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. Author manuscript; available in PMC: 2019 Apr 30.
Published in final edited form as: Nurs Res. 1994 Jul-Aug;43(4):212–218.

Predictors of Metamemory In Older Adults

GRAHAM J McDOUGALL 1
PMCID: PMC6488932  NIHMSID: NIHMS1017222  PMID: 8047425

Abstract

The purpose of this study was to examine the relationships of depression, health status, self-efficacy, and selected demographic variables to the metamemory of older adults. Community-residing adults (N = 169), 55 years of age and older, were recruited from continuing education programs. No relationships were found between age and seven metamemory factors, Strategy, Task, Capacity, Change, Anxiety, Achievement, and Locus. Those in the age group 65 to 74 years scored significantly higher on the metamemory Strategy factor. Memory efficacy, both level and strength, was significantly correlated (p < .01) with the Capacity, Change, Anxiety, and Locus subscales. Overall, the set of variables accounted for 4% to 21% of the total variance in metamemory factors.

General or specific incidents of forgetting are often used by older adults to interpret the effectiveness of their memory ability and awareness. Poon (1985) reported that 80% of elderly people living in the community were concerned about forgetfulness and memory problems. According to Cutler and Grimes (1988), memory problems during the past year were reported by 15% of those 55 and older and 23% of those 85 and older. Many of the cognitive changes and individual assessments of change often attributed to aging may be due, in part, to psychosocial and environmental factors rather than biological decrement. These factors may be modifiable (Perlmutter et al., 1987; Schooler, 1987). The purpose of this study was to examine the relationships of depression, health status, self-efficacy, and selected demographic variables to the metamemory of older adults.

Review of the Literature

Closely related to memory is the construct metamemory derived from metacognition. Metacognition, the supraordinate construct, initially referred to the self-monitoring of cognitive processes and the influences self-monitoring had on these processes when they were focused on a specific task or goal (Flavell, 1979). The learner’s knowledge of person, task, and strategy variables was emphasized. Flavell later defined metacognition as the monitoring of social cognitive enterprises to include all intellectual endeavors in which the aim was to think or learn about social or psychological processes in the self, individual others, or human groups of all sizes and kinds, including social organizations, nations, and people in general (1981). A social-cognitive enterprise could be brief or extended. This definition included thinking about any process or property of self or others. Researchers interested in metacognitive phenomena initially investigated children’s learning strategies to help them improve cognitive enterprises, such as comprehension or memory (Brown, 1978; Weinstein & Mayer, 1985). This research emphasized aspects of executive control, such as planning, monitoring, and revising one’s thinking. Current metacognitive research combines both approaches to metacognition, emphasizing knowledge about cognitive states and processes, and control or executive aspects of metacognition (Paris & Winograd, 1990).

Metamemory, defined from the developmental perspective, is an individual’s knowledge, perceptions, and beliefs about the functioning, development, and capacities of one’s own memory and the human memory system. This knowledge includes memory-relevant characteristics, such as awareness of the demand characteristics of particular tasks or situations and the availability and employability of relevant strategies and aids (Hultsch, Hertzog, Dixon, & Davidson, 1988). Memory performance is known to vary as a function of subject state, such as physical and emotional status and self-efficacy. Yet, memory researchers have not adequately incorporated these last two factors into their theories or investigations (Perlmutter, 1988). If older persons’ perceptions of their memories prove to be one link in a process relating the social and cognitive domains, then metamemory is of interest even if it is not a substitute for memory performance measures (Hultsch et al., 1988).

The distinction in perceptions of cognitive functioning between young-old and old-old age appears to be important in understanding self-reported memory functioning, memory test performance, and performance on tests of intellectual ability (Schaie & Geiwitz, 1982). Investigators report that when depression is treated successfully, memory complaints decrease (Popkin, Gallagher, Thompson, & Moore, 1982) and memory performance is improved (Zarit, Gallagher, & Kramer, 1981). Memory-complaint studies of a clinical nature include depression, which has been viewed by some as antecedent to the relationship between memory complaint and performance (West, Boatwright, & Schleser, 1984).

Clearly, identifying risk factors influencing cognitive aging is important. The relationship between memory complaint, memory performance, and affective status was clarified in a recent study by Scogin, Storandt, and Lott (1985). Differences between groups of old “complainers” and “noncomplainers” on measures of memory, metamemory, and depression were examined. Complainers and noncomplainers fared differently on metamemory measures, but there were minimal group differences in memory performance and no differences on depression. These results suggest that memory complaint is not always related to memory performance or depression. The meaning and function of memory complaint remains perplexing, since complainers and noncomplainers were not differentiated by depression scores or objective memory abilities (Scogin et al., 1985).

In a memory training study with younger and older adults, Weaver and Lachman (1989) observed that those older individuals who had minor depression became more accurate in their performance predictions over time than those who had major depression. Depression and anxiety may moderate the effects of age changes on an individual’s perception of memory performance (McDougall, 1993; O’Connor, Pollitt, Roth, Brook, & Reiss, 1990; Zelinski, Gilewski, & Anthony-Bergstone, 1990).

A major criticism of cognitive aging research has been that more than 35% of 263 published studies reviewed during the period 1975–1982 failed to report the health of the subjects (Camp, West, & Poon, 1989; Christensen, Moye, Armson, & Kern, 1992). Health in older adults is usually defined in one of three ways: presence or absence of disease; how well the person functions; or general sense of well-being (Shanas & Maddox, 1985). Poor health or presence of chronic illness requires greater use of medications and may affect cognitive functioning (Office of Technology Assessment, 1987; Perlmutter et al., 1987). In a major health survey of adults 55 years of age and older from the National Health Interview Survey of 1984, Cutler and Grimes (1988) found that several measures of health, functional limitations, and sensory impairments best predicted everyday memory problems but only accounted for 7% of the variance. A measure of depression was recommended to be included in future studies.

In another community sample of older adults (N = 1,491), self-reports of memory were strongly and positively related to physical health and negatively related to depression and cognitive rigidity (Herzog & Rodgers, 1989). Gilewski, Zelinski, and Schaie (1990) found self-ratings of health to account for 17% of the variance in self-assessed memory scores. Memory loss resulting from prescription and over-the-counter drugs is significant but not well understood or researched (Avron, 1983; Halliday, Callaway, Naylor, Gratzinger, & Prael, 1986). Therefore, medications must also be included to determine their influence on cognitive function. No studies, however, distinguished among self-perceived health status, medications, and chronic conditions in older subjects. Even though the Cutler and Grimes study contained an extremely large sample (N = 14,783) and the major dependent variable was memory problems, it was methodologically flawed by inadequate measures. Individuals were asked the following two questions about memory: (a) In the past year, about how often did you have trouble remembering things — frequently, sometimes, rarely, or never? (b) Excluding never, does this happen now more often, less often, or about the same compared with a year ago? Self-reported health was determined based on responses to the question, Would you say your health in general is excellent, very good, good, fair, or poor?

In studies of self-care behaviors in the elderly, memory complaints and forgetfulness were rated the least serious, and, typically, most older adults took no action (Brody & Kleban, 1981; Haug, Wykle, & Namazi, 1989; Holtzman, Akiyama, & Maxwell, 1986; Kaszniak, 1986). Even though memory abilities were comparable among individuals, studies indicated that the level of complaint might be related to lower self-evaluation, increase in self-blame, helpless behavior, and premature termination of effort. Robertson-Tchabo (1980) and Robertson-Tchabo, Hausman, and Arenberg (1976) proposed two hypotheses: (a) Individuals with complaints avoid situations because of fear of failure, and (b) complaints are based in part on recognition of and frustration with a failing system.

The link to memory complaints may be related to self-perceptions and beliefs about cognitive function (Herrmann, 1990). Although metamemory instruments are poor indicators of memory performance, with typical correlations in the .20 to .30 range (Hultsch et al, 1988), they may, nevertheless, elucidate the properties of beliefs that underlie performance (Herrmann, 1982, 1983). Self-efficacy has been considered a mediating factor in the improvement of the memory abilities of older adults trained in the use of mnemonic strategies (Rebok & Balcerak, 1989; Rebok & Offerman, 1983). Bandura’s (1991) self-efficacy construct is based on an individual’s judgment about how well one can organize and execute courses of action required to deal with prospective and unpredictable situations — some of which may be ambiguous, unpredictable, and often stress producing. Self-efficacy provides a mechanism to understand how individuals exercise influence over their motivation and behavior. Judgments of efficacy determine behavior to be chosen, affecting the amount of effort one devotes to a task and the duration of one’s persistence when encountering difficulties. Individuals who have a decrease in confidence may give up trying because of efficacy doubts in achieving a desired level of performance, or they may be convinced of abilities but give up trying because of an unresponsive or punishing environment.

Hertzog, Dixon, and Hultsch (1990) stated that little is known at this time regarding memory self-efficacy beliefs across different contexts and processes, nor do we understand the structure of the belief system or the way aging affects mechanisms relating to access and evaluation of propositions about the “self” stored in memory. Researchers are only now beginning to understand the complexity of the self-efficacy relationship with human cognition, affect, and behavior (Berry, West, & Dennehey, 1989; Lachman, Steinberg, & Trotter, 1987). According to Bandura (1989), the cognitive, affective, and motivational processes activated by beliefs of self-efficacy may enhance or impair memory performance.

When metamemory factors from the Metamemory in Adulthood Questionnaire (MIA) were compared between university students and community-residing elders, age and sex differences were reported in seven multinational samples (Hultsch, Hertzog, & Dixon, 1987; Hultsch et al., 1988). The influence of age accounted for ranges of variance on three MIA subscales: Capacity, range 3% to 10%; Change, range 13% to 37%; Locus, range 3% to 19%. Only one of the seven samples in the older age groups had significant age differences in Strategy scores. Subjects between the ages of 55 and 6l years (n = 73) scored significantly higher (M = 67.21) on Strategy use than the other age groups. Metamemory knowledge has implications for the remediation of memory deficits in the elderly. According to Diller and Gordon (1981), strategic and adaptive behaviors are often more amenable to change than are cognitive deficits, such as dementia. Thus, should metamemory prove to mediate the relationship between memory and everyday functioning, it would be a logical point for remedial intervention. Since all previous studies of metamemory in adulthood have compared older adults to younger college-aged adults, intragroup age differences could not be determined. The purpose of this study was to determine the contribution of age, depression, sex, health status, and self-efficacy beliefs in predicting metamemory among community-dwelling older adults.

Method

Sample

The nonprobability sample for this study consisted of 128 (76%) females and 41 (24%) males, 55 years and older, attending two continuing education (CE) programs, one in central Texas (26%) and one in southern Louisiana (74%). The majority of the participants were white (96%); the remainder were black. Forty-one percent of the individuals were married (N = 69); 37% widowed (n = 63); 10% divorced (n = 17); and 12% never married (n = 20). Subjects ranged in age from 55 to 83 years (M = 67–94, SD = 6.30). Males were significantly younger (M = 66.15, SD = 6.83) than females (M = 68.51, SD = 6.03), F(1, 167) = 4.459, p < .05. Seventy percent of the subjects belonged to at least two organizations, with many belonging to five. Yearly incomes (n = 100) ranged from $3,000 to $450,000. Seventy-three percent of the subjects earned between $3,000 and $33,000. Only three individuals earned more than $83,000 per year. The overall return rate for the Louisiana program was 6l%; for the Texas program, 100%. Questionnaire completion time as reported by 119 individuals ranged from 20 minutes to 180 minutes.

Instruments

Data were collected with self-report, self-administered questionnaires. Five types of self-evaluation instruments measuring memory knowledge are currently available: metamemory questionnaires, memory-complaint questionnaires, self-efficacy measures, task-specific predictions, and feeling-of-knowing or confidence ratings (Berry et al., 1989). The use of questionnaires by older adults for self-assessment of cognitive functions offers researchers a method to investigate everyday memory phenomena. The concern with the ecological validity of cognitive research implies a neofunctionalist approach or pragmatism, that is, that the phenomena under investigation relate to actual experience and activity, as opposed to cognitive research, which is artificial and removed from everyday events and concerns (Hoffman & Diffenbacher, 1992). The metamemory questionnaire emphasizes ecologically relevant activities.

The Metamemory in Adulthood Questionnaire (Dixon & Hultsch, 1983; Dixon, Hultsch, & Hertzog, 1988) is a measure of the memory components of knowledge, beliefs, and affect. The MIA consists of 108 statements, with responses rated on a 5-point Likert scale. The seven subscales measure Strategy, Task, Capacity, Change, Anxiety, Achievement, and Locus. Strategy is knowledge of one’s remembering abilities, such that performance in given instances is potentially improved; it includes reported use of mnemonics, strategies, and memory aids. Task is knowledge of basic memory processes, especially the knowledge of how most people perform. Capacity is the perception of memory capacities as measured by predictive report of performance on given tasks. Change is the perception of memory abilities as generally stable or subject to long-term decline. Anxiety is the rating of the influence of anxiety and stress on performance. Achievement is the perceived importance of having a good memory and of performing well on memory tasks. Locus is the individual’s perceived personal control over remembering abilities.

The MIA’s psychometric characteristics have been examined with community-dwelling middle-aged and older adults. Cronbach’s alphas for the seven subscales are reported as: Strategy, .85; Task, .84; Capacity, .85; Change, .92; Anxiety, .83; Achievement, .80; and Locus, .79. In the present study, Cronbach’s alpha for each scale varied considerably from .73 to .95. Intercorrelations between the MIA subscales range from extremely low, −.05, to moderate, .60 (Dixon et al., 1988).

Memory self-efficacy was operationalized with the Memory Self-Efficacy Questionnaire (MSEQ), a Guttman scale consisting of 50 questions (Berry et al., 1989). The MSEQ, derived from Bandura’s self-efficacy methodology, is a self-report assessment tool consisting of multiple indices to obtain direct memory predictions from older adults regarding self-efficacy level (SEL) and strength (SEST). Ten memory tasks are included. These relate to groceries, phone, picture, location, word, digit, map, errands, photographs, and a maze. Internal consistencies for the eight scales were high: r (SEL) = .90 and r (SEST) = .92. Criterion-related or predictive validity was determined by dividing the scales into two logical groupings: laboratory tasks (word, picture, digit, and maze) and everyday tasks (map, location, phone, and grocery). Satisfactory internal consistency estimates were obtained for the laboratory tasks, r (SEL) = .88, r (SEST) = .90, and for everyday tasks, r (SEL) = .74, r (SEST) = .78. The eight MSEQ subscales are moderately to highly correlated, ranging from .25 to .79 for SEL and .38 to .74 for SEST, which suggests that the eight MSEQ tasks are similar with overlapping characteristics (Berry et al, 1989).

Depression was operationalized with the short version of the Geriatric Depression Scale (GDS) (Brink et al., 1982; Sheikh & Yesavage, 1986). The 15-item instrument has a Yes/No response format. Scores range from 0 to 15, with a score ≥ 5 indicating depression. The GDS correlates highly with other depression measures; the authors reported an alpha reliability coefficient of .94 and a split-half reliability of .94 (Yesavage et al., 1983). The coefficient alpha in this sample was .73.

Health status was operationalized by the Health Scale, a subscale of the Multilevel Assessment Instrument (Lawton, Moss, Fulcomer, & Kleban, 1982). Subjects rated the quality of their health using a 4-point response format, with higher scores indicating better health. Total scores of the 4-item tool range from 4 to 13. Anchors are “better” to “not so good” and “excellent” to “poor.” Lawton et al. (1982) reported an alpha coefficient of .76 and test-retest correlation of .92. Alpha in the present study was .75. Chronic conditions and prescription medications known to affect memory functioning by causing or simulating dementia were included as predictor variables. Subjects responded to a checklist of common chronic conditions known to affect cognitive functioning and provided a list of their prescription medications.

Procedure

Informed consent was obtained by having potential subjects sign a consent letter before agreeing to participate. In Louisiana, the investigator gave a 10-minute presentation during classes to enlist volunteers, answer questions, and discuss concerns about the nature of the study. Questionnaire packets and self-addressed stamped envelopes were distributed to individuals who signed an informed consent indicating their willingness to participate. Participants then returned the packets to the investigator. The return rate was 54%.

In the Texas program, information about the research study was posted near the administrative office on the community bulletin board. Individuals who signed their names and phone numbers to indicate interest were then contacted by the investigator, by telephone, to discuss the project and answer questions. A survey packet and self-addressed stamped envelope were mailed to each person wishing to participate. Questionnaires were returned to the investigator upon completion. The return rate for the Texas sample was 100%.

Results

Research on cognitive aging has typically emphasized average age-related losses over 20- to 40-year spans and neglected the substantial heterogeneity of older persons between and within age groups (Kahn, Zarit, Hilbert, & Niedehrehe, 1975; Rowe & Kahn, 1987). The differential distribution of self-perceived health, actual chronic conditions, and frequent memory complaints with age is a serious consideration in a cross-sectional design (Siegler, Nowlin, & Blumenthal, 1980). The sample was therefore divided into three age groups spanning 10 years: the young-old (ages 55 to 64, N = 50); the middle-old (ages 65 to 74, n = 90); and the old-old (ages 75 to 83, n = 29). Means, standard deviations, and ranges were calculated on all predictor variables and criterion variables according to the three age groupings (Tables 1 and 2). Analysis of variance indicated significant (p < .05) age group differences on four variables: medications, memory-efficacy, both level and strength, and MIA strategy scores. Post-hoc comparisons were done using Fischer’s LSD to examine group differences. The oldest age group reported taking significantly more prescription medications than the young-old and middle-old groups, M = 2.66, SD = 1.14, F (2,166) = 3.9. The oldest age group had significantly lower memory-efficacy level scores, M= 3–02, SD = 3.02, F (2,166) = 3.437, and memory efficacy-strength scores, M = 44.67, SD = 17.16, F (2,166) = 3.222, than the young-old group. The middle-old group’s strategy scores were significantly higher than the young-old and old-old groups, M = 66.44, SD = 8.40, F (2,166) = 4.563.

Table 1.

Means and Standard Deviations for Predictor Variables, Three Age Groups

Young 55 to 64 (n = 50) Middle 65 to 74 (n = 90) Older 75 to 83(n = 29)
M (SD) M (SD) M (SD)
Health 10.10 (1.57) 10.20 (1.83) 9.5 (2.32)
Chronic illness 1.15 (1.05) 1.54 (1.32) 1.96 (1.67)
Depression 1.38 (2.12) 1.26 (1.75) 1.62 (1.99)
Prescription medications 1.94 (1.71) 2.43 (1.45) 2.66 (1.14)
Memory efficacy-level 3.52 (.82) 3.21 (.88) 3.02 (.94)
Memory efficacy-strength 54.35 (15.28) 50.33 (16.70) 44.16 (17.16)
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Table 2.

Means and Standard Deviations for Criterion Variables (MIA), Three Age Groups

Young 55 to 64 (n = 50) Middle 65 to 74 (n = 90) Older 75 to 83 (n = 29)
M (SD) M (SD) M (SD)
Strategy 62.66 (9.50) 66.40 (8.92) 61.86 (8.92)
Task 63.30 (6.64) 63.04 (6.37) 62.72 (6.74)
Capacity 52.90 (9.33) 55.03 (9.42) 53.38 (9.91)
Change 52.44 (11.05) 50.21 (13.38) 47.72 (13.37)
Anxiety 43.06 (8.23) 44.25 (7.91) 45.90 (9.03)
Achievement 57.96 (8.34) 59.47 (6.81) 59.28 (7.47)
Locus 30.42 (5.53) 32.02 (4.62) 31.43 (5.17)
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Subjects were also compared on predictor and criterion variables according to state of participation (Louisiana or Texas). Significant differences were observed on two predictor variables, age and number of chronic conditions. The Louisiana sample was significantly older, M = 68.38, SD = 6.02, than the Texas sample, M = 65.41, SD = 6.00, F (1,158) = 7.787, p < .05. The Louisiana sample also had significantly more chronic conditions, M = 1.67, SD = 1.41, than the Texas sample, M = 1.05, SD = 1.01, F(1,153) = 6.591, p < .05. Since no significant differences were found between the two samples on metamemory factors, the groups were collapsed for data analysis.

Pearson product moment correlations between age as a continuous variable and the seven metamemory factors were nonsignificant. Due to significant age group differences and nonlinearity of the Strategy scores, manovas were calculated on all seven metamemory factors, using the three age groups as the independent variable. Significant differences were found among the three groups, with the middle-old group scoring significantly higher than the young-old and old-old groups on the Strategy subscale, F (14,316), Wilks’s lambda = .888, p = .038. The young-old and old-old Strategy scores were almost identical. Pearson product moment correlations were also computed between memory-efficacy strength and level scores to determine if any multicollinearity was present. Since the correlation (r = .86) was high, only memory-efficacy strength scores were used in the regression analysis.

Multiple regression analyses were conducted to study the effects of demographic variables in conjunction with the study variables (depression, health status, and memory self-efficacy strength) on the metamemory outcome variables of Strategy, Task, Capacity, Change, Anxiety, Achievement, and Locus.

In the first step, the demographic variables were tested by entering age and sex into the models. In the second step, demographic variables in combination with depression were entered. In the third step, demographic variables, depression and health status, chronic conditions, prescription medications, memory self-efficacy strength, and memory self-efficacy level were entered into the models.

In each regression, age and sex were entered first; however; they only predicted 4% of the variance in the change scale. Second, age and sex along with depression were entered. Of these, only one, the Change scale, met the entry criteria for inclusion. Together, the demographic and depression variables accounted for 7% of the variance in Change and 9% of the variance in Anxiety subscale scores. Third, analyses were conducted to determine whether the addition of health status, prescription medications, and memory self-efficacy strength would increase the amount of variance explained. No combination of the demographic, depression, and study variables predicted the Achievement, Strategy, or Task subscale scores. The addition of the variables increased the overall R2 by 12% in the Anxiety scores and by 14% in the Change scores. The set of study variables in Step 3 accounted for 21% of the variance in Capacity scores and 17% of the variance in the Locus scores. Results of regressions for each outcome variable are presented in Table 3.

Table 3.

Multiple Regression Analyses of Demographic and Study Variables to the Metamemory in Adulthood Subscales

Predictor Variable Entered R R2 Adj. R2 Beta F
Capacity Subscale
Health status .25 .06 .06 .18 10.77
Self-efficacy .42 .18 .17 .34 17.65
Change Subscale
Health status .25 .06 .06 .19 10.73
Self-efficacy .37 .14 .13 .29 13.50
Anxiety Subscale
Health status .35 .12 .11 −.30 22.66
Self-efficacy .43 .18 .17 −.26 18.64
Locus Subscale
Health status .23 .05 .05 .18 9.53
Self-efficacy .37 .14 .13 .30 13.45
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N = 169

Discussion

The low incidence and invariance in depression scores may have accounted for this variable’s ability to predict only two of the seven metamemory factors, Anxiety and Change. A confounding effect may be operating between depression and health status, such that the significant effect of depression on the outcome variables is cancelled in the aggregate set of predictor variables. Eleven individuals (6.6%) in the present study scored within the mildly depressed range, between 5 and 9 on the GDS. This is contrary to findings reported in current literature, where the incidence of depression in a community sample was as high as 27% (Blazer, 1990). In a previous study, McDougall (1993) reported significant inverse relationships between depression (even though scores on the Zung Self-Rating Depression Scale [SDS], M = 33.00, SD = 7.08, indicated little depression) and the metamemory factors: frequency of forgetting (r = −.49), remembering past events (r = −.45), retrospective functioning (r = −.34), seriousness of forgetting (r = −.39), and mnemonics usage (r = −.40). The Geriatric Depression Scale may not be as sensitive a screening instrument as the SDS. The low incidence of depression in the present study may also be a function of the characteristics of the sample, such as their high perceived health status, low numbers of chronic conditions, and prescription medications.

McDougall (1993) reported significant relationships between depression and mnemonics usage (r = −.39) and general self-efficacy and mnemonics usage (r = .51). Depression scores of the 75 and older (M = 1.62, SD = 1.99) group were significantly higher than those of the young-old and middle-old groups. Even though the older group in this sample had higher depression scores, they used mnemonic strategies less often. In the current study, the middle-old group reported significantly greater use of mnemonic strategies, M = 66.40, SD = 8.92, F (2,166), p < .05. The Strategy subscale determines an individual’s ability not only to know about memory strategies, both internal and external, but also to use cognitive strategies, such as mnemonics and other memory aids. A high score results from the reported frequent use of memory aids. The increased use of memory strategies may be related to an individual’s affective response, such as anxiety, and to the cognitive demands of a particular situation.

In general, older adults have limited repertoires of memory strategies and often do not use effective memory strategies (Dixon et al, 1988; Perlmutter, 1988). However, when given appropriate instructions, they are capable of using strategies that improve their memory perfonnance. An individuars performance is shaped by an understanding of a particular situation, such as cognitive demand characteristics, perception of likely outcomes of behavior, and use of both internal and external meniory aids (Cavanaugh & Murphy, 1986; Hultsch et al., 1987). Gilewski, Zelinski, and Schaie (1990) predicted a greater use of mnemonic strategies in the cognitively impaired elderly than in the elderly with depression. However, since cognitive status in this sample was not determined, future studies are needed to determine if this hypothesis is accurate.

Self-efficacy, specifically memory-efficacy strength (M = 50.79) scores, were comparable to other studies of memory self-efficacy. Since the MSEQ is relatively new, there are only two published studies available for comparison. In the Berry et al. (1989) seminal study, average MSEQ strength scores were 49.7 (Experiment 1), 51.1 (Experiment 3, pretest), and 45–5 (Experiment 3, posttest). Subjects from Experiment 1 were recruited from a newspaper advertisement offering memory training for older adults with memory difficulties. Recruitment procedures were not mentioned for Experiment 3-Weaver and Lachman (1989) reported mean MSEQ scores of 37.18 in a sample of 45 community-residing adults with a mean age of 68.40. Older adults in the Lachman study were highly educated (M = 15.20 years) and had medical problems (M = .74). Of comparable interest was that younger subjects (M = 18.93) scored 54.98 on the MSEQ strength component. Presence or absence of depression in subjects was not reported.

Even though the correlations between age and memory-efficacy strength (r = −.24) and level (r = −.24) were statistically nonsignificant, they are in line with those produced between age and general self-efficacy (r = −.38) in a previous study of similar adult participants (McDougall, 1993). If these results are not due to chance, then older individuals have less belief in their ability to execute a plan of action in situations requiring use of memory. Hertzog et al. (1990) noted that little is known at this time regarding memory self-efficacy beliefs across different contexts and processes, and that we do not understand the structure of the belief system or the way aging affects mechanisms relating to access and evaluation of propositions about the “self” stored in memory. Results of this investigation suggest that for this sample of older adults without any measurable depression, with a high perceived health status (M = 10.05, SD = 1.88) and a low number of chronic conditions and prescription medications, beliefs about memory may be inversely influenced by age.

A significant positive relationship was found between memory-efficacy strength and health status (r = .25). Positive relationships were found between numbers of chronic conditions and medications (r = .61, p < .01), and memory-efficacy strength and level (r = .71, p < .01). These findings indicate that for this group of older adults, the greater their perceived health status, the greater their perceived memory efficacy. These results support those of Lachman and Leff (1989), who found that individuals experiencing multiple chronic illness had a decreased sense of efficacy for intellectual tasks.

Medication and chronic conditions as variables have not been investigated to date in connection with metamemory factors. The older adults in the present study reported at least one chronic condition (M = 1.49, SD = 1.33) and consumed between one and three prescription medications daily (M = 1.69, SD = 1.68). Categories of prescription medications were not separated in the analysis. When relationships between medication, chronic conditions, and metamemory factors were examined, the results were nonsignificant.

Acknowledgments

Earlier versions of this paper were presented at the 1991 meeting of the Gerontological Society of America, the 1992 Sigma Theta Tau International State of the Science Congress, the 1992 American Nurses Association meeting, and the 1993 Midwest Nursing Research Society meeting. The author acknowledges the editorial assistance of Florence S. Downs, EdD, FAAN, Steve Zyzanski, PhD, JoAnne Youngblut, PhD, RN, and Linda Menzel, PhD, RN, and helpful comments on drafts of this manuscript. This research was supported by the American Nurses Foundation.

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