HomeLarge Type Edition
HOME ARCHIVE SEARCH TABLE OF CONTENTS
This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Services
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
PubMed
Right arrow PubMed Citation
The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 61:1324-1329 (2006)
© 2006 The Gerontological Society of America

The ACTIVE Cognitive Training Trial and Health-Related Quality of Life: Protection That Lasts for 5 Years

Fredric D. Wolinsky, Frederick W. Unverzagt, David M. Smith, Richard Jones, Anne Stoddard and Sharon L. Tennstedt

1 Center for Research in the Implementation of Innovative Strategies in Practice (CRIISP), VA Iowa City Health Care System, Iowa.
2 The University of Iowa, Iowa City.
3 Indiana University, Indianapolis.
4 Regenstrief Institute, Inc., Indianapolis, Indiana.
5 Hebrew Rehabilitation Center for the Aged, Boston, Massachusetts.
6 New England Research Institutes, Boston, Massachusetts.

Address correspondence to Fredric D. Wolinsky, PhD, The John W. Colloton Chair, Department of Health Management and Policy, College of Public Health, University of Iowa, 200 Hawkins Drive, E205 General Hospital, Iowa City, Iowa 52242. E-mail: fredric-wolinsky{at}uiowa.edu


   Abstract
Top
 Abstract
Methods
 Results
 Discussion
 References
 
Objective. We evaluated the ability of the three cognitive training interventions (memory, reasoning, or speed of processing) fielded in the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) multisite randomized controlled trial to protect against two thresholds of extensive decline in health-related quality of life (HRQoL) at 2 and 5 years post-training.

Method. Adults aged 65 years or older (2802) were enrolled and randomized to three cognitive interventions or a no-contact control group. Data on 1804 participants were available at both the 2- and 5-year follow-ups. HRQoL was measured by the eight MOS 36-Item Short-Form Health Survey (SF-36) scales. Clinically relevant decline on each scale was defined as a drop of ≥ 0.5 standard deviations from baseline. Extensive HRQoL decline was defined as clinically relevant drops on (i) ≥ 4 SF-36 scales, and (ii) ≥ 3 SF-36 scales, and was assessed using multiple logistic regressions, weighted to adjust for potential attrition bias.

Results. At 2 years post-training, 23.7% and 36.6% had clinically relevant drops on ≥ 4 and ≥ 3 SF-36 scales, respectively. At 5 years post-training, 32.9% and 47.3% had clinically relevant drops on ≥ 4 and ≥ 3 SF-36 scales, respectively. Participants in the speed of processing intervention arm were significantly less likely to have extensive HRQoL decline compared to participants in the control group regardless of the threshold or time period, whereas participants in the memory and reasoning intervention arms were significantly less like to have extensive HRQoL decline only at 5 years post-training and only at the lower threshold.

Conclusion. The effect of the speed of processing intervention was stronger and evident earlier than those for the memory and reasoning interventions. This result stems from the speed of processing intervention being the most procedural intervention, operating through sensory-motor elaboration and repetition, bringing about a broader pattern of regional brain activation. At 5 years post-training, however, all three interventions were successful in protecting against a lower threshold of age-related extensive declines in HRQoL.

OLDER adults face declining cognitive ability and increasing difficulty with activities of daily living (ADLs) and instrumental ADLs (IADLs) (1), which are the primary risk factors for nursing home placement (2–4). After nursing home placement occurs, the risk for mortality increases (3,5), most likely due to failure to thrive (6,7). Moreover, after cognitive decline has been documented, there is evidence suggesting that triage results in decreased proclivity for both inpatient and outpatient health services (8,9). Thus, it is not surprising that cognitive decline is the greatest fear of older adults.

Even before institutionalization is considered, however, declining cognitive ability is a major risk for disability (10). It is well known that the prevalence of cognitive and functional impairment increases with age (11). Indeed, it is estimated that 4–5 million Americans (about 2% overall and 15% of those older than 65 years) have some form and degree of cognitive failure (12). With cognitive and functional loss comes decreased social interaction, and reduced leisure-time physical activity with accompanying decrements in quality of life and active life expectancy (13). Therefore, noninvasive interventions that can delay the pace of cognitive decline have much to contribute both to public health and to quality of life among older people.

It is not surprising, then, that numerous cognitive enhancement interventions for older adults exist (14), although few of those target prevention in cognitively intact elderly persons (15). Reports from the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) (16) study, a large multisite randomized controlled trial (RCT) of cognitively intact older adults, have strongly supported the effectiveness of its three distinct cognitive training interventions in improving targeted cognitive ability (15). In addition, ACTIVE's speed of processing intervention was observed to have a protective effect against extensive clinically relevant declines in health-related quality of life (HRQoL) at 2 years post-training (17). However, this effect was not observed at 2 years post-training for the memory and reasoning interventions.

Two plausible explanations were posited for this. First, of the three cognitive interventions, speed of processing is the most clearly procedural, operating through sensory-motor elaboration and repetition, whereas the memory and reasoning interventions emphasize or require the explicit learning of new concepts. Procedural tasks have a broader pattern of regional brain activation (18); this may account for the greater sense of well-being captured by the HRQoL ratings. The second explanation suggested that the lack of protective effects from the memory and reasoning interventions may have occurred from a combination of the low rate (25%) of extensive decline in HRQoL observed at 2 years post-training, and because 2 years may not have been sufficient time for an effect targeted at delaying decline (rather than improving current status) to materialize.

The purpose of this study is to determine if the three ACTIVE cognitive interventions were effective in delaying extensive clinically relevant decline in HRQoL at 5 years post-training. To do this, we use data from both the 2-year and the recently completed 5-year post-training follow-up interviews. Moreover, we also consider two definitional thresholds for extensive decline in HRQoL.


   METHODS
Top
 Abstract
 Methods
Results
 Discussion
 References
 
Design
ACTIVE was a single-blind RCT with three treatment arms (memory, reasoning, or speed of processing) and a no-contact control group. All treatment arms involved 10 equal-length, standardized intervention sessions. Those researchers conducting the outcome assessments were blinded to the treatment assignment of their participants. In addition to outcome assessments immediately following completion of the training, outcomes were assessed at 1, 2, 3, and 5 years post-training (16).

Sample
At each of the six sites, participants were recruited who were 65 years old or older and were living independent of formal care. These participants, however, were at risk for loss of functional independence. Each site used slightly different recruitment strategies from March 1998 through October 1999 (16), and a total of 4970 potential participants were identified. Exclusion criteria were (a) cognitive impairment (Mini-Mental State Examination [MMSE] score < 23) (19), (b) vision < 20/50, (c) hygiene, bathing, or dressing dependence, (d) Alzheimer's disease, (e) strokes occurring in the prior year, (f) limited life expectancy from cancer, (g) chemotherapy or radiation treatment ongoing at enrollment, (h) difficulty communicating, (i) intent to move, (j) scheduling conflicts, and (k) prior participation in cognitive training. These exclusion criteria were met by 905 individuals (18.2%), and another 1263 individuals (25.4%) refused either to be screened or to be enrolled. Of the 2802 participants screened, enrolled, and randomized, 1804 (64.4%) were successfully reassessed on all outcomes at 5 years post-training. Attrition was not associated with treatment status.

Interventions
In each of the three treatment arms, sessions 1–5 focused on strategy instruction and practice exercises, whereas sessions 6–10 provided additional practice. Content was scripted in a trainer's manual and involved laboratory-type and everyday activities (16). Reasoning training focused on inductive reasoning, the ability to solve problems that follow a serial pattern and are manifest in executive functioning. Memory training focused on verbal episodic memory, with participants taught mnemonic strategies for remembering lists, sequences of items, text material, and main ideas and story details. Speed training focused on visual search and the ability to identify and locate visual information in a divided attention format, with and without distraction.

HRQoL
HRQoL was measured with the widely used MOS 36-Item Short-Form Health Survey (SF-36) (20). Detailed descriptions and procedures, as well as the exact wording of the SF-36 items are available elsewhere (21–26). Thirty-five of the 36 items make up eight scales: physical functioning (10 items), role limitations due to physical functioning (4 items), bodily pain (2 items), general health perceptions (5 items), vitality (4 items), social functioning (2 items), role limitations due to emotional problems (3 items), and mental health (5 items). Within scales, missing data are imputed using a prorated method. Scores are transformed to range from 0 (worst health) to 100 (best health).

Clinically relevant changes in HRQoL were defined as a decline of ≥ 0.50 standard deviations (SD) between baseline and the 5-year follow-up, as suggested by Cohen (27). Although different cut points have been recommended, the most widely cited are very close to Cohen's.50 SD level (28–30), and a recent meta-analysis found that the mean estimated meaningfully important difference was 0.50 SD (31). Moreover, given seven response options per scale question, 0.50 SD is close to the estimated maximum human ability to discriminate between two feeling states (32). Thus, the 0.50 SD effect size is used here to define clinically relevant change in a single SF-36 scale. We used two definitional thresholds for extensive HRQoL decline. As in our previous report (17), the first is defined as clinically relevant change in four or more of the eight SF-36 scales, which reflects decline in a majority of the SF-36 domains. Our second definitional threshold for extensive HRQoL decline requires clinically relevant change in only three or more of the eight SF-36 scales. This lower threshold is included to evaluate whether the memory and reasoning interventions are also protective, but only against somewhat less robust HRQoL declines.

Attrition Bias
Of the 2802 ACTIVE participants, 1804 (64.4%) were reassessed on the HRQoL outcomes at the 5-year follow-up, creating the potential for attrition bias. Therefore, propensity score methods were used to adjust for it (33–35). Simply put, a multivariable logistic regression model of whether outcome data were available at the 5-year follow-up was estimated, and the predicted probabilities of inclusion in the analytic sample were computed. The average participation rate within each propensity score (predicted probability) quintile was then determined, and the inverse (1 – the participation rate) was used to weight the data, giving greater influence to retained participants who were most like those participants who were not followed. The propensity score model included binary indicators for each of the three cognitive intervention arms, baseline age, sex, race, cognitive function, basic ADLs, IADLs, cognitive ADLs, depressive symptoms, comorbid medical conditions, and SF-36 scale scores.

Analysis
After weighting the data to adjust for potential attrition bias, a simple intent-to-treat analysis was conducted. A multivariable regression model was estimated that included binary indicators for each of the three cognitive intervention arms. This regression model was estimated using HRQoL change data derived from both the 2- and 5-year post-training interviews, first for the more stringent definitional threshold used previously (17), and then for the less stringent definitional threshold. All analyses include only the 1804 ACTIVE participants who were successfully re-interviewed at both 2 years and 5 years post-training.


   RESULTS
Top
 Abstract
 Methods
 Results
Discussion
 References
 
Descriptive Results
Table 1 contains means or percentages for selected sociodemographic and functional status characteristics, as well as the eight SF-36 scale scores at baseline, by treatment group. Overall, the 1804 ACTIVE participants who were successfully interviewed at both the 2-year and 5-year follow-ups were 73.0 years old, 78% were women, and 23.5% were African American. The mean MMSE (19) score was 27.6, the average number of ADLs with difficulty (36) was 0.3, and the average number of IADLs with difficulty (37) was 4.1. The mean number of successful answers on the Everyday Performance Test (38) was 18.2, the average number of depressive symptoms (39) was 5.4, and the mean number of chronic conditions (40) was 2.3. As shown, the only significant difference was on depressive symptoms, for which the control group was favored. In contrast, data in Table 1 show significant differences in baseline SF-36 scale scores by treatment group. These differences, however, form no consistent pattern in advantaging or disadvantaging any of the treatment groups. Moreover, it is important to remember that it is the extent of clinically relevant decline over time, not at baseline, that is under examination.


View this table:
[in this window]
[in a new window]

  		Table 1. Means or Percentages of Sociodemographic, Functional Status, and SF-36 Scales Scores at Baseline, by Treatment Arm, Weighted to Adjust for Attrition Bias (N = 1804).

 
Propensity Score Model
Table 2 contains the results of the multiple logistic regression analysis predicting follow-up at 5 years. As shown, none of the cognitive intervention treatment arms were significantly associated with retention to the 5-year follow-up. Among the other factors in the model, loss to follow-up was associated with older age, being African American, and male gender. Retention to the 5-year follow-up was associated with better MMSE scores, better Everyday Performance Test scores (cognitive ADL function), and better scores on the SF-36 physical function scale. The not statistically significant (p =.594) Hosmer–Lemeshow statistic (41) and the C-statistic (.658) (42), respectively, indicate that the propensity score model fit the data well (i.e., had no evidence of heteroscedastic error) and was moderately successful in accurately distinguishing between those followed and not followed for 5 years.


View this table:
[in this window]
[in a new window]

  		Table 2. Multiple Logistic Regression Analysis of Completion of the 5-Year Follow-Up Interview (N = 2802).

 
Clinically Relevant Declines in SF-36 Scales
Table 3 shows the percentage of participants at each number (0–8) of clinically relevant declines (i.e., ≥ 0.50 SD) between baseline and the 2- and 5-year follow-ups on the eight SF-36 scales. These data indicate that there was considerable decline in HRQoL by 2 years post-training and that, as expected, this decline increased substantially by 5 years post-training. At 2 years post-training, 23.7% and 36.6% had clinically relevant drops on ≥ 4 and ≥ 3 SF-36 scales, respectively. At 5 years post-training, 32.9% and 47.3% had clinically relevant drops on ≥ 4 and ≥ 3 SF-36 scales, respectively.


View this table:
[in this window]
[in a new window]

  		Table 3. Percentage Distribution of the Number of Clinically Important Declines (i.e., ≥ 0.5 SD) on the SF-36 Scales at the 2- and 5-Year Follow-Ups, Weighted to Adjust for Attrition Bias (N = 1804).

 
Extensive Decline in HRQoL
Table 4 contains the results from the multiple logistic regression analysis of whether the ACTIVE participants had extensive declines in HRQoL at 2 years and 5 years post-training. In this analysis, extensive declines were defined as clinically relevant change on four or more of the SF-36 scales between baseline and the 2- or 5-year follow-ups. The results of this intent-to-treat analysis show that participants in the speed of processing intervention treatment arm were significantly protected from extensive declines in HRQoL at both 2 and 5 years post-training (adjusted odds ratios [AORs] = 0.617 and 0.744, p values =.004 and.038, respectively). Participants in the memory and reasoning treatment arms, however, were not significantly protected from extensive HRQoL decline at either period.


View this table:
[in this window]
[in a new window]

  		Table 4. Adjusted Odds Ratios of Extensive Decline in HRQoL at the 2- and 5-Year Follow-Ups (i.e., ≥ 0.5 SD Decline on ≥ 4 SF-36 Scale Scores) for Each Cognitive Intervention Group Versus Control Group, Weighted to Adjust for Attrition Bias (N = 1804).

 
Table 5 contains the results when extensive declines were defined as clinically relevant change on three or more of the SF-36 scales between baseline and the 2- or 5-year follow-ups. The results of this intent-to-treat analysis again show that participants in the speed of processing intervention treatment arm were significantly protected from extensive declines in HRQoL at both 2 and 5 years post-training (AORs = 0.740 and 0.737, p values =.033 and.022, respectively) and that the amount of risk reduction was virtually identical over time. Participants in the memory and reasoning treatment arms, however, were not significantly protected from extensive HRQoL decline at 2 years post-training, but were significantly protected from extensive HRQoL decline at 5 years post-training (AORs = 0.664 and 0.762, p values =.002 and.041, respectively).


View this table:
[in this window]
[in a new window]

  		Table 5. Adjusted Odds Ratios of Extensive Decline in HRQoL at the 2- and 5-Year Follow-Ups (i.e., ≥ 0.5 SD Decline on ≥ 3 SF-36 Scale Scores) for Each Cognitive Intervention Group Versus Control Group, Weighted to Adjust for Attrition Bias (N = 1804).

 

   DISCUSSION
Top
 Abstract
 Methods
 Results
 Discussion
References
 
Inasmuch as ACTIVE is the largest multisite RCT ever conducted that focuses on improving or maintaining cognitive performance among older adults (16), the results reported here are especially important. At both 2 and 5 years post-training, the speed of processing intervention provided significant protection against extensive declines in HRQoL, and this was the case regardless of whether that outcome was defined as clinically important declines on four or more or on three or more of the eight SF-36 scales. Moreover, the risk reduction for participants in the speed of processing intervention treatment arm was nearly identical over time for the less robust definitional threshold, and only modestly lower for the more rigorous definitional threshold. In contrast, memory and reasoning had significant protective effects against extensive decline in HRQoL at 5 years post-training, but only when the less robust definitional threshold was used. However, under those circumstances, the protective effects of memory and reasoning were comparable to that of speed of processing.

On the one hand, we believe that the speed of processing intervention has its effect at both definitional thresholds, and has it sooner than do the memory and reasoning interventions, because speed of processing operates through sensory-motor elaboration and repetition. It has been shown that such procedural tasks have a broader pattern of regional brain activation than explicit memory tasks (18). Improved brain activation or structure may delay the onset of (if not reduce the risk for) "slowing down." Because slowing down is the single most dreaded fear of older adults (43), the tempo reductions delayed or avoided by participants in the speed of processing intervention may have helped these older adults retain higher (i.e., baseline) perceptions of their HRQoL compared to their counterparts.

On the other hand, it is not surprising that all three cognitive interventions—memory, reasoning, and speed of processing—ultimately had protective effects against extensive decline in HRQoL. Declining cognitive ability is a major risk for disability (10), and decreased social interaction, reduced leisure-time physical activity, and accompanying decrements in quality of life and active life expectancy are known sequelae of cognitive and functional loss (13), and it has been shown that each of the three cognitive interventions had significant effects on their targeted cognitive abilities (15). Why, though, were the protective effects of memory and reasoning against extensive HRQoL decline manifest only at 5 years post-training, and why did they only occur for the less robust definitional threshold? Based on the data shown in Tables 4 and 5, we can unequivocally say that the failure to detect significant protective effects for the memory and reasoning interventions at 2 years post-training was not due to statistical power, as previously assumed (17). That is, the 2-year post-training AORs for the memory and reasoning cognitive interventions, regardless of the definitional threshold, were greater than unity, not less than it. Issues related to statistical power would have affected the confidence intervals around the point estimates, but not the point estimates themselves.

But why was the speed of processing effect observed sooner, and at the higher definitional threshold? It has already been noted that speed of processing was the most procedural of the interventions, and its computer-based delivery allowed participants to proceed at their own pace. We believe that the former transferred across more HRQoL domains, and that the latter allowed maximal effective dosing. As a result, the speed of processing intervention provided protection across a wider spectrum of HRQoL domains and provided that protection sooner than did the memory and reasoning interventions.

What is less clear is whether the indisputable and protective effects of the speed of processing intervention will be observed when more distal outcomes are examined. Specifically, it will be important to determine whether these protective effects translate into more appropriate and reduced levels of health services utilization and resource consumption, and ultimately into greater longevity. Examining these outcomes is the next step.


   Acknowledgments
Top
 Abstract
 Methods
 Results
 Discussion
 References
 
This research was supported by grants from the National Institutes of Health to six field sites and the coordinating center, including: Hebrew SeniorLife, Boston (R01 NR04507), the Indiana University School of Medicine (R01 NR04508), the Johns Hopkins University (R01 AG14260), the New England Research Institutes (R01 AG14282), the Pennsylvania State University (R01 AG14263), the University of Alabama at Birmingham (R01 AG14289), and the University of Florida (R01 AG014276). This analysis was supported by a grant (R03 AG023042) to the New England Research Institutes.

Dr. Wolinsky is Associate Director of the Center for Research in the Implementation of Innovative Strategies in Practice (CRIISP) at the VA Iowa City Health Care System, which is funded through the Department of Veterans Affairs, Veterans Health Administration, Health Services Research and Development Service (HFP 04-149).


   Footnotes
Top
 Abstract
 Methods
 Results
 Discussion
 References
 
Decision Editor: Darryl Wieland, PhD, MPH

Received June 1, 2006

Accepted August 31, 2006


   References
Top
 Abstract
 Methods
 Results
 Discussion
 References
 

  1. Pathy MSJ, Morley JE, Sinclair A, eds Principles and Practice of Geriatric Medicine, 4th Ed. New York: John Wiley & Sons; 2006.
  2. Kane RA, Kane RL, Ladd RC. The Heart of Long-Term Care. New York: Oxford University Press; 1998.
  3. Wolinsky FD, Callahan CM, Fitzgerald JF, Johnson RJ. The risk of nursing home placement and subsequent death among older adults. J Gerontol Soc Sci. 1992;47:S173-S182.
  4. Wolinsky FD, Callahan CM, Fitzgerald JF, Johnson RJ. Changes in functional status and the risks of subsequent nursing home placement and death. J Gerontol Soc Sci. 1993;48:S94-S101.
  5. Aneshensel CS, Pearlin LI, Schuler RH. Stress, role captivity, and the cessation of caregiving. J Health Soc Behav. 1993;34:54-70.[Medline]
  6. Braun JV, Wykle MY, Cowling WR. Failure to thrive in older persons: a concept derived. Gerontologist. 1988;28:809-812.[Medline]
  7. Wolinsky FD, Stump TE, Callahan CM. Does being placed in a nursing home make you sicker and more likely to die? In: Willis SL, Schaie KW, Hayward M, eds. Societal Mechanisms for Maintaining Competence in Old Age. New York: Springer; 1997:94–130.
  8. Wolinsky FD, Culler SD, Callahan CM, Johnson RJ. Hospital resource consumption among older adults: a prospective analysis of episodes, length of stay, and charges over a seven-year period. J Gerontol Soc Sci. 1994;49:S240-S252.
  9. Wolinsky FD, Stump TE, Johnson RJ. Hospital utilization profiles among older adults over time: consistency and volume among survivors and decedents. J Gerontol Soc Sci. 1995;50B:S88-S100.[Abstract]
  10. Murray C, Lopez A., The Global Burden of Disease and Injury Series. Vol 1. Cambridge, MA: Harvard University Press; 1996.
  11. Yesavage JA. Nonpharmacologic treatments for memory losses with normal aging. Am J Psychiatry. 1985;142:600-605.[Abstract/Free Full Text]
  12. Abrams W, Beers M, Berkow R. The Merck Manual of Geriatrics. Whitehouse Station, (NJ): Medical Services, 1995.
  13. Gallo J, Schoen R, Jones R. Cognitive impairment and syndromal depression in estimates of active life expectancy: the 13-year follow-up of the Baltimore Epidemiologic Catchment Area sample. Acta Psych Scand. 2000;101:265-273.[Medline]
  14. Rowe JW, Kahn RL. Successful Aging. New York: Pantheon; 1998.
  15. Ball D, Berch DB, Helmers KF, et al. Effects of cognitive training interventions with older adults: a randomized controlled trial. JAMA. 2002;288:2271-2281.[Abstract/Free Full Text]
  16. Jobe JB, Smith DM, Ball K, et al. ACTIVE: a cognitive intervention trial to promote independence in older adults. Controlled Clin Trials. 2001;22:453-479.[Medline]
  17. Wolinsky FD, Unverzagt FW, Smith DM, Jones R, Wright E, Tennstedt S. The effects of the ACTIVE cognitive training interventions on clinically relevant declines in health-related quality of life. J Gerontol Soc Sci. 2006;61B:S281-S287.[Abstract/Free Full Text]
  18. Cabeza R, Nyberg L. Imaging cognition II: an empirical review of 275 PET and MRI studies. J Cogn Neurosci. 2000;12:1-47.[Medline]
  19. Folstein MR, Folstein S, McHugh PR. Mini-mental state: a practical method for grading the cognitive state of patients for the clinician. J Psychol Res. 1975;12:189-198.
  20. Brazier J, Harper R, Jones N. Validating the SF-36 health survey questionnaire: new outcome measure for primary care. BMJ. 1992;305:160-164.[Abstract/Free Full Text]
  21. McHorney CA, Ware JE, Raczek AE. The MOS 36-Item Short-Form Health Survey (SF-36). II. Psychometric and clinical tests of validity in measuring physical and mental health constructs. Med Care. 1993;31:247-263.[Medline]
  22. Stewart AL, Hays RD, Ware JE. The MOS Short-Form General Health Survey: reliability and validity in a patient population. Med Care. 1988;26:724-736.[Medline]
  23. Tarlov AR, Ware JE, Greenfield S. The Medical Outcomes Study: an application of methods for monitoring the results of medical care. JAMA. 1999;262:925-934.
  24. Ware JE, Kosinski M. The SF-36 Physical and Mental Health Summary Scales: A Manual for User's of Version 1. 2nd Ed. Boston, MA: QualityMetric; 1999.
  25. Ware JE, Kosinski M, Dewey JE. How to Score Version 2 of the SF-36 Health Survey. Boston, MA: QualityMetric; 2000.
  26. Ware JE. The SF-36 Health Survey. In: Spilker B, ed. Quality of Life and Pharmacoeconomics in Clinical Trials. 2nd Ed. Philadelphia: Lippincott-Raven Publishers; 1996:337–345.
  27. Cohen J. Statistical Power Analysis for the Behavioural Sciences. London: Academic Press; 1969.
  28. Feinstein AR. Indexes of contrast and quantitative significance for comparisons of two groups. Stat Med. 1999;18:2557-2581.[Medline]
  29. Sloan JA, Loprinzi CL, Kuross SA. Randomized comparison of four tools measuring overall quality of life in patients with advanced cancer. J Clin Oncol. 1998;16:3662-3673.[Abstract]
  30. Testa MA. Interpreting quality of life clinical trial data for use in the clinical practice of antihypertensive therapy. J Hypertens. 1987;5:S9-S13.
  31. Norman GR, Sloan JA, Wyrwich KW. Interpretation of changes in health related quality of life: the remarkable universality of half a standard deviation. Med Care. 2003;41:582-592.[Medline]
  32. Miller GA. The magic number seven plus or minus two: some limits on our capacity for processing information. Psychol Rev. 1956;63:81-97.[Medline]
  33. Rubin DB. Using multivariate matched sampling and regression adjustment to control bias in observational studies. J Am Stat Assoc. 1979;74:318-324.
  34. Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika. 1983;70:41-55.[Abstract/Free Full Text]
  35. D'Agostino RB. Propensity score methods for bias reduction in the comparison of a treatment to a non-randomized control group. Stat Med. 1998;17:2265-2281.[Medline]
  36. Morris J, Morris S. ADL assessment for use with frail elders. J Mental Health Aging. 1997;3:19-45.
  37. Morris JN, Fries BE, Steel K, et al. Comprehensive clinical assessment in community setting: applicability of the MDS-HC. J Am Geriatr Soc. 1997;45:1017-1024.[Medline]
  38. Willis SL. Everyday cognitive competence in elderly persons: conceptual issues and empirical findings. Gerontologist. 1994;36:595-601.
  39. Radloff L. The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Measurement. 1977;1:385-401.
  40. Fillenbaum G. Multidimensional Functional Assessment of Older Adults: The Duke Older American Resources and Services Procedures. Hillsdale, NJ: Erlbaum; 1988.
  41. Hosmer DW, Lemeshow S. Applied Logistic Regression. New York: Wiley; 1989.
  42. Hanley JA, McNeil BJ. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology. 1982;143:29-36.[Abstract/Free Full Text]
  43. Cape RDT. The geriatric patient. In Cape RDT, Coe RM, Rossman I, eds. Fundamentals of Geriatric Medicine. New York: Raven Press; 1983:17–24.



This article has been cited by other articles:


Home page
 J Gerontol B Psychol Sci Soc SciHome page
F. D. Wolinsky, H. W. Mahncke, M. W. V. Weg, R. Martin, F. W. Unverzagt, K. K. Ball, R. N. Jones, and S. L. Tennstedt
The ACTIVE Cognitive Training Interventions and the Onset of and Recovery from Suspected Clinical Depression
J Gerontol B Psychol Sci Soc Sci, September 1, 2009; 64B(5): 577 - 585.
[Abstract] [Full Text] [PDF]

Home page
 Journals of Gerontology Series A: Biological Sciences and Medical SciencesHome page
H. H. Dodge, Y. Kita, H. Takechi, T. Hayakawa, M. Ganguli, and H. Ueshima
Healthy Cognitive Aging and Leisure Activities Among the Oldest Old in Japan: Takashima Study
J. Gerontol. A Biol. Sci. Med. Sci., November 1, 2008; 63(11): 1193 - 1200.
[Abstract] [Full Text] [PDF]

Home page
 Journals of Gerontology Series A: Biological Sciences and Medical SciencesHome page
D. K. Miller, F. D. Wolinsky, E. M. Andresen, T. K. Malmstrom, and J. P. Miller
Adverse Outcomes and Correlates of Change in the Short Physical Performance Battery Over 36 Months in the African American Health Project
J. Gerontol. A Biol. Sci. Med. Sci., May 1, 2008; 63(5): 487 - 494.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Services
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
PubMed
Right arrow PubMed Citation

HOME ARCHIVE SEARCH TABLE OF CONTENTS