Evaluating the Acceptability of AI-Personalized Virtual Reality Picture Books for Hospitalized Pediatric Patients (LLM-audiobook)

Kokeellinen: Pediatric patient

Käyttäytyminen: LLM-audiobook

Develop and refine a two-stage personalization LLM pipeline: (1) a structured brief interview template and (2) an LLM prompt chain for content generation. The interview instrument will be a structured guide (~20 minutes) capturing details about the child's background, interests, and aspirations. All information collected during the interview will be deidentified prior to being passed into the LLM.

Content Generation: Deidentified interview responses will be input to a standardized LLM prompt pipeline. The pipeline generates a structured patient profile that interprets the participant's interests, personality, and preferences, then uses that profile to produce a personalized narrative, formatted as a picture book story. AI voice synthesis will generate an audio narration of the story. AI image generation tools will produce a set of 6-10 accompanying illustrations. The final product - a synchronized audio picture book - will be delivered via VR headset at bedside.

Determine the acceptability of the Large Language Model generated audiobook

Semi-structured focus group interviews conducted in person immediately after intervention. Six core questions plus probing prompts assessing attitudes and opinions, and perceptions of the intervention experience

To assess the degree to which participants identified with the protagonist of the personalized audio picture book.

Participants will complete the Cohen Identification Scale following the VR experience.

Items are answered using a 5-point Likert scale ranging from 1 = strongly disagree to 5 = strongly agree. Item responses will be averaged to generate a composite score, with higher scores indicating greater identification with the main character.

To assess emotional state using Positive and Negative Affect Schedule - Child Form (PANAS-C)

The PANAS-C measures the degree to which children experience positive and negative affective states, yielding two subscale scores: Positive Affect and Negative Affect. Items are answered using a 5-point Likert scale ranging from 1 = very slightly or not at all to 5 = extremely. Higher Positive Affect (PA) Score indicates a higher level of positive emotions while higher Negative Affect (NA) Score indicates a higher level of negative emotions.

To assess subjective wellbeing using the World Health Organization-Five Child Well-Being Index (WHO-5)

The WHO-5 is a brief, validated self-report measure assessing current mental wellbeing across five positively worded items covering mood, relaxation, energy, rest, and daily interest. The WHO-5 instructs respondents to rate how they have felt "over the last two weeks,"; the scale will be modified in this study to ask the participants to reflect on their current state. Items are answered using a 5-point Likert scale ranging from 0 = never to 5 = all of the time. To calculate the overall wellbeing score, the responses to the five items are summed and the total is multiplied by 5, yielding a final score between 0 and 100. Higher scores reflect higher levels of wellbeing.