French Versions of 4 English Questionnaires on Problematic Smartphone Use: Cross-Cultural Linguistic Translation and Adaptation Study
Bibliographic record
Abstract
BACKGROUND: Excessive use of smartphones is recognized as a major problem in our modern society and can have dramatic consequences on the health of adolescents and young adults. Measuring problematic smartphone use in research and clinical practice is generally operationalized with self-reported questionnaires. In order to comprehensively assess the issue of problematic smartphone usage within the French population, it is imperative to employ validated French-language questionnaires. However, at this point, existing questionnaires are primarily available in English. Furthermore, to the best of our knowledge, these English questionnaires have yet to undergo validation processes for French-speaking cohorts. OBJECTIVE: The aim of this study was to perform a cross-cultural translation of the Smartphone Addiction Scale, Nomophobia Questionnaire, Problematic Use of Mobile Phones scale, and Smartphone Addiction Proneness Scale to French. METHODS: The translation process was performed using the forward/backward method. The first translation phase involved asking 4 independent French translators to translate the original English version of the questionnaires into French. In the second phase, the French version was backtranslated to English by a native English speaker. In the third phase, 2 concept experts were asked to comment and suggest modifications to the statements if necessary. Finally, the last version of the translated questionnaires was presented to 18 participants to assess the clarity, intelligibility, and acceptability of the translations. RESULTS: During the forward translation step, the translation differences were minor. During the backward translation, the English native speaker correctly backtranslated 18 of the 33 items of the Smartphone Addiction Scale, 17 of the 20 items of the Problematic Use of Mobile Phones scale, and 13 of the 15 items of the Smartphone Addiction Proneness Scale. Backtranslation for the Nomophobia Questionnaire was less satisfactory, with only 10 out of 20 items that were correctly backtranslated. The linguistic verification step revealed a minimal modification for the 4 questionnaires. The participants also suggested few improvements that we have considered for the final version. We produced the final version directly after this step. CONCLUSIONS: We successfully adapted and effectively translated 4 questionnaires that assess problematic smartphone use to French. This step is a prerequisite for the validation of the French questionnaires. These adapted measures can serve as valuable research instruments for investigating and addressing issues related to problematic smartphone use in French-speaking countries and for making international comparisons.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".