Journal of Gerontological Nursing

Feature Article 

Exergames-Based Intervention for Assisted Living Residents: A Pilot Study

Ying-Yu Chao, MS, RN, GNP; Yvonne K. Scherer, EdD, RN; Carolyn A. Montgomery, PhD, ANP-C, GNP; Kathleen T. Lucke, PhD, RN; Yow-Wu Wu, PhD

Abstract

The physical and psychosocial benefits of exergames have been reported in various literature. A pre-posttest, single-group design was used to test the effects of an exergames-based intervention on cognition, depression, and health-related quality of life (QOL) in assisted living residents. Bandura’s self-efficacy theory was applied. Seven residents (mean age = 86, SD = 5 years) participated in the program two times per week for 8 weeks. Outcome measures included cognition, depression, and health-related QOL. No statistically significant differences were found in any of the outcomes after the intervention. A tendency toward improved cognition occurred, but the outcomes of depression and health-related QOL did not follow a similar trend. However, improved socialization and motivation to exercise were reported. Continued research is needed to investigate the cognitive and psychosocial effects of exergames on this population. Nurses can collaborate with other health care professionals to engage residents in exercise and thus improve residents’ QOL. [Journal of Gerontological Nursing, 40(11), 36–43.]

Ms. Chao is PhD Candidate Student, Dr. Scherer is Associate Professor, Dr. Montgomery is Clinical Assistant Professor, and Dr. Wu is Associate Professor, School of Nursing, University at Buffalo, The State University of New York, Buffalo, New York; and Dr. Lucke is Dean of Health Sciences and Professor of Nursing, Elmira College, Elmira, New York.

The authors have disclosed no potential conflicts of interest, financial or otherwise. This study was supported by the Sigma Theta Tau International Honor Society of Nursing Gamma Kappa Chapter research grant. The authors thank the administrator, staff, and all individuals who participated in the study. The authors would also like to thank the following individuals for assisting with the program implementation and data collection: Anna Jao, MS; Pataraporn Kheawwan, PhD, APN, RN; and Sunee Suwanpasu, PhD, MS, RN.

Address correspondence to Ying-Yu Chao, MS, RN, GNP, PhD Candidate Student, School of Nursing, University at Buffalo, The State University of New York, 102 Wende Hall, 3435 Main Street, Buffalo, NY 14214-3079; e-mail: ychao3@buffalo.edu.

Received: June 11, 2013
Accepted: February 21, 2014
Posted Online: April 07, 2014

Abstract

The physical and psychosocial benefits of exergames have been reported in various literature. A pre-posttest, single-group design was used to test the effects of an exergames-based intervention on cognition, depression, and health-related quality of life (QOL) in assisted living residents. Bandura’s self-efficacy theory was applied. Seven residents (mean age = 86, SD = 5 years) participated in the program two times per week for 8 weeks. Outcome measures included cognition, depression, and health-related QOL. No statistically significant differences were found in any of the outcomes after the intervention. A tendency toward improved cognition occurred, but the outcomes of depression and health-related QOL did not follow a similar trend. However, improved socialization and motivation to exercise were reported. Continued research is needed to investigate the cognitive and psychosocial effects of exergames on this population. Nurses can collaborate with other health care professionals to engage residents in exercise and thus improve residents’ QOL. [Journal of Gerontological Nursing, 40(11), 36–43.]

Ms. Chao is PhD Candidate Student, Dr. Scherer is Associate Professor, Dr. Montgomery is Clinical Assistant Professor, and Dr. Wu is Associate Professor, School of Nursing, University at Buffalo, The State University of New York, Buffalo, New York; and Dr. Lucke is Dean of Health Sciences and Professor of Nursing, Elmira College, Elmira, New York.

The authors have disclosed no potential conflicts of interest, financial or otherwise. This study was supported by the Sigma Theta Tau International Honor Society of Nursing Gamma Kappa Chapter research grant. The authors thank the administrator, staff, and all individuals who participated in the study. The authors would also like to thank the following individuals for assisting with the program implementation and data collection: Anna Jao, MS; Pataraporn Kheawwan, PhD, APN, RN; and Sunee Suwanpasu, PhD, MS, RN.

Address correspondence to Ying-Yu Chao, MS, RN, GNP, PhD Candidate Student, School of Nursing, University at Buffalo, The State University of New York, 102 Wende Hall, 3435 Main Street, Buffalo, NY 14214-3079; e-mail: ychao3@buffalo.edu.

Received: June 11, 2013
Accepted: February 21, 2014
Posted Online: April 07, 2014

Cognitive impairment, severity of depression, and general medical health are significant predictors of functional impairment in frail older adults residing in assisted living facilities (ALFs) (Burdick et al., 2005). Advanced age increases the risk of dementia, with approximately 45% to 67% of ALF residents diagnosed with Alzheimer’s disease or other forms of dementia (Alzheimer’s Association, 2011). Depressive symptoms of ALF residents are significantly related to medical comorbidity, social withdrawal, and residents’ lengths of stay in the facility (Watson, Garrett, Sloane, Gruber-Baldini, & Zimmerman, 2003). Regular exercise can lower the probability of cognitive decline, reduce depressive symptoms, and improve and maintain quality of life (QOL) in the older adult population (Nelson et al., 2007).

Nintendo® Wii exergames, a new generation of exercise video games that provide interactive response in direction, speed, and acceleration and incorporate music and visual feedback, are increasingly used in rehabilitation and long-term care facilities. In addition to improved exercise motivation, studies have reported that older adults exercising with Wii exergames showed improvement in cognition and psychosocial well-being, such as decreased anxiety and depression and improved health-related QOL (Rosenberg et al., 2010; Wollersheim et al., 2010). To date, only one study has evaluated the effects of exergames on gait, balance, cognition, and QOL in ALFs (Padala et al., 2012); however, results only showed significant improvements in gait and balance (Padala et al., 2012). In addition, no theoretical framework was applied in any of the Wii exergames studies in older adults. Therefore, more research is needed to investigate the effects of a theoretically based exergame program on cognition and psychosocial benefits in transitional older adults in ALFs (i.e., ALF residents who would need to transfer to a nursing home if their physical or mental health deteriorates).

Nonadherence (i.e., resistance to exercise) is a key barrier to most exercise programs for older adults. The application of the self-efficacy theory has been shown to increase engagement in and adherence to exercise in older adults (Resnick, 2008). Therefore, the researchers of the current study developed the self-efficacy theory-based Staying Active, Healthy Aging (SAHA) program, which used Wii Fit exergames to engage ALF residents in an extended exercise program. The purpose of this pilot study was to evaluate the effects of the SAHA program on physical function, cognition, depression, and health-related QOL in ALF residents. The current study only reports the results of cognition, depression, and health-related QOL. The results of physical function are reported elsewhere (Chao, Scherer, Wu, Lucke, & Montgomery, 2013).

Method

Design

The current study was approved by the Health Science Institutional Review Board of the participating university. The study used a single-group, pre-posttest design. Bandura’s self-efficacy theory (Bandura, 1997) was used to guide the 8-week SAHA program. Three research assistants (RAs) were trained to implement the study protocol prior to the program’s initiation.

Sample

Residents were recruited from one ALF in western New York. Residents were eligible to participate in the study if they were older than 65, were mentally competent (Mini Mental State Examination-2: Standard Version [MMSE-2: SV; Folstein, Folstein, While, & Messer, 2010] ≥20), and had the ability to ambulate independently with or without the use of assistive devices, such as walkers. Residents were excluded if they had contraindications for exercise (American College of Sports Medicine, 2010). Seven participants between the ages of 80 and 94 joined and completed the study.

Intervention

Four mechanisms of Bandura’s (1997) self-efficacy theory were used to enhance residents’ exercise self-efficacy, including (a) enactive mastery experiences, (b) vicarious experiences, (c) verbal persuasion, and (d) emotional or physical feedback. Enactive mastery experiences were integrated into the SAHA program by setting goals and providing an individualized exercise prescription for residents. Researchers documented residents’ exercise progress and discussed exercise performance with participants.

To foster vicarious experiences, researchers shared success stories with participants and provided techniques on how to remain safe while performing gaming activities. In addition, Wii Fit also provided a “virtual trainer” who demonstrated ways to improve performance (e.g., posture, strength, balance).

To enhance verbal persuasion, researchers distributed health education booklets and displayed a poster of exercise benefits in each participant’s room. Topics of health education included (a) the benefits of exercise, (b) how to get started exercising, (c) safety issues, and (d) how to stay active (National Institute on Aging, 2013). Researchers provided ongoing encouragement and support during each exercise session. In addition, participants supported one another by sharing their experiences and offering encouragement. The Wii Fit also provided various motivational feedback (e.g., encouragement commentaries, bonus incentives, pleasant music).

To ensure that physiological and affective states were maintained, researchers assessed participants for emotional and physical adverse effects. For example, if a participant exhibited signs of fear of falling while exercising, researchers shared strategies to maintain balance confidence for that particular exercise. In addition, if participants exhibited signs of pain or fatigue, they were instructed to stop the exercise immediately; vital signs were assessed, and pain management interventions were initiated, if necessary.

Residents joined the program two times per week for 8 weeks, with a goal of 60 minutes of participation per session. The exercise intervention was modified based on the Exercising with Computers in Later Life (EXCELL) program (Williams, Soiza, Jenkinson, & Stewart, 2010). Participants were grouped in teams of two because of the benefits noted in the literature related to group exercise, including social interaction and connections (Wollersheim et al., 2010). The SAHA program was led by two RAs. Because there were only seven participants and participants were assigned two to a group, one participant was assigned to exercise with an RA.

During each session, participants performed four types of exercise using Wii Fit exergames, including aerobic exercise (jogging), strength exercise (lunge), balance exercise (penguin slide and table tilt), and yoga exercise (chair and deep breathing). A walker was provided for stability for all participants. Participants took turns playing the gaming activities. One resident watched and provided encouragement as his or her partner played the games; then, the roles were reversed. The goal was to have each session last for 60 minutes, with each participant engaging in activity for 30 minutes and observing for the remaining 30 minutes. The amount of time performing the strength exercise (lunge) was gradually increased at Week 4 and Week 7, as the strength exercise has been shown to offer the greatest benefit for physical function (Gu & Conn, 2008). Therefore, time spent on other gaming activities was decreased to accommodate for the increased time spent on the strength exercise and to ensure that each participant maintained the goal of 30 minutes of exercise during each session. Participants were allowed to rest at any time during the exercise intervention. Actual exercise time depended on each individual’s physical tolerance and performance.

Measures

Outcomes included cognition, depression, and health-related QOL. These measures were taken at baseline (pretest) and 1 week following the 8-week intervention (posttest).

Cognition. The MMSE-2: SV is a measure of five tests of cognitive function, including (a) orientation, (b) registration, (c) attention and calculation, (d) recall, and (e) language. The scores of the MMSE-2: SV are adjusted based on age and years of education. Higher scores indicate better cognitive function. The MMSE-2: SV has acceptable internal consistency (Cronbach’s alpha = 0.66 to 0.70) and high test–retest reliability (r = 0.86). The validity has been established with different measurements, such as the Wechsler Memory Scale-Revised and the Boston Naming Test (Folstein et al., 2010).

Depression. The Geriatric Depression Scale (GDS-15) is a 15-question scale used to assess depression in older adults. The GDS-15 rates symptoms over the past 7 days. Each question has dichotomous answers (1 = yes, symptom present; 0 = no, symptom not present). A score >5 suggests depression (Sheikh & Yesavage, 1986). The GDS-15 has good internal consistency (Cronbach’s alpha = 0.87), which is a satisfactory sensitivity and specificity in older adults with mild to moderate dementia in an outpatient geriatric assessment program (Lach, Chang, & Edwards, 2010) .

Health-Related QOL. The SF-8TM Healthy Survey (SF-8) 4-week recall is used to measure the perception of general physical and mental health-related QOL. The SF-8 contains eight domains, including (a) general health, (b) physical functioning, (c) role-physical, (d) bodily pain, (e) vitality, (f) social functioning, (g) mental health, and (h) role-emotional. Each item has a 5- or 6-point response range. The physical component summary score and the mental component summary score are composed using all eight SF-8 health domains. Higher scores indicate better functional health and well-being (Ware, Kosinski, Dewey, & Gandek, 2001). The SF-8 has good test–retest reliability (intraclass correlation coefficient = 0.8 to 0.88) and strong construct validity. The SF-8 shows excellent convergent validity with the SF-36 (Gulati, Coughlin, Hat-field, & Chetter, 2009).

Mediating Factors for Residents. The Self-Efficacy for Exercise (SEE) scale is a nine-item scale used to evaluate older adults’ confidence to continue exercising. Nine exercise barriers (e.g., feel pain, exercise alone, feel bored) are presented to assess older adults’ exercise participation. Each item is rated from 0 (not confident) to 10 (very confident). The higher the mean score, the stronger the efficacy expectations. The SEE scale has excellent reliability (Cronbach’s alpha = 0.89 to 0.94) and validity, with efficacy expectations significantly related to exercise activity (Resnick & Jenkins, 2000; Resnick, Luisi, Vogel, & Junaleepa, 2004).

Data Analysis

Descriptive statistics were used to describe the sample characteristics. The non-parametric Wilcoxon signed-rank test was used to examine the effects of the intervention on cognition, depression, health-related QOL, and the self-efficacy for exercise of the participants. A p < 0.05 level of significance was used in all analyses. Effect sizes (r) for each outcome measure were calculated (Field, 2009) and interpreted (Cohen, 1988).

Results

Sample characteristics are described in Table 1. The seven participants (five women, two men) were all Caucasian. Four participants were able to walk without any assistive device, two needed a walker, and one needed a cane. The effects of the intervention on the outcomes are presented in Table 2. There were no statistically significant differences in any of the outcomes following the implementation of the SAHA program. Although not statistically significant, there was a trend indicating that participants had better cognitive function after the intervention (p = 0.058). Participants had a better understanding of time orientation, recall, and calculation after the intervention. However, the outcomes of depression and health-related QOL did not follow a similar trend. Individual changes of cognition are presented in Table 3.

Characteristics of the Sample (N = 7)

Table 1:

Characteristics of the Sample (N = 7)

Effects of Intervention on Outcomes (N = 7)

Table 2:

Effects of Intervention on Outcomes (N = 7)

Pre-and Posttest Individual Change as Measured on the MMSE-2: SV

Table 3:

Pre-and Posttest Individual Change as Measured on the MMSE-2: SV

Participants reported 2.3 (SD = 2.1) depression symptoms at the pretest, but 2.9 (SD = 2.1) at the posttest. For the health-related QOL outcome, participants showed slight improvement on the posttest in general health, physical functioning, role-physical, social functioning, and role-emotional. However, scores did not improve but became slightly worse in the areas of bodily pain, vitality, and mental health after the intervention. Overall, participants had similar component summary scores in the physical and mental health-related QOL before and after the intervention. The mean scores of self-efficacy for exercise were comparable between the pre- and post-test as well.

Discussion

All participants attended the 16 exercise sessions offered over the 8-week period. The participants tended to have better cognitive function after the intervention. Although not statistically significant, the effect on cognition is a large effect, which is clinically significant in these frail older adults. Two residents with a diagnosis of cognitive impairment became more oriented after the intervention. Researchers found that depressive symptoms were related to cognitive functioning. In particular, the participant with a diagnosis of chronic obstructive pulmonary disease and severe depression showed the biggest range of improvement in cognition. Prior to the SAHA program, this participant spent most of the time staying in her room. She did not perform well on the cognitive test at pretest due to her lack of interaction with her surroundings; however, she became more oriented through socializing with other residents and researchers as the study progressed. These findings supported the Ganguli, Du, Dodge, Ratcliff, and Chang (2006) study, in which depressive symptoms were found to be cross-sectionally associated with cognitive impairment.

The magnitude of exercise effects on cognition in older adults was moderated by factors such as the length of exercise training intervention, the duration of training session, the types of exercise, and the gender of the study participants (Colcombe & Kramer, 2003). Rosenberg et al. (2010) reported that older adults with subsyndromal depression showed significant improvement in cognitive function after a 12-week Wii exergames program. Therefore, carrying out the Wii exergames intervention over a longer period of time may better determine the long-term effects of the intervention.

Regarding psychosocial outcomes, the current pilot study showed there were no significant differences in depression and health-related QOL between pre- and posttest. The findings were not consistent with the Rosenberg et al. (2010) study, in which older adults with subsyndromal depression were found to have a statistically significant decrease in depressive symptoms and improvement in mental health-related QOL after a 12-week Wii exergame program. Possible reasons for the differing results could be related to differences in the exercise prescription (i.e., frequency and duration), sample size, and measurements issues (i.e., ceiling effects). The current study’s researchers also noticed that one participant with Parkinson’s disease and stroke and another participant who experienced a stroke had more depressive symptoms after the intervention. These two participants expressed frustration, as they were sometimes unable to move fast enough to receive high scores on the gaming activities. This frustration may have affected their psychological outcomes at the posttest. Another possible reason for an increase in depression postintervention may be that participants felt more comfortable expressing negative feelings to the researchers because of the bonding that occurred during the exercise session. Once a therapeutic relationship was established, participants may have felt more comfortable sharing their true feelings with researchers.

When asked to provide feedback, participants reported that exercising with Wii exergames was enjoyable and that they would like to continue to exercise by using exergames. Participants made the following statements during the program:

  • I felt myself become stronger.
  • I usually exercise alone in my own room with an exercise video. I really enjoy exercise with the exercise partner.
  • I like the music and the visual motion the games provided. Some games even make me think.
  • These games are so interesting! I will continue to exercise with the games after the program.

According to participants’ conversations, the above statements reflect the certain levels of influence of the integration of self-efficacy theory into the Wii exergames. Overall, however, the result of the SEE scale did not show significant improvement after the intervention.

The exergames showed promise as a potential tool to motivate older adults to exercise. These findings of the pilot study can be used to support the development and implementation of theoretically based exergame programs for older adults in future studies, such as theory application, program frequency and duration, and sample size estimation.

Limitations

This study was limited by sample selectivity because all of the participants were Caucasian and from a single facility. The findings of the small sample cannot be generalized to all residents. Second, the seven residents who participated in the study had a wide range of medical diagnoses. If the program was implemented in older adults who had a similar degree of physical disability, similar cognitive impairments, or similar psychological statuses, the results would be more informative to the effects of the program per specific disease. Finally, the psychosocial instruments may not have been sensitive enough to measure certain physical and psychological benefits of the exercise program. Although participant feedback reflected the positive aspects of the interventions, the instruments were unable to capture the physical and psychosocial program benefits. Therefore, adding a qualitative component (i.e., a focus group or individualized interview) to future studies may help provide a better understanding of the effects of the exergames on older adults.

Implications

Nurses play an important role in supporting older adults in physical activity. However, there are limited nursing staff resources in ALFs. Nursing aides provide most of the care for older adults living in long-term care settings. The success of any intervention designed to improve restorative care depends primarily on training nursing aides to provide care regularly and properly. The increase in cost to supply training and the possible need to hire more nursing aides would be offset by the beneficial effects of exercise, resulting in ALF residents being able to remain in the ALF. Moreover, to make the exergames more translatable to clinical practice, nurses need to collaborate with other health care professionals (i.e., recreational therapists, physical and occupational therapists, and physicians) to design and implement an exergames-based intervention to help engage older adults in exercise. Recommendations for future research include implementing the exergames program with a larger sample in a controlled trial, revising the program duration, and including a focus group or individual interviews.

Conclusion

Wii exergames have several motivational attributes (e.g., attractive graphics, audio feedback), which can enhance exercise adherence in older adults. The current study’s findings support the integration of self-efficacy theory into exergames interventions, as a mechanism to increase ALF residents’ socialization and motivation to exercise. The effects of exergames on cognition and the physical and psychological benefits in older adults need to be further investigated.

References

  • Alzheimer’s Association. (2011). 2011 Alzheimer’s disease facts and figures. Retrieved from http://www.alz.org/downloads/facts_figures_2011.pdf
  • American College of Sports Medicine. (2010). ACSM’s resource manual for guidelines for exercise testing and prescription (7th ed.). Philadelphia, PA: Lippincott Williams & Wilkins.
  • Bandura, A. (1997). Self-efficacy: The exercise of control. New York, NY: W.H. Freeman and Company.
  • Burdick, D.J., Rosenblatt, A., Samus, Q.M., Steele, C., Baker, A., Harper, M. & Lyketsos, C.G. (2005). Predictors of functional impairment in residents of assisted-living facilities: The Maryland assisted living study. Journals of Gerontology. Series A, Biological Sciences and Medical Sciences, 60, 258–264. doi:10.1093/gerona/60.2.258 [CrossRef]
  • Chao, Y.-Y., Scherer, Y.K., Wu, Y.-W., Lucke, K.T. & Montgomery, C.A. (2013). The feasibility of an intervention combining self-efficacy theory and Wii Fit exergames in assisted living residents: A pilot study. Geriatric Nursing, 34, 377–382. doi:10.1016/j.gerinurse.2013.05.006 [CrossRef]
  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.
  • Colcombe, S. & Kramer, A.F. (2003). Fitness effects on the cognitive function of older adults: A meta-analytic study. Psychological Science, 14, 125–130. doi:10.1111/1467-9280.t01-1-01430 [CrossRef]
  • Field, A. (2009). Non-parametric tests. In Field, A. (Ed.), Discovering statistics using SPSS (3rd ed., pp. 539–583). Thousand Oaks, CA: Sage.
  • Folstein, M.F., Folstein, S.E., White, T. & Messer, M.A. (2010). MMSE-2: Mini-mental state examination (2nd ed.). Lutz, FL: Psychological Assessment Resources, Inc.
  • Ganguli, M., Du, Y., Dodge, H.H., Rat-cliff, G.G. & Chang, C.-C.H. (2006). Depressive symptoms and cognitive decline in late life: A prospective epidemiological study. Archives of General Psychiatry, 63, 153–160. doi:10.1001/archpsyc.63.2.153 [CrossRef]
  • Gu, M.O. & Conn, V.S. (2008). Meta-analysis of the effects of exercise interventions on functional status in older adults. Research in Nursing & Health, 31, 594–603. doi:10.1002/nur.20290 [CrossRef]
  • Gulati, S., Coughlin, P.A., Hatfield, J. & Chetter, I.C. (2009). Quality of life in patients with lower limb ischemia: Revised suggestions for analysis. Journal of Vascular Surgery, 49, 122–126. doi:10.1016/j.jvs.2008.08.011 [CrossRef]
  • Lach, H.W., Chang, Y.P. & Edwards, D. (2010). Can older adults with dementia accurately report depression using brief forms? Reliability and validity of the Geriatric Depression Scale. Journal of Gerontological Nursing, 36(5), 30–37. doi:10.3928/00989134-20100303-01 [CrossRef]
  • National Institute on Aging. (2013). Exercise & physical activity: Your everyday guide from the National Institute on Aging. Retrieved from http://www.nia.nih.gov/health/publication/exercise-physical-activity-your-everyday-guide-national-institute-aging-0
  • Nelson, M.E., Rejeski, W.J., Blair, S.N., Duncan, P.W., Judge, J.O., King, A.C. & Castaneda-Sceppa, C. (2007). Physical activity and public health in older adults: Recommendation from the American College of Sports Medicine and the American Heart Association. Medicine & Science in Sports & Exercise, 39, 1435–1445. doi:10.1249/mss.0b013e3180616aa2 [CrossRef]
  • Padala, K.P., Padala, P.R., Malloy, T.R., Geske, J.A., Dubbert, P.M., Dennis, R.A. & Sullivan, D.H. (2012). Wii-Fit for improving gait and balance in an assisted living facility: A pilot study (Article ID 597573). Journal of Aging Research. doi:10.1155/2012/597573 [CrossRef]
  • Resnick, B. (2008). Self-efficacy. In Peterson, S.J. & Bredow, T.S. (Eds.), Middle range theories: Application to nursing research (2nd ed., pp. 117–145). Philadelphia, PA: Lippincott Williams & Wilkins.
  • Resnick, B. & Jenkins, L.S. (2000). Testing the reliability and validity of the Self-Efficacy for Exercise scale. Nursing Research, 49, 154–159. doi:10.1097/00006199-200005000-00007 [CrossRef]
  • Resnick, B., Luisi, D., Vogel, A. & Junaleepa, P. (2004). Reliability and validity of the self-efficacy for exercise and outcome expectations for exercise scales with minority older adults. Journal of Nursing Measurement, 12, 235–248. doi:10.1891/jnum.12.3.235 [CrossRef]
  • Rosenberg, D., Depp, C.A., Vahia, I.V., Reichstadt, J., Palmer, B.W., Kerr, J. & Jeste, D.V. (2010). Exergames for sub-syndromal depression in older adults: A pilot study of a novel intervention. American Journal of Geriatric Psychiatry, 18, 221–226. doi:10.1097/JGP.0b013e3181c534b5 [CrossRef]
  • Sheikh, J.I. & Yesavage, J.A. (1986). Geriatric Depression Scale (GDS): Recent evidence and development of a shorter version. In Brink, T.L. (Ed.), Clinical gerontology: A guide to assessment and intervention (pp. 165–173). New York, NY: The Haworth Press.
  • Ware, J.E., Kosinski, M., Dewey, J. & Gandek, B. (2001). How to score and interpret single-item health status measures: A manual for users of the SF-8 health survey. Boston, MA: QualityMetric, Inc.
  • Watson, L.C., Garrett, J.M., Sloane, P.D., Gruber-Baldini, A.L. & Zimmerman, S. (2003). Depression in assisted living: Results from a four-state study. American Journal of Geriatric Psychiatry, 11, 534–542. doi:10.1097/00019442-200309000-00008 [CrossRef]
  • Williams, M.A., Soiza, R.L., Jenkinson, A.M. & Stewart, A. (2010). EXercising with Computers in Later Life (EXCELL): Pilot and feasibility study of the acceptability of the Nintendo WiiFit in community-dwelling fallers. BMC Research Notes, 3, 238. doi:10.1186/1756-0500-3-238 [CrossRef]
  • Wollersheim, D., Merkes, M., Shields, N., Liamputtong, P., Wallis, L., Reynolds, F. & Koh, L. (2010). Physical and psychosocial effects of Wii video game use among older women. International Journal of Emerging Technologies and Society, 8, 85–98.

Characteristics of the Sample (N = 7)

Characteristic n (%)
Age (years)
  80 to 84 4 (57.1)
  85 to 89 1 (14.3)
  >90 2 (28.6)
Sex
  Female 5 (71.4)
  Male 2 (28.6)
Race
  Caucasian 7 (100)
Marital status
  Widowed 6 (85.7)
  Divorced 1 (14.3)
Education
  High school 2 (28.6)
  College 3 (42.9)
  Graduate school and above 2 (28.6)
Ambulation with assistive device
  No 4 (57.1)
  Walker 2 (28.6)
  Cane 1 (14.3)
Activities of daily living
  Requires no assistance 4 (57.1)
  Requires some assistance 3 (42.9)
Medical diagnosisa
  Neurological disorder 4 (57.1)
  Cognitive impairment 3 (42.9)
  Musculoskeletal disease 2 (28.6)
  Psychiatric disorder 2 (28.6)
  Pulmonary disease 1 (14.3)

Effects of Intervention on Outcomes (N = 7)

Outcome Pretest (Mean [SD]) Posttest (Mean [SD]) p Value Cohen’s Effect Size (r)
Cognition 32.0 (12.9) 39.7 (12.2) 0.058 0.51
Depression 2.3 (2.1) 2.9 (2.1) 0.285 0.29
Health-related QOL
  General health 49.1 (9.3) 49.9 (7.7) 0.655 0.12
  Physical functioning 45.6 (10.8) 46.4 (6.4) 0.715 0.10
  Role-physical 44.9 (10.0) 45.4 (6.9) 1.000 0.00
  Bodily pain 54.9 (8.3) 51.9 (9.5) 0.180 0.36
  Vitality 53.7 (8.4) 49.6 (5.6) 0.102 0.44
  Social functioning 42.1 (12.9) 45.8 (12.4) 0.414 0.22
  Mental health 50.0 (10.0) 48.1 (8.2) 0.593 0.14
  Role-emotional 45.1 (8.8) 47.5 (5.3) 0.465 0.20
  Physical component summary 48.3 (10.8) 48.2 (7.4) 0.600 0.14
  Mental component summary 49.7 (10.2) 48.8 (8.8) 0.600 0.14
  Self-efficacy for exercise 5.9 (1.7) 6.0 (1.5) 0.600 0.14

Pre-and Posttest Individual Change as Measured on the MMSE-2: SV

Participant Age (Years) Diagnosis Raw Scores Adjusted Scores
Pretest Posttest Change Pretest Posttest Change
1 84 Cognitive dysfunction, arthritis 20 20 0 25 25 0
2 82 Cognitive dysfunction, CAD 20 22 2 20 28 8
3 84 Parkinson’s disease, CAD 29 30 1 55 59 4
4 87 COPD, diabetes, depression 20 27 7 25 52 27
5 94 Stroke, hypertension, CAD 25 24 −1 45 41 −4
6 80 Stroke, Parkinson’s disease, depression 20 23 3 25 36 11
7 91 Alzheimer’s disease, arthritis 21 23 2 29 37 8

Keypoints

Chao, Y.-Y., Scherer, Y.K., Montgomery, C.A., Lucke, K.T. & Wu, Y.-W. (2014). Exergames-Based Intervention for Assisted Living Residents: A Pilot Study. Journal of Gerontological Nursing, 40(11), 36–43.

  1. Exergames have several motivational attributes (e.g., attractive graphics, audio feedback), which can enhance exercise adherence for older adults.

  2. An intervention that integrates self-efficacy theory into exergames can serve as a mechanism to increase residents’ socialization and motivation to exercise.

  3. Nurses should collaborate with other health care professionals to design and implement an exercise program to help residents engage in exercise.

10.3928/00989134-20140407-04

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