重新思考预防自杀的研究 - 超越传统的统计学意义
Beth Ann Griffin1, Gabriel W Hassler1, Arielle H Sheftall2
1Economics, Statistics, and Sociology Department, RAND, Arlington, VA, USA.
Crisis
|February 19, 2025
概括
研究人员应该公布在预防自杀方面的微不足道发现,以推进有效的干预措施. 过度依赖严格的统计截止值阻碍了这一关键公共卫生领域的进展.
科学领域:
- 公共卫生 公共卫生
- 精神病学是一个精神病学.
- 统计学方法论 统计学方法论
背景情况:
- 自杀预防研究取得了有限的进展,尽管全球存在重大关注.
- 传统的依赖p < .05的统计学意义可能会掩盖有希望的,虽然边际的发现.
- 领先的期刊和统计机构主张持续的p值解释,但在自杀研究中采用速度很慢.
研究的目的:
- 倡导更大的开放性,发表在自杀预防研究中微不足道的重要发现.
- 鼓励采用连续的p值解释来更好地评估证据的强度.
- 通过突出潜在有效的干预措施,加速预防自杀的实际进展.
主要方法:
- 本研究提出了一个概念论证,并呼吁研究界采取行动.
- 它回顾了自杀预防期刊中统计报告的当前做法.
- 它引用了美国统计学会关于p值解释的建议.
主要成果:
- 过度依赖传统的统计学意义值 (p < .05) 可能会限制潜在有益的自杀预防策略的可见性.
- 边际显著的发现,当连续考虑时,可以为临床决策和进一步研究提供有价值的见解.
- 大多数自杀预防期刊没有明确的政策来评估使用连续p值的证据强度,研究人员还没有广泛采用这种方法.
结论:
- 在预防自杀的研究中,对统计学意义采取更灵活的方法至关重要.
- 发表和考虑边际显著的结果可以促进创新,加快有效干预措施的发展.
- 自杀研究人员和期刊需要更多地采用连续的p值解释,以改善临床益处和实际进展.
更多相关视频
07:31Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
7.0K
06:42Continuous Theta Burst Stimulation of the Posterior Medial Frontal Cortex to Experimentally Reduce Ideological Threat Responses
Published on: September 28, 2018
11.6K
相关概念视频
01:50Statistical Significance
20.1K
Once data is collected from both the experimental and the control groups, a statistical analysis is conducted to find out if there are meaningful differences between the two groups. A statistical analysis determines how likely any difference found is due to chance (and thus not meaningful). In psychology, group differences are considered meaningful, or significant, if the odds that these differences occurred by chance alone are 5 percent or less. Stated another way, if we repeated this...
20.1K
01:20Comparing the Survival Analysis of Two or More Groups
122
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
122
01:04Significance Testing: Overview
3.3K
Significance testing is a set of statistical methods used to test whether a claim about a parameter is valid. In analytical chemistry, significance testing is used primarily to determine whether the difference between two values comes from determinate or random errors. The effect of a particular change in the measurement protocol, analyst, or sample itself can cause a deviation from the expected result. In the case of a suspected deviation/outlier, we need to be able to confirm mathematically...
3.3K
01:52Regression Toward the Mean
6.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.3K
01:15Assumptions of Survival Analysis
84
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
84
01:23Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
112
Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
112