Evidence of a Relationship Between Need For Cognition and Chronological Age: Implications For Persuasion in Consumer Research

Harlan Spotts, Northeastern University
ABSTRACT - Originally developed in the persuasion literature by social psychologists, the need for cognition construct has received much interest from researchers in a variety of disciplines. Need for cognition has recently become a topic of interest among consumer researchers examining advertising effects. The research presented in this paper provides evidence of a potential interactive relationship between the primary variables in the ELM that control route to persuasion. Specifically, age-related declines in cognitive ability affect the motivational variable, need for cognition. This points to the possibility that need for cognition may be a dynamic factor that changes over time with respect to age-related cognitive processing changes. Implications for future research in information processing and persuasion are discussed.
[ to cite ]:
Harlan Spotts (1994) ,"Evidence of a Relationship Between Need For Cognition and Chronological Age: Implications For Persuasion in Consumer Research", in NA - Advances in Consumer Research Volume 21, eds. Chris T. Allen and Deborah Roedder John, Provo, UT : Association for Consumer Research, Pages: 238-243.

Advances in Consumer Research Volume 21, 1994      Pages 238-243

EVIDENCE OF A RELATIONSHIP BETWEEN NEED FOR COGNITION AND CHRONOLOGICAL AGE: IMPLICATIONS FOR PERSUASION IN CONSUMER RESEARCH

Harlan Spotts, Northeastern University

ABSTRACT -

Originally developed in the persuasion literature by social psychologists, the need for cognition construct has received much interest from researchers in a variety of disciplines. Need for cognition has recently become a topic of interest among consumer researchers examining advertising effects. The research presented in this paper provides evidence of a potential interactive relationship between the primary variables in the ELM that control route to persuasion. Specifically, age-related declines in cognitive ability affect the motivational variable, need for cognition. This points to the possibility that need for cognition may be a dynamic factor that changes over time with respect to age-related cognitive processing changes. Implications for future research in information processing and persuasion are discussed.

INTRODUCTION

Consumer researchers have recently shown increased interest in the construct of need for cognition and its impact on marketing communications within an advertising context. Need for cognition refers to a person's desire to engage in and enjoy effortful cognitive processing, or thinking. The construct has significant effect on the persuasion process as detailed by the Elaboration Likelihood Model (ELM, Petty and Cacioppo 1986).

While age-related issues in consumer research have received less scrutiny, numerous researchers have studied the impact of chronological age on consumer behavior and information processing. Aging has been shown to impact shopping behavior (Lumpkin 1985), information usage (Bearden and Mason 1979, Cole and Houston 1987), and media behavior (Rubin 1986, Davis and French 1989).

Gerontological research has studied the cognitive processing changes that occur with age. Older adults (over the age of 60) appear to have deficits in memory performance, constraints on cognitive resources used in attentional processes, difficulty in discriminating relevant from irrelevant stimuli, and, are slower in learning new information.

Taken together, findings from consumer research and gerontology indicate a potential inverse relationship between need for cognition and chronological age. After a brief review of need for cognition and gerontological research on cognitive processing, two studies are reported that specifically examine the need for cognition and aging relationship. Implications of this relationship on the persuasion process and potential research propositions are then discussed.

LITERATURE REVIEW

Need for Cognition

Drawing from the work of Cohen (1957) and Cohen, Stotland and Wolfe (1955), Cacioppo and Petty (1982) redefined and developed need for cognition as an individual difference variable affecting the persuasion process. Need for cognition reflects an "...individual's tendency to engage in and enjoy effortful cognitive endeavors..."(Cacioppo, Petty and Kao 1984). A series of studies by Cacioppo and Petty (1982; Cacioppo, Petty and Morris 1983, Cacioppo, Petty and Kao 1984, Cacioppo, Petty, Kao and Rodriguez 1986) developed an 18 item scale for assessing a person's need for cognition. Individuals who score high in need for cognition like effortful thinking, such as solving puzzles, extensive deliberation, and thinking abstractly. Those individuals who are low in need for cognition avoid effortful thinking.

In the context of the ELM, need for cognition was developed as an individual difference variable potentially affecting a person's motivation to process persuasive communication. Individuals high in need for cognition are more likely to attend to message argument quality than individuals low in need for cognition (Cacioppo, Petty and Kao 1983); and, exhibit more extensive issue-relevant thinking and stronger attitude-behavior relationships (Cacioppo, Petty, Kao and Rodriguez 1986). Low need for cognition individuals are more likely to engage in peripheral (heuristic) processing than central (systematic) processing (Axsom, Yates and Chaiken 1987).

Need for Cognition and Consumer Research. Using advertising stimuli, Haugtvedt, Petty, Cacioppo and Steidley (1988) replicated the results of earlier need for cognition studies conducted in other disciplines. Not only were attitudes of high need for cognition individuals primarily influenced by strong message arguments, but attitudes of those low in need for cognition were primarily influenced by product endorser attractiveness. These findings were later supported by other researchers (Batra and Stayman 1990, Haugtvedt, Petty and Cacioppo, 1992).

Further studies indicated that attitudes developed by high need for cognition individuals are more persistent than those developed by low need for cognition individuals (Haugtvedt and Petty, 1989). It has also been shown that message content has a moderating effect on message judgments, with more favorable judgments of factual messages observed as need for cognition increases (Venkatraman, Marlino, Kardes and Sklar 1990). Need for cognition had no impact on judgments of evaluative messages.

Additional effects of need for cognition on attitude formation and change processes existed under the following conditions (Haugtvedt, Petty and Cacioppo, 1992): when people are not explicitly told to evaluate the message, and, when people are exposed to relatively short messages in both paced and self-paced situations. Stayman and Kardes (1992) examined memory recall behavior under conditions of implicit and explicit advertising claims. Need for cognition was found to have an impact on retrieval processes under conditions of implicit advertising claims, with recall scores similar to those subjects given explicit advertising claims.

Thus, it becomes clear that need for cognition impacts the processing of information in persuasive messages. It appears to be a factor affecting a person's motivation to process, and in turn, the route to persuasion employed. Given the composition of subjects used in prior research (i.e., primarily young, college-age adults), it seems logical to question the nature of need for cognition in the noncollege, adult population. Is need for cognition a stable personality trait, assumed not to change across lifespan? Or, is it a dynamic construct that varies over time within the individual during different life situations and ages? Little research has focused on changes in a person's level of need for cognition as they age. The next section reviews cognitive processing research in gerontology relevant to this issue.

Gerontological Research in Cognitive Processing

A plethora of research findings have documented a decrease in certain processing abilities as one gets older. Deficits have been found in attentional processes (Hasher and Zacks 1979), memory (Craik 1977), problem solving (Reese and Rodeheaver 1985), and learning (Arenberg and Robinson-Tchabo 1977). It has been acknowledged that older adults tend to slow down in terms of processing time (Hoyer and Plude 1980, Birren Woods and Williams 1980) and utilize less information (Johnson 1990). One explanation for these deficits is related to constraints in cognitive processing resources, which affect the attentional capacity of the older adult (Hasher and Zacks, 1979), alter the available capacity of working memory for cognitive elaboration, and/or affect speed of processing (Salthouse, 1988a).

Hasher and Zacks (1979) proposed a framework that suggested attentional capacity affects the type of processing in which adults engage. The more attentional capacity available for cognitive processing, the more likely it is a person will engage in "effortful" cognitive processes. These types of processes include rehearsal of information and elaborative mnemonic activities requiring excessive attentional capacity that drain resources away from other cognitive operations. The framework differentiates effortful processing with "automatic" processing. The latter are cognitive operations that require little attentional capacity; such as, encoding temporal or frequency of occurrence information, or, activities that were originally effortful, but due to repeated practice require little thought to conduct.

It appears to be evident that age-related changes affect the cognitive capacity of older adults. Salthouse (1988b) conceptualized these limitations in three distinct ways. If cognitive processing occurs through the activation of various nodes in memory, then capacity could be constrained through a decrease in the number of simultaneously active nodes (a reduction in working memory). A second alternative relates to the total number of nodes available for activation at any given time (a reduction in attentional capacity). Finally, the rate at which nodes are activated may slowdown, thus increasing the time required to transmit information (a speed of processing decrement).

To this point in the discussion it seems clear that the consequences of aging on cognitive processing would affect the "ability" variable in the persuasion process as delineated by the ELM. In this context ability is one critical variable affecting route to persuasion. Motivation is the other critical variable. Adults who are low in need for cognition are assumed to have lower motivation to process a message. Thus, under some circmstances they are less likely to process messages via the central route.

In the traditional view of the ELM, the ability variable is not perceived as directly affecting the motivational component. The older adult could be highly motivated to process a message, but deficits in attentional capacity make them more susceptible to distraction; and, consequently messages are processed peripherally. It is possible, however, that ability may indirectly affect the persuasion process through motivation. The concept of interactive effects of variables within the persuasion model is not new. Ratneshwar and Chaiken (1991) found that message comprehensibility had a moderating effect on the impact of source expertise by directly affecting a person's ability to systematically process the message.

In the present research, a scarcity of cognitive resources in older adults may affect their motivation to process a message. In fact, past research has shown that older adults opt to process information differently from younger adults. Johnson (1990) found that retirement-age adults (over the age of 60) were more likely to use a noncompensatory decision strategy in product selection. Younger adults were more likely to use compensatory strategies. It was proposed that older adults were compensating for their reduction in processing capacity by utilizing less cognitively demanding decision strategies.

It is apparent that these deficiencies should impact other variables related to information processing. What is important to highlight is that need for cognition may be a dynamic construct that changes over time in relation to age-related changes in cognitive processing. The focus of this discussion pertains to the relationship between need for cognition, chronological age, and how these factors potentially impact the persuasion process. Specifically, the studies document a decline in need for cognition among older adults. The next section of this paper reports two studies that investigate this relationship. Following this, implications for the persuasion process are presented.

METHODOLOGY

Study 1

Two hundred and thirty-eight adults from local civic groups, senior citizen centers and university staff personnel participated in a self-administered survey. As part of a larger study, each participant completed a number of measures, including the need for cognition scale. While more women than men took part in the study, the percent representation of women to men remained proportionally constant within both the younger and older adult age groups (see Table 1). After accounting for missing data, 201 responses remained for analysis.

Measures. Need for cognition was measured using the 18 item short form (Cacioppo, Petty, Kao, and Rodriguez 1984). Responses were recorded on a seven-point agree/disagree scale. Age was measured by asking respondents to indicate how old they were in number of years. Adults were grouped by ages based on standard practices both in consumer and gerontological research, the cut point being 60 years of age.

Results. The need for cognition scale exhibited adequate reliability (alpha = .81, inter-item correlation = .19). One item assessing the degree to which thinking was used to "make one's way to the top" exhibited unusually low item-to-total correlations. It was dropped from the analysis and the remaining 17 items were summed to create an index (alpha = .81, inter-item correlation = .19). Since a 7 point agree-disagree scale was used, participants could receive scores ranging from 17 to 119. The higher the score, the higher the need for cognition. An examination of the mean level of need for cognition showed older adults had significantly lower levels of need for cognition (t = 9.81, p < .001; see Table 1).

Since both need for cognition and age were measured as continuous variables, regression analysis was employed to investigate the relationship between the two variables. The regression of need for cognition on age was significant (F1,200 = 74.887, p < .001) and explained approximately 27 percent of the variance in the dependent variable. [Initial analysis for both studies examined the impact of gender on the results. Gender was not significant in explaining any of the variance in need for cognition and was omitted from the discussion of results.] The regression weight of -.45 was significant (t=-8.64, p<.001) and in the expected direction. To highlight the relationship between the two variables, age was divided into five categories and regression analysis was used to examine group differences. [Age groups do not exactly correspond to age decades due to small cell sizes in the middle of the age range. Subjects in the 40's and 50's decades were grouped together. Additionally, subjects in their 70's, 80's and 90's were combined for the same reason. In the examination of need for cognition scores, the age decades that were combined were not significantly different from each other. Thus, the collapsing of age decades does not subtantively change the analysis or results.] The significant regression weights indicate that older adults had lower scores than younger adults.. For adults under the age of 60, 74 percent had need for cognition scores higher than the median; while for adults over the age of 60, 74 percent had need for cognition scores under the median.

TABLE 1

SUMMARY STATISTICS

TABLE 2

NEED FOR COGNITION SCORES BY AGE DECADE REGRESSION

Prior research found that education influences need for cognition. Since the two age groups exhibited differences in educational level, this may explain the observed differences in need for cognition. It should be noted, however, that examining the impact of education on the relationship cannot fully equate the two age groups since the educational system in this country has undergone tremendous change over the last 50 years. Also, people continue to educate themselves after they have finished formal schooling through a variety of life experiences.

Respondents indicated the number of years of education they had completed. As can be seen in Table 1, young adults had slightly higher levels of education. Chronological age and education had a strong, negative relationship (r = -.637, p < .001). Education also had a positive relationship with need for cognition (r = .46, p < .001). Hierarchical regression was used to examine the impact of age on need for cognition after accounting for education (see Table 3). [The initial analysis included the interaction between need for cognition and age as well as the main effects for each variable. In the first study, this interaction was marginally significant (R2 change F=5.2, p<.10) and explained less than 1 percent of the variance in need for cognition. In the second study, the interaction term was not significant.] Education explained approximately 21 percent of the variance in need for cognition; chronological age explained an additional seven percent of the variance.

This study provided initial evidence of a relationship between need for cognition and chronological age. A second study using a different methodology gathered additional evidence.

Study 2

One hundred and sixty-five adults participated in a mail survey. Subjects were randomly selected from 10 Massachusetts communities. Due to missing data, ten subjects were dropped from the analysis. The need for cognition measure used in Study 1 was again employed. Two modifications were made to the scale. First, the troublesome item from the first study was dropped. Next, a five point response scale was used instead of a seven-point scale. Thus, need for cognition scores could range from 17 to 85.

TABLE 3

EFFECTS OF EDUCATION AND CHRONOLOGICAL AGE ON NEED FOR COGNITION

The average age of adults in this sample was 50. There was a 60/40 split between men and women. The overall proportion of men to women remained relatively constant within both age groups (see Table 1).

Results. The need for cognition scale exhibited adequate reliability (alpha = .91, inter-item correlation = .37). Similar to Study 1, older adults exhibited lower levels of need for cognition than younger adults (t = 5.08, p < .001, see Table 1). The regression weight of -.21 was in the expected direction and significant (t = -4.99, p < .001)

The regression of need for cognition on age was again significant (F1,154 = 24.95, P < .001), explaining approximately 14 percent of the variance in the dependent variable. Approximately 57 percent of younger adults scored above the median need for cognition score; while only 26 percent of older adults scored above the median. Investigation of need for cognition across the five age groups highlights the expected relationship (see Table 2).

This sample exhibited a similar relationship between need for cognition and chronological age to that of Study 1 (r = -.45, p < .001). Education again had a positive correlation with need for cognition (r = .425, p < .001). Results of the hierarchical regression indicated that education explained approximately 18 percent of the variance in need for cognition scores, with chronological age explaining an additional five percent.

DISCUSSION

The results of these two studies provide evidence that need for cognition may be affected by dispositional factors inherent in the individual. Specifically, need for cognition may be a dynamic variable that changes with age. This is not to say that everyone over the age of 60 will have low levels of need for cognition. It may be that other factors affect this relationship, such as physical conditioning and/or health, cognitive age, or other physiological/psychological factors.

Education affected need for cognition, which was expected. It is important to note, however, that even after accounting for the impact of education, chronological age had a small, but significant impact on a person's level of need for cognition.

Limitations. While the theoretical basis for the relationship between need for cognition and chronological age is sound, methodological issues may have kept age from having more of an impact on need for cognition. With respect to sampling, Study 1 employed a convenience sample which may have been biased due to self-selection of subjects. However, given the environment in which subjects were recruited (senior citizen centers) the older adults participating in the study may have been in better health than older adults who were unable to travel to the senior center. Since good health has a positive impact on cognitive processing, it could have been possible that no relationship would have been found. A similar argument could be made for the Study 2 sample since the mail survey respondents may have been in better health and consequently had higher levels of processing capacity than nonrespondents. A strength of the study lies in the similarity of results across different data collection methods, scale points and sample composition (women versus men).

It could be argued that since this is cross-sectional research it is subject to all of the associated deficiencies affecting validity. Salthouse (1988) addresses these issues, specifically, as they relate to gerontological research on cognitive processing. Based on extensive reviews of the literature, he concluded that cross-sectional research yields very similar results to longitudinal research.

RESEARCH DIRECTIONS

The implications of these results are important in relation to the motivation and ability variables that control the persuasion process. This highlights the need for further research into the interactive effects of variables controlling the persuasion process. If physiological changes can directly affect the motivational variable in the ELM, then motivation becomes a function of personal relevance and unique individual characteristics. Investigating the following research proposition would be interesting:

P1: Ability factors in the ELM will have direct effects on route to persuasion (i.e., distraction), as well as indirect effects by affecting motivational factors such as need for cognition.

Given the results of this study, there are issues that deal specifically with the older adult. According to prior research, need for cognition directly affects a person's motivation to process message arguments in an advertisement. The higher the need for cognition, the higher the motivation; thus resulting in more cognitively effortful central processing. One interesting aspect of the need for cognition and aging relationship would be:

P2: Due to lower levels of need for cognition, older adults are are more likely to process advertisements via a peripheral route than central route to persuasion.

Since level of need for cognition has implications for route to persuasion, a variety of issues arise about message effectiveness, frequency of exposure, and media usage. Many of these issues, as related to age, have been explored in prior research in advertising, but not in the context of the ELM. Prior research has shown that high need for cognition individuals are more likely to attend to, synthesize, and integrate advertising message information into existing knowledge and belief structures. Interesting research propositions relating to need for cognition and chronological age would be:

P3: Given lower levels of need for cognition, older adults should process less advertising information, generate fewer cognitive responses and consequently have weaker and/or nonexistent attitude changes.

Advertising information processed via the central route has been shown to have a greater effect on attitude persistence than processing via the peripheral route; these attitudes are more resistant to counterpersuasion and predictive of future behavior. Individuals low in need for cognition have been shown to process advertisements peripherally. Research may investigate the following:

P4: Older adult attitudes developed through advertising messages may be more transient than those of younger adults due to lower levels of cognitive functioning.

P5: Older adults may experience weak or nonexistent attitude change when exposed to advertising messages, thus retaining the stronger prior attitudes; subsequently, they may be less susceptible to attempts at counterpersuasion than younger adults.

Low need for cognition individuals should be more influenced by peripheral cues (i.e., number of message arguments, source attractiveness and/or credibility, presence of pleasant music, celebrities, etc.) than message content. Thus, the following proposition bears investigation:

P6: Older adults may be more attentive to the peripheral cues (type of models and spokespeople) used in advertisements than younger adults, and consequently more sensitive to their portrayal in advertising.

However, researchers have discussed the possibility that peripheral cues may be processed centrally in some instances. Given the indication that older adults are more likely to use noncompensatory than compensatory decision strategies, peripheral cues may be used in a variety of ways to reduce processing demands. Thus, investigation of the following could be fruitful:

P7: Due to lower levels of need for cognition, older adults may be more likely than younger adults to use peripheral cues in a central manner to reduce demands on their processing capacity resources.

These are just a few of the many research propositions that deserve investigation. It is important to delineate these propositions to guide future research into the processing of advertising information.

CONCLUSION

The research presented in this paper provides evidence of a potential interactive relationship between the primary variables in the ELM that control route to persuasion. Specifically, age-related declines in cognitive ability affect the motivational variable, need for cognition. This points to the possibility that need for cognition may be a dynamic factor that changes over time with respect to age-related cognitive processing changes.

Haugtvedt, Petty and Cacioppo (1992) point out that it is important to identify "... profiles of differences in personal habits and preferences of individuals who differ in need for cognition." Given the rapidly increasing population of adults over the age of 60, it is imperative that consumer researchers delve more deeply into the information processing changes that arise with advancing age and identify those characteristics, like need for cognition, that affect the processing of advertising messages. By doing so, this will produce more effective methods for connecting with this increasing important target market.

REFERENCES

Arenberg, D. and E.A. Robinson-Tchabo (1977). "Learning and Aging," in Handbook of the Psychology of Aging, 2nd edition, J.E. Birren and K.W. Schaie (eds.), New York: Van Nostrand Reinhold Company, Inc., 421-449.

Axsom, D., S. Yates and S. Chaiken (1987). "Audience Response as a Heuristic Cue in Persuasion," Journal of Personality and Social Psychology, 53, 30-40.

Batra R., and D.M. Stayman (1990). "The Role of Mood in Advertising Effectiveness," Journal of Consumer Research, 17, 203-214.

Bearden, W.O. and J.B. Mason (1979). "Elderly Use of In-Store Information Sources and Dimensions of Product Satisfaction/Dissatisfaction," Journal of Retailing, 55(1), 79-91.

Birren J. E., A.M. Woods and M.V. William (1980). "Behavioral Slowing with Age: Causes, Organization, and Consequences," in Aging in the 1980's: Psychological Issues, L.W. Poon (ed.) Washington, D.C.: American Psychological Association.

Cacioppo, J. T. and R. E. Petty (1982). "The Need for Cognition," Journal of Personality and Social Psychology, 42, 116-131.

Cacioppo, J. T., R. E. Petty and C. F. Kao (1984). "The Efficient Assessment of Need for Cognition," Journal of Personality-Assessment, 48, 306-307.

Cacioppo, J. T., R. E. Petty and K. Morris (1983). "Effects of Need for Cognition on Message Evaluation, Recall,and Persuasion," Journal of Personality and Social Psychology, 39, 805-818.

Cacioppo, J. T., R. E. Petty, C. F. Kao and R. Rodriguez (1986). "Central and Peripheral Routes to Persuasion: An Individual Difference Perspective," Journal of Personality and Social Psychology, 51, 1032-1043.

Canestrari, R. E. (1963). "Paced and Self-paced Learning in Young and Elderly Adults," Journal of Gerontology, 18, 165-168.

Cohen, A.R. (1957). "Need for Cognition and Order of Communication as determinants of Opinion Change," in C.I. Hovland (ed.) The Order of Presentation in Persuasion, New Haven, CT: Yale University Press.

Cohen, A., E. Stotland, and D. Wolfe (1955). "An Experimental Investigation of Need for Cognition," Journal of Abnormal and Social Psychology, 51, 291-294.

Cole, C. A. and M. J. Houston (1987). "Encoding and Media Effects on Consumer Learning Deficiencies in the Elderly," Journal of Marketing Research, 23 (February), 55-63.

Craik, F.M. (1977). "Age Differences in Human Memory," in Handbook of the Psychology of Aging, 2nd edition, J.E. Birren and K.W. Schaie (eds.), New York: Van Nostrand Reinhold Company, Inc.

Davis, B. and W.A. French (1989). "Exploring Advertising Usage Segments Among the Aged," Journal of Advertising Research, 29(1), 22-29.

Hasher, L. and R.T. Zacks (1979). "Automatic and Effortful Processes in Memory," Journal of Experimental Psychology: General, 108(3), 356-88.

Haugtvedt, C. P. and R. E. Petty (1989). "Need for Cognition and Attitude Persistence," Advances in Consumer Research, 16, 33-36.

Haugtvedt, C. P., R. E. Petty and J. T. Cacioppo (1992). "Need for Cognition in Advertising: Understanding the Role of Personality Variables in Consumer Behavior," Journal of Consumer Psychology, 1(3), 239-260.

Haugtvedt, C., R. E. Petty, J. T. Cacioppo and Theresa Steidley (1988). "Personality and Ad Effectiveness: Exploring the Utility of Need for Cognition," Advances in Consumer Research, 15, 209-212.

Hoyer, W. J. and D. J.Plude (1980). "Attentional and Perceptual Processes in the Study of Cognitive Aging," in Aging in the 1980's: Psychological Issues, L.W. Poon (ed.) Washington, D.C.: American Psychological Association.

Johnson, M. M. (1990). "Age Differences in Decision Making: A Process Methodology for Examining Strategic Information Processing," Journal of Gerontology: Psychological Sciences, 45(2) p75-78.

Lumpkin, J. R. (1985). "Shopping Orientation Segmentation of the Elderly Consumer," Journal of the Academy of Marketing Science, 13(2), 271-289.

Petty, R. E. and J. T. Cacioppo (1986). Communication and Persuasion: Central and Peripheral Routes to Attitude Change. New York: Springer-Verlag.

Ratneshwar, S. and S. Chaiken (1991). "Comphension's Role in Persuasion: The Case of Its Moderating Effect on the Persuasive Impact of Source Cues," Journal of Consumer Research, 18(1), 52-62.

Reese, H.W., and D. Rodeheaver (1985). "Problem Solving and Complex Decision Making," in Handbook of the Psychology of Aging, 2nd edition, J.E. Birren and K.W. Schaie (eds.), New York: Van Nostrand Reinhold Company, Inc.

Rubin, A.L. (1986). "Television, Aging and Information Seeking," Language and Communication, 6(1/2), 125-137.

Salthouse, T.A. (1988a). "Resource-Reduction Interpretations of Cognitive Aging," Developmental Review, 8, 238-272.

Salthouse, T.A. (1988b). "Initiating the Formalization of Theories of Cognitive Aging," Psychology and Aging, 3(1), 3-16.

Srull, T., M. Lichtenstein and M. Rothbart (1985). "Associated Storage and Retrieval Processes," Journal of Experimental Psychology: Learning, Memory and Cognition, 11, 316-345.

Stayman, D. M. and F. R. Kardes (1992). "Spontaneous Inference Processes in Advertising: Effects of Need for Cognition and Self-Monitoring on Inference Generation and Utilization," Journal of Consumer Psychology, 1(2), 125-142.

Venkatraman, M.P., D. Marlino, F.R. Kardes, and K.B. Sklar (1990). "The Interactive Effects of Message Appeal and Individual Differences on Information Processing and Persuasion," Psychology and Marketing, 7(2), 85-96.

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