Public Interest in Limb Lengthening Procedures: a Google Trend Analysis

Detailed Description This retrospective observational time-series study analyzes publicly available, aggregated, and fully anonymized Google Trends data to characterize online search interest in limb-lengthening surgery and cosmetic stature augmentation across four English-speaking countries (United States, United Kingdom, Canada, Australia) between January 1, 2015, and July 19, 2025.

Keyword identification: An initial seed set of five terms ("limb lengthening," "limb lengthening surgery," "surgery for height," "lengthening surgery," "height increase surgery"), drawn from prior published work (Gomez-Alvarado et al.), was expanded using the SEO platform Semrush (Keyword Magic Tool). Each seed term was searched separately per country in May 2025, and the top 10 keywords by average monthly search volume (trailing 12-month Semrush data) were extracted per seed term per country, yielding 200 candidate keyword entries (50 per country). Candidates were then screened in country-specific Google Trends searches (Jan 1, 2015-Jul 19, 2025; category "All"; search type "Web Search") and retained if relevant to limb-lengthening/cosmetic stature terminology, showed measurable trend data, and ranked among the most consistent high-interest terms across all four countries; terms were excluded for low ranking, insufficient data, or irrelevance (e.g., penile or dental crown lengthening). Six final terms were retained: "limb lengthening," "leg lengthening," "leg lengthening surgery," "height surgery," "limb lengthening surgery," "lengthening surgery." A combined query using the Google Trends "+" operator was also generated. The full candidate keyword bank and screening rationale are provided as Supplementary Table S1; the exact combined query string as Supplementary Table S2.

Related queries: For each of the six terms, Google Trends "Top" and "Rising" related queries were recorded separately by country, each carrying a relative popularity score (0-100). Related queries were manually grouped into descriptive themes (cost, safety/complications, online forum/Reddit discussion, medical tourism, general procedure information) based on wording and content. The full coded list is provided as Supplementary Table S3.

Data source and extraction: Raw exported Google Trends time-series CSV files for all search terms and countries are provided as supplementary material for transparency and reproducibility. No individual-level, demographic, or identifiable data were accessed at any stage; Google Trends provides only aggregated, anonymized relative search volume (RSV) indices normalized to a 0-100 scale within each queried context.

Statistical analysis plan: Monthly RSV values were summarized descriptively (mean, SD, median, IQR, minimum, maximum) by country and search term. Spearman's rank correlation was used to assess (i) the temporal trend between calendar month (coded 1-127) and monthly RSV for each term within each country, and (ii) pairwise correlations between the six search terms within each country (15 pairwise comparisons per country; 60 total across all four countries). Zero RSV values were retained as valid observations; tied ranks were handled using standard Spearman methodology. All tests were two-tailed with significance set at p<0.05; given the number of comparisons performed, results were treated as exploratory and p-values interpreted cautiously rather than adjusted for multiplicity.

Applicability of patient-registry quality elements: This study does not constitute a patient registry. It involves no recruitment, enrollment, or follow-up of individual human participants, and no patient-level data of any kind are collected, stored, or analyzed. Accordingly, the following registry-specific elements are not applicable to this protocol: quality assurance/site monitoring plan, data validation/range-check procedures against a registry database, source data verification against medical records or case report forms, a participant-level data dictionary, standard operating procedures for patient recruitment or adverse event reporting, and formal sample size/power calculation (the "sample" here is the full available Google Trends time series for each term and country, not a recruited cohort). A plan for missing data is nonetheless addressed: where Google Trends returned insufficient or non-measurable data for a candidate term, that term was excluded during the keyword-screening stage (per the criteria above) rather than imputed, and no missing-data imputation was performed on the retained time series.