Memorial Sloan Kettering Cancer Center, Department of Psychiatry and Behavioral Sciences, 633 Third Ave, New York, NY 10017, USA.
Department of Health Outcomes and Biomedical Informatics, University of Florida College of Medicine, P.O. Box 100216, Gainesville, FL 32610, USA.
Soc Sci Med. 2024 Jun;351:116987. doi: 10.1016/j.socscimed.2024.116987. Epub 2024 May 18.
Turning Point Analysis (TPA) is a methodological approach that allows scholars to retrospectively capture change over time by identifying instances of critical change (i.e., turning points) encountered across a given time period. While TPA has been used to examine time as a variable in health and illness experiences, the use of the method in behavioral medicine scholarship may be limited by the lack of understanding of TPA procedures and applicability.
To describe how TPA has been used and enhance its accessibility by identifying and synthesizing methods of TPA data collection and analysis.
A systematic search of electronic databases, including Academic Source Premier, Psychology and Behavioral Sciences Collection, APA PsycInfo, and ProQuest Dissertation and Theses Database, was conducted in May 2020. In July 2020, we used hand searching to identify additional articles, including forward and back tracking seminal articles on TPA. Studies were screened in duplicate.
Of the 1184 studies screened for this review, we included 52. Studies used TPA to examine relational (k = 40), organizational (k = 6), and individual (k = 6) variables and included an analysis of either turning points (k = 28), the trajectories of change over time created by the turning points (k = 3), or both (k = 21). Turning points and trajectories were captured and analyzed using qualitative and quantitative analytic approaches, with most studies using either purely qualitative (k = 26) or mixed methods (k = 21).
The findings of this review provide insight into the varied applications of TPA and suggest the potential value of this methodological approach in better understanding health experiences across time. By synthesizing the procedural and analytic steps to conducting a TPA, this review could also increase the accessibility and use of TPA in behavioral medicine research.
转折点分析（TPA）是一种方法学方法，它允许学者通过识别给定时间段内遇到的关键变化（即转折点）来回顾性地捕捉随时间的变化。虽然 TPA 已被用于研究时间作为健康和疾病体验的变量，但由于对 TPA 程序和适用性缺乏了解，该方法在行为医学研究中的应用可能受到限制。
通过识别和综合 TPA 数据收集和分析方法，描述 TPA 的使用情况并提高其可及性。
我们于 2020 年 5 月对电子数据库（包括 Academic Source Premier、Psychology and Behavioral Sciences Collection、APA PsycInfo 和 ProQuest Dissertation and Theses Database）进行了系统搜索。2020 年 7 月，我们使用手工搜索来确定其他文章，包括对 TPA 的开创性文章进行前向和后向跟踪。研究由两人进行筛选。
在本次综述中，我们共筛选了 1184 项研究，纳入了 52 项研究。这些研究使用 TPA 来检验关系变量（k=40）、组织变量（k=6）和个体变量（k=6），并分析了转折点（k=28）、转折点产生的随时间变化的轨迹（k=3）或两者（k=21）。转折点和轨迹是通过定性和定量分析方法来捕捉和分析的，大多数研究使用的是纯定性方法（k=26）或混合方法（k=21）。
本综述的结果深入了解了 TPA 的各种应用，并表明该方法在更好地理解随时间变化的健康体验方面具有潜在价值。通过综合进行 TPA 的程序和分析步骤，本综述还可以提高 TPA 在行为医学研究中的可及性和使用。
