the BELLA study. Eur. Child Adolesc. Psychiatry; 2008; 17, pp. 71-81. [DOI: https://dx.doi.org/10.1007/s00787-008-1008-x] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/19132306]
105. Nik-Azin, A.; Shairi, M.R.; Naeinian, M.R.; Sadeghpour, A. The Health-Related Quality of Life Index KIDSCREEN-10: Confirmatory Factor Analysis, Convergent Validity and Reliability in a Sample of Iranian Students. Child Indic. Res.; 2014; 7, pp. 407-420. [DOI: https://dx.doi.org/10.1007/s12187-013-9216-4]
106. Ravens-Sieberer, U.; Erhart, M.; Rajmil, L.; Herdman, M.; Auquier, P.; Bruil, J.; Power, M.; Duer, W.; Abel, T.; Czemy, L. et al. Reliability, construct and criterion validity of the KIDSCREEN-10 score: A short measure for children and adolescents’ well-being and health-related quality of life. Qual. Life Res.; 2010; 19, pp. 1487-1500. [DOI: https://dx.doi.org/10.1007/s11136-010-9706-5]
107. Kelly, C.; Molcho, M.; Doyle, P.; Gabhainn, S.N. Psychosomatic symptoms among schoolchildren. Int. J. Adolesc. Med. Health; 2010; 22, pp. 229-236. [DOI: https://dx.doi.org/10.1515/IJAMH.2010.22.2.229]
108. Shamsah, A.; Aburezq, M.; Abdullah, Z.; Khamissi, F.; Almaateeq, B.; AlAlban, F.; Almashmoom, S.; Ziyab, A. General health status and psychological impact of COVID19 pandemic and curfew on children aging 3 to 12 years. Front. Child Adolesc. Psychiatry; 2022; 1, 1034492. [DOI: https://dx.doi.org/10.3389/frcha.2022.1034492]
109. Dönmez, Y.E.; Uçur, Ö. Frequency of Anxiety, Depression, and Irritability Symptoms in Children during the COVID-19 Outbreak and Potential Risk Factors Associated with These Symptoms. J. Nerv. Ment. Dis.; 2021; 209, pp. 727-733. [DOI: https://dx.doi.org/10.1097/NMD.0000000000001364]
110. Al-Rahamneh, H.; Arafa, L.; Al Orani, A.; Baqleh, R. Long-Term Psychological Effects of COVID-19 Pandemic on Children in Jordan. Int. J. Environ. Res. Public Health; 2021; 18, 7795. [DOI: https://dx.doi.org/10.3390/ijerph18157795]
111. Sherwood, S.N.; Youngstrom, J.K.; Findling, R.L.; Youngstrom, E.A.; Freeman, A.J. Irritability Is Associated with Illness Severity and Anhedonia Is Associated with Functional Impairment among Depressed Children and Adolescents. J. Child Adolesc. Psychopharmacol.; 2021; 31, pp. 531-537. [DOI: https://dx.doi.org/10.1089/cap.2021.0018]
112. Breda, M.; Ardizzone, I. Irritability in developmental age: A narrative review of a dimension crossing paediatric psychopathology. Aust. N. Z. J. Psychiatry; 2021; 55, pp. 1039-1048. [DOI: https://dx.doi.org/10.1177/00048674211011245]
113. Grigorian, K.; Östberg, V.; Raninen, J.; Åhlén, J.; Brolin Låftman, S. Prospective associations between psychosomatic complaints in adolescence and depression and anxiety symptoms in young adulthood: A Swedish national cohort study. SSM—Popul. Health; 2023; 24, 101509. [DOI: https://dx.doi.org/10.1016/j.ssmph.2023.101509]
114. Malinauskiene, V.; Malinauskas, R. Predictors of Adolescent Depressive Symptoms. Int. J. Environ. Res. Public Health; 2021; 18, 4508. [DOI: https://dx.doi.org/10.3390/ijerph18094508] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33922778]
115. Richardson, C.; Phillips, S.; Paslakis, G. One year in: The impact of the COVID-19 pandemic on help-seeking behaviors among youth experiencing eating disorders and their caregivers. Psychiatry Res.; 2021; 306, 114263. [DOI: https://dx.doi.org/10.1016/j.psychres.2021.114263] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/34758404]
116. Swanson, S.A.; Crow, S.J.; Le Grange, D.; Swendsen, J.; Merikangas, K.R. Prevalence and Correlates of Eating Disorders in Adolescents. Arch. Gen. Psychiatry; 2011; 68, pp. 714-723. [DOI: https://dx.doi.org/10.1001/archgenpsychiatry.2011.22] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/21383252]
117. Hudson, J.I.; Hiripi, E.; Pope, H.G.; Kessler, R.C. The Prevalence and Correlates of Eating Disorders in the National Comorbidity Survey Replication. Biol. Psychiatry; 2007; 61, pp. 348-358. [DOI: https://dx.doi.org/10.1016/j.biopsych.2006.03.040]
118. Robinson, L.; Zhang, Z.; Jia, T.; Bobou, M.; Roach, A.; Campbell, I.; Irish, M.; Quinlan, E.B.; Tay, N.; Barker, E.D. et al. Association of Genetic and Phenotypic Assessments with Onset of Disordered Eating Behaviors and Comorbid Mental Health Problems Among Adolescents. JAMA Netw. Open; 2020; 3, e2026874. [DOI: https://dx.doi.org/10.1001/jamanetworkopen.2020.26874]
119. Herpertz-Dahlmann, B.; Dempfle, A.; Konrad, K.; Klasen, F.; Ravens-Sieberer, U. the BELLA Study Group. Eating disorder symptoms do not just disappear: The implications of adolescent eating-disordered behaviour for body weight and mental health in young adulthood. Eur. Child Adolesc. Psychiatry; 2015; 24, pp. 675-684. [DOI: https://dx.doi.org/10.1007/s00787-014-0610-3]
120. Herpertz-Dahlmann, B.; Wille, N.; Hölling, H.; Vloet, T.D.; Ravens-Sieberer, U. the BELLA Study Group. Disordered eating behaviour and attitudes, associated psychopathology and health-related quality of life: Results of the BELLA study. Eur. Child Adolesc. Psychiatry; 2008; 17, pp. 82-91. [DOI: https://dx.doi.org/10.1007/s00787-008-1009-9]
121. Katzman, D.K. The COVID-19 Pandemic and Eating Disorders: A Wake-Up Call for the Future of Eating Disorders Among Adolescents and Young Adults. J. Adolesc. Health; 2021; 69, pp. 535-537. [DOI: https://dx.doi.org/10.1016/j.jadohealth.2021.07.014]
122. Rodgers, R.F.; Lombardo, C.; Cerolini, S.; Franko, D.L.; Omori, M.; Fuller-Tyszkiewicz, M.; Linardon, J.; Courtet, P.; Guillaume, S. The impact of the COVID-19 pandemic on eating disorder risk and symptoms. Int. J. Eat. Disord.; 2020; 53, pp. 1166-1170. [DOI: https://dx.doi.org/10.1002/eat.23318]
123. Lin, J.A.; Hartman-Munick, S.M.; Kells, M.R.; Milliren, C.E.; Slater, W.A.; Woods, E.R.; Forman, S.F.; Richmond, T.K. The Impact of the COVID-19 Pandemic on the Number of Adolescents/Young Adults Seeking Eating Disorder-Related Care. J. Adolesc. Health; 2021; 69, pp. 660-663. [DOI: https://dx.doi.org/10.1016/j.jadohealth.2021.05.019]
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Abstract
The aim of this study was to assess the mental health situation of children and adolescents during a period of less strict COVID-19-pandemic-related measures after the first pandemic wave. This cross-sectional study was conducted in July 2021 by carrying out an online survey among children and adolescents (aged 10–18 years) from Halle (Saale), Germany (n = 233). The questionnaire measured important aspects of mental health among young people, namely health-related quality of life (HRQoL, using the self-report version of the KIDSCREEN-10), mental health problems in general (using the SDQ), depressive symptoms (using the CES-DC), and psychosomatic complaints (using the HBSC symptom checklist). In addition, other important health issues such as sleep behavior and related difficulties, disordered eating, and any positive consequences of the pandemic were addressed. The results were analyzed using descriptive statistics. A total of 223 children participated in the survey. About 69.7% of the participating children and adolescents had a high HRQoL, while 10.5% displayed abnormal results on the SDQ. There were indications of emotional problems in 16.5% of the participants based on the SDQ subscales. Almost 44% of the participants were screened as positive for depressive symptoms on the CES-DC, with girls and older adolescents being more likely to be affected. This also applied for psychosomatic complaints. Here, irritability was experienced at least once a week or more frequently by 58.9% of the children and adolescents. Although we had a small sample size, this study showed a high prevalence of mental health problems regarding the SDQ and HRQoL. However, our study population showed a better mental health than comparable studies conducted earlier in the pandemic. Depressive symptoms were still substantially higher than those in pre-pandemic data. We hypothesize that this might reflect the fact that there were a few COVID-19-related restrictions at the time when our survey took place. Based on these findings, we assume that the mental health of children and adolescents differed between different phases in the pandemic.
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
Details
; Binder, Mascha 2 ; Diexer, Sophie 1
; Frese, Thomas 3 ; Gekle, Michael 4 ; Girndt, Matthias 5
; Gottschick, Cornelia 1
; Hoell, Jessica 6 ; Klee, Bianca 1
; Kreilinger, Katharina 6 ; Moor, Irene 7
; Rosendahl, Jonas 8
; Sedding, Daniel 9 ; Jan-Henning Klusmann 10 ; Mikolajczyk, Rafael 11
; Raberger, Katja 6 1 Institute for Medical Epidemiology, Biometrics and Informatics (IMEBI), Interdisciplinary Center for Health Sciences, Medical School of the Martin Luther University Halle-Wittenberg, 06097 Halle, Germany
2 Department of Internal Medicine IV, Oncology/Haematology, Martin Luther University Halle-Wittenberg, 06120 Halle, Germany
3 Institute of General Practice and Family Medicine, Interdisciplinary Center for Health Sciences, Medical Faculty of the Martin Luther University Halle-Wittenberg, 06112 Halle, Germany
4 Julius-Bernstein-Institute of Physiology, Medical Faculty of the Martin Luther University Halle-Wittenberg, 06112 Halle, Germany
5 Department of Internal Medicine II, Martin Luther University Halle-Wittenberg, 06120 Halle, Germany
6 Department of Pediatrics I, University Hospital, Martin Luther University Halle-Wittenberg, 06120 Halle, Germany
7 Institute for Medical Sociology, Martin Luther University Halle-Wittenberg, 06112 Halle, Germany
8 Department of Internal Medicine I, Martin Luther University Halle-Wittenberg, 06120 Halle, Germany
9 Department of Cardiology and Intensive Care Medicine, Mid-German Heart Center, Martin Luther University Halle-Wittenberg, 06120 Halle, Germany
10 Department of Pediatrics, Goethe University Frankfurt, 60596 Frankfurt, Germany
11 Institute for Medical Epidemiology, Biometrics and Informatics (IMEBI), Interdisciplinary Center for Health Sciences, Medical School of the Martin Luther University Halle-Wittenberg, 06097 Halle, Germany; German Center for Mental Health, Site Jena-Magdeburg-Halle, 07743 Jena, Germany