Digital interventions, such as serious games, are becoming increasingly important in the context of prevention and treatment approaches of mental disorders. A project (SG4ChildD) funded by the Federal Ministry of Research, Technology and Space (BMFTR) aims to develop a gamified app to promote emotion regulation in children aged 8 to 12 with increased depressive symptoms or a manifest diagnosis of depression. The app intends to train emotion regulation skills through playful and everyday-relevant scenarios. To ensure that the app meets the needs of the target group, a participatory needs assessment will be conducted that involves both children and their parents. Based on interviews with children and focus groups with parents and complemented by questionnaires, it will be assessed which everyday stressors children experience, how they cope with them, and what kind of support they and their parents find helpful.

Depressive disorders are among the most common psychiatric disorders in youth. Early depression can have serious effects on psychosocial development and long-term life outcomes. Despite the high demand for early intervention, substantial barriers to care persist, including long waiting times for therapy and administrative obstacles. As a result, low-threshold, location-independent interventions play an increasingly important role in improving access to care. In recent years, digital interventions such as serious games have gained increasing recognition in this context. These purposefully designed digital games go beyond mere entertainment by delivering targeted health-promoting, therapeutic, or psychoeducational content.

An important therapeutic focus in childhood depression is the improvement of emotion regulation - an ability strongly linked to mental health and resilience. The overarching goal of the present BMFTR-funded research project (SG4ChildD) is the development of a gamified app aimed at strengthening emotion regulation skills in children aged 8 to 12 with increased depressive symptoms or depressive disorders, serving as an add-on to professional treatment. In the current subproject, a participatory needs assessment with the app's target group (children with increased depressive symptoms/depressive disorders) and their parents will be conducted prior to the development of the app.The subproject aims to gain a deeper understanding of (1) everyday stressors experienced by children with depressive symptoms, (2) the subjective perception and emotional impact of these stressors, (3) the coping strategies children apply, and (4) the parental perspective on children's emotional challenges and supportive needs.

For this purpose, a primarily qualitative approach is chosen. Following an initial screening questionnaire to assess eligibility, participating children will take part in a semi-structured interview focusing on their subjective experience of emotional stress in everyday life (daily hassles). The interview will e.g. explore situations that trigger sadness or frustration and examine how children attempt to manage these feelings. This will be supplemented by standardized questionnaires on daily hassles, stress exposure and emotion regulation. In parallel, focus groups will be conducted with parents to explore their observations regarding children's exposure to daily hassles, coping strategies and what kind of support they and their children might need. Additionally, parents will complete questionnaires assessing their own regulatory parenting skills (i.e., the degree to which parents assist their children in the use of different regulation strategies) and parental report of the child´s depressive symptoms.

The insights gained through this needs assessment will directly inform the development of the app, and particularly the selection of game-based scenarios that reflect children's real-world challenges. By involving children and parents at an early stage of development, the project aims to maximize usability, acceptance, and clinical relevance of the digital intervention.

Participants will be recruited based on predefined inclusion criteria (e.g., elevated depressive symptoms in children). Recruitment will primarily take place via the Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy at the LMU University Hospital Munich. Additional recruitment may be supported by collaborating child and adolescent psychiatric clinics in the Munich area and by licensed outpatient therapists.

Inclusion Criteria (Children):

• increased depressive symptoms indicated by either (1) self report assessed with Beck Depression Inventory for Youth 2 (Beck et al., 2019; T-score > 60) , or (2) parental report assessed with DISYPS-III - external rating scale for depressive disorders (FBB-DES; Döpfner et al., 2017; applying gender- and age-normed Stanine scores ≥ 7).

Exclusion Criteria (Children):

• Insufficient German language skills
• Acute suicidality
• Schizophrenic disorder
• Severe developmental disorder
• Mental and behavioral disorders due to psychotropic substances

Inclusion Criteria (Parents):

Parent of a child meeting the above inclusion criteria

In total, 15-20 participants will be included in the study, including both children aged 8-12 with increased depressive symptoms and parents of children with increased depressive symptoms. Parents will be included in the study (focus group), even if their child is not taking part in the study and vice versa. The sample size is based on the concept of data saturation, which refers to the point at which no new information emerges from additional data.

The data collected in this study include sensitive details about participants, such as various sociodemographic and clinical characteristics. Publicly sharing the raw dataset could risk revealing individual identities, thereby violating ethical standards related to participant confidentiality. As a result, the data will not be publicly released. However, detailed descriptions of the methodology, materials used, and sample characteristics will be provided within the article and supplementary materials. Aggregated data and additional supporting materials may be shared upon request (contact: Lisa.Feldmann@med.uni-muenchen.de).