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Record W4416343602 · doi:10.2147/jmdh.s555927

Parental Voices on Virtual Reality in Pediatric Oncology: Experiences, Needs, and Pathways for Co-Design

2025· article· en· W4416343602 on OpenAlexaff
Charlotte Hélie, Jade Véronneau, Orly Desjardins, Léa Barada, Julie Lebeau, David Ogez

Bibliographic record

VenueJournal of Multidisciplinary Healthcare · 2025
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsUniversité du Québec en OutaouaisUniversité de MontréalHôpital Maisonneuve-Rosemont
Fundersnot available
KeywordsPsychological interventionPsychosocialIntervention (counseling)Virtual realityQualitative researchCitizen journalismChildhood cancerParticipatory action research

Abstract

fetched live from OpenAlex

Introduction: Pediatric cancer treatments significantly affect children’s physical, emotional, and social well-being. Virtual reality (VR) is emerging as a promising non-pharmacological tool to enhance quality of life during hospitalization, yet little is known about parents perceive its potential role in supportive care. Methods: This qualitative study used semi-structured interviews with five parents of children in remission from cancer. It explored their experiences during chemotherapy and their perspectives on how VR could help support children and families during treatment. Results: Parents described multiple challenges during hospitalization, including emotional distress, physical side effects, social isolation, logistical difficulties, and communication issues. While most had limited prior exposure to VR, they expressed openness toward its use to reduce anxiety, boredom, and loneliness. Parents emphasized that VR should complement, not replace, human interaction, and suggested age-specific applications, interactive content for adolescent and calming, passive experiences for younger children. Discussion: This study provides novel insights by integrating parental voices early in the co-design process of VR interventions for pediatric oncology. It identifies concrete psychosocial needs and offers recommendations to ensure future digital tools are developmentally appropriate and family-centered. While the small, homogeneous sample and absence of child participants limit generalizability, the in-depth qualitative approach offers valuable groundwork for future participatory research and VR intervention development in pediatric cancer care. Plain Language Summary: When a child is hospitalized for cancer treatment, it can be a stressful experience for the entire family. Children often experience fear, loneliness, and pain. Their parents also face emotional and practical challenges, such as long hospital stays, lack of sleep, and concerns about their child’s well-being. In this study, we interviewed five parents whose children had undergone chemotherapy and were now in remission. We asked them to share what they went through during the treatment and how they feel about using virtual reality (VR) as a support tool for children during hospitalization. The parents described many difficulties their children faced: physical side effects, anxiety, boredom, and being cut off from school and friends. They also spoke about their own struggles, including emotional exhaustion and communication problems with hospital staff. Despite having little experience with VR, most parents were open to using it during treatment. They saw VR as a possible way to reduce anxiety, help children relax, and even keep in touch with friends. However, they were clear that VR should not replace human contact. Parents suggested ideas like calming virtual nature scenes for young children, or interactive games for teenagers. Their input helps us understand how to design VR tools that are both useful and acceptable for families. This study highlights the importance of involving parents in the development of new health technologies. By listening to their experiences, we can create better tools to support children with cancer and their families. Keywords: pediatric oncology, chemotherapy, parental experiences, virtual reality, supportive care, qualitative research, thematic analysis

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.680

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.065
GPT teacher head0.404
Teacher spread0.339 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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