Francis I Proctor Foundation, University of California San Francisco, San Francisco, CA, United States.
Department of Ophthalmology, University of California San Francisco, San Francisco, CA, United States.
J Med Internet Res. 2022 Jul 5;24(7):e27310. doi: 10.2196/27310.
Studies suggest diurnal patterns of occurrence of some eye conditions. Leveraging new information sources such as web-based search data to learn more about such patterns could improve the understanding of patients' eye-related conditions and well-being, better inform timing of clinical and remote eye care, and improve precision when targeting web-based public health campaigns toward underserved populations.
To investigate our hypothesis that the public is likely to consistently search about different ophthalmologic conditions at different hours of the day or days of week, we conducted an observational study using search data for terms related to ophthalmologic conditions such as conjunctivitis. We assessed whether search volumes reflected diurnal or day-of-week patterns and if those patterns were distinct from each other.
We designed a study to analyze and compare hourly search data for eye-related and control search terms, using time series regression models with trend and periodicity terms to remove outliers and then estimate diurnal effects. We planned a Google Trends setting, extracting data from 10 US states for the entire year of 2018. The exposure was internet search, and the participants were populations who searched through Google's search engine using our chosen study terms. Our main outcome measures included cyclical hourly and day-of-week web-based search patterns. For statistical analyses, we considered P<.001 to be statistically significant.
Distinct diurnal (P<.001 for all search terms) and day-of-week search patterns for eye-related terms were observed but with differing peak time periods and cyclic strengths. Some diurnal patterns represented those reported from prior clinical studies. Of the eye-related terms, "pink eye" showed the largest diurnal amplitude-to-mean ratios. Stronger signal was restricted to and peaked in mornings, and amplitude was higher on weekdays. By contrast, "dry eyes" had a higher amplitude diurnal pattern on weekends, with stronger signal occurring over a broader evening-to-morning period and peaking in early morning.
The frequency of web-based searches for various eye conditions can show cyclic patterns according to time of the day or week. Further studies to understand the reasons for these variations may help supplement the current clinical understanding of ophthalmologic symptom presentation and improve the timeliness of patient messaging and care interventions.
研究表明,一些眼部疾病的发生存在昼夜节律。利用网络搜索数据等新的信息来源来更多地了解这些模式,可以加深对患者眼部疾病和健康状况的认识,更好地确定临床和远程眼科护理的时间,并在针对服务不足人群的网络公共卫生活动中提高靶向性。
为了验证我们的假设,即公众可能会在一天中的不同时间或一周中的不同日子持续搜索不同的眼科疾病,我们使用与结膜炎等眼科疾病相关的搜索词进行了一项观察性研究。我们评估了搜索量是否反映了昼夜节律或周内模式,以及这些模式是否彼此不同。
我们设计了一项研究,使用时间序列回归模型分析和比较与眼部相关的和对照搜索词的每小时搜索数据,该模型使用趋势和周期性术语来去除异常值,然后估计昼夜效应。我们计划在 Google Trends 中设置,从 2018 年全年的 10 个美国州提取数据。暴露因素是互联网搜索,参与者是通过我们选择的研究术语使用 Google 搜索引擎进行搜索的人群。我们的主要观察指标包括周期性的每小时和每周的网络搜索模式。对于统计分析,我们认为 P<.001 为具有统计学意义。
观察到与眼部相关的术语存在明显的昼夜(所有搜索词均 P<.001)和周内搜索模式,但具有不同的高峰时间段和周期性强度。一些昼夜模式代表了之前的临床研究报告的模式。在眼部相关术语中,“红眼病”显示出最大的昼夜幅度与均值比。更强的信号局限于早晨,并在工作日达到高峰,而周末的振幅较高。相比之下,“干眼症”在周末有更高的昼夜振幅模式,更强的信号发生在傍晚到早晨的更广泛时间段,并在清晨达到高峰。
各种眼部疾病的网络搜索频率可以根据一天中的时间或周内呈现周期性模式。进一步研究了解这些变化的原因可能有助于补充当前对眼科症状表现的临床认识,并提高患者信息传递和护理干预的及时性。