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Response Efficacy

Definition

Response efficacy is defined as the extent people believe a recommended response effectively deters or alleviates a health threat (Witte, 1992, 1994).

Response efficacy is a central concept in several health information processing models, including the Health Belief Model (Becker, 1974; Rosenstock, 1974) and Protection Motivation Theory (Rogers, 1975, 1983). As is the case with self-efficacy, response efficacy sometimes is conceptualized as a property of a message, such as when a message has response-efficacy characteristics (e.g., Lapinski, 2006; Rimal & Real, 2003). Response efficacy is frequently conceptualized as a belief in the ability of a recommended behavior to alleviate a health threat (e.g., "I think condoms prevent AIDS," Witte & Morrison, 2000).

Within Protection Motivation Theory (PMT), response efficacy is part of a second appraisal (coping) following exposure to a fear appeal message. If a perceived threat (threat appraisal) is judged to be high, then an individual will engage in assessing both self and response efficacy. If both efficacy appraisals are judged to be sufficiently high, then an individual will be motivated to reduce the threat (by adopting message recommendations). If one or both of the efficacy appraisals are insufficiently high, then the individual will be motivated to reduce fear by a number of different strategies (e.g., message derogation, message avoidance).

Response efficacy is a construct similar to the benefits-of-change component of the health belief model (Hochbaum, 1958; Janz & Becker, 1984). In addition, response efficacy has common conceptual components with outcome expectations found in expectancy value theories, such as Theory of Reasoned Action [TRA] and Theory of Planned Behavior [TPB] (Ajzen, 1988; Schifter & Ajzen, 1985). These theories include an attitudinal component (outcome expectancies) of the consequences people anticipate when they engage in a specific health behavior.

Nevertheless, Bandura, distinguishes among the response efficacy and outcome expectations of the TRA and TPB health behavior models. Response efficacy is concerned with whether a prescribed remedy or course of action can produce a particular health-related goal. For instance, response efficacy encompasses a belief that wearing a condom can prevent the spread of sexually transmitted disease, while outcome expectations reflect the consequences (physical, social, and psychological) of possibly contracting a sexually-transmitted disease.

Response efficacy also overlaps with several concepts within the health communication literature. Similar concepts include perceived benefits, which is defined as beliefs about the positive outcomes associated with a behavior in response to a perceived threat. For example, the perceived benefits of limiting one's number of sexual partners may include a person's belief that he or she can reduce their chances of AIDS, e.g., "Do you think you can reduce your risk of AIDS by limiting the number of male sex partners you have?" (Aspinwall, Kemeny, Taylor, & Schneider, 1991).

Response efficacy is theoretically linked to people's beliefs about their own outcomes and not those that might occur for others. As a result, people could think reducing the number of sex partners would help reduce AIDS for others, but not necessarily deem it helps them. Hence, a response efficacy measure should include a specific health behavior, the specific benefit it affords, and the belief the behavior alleviates a personal health threat.

Suggested Measure

Since response-efficacy tends to be measured in relationship to a specific health problem, there is no encompassing or single measure of response efficacy. A measure of response efficacy should include the specific behavior to be taken and the specific health benefit that will occur. Four functional examples are provided below (mammograms, two for breast self-exams, and a general measure of recommended advice).

1) Champion, V.L. (1999). Revised susceptibility, benefits, and barriers scale for mammography screening. Research in Nursing & Health, 22, 341-348.

Champion assessed the response efficacy of obtaining a mammogram with the following five items:

  1. If I get a mammogram and nothing is found, I do not worry as much about breast cancer.
  2. Having a mammogram will help me find breast lumps early.
  3. If I find a lump through a mammogram, my treatment for breast cancer may not be as bad.
  4. Having a mammogram is the best way for me to find a very small lump.
  5. Having a mammogram will decrease my chances of dying from breast cancer.

All items were anchored with a five-point Likert scale with response options from "strongly agree" to "strongly disagree" (α = .75)

2) Umphrey, L.R. (2004). Message defensiveness, efficacy, and health-related behavioral intentions. Communication Research Reports, 21(4), 329-337.

Response efficacy was measured using the following three items:

  1. Breast self-examinations are highly effective in the detection of breast cancer.
  2. Performing breast self-examinations could significantly affect one's medical outcome.
  3. Breast self-examination is an effective method for the early detection of breast cancer.

All items were anchored with a five-point Likert scale with response options from "strongly agree" to "strongly disagree" (α = .70).

3) Anderson, R.B. (2000). Vicarious and persuasive influences on efficacy expectations and intentions to perform breast self-examination. Public Relations Review, 26(1), 97-114.

Participants rated their beliefs about the effectiveness of practicing breast self examination (BSE) on three items:

  1. I believe BSE is worthwhile.
  2. I believe BSE is an effective technique for detecting breast abnormalities.
  3. I believe BSE is an effective technique for reducing the number of breast cancer deaths.

All items were anchored with 11-point response scales with response options from "not at all worthwhile or effective" to "extremely worthwhile or effective" (α = .98).

4) Feng, B., & Burleson, B.R. (2008). The effects of argument explicitness on responses to advice in supportive interactions. Communication Research, 35(6), 849-874.

Feng and Burleson assessed the degree to which people believed the recommended advice within a message was efficacious.

Perceived efficacy was measured with the following three items:

  1. I believe that the advised action could help to solve my problem.
  2. I think that the advised action could solve my difficulties.
  3. I perceive that the advised action could help fix my problem.

All items were anchored with a five-point Likert scale with response options from "strongly agree" to "strongly disagree" (α = .85).

Rationale for Selection

The aforementioned items were chosen because they represent a wide range of contexts in which perceived self-efficacy has been measured reliably. In aggregate, they provide a flavor of the types of items that are typically used in current research, and they can be adapted to a particular health context under study.

Reliability

Alphas for response efficacy tend to have a range in the literature (e.g., .65 to .98) depending on the unique context of a study and the particular response and health threat considered. The items selected as examples herein have a range (.70 to .98).

Use of Measure (with examples)

Response efficacy and closely aligned concepts are core components of popular information processing models used in health communication, including Social Cognitive Theory (Bandura, 2001), the Health Belief Model (Janz & Becker, 1984; Maiman & Becker, 1974; Rosenstock, 1974), Protection Motivation Theory (Rogers, 1975, 1983), the Extended Parallel Process Model (Witte, 1992, 1998), and the Theory of Planned Behavior (Ajzen, 1985).

Response efficacy has been positively associated with health outcomes in prior research: mammography compliance (Champion, 1999), sunscreen use (Rimal & Real, 2003), as well as STD and HIV testing among college students, (Zak-place & Stern, 2004). Response efficacy has been negatively associated with: defensive message processing of breast self-exam messages (Umphrey, 2004), and trait anxiety (Witte & Morrison, 2000). Response efficacy has been shown to mediate self-affirmations and the extent persons eat fruits and vegetables (Epton & Harris, 2008).

Additional Commentary

The literature provides some examples where only a portion of a study's response items are provided. A few examples are:

1) Epton & Harris (2008) measured response efficacy using six items based on the health message, but provided only two of the items:

  1. Eating at least 5 portions of fruit and vegetables each day will reduce my risk of heart disease and some cancers
  2. Eating at least 5 portions of fruit and vegetables each day will improve my health by boosting my immune system

All items were measured on 7-point scales, anchored by (strongly agree) to (strongly disagree). α = .70.

2) Witte, K., & Morrison, K. (2000) measured response efficacy with two items, but provided only one:

"I think that condoms prevent AIDS" on scales anchored by (strongly disagree) to (strongly agree). α = .81.

3) McMahan, Witte, & Meyer (1998) measured response efficacy with three items, but provided only one:

"Reducing exposure to electromagnetic fields is effective in preventing unwanted health effects", α = .82).

At times, journal editors require authors to shorten manuscripts and the full listing of index items can be a casualty. Nevertheless for the literature to advance, all measures should be included so other scholars can employ them in their research. The latter should be encouraged in journals that are in print and provided online as well as online-only journals.

Several studies report development of indexes through diverse qualitative means, such as the completion of open-ended questionnaires from moderately sized samples as well as combinations of interviews and existing measures, etc. The primary benefit of this approach is prior measures are bypassed deliberately and the process develops operant or original, case study measures. Wulfert and Wan (1993, 1995) use the latter approach, which might be considered if a researcher has the time and money to originate measures.

Finally, Witte, Cameron, McKeon, & Berkowitz (1996) provide a template for researchers to develop their own response efficacy index tailored to their specific research context:

  1. (Recommended response) works in preventing (health threat)
  2. (Doing/using recommended response) is effective in preventing (health threat).
  3. If I (do/use recommended response), I am less likely to get (health threat).

References

Ajzen, I. (1985).

From intentions to action: A theory of planned behavior. In J. Kuhl and J. Beckman (Eds.) Action control: From cognitions to behaviors (pp. 11-39). New York: Springer.

Ajzen, I. (1988).

Attitudes, personality, and behavior. Homewood, IL, US: Dorsey Press.

Anderson, R.B. (2000).

Vicarious and persuasive influences on efficacy expectations and intentions to perform breast self-examination. Public Relations Review, 26(1), 97-114.

Aspinwall, L.G., Kemeny, M.E., Taylor, S.E., & Schneider, S.G.(1991).

Psychosocial predictors of gay men's AIDS risk-reduction behavior. Health Psychology, 10(6), 432-444.

Bandura, A. (2001).

Social cognitive theory: An agentic perspective. Annual Review of Psychology, 52, 1-26.

Becker, M. H. (1974).

The Health Belief Model and personal health behavior. San Francisco, CA: Society for Public Health Education.

Champion, V.L. (1999).

Revised susceptibility, benefits, and barriers scale for mammography screening. Research in Nursing & Health, 22, 341-348.

Epton, T. & Harris, P.R. (2008).

Self-affirmation promotes health behavior change. Health Psychology, 27(6), 746-752.

Feng, B., & Burleson, B.R. (2008).

The effects of argument explicitness on responses to advice in supportive interactions. Communication Research, 35(6), 849-874.

Hochbaum, G.M. (1958).

Public participation in medical screening programs: A sociopsychological study. (Public Health Service, PHS, Publication 572). Washington, DC: U.S. Government Printing Office.

Janz, N., & Becker, M. (1984).

The Health Belief Model: A decade later. Health Education Quarterly, 11, 1-47.

Lapinski, M. K. (2006).

StarvingforPerfect.com: A theoretically based content analysis of pro-eating disorder web sites. Health Communication, 20(3), 243-253.

Maiman, L. A. & Becker, M. H. (1974).

The Health Belief Model: Origins and correlates in psychological theory. Health Education Monographs, 2, 336-353.

McMahan, S., Witte, K., & Meyer, J. (1998).

The perception of risk messages regarding electromagnetic fields: Extending the Extended Parallel Process Model to an unknown risk. Health Communication, 10(3), 247-260.

Rimal, R.N. & Real, K. (2003).

Perceived risk and efficacy beliefs as motivators of change: Use of the Risk Perception Attitude (RPA) framework to understand health behaviors. Human Communication Research, 29(3), 370-399.

Rogers, R. W. (1975).

A protection motivation theory of fear appeals and attitude change. Journal of Psychology 91, 93-114.

Rogers, R. W. (1983).

Cognitive and physiological processes in fear appeals and attitude change: a revised theory of protection motivation. In J. T. Cacioppo & R. E. Petty (Eds.), Social Psychophysiology: A sourcebook (pp. 153-176). New York: The Guildford Press.

Rosenstock, I. M. (1974).

Historical origins of the health belief model. Health Education Monographs, 2, 1-8.

Schifter, D. E., & Ajzen, I. (1985).

Intention, perceived control, and weight loss: An application of the theory of planned behavior. Journal of Personality and Social Psychology, 49(3), 843-851.

Umphrey, L.R. (2004).

Message defensiveness, efficacy, and health-related behavioral intentions. Communication Research Reports, 21(4), 329-337.

Witte, K. (1992).

Putting the fear back into fear appeals: The extended parallel process model. Communication Monographs, 59, 330-349.

Witte, K. (1994).

Fear control and danger control: A test of the extended parallel process model (EPPM). Communication Monographs, 61, 113-134.

Witte, K. (1998).

Fear as motivator, fear as inhibitor: Using the Extended Parallel Process Model to explain fear appeal successes and failures. In P.A. Andersen & L.K. Guerrero (Eds.), The handbook of communication and emotion: Research, theory, applications, and contexts (pp. 423-450). Sand Diego, CA: Academic Press.

Witte, K., Cameron, K., McKeon, J., & Berkowitz, J. (1996).

Predicting risk behaviors: Development and validation of a diagnostic scale. Journal of Health Communication, 1, 317-341.

Witte, K., & Morrison, K. (2000).

Examining the influence of trait anxiety/repression-sensitization on individuals' reactions to Fear Appeals. Western Journal of Communication, 64(1), 1-27.

Wulfert, E., & Wan, C.K. (1993).

Condom use: A self-efficacy model. Health Psychology, 12(5), 346-353.

Wulfert, E., & Wan, C.K. (1995).

Safer sex intentions and condom use viewed from a Health Belief, Reasoned Action, and Social Cognitive perspective. The Journal of Sex Research, 32(4), 299-311.

Zak-Place, J. & Stern, M. (2004).

Health believe factors and dispositional optimism and predictors of STD and HIV preventative behavior. Journal of American College Health, 52(5), 229-236.