Effects of spatial disorientation on cognitive processing - 2010

Disorientation and cognition

Webb et al (20101) carried out research into the effects of spatial disorientation on the cognitive processing ability of United States army helicopter pilots. This study examined how spatial disorientation affects working memory and mathematical ability during simulated flight.

Illustration 1 show the results. Spatial disorientation has an effect on working memory in terms of span length, reducing the mean length from 7 to 6 digits. Spatial disorientation has no significant effect on reaction time for the working memory test.

Illustration 1
Flight condition Digit span test Addition task test
Accuracy2 Reaction time3 Accuracy4 Reaction time3
Oriented 7.0 1.22 90 1.25
Oriented in-formation 7.0 1.13 89 1.13
Disoriented in-formation 5.9 1.25 72 1.52

Spatial disorientation has a very significant effect on mathematical ability reducing mean test accuracy from 90% to 72% when disorientated. Spatial disorientation also has a significant effect on reaction time for the mathematical ability test increasing reaction time when disoriented.

The results of this study confirm those of the earlier research, indicating that spatial disorientation does adversely affect cognitive processing ability.


Research approach

Exploratory research performed in a flight simulator, using quantitative research methodology. The research measured how being spatially disorientated effects pilots cognitive abilities, during simulated flight.


Thirty-six United States Army Sikorsky UH-60 helicopter pilots were chosen using convenience sampling, their average age was 29.9 years. The vast majority of the participants (32) were male. Only 4 participants were female. The participants had a median flight time of 190 hours, and were made up from the following ranks;
Line pilots - 75% (flying regularly)
Instructors – 17% (assumed to be both flying and instructing)
Staff Officers – 8% (Not regularly flying)
To reduce the effect of extraneous variables all the participants underwent pretest medical screening.


A repeated measures, within subjects design. Presentation of the various flight profiles was randomized to reduce possible order effects. The article does not however mention whether any counterbalancing or Latin square methodology was used, meaning some order effects may remain


  • Dependent variables (DV): The participant’s response time to, and the accuracy of their cognitive tests.
  • Independent variables (IV): The three different levels of flight condition; Orientated flight, Orientated and in-formation flight, and disorientated and in-formation flight.
  • Confounding variables:
  • Workload - The orientated in-formation condition is included to expose any potential confounding effects of workload on spatial disorientation.
  • Simulator sickness - Participants completed a likert type scale sickness questionnaire after exiting the simulator. This enabled researchers to rule out simulator sickness effects on performance.


  • Simulated flights using the United States army aeromedical research laboratory’s NUH-60 research flight simulator.
  • The simulators research data acquisition system (RDAS) was used to record flight data with specific emphasis on control reversal errors, as a sign of disorientation.
  • Cognitive tests consisting of a forward digit span task to assess working memory, and an addition task to assess mathematical functioning.
  • A Likert type scale simulator sickness questionnaire


The study took place over two days. Day 1 involved medical screenings, and other administrative tasks. On day 2 the participants received 3 practice runs at each of the two cognitive tests. Each participant then underwent a 75-minute simulated flight during which they completed 6 separate and randomized flight sequences consisting of 2 orientated situations, 2 orientated and in-formation situations and 2 disorientated in-formation situations. Administration of one of the two cognitive tests began once the participant was established in the applicable flight situation. Both of the orientated situations were performed using full motion simulation; the disorientated situation was performed with motion off. After the experiment participants completed a simulator sickness questionnaire.

Data analysis

  • IBM SPSS Statistics software was used for all statistical analyses.
  • Cognitive performance during each flight situation was assessed using a repeated measures analysis of variance between groups (ANOVA)
  • The SPSS software had significance set at alpha 0.05, offering a compromise between the likelihood of making type I or type II error.

Generalization potential

  • As this was a convenience sample which does not use a randomized selection process, the results should only be generalized to similar populations.
  • The relatively low median flight time of the participants (190 hours) may also reduce the generalization potential to similarly low time military helicopter pilots.
  • The first two-inflight experimental conditions utilised full motion simulation while the last (disorientated in-formation) used no motion. This may have caused a confounding effect on the experiment due to differing vestibular stimulation with motion on as compared to with motion off.
  • Further research should be undertaken using a simulator with a full motion capacity which is able to be used in all 3 experimental flight situations.
1. WEBB Catherine M, Arthur III ESTRADA & Amanda M KELLEY (2010). The effects of spatial disorientation on cognitive processing. The International Journal of Aviation Psychology (ISSN 1532-7108), 2012, volume 22, issue 3, pages 224-241.
+++ Footnotes +++
2. Number of digits repeated with no mistakes. Mean values were not provided in the original article, thus they have been estimated by 'eye-balling' the available figures.
3. Reaction time (in seconds). Mean values were not provided in the original article, thus they have been estimated by 'eye-balling' the available figures.
4. Addition task accuracy show as a percentage of correct additions over 19 trials. Mean values were not provided in the original article, thus they have been estimated by 'eye-balling' the available figures.

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Contributors to this page

Authors / Editors

Steve GEDDES (2013). Massey University, New Zealand (Steve GeddesSteve Geddes).


Dean J BISHOP (2013). Massey University, New Zealand (dean bishopdean bishop).
Sam TWALA (2013). Massey University, New Zealand (Sam_saSam_sa).

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