Printer Friendly

Aging and the problem of television clutter.

To the 32 million Americans who are 65 or older (U.S. Bureau of the Census, 1990), television is more than just a broadcast medium. It is a social presence in their homes and in their lives. For some seniors, television fills the gap created by the loss of a loved one. For others, whose contacts have diminished through retirement and the departure of grown children, television offers "the illusion of living in a populated world" (Davis and Kubey, 1982).

Since television was first introduced, its influence on the elderly has grown steadily. Older Americans once rated newspapers as their most important medium of communication (Steiner, 1963). More recently, however, senior citizens have come to rely on the small screen as their primary source of both information and entertainment (Stephens, 1981). They learn about new products through television and are heavily influenced by advertising (French and Crask, 1977).

According to the 1990 Nielsen Report, viewers over the age of 54 watch an average of 40 hours per week--more than any other age group (Huston et al., 1992). Their heavy usage of the medium, coupled with their sheer size and buying power, make older viewers an attractive target for many commercial messages. Despite this, advertisers really do not know much about the elderly and the possibility of age-related differences in responses to advertising (Wolfe, 1987).

The elderly have been shown to be less efficient at information-processing tasks than younger individuals (Phillips and Sternthal, 1977). Processing televised information may pose a particular problem because television is an externally-paced medium. Further complicating the issue is the increasing complexity of the commercial environment.

Greenberg (1974) and others have noted that the effects of television depend on characteristics of the individual as well as characteristics of the medium. Thus, any outcome of the television-viewing experience may well be the result of an interaction between the medium and the viewer. The purpose of the present study is to examine the effects of one aspect of the commercial environment--television clutter--and one viewer characteristic--age--on responses to television advertising. We measure age functionally in terms of cognitive speed, or the rate at which an individual processes information. For comparative purposes, we also include a chronological measure of age.

Given the importance of television to the elderly and the growing importance of the elderly to television advertisers, it is vital that marketers be able to communicate effectively with older consumers. This study should provide some useful information in meeting that goal.

Theoretical Framework

Age-Related Consumer Differences. Classifying individuals based on calendar time is commonplace in our society as a means of conferring legal rights and responsibilities (Cain, 1974). It is simple and easily measured. However, chronological age is not a direct indicator of human functioning. Individual abilities grow and decline at different rates, and the passage of time alone is not a cause of change. To wit, individuals of a given chronological age frequently show vast differences in ability (Schonfield, 1974).

An alternative is to describe people by their functional age. That is, individual differences and changes are reflected through the biological, psychological, and social changes that are associated with increasing age (Birren and Renner, 1977). With the passing of time, individuals mature in a physiological sense. Their psychomotor skills, cognition, motivation, and personality also develop. And their involvement with social institutions evolves. Gerontologists have come to realize that it is these changes in human functioning, rather than the passage of time itself, which should be viewed as the cause of behavioral changes or differences.

An important factor influencing an individual's ability to respond to the environment is the speed of his or her responses (Salthouse, 1985). The universality of behavioral slowing with advancing age has been recognized by gerontologists since the 1800s (Birren, Woods, and Williams, 1980). This slowing has been found to affect perception, encoding, and storage, and retrieval of information (Hoye and Plude, 1980; Rybash, Hoyer, and Roodin, 1986; Waugh and Barr, 1980).

For marketers, the questions of how changes in functional age affect consumer behavior remains largely unexplored. Exceptions to this are studies by Calcich and Blair (1983) and Cole and Gaeth (1990), which examine the effect of speed-related perceptual abilities on information acquisition and choice. In a review article, John and Cole (1986) suggest that slower central nervous system activity may be responsible for impaired memory performance in the elderly.

In the present study, cognitive speed is used to refer to an individual's rate of information processing. Cognitive slowing may mean that elderly individuals will suffer in acquiring information from an externally-paced medium such as television (cf., Cole and Gaeth, 1990). Cognitively slower individuals may not have adequate time to elaborate on or rehearse messages (Wingfield, 1980); or they may miss one message as a result of elaborating on a previous one. To the extent that any of these problems exist, age-related differences in responses to television advertising can be expected. Thus, the following hypothesis is suggested:

H1: Recall and recognition of television advertisements will decline with declining cognitive speed.

The Television Environment. Changes in the commercial environment have led to growing concern over the continued effectiveness of television as an advertising medium. One of the most noticeable changes has been an increase in clutter. Between 1981 and 1989, the number of network commercials grew by 35 percent (DDB Needham Worldwide, 1991). Much of this growth was due to the use of split :30s and 15-second spots. According to the Television Bureau of Advertising, :15s accounted for 38 percent of all network commercials and 6 percent of all non-network commercials in 1989.

As the number of commercials has increased, so has the amount of time devoted to ads and other nonprogram material. On CBS, for example, average network nonprogram time increased from 10 minutes, 8 seconds per prime-time hour in 1984 to 11 minutes, 40 seconds in 1989. During network daytime programming (when many elderly are likely to be watching), hourly nonprogram time was as high as 16 minutes, 45 seconds in 1989 (Advertising Age, 1990).

Despite these trends in non-program material, the fact remains that consumers possess limited capacity for processing and storing information (Bettman, 1979). Previous research has shown that ads in highly cluttered environments are recalled less frequently than are ads in less-cluttered environments (Cobb, 1985; Webb, 1979; Webb and Ray, 1979). Further, it has been shown that as viewers perceive more clutter, they become more negative toward advertising (Mord and Gilson, 1985).

Existing studies of clutter have not considered the elderly viewer. However, we expect that older, cognitively slower adults will be affected by processing limitations at least as severely as younger adults. Thus, we hypothesize that for consumers of all levels of cognitive speed:

H2: Recall and recognition of television advertisements will be higher in low-clutter than in high-clutter conditions.

The Environment x Age Interaction. While we expect clutter to affect everyone, the existence of clutter may pose a particular detriment to information acquisition by elderly consumers. More messages represent more chunks of information to be processed and a more complex environment. The externally-paced nature of television is likely to exaggerate clutter's effects on older viewers.

It has been demonstrated in other contexts that as information complexity increases, processing by the elderly is hindered even more than is processing by younger adults (e.g., Cohen and Faulkner, 1983; Hartley and Anderson, 1983; Wright, 1981). This age-complexity phenomenon is consistent with the view that many differences in the performance of cognitive tasks originate because of the limited availability of cognitive resources. Increasing task complexity can be assumed to increase the demands on processing resources. And the performance of older adults is affected more than that of younger adults because they have smaller quantities of resources available (Salthouse, 1991).

Because of the externally-paced nature of television, effects observed in other contexts should also be significant here. Demonstrating an age-related interaction effect, Stephens (1982) reported that while time-compressed television commercials were associated with improved recall for younger consumers, they led to worsened recall among the elderly. It may be that the time-compressed ads are close to the younger viewer's optimal rate of information processing but fall further from the rate at which the elderly process information. Consistent with this, hypothesis three is proposed:

H3: The relationship between cognitive speed and ad recall and recognition will be stronger in high-clutter conditions than in low-clutter conditions.


Hypotheses were tested via an experimental study. Four treatment groups were used, two each at high- and low-clutter levels. Cognitive speed was included as a nonmanipulated independent variable.

Subjects watched a videotape including two freestanding and complete storyline segments of 10 to 12 minutes each. The experimental manipulation, a series of nonprogram elements, was embedded between the two program segments. Treatments included either four or eight messages. Commercials in the third and fourth positions were held constant as test ads.

Program and nonprogram elements were obtained from broadcasts on stations outside the test area. Over one hundred spots were screened for production quality, executional style, and product-category usage. Based on SMRB data, the product categories selected had usage rates of at least 65 percent for all age groups included in the study.

Independent Variables. Clutter--the mass of nonprogram material that is sandwiched between program content is a complex phenomenon that is related to both the length of the individual ads and the length of the commercial break. For example, given a commercial break with two :30s, clutter may be increased either by broadcasting the original two :30s plus others in a longer break, or by breaking the one-minute pod into additional, shorter units.

In this study, clutter was manipulated by holding the length of the ads constant and adding more messages to the break. This approach is consistent with several previous experimental investigations of clutter (e.g., Cobb, 1985; Webb, 1979). It is also consistent with the industry trend toward increasing both the number of nonprogram messages and total nonprogram time. A field study by the second author indicated that a low-clutter treatment of four messages and a high-clutter treatment of eight messages would provide findings relevant to all dayparts (Cobb-Walgren, 1991).

Cognitive speed was defined as the individual's rate of information processing. In this study, it was operationalized as the individual's score on the Digit Symbol Substitution Test, a subtest of the Weschler Adult Intelligence Scale. The Digit Symbol Substitution Test has been shown in previous research to provide a reliable measure of cognitive speed (Salthouse, 1985; Zimmerman and Woo-Sam, 1973).

The test is a paper-and-pencil procedure which consists of a key containing pairs of digits (1, 2, 3, . . . . , 9) and symbols (e.g., ???, ???, ???), and a series of randomly ordered digits, below which is an empty box. Subjects must write the appropriate symbol below each digit and complete as many pairs as possible in 90 seconds. The symbols to be substituted are always visible in the key printed above the coding problems.

Dependent Variables. Given the emphasis in this study on perceptual processes, advertising effectiveness was evaluated through recall and recognition measures. The response measures were applied to test ad 1 and test ad 2, which were seen by all treatment groups.

To measure recall, subjects were asked what nonprogram messages they saw while viewing the programs. They were instructed to give for each message the product category, brand name, and sales claims made. Two examples were given for messages not included in the experiment. Consistent with the coding scheme described by Bettman and Park (1980a, 1980b), responses were divided into phrases, each representing an independent detail. Recall credit was given for exact matches of brand and product category, close matches of brand name judged to be phonetic misspellings, and exact or close conceptual matches with visual or verbal aspects of the sales message.

To measure recognition, subjects were provided with a series of multiple-choice checklists and were asked to identify the product category, brand name, and two product claims made in the ad (cf. Singh and Rothschild, 1983). Scores had a range of 0 to 4.

Subjects. A sample of 148 subjects was drawn on a voluntary basis from organizations including church groups, neighborhood and social organizations, and senior citizens' groups in a large metropolitan city in the southeast. A monetary incentive was offered to encourage participation.

Gerontologists suggest that cognitive slowing begins at about age 40 (Denney, 1982). To capture this effect, efforts were made to select equally among each age decade from 30 through 80. The sample ranged in age from 26 to 91, with a mean age of 59. The sample was 67 percent white and 74 percent female. Forty-seven percent of subjects had completed college or graduate school. Due to incomplete responses from some subjects and the desire to equalize cell sizes, 126 individuals were included in the analysis.

Procedure. Given the advanced age of some subjects, it was necessary to take the experiment to them rather than have them report to a central testing site. This had the added advantage of providing a more comfortable and natural viewing environment. Subjects participated in groups and were assigned to treatments based on a quota system under which each age decade was represented within each treatment cell.

Subjects were told that they were participating in a study of social communication via television and that they were to view and give their opinions about two program segments. No mention of the ads was made. Following viewing of the videotape, subjects completed a questionnaire measuring: (1) attitudes toward television in general and toward the specific program segments viewed; (2) recall of all nonprogram messages and recognition of the test ads; and (3) selected lifestyle and demographic questions and cognitive speed. Following the experiment, subjects were debriefed and compensated for their time.


This study examined the effects of commercial clutter and viewer age on responses to television advertising. The four recall and recognition variables were treated as repeated measures within multivariate analysis of variance (MANOVA). To test the hypotheses, we looked at the effects of cognitive speed, clutter, and the cognitive speed x clutter interaction. To better understand the interaction effect, we also examined the impact of each variable within levels of the other. Finally, we compared the effects of cognitive speed with those of chronological age.

Cognitive speed produced an effect among all subjects. As predicted, declining cognitive speed led to poorer recall and recognition of the ads. The expected interaction also was found. However, clutter effects were not consistent across all subjects. The cognitively slowest subjects were most affected by clutter while the cognitively fastest were somewhat affected and the moderately speeded responded equally well under conditions of low and high clutter.

The Chronological Age vs. Cognitive Speed Relationship. The basis of our investigation was the expectation that cognitive speed declines with increasing age. Analysis of Pearson's correlation showed that this was, in fact, the case. Age and cognitive speed had a correlation of -.637 (p [is less than] .001). It was further found that this relationship was significant even when the effects of gender and education were removed (r = -.613; p [is less than] .001).

The strength of the association between chronological age and cognitive speed suggests that cognitive speed is indeed related to age, but that the two variables are different. This gives reason to look further at the relationship between cognitive speed and ad response. Again, while correlation analysis cannot speak directly to the issue, we expect cognitive speed (as a measure of functional age) to have a greater ability to theoretically explain consumer responses than chronological age. Functional age is a direct indicator of ability, whereas chronological age is merely a proxy variable. If older consumers are more adversely affected by clutter, it is not merely because they have lived longer, but rather because their biological and psychological capabilities have slowed.

Cognitive Speed Effects. Hypothesis 1 predicted that cognitive speed would affect advertising response within both low-and high-clutter conditions. This hypothesis received strong support.

Our analysis of main effects shows that across all respondents, cognitive speed did significantly affect responses. Because of the expected interaction effect, it was also important to evaluate the presence of cognitive speed effects separately within both low- and high-clutter groups. In this additional analysis, the sample was divided into low- and high-clutter groups, then MANOVAs were performed on each group. Cognitive speed effects were found in both low-clutter (F = 5.760, p [is less than] .001) and high-clutter (F = 6.052, p [is less than] .001) groups. Thus, regardless of the amount of nonprogram material, viewer recall and recognition suffered as cognitive speed declined.
Table 1

Effects of Cognitive Speed and Clutter

Effect                      Wilks' Lambda      F      Significance of F

Cognitive Speed x Clutter      .919          2.683        .037
Clutter                        .945          1.738        .146
Cognitive Speed                .769          8.981        .000

Clutter Effects. Hypothesis 2 suggested that advertising response would be greater under conditions of low rather than high clutter, and that this would be true for all individuals, regardless of cognitive speed. This hypothesis was not confirmed. Our analysis of main effects shows that on average across all respondents, there was no clutter effect.

The shape of our expected interaction indicated that clutter effects would be greatest among the cognitively slowest subjects. It is possible that considering all subjects together served to hide effects on subgroups of the sample. To investigate this, cognitive speed was converted into a categorical variable, with subjects assigned to groups representing low, medium, and high speeds. Then, differences in clutter effects were examined within each of these three groups. Here we found that clutter did affect the cognitively slowest subjects (F = 6.407, p [is less than] .001) and the cognitively fastest subjects (F = 3.285, p [is less than] .02). The medium-speeded group, however, was apparently unaffected by the level of clutter (F = 1.460, n.s.).

The Clutter x Cognitive Speed Interaction. Hypothesis 3 predicted that there would be an interaction between clutter and cognitive speed. As shown in Table 1, the MANOVA yielded a significant interaction effect, supporting this hypothesis. In general, individuals of lower cognitive speed suffered dispro-portionately in their advertising response under conditions of high clutter.

We can use the information about cognitive speed and clutter effects to further evaluate the clutter x cognitive speed interaction. It was suggested in Hypothesis 3 that the relationship between cognitive speed and viewer responses would be strongest when clutter was high. In fact, the relationship was somewhat stronger in the high-clutter than in the low-clutter condition. Further, the difference in response to clutter was larger for the cognitively slowest group than for either the medium- or highest-speeded groups. Interaction effects are depicted graphically in Figure 3.

Chronological Age Effects. This study demonstrates that cognitive speed holds a great deal of potential for explaining age-related changes in behavior. We do recognize, however, that consideration of chronological age is useful both for the practitioner and for those interested in comparing this study to other studies of age-related ad response. Therefore, we performed the same analysis using chronological age rather than cognitive speed as the independent variable. Results are provided in Table 2.

As with cognitive speed, there was a chronological age main effect. This effect was evidenced in both the low- and high-clutter conditions. Regardless of clutter level, older viewers had lower recall and recognition scores than did younger viewers. There was no support for the existence of a chronological age x clutter interaction.
Table 2

Effects of Chronological Age and Clutter

Effect                          Wilks' Lambda      F        Significance of F

Chronological Age x Clutter         .953          1.462          .218
Clutter                             .935          2.075          .088
Chronological Age                   .759          9.509          .000

Comparing Chronological Age and Cognitive Speed. It was argued that cognitive speed provides advantages over chronological age for those attempting to understand the cause of age-related differences in responses to advertising. The theoretical grounding of the cognitive speed concept supports this notion. Measures of functional age indicate changes in human functioning and, thus, represent causes of behavior. Chronological age merely acts as a proxy for functional variables.

While cognitive speed provides theoretical advantages, its performance in the present investigation failed to demonstrate a clear predictive superiority. The cognitive speed x clutter interaction explained significantly more variation than did the age x clutter interaction (F = 1.723, p [is less than] .05). However, neither cognitive speed main effects nor the entire model (cognitive speed + clutter + interaction effects) represented improvements over the use of chronological age. More study is recommended to provide a better understanding of these effects. Meanwhile, researchers may find it useful to use both functional and chronological age measures.


The aging of the American population had led to an increased interest in the study of age-related factors as they affect information processing. The research presented here was designed to extend previous aging research by using a measure of functional, as well as chronological, age. The two measures of age were shown to be strongly related. However, the use of functional age (which is a direct indicator of human ability) gives greater explanation of age differences in behavior from a theoretical standpoint than does chronological age (which merely indicates the passage of time).

One contribution of this study is in providing evidence of the effects of cognitive speed on behavior. A decline in cognitive speed resulted in lower advertising response, regardless of clutter level. As a practical matter, these results suggest that even relatively uncluttered environments may not be sufficient to mitigate the effects of low cognitive speed. Rather, marketers should take steps to facilitate information processing when developing ads targeted to older adults. This might include using longer, slower-paced ads to allow more time for elaboration. Marketers may also improve the elderly's processing of messages by using self-paced media such as newspapers and magazines. The use of print may be most important for new products or information, when memory traces must be newly established.

Consideration of cognitive speed has implications for marketing to elderly consumers; however, it must also be recognized that there is not a one-to-one correspondence between cognitive speed and chronological age. Some elderly consumers are capable of quite rapid processing. It remains for future studies to identify variables related to cognitive speed which are useful in market segmentation. For example, individuals who have a more active lifestyle or who engage in more mentally stimulating activities may retain greater processing capabilities.

This study failed to provide evidence that a cluttered commercial environment has uniformly negative effects on advertising response. Rather, evidence was provided that clutter adversely affects the cognitively slowest and fastest consumers. Clutter did not appear to have an effect on the moderately speeded consumers.

Achievement of this mixed result represents an additional contribution to marketing knowledge. From a theoretical standpoint, the results of this study suggest the need to reconsider the role of cognitive capacity in determining advertising response. One limitation of this study, as with previous studies of clutter, was a failure to separate ability and motivation to process information. Individuals possess a finite capacity for information processing. However, in the low-involvement task of television viewing, processing capacity simply may not be a relevant variable for many viewers. Younger, cognitively faster viewers may attend to those messages with attention-getting characteristics (such as product involvement or arousing audio or visual cues) and may choose not to process other messages.

A low level of motivation to process information from television could account for the relative lack of clutter effects among individuals of high or medium cognitive speed. It also is consistent with previously made suggestions that high-involvement ads may not be susceptible to clutter effects (e.g., Webb, 1979). To the extent that a mixture of high- and low-involvement messages is presented in a single break, the number of ads that viewers attempt to process may remain low; thus, ability is not challenged.

From a practical standpoint, marketers must evaluate and make trade-offs between the benefits and costs of any particular course of action. Using shorter messages or placing messages in more cluttered positions may be an option with only minimal impact if younger, cognitively faster consumers are being targeted. On the other hand, if older consumers are being targeted, the costs of this strategy may outweigh potential benefits.


Advertising Age, July 2, 1990.

Bettman, James R. An Information Processing Theory of Consumer Choice. Reading, MA: Addison-Wesley Publishing Company, 1979.

-----, and C. Whan Park. "Effects of Prior Knowledge and Experience and Phase of the Choice Process on Consumer Decision Processes: A Protocol Analysis." Journal of Consumer Research 7, 4 (1980a): 234-48.

-----, and -----. "Implications of a Constructive View of Choice for Analysis of Protocol Data: A Coding Scheme for Elements of Choice Processes." In Advances in Consumer Research, Vol. 7, Jerry C. Olson, ed. Ann Arbor, MI: Association for Consumer Research, 1980(b).

Birren, James E., and V. Jayne Renner. "Research on the Psychology of Aging: Principles and Experimentation." In Handbook of the Psychology of Aging, James E. Birren and K. Warner Shaie, eds. New York: Van Nostrand Reinhold Company, 1977.

-----; Anita M. Woods; and M. Virtrue Williams. "Behavioral Slowing with Age: Causes, Organization, and Consequences." In Aging in the 1980's, Leonard W. Poon, ed. Washington, D.C.: American Psychological Association, 1980.

Calcich, Stephen, and Edward Blair. "The Perceptual Task in Acquisition of Package Information." In Advances in Consumer Research, Vol. 10, Richard P. Bagozzi and Alice M. Tybout, eds. Ann Arbor, MI: Association for Consumer Research, 1983.

Cobb, Cathy J. "Television Clutter and Advertising Effectiveness." In 1985 AMA Educators' Proceedings, Robert F. Lusch et al., eds. Chicago: American Marketing Association, 1985.

Cobb-Walgren, Cathy J. "Tuning In and Turning Off: Trends in Television Viewing Behavior." In Proceedings of the Society for Consumer Psychology, American Psychological Association, Michael Lynn and Jeffrey M. Jackson, eds. Washington, D.C.: American Psychological Association, 1991.

Cohen, Gillian, and Dorothy Faulkner. "Age Differences in Performance on Two Information Processing Tasks: Strategy Selection and Processing Efficiency." Journal of Gerontology 38, 4 (1983): 447-54.

Cole, Catherine A., and Gary J. Gaeth. "Cognitive and Age-Related Differences in the Ability to Use Nutritional Information in a Complex Environment." Journal of Marketing Research 27, 2 (1990): 175-84.

DDB Needham Worldwide. Media Trends. February 1991.

Davis, R. H., and R. W. Kubey. "Growing Old on Television and With Television." In Television and Behavior: Ten Years of Scientific Progress and Implications for the Eighties, D. Pearl, L. Bouthilet, and J. Lazar, eds. Washington, D. C.: U.S. Department of Health and Human Services, 1982.

Denney, Nancy Wadsworth. "Aging and Cognitive Changes." In Handbook of Developmental Psychology, Benjamin B. Wolman, ed. Englewood Cliffs, NJ: Prentice-Hall, Inc., 1982.

French, Warren, A., and Melvin R. Crask. "The Credibility of Media Advertising for the Elderly." In Contemporary Marketing Thought, B. A. Greenberg and D. N. Bellinger, eds. Chicago, IL: American Marketing Association, 1977.

Greenberg, B. S. "Gratifications of Television Viewing and Their Correlates for British Children." In The Uses of Mass Communications: Current Perspectives on Gratifications Research, J. G. Blumler and E. Katz, eds. Beverly Hills, CA: Sage Publications, 1974.

Hartley, Alan A., and Joan Wilson Anderson. "Task Complexity and Problem-Solving Performance in Younger and Older Adults." Journal of Gerontology 38, 1 (1983): 72-77.

Hoyer, William J., and Dana J. Plude. "Attentional and Perceptual Processes in the Study of Cognitive Aging." In Aging in the 1980's: Psychological Issues, Washington, D.C.: American Psychological Association, 1980.

Huston, Althea C.; Edward Donnerstein; Halford Fairchild; Norma D. Feshbach; Phyllis A. Katz; John P. Murray; Eli A. Rubenstein; Brian L. Wilcox; and Diana Zuckerman. Big World, Small Screen. Lincoln, NE: University of Nebraska Press, 1992.

John, Deborah Roedder, and Catherine A. Cole. "Age Differences in Information Processing: Understanding Deficits in Young and Elderly Consumers." Journal of Consumer Research 13, 3 (1986): 297-315.

Mord, Marvin S., and Edith Gilson. "Shorter Units: Risk--Responsibility--Reward." Journal of Advertising Research 25, 4 (1985): 9-19.

Neter, John; William Wasserman; and Michael H. Kutner. Applied Linear Statistical Methods. Homewood, IL: Richard D. Irwin, Inc., 1985.

Phillips, Lynn W., and Brian Sternthal. "Age Differences in Information Processing: A Perspective on the Aged Consumer." Journal of Marketing Research 14, 4 (1977): 444-47.

Rybash, John M.; William J. Hoyer; and Paul A. Roodin. Adult Cognition and Aging: Developmental Changes in Processing, Knowing, and Thinking. New York: Pergamon Press, 1986.

Salthouse, Timothy A. A Theory of Cognitive Aging. North Holland, Netherlands: Elsevier Science Publishing Company, 1985.

-----. Theoretical Perspectives on Cognitive Aging. Hillsdale, N.J.: Lawrence Erlbaum Associates, 1991.

Schonfield, David. "Translations in Gerontology--From Lab to Life: Utilizing Information." American Psychologist 29, 11 (1974): 796-801.

Singh, Surendra, and Michael L. Rothschild. "Recognition as a Measure of Learning from Television Commercials." Journal of Marketing Research 20, 3 (1983): 235-48.

Steiner, Gary A. The People Look at Television: A Study of Audience Attitudes. New York: Alfred A. Knopf, 1963.

Stephens, Nancy. "Media Usage and Media Attitude Change with Age and with Time." Journal of Advertising 10, 1 (1981): 38-47.

-----. "The Effect of Time-Compressed Television Advertisements with Older Consumers." Journal of Advertising 11, 4 (1982): 48-55+.

U.S. Bureau of the Census. Statistical Abstract of the United States, 1990, 110th ed. Washington, D.C.: U.S. Government Printing Office, 1990.

Waugh, Nancy C., and Robin A. Barr. "Memory and Mental Tempo." In New Directions in Memory and Aging, Leonard W. Poon et al., eds. Hillsdale, NJ: Lawrence Erlbaum Associates, 1980.

Webb, Peter H. "Consumer Initial Processing in a Difficult Media Environment." Journal of Consumer Research 6, 4 (1979): 225-36.

-----, and Michael L. Ray. "Effects of TV Clutter." Journal of Advertising Research 19, 3 (1979): 7-12.

Wingfield, Arthur. "Attention, Levels of Processing, and State-Dependent Recall." In New Directions in Memory and Aging, Leonard W. Poon et al., eds. Hillsdale, NJ: Lawrence Erlbaum Associates, 1980.

Wolfe, David B. "The Ageless Market." American Demographics, July 1987.

Wright, Ruth E. "Aging, Divided Attention, and Processing Capacity." Journal of Gerontology 36, 5 (1981): 605-14.

Zimmerman, Irla Lee, and James M. Woo-San. Clinical Interpretation of the Wechsler Adult Intelligence Scale. New York: Grune and Stratton, Inc., 1973.

ROSE L. JOHNSON is an assistant professor of marketing at Temple University. She received her Ph.D. from Georgia State University. Dr. Johnson's principal research is in the area of consumer information processing.

CATHY J. COBB-WALGREN is an associate professor of marketing at Georgia State University. She received her Ph.D. from the University of Texas. Dr. Cobb-Walgren has published research on advertising and consumer behavior in the Journal of Advertising, the Journal of Retailing, the Journal of Public Policy and Marketing, the Journal of Health Care Marketing, Current Issues and Research in Advertising, Psychology and Marketing, and other journals.
COPYRIGHT 1994 World Advertising Research Center Ltd.
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 1994 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:Johnson, Rose L.; Cobb-Walgren, Cathy J.
Publication:Journal of Advertising Research
Date:Jul 1, 1994
Previous Article:Advertising awards and advertising agency performance criteria.
Next Article:Observations: the long and short of persuasive advertising.

Terms of use | Privacy policy | Copyright © 2018 Farlex, Inc. | Feedback | For webmasters