title: On-site electronic observational assessment tool for discomfort and pain.
abstract: Over the recent years pen-paper observational assessment scales have proven to be useful to monitor behaviour and responses of humans and animals. Observational assessment tools are typically applied for subjects who are not able to communicate directly. For on-site observational assessment however it is hard to record and evaluate timing patterns of observed events using pen-paper scales. Although timing information is in many cases assumed highly valuable, only (videotaped) laboratory scales are able to benefit from this knowledge. In the work described in this paper we digitize pen-paper assessment scales resulting in new functionalities capable to improve assessment scores. A study of on-site pain and discomfort assessment of severely demented elderly is presented. The resulting system is a mobile electronic device with a graphical user interface (GUI) on a touch screen. Moreover digital information is stored in a database improving administration, providing immediate feedback and allowing applications like: visualisation, statistical analysis and scientific research like data mining. The device allows easily registering and automatically interpreting complex timing patterns of behaviours and responses, on-site. This feature could be employed in the development of new more accurate observational assessment instruments.
authors.affiliation: Division M3-BIORES, Catholic University of Leuven, Heverlee, Belgium.
authors.forename: Pieter
authors.initials: P
authors.lastname: Schiepers
authors.forename: Bert
authors.initials: B
authors.lastname: Bonroy
authors.forename: Greet
authors.initials: G
authors.lastname: Leysens
authors.forename: Dragana
authors.initials: D
authors.lastname: Miljkovic
authors.forename: Lieven
authors.initials: L
authors.lastname: De Maesschalck
authors.forename: Stijn
authors.initials: S
authors.lastname: Quanten
authors.forename: Bart
authors.initials: B
authors.lastname: Vanrumste
authors.forename: Daniel
authors.initials: D
authors.lastname: Berckmans
mesh_terms: D000369:Aged, 80 and over; D016208:Databases, Factual; D003704:Dementia / Q000453:epidemiology; D005260:Female; D006801:Humans; D015588:Observer Variation; D010146:Pain / Q000209:etiology; D010147:Pain Measurement / Q000379:methods*; D012984:Software