Skip Navigation



Exposure in mass communication is defined conceptually as "the extent to which audience members have encountered specific messages or classes of messages/media content" (Slater, 2004, p. 168); and "the degree to which audience members have access to, recall or recognize the intervention" (Valente, 2001, p. 117).

Exposure's fundamental importance as a variable in health communication is self-evident. It is difficult to test the impact of communications or messages unless researchers establish that subjects or respondents are exposed to the communications or messages. Hornik (2002) notes "good evidence" suggests variation in exposure is a more robust predictor of public health communication campaign success than variation in message quality (p. 31). Hornik adds the reason some large health communication projects fail (or reach a null hypotheses) is insufficient exposure. Reliable measures of exposure additionally are important because unreliable measures may underestimate the associations among interventions and outcomes (Lee, Hornik, & Hennessy, 2008).

Although exposure has been described as "a straightforward concept," it is "messy" to operationalize in measurement (Slater, 2004, p. 168). Given the above conceptual definitions, an immediate question is how to operationalize "encountered" or "access." Has a subject or respondent "encountered" or "accessed" a message simply by being in the room where and when it is broadcast or discussed?

Some clarification occurs by delineating between potential exposure and encoded exposure. Encoded exposure "generates at least a minimal memory trace in individuals" (Southwell, Barmada, Hornik, & Maklan, 2002, p. 446). Herein scholars suggest exposure overlaps with attention, because "attention is the medium that makes information appear in consciousness" (Csikszentmihalyi as cited in Potter, 2008, p. 153). However, Potter (2008) differentiates between physical exposure and encoded exposure based on attention by arguing "…exposure addresses whether a person is physically exposed to a message or not, while the idea of attention addresses how much cognitive effort of concentration the person devoted to the message" (p. 153). Building on the second of our initial definitions, encoded exposure requires enough attention to generate a memory trace that enables a respondent to recognize the intervention.

General recognition of an intervention is theorized more as a specific recall of content of the intervention than representing a memory trace (Southwell, 2005). Consistent with this, closed-ended recognition questions that ask respondents if they recognize an advertisement often deemphasize respondent memory in lieu of open-ended questions that ask respondents to recall the arguments used in an advertisement (Southwell, 2005). Recognition and recall vary in terms of specific user specificity, which is an important dimension of exposure measurement (Nagler & Hornik, 2012). Consistent with Southwell, et al.'s (2002) requirement of "at least a minimal memory trace," and with other conceptualizations (Lang, 1995), encoded exposure is achieved at the less specific level of recognition. Slater (2004) speculates that "exposure may leave an affective if not a cognitive impression of some kind, even if the messageshave not been attended to well enough to be remembered" (p. 168).

Exposure to the information or message also is a fundamental element of mass communication and communication theory. McGuire's (2001) conceptual, sequential Communication-Persuasion Matrix has as its initial two steps exposure followed by attention. Encoded exposure is a necessary precursor of hypothesized effects on downstream variables, such as knowledge, belief, attitude, intention, and behavior. Message argument effects on these downstream variables require deeper cognitive processing, according to theoretical models such as the Heuristic Systematic Model (HSM) (Chaiken, 1980) and the Elaboration Likelihood Model (ELM) (Petty & Cacioppo, 1984). All the latter models postulate deeper cognitive processing is systematic and involves elaboration.

A higher frequency of campaign messages increases the opportunities to assess encoded exposure within a research population, and potentially stimulates deeper processing among those who have achieved encoded exposure. The latter may include the cumulative effects (Lee, et al., 2008) of repeated exposure. These effects may offset identified concerns that insufficient exposure opportunities may explain the inability of some large health communication interventions to achieve hypothesized effects.

It is important to remember that mass mediated exposure can be multiplied or amplified by interpersonal or group conversation or discussion. People may be initially exposed to the message through such social interaction, which multiplies mediated exposure and may eclipse or extend the impact of media channels. People initially exposed through a media health campaign may be exposed again to the message through social interaction, which amplifies their exposure frequency. In the measurement of mediated campaigns, the addition of social interaction measures (when relevant) provides a more comprehensive picture of message exposure.

Measurement approaches and commentary on associated general validity and reliability

Methods of measuring exposure vary by research setting. Exposure in experimental research can be assigned. Assignment to the exposed group does not mean a subject pays attention to or encodes the message. However, attention and encoding may be manipulated in a controlled experiment, making this setting especially useful in isolating exposure and related variables within theoretical frameworks.

The two approaches and associated measures of exposure frequently used in survey research are individual-level self-report and population-level general media exposure. The most frequently used method to measure encoded exposure in mass communication research is self-reports derived within surveys (Fishbein & Hornik, 2008). Other instruments of self-reports, such as diaries, also have been used. Population-level general media exposure, from which some level of encoded exposure is assumed, will be described before discussing the more commonly used individual-level self-report.

Population-level measures fundamentally measure potential encoded exposure based on opportunities or possibilities of physical exposure. The measurement of encoded exposure of a mediated message (using population-level media exposure) assumes some exposure to the message, either through the mass media or indirectly through related conversations (Southwell & Yzer, 2007). Conventional advertising measures such as Gross Rating Points (GRPs), based on the underlying measures of reach and frequency, quantify the physical opportunities for exposure.

There has been some research comparing GRPs to self-reported encoded exposure. Southwell et al. (2002) found GRPs for an advertisement used in a study significantly predicted average memory for an advertisement.

Self-reports operate, by definition, at the individual level and includes measures of unaided recall and aided recall - or recognition. In unaided recall, respondents are asked to recall communications, such as ads and/or their messages, with minimal prompting. In aided recall there is more description provided, often with incrementally increasing detail (Morris, Rooney, Wray, & Kreuter, 2009).

Recognition can be described similarly, as recognition and aided recall often have been synonymous in disease prevention research (Valente in Morris et al., 2009). Some research suggests unaided recall often under-reports exposure and aided recall frequently over-reports exposure (Freimuth, Cole, & Kirby, 2000).

The specificity within both measurement approaches contribute to validity (Romantan, Hornik, Price, Cappella, & Viswanath, 2008; Slater, 2004). An obvious example in population-level, assumed encoded exposure is measuring respondent use of the specific media channels that carried an intervention's communication initiatives. More specificity at a population level includes measuring a user's exposure to specific health programming.

At the individual level, Romantan et al. (2008 p. 2) cite "ample evidence that exposure measures that assess people's aided or unaided recall of specific campaign messages are more predictive of health cognitions and behaviors than measures which ask generally about exposure to health topics or merely assess the amount of time people use a certain media channel."

User recognition is less confounded than unaided recall "with variables related to attention such as prior interest in topic" (Slater, 2004, p. 170). The latter is a key reason user recognition is often recommended. On the other hand, with less specificity required than recall, recognition may increase the potential of respondents recognizing communications to which they actually have not been exposed. The use of foil or ringer communications, in addition to the actual ones, helps overcome this confound (Slater, 2004).

Both self-report and general media exposure have noted there are threats to validity in measuring encoded exposure. Clearly, with general media exposure comes "absorbing the error associated with [respondents] not actually encountering the messages of interest" (Slater, 2004, p. 169). On the other hand, self-reports include the threat of selective exposure (Morris, et al., 2009; Slater, 2004), necessitating the "use of various strategies to control the effects of selective attention due to prior knowledge or involvement which would otherwise undermine causal claims" (Slater, 2004, p. 169). The risk to valid research conclusions is the communication or message is systematically attended to, to a greater degree, by certain groups of individuals within the population of interest (e.g., when physically active persons comparatively pay more attention to an exercise campaign). Self-reports about time devoted to watching general television news watched also have been found to be significantly inflated (Prior, 2009a). Prior (2009b) found this inflation was due to inaccurate recall rather than social desirability biases.

Based on this review of exposure measurement, self-reported recognition (or aided recall) measures of encoded exposure of specific messages are recommended. For mediated campaigns, the addition of measuring encoded exposure through conversation is recommended. Additionally, foil communications may be used to establish validity. Although more problematic in unaided recall, controlling for prior knowledge or involvement also is recommended.

Example measures with reliability and validity findings

Self-report recognition measures

Self-report recognition measures from the National Survey of Parents and Youth (NSPY) (Southwell, et al., 2002):

Have you ever seen or heard this ad?

Not at all;      Once;      2 to 4 times;      5 to 10 times;      More than 10 times;      Don’t know.

In recent months, how many times have you ever seen or heard this ad?

Not at all;      Once;      2 to 4 times;      5 to 10 times;      More than 10 times;

In the Southwell et al. (2002) study, 84% of youth respondents (9-18 years of age) identified at least one of the ads as were broadcast during the designated time period. 62% of parents recognized at least of one of the ads. In terms of perceived frequency of exposure, 35% of youth reported at least one ad each week, compared to 24% of parents.

The validity of encoded recognition was measured by comparing accurate identification of actual televised ads to untelevised foil ads. On average, 45% of youth correctly recognized an actual youth-oriented ad and 12% of youth incorrectly recognized a foil youth-oriented ad. Young persons were more likely to report recognizing an actual ad than a foil ad (t = 50.05, p =.01). For parents, on average, 30% correctly recognized an actual parent-oriented ad and 16% incorrectly recognized a foil parents-oriented ad. For parents, as well, there was a significant difference between recognition of actual and foil ads (t = 16.62, p = .01).

A second finding in this study suggests an increased frequency of a communication, and ensuing opportunities for encoded exposure, is associated with actual encoded exposure as measured. Gross rating points (GRPs) are a measure of opportunities for a given population to be exposed to a mediated communication. Across ads, there was a significant correlation between the average recognition or encoded exposure of an advertisement and its GRPs. Higher correlation was found for youth (r = 0.82; n = 23 ads) than for parents (r = 0.53; n = 10). Reasonable alternative explanations noted why correlation for parents was lower. Overall, the correlations between self-reported encoded exposure and GRPs, or opportunities for exposure, lend some validity to self-report measures.

General media exposure measures

General media exposure measures from the National Survey of Parents and Youth [NSPY] (Lee, et al., 2008):

TV and radio use

Respondents were asked how much they used each medium on a weekday, using the following nine-point scale:

1 = none,
2 = half-hour or less,
3 = about 1 hour,
4 = about 2 hours,
5 = about 3 hours,
6 = about 4 hours,
7 = about 5 hours,
8 = about 6 hours,
9 = 7 hours
or more.

An eight-point scale was used for the weekend:

1 = none,
2 = less than 1 hour,
3 = 1-2 hours,
4 = 3-4 hours,
5 = 5-6 hours,
6 = 7-8 hours,
7 = 9-10 hours,
8 = 11 hours
or more

Internet use

Respondents were asked how often they had used the Internet in the last six months, using the following five-point scale:

1 = never,
2 = a few times a year,
3 = once or twice a month,
4 = at least once a week,
5 = every day
or almost every day

Magazine use

Respondents were asked how often they read magazines, using the following five-point scale:

1 = never,
2 = a few times a year,
3 = once or twice a month,
4 = at least once a week,
5 = every day
or almost every day

Newspaper use

Parents were asked how often they read newspapers, using the following five-point scale:

1 = never,
2 = a few times a year,
3 = once or twice a month,
4 = at least once a week,
5 = every day
or almost every day

Using multiple rounds of data from the six NSPY general media exposure measures, Lee et al. (2008) tested both reliability and stability using general media exposure. While reliability includes consistency of the measurement instrument, stability includes consistency of the underlying behavior (Lee, et al., 2008). There were some differences in the media exposure questions posed to young persons and parents (i.e., newspaper reading was not tested in youths) and within youths (i.e., the youngest children, 9-11, were asked only about TV, and not about Internet, magazines, or radio).

In order to try to distinguish stability from reliability, a structural equation model proposed by Wiley and Wiley (as cited in Lee et al., 2008) was used. Correlation coefficients over the three survey rounds showed overall low to moderate reliability for the selected media, with r-values between .54 and .66 for youths, and .49 and .87 for parents. Stability was higher, showing moderate stability for youths, with correlations in the range of .62 and .80 between times 2 and 1; .82 and .90 between times 3 and 2; and .54 and .68 between times 3 and 1. Stability of exposure for parents was higher, with correlations in the range of .79 and 1.0 between times 2 and 1; .85 and .96 between times 3 and 2; and .70 and .90 between times 3 and 1. All correlation coefficients were statistically significant (p =.01).

Rationale for Selection

Self-reported recognition measures were included and recommended for reasons already discussed. General media exposure measures were included for media studies interested in exposure to routine communications (e.g., health-related news) and because, as a proxy, they have been used to measure exposure to health campaign inteventions.

Additional Commentary

Morris et al. (2009) provide a systematic review of exposure measurement in community-based health communication intervention studies. Morris et. al. (2009) contrast current practices and recommended practices. For the 54 studies between 2003 and 2007 they reviewed, a majority (n = 38%; 70%) assessed exposure. Of those, most (n = 31; 80%) used simple dichotomous measures, while less than half (n = 16; 42%) used exposure data to adjust intervention effects. Only six (16%) of the studies that assessed exposure addressed the potential threat of selective exposure.

Finally, the validity of exposure measurement can be strengthened through research design.
For example, longitudinal studies with self-reports can establish a baseline to account for self-selection (Slater, 2004) and possibly evaluate dose-response relationships (Morris, et al., 2009). Quasi-experiments in the field can vary message availability and amount or dose between communities and/or across time (Fishbein & Hornik, 2008). This approach strengthens positive hypothesized findings in studies using self-report measures and using population-level assumed encoded exposure measures.


Chaiken, S. (1980).

Heuristic versus systematic information processing and the use of source versus message cues in persuasion.
Journal of Personality and Social Psychology, 39(5), 752-766.

Fishbein, M., & Hornik, R. (2008).

Measuring media exposure: An introduction to the special issue.
Communication Methods and Measures, 2(1), 1-5.

Freimuth, V., Cole, G., & Kirby, S. (2000).

Issues in evaluating mass media-based health communication campaigns

Hornik, R. C. (2002).

Exposure: Theory and evidence about all the ways it matters.
Social Marketing Quarterly, 8(3), 30-37.

Lang, A. (1995).

Defining audio/video redundancy from a limited-capacity information processing perspective.
Communication Research, 221(1), 86-115.

Lee, C, Hornik, R., & Hennessy, M. (2008).

The reliability and stability of general media exposure measures.
Communication Methods and Measures, 2(1), 6 - 22.

Morris, D. S., Rooney, M. P., Wray, R. J., & Kreuter, M. W. (2009).

Measuring exposure to health messages in community-based intervention studies: A systematic review of current practices.
Health Education & Behavior, 36(6), 979-998.

Nagler, R. H., & Hornik, R. C. (2012).

Measuring media exposure to contradictory health information: A comparative analysis of four potential measures.
Communication Methods and Measures, 6(1), 56-75.

Petty, R. E., & Cacioppo, J. T. (1984).

The effects of involvement on responses to argument quantity and quality: Central and peripheral routes to persuasion.
Journal of Personality and Social Psychology, 46(1), 69-81.

Potter, J. W. (2008).

The importance of considering exposure states when designing survey research studies.
Communication Methods and Measures, 2(1), 152-166.

Prior, M. (2009a).

The immensly inflated news audience: Assessing bias in self-reported news exposure.
Public Opinion Quarterly, 73(1), 130-143.

Prior, M. (2009b).

Improving media effects research through better measurement of news exposure.
The Journal of Politics, 71(3), 893-908.

Romantan, A., Hornik, R., Price, V., Cappella, J., & Viswanath, K. (2008).

A comparative analysis of the performance of alternative measures of exposure.
Communication Methods and Measures, 2(1), 80-99.

Slater, M. D. (2004).

Operationalizing and analyzing exposure: The foundation of media effects research.
Journalism and Mass Communication Quarterly, 81(1), 168.

Southwell, B. G., Barmada, C. H., Hornik, R. C., & Maklan, D. M. (2002).

Can we measure encoded exposure? Validation evidence from a national campaign.
Journal of Health Communication, 7(5), 445-453.

Southwell, B., & Yzer, M. (2007).

The roles of interpersonal communication in mass media campaigns.
Communication Yearbook (Vol. 31, pp. 420-462).

Southwell, B. (2005).

Between messages and people: A multilevel model of memory for television content.
Communication Research, 32(1), 112-140.

Valente, T. W. (2001).

Evaluating communication campaigns. In R. E. Rice & C. K. Atkin (Eds.), Public communication campaigns. (3rd ed., pp. 105-124).
Thousand Oaks, CA: Sage Publications, Inc.