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Record W4412496495 · doi:10.2196/63612

In-Game Need Satisfaction, Frustration, and Gaming Addiction Patterns Across Subgroups of Adolescents Through Structural Equation Modeling: Cross-Sectional and Instrument Validation Study of the Youth Gaming Experience Scales

2025· article· en· W4412496495 on OpenAlexvenueno aff
Amparo Luján-Barrera, Lydia Cervera-Ortiz, Mariano Chóliz Montañés

Bibliographic record

VenueJMIR Serious Games · 2025
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsnot available
Fundersnot available
KeywordsPreprintFrustrationStructural equation modelingPsychologyAddictionSocial psychologyComputer scienceStatisticsMathematicsWorld Wide WebPsychiatry

Abstract

fetched live from OpenAlex

Background Gaming is a prevalent activity during adolescence, a developmental stage characterized by vulnerability to gaming disorder (GD). According to the self-determination theory, gaming environments can satisfy and frustrate basic psychological needs—autonomy, competence, and relatedness—processes linked to GD. However, existing research has primarily focused on adult populations, and validated instruments assessing both in-game need satisfaction (NS) and in-game need frustration (NF) in adolescents are lacking. Objective This study aimed to address this gap by validating the Spanish version of the Basic Psychological Need Satisfaction and Frustration Scale for Gaming (BPNSFS-G) in adolescents. We examined its psychometric properties, its relationship with GD and gaming behavior, and differences in NS and NF across subgroups defined by risk factors for GD (sex, the developmental stage, and the gaming modality). Methods A total of 1174 adolescents (mean 12.07, SD 1.23; middle adolescents: 815/1174, 69.4%; male: 637/1037, 61.4%; online gamers: 388/511, 76.3%) participated in a school-based GD prevention program and completed a self-report battery, which included the adapted BPNSFS-G, a validated GD scale, and ad hoc items (daily gaming time and weekly frequency). The Spanish adaptation of the BPNSFS-G was developed using the back-translation method to ensure its content validity. A structural equation modeling approach was used to test its structural, construct, convergent, and discriminant validity, as well as measurement invariance. Reliability at both the item and factor levels, along with criterion validity, was also assessed. Results Through exploratory and confirmatory factor analyses, the scale structure was confirmed, validating 2 separate measures: a 3-factor second-order model for NS and a unidimensional model for NF, both with adequate internal consistency (NS: Cronbach α=0.75; NF: Cronbach α=0.77). The results also supported its validity, with NF more strongly associated with GD (r=0.49), and NS more closely related to gaming time (r=0.25-0.36). The scales functioned similarly across sex and developmental stage groups, but not across gaming modalities. Notably, NS showed significant differences across all subgroups, especially between boys and girls (t759.31=8.28; P<.001; g=0.55) and between online and offline gaming modes (t178.47=5.13; P<.001; g=0.58), with no meaningful differences found for NF. Conclusions This study provides initial evidence for the validity and reliability of the Spanish version of the BPNSFS-G for adolescents. The resulting Youth Gaming Experience Scales (Youth Satisfying Gaming Experience Scale and Youth Frustrating Gaming Experience Scale) are brief, theoretically grounded, and empirically supported instruments for assessing in-game psychological need satisfaction and frustration. Given NF’s potential as a risk factor, these scales have a strong potential to explore self-determination theory–based mechanisms underlying the motivational etiology of GD and to advance both its assessment and prevention in adolescent populations.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.577

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)0.0000.000

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 head0.038
GPT teacher head0.350
Teacher spread0.312 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

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