Are insomniacs sleepy during the day? A pupillometric assessment.

A biodevelopmental model of insomnia is articulated specifying coordinated nighttime (disturbed sleep pattern) and daytime (no excessive daytime sleepiness) characteristics defining an insomnoid classification in at-risk groups: short sleepers and older adults. Pupillometry is proposed as a useful means of discriminating degree of daytime sleepiness to aid in the differential diagnosis of insomnia and insomnoid states, and the present study tested the discriminative validity of this approach. Noninsomniac (n = 34) and insomniac (n = 29) college students submitted to four 10 min pupillometry sessions tracking daytime sleepiness from morning arising to bedtime. Pupil diameter proved to be an able discriminator of these two groups though substantial overlap of the two distributions was also noted. The results supported the sensitivity of pupillometry in detecting daytime sleepiness, but yielded alternative interpretations. We observed statistical differentiation in insomniac and noninsomniac daytime sleepiness, but substantial, functional overlap between these groups. Assessment and treatment implications arising from the biodevelopmental model were hypothesized.     

EFFECTS OF VIDEO-ASSISTED TRAINING ON EMPLOYMENT-RELATED SOCIAL SKILLS OF ADULTS WITH SEVERE MENTAL RETARDATION

Two studies investigated effects of video-assisted training on employment-related social skills of adults with severe mental retardation. In video-assisted training, participants discriminated a model's behavior on videotape and received feedback from the trainer for responses to questions about video scenes. In the first study, 3 adults in an employment program participated in video-assisted training to request their supervisor's assistance when encountering work problems. Results indicated that participants discriminated the target behavior on video but effects did not generalize to the work setting for 2 participants until they rehearsed the behavior. In the second study, 2 participants were taught to fix and report four work problems using video-assisted procedures. Results indicated that after participants rehearsed how to fix and report one or two work problems, they began to fix and report the remaining problems with video-assisted training alone.     

Wayfinding on foot from information in retinal, not optical, flow.

People find their way through cluttered environments with ease and without injury. How do they do it? Two approaches to wayfinding are considered: Differential motion parallax (DMP) is a retinal motion invariant of near and far objects moving against fixation; the information in optical flow (IOF) is a radial pattern of vectors, relying on decomposition of retinal flow. Evidence is presented that DMP guides wayfinding during natural gait, accounting for errors as well as correct responses. Evidence against IOF is also presented, and a space-time aliasing artifact that can contaminate IOF displays is explored. Finally, DMP and IOF are separated, showing they can yield different results in different environments. Thus, it is concluded that (a) DMP and IOF are different, (b) DMP and not IOF is used for wayfinding, (c) moving observers do not usually decompose retinal flow, and (d) optical flow may be a mathematical fiction with no psychological reality.     

Goal-performance relations: The effects of initial task complexity and task practice

The current study was conducted to examine the effects of task complexity and task practice (trials) on the goal-performance relationship. Specific, difficult goal assignments were predicted to enhance performance on a complex task only in later task practice. On a simpler task, specific, difficult goal assignments were predicted to enhance performance in early task practice and to disrupt performance in later task practice. The results indicated that goals exerted the predicted effects in the simple task version but had no effect in the complex task version. Possible relationships between amount of task practice and stages of skill acquisition are discussed for tasks differing in complexity. The results are also discussed in terms of cognitive resource demands and self-regulatory processes. Implications for the effectiveness of goals in relation to task complexity and task trials are also discussed.This article is based on the senior author's dissertation at the University of Minnesota. We thank Milt Hakel, Allan Jones, and Bart Osburn for their helpful comments on earlier drafts. The authors also wish to thank Phil Ackerman and John Campbell for their insightful comments throughout the research project and other members of the dissertation committee: Rich Arvey, Mark Davisson, and Marvin Dunnette.This research was partially supported by the Air Force Office of Scientific Research Project LAMP, under the auspices of the Air Force Human Resources Laboratory (contract AFOSR-87-0234) and by a Research Initiation Grant from the University of Houston.Portions of this data were presented at the American Psychological Association Meetings, Atlanta, 1988.     

Factor structure of the Treatment Evaluation Inventory: Implications for measurement of treatment acceptability

The Treatment Evaluation Inventory (TEI), a frequently used measure of treatment acceptability, was used by 164 undergraduates to rate the acceptability of each of the following treatments: differential reinforcement of other behavior, exclusionary time-out, overcorrection, medical restraint, contingent electric shock, and physical restraint. TEI ratings of each treatment type were grouped separately, variance-covariance matrices were formed and compared, and data were subjected to factor analysis. The results indicated that the factor structure of the TEI varied with the treatment it was used to evaluate. Item analysis of the TEI indicated a high degree of internal consistency, although item-total correlations varied between rated treatments. The findings suggest that although the TEI is a reliable instrument, sensitive assessment of the treatment acceptability construct probably requires multidimensional measurement.