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Record W4412602304 · doi:10.2196/60752

The Added Value of Parents Practicing in Virtual Reality to Illustrate the Use of Innovative Methods in Parent-Child Interaction Therapy: Single-Case Experimental Design

2025· article· en· W4412602304 on OpenAlexvenueno aff
Iza C A Scherpbier, Mariëlle E. Abrahamse, Samantha Bouwmeester, Robert G. Belleman, Arne Popma, Ramón Lindauer

Bibliographic record

VenueJMIR Pediatrics and Parenting · 2025
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsnot available
FundersMinisterie van Volksgezondheid, Welzijn en Sport
KeywordsPaceIntervention (counseling)PopulationPsychologyDevelopmental psychologyClinical psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Throughout years of research, the well-known behavioral parent training program, Parent-Child Interaction Therapy (PCIT), has been adapted and enhanced to tailor the treatment to the needs of families in community-based clinical care. This study wished to evaluate an add-on to PCIT that could be engaging for parents. As a way to enlarge practice opportunity and potentially allow parents to achieve positive treatment effects sooner, this study added virtual reality (VR) to PCIT. OBJECTIVE: This study aimed to increase positive parenting skills at a faster pace with the use of PCIT-VR, on the basis that practicing positive parenting skills in the VR tool would increase parents' overall practice time, thus leading to more confidence in their skills, which could consequently increase the pace of skill acquisition. Furthermore, we hypothesized that due to the overall increase in positive parenting skills, PCIT treatment effects such as diminishment of child disruptive behavior and parenting stress would decrease at a faster pace when VR was introduced. METHODS: Families were recruited from a specialized child and adolescent psychiatry clinical practice in the Netherlands. Using a single-case experimental design, 11 families, equating to 18 participants, signed informed consent forms and received the staggered introduction of VR to treatment. As is common with a single-case experimental design, visual inspection analyses and randomization tests were conducted. Group differences were evaluated with nonparametric tests and reliable change indices. RESULTS: Overall, our study reaffirmed that PCIT is an effective intervention for this population as there were positive treatment effects found in almost all cases. Nevertheless, there did not seem to be a clear relationship between the use of the VR tool and PCIT treatment effects, although positive parenting skills seemed to increase when VR was introduced to treatment for some parents. For all parents, questions and comments decreased with the introduction of VR. These findings tentatively suggest that practicing with VR could potentially increase positive parenting skills and also have an impact on other treatment-related outcomes, such as child disruptive behavior and parenting stress. CONCLUSIONS: This was the first time that PCIT has been supplemented with VR. We provide preliminary evidence of its added value. We cautiously suggest that VR could provide added value to PCIT and increase confidence in parenting skills for certain parents, although there are complex factors that play into treatment success that must simultaneously be considered. These factors include parents having the motivation and mental capacity to change and the complex psychological problems some families face. Although promising, we believe that due to the novelty of our VR practice tool and the variety of results from our study, more research is necessary into PCIT-VR to draw further conclusions on its effects.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.198
GPT teacher head0.425
Teacher spread0.227 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2025
Admission routes1
Has abstractyes

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