Biased probability estimates in trait anxiety and trait depression are unrelated to biased availability

心理学 特质 焦虑 特质焦虑 萧条(经济学) 集合(抽象数据类型) 临床心理学 精神科 计算机科学 宏观经济学 经济 程序设计语言
作者
Robert W. Booth,Dinkar Sharma
出处
期刊:Journal of Behavior Therapy and Experimental Psychiatry [Elsevier]
卷期号:73: 101672-101672 被引量:5
标识
DOI:10.1016/j.jbtep.2021.101672
摘要

People high in trait anxiety or depression overestimate the probability of negative events, and underestimate the probability of positive events, relative to people low in trait anxiety and depression. Although this probability bias may be fundamental to some emotional disorders, its causes are not well understood. The dominant explanations are based on the availability heuristic: people relatively high in anxiety or depression find it relatively easy to imagine reasons why bad things might happen to them, and this affects their probability estimates. We tested, for the first time, whether individual differences in the availability of such reasons mediate the relationships between trait anxiety or depression and probability bias, in a nonclinical sample.Two hundred and seventy-eight undergraduates generated reasons why a set of positive and negative events might vs. might not happen to them, before rating those events' probability and potential impact on their lives.Individual differences in the availability of reasons why good and bad events might vs. might not happen did not mediate the sizeable relationships between trait anxiety and probability bias, and between trait depression and probability bias; these relationships remained significant when availability was controlled. Results for the impact of events ('cost bias') were less clear.Replication with patient groups would be invaluable; different operationalisations of availability may change the results.Availability can influence probability estimates, but it does not explain why we see probability bias in people with high trait anxiety or depression.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
小黄豆完成签到,获得积分10
1秒前
沟通亿心完成签到,获得积分10
1秒前
jacobian完成签到,获得积分10
3秒前
量子星尘发布了新的文献求助10
4秒前
fuluyuzhe_668完成签到,获得积分10
4秒前
4秒前
怎么办完成签到 ,获得积分10
4秒前
天玄完成签到 ,获得积分10
4秒前
spinon完成签到,获得积分10
5秒前
gougou发布了新的文献求助10
5秒前
5秒前
苏素完成签到,获得积分10
6秒前
DrLin完成签到 ,获得积分10
6秒前
彼方完成签到,获得积分10
6秒前
小胖wwwww完成签到 ,获得积分10
6秒前
杨丽完成签到,获得积分10
6秒前
8秒前
8秒前
MrChew完成签到 ,获得积分10
8秒前
9秒前
9秒前
9秒前
科研通AI6应助科研通管家采纳,获得10
9秒前
CipherSage应助科研通管家采纳,获得10
9秒前
大模型应助科研通管家采纳,获得10
9秒前
Savitr发布了新的文献求助10
9秒前
木康薛完成签到,获得积分10
10秒前
黄鹂完成签到,获得积分10
10秒前
阿呷惹完成签到,获得积分10
12秒前
scarlet完成签到 ,获得积分10
13秒前
俏皮诺言发布了新的文献求助10
13秒前
清脆的秋寒完成签到,获得积分10
14秒前
果茶去冰完成签到 ,获得积分10
14秒前
momoni完成签到 ,获得积分10
14秒前
天明完成签到,获得积分10
15秒前
蕉鲁诺蕉巴纳完成签到,获得积分0
15秒前
迟宏珈完成签到,获得积分10
15秒前
啦啦啦123完成签到,获得积分10
15秒前
量子星尘发布了新的文献求助10
16秒前
量子星尘发布了新的文献求助10
16秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Clinical Microbiology Procedures Handbook, Multi-Volume, 5th Edition 2000
The Cambridge History of China: Volume 4, Sui and T'ang China, 589–906 AD, Part Two 1000
The Composition and Relative Chronology of Dynasties 16 and 17 in Egypt 1000
Russian Foreign Policy: Change and Continuity 800
Real World Research, 5th Edition 800
Qualitative Data Analysis with NVivo By Jenine Beekhuyzen, Pat Bazeley · 2024 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5715621
求助须知:如何正确求助?哪些是违规求助? 5235764
关于积分的说明 15274658
捐赠科研通 4866353
什么是DOI,文献DOI怎么找? 2612926
邀请新用户注册赠送积分活动 1563081
关于科研通互助平台的介绍 1520565