ABSTRACT The increasing global prevalence of myopia has prompted increased efforts to identify, quantify, and modify risk factors associated with its onset and progression. Myopia risk factors can be broadly categorized into four areas: (1) genetics and inheritance, (2) demographics, (3) ocular metrics, and (4) environmental and behavioral influences. Environmental and behavioral factors, including near work, screen time, light exposure, and outdoor activity, are increasingly recognized as modifiable contributors, and therefore, offer promise as prevention strategies. However, inconsistencies across studies regarding their contribution highlight the challenges of subjective data collection and population variability. This review aims to equip researchers, clinicians, and public health professionals with a comprehensive understanding of available tools to quantify myopia risk factors and their applications in research and clinical practice. Traditional and emerging methods for quantifying environmental and behavioral risk factors for myopia are critically evaluated. First, subjective methods, including questionnaires, diaries, and experience sampling, are discussed, and their practical advantages and inherent limitations, such as recall bias and low temporal resolution, are highlighted. Further, objective approaches, enabled by advances in wearable technology, including light sensors, rangefinders, and integrated devices, are explored. The capabilities and constraints of currently available tools, future directions for wearable innovations, and necessary analytical techniques are considered. Improving the precision and standardization of these measurements will enhance the ability of researchers and clinicians to detect myopia risk early, tailor interventions, and develop evidence‐based guidelines for myopia control.
Lisa A. Ostrin (Thu,) studied this question.