Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Accounting for partial sleep deprivation and cumulative sleepiness in the Three-Process Model of alertness regulation.
Stockholm University, Faculty of Social Sciences, Stress Research Institute.
Stockholm University, Faculty of Social Sciences, Stress Research Institute.
Stockholm University, Faculty of Social Sciences, Stress Research Institute.
Show others and affiliations
2008 (English)In: Chronobiol Int, ISSN 1525-6073, Vol. 25, no 2, 309-19 p.Article in journal (Refereed) Published
Abstract [en]

Accounting for partial sleep deprivation and cumulative sleepiness in the Three-Process Model of alertness regulation.

Akerstedt T, Ingre M, Kecklund G, Folkard S, Axelsson J.

Stress Research Institute, University of Stockholm, Stockholm, Sweden. torbjorn.akerstedt@ki.se

Mathematical models designed to predict alertness or performance have been developed primarily as tools for evaluating work and/or sleep-wake schedules that deviate from the traditional daytime orientation. In general, these models cope well with the acute changes resulting from an abnormal sleep but have difficulties handling sleep restriction across longer periods. The reason is that the function representing recovery is too steep--usually exponentially so--and with increasing sleep loss, the steepness increases, resulting in too rapid recovery. The present study focused on refining the Three-Process Model of alertness regulation. We used an experiment with 4 h of sleep/night (nine participants) that included subjective self-ratings of sleepiness every hour. To evaluate the model at the individual subject level, a set of mixed-effect regression analyses were performed using subjective sleepiness as the dependent variable. These mixed models estimate a fixed effect (group mean) and a random effect that accounts for heterogeneity between participants in the overall level of sleepiness (i.e., a random intercept). Using this technique, a point was sought on the exponential recovery function that would explain maximum variance in subjective sleepiness by switching to a linear function. The resulting point explaining the highest amount of variance was 12.2 on the 1-21 unit scale. It was concluded that the accumulation of sleep loss effects on subjective sleepiness may be accounted for by making the recovery function linear below a certain point on the otherwise exponential function.

Place, publisher, year, edition, pages
2008. Vol. 25, no 2, 309-19 p.
Keyword [en]
Mathematic modeling, Sleep, Sleepiness, Performance
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:su:diva-14167ISI: 000257613200013PubMedID: 18484366OAI: oai:DiVA.org:su-14167DiVA: diva2:180687
Note
Internt publ.nr. P2657Available from: 2008-06-17 Created: 2008-06-17 Last updated: 2011-01-10Bibliographically approved

Open Access in DiVA

No full text

Other links

PubMedhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Retrieve&list_uids=18484366&dopt=Citation
By organisation
Stress Research Institute
Medical and Health Sciences

Search outside of DiVA

GoogleGoogle Scholar

pubmed
urn-nbn

Altmetric score

pubmed
urn-nbn
Total: 115 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf