1. Longitudinal Self‑Tracking of Masturbation Frequency, 1957–2025

This dataset documents the annual masturbation frequency of a single adult individual over a period of 69 years (1957–2025). The data were collected manually and continuously and include, for each year, the individual’s age, the number of masturbation events, and the cumulative total since the beginning of the record. The dataset is fully anonymized and contains no personal information other than age, which is necessary for scientific analysis.The dataset provides a rare long‑term perspective on individual sexual behavior across the adult lifespan. Its continuous and consistent structure makes it suitable for analyzing long‑term trends, age‑related patterns, and intra‑individual developmental trajectories. The data are relevant for research in sexual science, gerontology, psychology, behavioral science, and health sciences.The dataset is organized in a clear tabular format and can be directly processed in statistical software such as R, Python, SPSS, or Stata. A detailed README file is included, describing variable definitions, methodology, data cleaning procedures, strengths, limitations, and potential use cases. The dataset represents a unique single‑case longitudinal record and offers valuable insights that are often not visible in population‑based studies.本数据集记录了一名成年个体在1957年至2025年共计69年期间的年度自慰频率。数据以人工方式持续采集，每年记录该个体的年龄、自慰事件发生次数，以及自记录起始以来的累计次数。本数据集已完全匿名化，仅包含科学分析所需的年龄信息，无其他个人身份信息。该数据集为研究成年生命周期内的个体性行为提供了罕见的长期视角，其结构连续且统一，适用于分析长期趋势、年龄相关模式以及个体内部发展轨迹。该数据可用于性科学、老年学、心理学、行为科学与健康科学领域的研究。本数据集采用清晰的表格格式组织，可直接在R、Python、SPSS及Stata等统计软件中进行处理。数据集附带详细的README文件，说明变量定义、采集方法、数据清洗流程、优势、局限性以及潜在应用场景。本数据集是一份独特的单案例纵向记录，能够提供基于人群的研究通常无法展现的宝贵研究视角。