1. Introduction
During the COVID-19 pandemic, schools in Germany canceled in-person teaching in March 2020. The lockdown was eased systematically following the Easter break in April, and, at least since the end of the summer break, schools have completely re-opened. Research has shown the impact of the pandemic situation on children’s and adolescents’ wellbeing and mental health. Although the research base is small for students with special educational needs (SEN) in the area of emotional and behavioral disorders (E/BD), the negative impacts of school closures can also be assumed for them.
1.1. Special Educational Needs and Emotional and Behavioral Disorders
Since the current study was conducted in Germany, it is important to introduce the terminology used for SEN and E/BD. According to the
Standing Conference of the Ministers of Education and Cultural Affairs of the Länder in the Federal Republic of Germany [Kultusministerkonferenz], which is responsible for coordinating the school system across the sixteen federal states in Germany, SEN students are defined as children and young people who either have disabilities or face the threat of disablement (
Kultusministerkonferenz 2019, p. 251). SEN is used as an administrational category to allocate and legitimize resources for individualized remedial support or special accommodations, either in regular classrooms or in special schools. Since there are no general guidelines for SEN diagnoses across Germany, regulations for diagnosing SEN (and therefore the number of SEN students) vary across the federal states (
Scheer and Melzer 2020).
The term “special educational needs in emotional and behavioral disorders” (SEN-E/BD) describes “a particularly severe education problem caused by particularly pronounced emotional-social developmental and behavioral disorder or characterized by an accumulation of severe risk factors for development” (
Blumenthal et al. 2020, pp. 12–13). Following this definition, SEN-E/BD refers to the international term of emotional and behavioral disorders (E/BD) (see
Forness and Kavale 2000), which differentiates between externalizing problems (EP; for example, aggressive behavior, defiant and oppositional behavior, and hyperactivity) and internalizing problems (IP; for example, anxiety disorders or depression).
In the school year 2018–2019, 1.3% of all students in Germany were diagnosed as SEN-E/BD, and 0.56% of all students were attending a special school for SEN-E/BD (
Scheer and Melzer 2020). Whereas, studies on child and adolescent mental health indicated a prevalence of E/BD between 16% and 21% (
Baumgarten et al. 2018).
1.2. Effects of the Pandemic Situation on Children and Adolescents
In a rapid umbrella review of several previous reports,
Baumann (
2020) summarized evidence of mental health and psychosocial problems among children and adolescents due to quarantine measures during the pandemic (
Brooks et al. 2020;
Graber et al. 2020;
Henssler et al. 2020;
Hossain et al. 2020;
Imran et al. 2020;
Röhr et al. 2020;
Sharan and Rajhans 2020). The consequences of quarantine measures seemed to correspond with the socioeconomic situation of families. Although quarantine conditions are stricter than Germany’s overall lockdown measures, the latter may have similar effects (
Chawla et al. 2021;
Lee 2020;
Sharma et al. 2020;
Ron and Cuéllar-Flores 2020;
Singh et al. 2020). Despite acknowledging the possible negative effects of school lockdowns on mental health,
Chawla et al. (
2021) assumed that the lockdown could mean an absence of bullying or school pressure for SEN students; thus, it might have a somewhat positive effect on their psychological wellbeing. It was found that parental stress during the lockdown may be transferred to children, where the lockdown situation might induce higher in-family violence, emotional neglect, or isolation (
Clemens et al. 2020;
Fontanesi et al. 2020;
Mechili et al. 2021;
Spinelli et al. 2020). This further underpins the assumption of the pandemic’s negative impact on child wellbeing. Furthermore, the pandemic challenged the system of public child welfare. Moreover, although child welfare practitioners appear to have adjusted to the new situation, the long-term effects of the lockdown on the public child welfare system remain unknown (
Baginsky and Manthorpe 2021;
Jentsch and Schnock 2020).
Empirical research shows that the pandemic induced higher psychological and mental health issues for students (
Chen et al. 2020;
Idoiaga Mondragon et al. 2021;
Ravens-Sieberer et al. 2020,
2021;
Xie et al. 2020;
Langmeyer et al. 2020;
Pearcey et al. 2020). Although
Pearcey et al. (
2020) reported an increase in primary school-aged children’s emotional, behavioral, and attentional challenges from a parent-carer perspective, they found a reduction in such problems for secondary school-aged children or adolescents and those with SEN or pre-existing mental health issues. Further, they found no changes regarding adolescents’ self-reported difficulties, whereas, an increase in behavioral difficulties was reported for high-income households.
Langmeyer et al. (
2020) found that about a third of parents reported problems in coping with the lockdown, which was correlated with conflicts and chaos within the family. They also found that more children seemed to suffer from loneliness in low-income households. However, according to
Langmeyer et al. (
2020), children’s constant or frequent contact with teachers or kindergarten educators had a protective effect on their mental health.
Research on schooling during the lockdown in Germany shows that distance teaching and learning, and parental support for learning, were challenging for all those involved (
Huber et al. 2020;
Wacker et al. 2020;
Wildemann and Hosenfeld 2020). Although students acknowledged more flexibility and individualization of learning, they also lacked communication with and feedback from teachers (
Wacker et al. 2020). Children and adolescents with lower socio-economic status faced greater challenges with distance learning or homeschooling (
Wildemann and Hosenfeld 2020).
Casale et al. (
2020a) found that most German federal states had no further regulations and documentation about the continuation of special education services for SEN students during the school lockdown. In an online survey, SEN teachers analyzed the actual implementation of and obstacles and conditions for SEN support and digital learning during the school lockdown (
Börnert-Ringleb et al. 2021;
Casale et al. 2020b).
However, from an international and German perspective, prior studies present insufficient empirical evidence on (1) the specific effects of the pandemic school lockdown on SEN students with emotional and behavioral disorders (E/BDs) and (2) predictors for such effects from the teachers’ perspective.
3. Methods
3.1. Procedure
The present study employed a retrospective cross-sectional design to investigate teachers’ perceptions of changes in students’ E/BD. Teachers from across Germany were invited to participate in an online survey. The invitation was advertised on social media (Twitter and Facebook), mailing lists of teacher associations and unions, and press releases. Two federal states (Baden-Wuerttemberg and Rhineland-Palatinate) gave explicit permission to contact schools officially. The survey was conducted using LimeSurvey Version 3.17.16 (
LimeSurvey 2019), and hosted by the second author’s university. Before the survey, participants were provided information about the study to grant conclusive informed consent for participation. Therefore, given the ad-hoc sample, we could not determine our sample size a priori.
In the first part of the survey, participants were required to disclose the schools in which they taught, the number of students in each class, and how many students were diagnosed with SEN-E/BD. They were also required to state the number of students they were willing to assess during the survey (two, three, four, or five).
Figure 1 illustrates how scenarios are chosen from the answers provided in this part, which determined the next step for participants and the randomization procedure characteristics. The instructions that participants were given in each of the four scenarios displayed in
Figure 1 can be found in
Appendix A (
Appendix A.1,
Appendix A.2,
Appendix A.3 and
Appendix A.4). The full structure of the survey is provided via OSF as a LimeSurvey structure file (*.lss) and as an Excel spreadsheet to make the procedure replicable.
After completing the questionnaire (measurements described below), participants were asked if they were willing to (a) participate in a repeated survey in case of new lockdowns, and (b) participate in qualitative interviews for further in-depth insights (qualitative interviews with 22 teachers have been conducted in early 2021 and are currently being analyzed).
3.2. Measurements
In this paper, we only report those variables that were included in the data analysis. The full set of variables measured can be obtained from the dataset and its documentation on OSF.
The scale ranges are transformed as per their 0 starting point, except for the retrospective scales which range from −2 to +2 (see
Section 3.2.3). Due to technical reasons, scale ranges (answer codes) in the questionnaire deviate from this structure.
3.2.1. Students’ Sociodemographic Data
Teachers were required to provide students’ gender, grade, age, and living environment conditions. Further, they provided information on any official diagnosis of SEN.
3.2.2. DBR-PUTSIE
To assess students’ internalizing problems (IP), externalizing problems (EP), and positive school-related behavior (P-SRB), we employed the DBR-PUTSIE (
Schurig et al. 2020), a standardized instrument for directly assessing behavior in schools. It is published under a CC BY-NC-SA 4.0 license and is free to use for research purposes. The DBR-PUTSIE is based on well-established instruments, such as the Strengths and Difficulties Questionnaire (SDQ) (
Goodman 2005,
1999), and on the behaviors described by the Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5). Development of the DBR-PUTSIE is strongly related to that of the Direct Behavior Rating and Multi-Item Scales by
Gebhardt et al. (
2018). Thus, we assumed comparable psychometric properties (
Gebhardt et al. 2019). The DBR-PUTSIE covers the three dimensions of EP (oppositional defiant behavior (4 items), inattention (6 items), impulsiveness (6 items)), IP (emotional problems (5 items), peer problems (3 items)), and P-SRB (5 items). The items are rated on a seven-point scale with verbalized endpoints (1 = never, 7 = always).
The DBR-PUTSIE was preferred over the SDQ because a seven-point rating scale is preferable for direct behavior ratings (
Christ et al. 2009). Furthermore, the SDQ is not licensed for online survey use.
The items are displayed in
Appendix B Table A1. We observed acceptable to good internal consistency, with α = 0.85 to 0.95, and a corrected item-total correlation of
rit > 0.5 for all items, with only five items falling below an
rit of 0.6.
3.2.3. Retrospective Ratings
After participants assessed the current state of social/emotional development with the original DBR-PUTSIE instructions, they were asked to assess the current situation relative to the situation before school lockdown on a fully verbalized five-point scale (−2 = much lower than before, −1 = somewhat lower than before, 0 = no change, +1 = somewhat higher than before, +2 = much higher than before). As shown in
Appendix B Table A2, the internal consistency ranged from 0.82 to 0.92. The corrected item-total correlation was slightly lower than for the rating of the current situation, with two items falling below an
rit of 0.5. Four items showed an
rit between 0.5 and 0.6.
3.2.4. Students’ Coping with Distance Learning and Psychosocial Threats during the Lockdown
A scale measuring how students addressed distance learning during school lockdown (“coping with distance learning”, 6 items) was developed following
Huber et al. (
2020). The items were rated on a fully verbalized five-point scale (0 = not true at all, 1 = somewhat not true, 2 = yes and no, 3 = somewhat true, 4 = very true). Along with the scale on students’ coping with distance learning, five items on psychosocial threats were presented to be assessed on the same rating scale.
Table A3 in the
Appendix B indicates acceptable internal consistency for both scales (α = 0.83 and 0.81, respectively). For the scale on coping with distance learning, one item had a poor
rit of 0.256, one item had a good
rit of 0.551, and the other items were all above 0.7. For the scale on psychosocial threats, one item had an
rit = 0.365, while all other items were above 0.6.
3.2.5. Teacher Variables
Using a five-point rating scale (1 = never, 5 = almost always), we asked teachers how often they employed analogue and digital teaching or instruction for distance teaching during the school lockdown. The two questions were taken from the SOLVE-questionnaire (
Casale et al. 2020b) in
Börnert-Ringleb et al. (
2021).
Using the SOLVE-questionnaire, we employed a scale to measure the teachers’ perception of their student-teacher relationship following
Pianta et al. (
2008). The scale consists of nine items to be rated on a fully verbalized five-point scale (0 = not true at all, 1 = somewhat not true, 2 = yes and no, 3 = somewhat true, 4 = very true). Since the original scale has yet to be published, we cannot provide the full text of the items here. The internal consistency was acceptable (α = 0.78). Three items showed an
rit < 0.5.
3.3. Data Inclusion and Data Availability
Only complete cases were included in the data analysis. The raw data from LimeSurvey, the final data set used for analysis, and the R input are available via OSF.
3.4. Participants
In total, 94 teachers (28 from primary schools, 37 from secondary schools (including comprehensive schools, academic high schools, and vocational schools), and 29 from special schools) participated in the survey. The average number of students (with SEN-E/BD and total) in the participants’ classes is displayed in
Table 1. From the secondary schools, 2 participants were from a lower secondary school, 3 from a middle secondary school, 6 from an integrated secondary school, 12 from an academic high school, 9 from a comprehensive school, and 5 from a vocational school.
Data were included from 173 (55 female) students, of which 82 (11 female) were officially diagnosed with SEN-E/BD, and 27 (10 female) with other types of SEN.
Table 2 presents a summary of the students’ sociodemographic data. It was observed that students with SEN-E/BD were more likely to be living in foster families or youth welfare facilities than students without SEN-E/BD.
3.5. Data Analysis
Data analyses were performed in the R language (
R Core Team 2020), using the R Studio Environment (
RStudio 2020). Descriptive statistics were analyzed using the describe() and describeBy() commands from the package “psych” (
Revelle 2020).
In the first step of the analysis, we compared social and emotional development, coping with distance learning, and psychosocial threats during lockdown across SEN-E/BD students, other SEN students, and students without SEN. One-way ANOVAs were computed using the lm()-function along with the apa.1way.table()-function from “apaTables” (
Stanley 2018).
Predictors for social and emotional problems and the effect of school lockdown were analyzed using stepwise regression analysis. Hence, we incorporated students’ SEN status as predictors in block one (Step 1). Students’ coping with distance learning and psychosocial threats during lockdown were added in Step 2. Step 3 included the teachers’ perception of the student-teacher relationship. Stepwise regression was conducted for each dependent variable (effects of the lockdown on EP, IP, and P-SRB), using the lm() command from the base functions of R and the apa.reg.table() function from “apaTables”.
5. Discussion
Differences between the three groups in the current situation were to be expected, given the underlying construct of SEN-E/BD presented in prior research (e.g.,
Dasioti and Kolaitis 2018;
DeVries et al. 2018;
Schwab et al. 2016). Furthermore, our results indicate that SEN-E/BD students were confronted with more psychosocial threats during the school lockdown than other students, and had fewer individual resources to cope with distance learning. However, there was no evidence for the severe effects of the school lockdown on social and emotional variables. Moreover, the difference was marginal between SEN-E/BD students, other SEN students, and students without SEN regarding the teacher-rated effects of school lockdown. Hence, further research must focus on a wider variety of factors influencing the effect of school lockdown, instead of focusing exclusively on SEN-E/BD. Since the findings were partly contrary to the self-reported or parent-reported effects of the lockdown situation (
Ravens-Sieberer et al. 2020,
2021;
Langmeyer et al. 2020;
Pearcey et al. 2020), an explanation of these discrepancies has yet to be analyzed. Therefore, several hypotheses might be possible. First, there could be general discrepancies between parent-, self-, and teacher-reports. This situation might be the case for the DBR-PUTSIE, since the SDQ parent- and self-reported scores differed slightly (
Arman et al. 2013), and the SDQ teacher- and parent-reports showed only low to moderate agreement (
Cheng et al. 2018;
Stone et al. 2010). Second, this study analyzed the situation after the school lockdown period, while other studies (
Ravens-Sieberer et al. 2020,
2021;
Langmeyer et al. 2020) analyzed the situation during the lockdown. Third,
Langmeyer et al. (
2020) did not compare their results to the situation before the lockdown, and
Ravens-Sieberer et al. (
2020;
2021) based their comparison on neither retrospective data nor longitudinal data but on a comparison of their cross-sectional data with data from prior cross-sectional studies. Fourth, as these studies (
Ravens-Sieberer et al. 2020,
2021;
Langmeyer et al. 2020) mostly considered children and adolescents without addressing SEN, the finding that the lockdown had only mild effects for SEN students is consistent with
Pearcey et al. (
2020) and
Chawla et al. (
2021). Hence, results from several perspectives must be triangulated and completed via in-depth insights from qualitative research.
As expected, the psychosocial threats students faced in their living environment during the lockdown were the most prevalent risk factor for the negative effects of the lockdown on social and emotional problems. Moreover, having the inner resources to master the distance-learning situation was a protective factor for many aspects of social and emotional development. However, the teacher-level predictors did not have the expected effect from a theoretical perspective, and student-teacher relationships had marginal protective effects.
The finding that psychosocial threats during lockdown are a strong predictor for an impact on the social-emotional problems of children and adolescents is consistent with prior findings and research-based assumptions, as mentioned in the introduction (
Clemens et al. 2020;
Fontanesi et al. 2020;
Mechili et al. 2021;
Spinelli et al. 2020). However, according to prior research (
Lee 2012;
Pianta and Stuhlman 2004;
Wanders et al. 2020), the student-teacher relationship scale had a surprisingly small impact. This situation can be explained in two ways. First, psychosocial threats and other student-level predictors might have such an impact that teachers’ student-teacher relationships cannot compensate for them, especially when a lockdown makes the situation more complicated. Second, the student-teacher relationship scale seeks teachers’ perspectives (students’ perspectives might be different).
5.1. Limitations
Several methodical limitations must be considered. First, our sample size was small, with 94 teachers. Furthermore, it was an ad-hoc sample recruited via social media, the local press, and mailing lists. Several factors of teacher variables may confound the willingness to participate in this online survey and their perception of students’ EB/D. Hence, the influence of a selection bias must be considered, which limits the external validity of our findings when addressing students in general. Second, as discussed, the findings employed teachers’ perspectives, which may under- or overestimate emotional problems relative to self- or parent-reports (
Arman et al. 2013;
Cheng et al. 2018;
Stone et al. 2010;
Langmeyer et al. 2020). This also indicates a further limitation that we could not sufficiently collect data on students’ socioeconomic situation and their families’ situations. Third, to evaluate changes in the dependent variables, we used retrospective ratings. Thus, we have no longitudinal data and must consider that a recall bias may influence teachers’ retrospective perceptions. Finally, the adequate psychometric quality of the DBR-PUTSIE was assumed based on findings from similar instruments but was not evaluated for this measurement; however, the PUTSIE-scales demonstrated good reliability in our study (see
Appendix B Table A1 and
Table A2).
Although we were interested in comparing the period before and after school lockdown, we could not distinguish between the effects of the school lockdown and the pandemic. It is reasonable to assume that IP would be affected by several factors related to the pandemic (e.g., the fear of getting infected or losing beloved family members to a fatal COVID-19 infection). Thus, we cannot posit any causal effect of the school lockdown but only the coincidence.
5.2. Conclusions
This study found evidence for marginal effects of the school lockdown on students’ E/BD rather than for severe issues. However, our findings suggest that the psychosocial situation of children and adolescents during the pandemic is a potential risk factor that should be monitored by teachers, school social workers, and school psychologists. Moreover, measures should be taken to strengthen student-teacher relationships even over a distance. Hence, where necessary, opportunities for personal accompaniment and support for students, and even parents, must be provided.
As indicated above, further research is required that triangulates the perspectives of teachers, students, and parents. Additionally, it would be helpful to implement a longitudinal design to evaluate the continuing effects of repeated lockdowns. Further, we gathered qualitative data providing in-depth insights into the teachers’ perspectives in a follow-up inquiry via qualitative interviews. The interviews are currently under preparation for analysis.