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Record W4281650677 · doi:10.2196/34476

Co-creation of a Serious Game About Radiotherapy: Participatory Action Research Study With Children Treated for Cancer

2022· article· en· W4281650677 on OpenAlexvenueno aff
Catarina Cederved, Jon Back, Charlotte Ångström-Brännström, Gustaf Ljungman, Gunn Engvall

Bibliographic record

VenueJMIR Human Factors · 2022
Typearticle
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsnot available
FundersUppsala UniversitetBarncancerfonden
KeywordsThematic analysisParticipatory action researchCitizen journalismTheme (computing)Action (physics)Qualitative researchPsychologyMedical educationMedicineComputer scienceSociologySocial science

Abstract

fetched live from OpenAlex

BACKGROUND: Children with cancer who have to undergo radiotherapy can experience fear, because they have no prior knowledge of the treatment. One way of teaching children about the treatment and reducing their fear is to prepare them for it through serious games. Involvement of the end user in the design process within medicine is a way of ensuring that the product being developed will fit the intended user. OBJECTIVE: The aim was to outline the contributions made by children and their parents through participatory action research when designing a serious game about radiotherapy. METHODS: By means of participatory action research, children and their parents participated in the development of a serious game about radiotherapy. Nine children (7-10 years old) were included, each with an accompanying parent. A qualitative approach was used that included interviews and participant observation. Six rounds of iterative development process were used with the children and their parents. Meetings with the children were held either face-to-face or online. Each round resulted in a list of suggestions for changes to the game. A thematic analysis was performed based on the list of proposed changes, underpinned by all gathered data, to highlight how the children's participation changed the game. RESULTS: Two main themes were identified. The first theme was "The children's participation was affected by their health and treatment" and included the following subthemes: "an opportunity to share emotions and perceptions of radiotherapy" and "the possibility to participate was affected by the severity of the disease." The second theme was "participation allowed becoming an active part of game development" and included the following subthemes: "the opportunity to express sentiments about the game," "the emergence of a playable game through the children's contributions," and "the necessity of understanding the text." CONCLUSIONS: The method used in this study made the children active participants, and our results suggest that this method can be used by health care researchers to cocreate serious games with children. It is necessary to inform the children involved that the process takes time, and that the process can be altered to allow as much participation as possible without placing a burden on them. The children's illness affected their possibility to take part; thus, it is crucial to accommodate the children's needs when conducting similar studies. The parents' participation facilitated the meetings for their children, even though their involvement in the game design was negligible.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.135
GPT teacher head0.503
Teacher spread0.368 · 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.

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

Citations12
Published2022
Admission routes1
Has abstractyes

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