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A prospective analysis of the long-term impact of the COVID-19 pandemic on well-being and health care among children with a chronic condition and their families: a study protocol of the KICK-COVID study

BMC Pediatrics volume 23, Article number: 130 (2023) Cite this article

Abstract

Background

There is consistent evidence that the COVID-19 pandemic is associated with an increased psychosocial burden on children and adolescents and their parents. Relatively little is known about its particular impact on high-risk groups with chronic physical health conditions (CCs). Therefore, the primary aim of the study is to analyze the multiple impacts on health care and psychosocial well-being on these children and adolescents and their parents.

Methods

We will implement a two-stage approach. In the first step, parents and their underage children from three German patient registries for diabetes, obesity, and rheumatic diseases, are invited to fill out short questionnaires including questions about corona-specific stressors, the health care situation, and psychosocial well-being. In the next step, a more comprehensive, in-depth online survey is carried out in a smaller subsample.

Discussion

The study will provide insights into the multiple longer-term stressors during the COVID-19 pandemic in families with a child with a CC. The simultaneous consideration of medical and psycho-social endpoints will help to gain a deeper understanding of the complex interactions affecting family functioning, psychological well-being, and health care delivery.

Trial registration

German Clinical Trials Register (DRKS), no. DRKS00027974. Registered on 27th of January 2022.

Peer Review reports

Background

In Germany, around 10% of children and adolescents are affected by a chronic physical health condition, such as obesity, diabetes, or rheumatic disease [1,2,3]. Although children and adolescents seem to be less often and less severely affected by the coronavirus disease 2019 (COVID-19) compared to adults [4,5,6,7,8,9], children and adolescents with a chronic health condition (CC), such as diabetes, obesity, or inflammatory rheumatic disease, are assumed to be at higher risk of a more severe course of an infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [6, 10, 11]. Type 1 diabetes, for instance, ranks among the strongest risk factors for severe illness and hospitalization when infected with the SARS-CoV-2 virus [10], depending on the metabolic control [12], which often deteriorates in adolescence [13, 14]. Also, obesity belongs to the strongest risk factors for hospitalization with the SARS-CoV-2 virus. Various influence factors constitute this risk, most of all chronic inflammation, impaired immune response, and underlying cardiopulmonary disease [15]. Evidence regarding rheumatic diseases or a consequential therapeutically induced immunosuppression as a risk factor for severe infection with the SARS-CoV-2 virus show conflicting results [16,17,18,19]. At the same time, altered daily structure and, therefore, altered health behavior can impair the underlying rheumatic disease or obesity [15, 20]. In addition, these changes result in a higher prevalence of several chronic conditions, such as obesity [21]. Also, for diabetes, an increased prevalence has been observed during the COVID-19 pandemic [22].

Also in times without a pandemic, children and youth with CCs as well as their parents are at increased risk of developing mental health problems, such as anxiety, depression, and impaired health-related quality of life [23,24,25,26,27,28,29]. During the COVID-19 pandemic, children with CCs and their families are confronted with unique challenges in their disease management routines. The federal states in Germany have implemented swift, wide-ranging public health emergency measures that have included a national lockdown with social restrictions (e.g., stay-at-home orders) and quarantines to reduce interpersonal contacts. On March 13, 2020, all federal states in Germany closed kindergartens and schools; nearly all colleges and universities followed. School closures substantially disrupt the lives of children and their families and may have consequences for child health [30,31,32,33,34] and parental well-being [35,36,37,38,39]. In addition, Kindergartens and schools provide an essential source of meals and nutrition, health care, including behavioural health supports, physical activity, social interaction, support for students with special education needs and disabilities, and other vital resources for healthy development [40]. It is important to note that childhood and adolescence are periods of life characterized by heightened sensitivity to social stimuli and the increased need for peer interaction. The physical distancing measures have radically reduced opportunities to engage in social contacts outside of the household. Consequently, social deprivation during this sensible developmental period might have caused far-reaching consequences [41]. In addition, parents may have faced economic insecurity, had to educate their children at home as a substitute for school attendance and had to deal with an uncertain outlook into the future. Working at home and living with preschool-aged children has particularly influenced the extent of mental distress during the pandemic [42, 43]. Therefore, the impact of lockdowns implemented in response to COVID-19 on mental health has raised concerns [44, 45]. There is increasing empirical evidence underpinning the negative effects of the pandemic and the associated containment measures on the psychosocial well-being of children [33, 34, 46] and their parents [38, 39] in the general population. However, so far only few studies focused on the psychosocial situation of children and adolescents with CCs [47, 48]. Given that preexisting mental and physical health problems are associated with higher levels of anxiety and depression during the COVID-19 pandemic [49], it can be assumed that the COVID-19 pandemic represents an additional risk that will be more pronounced among those children and adolescents and their families who are facing preexisting physical, mental or social vulnerabilities [36, 50].

With respect to regular medical care, which is essential for children and adolescents with CCs, there were major changes. During the lockdown, in most medical institutions across the country, routine consultations took place alternatively by telephone or video contact. Socially and educationally disadvantaged populations might face more problems using telehealth services [36]. It is well known that threat appraisals (rating of the subjective vulnerability and severity of a disease risk) affect the adoption of health-protective behaviors and health care use [51]. In childhood, research has shown that in addition to the risk perceptions of the children themselves, parental threat appraisals also influence their intention to engage in preventive or intervention efforts [52, 53]. Reduced access to health care can be detrimental to pediatric health, and children with special needs are potentially at higher risk of severe illness due to a lack of health care than their healthy peers.

Methods

Objectives

Based on a comprehensive understanding of the complex interplay between medical condition, health care use, and environmental and specific context factors in CC (see Fig. 1 [54];), the overarching aim of the so-called KICK-COVID study is to examine the longer-term effects of the COVID-19 pandemic on both medical as well as psychosocial outcomes in children and adolescents with a CC and their families.

Fig. 1
figure 1

Conceptual model of the proposal considering the ICF structure (modified according to Cieza and Stucki [54])

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Based on the biopsychosocial model, the specific study objectives are to examine

  1. 1.

    the impact of the COVID-19 pandemic on the care of children and adolescents with a CC by analyzing deficiencies, interruptions and unmet needs in care and treatment,

  2. 2.

    the impact of the COVID-19 pandemic on body function and clinical outcomes (e.g., disease specific medical endpoints, physical and mental health), activities and participation of children and adolescents with different chronic diseases (diabetes, obesity, and rheumatic disease),

  3. 3.

    the psychosocial resources and risk perceptions of children and their parents facing the Corona pandemic and their influence on child’s psychosocial adjustment, mental and physical health,

  4. 4.

    the interplay of the physical and mental health of the children,

  5. 5.

    the course of physical and mental health over time,

  6. 6.

    the impact of a potential COVID-19 infection on these variables, and

  7. 7.

    disease-specific differences and similarities with respect to the impact of the COVID-19 pandemic.

Study design

The ongoing prospective observational study started recruitment in June 2021. A two-step approach (see Fig. 2) has been implemented: In the first step, additional COVID-19-specific questions have been added to the already existing surveys for the regular check-ups. Parents and adolescents provide data on their own psychosocial situation. In addition, parents assess as proxies the situation of their children under 12 years. Since this assessment is part of a comprehensive medical examination, only short economic instruments can be used in order to prevent exhaustive strain on the families. To get a deeper insight into the relevant psychological processes, a smaller voluntary subsample is asked to fill-in an extended online survey and forward it to their children (> 9 years) as well. After one-year, follow-up assessments will take place.

Fig. 2
figure 2

Illustration of the study design and recruitment process

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Study participants

Parents and their underage children (aged up to 18 years) who are already taking part in any of the three patient registries for diabetes (German Diabetes Prospective Follow-up Registry, DPV [55]), obesity (German Obesity Prospective Follow-up Registry, APV [56]), or rheumatic disease (National Pediatric Rheumatology Database, NPRD [57]) are eligible for inclusion.

Recruitment

Recruitment takes place during the regular check-ups within the participating clinical facilities. Clinicians ask their adolescent patients and their accompanying parents to fill in a two-page short questionnaire during their waiting time; for children younger than 12 years, the questionnaire is only completed by the accompanying parent. After the completed questionnaires are handed over to the treatment team in the healthcare facility, the next step is to ask whether the relatives would also be willing to take part in a further, more extensive survey. If they agree, the families receive a flyer with information and a barcode that leads directly to the online questionnaire. At the end of the questionnaire, consent is obtained from the parents to be contacted again after 1 year. In addition, the parents are asked for parental consent for the participation of the underage child (from about 9 years of age). If the parents agree, the children also receive an online questionnaire at the e-mail address provided and can then fill out the children’s questionnaire themselves. At the end of the respective questionnaires, parents and their children can download quizzes, an audio-guided relaxation training [58], small puzzles and colouring books, or take part in a computer game on risk-taking behavior as an incentive. In order to recruit a high number of eligible participants, it is planned to realize the whole recruitment process over a period of 1 year. The whole recruitment process is depicted in Fig. 3.

Fig. 3
figure 3

Recruitment flow chart

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Study measures

This survey uses several questionnaires and self-constructed items to fulfil the primary study objectives stated above.

Basic survey

An overview of the study measures applied in the basic surveys is given in Table 1.

Table 1 Overview of corona-specific study measures in the basic survey
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Basic survey: Common measures for parents and children

Several measures are administered for the data collection. While parents are asked to fill out the questionnaire for their children under the age of 12, they answer an additional separate questionnaire when their afflicted child is older than 12. The following assessments are identical for the parents of these two age groups.

COVID-19 pandemic-specific impact on well-being and everyday life

Based on experience from a previous study [59], a self-constructed 6-item scale is administered to assess how the COVID-19 pandemic has impacted the well-being of afflicted children and their families in different aspects of their every-day life. Parents are asked to rate the quality of several life domains in light of the COVID-19 pandemic: the care for the child at home, the treatment of the child’s condition, the occupation, the financial situation, and the partnership; with scales ranging from 0 “totally bad” to 10 “totally good”. Furthermore, participants are asked to indicate how stressed they feel due to the COVID-19 pandemic with a scale ranging from 0 “not stressed at all” to 10 “totally stressed”.

Health-related strain

Two self-constructed items [59] are used to assess health-related strain in the light of the COVID-19 pandemic. On two 11-point Likert scales, participants are asked to (i) state how dangerous they consider a COVID-19 infection in their afflicted child, ranging from 0 “totally harmless” to 10 “totally dangerous”, and (ii) rate the intensity of their fear for the child’s health, with 0 indicating “no fear at all” and 10 indicating a very intense fear.

Disease-specific health care use

A total of 10 self-constructed items are implemented to assess the corona-specific utilization of health services in the past 12 months. Parents are asked to provide information about the frequency of disease-specific health care visits; medical appointment cancellations and their causes; and the provision and quality of alternative virtual office hours.

Basic survey: Common measures for children and adolescents

For the questionnaires aiming at the data collection in children under the age of 12 and adolescents aged 12 years or older, the following measures are applied.

Perceived stress

A self-constructed item aims to assess how stressed the child feels because of the COVID-19 pandemic with an 11-point numerical rating scale ranging from 0 “not stressed at all” to 10 “totally stressed”. As described above, for children under the age of 12, the accompanying parent is asked to rate this item for their child.

Perceived loneliness

To measure how lonely a child feels due to the COVID-19 pandemic, a self-constructed item on a Likert scale ranging from 0 to 10 is applied. Older children are asked to select a response ranging from “not stressed at all” to “totally stressed”, and the parents answer this item for younger children.

COVID-19-specific well-being in everyday life

A self-constructed 5-item scale based on Warschburger et al. [59] aims to assess the child’s well-being across several life domains. Children from 12 years are asked to rate the current state of their: family, education/vocational education/occupation, friends, leisure time, and illness. The scales range from 0 “totally bad” to 10 “totally good”. These items are posed to the parents of children when they are younger than 12 years. The German version of the World Health Organization Five Well-Being Index (WHO-5) is additionally administered to measure the current general well-being (e.g., “I was happy and in a good mood”) of children and adolescents during the past 2 weeks [60, 61]. The WHO-5 has a 5-item Likert scale ranging from 0 “at no time” to 5 “all of the time” and has an internal consistency of Cronbach’s α = .89 to Cronbach’s α = .92 [60, 62].

Basic survey: Measures for adolescents

School experience

Two items have been constructed for the purpose of assessing the educational experiences of adolescents during the COVID-19 pandemic. One multiple-choice question aims to assess the teaching method that the students encountered during the last 2 weeks, with possible answers comprising home-schooling, classroom teaching and frequency, holidays, or having finished school. The other item asks, if applicable, how students have succeeded in learning at home, with a Likert scale ranging from 0 “totally badly” to 10 “totally well”.

Perceived risk

The risk perception of adolescents is measured with three self-constructed items [39]. Adolescents are asked to state how dangerous they consider a COVID-19 infection to be for (i) themselves, and (ii) others on an 11-point Likert scale. Furthermore, adolescents indicate (iii) their perceived risk of a coronavirus infection, on a scale ranging from 0 (“totally unlikely”) to 10 (“very likely”).

Media usage

A 5-point Likert scale established by another survey [63, 64] is administered to assess the electronic media usage of teenagers. The adolescents are asked to report how much time they spend on average during the day with watching TV/videos, a gaming console, using the computer/internet, listening to music, their phone; answers range from “not at all” to “more than 4 hours”.

Anxiety

Anxiety symptoms (e.g., not being able to stop or control worrying) during the past 2 weeks are measured with the German version of the General Anxiety Disorder-Scale (GAD-7) [65, 66]. The 4-point Likert scale consisting of seven items ranges from 0 “not at all” to 3 “nearly every day”. The GAD-7 has an internal consistency of Cronbach’s α = .79 to Cronbach’s α = .91 [67] and studies reported a successful usage in adolescents [68, 69].

Depression

To detect depressive symptoms during the past 2 weeks (e.g., feeling down, depressed, or hopeless), the German version of the 9-item Patient Health Questionnaire (PHQ-9) [70] is administered as a screening inventory. The 4-point Likert scale of the PHQ-9 ranges from 0 “not at all” to 3 “nearly every day” and has an internal consistency of Cronbach’s α = .88 [71].

Web-based extended psychosocial survey

In addition to the baseline survey, parents and with their consent also the children (aged > 9 yrs.) are invited to fill a more comprehensive psychosocial web-based survey. Table 2 summarizes the questionnaires used in the parental and child assessment.

Table 2 Overview of study measures in the web-based survey
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Web-based common measures for parents and children

Sociodemographic and medical assessment

Two self-constructed items are implemented asking the participants about their age and gender. The child questionnaire includes a third item assessing the adolescents’ living situation (“Where do you currently live?”), while the parental questionnaire incorporates three additional questions regarding the child’s year of birth, weight and height, and location of their child’s treatment.

Furthermore, items adapted from Warschburger [59] measure CC-specific medical variables. On a 5-point scale, participants are asked to rate the subjective severity, long-term effect of the CC, and impact of the COVID-19 pandemic on the child’s CC. A fourth item, included in the child questionnaire assesses how well the child is coping with the CC in general, with a scale from 0 = “not at all “to 4 = “very well“.

COVID-19-specific questions

COVID-19-specific questions are included to assess the COVID-19 related impact and burden experienced by the participants. Two self-constructed items adapted from Warschburger et al. [59] ask the children and parents to indicate whether they have faced a COVID-19 infection and rate its severity on a 4-point scale ranging from “symptom-free” to “severe”. The parental survey includes 30 additional self-constructed items, assessing, e.g., if their afflicted child suffered from the long-COVID syndrome, or whether they and their child received COVID-19 vaccinations.

Modified items based on Calvano et al. [39] further measure the subjective burden on several areas of everyday life caused by the COVID-19 pandemic, such as the children’s education or the parents’ work. On a 5-point Likert scale, participants are asked to rate how burdensome they experienced COVID-19 with higher ratings indicating a higher burden. In addition, participants are asked to assess what has caused the most stress and anxiety and what has changed positively during the pandemic.

Psychosocial adjustment: Overall well-being

Two picture-based items using the Self-Assessment Manikin [72] are implemented assessing how the parents and children feel in general, and how stressed they are.

Psychosocial adjustment: Loneliness

The 6-item short version of the De-Jong-Gierveld-Skala [73] is administered to measure the children’s and parents’ overall loneliness. Statements relating to social and emotional loneliness are evaluated on a 4-point scale, with higher scores indicating more frequent loneliness. The questionnaire has an internal consistency of Cronbach’s α = .71 to Cronbach’s α = .76 [73].

Psychosocial adjustment: Child behavior

To assess the children’s emotional and behavioral problems during the last 12 months, the Strengths and Difficulties Questionnaire (SDQ) is utilized. On a 3-point Likert scale ranging from 0 “not true” to 2 “certainly true”, children are asked to rate problems relating to the subscales hyperactivity (with Cronbach’s α = .87) and conduct problems (α = .73) [74]. The questionnaire for the parents includes a proxy-report of their children’s emotional symptoms, conduct problems, hyperactivity, and peer problems with Cronbach’s α of .66, .60,.76, and α = .58, respectively [75].

Web-based extended measures for parents

Sociodemographic assessment

The parental socioeconomic status (SES) is measured using the MacArthur Scale [76] and Winkler-Index. The German version of the single-item MacArthur Scale [76] is applied to measure the parental subjective SES. Participants are asked to indicate their social rank on a 10-rung ladder, with the bottom representing people with the lowest education and least money and the top representing people with the highest education and most money. Three items of the Winkler-Index [77] are applied to measure the parent’s socioeconomic status by asking about the highest secondary education, professional degree, and employment status. The family’s SES is derived from an overall score, ranging from 3 to 21.

Psychosocial adjustment

In addition to the measures described above, the extended online survey for parents includes several other questionnaires to measure their psychosocial adjustment. As previously applied in the basic questionnaires, the WHO-5 measures the parents’ overall well-being. Further characteristics of the questionnaire are discussed in section “COVID-19-specific well-being in the everyday life”.

Psychosocial adjustment: Anxiety and depression

To assess parent’s anxiety and depression levels, the German version of the PHQ-4, the short version of the PHQ-9 and GAD-7 used for adolescents in the basic survey, is applied as screening instrument. Four Items are to be rated on a 4-point Likert scale ranging from 0 “not at all” to 3 “nearly every day”. An internal consistency of Cronbach’s α = .82 has been reported [78].

Psychosocial adjustment: Perceived stress

The frequency of distress experienced by the subject will be measured using four items with the German version of the Perceived-Stress Scale (PSS-4). On a 5-point Likert scale, parents are asked to indicate how often they felt stressed during the last year (e.g., “In the last 12 months, how often have you felt difficulties were piling up so high that you could not overcome them?“), with a higher score indicating higher chronic stress. The PSS-4 has an internal consistency of Cronbach’s α = .72 [79].

Psychosocial adjustment: Quality of life

This study applies 13 items of the German version of the Child Health Questionnaire Parent Form (CHQ) to assess the impact of the child’s health on the parental quality of life across several domains. On a 5-point scale, the emotional impact is assessed with 3 items (e.g., “How much emotional worry or concern did each of the following cause for you: your child’s physical health?“), the impact on the family with 6 items (e.g., “How often has your child’s health or behavior limited the types of activities you could do as a family?“), and family cohesion with one item (e.g., “In general, how would you rate your family’s ability to get along with one another?“). On a 4-point Likert scale, 3 items measure the impact of the child’s health on the leisure time (e.g., “Were you limited in the amount of time you had for your own needs because of your child’s emotional well-being?“). The German version of the CHQ reports an internal consistency of Cronbach’s α = .76 for parental emotional impact, and α = .81 for parental time impact. For the family impact subscale, an internal consistency of Cronbach’s α = .83 has been reported [80].

Coping and resources

The following instruments are used to assess the coping strategies and the resources and burdens of the parents:

Coping and resources: Parental disease management

To assess the parental coping style, the German short version of the coping orientation to problems experienced (Brief COPE) inventory [81] will be utilized. The questionnaire consists of 14 subscales with 2 items each, namely, active coping; planning; positive reframing; acceptance; humour; religion; emotional support; instrumental support; self-distraction; denial; venting; substance use; behavioural disengagement; and self-blame. Each subscale is represented by two items, measured on a four-point Likert scale ranging from “not at all “to “very much“. Higher scores indicate a greater use of the respective coping style. All scales reached Cronbach’s alpha α > .60.

Coping and resources: Self-efficacy

The German version of the General self-efficacy scale (in German: Allgemeine Selbstwirksamkeitsskala (ASKU)) [82] is applied to measure the parental expectations of being competent to deal with daily difficulties and obstacles. The inventory consists of 3 items (e.g., “I can rely on my own abilities in difficult situations“), answered on a 5-point scale ranging from 0 = “doesn’t apply at all” to 4 = “applies completely”. Findings indicate a good reliability of McDonalds’s omega = .81 to .86 [82].

Coping and resources: Locus of control

Measuring the internal and external sense of control, a four-item scale for the assessment of locus of control (In German: Internale-Externale-Kontrollüberzeugung-4 (IE-4)) [83] is administered. Parents are asked to rate the items (e.g., “If I work hard, I will succeed“) on a 5-point Likert scale ranging from 0 = “doesn’t apply at all” to 4 = “applies completely”. The IE-4 has a McDonalds Omega of .53 to .71 [84].

Coping and resources: Social support

The 3-item OSLO social support scale (OSS-3) is implemented to measure the level of social support that parents perceive. The questions assess how many close confidents parents have, the amount of concern they receive from others, and how accessible practical help is from their neighbours. The sum score of 3-8 is categorized as poor social support, from 9 to 11 as moderate social support, and 12-14 as strong social support. In a representative German population, the OSS-3 showed an internal consistency of Cronbach’s α = .64 [85].

Coping and resources: Child’s coping and resources

If their child cannot or does not want to participate themselves, parents are asked to rate the child’s coping and resources. Three items, taken from the COVID-19 Snapshot Monitoring questionnaire [86], are implemented. On a 7-point scale, reaching from 0 = “totally disagree “to 6 = “totally agree”, the proxy-report items assess whether the child suffers from not seeing their friends, whether it is happy to spend more time with the family, and whether it is overall coping well with the changes. Additionally, 6 self-constructed items based on the scales of the Resource Questionnaire for Children and Adolescents (in German: Fragebogen zu Ressourcen im Kindes- und Jugendalter (FRKJ 8–16)) [87] are presented on a 4-point scale to measure the child’s resources as a proxy-report. Ranging from “never true “to “aways true“, the parents are asked to rate their child’s empathy, self-efficacy, confidence, coherence, optimism, and locus of control.

Family relations and interactions

The following tools are used to consider the potential impact at family level.

Family relations and interactions: Parenting behaviour

To measure the risk of harmful parenting, 4 items originating from a study by Clemens et al. [88] is implemented. The items range on a 7-point Likert scale from 0 “does not apply at all “to 6 “applies very strongly“, asking the parents to indicate whether they are yelling more at the child, are more impatient, are more scared of slapping the child, or are more scared that their partner will slap the child since the beginning of the COVID-19 pandemic.

Family relations and interactions: Family-related quality of life

The survey includes 12 items assigned to two of three subscales of the family-related life questionnaire (FLQ) developed by Tröster [89]. Four items are ascribed to the subscale “relief from stress and self-fulfilment “and 8 items measure the subscale “social support within the family“. The 5-point scale ranges from 0 = “never/almost never “to 4 = “very frequently”, and the FLQ has an overall good internal consistency of Cronbach’s α = .93 to .94 [89].

Family relations and interactions: Parental burnout

The 5-item Brief Parental Burnout scale (BPBs) is applied to measure the risk of parental burnout. Parents are asked to rate the frequency of feelings related to burn-out (e.g., “I’m so tired out by my role as a parent that sleeping doesn’t seem like enough.“) on a 3-point response scale reaching from daily to more seldom/never. The BPBs reports an internal consistency of Cronbach’s α = .81 to .84 [90].

Control variables

The short form of the German Scale for Detecting Test Manipulation through Faking Good and Social Desirability Bias (in German: Skala zur Erfassung von Testverfälschung durch positive Selbstdarstellung und sozial erwünschte Antworttendenzen (SEA-K)) [91] is implemented to control for the social desirability bias. On a 4-point Likert scale, parents are asked to rate how much they agree with statements closely related to social desirability (e.g., “I would never talk behind my employer’s or colleague’s back“). The SEA-K has an internal consistency of Cronbach’s α = .59 [91].

Web-based extended measures for children

Psychosocial adjustment

To measure the child’s health related quality of life (HRQoL), 16 items of the KIDSCREEN-27 [92] are implemented. The participants are asked to indicate their HRQoL on 5 dimensions. The subscale “physical well-being “comprises 5 items (e.g., “Thinking about the last week, have you felt fit and well?“), 4 items are assigned to the dimension “social support and peers “(e.g., “Thinking about the last week, have you spent time with your friends?“). The internal consistency for each subscale of the KIDSCREEN-27 is Cronbach’s α > .70 [92]. Furthermore, the Kidscreen-10 index is applied to determine a global HRQoL score. The global score is derived from 10 items and has a good internal consistency of Cronbach’s α = .82 [92].

Coping and resources: Coping

Children’s coping strategies are assessed with the Coping with a disease questionnaire CODI [93]. Children indicate how frequently they use six coping styles on a 5-point Likert scale ranging from “never “to “always“. The items are assigned to the 6 subscales: acceptance, avoidance, cognitive-palliative, distance, emotional reaction, and wishful thinking, with internal consistencies ranging from α = .69 to α = .83 [93].

Coping and resources: Resources

To assess the children’s personal and social resources, the Questionnaire of Resources in Childhood and Youth (in German: Fragebogen zu Ressourcen im Kindes und Jugendalter (FRKJ-8-16)) is applied. The current study uses the subscales “sense of coherence“, “optimism“, “self-efficacy“, and “parental support“, comprising 6 items each (e.g., “I make sense of my life“). Responses are measured on 4-point Likert scales ranging from “never true “to “always true“. The internal consistency of the subscales varies between Cronbach’s α = 0.69 to α = 0.89 [87].

Based on self-constructed items from another study [59], 6 items are implemented to measure children’s corona-specific self-efficacy. Children are asked to rate the items (e.g., “I always know how to behave during the corona crisis”) on a 5-point Likert scale ranging from “not true at all” to “absolutely true”.

Coping and resources: Social integration

The survey includes 4 items based on self-constructed items from another study [59] to measure the amount of time children spend with their peers during and before the pandemic. On a 5-point Likert scale ranging from “very rarely “to “very often“, children are asked to answer how often they are meeting their friends, how often they met before the pandemic, how often they communicate digitally, and how often they used to communicate before the pandemic.

Family relations and interactions: Quality of child-parent relationship

The German version of the Parental-Representation-Screening-Questionnaire (PRSQ), in German “Elternbildfragebogen für Kinder und Jugendliche “(EBF-KJ), is administered to assess how the children rate the relationship with their parents. This survey uses two modified scales of the EBF-KJ, namely “autonomy “and “overprotection“, asking children to answer 8 items on 5-point Likert scales. The internal consistency of the subscales ranges from Cronbach’s α = .72 to .85 for patients [94].

Family relations and interactions: COVID-19-specific social support

To assess the perceived support during the COVID-19 pandemic, 8 self-constructed items are applied. On a scale ranging from 0 “completely disagree “to 4 “completely agree“, children are asked how much they have talked about the coronavirus with their parents (e.g., “My parents have explained to me what COVID-19 is“) and their friends (e.g., “I have talked to my friends about COVID-19″).

Sample size

With respect to the baseline survey, we will implement a convenience sampling procedure: That means that all facilities taking part in one of the three patient registries have been informed about the ongoing KICK-COVID study via newsletters and regular meetings of the collaborators. We aim to include (and re-assess) as many participants as possible in order to get sufficient data sets to make generalizable statements. Therefore, we intend to recruit at least 1000 parents of either children or adolescents per CC. In addition, we assume that around 500 adolescents (> 12 yrs) per CC will fill in the baseline survey. For the web-based psychosocial assessment, the primary goal is to get a deeper understanding of the assumed psychosocial processes that can explain the level of mental and physical strain experienced. Therefore, we aim to include a subsample of participants of the baseline survey. To apply structural equation modeling (SEM) required sample sizes are dependent on various data characteristics such as data distribution, the number of missing data, or parameters that have to be computed. According to Kline [95], the sample size should fall above the number of 200 although sample sizes with at least 100 participants might be sufficient. Since drop-out rates vary between 0 and 54% [96] we aim to include between 300 and 400 parents and about 100 adolescents.

Statistical analyses

In accordance with common guidelines, we will only include online survey data with a high data quality indication but a “realistic” completion time of the questionnaire (a relative speed indicator higher than 2 and a total completion time of at least 5 minutes [97]). With respect to missing data and drop-outs, multiple imputations via fully conditional specification implemented will be performed [98]. We will apply multivariate ANOVAs and (logistic, hierarchal) regression analyses to analyze disease-specific differences with respect to health care use, risk perception and mental health. Sociodemographic variables such as age and sex of the child, disease severity, and risk perception will be included as predictors, as well as the date the questionnaire is completed as indicator of the stringency of current containment measures. To analyze the interplay between physical and mental health and the impact of corona-related stressors, SEM will be applied. All analyses will be conducted using SPSS, SAS; R or Mplus.

Discussion

The COVID-19 pandemic has led to far-reaching changes in everyday life for everyone worldwide. Families with underage young people in particular are and were affected in many ways: be it the closure of schools and daycare centers with the resulting need for homeschooling or home care, far-reaching contact restrictions and lockdowns, or the changed working situation of parents with home offices or part-time work, to name just a few measures that aimed to curb the further spread of the contagious virus. These measures have not spared the health system with the (partial) closure of outpatient clinics, limited contact times, or the establishment of video consultation hours. It is precisely these restrictions that affect those who are most in need of regular medical and psychosocial care: people with CCs.

Since the outbreak of the pandemic, numerous studies have examined the consequences for society. There is now meta-analytical evidence on the psychological consequences for children and adolescents [33, 46, 99] and their parents [100]. The psychosocial effects of the COVID-19 pandemic on children and their parents have also been and are being extensively examined for the German-speaking area, e.g., with the COPSY study [101] or the LIFE Child study [102]. In contrast, KICK-COVID focuses explicitly on the group of children with a chronic illness and their parents. With the help of three patient registers, not only medical outcomes but also psychosocial outcomes and their interplay can be examined comprehensively.

Strengths and limitations

To the best of our knowledge, no other national study focuses on the group of children and adolescents with a chronic illness during the COVID-19 pandemic.

The KICK-COVID study and its expected results must be viewed in light of its strengths and weaknesses. A major strength of our approach is the large expected sample size. The short economic questionnaire aims to reach as many of those affected as possible. The large sample size makes it possible to make statements that are as representative as possible, not only in relation to the respective underlying physical disease, but also across the disease groups in order to identify generic and condition-specific patterns. In addition, the extended psychosocial web survey will enrich our database by providing more detailed information on the psychosocial situation and coping strategies of the families. Of note, a follow-up over 1 year will allow us to examine short and longer-term effects and different trajectories over time.

With respect to the limitations of the study, it should be mentioned that a self-selection of interested clinicians and patients cannot be ruled out. Thus, clinicians might not approach certain patients, either because they may perceive these persons as too distressed or because they believe that the afflicted patients do not have any problems. Especially, a bias regarding the inclusion of the high-risk group in the obesity sample can be expected for the basic survey and the extended survey in particular. Due to organizational reasons, we are not able to implement the questionnaires as obligatory, and we could not offer monetary compensation for the clinics and patients to mitigate this effect. However, we are aiming for a large sample that may be able to compensate for this effect. Furthermore, the data already available from the registers allow us to characterize our sample in relation to the total population. Of course, self-selection could be even more pronounced when parents are invited to fill in the questionnaire. Due to ethical reasons and German data protection law regulations, we have to ask the parents to forward the children’s questionnaire with their consent to their children.

Taken together, the results of the proposed study will provide empirical data on how to support families with a child suffering from a CC and contribute to a more successful and sustainable health system. The identification of determining factors for positive adjustment will offer new opportunities for interventions. The prospective design will not only allow the detection of acute and delayed long-term effects, but also the analysis of mediating and moderator influences.

Availability of data and materials

Fully anonymized data will be available from the corresponding author on reasonable request and with the permission of the collaboration partners.

Abbreviations

APV:

German Obesity Prospective Follow-up Registry

ASKU:

General self-efficacy scale (in German: Allgemeine Selbstwirksamkeitsskala)

BPBs:

Brief Parental Burnout scale

Brief COPE:

Short version of the coping orientation to problems experienced inventory

CC:

Chronic physical health condition

CHQ:

Child Health Questionnaire

CODI:

Coping with a disease questionnaire

DPV:

German Diabetes Prospective Follow-up Registry obesity

EBF-KJ:

German Parental-Representation-Screening-Questionnaire (in German: Elternbildfragebogen für Kinder und Jugendliche)

FLQ:

Family-related life questionnaire

FRKJ-8-16:

Questionnaire of Resources in Childhood and Youth (in German: Fragebogen zu Ressourcen im Kindes und Jugendalter)

GAD-7:

General Anxiety Disorder-Scale

HRQoL:

Health related quality of life

IE-4:

Assessment of locus of control (In German: Internale-Externale-Kontrollüberzeugung-4)

NPRD:

National Pediatric Rheumatology Database

OSS-3:

OSLO social support scale

PHQ-9:

9-item Patient Health Questionnaire

PRSQ:

Parental Representation-Screening-Questionnaire (for the German version see also EBF-KJ)

PSS-4:

Perceived-Stress Scale

SDQ:

Strengths and Difficulties Questionnaire

SEA-K:

Scale for Detecting Test Manipulation through Faking Good and Social Desirability Bias (in German: Skala zur Erfassung von Testverfälschung durch positive Selbstdarstellung und sozial erwünschte Antworttendenzen)

SEM:

Structural equation modeling

SES:

Socioeconomic status

WHO-5:

World Health Organization Five Well-Being Index

References

  1. Minden K, Niewerth M, Klotsche J, Zink A. Versorgung von Kindern, Jugendlichen und jungen Erwachsenen mit juveniler idiopathischer Arthritis. Akt Rheumatol. 2018;43:375–82. https://doi.org/10.1055/a-0629-8776.

    Article  Google Scholar 

  2. Schienkiewitz A, Damerow S, Schaffrath Rosario A, Kurth B-M. Body-Mass-Index von Kindern und Jugendlichen: Prävalenzen und Verteilung unter Berücksichtigung von Untergewicht und extremer Adipositas: Ergebnisse aus KiGGS Welle 2 und Trends. [Body mass index among children and adolescents: prevalences and distribution considering underweight and extreme obesity: Results of KiGGS Wave 2 and trends]. Bundesgesundheitsbl Gesundheitsforsch Gesundheitsschutz. 2019;62:1225–34. https://doi.org/10.1007/s00103-019-03015-8.

    Article  Google Scholar 

  3. Deutsche Diabetes Gesellschaft (DDG) und diabetesDE - Deutsche Diabetes Hilfe. Deutscher Gesundheitsbericht Diabetes 2022: Die Bestandsaufnahme. Mainz: Kirchheim & Co; 2021.

  4. Ludvigsson JF. Systematic review of COVID-19 in children shows milder cases and a better prognosis than adults. Acta Paediatr. 2020;109:1088–95. https://doi.org/10.1111/apa.15270.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Streng A, Hartmann K, Armann J, Berner R, Liese JG. COVID-19 bei hospitalisierten Kindern und Jugendlichen. Monatsschr Kinderheilkd. 2020;168:615–27. https://doi.org/10.1007/s00112-020-00919-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Lu X, Xiang Y, Du H, Wing-Kin WG. SARS-CoV-2 infection in children - understanding the immune responses and controlling the pandemic. Pediatr Allergy Immunol. 2020;31:449–53.

    Article  CAS  PubMed  Google Scholar 

  7. Dong Y, Mo X, Hu Y, Qi X, Jiang F, Jiang Z, et al. Epidemiology of COVID-19 among children in China. Pediatrics. 2020. https://doi.org/10.1542/peds.2020-0702.

  8. Tagarro A, Epalza C, Santos M, Sanz-Santaeufemia FJ, Otheo E, Moraleda C, et al. Screening and Severity of Coronavirus Disease 2019 (COVID-19) in children in Madrid, Spain. JAMA Pediatr. 2020. https://doi.org/10.1001/jamapediatrics.2020.1346.

  9. Stephanie Bialek CD, Ryangierke CD, Michelle Hughes CD. Coronavirus Disease 2019 in children - United States, February 12-April 2, 2020. MMWR Morb Mortal Wkly Rep. 2020;69:422–6. https://doi.org/10.15585/mmwr.mm6914e4.

    Article  PubMed Central  Google Scholar 

  10. Kompaniyets L, Agathis NT, Nelson JM, Preston LE, Ko JY, Belay B, et al. Underlying medical conditions associated with severe COVID-19 illness among children. JAMA Netw Open. 2021;4:e2111182. https://doi.org/10.1001/jamanetworkopen.2021.11182.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Madjid M, Safavi-Naeini P, Solomon SD, Vardeny O. Potential effects of coronaviruses on the cardiovascular system: a review. JAMA Cardiol. 2020;5:831–40. https://doi.org/10.1001/jamacardio.2020.1286.

    Article  PubMed  Google Scholar 

  12. Zhou Y, Chi J, Lv W, Wang Y. Obesity and diabetes as high-risk factors for severe coronavirus disease 2019 (Covid-19). Diabetes Metab Res Rev. 2021;37:e3377. https://doi.org/10.1002/dmrr.3377.

    Article  CAS  PubMed  Google Scholar 

  13. Gerstl E-M, Rabl W, Rosenbauer J, Gröbe H, Hofer SE, Krause U, et al. Metabolic control as reflected by HbA1c in children, adolescents and young adults with type-1 diabetes mellitus: combined longitudinal analysis including 27,035 patients from 207 centers in Germany and Austria during the last decade. Eur J Pediatr. 2008;167:447–53. https://doi.org/10.1007/s00431-007-0586-9.

    Article  CAS  PubMed  Google Scholar 

  14. Guo J, Whittemore R, He G-P. The relationship between diabetes self-management and metabolic control in youth with type 1 diabetes: an integrative review. J Adv Nurs. 2011;67:2294–310. https://doi.org/10.1111/j.1365-2648.2011.05697.x.

    Article  PubMed  Google Scholar 

  15. Nogueira-de-Almeida CA, Del Ciampo LA, Ferraz IS, Del Ciampo IR, Contini AA, Da Ued FV. COVID-19 and obesity in childhood and adolescence: a clinical review. J Pediatr. 2020;96:546–58. https://doi.org/10.1016/j.jped.2020.07.001.

    Article  Google Scholar 

  16. Sengler C, Eulert S, Minden K, Niewerth M, Horneff G, Kuemmerle-Deschner J, et al. Clinical manifestations and outcome of SARS-CoV-2 infections in children and adolescents with rheumatic musculoskeletal diseases: data from the National Paediatric Rheumatology Database in Germany. RMD Open. 2021. https://doi.org/10.1136/rmdopen-2021-001687.

  17. D'Silva KM, Serling-Boyd N, Wallwork R, Hsu T, Fu X, Gravallese EM, et al. Clinical characteristics and outcomes of patients with coronavirus disease 2019 (COVID-19) and rheumatic disease: a comparative cohort study from a US 'hot spot'. Ann Rheum Dis. 2020;79:1156–62. https://doi.org/10.1136/annrheumdis-2020-217888.

    Article  CAS  PubMed  Google Scholar 

  18. Cordtz R, Lindhardsen J, Soussi BG, Vela J, Uhrenholt L, Westermann R, et al. Incidence and severeness of COVID-19 hospitalization in patients with inflammatory rheumatic disease: a nationwide cohort study from Denmark. Rheumatology (Oxford). 2021;60:SI59–67. https://doi.org/10.1093/rheumatology/keaa897.

    Article  CAS  PubMed  Google Scholar 

  19. Jovani V, Calabuig I, Peral-Garrido ML, Tovar-Sugrañes E, López-González M-D-C, Bernabeu P, et al. Incidence of severe COVID-19 in a Spanish cohort of 1037 patients with rheumatic diseases treated with biologics and JAK-inhibitors. Ann Rheum Dis. 2022;81:e131. https://doi.org/10.1136/annrheumdis-2020-218152.

    Article  CAS  PubMed  Google Scholar 

  20. Conti G, Galletta F, Carucci NS, La Mazza A, Mollica SA, Alibrandi A, et al. Negative effect of lockdown on juvenile idiopathic arthritis patients. Clin Rheumatol. 2021;40:3723–7. https://doi.org/10.1007/s10067-021-05694-8.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Vogel M, Geserick M, Gausche R, Beger C, Poulain T, Meigen C, et al. Age- and weight group-specific weight gain patterns in children and adolescents during the 15 years before and during the COVID-19 pandemic. Int J Obes. 2022;46:144–52. https://doi.org/10.1038/s41366-021-00968-2.

    Article  CAS  Google Scholar 

  22. Kamrath C, Rosenbauer J, Eckert AJ, Siedler K, Bartelt H, Klose D, et al. Incidence of type 1 diabetes in children and adolescents during the COVID-19 pandemic in Germany: results from the DPV registry. Diabetes Care. 2022;45:1762–71. https://doi.org/10.2337/dc21-0969.

    Article  CAS  PubMed  Google Scholar 

  23. Pinquart M, Shen Y. Behavior problems in children and adolescents with chronic physical illness: a meta-analysis. J Pediatr Psychol. 2011;36:1003–16. https://doi.org/10.1093/jpepsy/jsr042.

    Article  PubMed  Google Scholar 

  24. Pinquart M, Shen Y. Depressive symptoms in children and adolescents with chronic physical illness: an updated meta-analysis. J Pediatr Psychol. 2011;36:375–84. https://doi.org/10.1093/jpepsy/jsq104.

    Article  PubMed  Google Scholar 

  25. Pinquart M. Parenting stress in caregivers of children with chronic physical condition-a meta-analysis. Stress Health. 2018;34:197–207. https://doi.org/10.1002/smi.2780.

    Article  PubMed  Google Scholar 

  26. Pinquart M. Featured article: depressive symptoms in parents of children with chronic health conditions: a Meta-analysis. J Pediatr Psychol. 2019;44:139–49. https://doi.org/10.1093/jpepsy/jsy075.

    Article  PubMed  Google Scholar 

  27. Pinquart M. Meta-analysis of anxiety in parents of young people with chronic health conditions. J Pediatr Psychol. 2019;44:959–69. https://doi.org/10.1093/jpepsy/jsz024.

    Article  PubMed  Google Scholar 

  28. Varni JW, Limbers CA, Burwinkle TM. Impaired health-related quality of life in children and adolescents with chronic conditions: a comparative analysis of 10 disease clusters and 33 disease categories/severities utilizing the PedsQL™ 4.0 generic Core scales. Health Qual Life Outcomes. 2007;5:43–57. https://doi.org/10.1186/1477-7525-5-43.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Plener PL, Molz E, Berger G, Schober E, Mönkemöller K, Denzer C, et al. Depression, metabolic control, and antidepressant medication in young patients with type 1 diabetes. Pediatr Diabetes. 2015;16:58–66. https://doi.org/10.1111/pedi.12130.

    Article  CAS  PubMed  Google Scholar 

  30. Samji H, Wu J, Ladak A, Vossen C, Stewart E, Dove N, et al. Review: mental health impacts of the COVID-19 pandemic on children and youth - a systematic review. Child Adolesc Mental Health. 2021. https://doi.org/10.1111/camh.12501.

  31. Donohue JM, Miller E. COVID-19 and school closures. JAMA. 2020;324:845–7. https://doi.org/10.1001/jama.2020.13092.

    Article  CAS  PubMed  Google Scholar 

  32. Dändliker L, Brünecke I, Citterio P, Lochmatter F, Buchmann M, Grütter J. Educational concerns, health concerns and mental health during early COVID-19 school closures: the role of perceived support by teachers, family, and friends. Front Psychol. 2022;12:733683. https://doi.org/10.3389/fpsyg.2021.733683.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Panchal U, Salazar de Pablo G, Franco M, Moreno C, Parellada M, Arango C, et al. The impact of COVID-19 lockdown on child and adolescent mental health: systematic review. Eur Child Adolesc Psychiatry. 2021:1–27. https://doi.org/10.1007/s00787-021-01856-w.

  34. Racine N, McArthur BA, Cooke JE, Eirich R, Zhu J, Madigan S. Global prevalence of depressive and anxiety symptoms in children and adolescents during COVID-19: a Meta-analysis. JAMA Pediatr. 2021;175:1142–50. https://doi.org/10.1001/jamapediatrics.2021.2482.

    Article  PubMed  Google Scholar 

  35. Huebener M, Waights S, Spiess CK, Siegel NA, Wagner GG. Parental well-being in times of Covid-19 in Germany. SOEPpapers on multidisciplinary panel data Research; 2020.

    Google Scholar 

  36. Prime H, Wade M, Browne DT. Risk and resilience in family well-being during the COVID-19 pandemic. Am Psychol. 2020;75:631–43. https://doi.org/10.1037/amp0000660.

    Article  PubMed  Google Scholar 

  37. Kerr ML, Fanning KA, Huynh T, Botto I, Kim CN. Parents' self-reported psychological impacts of COVID-19: associations with parental burnout, child behavior, and income. J Pediatr Psychol. 2021;46:1162–71. https://doi.org/10.1093/jpepsy/jsab089.

    Article  PubMed  Google Scholar 

  38. Alessi J, de Oliveira GB, Feiden G, Schaan BD, Telo GH. Caring for caregivers: the impact of the COVID-19 pandemic on those responsible for children and adolescents with type 1 diabetes. Sci Rep. 2021;11:6812. https://doi.org/10.1038/s41598-021-85874-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Calvano C, Engelke L, Di Bella J, Kindermann J, Renneberg B, Winter SM. Families in the COVID-19 pandemic: parental stress, parent mental health and the occurrence of adverse childhood experiences-results of a representative survey in Germany. Eur Child Adolesc Psychiatry. 2021. https://doi.org/10.1007/s00787-021-01739-0.

  40. Sharfstein JM, Morphew CC. The urgency and challenge of opening K-12 schools in the fall of 2020. JAMA. 2020;324:133–4. https://doi.org/10.1001/jama.2020.10175.

    Article  CAS  PubMed  Google Scholar 

  41. Orben A, Tomova L, Blakemore S-J. The effects of social deprivation on adolescent development and mental health. Lancet Child Adolesc Health. 2020;4:634–40. https://doi.org/10.1016/S2352-4642(20)30186-3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Taquet M, Quoidbach J, Fried EI, Goodwin GM. Mood homeostasis before and during the coronavirus disease 2019 (COVID-19) lockdown among students in the Netherlands. JAMA Psychiatry. 2021;78:110–2. https://doi.org/10.1001/jamapsychiatry.2020.2389.

    Article  PubMed  Google Scholar 

  43. Brooks SK, Webster RK, Smith LE, Woodland L, Wessely S, Greenberg N, et al. The psychological impact of quarantine and how to reduce it: rapid review of the evidence. Lancet. 2020;395:912–20. https://doi.org/10.1016/S0140-6736(20)30460-8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Varengue R, Brochard S, Bouvier S, Bailly R, Houx L, Lempereur M, et al. Perceived impact of lockdown on daily life in children with physical disabilities and their families during the COVID-19 pandemic. Child Care Health Dev. 2022;48:942–55. https://doi.org/10.1111/cch.12952.

    Article  PubMed  Google Scholar 

  45. Le Shi LZ-A, Que J-Y, Huang X-L, Liu L, Ran M-S, et al. Prevalence of and risk factors associated with mental health symptoms among the general population in China during the coronavirus disease 2019 pandemic. JAMA Netw Open. 2020;3:e2014053. https://doi.org/10.1001/jamanetworkopen.2020.14053.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Ma L, Mazidi M, Li K, Li Y, Chen S, Kirwan R, et al. Prevalence of mental health problems among children and adolescents during the COVID-19 pandemic: a systematic review and meta-analysis. J Affect Disord. 2021;293:78–89. https://doi.org/10.1016/j.jad.2021.06.021.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Hoefnagels JW, Schoen AB, van der Laan SEI, Rodijk LH, van der Ent CK, van de Putte EM, et al. The impact of the COVID-19 outbreak on mental wellbeing in children with a chronic condition compared to healthy peers. Int J Environ Res Public Health. 2022. https://doi.org/10.3390/ijerph19052953.

  48. Zijlmans J, Teela L, van Ewijk H, Klip H, van der Mheen M, Ruisch H, et al. Mental and social health of children and adolescents with pre-existing mental or somatic problems during the COVID-19 pandemic lockdown. Front Psychiatry. 2021;12:692853. https://doi.org/10.3389/fpsyt.2021.692853.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Pierce M, Hope H, Ford T, Hatch S, Hotopf M, John A, et al. Mental health before and during the COVID-19 pandemic: a longitudinal probability sample survey of the UK population. Lancet Psychiatry. 2020;7:883–92. https://doi.org/10.1016/S2215-0366(20)30308-4.

    Article  PubMed  PubMed Central  Google Scholar 

  50. World Health Organization. Mental health and psychosocial considerations during the COVID-19 outbreak, 18 March 2020. Geneva: World Health Organization; 2020.

  51. Warschburger P. Health Psychology in childhood. In: Wright J, editor. International encyclopedia of the social & Behavioral Sciences. Oxford: Elsevier; 2015. p. 679–85. https://doi.org/10.1016/B978-0-08-097086-8.14067-X.

  52. Calvano C, Warschburger P. Chronic abdominal pain in children and adolescents: parental threat perception plays a major role in seeking medical consultations. Pain Res Manag. 2016;2016:3183562. https://doi.org/10.1155/2016/3183562.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Warschburger P, Kröller K. Childhood overweight and obesity: maternal perceptions of the time for engaging in child weight management. BMC Public Health. 2012;12:295. https://doi.org/10.1186/1471-2458-12-295.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Cieza A, Stucki G. The international classification of functioning disability and health: its development process and content validity. Eur J Phys Rehabil Med. 2008;44:303–13.

    CAS  PubMed  Google Scholar 

  55. Hofer SE, Schwandt A, Holl RW. Standardized documentation in pediatric Diabetology: experience from Austria and Germany. J Diabetes Sci Technol. 2016;10:1042–9. https://doi.org/10.1177/1932296816658057.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Reinehr T, Wabitsch M, Andler W, Beyer P, Böttner A, Chen-Stute A, et al. Medical care of obese children and adolescents. APV: a standardised multicentre documentation derived to study initial presentation and cardiovascular risk factors in patients transferred to specialised treatment institutions. Eur J Pediatr. 2004;163:308–12. https://doi.org/10.1007/s00431-004-1421-1.

    Article  PubMed  Google Scholar 

  57. Minden K, Niewerth M, Listing J, Zink A. Health care provision in pediatric rheumatology in Germany--national rheumatologic database. J Rheumatol. 2002;29:622–8.

    PubMed  Google Scholar 

  58. Warschburger P, Wortmann HR, Gisch UA, Baer NR, Schenk L, Anton V, et al. An experimental approach to training interoceptive sensitivity: study protocol for a randomized controlled trial. Nutr J. 2022;21:74. https://doi.org/10.1186/s12937-022-00827-4.

  59. Warschburger P, Petersen A-C, von Rezori RE, Buchallik F, Baumeister H, Holl RW, et al. A prospective investigation of developmental trajectories of psychosocial adjustment in adolescents facing a chronic condition - study protocol of an observational, multi-center study. BMC Pediatr. 2021. https://doi.org/10.1186/s12887-021-02869-9.

  60. Klein EM, Brähler E, Dreier M, Reinecke L, Müller KW, Schmutzer G, et al. The German version of the perceived stress scale - psychometric characteristics in a representative German community sample. BMC Psychiatry. 2016;16:159. https://doi.org/10.1186/s12888-016-0875-9.

    Article  PubMed  PubMed Central  Google Scholar 

  61. WHO. WHO (Fünf). Fragebogen zum Wohlbefinden: Psychiatric Research Unit, WHO Collaborating Center for Mental Health, Frederiksborg General Hospital, DK-3400 Hillerød(Version 1998). 1998.

  62. Brähler E, Mühlan H, Albani C, Schmidt S. Teststatistische Prüfung und Normierung der deutschen Versionen des EUROHIS-QOL Lebensqualität-Index und des WHO-5 Wohlbefindens-Index. Diagnostica. 2007;53:83–96. https://doi.org/10.1026/0012-1924.53.2.83.

    Article  Google Scholar 

  63. Lampert T, Sygusch R, Schlack R. Nutzung elektronischer Medien im Jugendalter. Bundesgesundheitsbl Gesundheitsforsch Gesundheitsschutz. 2007;50:643–52.

    Article  CAS  Google Scholar 

  64. Hölling H, Schlack R, Kamtsiuris P, Butschalowsky H, Schlaud M, Kurth BM. Die KiGGS-Studie. Bundesgesundheitsbl. 2012;55:836–42. https://doi.org/10.1007/s00103-012-1486-3.

    Article  Google Scholar 

  65. Löwe B, Decker O, Müller S, Brähler E, Schellberg D, Herzog W, et al. Validation and standardization of the generalized anxiety disorder screener (GAD-7) in the general population. Med Care. 2008;46:266–74. https://doi.org/10.1097/MLR.0b013e318160d093.

    Article  PubMed  Google Scholar 

  66. Spitzer RL, Kroenke K, Williams JBW, Löwe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. 2006;166:1092–7. https://doi.org/10.1001/archinte.166.10.1092.

    Article  PubMed  Google Scholar 

  67. Dear BF, Titov N, Sunderland M, McMillan D, Anderson T, Lorian C, et al. Psychometric comparison of the generalized anxiety disorder scale-7 and the Penn State worry questionnaire for measuring response during treatment of generalised anxiety disorder. Cogn Behav Ther. 2011;40:216–27. https://doi.org/10.1080/16506073.2011.582138.

    Article  PubMed  Google Scholar 

  68. Fox CK, Gross AC, Rudser KD, Foy AMH, Kelly AS. Depression, anxiety, and severity of obesity in adolescents: is emotional eating the link? Clin Pediatr (Phila). 2016;55:1120–5. https://doi.org/10.1177/0009922815615825.

    Article  PubMed  Google Scholar 

  69. Puka K, Widjaja E, Smith ML. The influence of patient, caregiver, and family factors on symptoms of anxiety and depression in children and adolescents with intractable epilepsy. Epilepsy Behav. 2017. https://doi.org/10.1016/j.yebeh.2016.12.011.

  70. Löwe B, Spitzer RL, Zipfel S, Herzog W. Gesundheitsfragebogen für Patienten (PHQ-D). 2nd ed. Karlsruhe: Pfizer; 2002.

    Google Scholar 

  71. Erbe D, Eichert H-C, Rietz C, Ebert D. Interformat reliability of the patient health questionnaire: validation of the computerized version of the PHQ-9. Internet Interv. 2016;5:1–4. https://doi.org/10.1016/j.invent.2016.06.006.

    Article  PubMed  PubMed Central  Google Scholar 

  72. Abdel-Khalek A. Measuring happiness with a single-item scale. Soc Behav Pers. 2006;34:139–50.

    Article  Google Scholar 

  73. Gierveld JDJ, van Tilburg T. A 6-item scale for overall, emotional, and social loneliness. Res Aging. 2006;28:582–98. https://doi.org/10.1177/0164027506289723.

    Article  Google Scholar 

  74. Koglin U, Barquero B, Mayer H, Scheithauer H, Petermann F. Deutsche Version des Strengths and Difficulties Questionnaire (SDQ-Deu). Diagnostica. 2007;53:175–83. https://doi.org/10.1026/0012-1924.53.4.175.

    Article  Google Scholar 

  75. Woerner W, Becker A, Rothenberger A. Normative data and scale properties of the German parent SDQ. Eur Child Adolesc Psychiatry 2004;13:II3-II10. https://doi.org/10.1007/s00787-004-2002-6.

  76. Hoebel J, Müters S, Kuntz B, Lange C, Lampert T. Messung des subjektiven sozialen status in der Gesundheitsforschung mit einer deutschen version der MacArthur scale. [measuring subjective social status in health research with a German version of the MacArthur scale]. Bundesgesundheitsbl Gesundheitsforsch Gesundheitsschutz. 2015;58:749–57. https://doi.org/10.1007/s00103-015-2166-x.

    Article  Google Scholar 

  77. Winkler J, Stolzenberg H. Adjustierung des Sozialen-Schicht-Index für die Anwendung im Kinder- und Jugendgesundheitssurvey (KiGGS) 2003/2006. Wismar: Hochsch., Fakultät für Wirtschaftswiss; HWS-Hochsch.-Wismar-Service; 2009.

    Google Scholar 

  78. Löwe B, Wahl I, Rose M, Spitzer C, Glaesmer H, Wingenfeld K, et al. A 4-item measure of depression and anxiety: validation and standardization of the patient health Questionnaire-4 (PHQ-4) in the general population. J Affect Disord. 2010;122:86–95. https://doi.org/10.1016/j.jad.2009.06.019.

    Article  PubMed  Google Scholar 

  79. Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav. 1983;24:385. https://doi.org/10.2307/2136404.

    Article  CAS  PubMed  Google Scholar 

  80. Calvano C, Warschburger P. Quality of life among parents seeking treatment for their child's functional abdominal pain. Qual Life Res. 2018;27:2557–70. https://doi.org/10.1007/s11136-018-1916-2.

    Article  PubMed  Google Scholar 

  81. Knoll N, Rieckmann N, Schwarzer R. Coping as a mediator between personality and stress outcomes: a longitudinal study with cataract surgery patients. Eur J Personal. 2005;19:229–47. https://doi.org/10.1002/per.546.

    Article  Google Scholar 

  82. Beierlein C, Kemper CJ, Kovaleva A, Rammstedt B. Short Scale for Measuring General Self-efficacy Beliefs (ASKU). Methoden, daten, analysen. 2013;7:251–78. https://doi.org/10.12758/mda.2013.014.

  83. Kovaleva A. The IE-4: construction and validation of a short scale for the assessment of locus of control: SSOAR - GESIS Leibniz Institute for the Social Sciences; 2012.

    Google Scholar 

  84. Kovaleva A, Beierlein C, Kemper CJ, Rammstedt B. Internale-Externale-Kontrollüberzeugung-4 (IE-4): ZIS - GESIS Leibniz Institute for the Social Sciences; 2014.

    Google Scholar 

  85. Kocalevent R-D, Berg L, Beutel ME, Hinz A, Zenger M, Härter M, et al. Social support in the general population: standardization of the Oslo social support scale (OSSS-3). BMC Psychol. 2018;6:31. https://doi.org/10.1186/s40359-018-0249-9.

    Article  PubMed  PubMed Central  Google Scholar 

  86. Betsch C, Korn L, Felgendreff L, Eitze S, Schmid P, Sprengholz P, et al. COVID-19 snapshot monitoring (COSMO Germany) - Wave 60: PsychArchives; 2022.

    Google Scholar 

  87. Lohaus A, Nussbeck FW. FRKJ-8-16. Fragebogen zu Ressourcen im Kindes- und Jugendalter. Göttingen: Hogrefe; 2016.

    Google Scholar 

  88. Clemens V, Köhler-Dauner F, Ziegenhain U, Fegert JM. Predictors of parental coping during the Covid-19 pandemic: a survey in Germany. Front Psychol. 2021. https://doi.org/10.3389/fpsyg.2021.715327.

  89. Tröster H. Entwicklung eines Fragebogens zur familienbezogenen Lebensqualität (FLQ) für Mütter mit chronisch kranken Kindern. Kindh Entwickl. 2005;14:69–78. https://doi.org/10.1026/0942-5403.14.2.69.

    Article  Google Scholar 

  90. Aunola K, Sorkkila M, Tolvanen A, Tassoul A, Mikolajczak M, Roskam I. Development and validation of the brief parental burnout scale (BPBS). Psychol Assess. 2021. https://doi.org/10.1037/pas0001064.

  91. Satow L. SEA - Skala zur Erfassung von Testverfälschung durch positive Selbstdarstellung und sozial erwünschte Antworttendenzen: ZPID (Leibniz Institute for Psychology) – Open Test Archive; 2012.

    Google Scholar 

  92. Ravens-Sieberer U, Herdman M, Devine J, Otto C, Bullinger M, Rose M, et al. The European KIDSCREEN approach to measure quality of life and well-being in children: development, current application, and future advances. Qual Life Res. 2014;23:791–803. https://doi.org/10.1007/s11136-013-0428-3.

    Article  PubMed  Google Scholar 

  93. Petersen C, Schmidt S, Bullinger M. Brief report: development and pilot testing of a coping questionnaire for children and adolescents with chronic health conditions. J Pediatr Psychol. 2004;29:635–40. https://doi.org/10.1093/jpepsy/jsh066.

    Article  PubMed  Google Scholar 

  94. Titze K, Wiefel A, Assheuer J, Biermann M, Führer D, Riezler B, et al. Der Elternbildfragebogen für Kinder- und Jugendliche (EBF-KJ). Diagnostica. 2010;56:68–81. https://doi.org/10.1026/0012-1924/a000002.

    Article  Google Scholar 

  95. Kline RB. Principles and practice of structural equation modeling. New York: Guilford Press; 2016.

    Google Scholar 

  96. Karlson CW, Rapoff MA. Attrition in randomized controlled trials for pediatric chronic conditions. J Pediatr Psychol. 2009;34:782–93. https://doi.org/10.1093/jpepsy/jsn122.

    Article  PubMed  Google Scholar 

  97. Leiner DJ. Too Fast, too Straight, too Weird: Non-Reactive Indicators for Meaningless Data in Internet Surveys; 2019. https://doi.org/10.18148/SRM/2019.V13I3.7403.

    Book  Google Scholar 

  98. van Buuren S, Groothuis-Oudshoorn K. Mice: multivariate imputation by chained equations in R. J Stat Softw. 2011. https://doi.org/10.18637/jss.v045.i03.

  99. 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. https://doi.org/10.1016/j.psychres.2020.113429.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Fong VC, Iarocci G. Child and family outcomes following pandemics: a systematic review and recommendations on COVID-19 policies. J Pediatr Psychol. 2020;45:1124–43. https://doi.org/10.1093/jpepsy/jsaa092.

    Article  Google Scholar 

  101. Ravens-Sieberer U, Kaman A, Otto C, Adedeji A, Napp A-K, Becker M, 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. 2021:1–10. https://doi.org/10.1007/s00103-021-03291-3.

  102. Vogel M, Meigen C, Sobek C, Ober P, Igel U, Körner A, et al. Well-being and COVID-19-related worries of German children and adolescents: a longitudinal study from pre-COVID to the end of lockdown in spring 2020. JCPP Adv. 2021. https://doi.org/10.1111/jcv2.12004.

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Acknowledgments

We would like to thank all collaborating health facilities in supporting the study by motivating their patient families, handing out the patient questionnaires and making available the data in the registers. We would also like to thank Theresa Zickert for her support drafting the manuscript.

Funding

Open Access funding enabled and organized by Projekt DEAL, funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Projektnummer 491466077. This study is implemented as part of the joint project “A prospective analysis of the long-term impact of the COVID-19 pandemic on well-being and health care among children with a high-risk chronic condition and their families”, funded by the German Research Foundation (Grant No: HO 3228/2-1; MI 2760/1-1; WA 1143/18-1).

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Authors and Affiliations

  1. Department of Psychology, Counseling Psychology, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476, Potsdam, Germany

    Petra Warschburger & Julia M. Göldel

  2. Center of Child and Adolescent Medicine, University of Giessen, Gießen, Germany

    Clemens Kamrath

  3. Institute of Epidemiology and Medical Biometry, ZIBMT, Ulm University, Ulm, Germany

    Stefanie Lanzinger & Reinhard W. Holl

  4. German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany

    Stefanie Lanzinger & Reinhard W. Holl

  5. Deutsches Rheuma-Forschungszentrum (DRFZ), Program Area Epidemiology, Berlin, Germany

    Claudia Sengler & Kirsten Minden

  6. Center for Social-Pediatric Care, Department of Pediatric Endocrinology and Diabetology, Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin und Humboldt- Universität zu Berlin, Berlin, Germany

    Susanna Wiegand

  7. Department of Pediatrics I, Pediatric Endocrinology, University Hospital Halle/S, Halle/S, Germany

    Susann Weihrauch-Blüher

  8. Department of Pediatric Respiratory Medicine, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin und Humboldt- Universität zu Berlin, Immunology and Critical Care Medicine at Charité University Hospital Berlin, Berlin, Germany

    Kirsten Minden

Authors
  1. Petra Warschburger
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  2. Clemens Kamrath
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  3. Stefanie Lanzinger
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  4. Claudia Sengler
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  5. Susanna Wiegand
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  6. Julia M. Göldel
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  7. Susann Weihrauch-Blüher
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  8. Reinhard W. Holl
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  9. Kirsten Minden
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Contributions

CK and RWH had the idea to this study and initiated together with KM and PW the joint project. CS, SL and SW collaborated in the application and all authors contributed to its design. PW and JG designed the web-based survey and wrote the draft of this manuscript. All authors contributed to the further writing and approved the final manuscript. PW is its guarantor.

Corresponding author

Correspondence to Petra Warschburger.

Ethics declarations

Ethics approval and consent to participate

The study will be conducted in accordance with the principles of Good Clinical Practice, the Declaration of Helsinki (https://www.wma.net/wpcontent/uploads/2016/11/DoH-Oct2008.pdf), and current ethical standards. Written informed consent is obtained from each participant. For underage participants, informed consent from the legal representative or guardian will also be required. The central ethical approval of the Ethics Committee of Potsdam University was obtained (request number 62/2020). The study was registered in the German Clinical Trials Register (DRKS), no. DRKS00027974 on January 27, 2022 and the International Clinical Trials Registry Platform (WHO).

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The authors declare that they have no competing interests.

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Warschburger, P., Kamrath, C., Lanzinger, S. et al. A prospective analysis of the long-term impact of the COVID-19 pandemic on well-being and health care among children with a chronic condition and their families: a study protocol of the KICK-COVID study. BMC Pediatr 23, 130 (2023). https://doi.org/10.1186/s12887-023-03912-7

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Keywords

  • Chronic conditions
  • COVID-19
  • Children and adolescents
  • Parents
  • Risk perception
  • Psychosocial strain
  • Diabetes
  • Rheumatic diseases
  • Obesity

BMC Pediatrics

ISSN: 1471-2431

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