Public interest data for the search term “CO2 laser” in Germany were retrieved using Google Trends. To ensure dermatological relevance and exclude industrial applications, the query was restricted to the “Health” category (Category ID: 45). The study period covered six full calendar years, from January 1, 2020, to December 31, 2025. As the dataset consists of aggregated and anonymized search volumes, the study did not involve human subjects and was exempt from institutional review board approval.

To address the autocorrelation inherent in time-series data and isolate underlying patterns, a Seasonal-Trend decomposition (STL) using LOESS (locally estimated scatterplot smoothing) was applied. This method decomposed the monthly normalized search volume (NSV) into three distinct components: the long-term trend, seasonal variation, and residual noise. The long-term trajectory was evaluated using ordinary least squares linear regression performed on the extracted trend component to calculate the monthly rate of change and its 95% CI. Seasonal variation was quantified by averaging the seasonal component across the six-year period to identify recurring monthly peaks and troughs. All statistical tests were two-tailed, with a significance threshold of α=.05. For regional analysis, the “Interest by Region” output was exported as a single dataset for the entire period (2020‐2025) to ensure consistent normalization across all 16 federal states.

All analyses and visualizations were conducted using Python (version 3.11). Data processing was performed with Pandas and NumPy. Time-series decomposition was executed using the Statsmodels library. Statistical regressions were calculated via SciPy. For geospatial visualization, a high-resolution GeoJSON file of German state borders was merged with the search data using GeoPandas. Regional interest was represented as a choropleth map using the Matplotlib library, with federal states labeled using official two-letter abbreviations.

This study used publicly accessible, fully anonymized, and aggregated search volume data provided by Google Trends. As the research did not involve human subjects, clinical interventions, or the collection of any personally identifiable information, institutional review board approval and informed consent were not required in accordance with local and institutional guidelines.

The longitudinal analysis of search interest for the search term “CO2 laser” in Germany—filtered by the “Health” category to ensure medical relevance reveals a significant and sustained upward trajectory (Figure 1). By applying STL LOESS, the underlying long-term trend was isolated from seasonal noise and residuals, confirming that the growth is not merely a byproduct of transient spikes.

During the initial phase of the study (2020‐2021), the trend component remained at a stable baseline, with annual mean NSV values increasing from 15.0 to 20.6. A more pronounced transition occurred in mid-2022, marking the beginning of a continuous growth phase that reached its peak in 2025 with an annual mean of 68.1 NSV. This represents a total increase in sustained public interest of 354% compared to the 2020 baseline. Linear regression analysis of the isolated trend component confirmed the high statistical significance of this growth (Slope=0.87 NSV/month; 95% CI 0.83‐0.92; R²=.96; P<.001).

Complementing this long-term growth, a robust and recurring seasonal rhythm was identified. While Figure 1 (bottom panel) shows the consistency of these waves over time, Figure 2 illustrates the averaged seasonal deviations to highlight the typical annual cycle. Public interest follows a predictable pattern characterized by a “winter peak” and a “summer nadir.” Information-seeking behavior typically reaches its zenith in January (+13.8 NSV units) and February (+12.6 NSV units).

In contrast, interest consistently declines as annual UV radiation increases, reaching its lowest levels in August (–14.4 NSV units). This seasonal component remained highly consistent across the six-year period, with statistical analysis confirming that these monthly variations are non-random (P<.001), likely reflecting clinical recommendations to avoid laser treatments during periods of high solar exposure.

Annual mean normalized search interest is summarized in Figure 3. The data demonstrate a continuous increase in public attention toward “CO2 laser” in Germany throughout the six-year observation period.

The annual average was lowest in 2020 (15.0) and increased incrementally in each subsequent year: 20.6 in 2021, 25.2 in 2022, 37.8 in 2023, 48.7 in 2024, and 68.1 in 2025. These absolute values correspond to year-over-year increases of 37% (2020‐2021), 22% (2021‐2022), 50% (2022‐2023), and 29% (2023‐2024). By 2025, search interest reached a total increase of 354% compared to the 2020 baseline.

To quantify the overall trajectory while accounting for seasonality, a linear regression was performed on the monthly trend component. The model estimated a monthly increase of 0.87 units (95% CI 0.83‐0.92; R²=.96; P<.001), confirming a robust and well-fitting linear upward trend over the multi-year period. These findings indicate that the rise in interest reflects a sustained long-term development in population-level information-seeking behavior rather than transient search spikes.

Analysis of state-level search interest for the 2020‐2025 period, revealed distinct regional concentrations of public attention toward CO2 laser treatments (Figure 4). The results indicate that search activity is most pronounced in major metropolitan regions. The highest search volumes were recorded in the city-states of Berlin (NSV 100) and Hamburg (NSV 96), followed by the populous states of Hesse (NSV 64) and North Rhine-Westphalia (NSV 64).

This study used Google Trends data for “CO₂ laser” in Germany (2020 – 2025) in the category „Health“ as a real-time proxy for public interest in this dermatologic procedure. Two robust patterns emerged: (1) a 354% sustained rise in the baseline trend component, increasing from a mean of 15.0 in 2020 to 68.1 in 2025 (Slope=0.87; 95% CI 0.83‐0.92; P<.001) and (2) a predictable seasonal rhythm peaking in winter and reaching its nadir in summer.

Search-based infodemiology has repeatedly been shown to mirror real-world utilization of esthetic interventions [10-12]. Our upward trend corroborates earlier global observations by Tijerina et al [12] who reported growing interest in CO₂-laser resurfacing over time [12]. The summer trough aligns with routine clinical practice, where CO₂-laser treatments are avoided during periods of high UV exposure because of pigmentary risk; this concordance further validates Google Trends as a behavioral signal. From an operational perspective, the yearly rebound that starts each September implies that public-facing education or advertising campaigns could be most effective when launched in late summer.

While an immediate surge in search interest might have been expected during the initial COVID-19 lockdowns in 2020, our data indicate a more sustained upward trajectory that intensified later in the study period. This temporal alignment provides a compelling contextual hypothesis for the „Zoom effect“. the theory that heightened self-scrutiny during frequent videoconferencing acts as a catalyst for esthetic interest.

Survey-based research supports this possibility, with over half of respondents attributing increased interest in cosmetic procedures to videoconferencing, and two-thirds reporting habitual self-observation on screen [10,11]. However, it is important to note that without a formal interrupted time series analysis to identify a specific step change, this link remains speculative. The observed growth likely reflects a complex interplay between the „Zoom effect“ and a broader, pre-existing trend toward minimally invasive esthetic treatments.

Social-media ecosystems likely amplify these dynamics. Platforms such as TikTok and Instagram serve simultaneously as marketing channels and informal information sources; their algorithmic curation immerses users in procedure-related content, reinforcing norms and sustaining interest [5]. Such amplification may intensify both the secular growth and the seasonal peaks identified here.

Further social media platforms increasingly function as both promotional channels and informal information sources for not only esthetic procedures. Algorithm-driven content delivery creates personalized environments where users are repeatedly exposed to procedure-related imagery, reinforcing interest and perceived norms. This algorithmic amplification may contribute to sustained search activity and intensify seasonal peaks observed in our data.

This study has several limitations inherent to the use of Google Trends data. First, the platform provides normalized search volumes without absolute user counts, limiting the ability to quantify population-level interest. Second, demographic details (eg, age, gender) are unavailable, restricting subgroup analysis. Most importantly, it is essential to distinguish between online search interest and actual clinical treatment uptake. The observed increase in search volume reflects heightened public curiosity and information-seeking behavior, rather than a direct measure of performed procedures.

Google search behavior offers a reliable lens on public interest in CO₂-laser resurfacing, capturing both long-term growth and cyclical demand. This increasing digital curiosity heightens the need for rigorous practitioner training, regulatory oversight, and evidence-based patient education to ensure that online interest translates into safe, informed clinical decisions and mitigates potential complications.