Life-space mobility of middle-aged and older adults at various stages of usage of power mobility devices.

OBJECTIVE To examine whether the impact of power mobility devices (PMDs) varies as a function of stage of usage and to explore key factors associated with greater life-space mobility for middle-aged and older adults. DESIGN Multicohort study with respondents grouped as a function of stage of PMD usage (reference group with mobility impairments, n=42; initial users, 1-6mo, n=35; long-term users, 12-18mo, n=39). Cohorts were compared with respect to life-space mobility in a continuum of environments ranging from home to outside town, using analysis of variance and chi-square tests. Baseline personal, assistive device, intervention, and environmental factors associated with life-space mobility were explored with age-adjusted linear regression models. SETTING Four Canadian rehabilitation centers. PARTICIPANTS Random sample of middle-aged and older adults (N=116; 50-89y) living in the community or residential care. INTERVENTION Procurement of a powered wheelchair or scooter. MAIN OUTCOME MEASURE Life-Space Assessment composite score. RESULTS Cohort comparisons showed higher frequency of outings for PMD users in the neighborhood (P<.001) and around home (P<.05) and significantly greater Life-Space Assessment composite scores for initial and long-term users than for the reference group (P<.05). Factors such as sex, the nature of activities, and device type explained variances in Life-Space Assessment composite score ranging from 15.9% to 18.0% (P<.006). CONCLUSIONS Life-space mobility increases after PMD use and remains stable across the stages of initial and long-term use. To appreciate the impact of PMDs, clinicians should consider the environment and a combination of personal and device factors that are associated with the range of life-space mobility in the first 18 months after procurement.

[1]  R. Allman,et al.  Measuring Life‐Space Mobility in Community‐Dwelling Older Adults , 2003, Journal of the American Geriatrics Society.

[2]  Jeffrey W Jutai,et al.  The Effect of Wheelchair Use on the Quality of Life of Persons with Multiple Sclerosis , 2004, Occupational therapy in health care.

[3]  Jacob Cohen.  Statistical Power Analysis for the Behavioral Sciences , 1969, The SAGE Encyclopedia of Research Design.

[4]  Thomas Ewert,et al.  Linking health-status measurements to the international classification of functioning, disability and health. , 2002, Journal of rehabilitation medicine.

[5]  L. Gitlin,et al.  Emerging concerns of older stroke patients about assistive device use. , 1998, The Gerontologist.

[6]  Claudine Auger,et al.  Issues for the selection of wheelchair-specific activity and participation outcome measures: a review. , 2008, Archives of physical medicine and rehabilitation.

[7]  Ayumi Kono,et al.  Frequency of going outdoors predicts long-range functional change among ambulatory frail elders living at home. , 2007, Archives of gerontology and geriatrics.

[8]  M J Scherer,et al.  A framework for the conceptual modelling of assistive technology device outcomes , 2003, Disability and rehabilitation.

[9]  U S Nayak,et al.  The life-space diary: a measure of mobility in old people at home. , 1985, International rehabilitation medicine.

[10]  L Spazzafumo,et al.  Outdoor mobility and social relationships of elderly people. , 1997, Archives of gerontology and geriatrics.

[11]  Karen Hall,et al.  Power Mobility Driving Training for Seniors: A Pilot Study , 2005, Assistive technology : the official journal of RESNA.

[12]  Roger B. Davis,et al.  Mobility difficulties are not only a problem of old age , 2001, Journal of General Internal Medicine.

[13]  B. Tabachnick,et al.  Using multivariate statistics, 5th ed. , 2007 .

[14]  Stephen Sprigle,et al.  Characterization of power wheelchair use in the home and community. , 2008, Archives of physical medicine and rehabilitation.

[15]  Frances Harris,et al.  Conceptual issues in the measurement of participation among wheeled mobility device users , 2007, Disability and rehabilitation. Assistive technology.

[16]  Tae-Gyung Kang,et al.  Mobility Device Use in the United States , 2003 .

[17]  Å. Brandt,et al.  Older people's use of powered wheelchairs for activity and participation. , 2004, Journal of rehabilitation medicine.

[18]  Ingvor Pettersson,et al.  The effect of an outdoor powered wheelchair on activity and participation in users with stroke , 2006, Disability and rehabilitation. Assistive technology.

[19]  C. Peel,et al.  Assessing mobility in older adults: the UAB Study of Aging Life-Space Assessment. , 2005, Physical therapy.

[20]  Donald R. Miller,et al.  Barriers, facilitators, and access for wheelchair users: substantive and methodologic lessons from a pilot study of environmental effects. , 2002, Social science & medicine.

[21]  G. Gelderblom,et al.  Non-use of provided assistive technology devices, a literature overview , 2004 .

[22]  V. Freedman,et al.  Factors Influencing the Use of Mobility Technology in Community-Based Long-Term Care , 2004, Journal of aging and health.

[23]  Denise Reid,et al.  The Experience of Senior Stroke Survivors: Factors in Community Participation among Wheelchair Users , 2006, Canadian journal of occupational therapy. Revue canadienne d'ergotherapie.

[24]  M. Finlayson,et al.  Responses to the acquisition and use of power mobility by individuals who have multiple sclerosis and their families. , 2006, The American journal of occupational therapy : official publication of the American Occupational Therapy Association.

[25]  Michael H. Kutner.  Applied Linear Statistical Models , 1974 .

[26]  M. Laplante,et al.  MOBILITY DEVICE USE IN THE UNITED STATES: DISABILITY STATISTICS REPORT , 2000 .

[27]  B. Tabachnick,et al.  Using Multivariate Statistics , 1983 .

[28]  William C Miller,et al.  Measuring wheelchair intervention outcomes: Development of the Wheelchair Outcome Measure , 2007, Disability and rehabilitation. Assistive technology.

[29]  François Routhier,et al.  Development of a French-Canadian version of the Life-Space Assessment (LSA-F): content validity, reliability and applicability for power mobility device users , 2009, Disability and rehabilitation. Assistive technology.

[30]  Y. Fujiwara,et al.  Frequency of Going Outdoors as a Good Predictors for Incident Disability of Physical Function as well as Disability Recovery in Community-Dwelling Older Adults in Rural Japan , 2006, Journal of epidemiology.

[31]  Frank DeRuyter,et al.  Powered Mobility for Middle-Aged and Older Adults: Systematic Review of Outcomes and Appraisal of Published Evidence , 2008, American journal of physical medicine & rehabilitation.

[32]  R. Allman,et al.  The UAB Study of Aging: background and insights into life-space mobility among older Americans in rural and urban settings , 2006 .

[33]  M. Shields,et al.  Use of wheelchairs and other mobility support devices. , 2004, Health reports.

[34]  Helen Hoenig,et al.  Effect of motorized scooters on physical performance and mobility: a randomized clinical trial. , 2007, Archives of physical medicine and rehabilitation.

[35]  David B. Gray,et al.  Designing and using assistive technology : the human perspective , 1998 .

[36]  R. Sims,et al.  Racial similarities and differences in predictors of mobility change over eighteen months , 2004, Journal of General Internal Medicine.

[37]  P. Lachenbruch.  Statistical Power Analysis for the Behavioral Sciences (2nd ed.) , 1989 .

[38]  H. Yatsuya,et al.  Factors associated with life space among community-living rural elders in Japan. , 2006, Public health nursing.