Effects of the High-Probability Request Procedure: Patterns of Responding to Low-Probability Requests

被引:0
|
作者
Jennifer J. McComas
David P. Wacker
Linda J. Cooper
Stephanie Peck
Zbigniew Golonka
Thomas Millard
David Richman
机构
[1] The University of Iowa,
关键词
high-probability requests; noncompliance; behavioral momentum; stimulus control; behavioral pediatrics;
D O I
暂无
中图分类号
学科分类号
摘要
The effects of high probability (high-p) requests on compliance with low-probability (low-p) responses have received increasing attention in investigations aimed at increasing compliance. Differential effects of high-p treatments and at least three distinct patterns of responding to low-p requests have been presented in recent literature. We present a series of case studies with three children who had developmental disabilities and who displayed severe noncompliance. The effects of high-p treatments across several topographies of behavior in a variety of settings are representative of the three patterns presented in recent literature. In Pattern 1, increased compliance to low-p requests was most likely when compliance with high-p requests immediately preceded the low-p requests. In Pattern 2, compliance with low-p requests initially occurred differentially immediately following compliance with high-p requests, but across sessions these effects were sustained in the absence of the high-p requests. In Pattern 3, compliance with high-p requests did not result in compliance with subsequent low-p requests and compliance to high-p requests also decreased across sessions. This paper provides case illustrations of these patterns, a discussion of hypotheses regarding the basis for these differential effects, and implications for future analyses involving high-p procedures.
引用
收藏
页码:157 / 171
页数:14
相关论文
共 50 条
  • [41] Increasing compliance of children with autism: Effects of programmed reinforcement for high-probability requests and varied inter-instruction intervals
    Pitts, Laura
    Dymond, Simon
    [J]. RESEARCH IN AUTISM SPECTRUM DISORDERS, 2012, 6 (01) : 135 - 143
  • [42] High-Probability Request Sequence: An Evidence-Based Practice for Individuals with Autism Spectrum Disorder
    Brosh, Chelsi R.
    Fisher, Larry B.
    Wood, Charles L.
    Test, David W.
    [J]. EDUCATION AND TRAINING IN AUTISM AND DEVELOPMENTAL DISABILITIES, 2018, 53 (03) : 276 - 286
  • [43] Processing of low-probability sounds by cortical neurons
    Ulanovsky, N
    Las, L
    Nelken, I
    [J]. NATURE NEUROSCIENCE, 2003, 6 (04) : 391 - 398
  • [44] Dynamics in risk taking with a low-probability hazard
    Royal, Andrew
    [J]. JOURNAL OF RISK AND UNCERTAINTY, 2017, 55 (01) : 41 - 69
  • [45] Neural network learning of low-probability events
    Munro, DJ
    Ersoy, OK
    Bell, MR
    Sadowsky, JS
    [J]. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 1996, 32 (03) : 898 - 910
  • [46] Opportunity Neglect: An Aversion to Low-Probability Gains
    Prinsloo, Emily
    Barasz, Kate
    John, Leslie K.
    Norton, Michael, I
    [J]. PSYCHOLOGICAL SCIENCE, 2022, 33 (11) : 1857 - 1866
  • [47] MOTIVATIONAL EFFECTS OF SMOKED MARIJUANA - BEHAVIORAL CONTINGENCIES AND LOW-PROBABILITY ACTIVITIES
    FOLTIN, RW
    FISCHMAN, MW
    BRADY, JV
    BERNSTEIN, DJ
    CAPRIOTTI, RM
    NELLIS, MJ
    KELLY, TH
    [J]. JOURNAL OF THE EXPERIMENTAL ANALYSIS OF BEHAVIOR, 1990, 53 (01) : 5 - 19
  • [48] High-Probability Mutation in Basic Genetic Algorithms
    Croitoru, Nicolae-Eugen
    [J]. 16TH INTERNATIONAL SYMPOSIUM ON SYMBOLIC AND NUMERIC ALGORITHMS FOR SCIENTIFIC COMPUTING (SYNASC 2014), 2014, : 301 - 305
  • [49] Human behavior in the context of low-probability high-impact events
    Sundh, Joakim
    [J]. HUMANITIES & SOCIAL SCIENCES COMMUNICATIONS, 2024, 11 (01):
  • [50] Can Overconfidence be Debiased by Low-Probability/High-Consequence Events?
    Li, Shu
    Li, Jin-Zhen
    Chen, Yi-Wen
    Bai, Xin-Wen
    Ren, Xiao-Peng
    Zheng, Rui
    Rao, Li-Lin
    Wang, Zuo-Jun
    Liu, Huan
    [J]. RISK ANALYSIS, 2010, 30 (04) : 699 - 707