In their lives, individuals encounter situations that require information processing, decision-making, and learning of new ideas and skills. Such situations require individuals to attend to important information and screen out irrelevant information. This aspect of cognitive functioning is known as the capacity to direct attention (CDA).
As individuals age, their CDA appears to decline (Barrett-Connor, & Kritz-Silverstein, 1999; Cimprich, 1993b, 1998). Based on a theoretical framework of directed attentional fatigue (DAF) and restoration by Kaplan and Kaplan (1983), Jansen and Keller (1998) have proposed at least two reasons for this decline. First, older adults experience growing demands on their attentional mechanisms. For example, difficulties with vision, hearing, and mobility require them to expend significant attentional effort to negotiate activities of daily life. Second, age-related changes in the brain can reduce their innate attentional capacity. Thus, older adults are faced with higher attentional demands at a period of life when they have reduced capacity to direct attention.
This framework of DAF and restoration can potentially lead to the development of interventions to enhance attentional capacity and improve quality of life for older adults. A central aspect of the framework is the proposed relationship between attentional demands and CDA. However, little research has been conducted exploring the attentional demands experienced by older adults and their influence on CDA. The purpose of this study was to explore the relationship between attentional demands and CDA among community-dwelling elderly women using the Attentional Demands Survey (ADS), a newly developed instrument.
This study was based on the evolving theoretical framework of DAF and restoration by Kaplan and Kaplan (1983; Kaplan, 1995). Main concepts include CDA, attentional demands, DAF, restoration, and neurological influences (Cimprich, 1992, 1995; Jansen & Keller, 1998, 1999; Kaplan, 1995) (Figure). Overall, in this framework, neurological influences, such as those occurring with age, physiologically lower CDA. Attentional demands arising from advancing age and declining health and functional status draw on CDA, thereby decreasing this capacity. Directed attentional fatigue results when CDA is depleted because of excessive attentional demands and neurological influences. However, restoration may moderate the effects of the attentional demands so DAF can be prevented or ameliorated in older adults. The present study focuses on the relationship between attentional demands and CDA. The main concepts of the theoretical framework are described.
Capacity to Direct Attention
Capacity to direct attention is a type of selective attention and refers to the use of neural inhibitory mechanisms to focus the mind on what is meaningful to a situation and block out less relevant, distracting, and competing stimuli (Kaplan, 1995). The operation of these inhibitory mechanisms requires mental effort. Although it takes a toll on our mental resources, CDA allows individuals to focus their thoughts and concentrate on complex tasks, develop goals and plans, make judgments, remember everyday situations, and generally manage the daily routines of life (Cimprich, 1995; Lezak, 1995).
Attentional demands, the distracting and competing stimuli inhibited by CDA, affect an individual's ability to keep one's thoughts from wandering from an intended focus. An individual must extensively use the neural inhibitory mechanisms of directed attention to maintain focus and achieve mental clarity. By excessively drawing on CDA, however, attentional demands may reduce this limited capacity (Jansen & Keller, 1998; Kaplan, 1995).
Attentional demands occur within four domains:
First, physical-environmental demands refer to external surroundings that make it more difficult to complete tasks because attentional capacity must be devoted to minimizing their effects or managing in spite of them. Examples are clutter, insufficient lighting, and cramped apartment living space and other environmental distractions such as noise, glare, and foul odors. Second, informational demands are circumstances that make it a struggle to perceive and interpret information, such as difficulty hearing and seeing, esoteric jargon, and conflicting instructions. Directed attentional capacity is devoted to clarifying the information so necessary tasks can be accomplished. Third, behavioral demands refer to situations where one's behaviors and preferences are restricted because of physical limitations or societal or situational impositions. Examples include impaired mobility; financial restrictions; and giving up privacy, independence, and control. The CDA may be needed to overcome these restrictions. Finally, affective demands are feelings and emotions that can preoccupy and distract and include feelings of loss and worries. These feelings need to be inhibited for a person to remain focused. These four types of attentional demands require mental effort (and sometimes physical effort) to manage and overcome them. Many of these demands arise from or are compounded by changes in life circumstances or physical health and functional status accompanying aging (Jansen & Keller, 1998).
Figure. Theoretical model of the relationships among concepts (Jansen & Keller, 1999).
Directed Attentional Fatigue
When an individual experiences too many attentional demands during a prolonged period, DAF develops. Directed attentional fatigue refers to a decline in CDA. A person with DAF has difficulty attending to important tasks, is forgetful, has trouble planning, and is apt to become frustrated and irritable with little provocation (Kaplan & Kaplan, 1983; Lezak, 1995). For example, a client with DAF would have difficulty learning and retaining information in clientteaching situations.
Restoration has been conceptualized as activities and environments to prevent and alleviate DAF by allowing the neural inhibitory mechanisms of CDA to rest and recover. Theoretically, a restorative environment allows one to reflect and experience fascination rather than boredom. This provides a break from the normal routine of life and is interesting and pleasing (Kaplan & Kaplan, 1989). Viewing nature, gardening, and just "getting away from it all" are examples of restoration (Cimprich, 1993a; Kaplan & Kaplan, 1989).
The final concept, neurological influences, pertains to physiological processes affecting brain structures, thereby decreasing CDA. Examples of neurological influences affecting older adults are changes that occur in the brain with age such as atrophy and declines in neurotransmitters, as well as lack of sleep, depression, alcoholism, and medications that interfere with concentration (Keefover, 1998; Raz, 2000; Reuter-Lorenz, 2000).
For this study, the concepts of attentional demands and CDA and their relationship to each other were studied. Because of their potential effect on CDA, select neurological influences including depression and alcoholism also were examined.
REVIEW OF LITERATURE
The following review of literature focuses on research related to the concepts of restoration and attentional demands and additional variables potentially influencing CDA.
Restoration and CDA
Cimprich's (1992) research has focused on applying the theoretical framework to women with breast cancer. She found that middle-aged and older women recovering from breast cancer surgery tended to have significantly lower scores on tests of CDA than other women of similar ages. Theoretically, the recovering women experienced multiple attentional demands related to the diagnosis and management of the cancer and subsequently experienced some degree of DAF. Using the concept of restoration, Cimprich (1993a) designed an intervention for the women. During a 3month period, these women with diminished attentional capacities demonstrated significant improvements in CDA by engaging in activities of restoration such as walking outdoors and tending flowers, compared to the recovering women who did not participate in the intervention.
In another study, Tennessen and Cimprich (1995) found that college students with dormitory windows overlooking natural scenery scored significantly higher on tests of CDA than did students with dormitory windows overlooking built settings such as parking lots and brick buildings. Likewise, Hartig, Mang, and Evans (1991) found that physically fit backpackers and college students participating in wilderness trips and nature walks scored higher on measures of CDA and mood than did control groups. Such studies support the benefits of restoration, however, more studies need to be performed exploring the restoration opportunities of older adults.
To date, little research on restoration has been conducted with older adults. In a study of community-dwelling elderly women, Jansen (1997) found the women tended not to engage in many potentially restorative experiences available to younger adults, particularly those involving nature or the outdoors. According to Kelly (1996), participation in some potentially restorative activities declines with age, particularly when the person is constrained by living in an institutional setting, financial restrictions, loss of transportation, the death or illness of a spouse or companion, health limitadons, and lack of information. Some women may feel constrained by family objections and past societal attitudes toward women going out alone without male escorts (Lopata, 1993).
Attentional Demands and CDA
To date, scarce research has been conducted exploring the attentional demands of various populations. Only two studies have systematically addressed the multiple attentional demands experienced by older adults. In the first study, Jansen and Keller (1998) conducted a qualitative descriptive study to ascertain the perceptions of community-dwelling elderly women and men related to the attentional demands in their lives. Participants described a wide range of demands including harsh winter and summer conditions; issues related to driving and negotiating public transportation; vision and hearing difficulties; trouble understanding complex financial, insurance, and health care paperwork; and dealing with loneliness and isolation. Information from the study was used to create items for the ADS, a close-ended instrument assessing attentional demands in the physical-environmental, informational, behavioral, and affective domains. In the second study, Jansen and Keller (1999) determined the psychometric properties of the instrument and found it to have acceptable validity and reliability. (See the Instruments section for a description of the reliability and validity of the ADS.)
Other researchers have addressed the attentional capacity needed by older adults for tasks such as maintaining balance and walking (Brown, Shumway-Cook, & Woollacott, 1999; Lindenberger, Marsiske, & Baltes, 2000), driving (McKnight & McKnight, 1999), and making social judgments and inhibiting distractions (Chen & Blanchard-Fields, 2000; Tun, 1998; von Hippel, Silver, & Lynch, 2000). Older adults are believed to expend more CDA in everyday activities such as walking because of losses in motor, sensory, and cognitive functioning (Lindenberger et al., 2000; Raz, 2000). These losses increase attentional demands by requiring the older person to be more attentive in carrying out the task safely and effectively.
Variables Influencing CDA
Because of the new and exploratory nature of this research, additional variables and neurological influences potentially affecting CDA must be considered, particularly depression (Williams et al., 2000). One manifestation of depression is psychomotor retardation, which may negatively influence attentional capacity performance (Lemelin & Baruch, 1998; Zakzanis, Leach, & Kaplan, 1998), making it necessary to assess for depressive symptoms. Alcohol use must also be assessed for elderly individuals because alcoholism may impair cognition, including attentional capacity (Loberg, 1986).
A number of other variables are known to be associated with lower CDA, including limited education, older age, and poorer health and functional status (Barrett-Connor, & Kritz-Silverstein, 1999; Lezak, 1995; Smith, 1982; Spreen & Strauss, 1991). Some CDA loss with age may be caused by decreases in neurotransmitters and neuronal cell shrinkage and damage in areas of the brain important to attention, including the frontal lobes and association cortices (Lezak, 1995; Raz, 2000; Reuter-Lorenz, 2000). Poor health and functional status may negatively influence CDA and other cognitive abilities in a number of ways, including interfering with cerebral blood flow and metabolism and reaction time (Keefover, 1998; Raz, 2000).
Older adults in particular are at risk for developing DAF because age-related changes in the brain and the many attentional demands encountered in day-to-day life reduce the capacity to respond. Additionally, in comparison to younger individuals, older adults, especially women, may have fewer opportunities for restoration. Thus, an older woman experiencing many attentional demands and adverse neurological influences and little restoration would be at very high risk for developing DAF. There is increasing evidence to support relationships and concepts of the framework, particularly for the concept of restoration. The relationship between attentional demands and CDA is a key aspect of the theoretical framework; however, it has not been tested. Additionally, because of the new and evolving nature of the theoretical framework and concepts, little is known about factors potentially influencing attentional demands, such as depressive symptoms and functional and health status.
Because a large proportion of older adults are women, and because of their potential risk for developing DAF, beginning research on older adults' experiences with attentional demands can start with them. Women comprise 59% of the U.S. population age 65 and older and more than 70% of the population age 85 years and older (U.S. Census Bureau, 1999). Thus, the main purpose of this study was to examine the relationship between attentional demands and CDA among a convenience sample of community-dwelling elderly women. The following primary research question was tested:
* What is the relationship between attentional demands and CDA for a sample of community-dwelling elderly women?
Because of the exploratory nature of this research, additional secondary research questions were examined:
* What are the relationships of attentional demands, depressive symptoms, and self-reported functional status and health for the sample?
* What proportion of variance in CDA can be explained by attentional demands and select additional and demographic variables for the sample?
A single group descriptive correlational design was used to examine the relationship between attentional demands and CDA among a convenience sample of elderly women living in the community.
Participants and Setting
To participate in this study, women had to meet six criteria:
* At least 65 years old.
* Vision and hearing adequate for completion of the measures.
* Able to function independently in the community.
* Normal mental status scores as determined by the Short Portable Mental Status Questionnaire (Pfeiffer, 1975).
* No history of neurological (e.g., Parkinson's disease, stroke) or select psychological disorders (e.g., schizophrenia, alcoholism).
* Not taking psychoactive medications (e.g., haloperidol [Haldol], chlorpromazine [Thorazine]) that could interfere with attention.
The sample included 72 community-dwelling elderly women from a Midwestern city (n = 60) and its surrounding suburbs (n = 12). Their ages ranged from 65 to 102 (M = 76.9, SD = 7.7). Sixty-six participants (92%) were White and 6 (8%) were Black; 70 individuals (97%) were born in the United States. Fifty-six percent of the women were widowed; 13% were married; and the remaining 32% were either never married, divorced, or separated. Seventy-eight percent of the women lived alone. Seventy-five percent lived in apartments and 25% lived in houses. For education, women had a mean of 14.2 years (SD = 2.8, range = 8 to 20 years) of formal education. Ninetythree percent of the participants were retired. All participants met the eligibility criteria and thus no one was excluded from the study.
CDA Measures. The CDA was measured by performance on standard visual and auditory measures requiring the inhibition of competing and distracting stimuli. These tests have been used successfully with older adults and were selected based on theoretical soundness. A battery of three measures rather than a single test was chosen to provide greater sensitivity in detecting variance in CDA (Cimprich, 1992).
Further details related to the administration of these measures and normal ranges for older adults can be obtained from the researchers.
The first measure was the forward and backward digit spans. Digit Span Forward (DSF) requires participants to repeat a series of digits read aloud by the researcher at a rate of one per second. Digit Span Backward (DSB) requires participants to sustain attention as they repeat the digits in reverse order (Lezak, 1995). Higher scores indicate better attentional functioning.
The second measure, the Symbol Digit Modalities Test (SDMT), requires the participant to substitute numbers for nine geometric symbols according to a key (Smith, 1982). The score is based on the number of correct written responses within a 90 second interval. A higher score indicates better attentional functioning.
The third measure, the Trail Making Test (TMT), consisting of two parts, was used to measure CDA (Reitan, 1958). For Part A, the participant is required to connect (using a pencil) a series of circles numbered from 1 to 25 in correct order and as quickly as possible. Part B requires the participant to connect a series of 25 circles numbered from 1 to 13 and lettered from A to L. The participant alternates between the numbers and letters while connecting the circles in sequence. The researcher points out errors as they occur so the participant can make the corrections. The score is the number of seconds required to complete the test, including the time for corrections. Higher scores as measured in seconds indicate poorer attentional functioning.
For analysis purposes, a total CDA score was computed. To permit the combination of the individual attention test scores, raw scores on all the attention measures were transformed to Z scores using a mean of 0 and a standard deviation of 1. To maintain consistency so all good performances were scored with high numbers and poor performances were scored with low numbers, the reciprocal of time (multiplied by 1,000 to eliminate the decimals) was used for the TMT scores. As performed in prior research (Cimprich, 1993a; Jansen & Cimprich, 1994), a total CDA score was created by summing the Z scores. In this study, total CDA scores ranged from -7.65 to 9.61, with higher scores indicating better attentional functioning.
Attentional demands measure. The ADS consists of 42 items measuring demands within four theoretically derived domains: physical-environmental, informational, behavioral, and affective Qansen & Keller, 1999). The participant was asked to rate the degree to which each item "takes effort or makes life difficult" on a 5-point Likerttype scale (0 = not at all, 4 = a lot). Content analysis of interview data obtained from 30 elderly women and men and reviews of the items by experts provided support for content validity (Jansen & Keller, 1998). In a study of 197 community-dwelling elderly women and men, a factor analysis provided support for the construct validity. Test-retest reliability was .91 after a 2week interval. Internal consistency for the four domains ranged from .87 to .90 Qansen & Keller, 1999). In this study, internal consistency (Cronbach's alpha) for the physical-environmental, informational, behavioral, and affective domains were .80, .85, .80, and .83, respectively. Examples of items include, "uncomfortable or harsh weather conditions,*' "financial restrictions,'' "pain and discomfort," and "worries about health and future of friends or family." Item ratings are summed for each domain and for the total instrument Higher scores indicate the presence of more or greater demands and lower scores indicate fewer demands.
Additional measures. Additional measures included tools to measure depressive symptoms, functional status, mental status, use of alcohol, health, and selected demographics. More details related to the administration and psychometrics of these tools can be obtained from the researchers.
The Geriatric Depression ScaleShort Form (GDS-SF) was used to obtain descriptive information related to depressive symptoms (Sheikh & Yesavage, 1986). The GDS-SF is a 15item dichotomous tool with higher scores indicating the presence of more depressive symptoms. A score of 0 to 4 is considered normal (Sheikh & Yesavage, 1986). Internal consistency (Cronbach's alpha) for the GDS-SF was .83 in the present study.
Attentional Demands Survey (ADS) Means and Ranges (N = 72)
The Instrumental Activities of Daily Living Scale (IADL) was used to obtain descriptive information about functional status (Lawton, 1988). The instrument consists of 9 items for which the participant was asked to rate herself on a 3-poínt scale (1 to 3) to describe how much help was needed for tasks such as using the telephone and shopping. Higher scores indicate greater independence and functional status.
The Short Portable Mental Status Questionnaire (SPMSQ) was used to limit the sample to women with normal cognitive functioning (Pfeiffer, 1975). The questionnaire consists of 10 questions worth 1 point each. A cut-off point of two errors gives sensitivities and specificities of 100% for detecting dementia in elderly community samples (Erkinjuntti, Sulkava, Wikstrom, & Autio, 1987). Data from participants with more than two errors were to be excluded from the present study. However, all participants had two or fewer errors, and thus no one was excluded.
CAGE is a 4-item tool to screen for alcoholism in participants (Mayfield, McLeod, & Hall, 1974). In a study of adults ranging from age 19 to 75 years, a positive response to 2 or more of the questions was associated with a sensitivity of .89 in detecting alcoholism (Mayfield et al., 1974). In the present study, no participants responded positively to two or more questions, and thus no one was excluded.
Demographic data included age, race, education, marital status, and medication usage. The screening criteria were included on the demographic data form. Also, a Likert-type question to compare one's health to the health of others of similar age was used (4 = excellent, 3 = good, 2 = fair, and 1 = poor); a higher score indicated better self-reported health.
The older participants were recruited via flyers posted in apartment buildings where older adults lived and at sites such as senior centers, libraries, and volunteer functions. The snowball effect added other participants.
Sixty-two of the interviews were in the home, five at the School of Nursing, and five at a local community center. First, both verbal and written informed consent (as approved by the Institutional Review Board) and demographic information were obtained. Then participants were screened using the SPMSQ. Next, the women were asked to complete the depression scale, IADL, and ADS (administered in random order).
Finally, the three measures of attention were presented in random order. Efforts were made to insure privacy, quiet, and adequate lighting during the interviews. Study administration took approximately 45 minutes of the participant's time and each was paid $15.
Descriptive statistics were computed for all the study measures. Total CDA score means did not differ significantly for those participants tested in the home (n = 62) versus other (n = 10) settings (?(69) = 1.56, ? = .12). Participants were thus treated as a single group.
To examine the relationship between attentional demands and CDA, the total CDA score and a summed total score for the ADS were used. Pearson r correlational techniques were employed to find the degree of association between attentional demands and CDA and among attentional demands, depressive symptoms, and self-reported functional status and health. A hierarchical multiple regression was conducted to account for variance in the total CDA score.
Research Question 1
The relationship between attentional demands and CDA was examined. A significant medium-sized negative correlation (r = -.31, ? < .01) was found between the total ADS and total CDA scores, indicating higher levels of attentional demands were associated with lower levels of CDA.
Attentional Demands, Depressive Symptoms, Functional and Health Status Pearson r Correlations (N = 72)
The mean total ADS score was 54.3 (SD = 26.1) with values ranging from 18 to 124 of a total possible score of 168. (See Table 1 for individual domain means and ranges.) To determine whether the women's attentional abilities were typical for their ages and educational backgrounds, responses on the individual tests of CDA were compared, using t tests, to age- and education-appropriate normative data. No significant differences were found.
Research Question 2
To examine the relationships among attentional demands, depressive symptoms, and self-reported functional status and health, descriptive information was tabulated and then Pearson r correlations were calculated. Eighty-six percent of the participants had GDS-SF scores in the non-depressed range (score less than 5); the mean score was 2.2 (SD = 2.8, range = 0 to 12) of a possible 15 points. Women managed common household tasks well, as evidenced by a favorable mean IADL score of 26.9 (SD = 2.1; range = 20 to 29) of a possible 29 points. Twenty-nine percent of the women rated their own health as "excellent" and 51% rated their health as "good." The remaining 19% rated themselves as being "fair."
Medium to large correlations among the ADS, GDS-SF, and selfreports of functional status and health ranged from -25 to .55 (Table 2). Fewer depressive symptoms and better health and functional status were associated with lower ADS scores (fewer demands). More depressive symptoms were associated with poorer functional status and health.
Research Question 3
For exploratory purposes, the total CDA score was correlated with the additional measures and selected demographic variables (age and education) believed to influence CDA. CDA correlated negatively with age (r = -.43, ? < .001) and positively with number of years of education (r - .49, ? < .001). Total CDA also correlated positively with functional status as measured by the IADL (r - .42, p < .001) and health status (r = .25, ? < .05).
No significant relationship was found between depressive symptoms and CDA (r = -.03).
A hierarchical multiple regression was conducted to account for variance in the total CDA score. Because age, years of education, health, and functional status had correlated significantly with CDA, these variables were entered into the regression along with the ADS. Together, they accounted for 44% of the variance in CDA (Table 3). Attentional demands accounted for 4% of the variance in CDA with the effects of the other variables partialled out from the ADS (sr2 = .04, F(I, 65) = 4.84,/» = .03).
Further analyses were performed exploring the subsets of women with higher and lower self -rating of health and functional status to compare them on CDA and attentional demands. To form the subsets, the health and IADL raw scores of all the participants were transformed to Z scores. A Z score of 0 (the mean) was used as a cut-off to separate the women into high and low groups on the health and IADL measures. In this study, the subset of women with lower ratings of health and functional status (n = 16) scored significantly more poorly on the attention measures (¿(33) = -2.43, ? = .02) and reported significantly higher levels of attentional demands (i(33) = 2.63, ? = .01) than did the women with higher self-ratings (n = 19).
Research Question 1
The aim of the present study was to examine the relationship between attentional demands and the CDA among elderly women. The significant correlation between the ADS and total CDA scores is consistent with an evolving theoretical framework of directed attentional fatigue and restoration proposing an inverse relationship between attentional demands and CDA. In this study, those women experiencing more attentional demands had more difficulty directing attention. Attentional demands accounted for a small but significant proportion of the variance in the total CDA score, even after the effects of age, years of education, health, and functional status were partialled out of the ADS.
Although the older participants in the sample experienced a variety of attentional demands, scores on the ADS tended to fall in the lower range of possible scores, indicating relatively few demands. The low level of attentional demands limited the probability of attaining a higher correlation between demands and CDA, possibly accounting for the small proportion of variance explained by demands. The low level of demands may have been related to the good health and functional status of the women in the sample. In contrast, the small subset of women with lower self-ratings of health and functional status reported more or greater attentional demands and had more difficulty directing attention. These findings suggest problems in health and physical status accompanying aging may be related to increased attentional demands. These changes may result in new demands such as worries about health and independence, difficulty reading and getting around, and problems managing the physical environment
Multiple Regression of Age, Education, Health, Functional Status, and Attentional Demands on Capacity to Direct Attention [N = 72)*
The nature of the sample may further account for the relatively low scores and proportion of variance accounted for in CDA by the ADS. Many of these women were living in environments such as apartment buildings where demands already were reduced for them. Additionally, these self-selected respondents may be women who have higher attentional functioning and fewer demands in their lives. Others not doing as well may have been too attentionaily or physically fatigued to volunteer or felt too threatened by the nature of the study.
Research Question 2
Significant relationships were found among attentional demands, depressive symptoms, and selfreported functional status and health. Specifically, attentional demands were associated with more depressive symptoms and reports of poorer health and functional status. These findings are consistent with attentional demands theoretically increasing as problems with physical ability and health status arise with age. The depressive symptoms may reflect the women's reactions to the new and increased attentional demands arising from their changed life situations. At the same time, it is possible the women with more depressive symptoms perceived and rated the demands as being greater than those women who were not depressed. This latter possibility is consistent with the finding of no direct relationship between depressive symptoms and CDA in this study.
Research Question 3
In this study, variables believed to influence CDA were assessed, including age, education, depressive symptoms, functional status, and health. Depressive symptoms were not significandy correlated with CDA. Although not consistently found, the lack of a relationship between CDA and depressive symptoms has occurred in research studies involving other populations, such as patients with multiple sclerosis (Jansen & Cimprich, 1994).
Consistent with the literature (Lezak, 1995; Smith, 1982; Spreen & Strauss, 1991), more education, younger age, and better health and functional status were associated with greater CDA. Age and education together accounted for proportionately more variance in CDA than did health and functional status. In this study, they appear to be important influences on CDA abilities later in life. Again, the limited variance explained by attentional demands may be related to the low level of demands reported by this highly functioning sample.
Limitations of this study include the non-random convenience sampling method, the small size and relatively homogeneous nature of the sample, the self-report of data by participants for some variables, and the lack of baseline CDA data to assist in determining the presence of DAF. Because the sample was a fairly well-educated and highly functional group, the individual participants could have had significant losses in CDA that were not identified in this study. That is, some participants who were functioning at very high levels in the past may have experienced significant declines in CDA. However, compared to other individuals their age, they did not appear to be attentionaily fatigued.
Implications for Practice
The study provides beginning evidence to support a relationship between attentional demands and CDA. As evidence accumulates, the framework can be used to develop and test the effectiveness of interventions to enhance and support attentional capacity and improve quality of Ufe. For instance, the ADS can be used by health care providers to identify areas of attentional demands interfering with an older client's ability to manage daily tasks, learn new information and skills, and engage in activities she enjoys. After identification of attentional demands, the health care provider can work with the client to reduce those that can be altered. For instance, in the area of physical-environmental demands, poor lighting, glare from polished floors and bright sunlight, and building design factors such as stairs may be modifiable. Informational demands such as hearing and vision difficulties and unclear and conflicting patient education materials can be corrected or made more discernable. Behavioral demands including loss of privacy and financial constraints and affective demands such as pain and discomfort, fear of falling, and worries about health and well-being can also be addressed.
In this study, women with more depressive symptoms and reports of poorer health and functional status reported greater attentional demands. When working with clients, health care workers may particularly want to consider screening and reducing attentional demands for women presenting with numerous health problems and depressive symptoms. These women may be experiencing higher levels of attentional demands and thus may be in greater need of intervention. Additionally, because age and education correlated significantly with CDA, health care providers may want to consider the influences of these variables when meeting with older clients. Older women with less education may have lower CDA and thus may find it more difficult to process complex information and learn new skills. Research provides evidence of the difficulties older adults have with common health-related tasks such as planning medication schedules and understanding advance directives (Park & Gutchess, 2000).
While working to reduce demands, the provider may consider other nursing interventions suggested by the theoretical framework. For instance, the provider could assist in finding feasible ways to incorporate moments of restoration into the lives of older adults. Although studies have shown that activities as simple as looking out a window with a scenic view and being with nature are associated with improved health, mood, and CDA (Cimprich, 1993a; Hartig et al., 1991; Tennessen & Cimprich, 1995; Ulrich, 1984), many elderly women appear to have limited exposure to restoration. Thus, time and opportunities for restoration must be considered a viable part of a plan of care for older adults living in the community and institutions.
Implications for Theory Development and Research
An important theoretical contribution of this research was the finding of a significant relationship between attentional demands and CDA. Because attentional demands accounted for a small proportion of the variance in CDA, this study needs to be replicated with other samples of older adults, including men, with varying and greater levels of attentional demands. Path analysis may be helpful in examining the relationships among attentional demands, CDA, depression, and restoration. As support accumulates, the framework can be used in the implementation and evaluation of future interventions to support, maintain, and even enhance CDA so the enjoyment of day-to-day life can be promoted and independence maintained.
- Barrett-Connor, E., & Kritz-Silverstein, D. (1999). Gender differences in cognitive function with age: The Rancho Bernardo study. Journal of the American Geriatrics Society, 47(2), 159-164.
- Brown, L.A., Shumway-Cook, A., & Woollacott, M.H. (1999). Attentional demands and postural recovery: The effects of aging. Journal of Gerontology: Medical Sciences, 54A(4), M165-M171.
- Chen, Y., & Blanchard-Fields, F. (2000). Unwanted drought: Age differences in the correction of social judgments. Psychology and Aging, Ii (3), 475^182.
- Cimprich, B. (1992). Attentional fatigue following breast cancer surgery. Research in Nursing & Heath, 15, 199-207.
- Cimprich, B. (1993a). Development of an intervention to restore attention in cancer patients. Cancer Nursing, 16(2), 83-92.
- Cimprich, B. (1993b). [Evaluating usefulness of tests of attentional capacity in healthy adults]. Unpublished raw data.
- Cimprich, B. (1995). Symptom management: Loss of concentration. Seminars in Oncology Nursing, 11(4), 279-288.
- Cimprich, B. (1998). Age and extent of surgery affect attention in women treated for breast cancer. Research m Nursing & Health, 21, 229-238.
- Erkinjunrri, T, Sulkava, R-, Wikstrom, J-, & Aurio, L. (1987). Short portable mental status questionnaire as a screening test for dementia and delirium among the elderly. Journal of the American Geriatria Society, 35, 412-416.
- Hartig, T., Mang, M., & Evans, G.W. (1991). Restorative effects of natural environment experiences. Environment and Behavior, 23, 3-26.
- Jansen, D.A. (1997). Attentional demands and restorative activities: Do they influence directed attention among the elderly? Unpublished doctoral dissertation, University of Wisconsin, Madison.
- Jansen, D.A., & Cimprich. B. (1994). Attentional impairment in persons with multiple sclerosis. Journal of Neuroscience Nursing 26(2), 95-102.
- Jansen, D.A., & Keller, M.L. (1998). Identifying die attentional demands perceived by elderly people. Rehabilitation Nursing, 23(1), 12-20.
- Jansen, D. ?., & Keller, M.L. (1999). An instrument to measure die attentional demands of community-dwelling elders. Journal of Nursing Measurement, 7(2), 197-214.
- Kaplan, S., & Kaplan, R. (1983). Cognition and environment. New York: Praeger.
- Kaplan, R, & Kaplan, S. (1989). The experience of nature: A psychological perspective. New York: Cambridge University.
- Kaplan, S. (1995). The restorative benefits of nature: Toward an integrative framework. Journal of Environmental Psychology, 15(3), 169-182.
- Keefover, R. W. (1998). Aging and cognition. Neurologic Clinics, /6(3), 635-648.
- Kelly, J.R. (1996). Leisure. In J.E. Birren (Ed.), Encyclopedia of gerontology: Age, aging, and the aged: VoL 2 (pp. 19-30). New York: Academic Press.
- Lawton, M.P. (1988). Scales to measure competence in everyday activities. Psychopharmacology Bulletin, 24(4), 609-614.
- Lemelin, S., & Baruch, P. (1998). Clinical psychomotor retardation and attention in depression. Journal of Psychiatric Research, 32(2), 81-88.
- Lezak, M.D. (1995). Neuropsychological assessment (3rd ed.). New York: Oxford University Press.
- Lindenberger, U., Marsiske, M., & Baltes, PB. (2000). Memorizing while walking: Increase in dual-task costs from young adukhood to old age. Psychology and Aging, 15(3), 417-436.
- Loberg, T. (1986). Neuropsychological findings in the early and middle phases of alcoholism. In I. Grant, & K.M. Adams (Eds.), Neuropsychological assessment of neuropsychiatrie disorders (pp. 415-440). New York: Oxford University Press.
- Lopata, H.Z. (1993). widows: Social integration and activity. InJ1R. Kelly (Ed.), Activity and aging: Staying involved in Uter life (pp. 99- 1 05). Newbury Park, CA: Sage.
- Mayfield, D., McLeod, G., & Hall, P. (1974). The CAGE questionnaire: Validation of a new alcoholism screening instrument. American Journal of Psychiatry, /3/(10), 1121-1123.
- McKnight, A.J., & McKnight, A.S. (1999). Multivariate analysis of age-related driver ability and performance deficits. Accident Analysis and Prevention, 31(5), 445-454.
- Park, D.C., & Gutchess, A.H. (2000). Cognitive aging and everyday life. In D. Park, & N. Schwarz (Eds.), Cognitive aging (pp. 217232). Philadelphia: Psychology Press.
- Pfeiffer, E. (1975). A short portable mental status questionnaire for the assessment of organic brain deficit in elderly patients. Journal of the American Geriatria Society, 23(10), 433-441.
- Raz, N. (2000). Aging of die brain and its impact on cognitive performance: Integration of structural and functional findings. In F.I.M. Craik, & TA. Salthouse (Eds.), The handbook of aging and cognition (2nd ed., pp. 1-90). Mahwah, NJ: Lawrence Erlbaum Associates.
- Reitan, R.M. (1958). Validity of the trail making test as an indicator of organic brain damage. Perceptual and Motor Skilh, 8, 271-276.
- Reuter-Lorenz, P.A. (2000). Cognitive neuropsychology of the brain. In D. Park, & N. Schwarz (Eds.), Cognitive aging (pp. 93114). Philadelphia: Psychology Press.
- Sheikh, J.I., & Yesavage, JA. (1986). Geriatric Depression Scale (GDS): Recent evidence and development of a shorter version. In T. L. Brink (Ed.), Clinical gerontology: A guide to assessment and intervention (pp. 165-173). New York: HaworuS Press.
- Smith, A. (1 982). Symbol digit modalities test. California: Western Psychological Services.
- Spreen, O., & Strauss, E. (1991). A compendium of neuropsychological tests. New York: Oxford University Press.
- Tennessen, CM, & Cimprich, B. (1995). Views to nature: Effects on attention. Journal of Environmental Psychology, 15, 77-85.
- Tun, P.A. (1998). Fast noisy speech: Age differences in processing rapid speech with background noise. Psychology and Aging, 13(3), 424-434.
- Ulrich, R. (1984). View through a window may influence recovery from surgery. Science, 224,420-421.
- U.S. Census Bureau (1999). Annual population estimates by age group and sex, selected years from 1990 to 1999 [Online]. Available: http:// www.census.gov/popuktion/estirnates/nation/inrfile2-l.txt [1999, July 1 1].
- von Hippel, W, Silver, L.A., & Lynch, M.E. (2000). Stereotyping against your will: The role of inhibitory ability in stereotyping and prejudice among die elderly. Personality and Social Psychology Bulletin, 26(5), 523-532.
- Williams, RA., Hagerty, B.M., Cimprich, B., Therrien, B., Bay, E., & Oe, H. (2000). Changes in directed attention and short-term memory in depression. Journal of Psychiatric Research, 34(3), 227-238.
- Zakzanis, K., Leach, L., & Kaplan, E. (1998). On die nature and pattern of neurocognitive function in major depressive disorder. Neuropsychiatry, Neuropsychology, & Behavioral Neurology, 11(3), 111-119.
Attentional Demands Survey (ADS) Means and Ranges (N = 72)
Attentional Demands, Depressive Symptoms, Functional and Health Status Pearson r Correlations (N = 72)
Multiple Regression of Age, Education, Health, Functional Status, and Attentional Demands on Capacity to Direct Attention [N = 72)*