This research explored whether individual interactions with a robotic cat could improve quality of life for persons living with advanced dementia. The research was conducted with five women residents in a Manitoba personal care home. Theories of personhood, agitation, and nurturance provided the conceptual framework. Ethnographic research methods included video-recorded observations of each resident with the cat, semi-structured interviews with staff and family, participant observation and three sets of agitation inventories (CMAI). Findings suggested agitation was reduced, socialization increased and, with pet loving residents, nurturant behaviour was evident. The cat, as a device for increased social attention, created positive results with the non-pet lovers. Advanced dementia did not prevent the women from indicating choice. The study concluded that a robotic cat could be a useful resource for persons with advanced dementia, dependent upon prior life-style and personal choice.

Background: Longitudinal studies enable the study of within person change over time in addition to between person differences. In longitudinal studies of older adult populations even when not the question of interest, identifying participants with dementia is desirable, and often necessary. Yet in practice, the time to collect information from each participant may be limited. Therefore, some studies include only a brief general cognitive measure of which the Mini Mental State Examination (MMSE) is the most commonly used (Raina et al., 2009). The current study explores whether group-based trajectory modeling of MMSE scores with a selection of covariates can identify individuals who have or will develop dementia in an 8 year longitudinal study. Methods: The sample included 651 individuals from the Origins of Variance in the Oldest Old study of Swedish twins 80 years old or older (OCTO-Twin). Participants had completed the MMSE every two years, and cases of dementia were diagnosed according to DSM-III criteria. The accuracy of using the classes formed in growth mixture modeling and latent class growth modeling as indicative of dementia status was compared to that of more standard methods, the typical 24/30 cut score and a logistic regression. Results: A three-class quadratic model with covariate effects on class membership was found to best characterize the data. The classes were characterized as High Performing Late Decline, Rapidly Declining, and Decreasing Low Performance, and were labeled as such. Comparing the diagnostic accuracy of the latent trajectory groups against simple methods; the sensitivity of the final model was lower but it was the same or superior in specificity, positive predictive value, negative predictive value, and allowed a more fine-grained analysis of participant risk. Conclusions: Group-based trajectory models may be helpful for grouping longitudinal study participants, particularly if sensitivity is not the primary concern. / Graduate

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No description available.

Thesis (Ph. D.)--University of Nevada, Reno, 2006. / "August, 2006." Includes bibliographical references (leaves 67-70). Online version available on the World Wide Web.

Thesis (Ph.D.)--Tufts University, 2000. / Adviser: David Harder. Submitted to the Dept. of Psychology. Includes bibliographical references (leaves 90-116). Access restricted to members of the Tufts University community. Also available via the World Wide Web;

Thesis (M.A.)--Georgia State University, 2007. / Title from file title page. Mary Ball, committee chair; Jaye Atkinson, Frank Whittington, committee members. Electronic text (114 p.) : digital, PDF file. Description based on contents viewed Nov. 1, 2007. Includes bibliographical references (p. 106-114).

Diss. (sammanfattning) Stockholm : Karol. inst. / Härtill 7 uppsatser.

Diss. (sammanfattning) Stockholm : Karol. inst. / Härtill 6 uppsatser.

Diss. (sammanfattning) Umeå : Univ., 2007. / Härtill 4 uppsatser.