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Perceived time pressure and recommended dietary practices: the moderating effect of knowledge of nutrition.

For increasing numbers of people, time is a major constraint. Robinson (1990) indicated that over the past two decades, an increasing proportion of the population has come to perceive themselves as time pressed. Time pressures have become a regular part of everyday life. As a result, consumers have begun implementing strategies for reducing these pressures (Berry 1979; Nickols and Fox 1983; Strober and Weinberg 1980), while firms have increased their emphasis on the ability of their products to economize on time (Gross and Sheth 1989).

There is evidence that time pressures affect the types of information used in decisionmaking (Wallsten and Barton 1982; Wright 1974). Time pressure has also been found to affect the sources and amount of nutrition information search (Feick, Herrmann, and Warland 1986) as well as eating habits and shopping behaviors (Bellante and Foster 1984; Berry 1979; Holman and Wilson 1982; Iyer 1989; Jackson, McDaniel, and Rao 1985; Nickols and Fox 1983; Park, Iyer, and Smith 1989; Strober and Weinberg 1980).

Two research questions were of concern in this study. First, what is the effect of time pressure on dietary quality? Dietary quality means including fruits, vegetables, and fiber in the diet and avoiding or limiting consumption of potentially harmful food constituents as fats, cholesterol, and sodium. The potentially negative effects of time pressure on eating habits and diet quality are of particular concern given the growing body of evidence linking the quality of dietary intake to health (National Research Council 1989). Second, can nutritional knowledge and perceptions of health risks mitigate the negative effects of time pressure on eating habits and dietary quality? Specifically, can nutritional knowledge and/or perceptions of health risks override time pressure so that, even under time pressure, people will eat a relatively high quality diet if they are knowledgeable about nutrition and/or perceive high health risks from poor dietary intake?


Although the popular press has attributed the demise of dietary quality to increasing time pressure (The Wall Street Journal 1988), relatively little research has investigated this relationship. Research on time constraints and eating behavior has focused almost entirely on the link between wives' employment status and use of convenience food items and eating out (Bellante and Foster 1984; Jackson, McDaniel, and Rao 1985; Nickols and Fox 1983; Reilly 1982; Schaninger and Allen 1981; Strober and Weinberg 1980). This line of research began with Becker (1965) who suggested that increases in the value of time associated with employment outside the home should lead to increased use of more expensive convenience food items that economize on time.

In general, research suggests that employment outside the home leads to increased frequency of eating out and a reduction in the time spent preparing meals. However, there is little support for the hypothesis that employment outside the home leads to greater use of convenience food items. In fact, Schaninger and Allen (1981) found that households with wives in high status occupations often consumed convenience food items less frequently than any other group. Two possible explanations exist for this lack of association. First, because perceptions of time pressure are caused by many factors, employment outside the home alone may not be sufficient to cause severe time pressure. Recognizing this shortcoming, Reilly (1982) modeled convenience food consumption as a direct result of role overload, a measure of perceived overall time pressure. Reilly found directional support for the hypothesis that those who feel more overload are more likely to use convenience food items.

Second, while researchers have investigated the main effect of employment (and hence time pressure), few researchers have considered possible moderator variables. Therefore, individual differences in abilities and resources and perceptions of health risks may have confounded the results. An exception is Schaninger and Allen (1981) who included wives' occupational status as a moderator by dividing households into three categories: wives not employed outside the home, wives employed in lower status occupations, and wives employed in higher status occupations. The moderator hypothesis was supported by Schaninger and Allen's finding that households with wives employed in high status occupations often consumed convenience food items less frequently than the other two groups.

The present study's approach differs in three ways from much of the research relating time pressure to food consumption and choice. First, instead of measuring time pressure objectively using employment status as a proxy, the authors assess perceptions of time pressure at mealtime.(1) This measure is used because employment status does not seem to fully or accurately reflect the nature of time constraints or pressures as perceived by the consumer. For example, Reilly (1982) found that employment status accounted for only three percent of the variation in perceived overall time pressure, indicating that employment is not the only cause of time pressures. In addition, Robinson (1989, 1990) has reported that while hours of employment have declined steadily over the past two decades, consumers' perceptions of time pressure have steadily increased. As perceptions drive behavior (Berry 1990) and as perceptions of time pressure do not seem to relate well to objective measures of time constraint, use of a perceived time pressure measure seems desirable.

A second difference between this research and previous research is that in addition to studying the main effects of perceived time pressure on dietary quality, the authors consider variables such as nutritional knowledge and perceptions of health risk that could offset or moderate the negative effects of time pressure. Research that has considered potential moderator variables suggests the utility of this approach. For example, results by Wallsten and Barton (1982) indicated that perceived benefits of using more information in making a decision mitigate the negative effects of time pressure on the amount of information use. Park, Iyer, and Smith (1989) found that the decline in unplanned purchases resulting from time pressure is much smaller when consumers are more familiar with a store and its layout. Taken together, these results suggest that individual characteristics such as knowledge of nutrition and perceived health risks may moderate or offset the effects of perceived time pressures on dietary practices.

A third difference is that rather than use of convenience food as a measure of dietary quality, the authors employ a self-reported measure of adherence to recommended dietary practices (RDPs). Instead of focusing solely on the need to avoid fats, cholesterol, and sodium or solely on the need to obtain adequate amounts of certain nutrients (Schafer 1978), the measure used incorporates both aspects.

The next section discusses variables as perceived time pressure, human capital (knowledge of nutrition and years of formal education), and perceptions of health risk that should be related to RDPs. In addition, a discussion of human capital and perceived health risk as potential moderators of the effects of perceived time pressure is included.


The variable of interest in this study is recommended dietary practices (RDPs). RDPs call for limiting the consumption of certain food constituents such as sugar, fats, and salt, while consuming adequate amounts of certain foods or food constituents as fruits, vegetables, and fiber. Activities associated with adherence to RDPs include information search and usage (e.g., label reading), meal planning, and meal preparation.

A variety of factors are expected to affect the extent to which RDPs are utilized. These factors can be broadly categorized into the costs and benefits of utilizing RDPs. For example, perceptions of time pressure may inhibit the extent to which RDPs are utilized by increasing the behavioral costs of meal preparation and planning activities. Ability factors such as knowledge of nutrition and education may facilitate the use of RDPs by increasing efficiency, and hence, decreasing the cost of using them. Other factors as perceptions of health risk may motivate the use of RDPs by increasing their perceived benefits.

In addition to the direct effects described, a major proposition of this paper is that the effect of perceived time pressure on adherence to RDPs is moderated by individual characteristics such as knowledge of nutrition, years of formal education (i.e., human capital), and perceptions of health risks.(2) Specifically, different people bring different sets of abilities and motivations to bear on a given problem, activity, or situation. Therefore, although time is a fixed resource, people have some control over how they use it. Hence, people with similar levels of time pressure may deal with these pressures differently depending on personal abilities and motivations.

The effects of perceived time pressure, human capital (knowledge of nutrition and education), and perceived health risk on the extent of RDP utilization are discussed. Two control variables (i.e., age and whether or not a person is on a diet) are also discussed.

Perceived Time Pressure

A major time using activity associated with utilizing RDPs is meal preparation. In fact, Hall and Schroeder (1970) and Robinson (1983) found meal preparation to be one of the most time consuming household activities. Although not all quick and easy to prepare meals lack nutritional quality, a majority of convenience and fast foods used to reduce preparation time may interfere with adherence to RDPs because of their high sodium and fat contents (e.g., Consumer Reports 1988, 1990a, 1990b).

In this study, perceived time pressure is measured as respondents' perceptions of time pressure at mealtime. Following Schary (1971) the authors view perceived time pressure as an indicator of an individual's time value, with higher perceived time pressure indicating higher time value and hence higher activity cost. Given that behavioral costs are expected to exhibit a negative influence on an activity, the authors hypothesize that,

H1: The higher a person's level of perceived time pressure at mealtime, the lower is adherence to recommended dietary practices.

In addition, to the extent that perceptions of time pressure at mealtime are associated with perceptions of overall time pressure (footnote 1; Herrmann et al. 1991), those under time pressure at mealtime may also be less likely to perform RDP-related activities such as careful meal planning and label reading. Although not investigated here, a reduction in such RDP-related activities should be associated with a reduction in the use of RDPs.

Human Capital

In this study, knowledge of nutrition and years of formal education represent specific and general human capital, respectively (Maynes 1989). Research suggests that the cognitive effort and cost of performing an activity decrease as knowledge about the activity increases (Alba and Hutchinson 1987; Britton, Westbrook, and Holdredge 1978; Converse 1989; Johnson and Kieras 1983). Given that utilization of RDPs depends heavily on the ability to understand and properly use nutritional information, knowledge of nutrition and education are hypothesized to reduce the behavioral cost and effort required to utilize RDPs. Other things being equal, this reduction in cost and effort should increase the use of RDPs. Therefore, the authors hypothesize that,

H2a: Higher levels of nutritional knowledge are associated with greater adherence to recommended dietary practices.

H2b: Higher levels of formal education are associated with greater adherence to recommended dietary practices.

Although time is a limited personal resource, some people are capable of accomplishing more within this limit. In addition, although perceived time pressure at mealtime may increase the cost of utilizing RDPs, these costs may be mitigated or offset by increases in efficiency associated with increases in human capital (Maynes 1989). Specifically, research on the differences between experts and novices (e.g., high versus low knowledge) suggests that consumer knowledge may offset the effects of time pressure by allowing more knowledgeable consumers to perform more activities in a given amount of time without a deterioration in performance (Alba and Hutchinson 1987; Bettman and Park 1980; Britton, Westbrook, and Holdredge 1978; Converse 1989; Johnson and Kieras 1983; Johnson and Russo 1984; Punj and Staelin 1983). Therefore, the authors hypothesize that,

H2c: Perceived time pressure has a greater negative effect on adherence to recommended dietary practices for those with lower levels of nutritional knowledge than those with higher levels of nutritional knowledge (time pressure x knowledge of nutrition interaction).

H2d: Perceived time pressure has a greater negative effect on adherence to recommended dietary practices for those with lower levels of formal education than those with higher levels of education (time pressure x education interaction).

Perceived Health Risk

The more a person feels that his/her health is likely to suffer in the future due to poor eating habits in the present, the greater the perceived health risk. Research on consumer risk suggests that perceptions of risk motivate people to engage in behaviors or adopt strategies such as increased information search to reduce risk (Feick, Herrmann, and Warland 1986; Reingen 1973; Roselius 1971). For example, Reingen (1973) and Roselius (1971) found that certain types of information as word-of-mouth from peers are more likely to be utilized when perceptions of risk are high. In addition, Feick, Herrmann, and Warland (1986) found that nutrition information search from various sources such as labels, books and pamphlets, and health professionals increased as perceptions of health risk increased.

One strategy for dealing with health risks would be to adopt RDPs. Therefore, the authors hypothesize that,

H3a: The greater the perceived health risk, the greater is the adherence to recommended dietary practices.

Given the discretionary nature of time, people under time pressures can "make time" for activities perceived as important by taking time from activities perceived as less important. One factor found to increase the perceived importance of an activity is perceived risk (Kapferer and Laurent 1985). Therefore, perceptions of increased health risk should lead to perceptions of the increased importance of food and nutrition related activities such as use of RDPs. Increased importance may, in turn, cause people under time pressures to make time for food and nutrition related activities (e.g., RDPs) at the expense of other less important activities.(3) Therefore, the authors hypothesize that,

H3b: Time pressure has a greater negative effect on adherence to recommended dietary practices for those who perceive lower health risks than for those who perceive higher health risks (time pressure x perceived health risk interaction).

Demographic and Control Variables

Two additional variables are hypothesized to be related to RDP use. These are age and whether or not the respondent is on a diet. Past studies suggest that the use of RDPs is higher for older age groups. Patterson and Block (1988) found that older people's diets conform more closely to the dietary guidelines of the National Research Council and the American Cancer Society. People on diets, whether weight reduction or health-related, most likely employ one or a number of RDPs. Therefore, the authors hypothesize that,

H4: Age is positively associated with adherence to recommended dietary practices.

H5: Being on a diet is positively associated with adherence to recommended dietary practices.


The data for this study were collected in 1985 in a nationwide telephone survey employing random digit dialing. A sample of 458 respondents was interviewed from the target population of people age 18 and over who were the predominant meal preparers in their households and were residing in the coterminous United States. Ninety percent of these meal preparers were female. The average respondent was 44 years old and had completed just under 13 years of formal education. Nearly 52 percent were employed outside the home. The sample somewhat underrepresents nonwhite and single-person households as compared to the U.S. population. Response rate, defined as the number of completed interviews divided by the total number of eligible contacts, was .45.


Specific items used to measure the variables in this study are shown in Table 1 and described below. Table 1 also contains Cronbach's alpha for variables measured with multiple items.

Recommended dietary practices (RDPs)

The measure of RDPs is an index consisting of nine three-point questions designed to measure the extent to which respondents (1) limited their consumption of salt, fats, cholesterol, calories, and sugar and (2) included fiber, fruits, and vegetables in their diets. Response categories for seven of the nine questions ranged from "don't worry about it" to "try very hard." The two remaining questions asked respondents how often they ate some kind of fruit (or vegetable). Response categories ranged from 1, "two to three times per week," to 3, "everyday."(4) A study by Peterson (1985) supports the use of three response categories, although some argue that more should be used. Peterson compared three-point scales with scales containing seven or more response categories. In each case, the three-point scale captured most of the variability expressed by the larger scale.

The nine items included in the RDP index are consistent with the key dietary recommendations set forth by the National Research Council and the American Cancer Society (see Patterson and Block (1988) for a summary). The mean value of the RDPs' index was 21.8 with a range from nine to 27. The standardized Cronbach's alpha of .78 for the RDP index is within the acceptable range set forth by Nunnally (1978). The corrected item-to-total correlations ranged from .35 to .51.

Perceived time pressure (TIME)

The measure of time pressure is an index of three three-point questions designed to measure consumer perceptions of time pressure at mealtime. These questions asked "How often do you (1) Fix quick meals because you're rushed for time? (2) Feel rushed for time when you are fixing meals? and (3) Fix meals which are easy to prepare to save bother?" Response categories ranged from "seldom or never" to "frequently." The mean value of TIME was 6.1 with a range from three to nine. The standardized alpha for this index was .67 and corrected item-to-total correlations ranged from .41 to .57.(5)

Knowledge of nutrition (KNOW)

Knowledge of nutrition was measured by asking "How much do you feel you know about nutrition?" The five response categories ranged from "almost nothing" to "a lot." This measure of nutritional knowledge is similar to measures used by other researchers (Alba 1983; Beattie 1983; Johnson and Russo 1984; Mackenzie 1986; Srull 1983). The mean value of KNOW was 3.4. Approximately 46 percent of the respondents said they knew "quite a bit" or "a lot," TABULAR DATA OMITTED while 39.5 percent said they knew "some," 11.4 percent "not too much," and 3.3 percent "almost nothing."

Several factors suggest that this study's single-item, self-assessed measure of nutritional knowledge is a reasonable, if not optimal, measure of nutritional knowledge. First, measures of actual and self-assessed knowledge have been found to be positively and significantly correlated. For example, Brucks (1985) found a correlation of .54 between self-assessed and objective measures of knowledge in a study of sewing machines. Second, and more important, Celsi and Olson (1988) and Maheswaran and Sternthal (1990) found no differences between results using multiple choice objective knowledge tests and results using a single self-assessed knowledge item. On the basis of these studies, the KNOW measure used in this study represents a reasonable measure of nutritional knowledge.

Education (EDUC)

Education was the highest grade of school completed by the respondent. The average level of education was 12.8 years.

Perceived health risks (RISK)

The measure of perceived health risks was a four-question index measuring respondent's perceptions of the health risks associated with not maintaining a nutritious diet. The specific questions asked "(1) How much of an effect do you feel what you eat will have on your future health? (2/3) How likely would you say it is that your health will suffer if you don't eat fruits/vegetables everyday? and (4) How likely do you believe it is that the foods we eat can help prevent some kinds of cancer?" Response categories for the first question ranged from "not very much" to "very much" on a three-point scale. The response categories for the other three questions ranged from "never thought about it" to "very likely" on a four-point scale. The first question was scored 1, 2.5, and 4 to avoid underweighting. The mean value of RISK was 12.2 with a range from four to 16. The standardized alpha for RISK was .69, and corrected item-to-item correlations ranged from .31 to .65.

Demographic and control variables

Age (AGE) was a continuous measure of the respondent's age on his/her last birthday. The mean value for AGE was 44.2 years with a range from 18 to 83 years. The measure of diet (DIET) was a dichotomy; zero indicates that the respondent was not on a diet, and one indicates that the respondent was on a diet. Approximately 27 percent of the respondents were on diets.


The hypotheses of this study were tested using a series of multiple regression models. The main effects hypotheses were tested using a linear additive regression model, while the conditional or moderator hypotheses were tested by adding appropriate interaction terms to the additive model. Bivariate correlations between the variables in this study are presented in the Appendix.

Main Effects

Table 2 contains the results obtained by regressing RDPs on the independent variables presented in Table 1. The results in Table 2 support the main effects hypotheses. As expected, TIME was negatively associated with adherence to RDPs. In addition, KNOW, EDUC, RISK, AGE, and DIET were all positively associated with RDPs, albeit the association was weak for education (p = .09).
Regression Model I: Main Effects of Perceived Time Pressure,
Human Capital, and Perceived Health Risks on RDPs
 Standardized Standard Error
Variable Beta Beta of Beta
Intercept 11.95 -- 1.39
TIME -0.26(**) -.14 0.09
KNOW 1.16(**) .26 0.20
EDUC 0.13(*) .08 0.07
RISK 0.24(**) .18 0.06
AGE 0.07(**) .28 0.01
DIET 1.06(**) .12 0.36
|R.sup.2~ = .29
* p |is less than~ .10.
** p |is less than~ .01.

Moderating Effects

In order to test the hypotheses that (1) knowledge of nutrition, (2) education, and (3) perceived health risks moderate the negative effects of perceived time pressure on adherence to RDPs, the authors added interaction terms to the basic regression model (Neter, Wasserman, and Kutner 1985, 232). Three separate models were estimated, each incorporating one of the interaction terms (KNOW, EDUC, or RISK). Significance of the interaction terms was tested in two ways: a t-test and a change in F-test (Chow test). Given the collinearity introduced by the interaction term, a change in F-test could show significance of an interaction even if the t-test failed to do so. Of the three interaction terms estimated, only the TIME x KNOW interaction was significant. Both the t-test (t = 2.46) and the change in F-test (F= 6.1, 1 and 429 df) were significant at the .05 level. To conserve space, Table 3 presents the results of the moderated regression model containing the TIME x KNOW interaction.

The significant interaction term shown in Table 3 supports hypothesis 2c, and indicates that the relationship between time pressure and use of RDPs is moderated by the level of nutritional knowledge. Specifically, when respondents indicated low levels of nutritional knowledge (KNOW = 1) the association between time pressure and RDPs was substantial and negative (-.79). However, when respondents indicated high levels of nutritional knowledge (KNOW = 5), the relationship between time pressure and RDPs was near zero. This interaction is shown in Figure 1 which illustrates the relationship between TIME and RDPs at varying levels of nutritional knowledge.(6)
Regression Model II: Knowledge of Nutrition as a Moderator of
the Effects of Perceived Time Pressure on RDPs
 Standardized Standard Error
Variable Beta Beta of Beta
Intercept 16.5 -- 2.24
TIME -1.00(**) -.50 0.31
TIME x KNOW 0.21(*) .46 0.09
KNOW -0.13 -.03 0.56
EDUC 0.11 .07 0.07
RISK 0.24(**) .19 0.06
AGE 0.06(**) .27 0.01
DIET 1.08(*) .13 0.35
|R.sup.2~ = .30
* p |is less than or equal to~ .01.
** p |is less than or equal to~ .001.

Additional Results

As employment has been used frequently in research examining time pressure and use of convenience foods, the relationships between employment status, perceptions of time pressure, and RDPs were examined. Because employment status is only one potential antecedent of time pressure and does not fully reflect the nature of time pressure as perceived by the consumer, the use of a perceptual measure of time pressure is desirable. Results in the Appendix indicate that the bivariate correlation between employment status and TIME is .39. Although significant (p |is less than~ .01), employment status accounts for less than 16 percent of the variance in TIME. As expected, employment status is negatively correlated (-.16, see Appendix) with RDPs (p |is less than~ .01). However, when TIME is controlled, the effect of employment status on RDPs becomes nonsignificant. Hence, although employment status has a negative effect on RDPs, this effect occurs indirectly through its effect on perceptions of time pressure.(7)


An important research question addressed in this study was the ability of certain characteristics to moderate the negative effects of perceived time pressure on adherence to recommended dietary practices (RDPs). A major proposition was that a main effects approach is not sufficient for understanding the effects of time pressure on consumer behavior, in general, and utilization of RDPs, in particular. Results in Table 3 support this logic. Specifically, knowledge of nutrition was found to moderate the negative effects of time pressure on RDPs. The negative effect of time pressure was high for those indicating low levels of nutritional knowledge but near zero for those indicating high levels of nutritional knowledge.

Therefore, results presented in Figure 1 indicate the importance of nutrition knowledge in mitigating the negative effects of perceived time pressure on the use of RDPs. More generally, these results suggest the importance of consumer knowledge as a moderator of time pressures that affect a wide range of behaviors including information search, shopping behavior, and decisionmaking.


There appears to be general agreement both in the popular media (TIME 1989) and in research (Robinson 1990) that perceived time pressures are increasing. Although actual time for leisure (time left over after work, household chores, personal care, and sleep) has increased or stayed the same for most groups in the last two decades (Robinson 1989) perceptions of being time pressed have increased. Given this pattern, perceived time pressures seem unlikely to lessen in the foreseeable future.

The results of this study indicate that perceptions of time pressure have adverse effects on eating habits and the quality of diets. Those perceiving higher levels of time pressure utilized recommended dietary practices to a lesser extent than those perceiving less time pressure. These adverse effects are likely to be especially severe in one- or two-parent households when the parents are employed. Under pressures of time, these parents can be expected to sacrifice activities considered less important. Planning and preparing meals that conform to recommended dietary practices may be one of these lower priority activities.

Even though time pressures may not be controllable, the results suggest that negative consequences can be mitigated by increases in efficiency associated with knowledge of nutrition. Because higher levels of nutritional knowledge can mitigate the negative effects of time pressure, nutritional education may help to ensure adherence to good dietary practices. The results suggest, however, that general knowledge (as measured by years of formal education) does not substitute for activity-specific knowledge. This is consistent with the results of expert/novice research reported by Anderson (1990), in which experts in chess have not been found to be more intelligent than less accomplished players. Instead, it is specific and extensive knowledge about chess that differentiates the expert from the novice.

Nutritional education can also play an important role in conveying the benefits of good dietary practices in terms of reducing risks associated with a poor diet. Although RISK did not moderate the negative effects of perceived time pressure on the use of RDPs, it did have a positive influence on their use (beta = .24). One possible reason that RISK did not moderate the effects of time pressure is while it measured the perceived probability of negative outcomes, it did not measure the perceived severity of these outcomes (Cunningham 1967; Kapferer and Laurent 1985). For perceived health risks to mitigate the negative effects of time pressure, it may be necessary that a person perceive the consequences as both very likely and very severe.

Interpreted broadly, the results underline the important role of consumer education in offsetting some negative aspects of contemporary lifestyles. The results demonstrate that general knowledge may not be sufficient to ensure use of recommended consumer practices when individuals feel time pressed. Instead, domain-specific knowledge as that typically conveyed by consumer education and information efforts is required. The results also suggest the importance of motivating consumers to use recommended practices by pointing out the negative consequences of neglecting them.

The evidence available about the effect of time pressure on information search and utilization suggests that it affects behaviors of central concern to consumer researchers. Therefore, time pressure clearly deserves a place on the consumer research agenda. Research might extend the results of the present study by investigating other behaviors such as exercise, information search, and label reading that are likely influenced by perceptions of time pressure. Second, research might investigate different types of messages and information formats to determine which best motivate and facilitate use of various recommended practices even when perceptions of time pressures are high. Finally, research might investigate how best to measure time pressures. For example, should global measures such as "always feel rushed" or activity-specific measures as the one in this study be utilized?



1 Throughout the paper the authors refer to perceived time pressure at mealtime simply as perceived time pressure. And, although an activity-specific measure of perceived time pressure such as that used here may not fully correspond to overall perceptions of time pressure, they are related (Herrmann et al. 1991). Therefore, those who perceive themselves to be time pressed overall are likely to perceive time pressures at mealtime as well.

2 The term moderator variable is used in this paper to indicate that the relationship between time pressure and RDPs depends on the level of another variable (e.g., nutritional knowledge, education, or perceived health risks). This is consistent with the way in which the term moderator variable is commonly used (Baron and Kenny 1986). Use of the term moderator variable does not indicate that variables as nutritional knowledge are somehow outside of the model of RDPs, but rather than such variables interact with time pressure in affecting the utilization of RDPs.

3 Perceived health risk may be a function, in part, of human capital (especially nutritional knowledge) because perceived health risk has to do with knowledge of and concern about the consequences of a poor diet. However, the authors distinguish perceived health risk from nutritional knowledge in terms of the mechanisms by which each affects the utilization of RDPs. Specifically, while nutritional knowledge is expected to operate as an ability variable that reduces behavioral costs and increases efficiency, perceived health risk is expected to operate as a motivational variable that increases the importance of food-related activities such as RDPs.

4 A major criticism of self-reported measures is that a subject's desire to appear consistent leads to inflated relationships among these variables. For example, those who indicate being under severe time pressures might also indicate that their utilization of RDPs is relatively low. However, as this study hypothesized moderated relationships (e.g., perceived time pressure has less effect on adherence to RDPs when knowledge of nutrition is high than low) the consistency bias works against the hypotheses.

5 A measure of employment status (EMP) was a three-point scale, with 1 representing "not employed outside the home," 2 "employed part-time outside the home," and 3 "employed full-time outside the home." Given the widespread use of employment status in research on time pressure and use of convenience foods, relationships among time pressure, employment status, and dietary practices are discussed later.

6 Although use of a summed index of items with a somewhat limited range (i.e., nine to 27) as the dependent variable in a regression model may not be optimal, several factors suggest that the regression results are robust to this limitation. First, unlike many regression models with limited dependent variables (e.g., dichotomous), the parameter estimates in this study did not lead to predicted values outside the range of actual values (nine to 27). Second, similar results were obtained using discriminant analysis (DA) even though DA utilizes a discrete dependent variable (e.g., four levels of RDP use) and is therefore not affected by range limitations on the dependent variable (Klecka 1980).

7 Employment status was incorporated into regression models I and II. Even when employment status was entered into the equation first, its effect on RDPs was nonsignificant, and the results were not substantively different from those in Tables 2 and 3.


Alba, Joseph W. (1983), "The Effects of Product Knowledge on the Comprehension, Retention, and Evaluation of Product Information," in Advances in Consumer Research, Volume X, Richard P. Bagozzi and Alice M. Tybout (eds.), Ann Arbor, MI: Association for Consumer Research: 577-580.

Alba, Joseph W. and J. Wesley Hutchinson (1987), "Dimensions of Consumer Expertise," Journal of Consumer Research, 13(March): 411-454.

Anderson, John R. (1990), Cognitive Psychology and Its Implications, Third edition, New York: W. H. Freeman and Company.

Baron, Reuben M. and David A. Kenny (1986), "The Moderator-Mediator Variable Distinction in Social Psychology Research: Conceptual, Strategic, and Statistical Considerations," Journal of Personality and Social Psychology, 51(December): 1173-1182.

Beattie, Ann E. (1983), "Product Expertise and Advertising Persuasiveness," in Advances in Consumer Research, Volume X, Richard P. Bagozzi and Alice M. Tybout (eds.), Ann Arbor, MI: Association for Consumer Research: 581-584.

Becker, Gary S. (1965), "A Theory of the Allocation of Time," The Economic Journal, 75(September): 493-517.

Bellante, Don and Ann C. Foster (1984), "Working Wives and Expenditures on Services," Journal of Consumer Research, 11(September): 700-707.

Berry, Leonard L. (1979), "The Time-Buying Consumer," Journal of Retailing, 55(Winter): 58-69.

Berry, Leonard L. (1990), "Market to the Perception," American Demographics. 12(February): 32.

Bettman, James R. and C. Whan Park (1980), "Effects of Prior Knowledge and Experience and Phase of the Choice Process on Consumer Decision Processes: A Protocol Analysis," Journal of Consumer Research, 7(December): 234-248.

Britton, Bruce K., Robert D. Westbrook, and Timothy S. Holdredge (1978), "Reading and Cognitive Capacity Usage: Effects of Text Difficulty," Journal of Experimental Psychology: Human Learning and Memory, 4(November): 592-591.

Brucks, Merrie (1985), "The Effects of Product Class Knowledge on Information Search Behavior," Journal of Consumer Research, 12(June): 1-16.

Celsi, Richard L. and Jerry C. Olson (1988), "The Role of Involvement in Attention and Comprehension Processes," Journal of Consumer Research, 15(September): 210-224.

Consumer Reports (1988), "Fast Food," 53(June): 355-361.

Consumer Reports (1990a), "Frozen Pot Pies," 55(January): 44-47.

Consumer Reports (1990b), "This Is Chili," 55(October): 688-691.

Converse, Philip E. (1989), "Perspectives on the Democratic Process," Institute for Social Research Newsletter, 16(2): 4-10.

Cunningham, Scott M. (1967), "The Major Dimensions of Perceived Risk," in Risk Taking and Information Handling in Consumer Behavior, Donald Cox (ed.), Boston: Harvard Business School: 82-108.

Feick, Lawrence F., Robert O. Herrmann, and Rex H. Warland (1986), "Search for Nutrition Information: A Probit Analysis of the Use of Different Information Sources," The Journal of Consumer Affairs, 20(Winter): 173-192.

Gross, Barbara L. and Jagdish N. Sheth (1989), "Time-Oriented Advertising: A Content Analysis of United States Magazine Advertising, 1890-1988," Journal of Marketing, 53(October): 76-83.

Hall, F. T. and M. P. Schroeder (1970), "Effects of Family and Housing Characteristics on Time Spent on Household Tasks," Journal of Home Economics, 62(January): 23-29.

Herrmann, Robert O., Rex H. Warland, Esther M. Forti, and Kuang-hua Hsieh (1991), "Time Scarcity: Conceptualizing, Operationalizing and Assessing Alternative Measures," in The Seventh Annual John-Labatt Marketing Research Seminar on Time and Consumer Behavior, Jean-Charles Chebat and Ven Venkatesan (eds.), Montreal: University of Quebec at Montreal (October).

Holman, Rebecca H. and R. Dale Wilson (1982), "Temporal Equilibrium as a Basis for Retail Shopping Behavior," Journal of Retailing, 58(Spring): 58-81.

Iyer, Easwar S. (1989), "Unplanned Purchasing: Knowledge of Shopping Environment and Time Pressure," Journal of Retailing, 65(Spring): 40-57.

Jackson, Ralph W., Stephen W. McDaniel, and C. P. Rao (1985), "Food Shopping and Preparation: Psychographic Differences of Working Wives and Housewives," Journal of Consumer Research, 12(June): 110-113.

Johnson, Eric J. and J. Edward Russo (1984), "Product Familiarity and Learning New Information," Journal of Consumer Research, 11(June): 542-550.

Johnson, Walter and David Kieras (1983), "Representation-Saving Effects of Prior Knowledge in Memory for Simple Technical Prose," Memory and Cognition, 11(September): 456-466.

Kapferer, Jean-Noel and Gilles Laurent (1985), "Consumer Involvement Profiles: A New Practical Approach to Consumer Involvement," Journal of Advertising Research, 25(December): 48-56.

Klecka, William R. (1980), "Discriminant Analysis," Sage University Paper series on Quantitative Applications in the Social Sciences, 07-019, Beverly Hills, CA and London: Sage Publications.

Mackenzie, Scott B (1986), "The Role of Attention in Mediating the Effect of Advertising on Attribute Importance," Journal of Consumer Research, 13(September): 174-195.

Maheswaran, Durairaj and Brian Sternthal (1990), "The Effects of Knowledge, Motivation, and Type of Message on Ad Processing and Product Judgments," Journal of Consumer Research, 17(June): 66-73.

Maynes, E. Scott (1989), "A Human Capital Model of Consumer Search," in Proceedings, 35th Annual Conference, Mary Carsky (ed.), Columbia, MO: American Council on Consumer Interests: 257-264.

National Research Council Committee on Diet and Health (1989), Diet and Health: Implications of Reducing Chronic Disease Risk, Washington, DC: National Academy Press.

Neter, John, William Wasserman, and Michael H. Kutner (1985), Applied Linear Statistical Models: Regression, Analysis of Variance, and Experimental Designs, 2nd Edition, Homewood, IL: Irwin.

Nickols, Sharon Y. and Karen D. Fox (1983), "Buying Time and Saving Time: Strategies for Managing Household Production," Journal of Consumer Research. 10(September): 197-208.

Nunnally, Jum C. (1978), Psychometric Theory, 2nd Edition, New York: McGraw-Hill.

Park, C. Whan, Easwar S. Iyer, and Daniel C. Smith (1989), "The Effects of Situational Factors on In-Store Grocery Shopping Behavior: The Role of Store Environment and Time Available for Shopping," Journal of Consumer Research, 15(March): 422-433.

Patterson, Blossom H. and Gladys Block (1988), "Food Choices and Cancer Guidelines," American Journal of Public Health, 78(March): 282-286.

Peterson, Bruce (1985), "Confidence: Categories and Confusion," GSS Technical Report No. 50, National Opinion Research Center, Chicago, IL.

Punj, Girish N. and Richard Staelin (1983), "A Model of Consumer Information Search Behavior for New Automobiles," Journal of Consumer Research, 9(March): 366-380.

Reilly, Michael D. (1982), "Working Wives and Convenience Consumption," Journal of Consumer Research, 8(March): 407-418.

Reingen, Peter H. (1973), "Risk-taking by Individuals and Informal Groups with the Use of Industrial Product Purchasing Situations as Stimuli," Journal of Psychology, 85(November): 339-345.

Robinson, John P. (1983), "Environmental Differences in How Americans Use Time: The Case for Subjective and Objective Indicators," Journal of Community Psychology, 11(April): 171-181.

Robinson, John P. (1989), "Time's Up," American Demographics, 11(July): 33-35.

Robinson, John P. (1990), "The Time Squeeze," American Demographics, 12(February): 30-35.

Roselius, Ted (1971), "Consumer Rankings of Risk Reduction Methods," Journal of Marketing, 35(January): 56-61.

Schafer, Robert B. (1978), "Factors Affecting Food Behavior and Quality of Husbands' and Wives' Diets," Journal of the American Dietetic Association, 72(February): 138-143.

Schaninger, Charles M. and Chris T. Allen (1981), "Wife's Occupational Status as a Consumer Behavior Construct," Journal of Consumer Research, 8(September): 189-196.

Schary, Philip B. (1971), "Consumption and the Problem of Time," Journal of Marketing, 35(April): 50-55.

Srull, Thomas K. (1983), "The Role of Prior Knowledge in the Acquisition, Retention, and Use of New Information," in Advances in Consumer Research, Volume X, Richard P. Bagozzi and Alice M. Tybout (eds.), Ann Arbor, MI: Association for Consumer Research: 572-576.

Strober, Myra H. and Charles B. Weinberg (1980), "Strategies Used by Working and Nonworking Wives to Reduce Time Pressures," Journal of Consumer Research, 6(March): 338-348.

TIME (1989), "How America Has Run Out of Time," 133(April 24): 58-67.

The Wall Street Journal (1988), "Are Square Meals Headed for Extinction," 211(51, March 15): 37.

Wallsten, Thomas S. and Curtis Barton (1982), "Processing Probabilistic Multidimensional Information for Decisions," Journal of Experimental Psychology: Learning, Memory, and Cognition, 8(September): 361-384.

Wright, Peter (1974), "The Harassed Decision Maker: Time Pressures, Distractions, and the Use of Evidence," Journal of Applied Psychology, 59(October): 555-561.

David L. Mothersbaugh is a doctoral candidate, Katz Graduate School of Business, The University of Pittsburgh, Pittsburgh, PA. Robert O. Herrmann is Professor of Agricultural Economics and Rex H. Warland is Professor of Rural Sociology, The Pennsylvania State University, University Park.

The authors express their appreciation to Lawrence Feick, Timothy B. Heath, Michael S. McCarthy, C. Whan Park, Linda L. Price, to the editor, Carole J. Makela, and to two anonymous reviewers for their comments on earlier versions of this paper.
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Title Annotation:includes appendix
Author:Mothersbaugh, David L.; Herrmann, Robert O.; Warland, Rex H.
Publication:Journal of Consumer Affairs
Date:Jun 22, 1993
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