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Information Processing and Negative Affect: Evidence From the 2003. Health Information National Trends Survey. Ellen Burke Beckjord, Lila J. Finney Rutten, ...
Health Psychology 2008, Vol. 27, No. 2, 249 –257

In the public domain DOI: 10.1037/0278-6133.27.2.249

Information Processing and Negative Affect: Evidence From the 2003 Health Information National Trends Survey Ellen Burke Beckjord, Lila J. Finney Rutten, Neeraj K. Arora, Richard P. Moser, and Bradford W. Hesse National Institutes of Health Objective: Health communication can help reduce the cancer burden by increasing processing of information about health interventions. Negative affect is associated with information processing and may be a barrier to successful health communication. Design and Main Outcome Measures: We examined associations between negative affect and information processing at the population level. Symptoms of depression (6 items) and cancer worry (1 item) operationalized negative affect; attention to health information (5 items) and cancer information-seeking experiences (6 items) operationalized information processing. Results: Higher cancer worry was associated with more attention to health information ( p ⬍ .01) and worse cancer information-seeking experiences ( p ⬍ .05). More symptoms of depression were associated with worse information-seeking experiences ( p ⬍ .01), but not with attention. Conclusions: We found population-level evidence that increased cancer worry is associated with more attention to health information, and increased cancer worry and symptoms of depression are associated with worse cancer information-seeking experiences. Results suggest that affect plays a role in health information processing, and decreasing negative affect associated with cancer communication may improve experiences seeking cancer information. Keywords: health communication, information processing, negative affect

Tomar & Logan, 2005), and interventions aimed at promoting health behavior or aiding health-related decision making often rely, in part, on processing of cancer communication (e.g., Miller et al., 2005). There are a number of challenges to promoting successful cognitive processing of cancer communication, including the increasing complexity of the cancer information environment and disparities in access to cancer information (Viswanath, 2005). An additional challenge that is largely unexplored is the impact of negative affect (e.g., symptoms of anxiety and depression) on the cognitive processing of cancer communication. Negative affect, generally defined to encompass a variety of aversive feelings and moods (Russell & Carroll, 1999; Watson, Clark, & Tellegen, 1988; Watson & Pennebaker, 1989), is prevalent across the cancer care continuum. For example, symptoms of depression have been associated with being at genetic risk for cancer (for a review, see Lerman, Croyle, Tercyak, & Hamann, 2002), symptoms of depression, anxiety, and increased cancerspecific distress have been associated with abnormal cancer screening results (Alderete, Juabre, Kaplan, Pasick, & Pe´rezStable, 2006; Andrykowski, Boerner, Slasman, & Pavlik, 2004; Brett, Bankhead, Henderson, Watson, & Austoker, 2005), and elevated symptoms of depression and anxiety have been observed among cancer patients and survivors (Burgess et al., 2005; Dausch et al., 2004; Stark et al., 2002). Given the importance of information processing to health interventions and the prevalence of negative affect across the cancer care continuum, understanding the interplay of negative affect and information processing has been identified as an important area of research in cancer prevention and control (Slovic, Peters, Finucane, & MacGregor, 2005). Several dual-process theories have considered affect as relevant to information processing (e.g., risk as feelings, Loewenstein,

The public is exposed to cancer information in several ways, including interpersonal exchanges (e.g., doctor-patient communication), mass media (e.g., TV public service announcements), and the Internet (e.g., cancer-specific websites). Promoting the effective processing of cancer information (e.g., attention to health information, information seeking) is one strategy for reducing the cancer burden (Hiatt & Rimer, 1999). Processing cancer information is related to participation in cancer-related health behavior (Finney Rutten, Meissner, Breen, Vernon, & Rimer, 2004; Finney Rutten, Nelson, & Meissner, 2004; Shim, Kelly, & Hornik, 2006;

Ellen Burke Beckjord is an Associate Behavioral and Social Sciences Researcher at RAND Corporation. Her work on this manuscript was completed while in the Cancer Prevention Fellowship in the Divisions of Cancer Prevention and Cancer Control and Population Sciences at the National Cancer Institute; Lila J. Finney Rutten, Division of Cancer Prevention, Office of Preventive Oncology, and Division of Cancer Control and Population Sciences, Behavioral Research Program, Health Communication and Informatics Research Branch, National Cancer Institute, National Institutes of Health; Neeraj K. Arora, Division of Cancer Control and Population Sciences, Applied Research Program, Outcomes Research Branch, National Cancer Institute, National Institutes of Health; Richard P. Moser, Division of Cancer Prevention, Office of Preventive Oncology, and Division of Cancer Control and Population Sciences, Behavioral Research Program, Office of the Director, National Cancer Institute, National Institutes of Health; and Bradford W. Hesse, Division of Cancer Control and Population Sciences, Behavioral Research Program, Health Communication and Informatics Research Branch, National Cancer Institute, National Institutes of Health. Correspondence concerning this article should be addressed to Ellen Burke Beckjord, RAND Corporation, 4570 Fifth Avenue, Room 4422; mailstop PA-4 Pittsburgh, PA 15213. E-mail: [email protected] 249

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Weber, Hsee, & Welch, 2001; experiential vs. analytic thinking, Slovic, Finucane, Peters, & MacGregor, 2004; see Epstein & Pacini, 1999, for a review). In these models, affect and cognition are considered as distinct, though mutually influential, systems of information processing. The role of negative affect in information processing has been examined in experimental psychological research as well. There is evidence that types of negative affect, such as anxiety or depression, differentially impact types of information processing, such as attention or understanding (Ellis & Ashbrook, 1988; Gotlib, Neubauer, & Joormann, 2005; MacLeod & Mathews, 1988). Anxiety, fear, and worry are distinct, though closely related, affective phenomena (Borkovec, Alcaine, & Behar, 2004; Borkovec, Robinson, Pruzinsky, & DePree, 1983; for an excellent review in the context of health research, see McCaul & Mullens, 2003) and each has been examined in relation to information processing (e.g., Lench & Levine, 2005; McKay, 2005; Mogg, Mathews, & Eysenck, 1992). Though worry specific to cancer has not been commonly investigated in previous information processing research, cancer worry has been positively and moderately associated with general measures of anxiety (e.g., McCaul, Branstetter, O’Donnell, Jacobson, & Quinlan, 1998); thus, conclusions from studies involving anxiety can be used to inform hypotheses about associations between cancer worry and information processing. A consistent finding across conclusions of previous research is that clinical and subclinical levels of anxiety or anxiety-related affect (e.g., worry) are associated with an attentional bias toward threatrelevant information (Gotlib & MacLeod, 1997; McKay, 2005; Mogg et al., 1992) and disruptions in understanding, problem solving, and decision making (Borkovec, Ray, & Sto¨ber, 1998; Pruzinsky & Borkovec, 1990). For example, individuals with high levels of health anxiety pay more attention to illness-related information than those with lower levels of health anxiety (Owens, Asmundson, Hadjistavropoulous, & Owens, 2004), and in a study of messages about health promotion, participants randomized to a fear-induction exercise had worse recall of health messages than those randomized to a neutral condition (Lench & Levine, 2005). Compared to anxiety, symptoms of depression are less associated with patterns of attention (Mogg & Bradley, 2005),1 though clinical and subclinical levels of depression are associated with understanding or remembering information (Borkovec, Ray, & Sto¨ber, 1998; Ellis & Ashbrook, 1988; Ellis, Thomas, & Rodriguez, 1984). For example, difficulty concentrating is a symptom of major depressive disorder (American Psychiatric Association, 2000), and depressed mood has been shown to interfere with tasks such as prospective memory (Kliegel et al., 2005), learning, problem solving, and reading comprehension (see Hartlage, Alloy, Va´zquez, & Dykman, 1993, for a review).

Present Study In the context of health, research on affect and information processing has rarely examined patterns of association between types of negative affect and information processing, and none have been conducted at the population level. We examined associations between two types of negative affect (cancer worry, symptoms of depression) and two indices of information processing (attention to health information, cancer information-seeking experiences) using

nationally representative data from the 2003 Health Information National Trends Survey (HINTS 2003; Hesse, Moser, Finney Rutten, & Kreps, 2006; Nelson et al., 2004). We hypothesized that cancer worry would be associated with both attention to health information and cancer information seeking experiences (e.g., accessing and understanding cancer information). Specifically, we expected higher levels of cancer worry to be associated with more attention to health information but with worse cancer information seeking experiences. In contrast, we expected symptoms of depression to only be associated with worse cancer information seeking experiences.

Method Data Source Data for this study are from HINTS 2003, a nationally representative survey designed to monitor the impact of the cancer information environment and the public’s knowledge of, attitudes toward, and behaviors related to cancer and cancer prevention biannually (see URL for complete copy of the survey instrument: http://cancercontrol.cancer.gov/hints/). Comprehensive reports on the conceptual framework and sample design are published elsewhere (Hesse et al., 2006; Nelson et al., 2004).

Data Collection, Response Rates, and Sample Data for HINTS 2003 were collected from October 2002 through April 2003. The survey was administered by trained interviewers to a representative sample of American households drawn from all telephone exchanges in the U.S. Exchanges with high numbers of African Americans and Hispanics were oversampled. One adult (age 18 or older) was selected from each household to participate in the full survey during a household screening. Complete interviews were conducted with 6,369 adults (Nelson et al., 2004). The final response rate for the household screener was 55%, and the final response rate for the extended interview was 62.8%. Due to skip patterns embedded in the survey design, respondents with a personal history of cancer (n ⫽ 763; 12% of the total sample) were not asked about cancer worry. Therefore, these respondents were not included in our analyses (study sample n ⫽ 5,589). Further, our analyses of attention to health information included the entire study sample, but only respondents who had ever personally searched for cancer information or who asked someone to search for cancer information for them (n ⫽ 2,627; 47% of the study sample) were asked about information-seeking experiences. Therefore, analyses of experiences with seeking cancer information included only these 2,627 respondents (see Finney Rutten, Squiers, & Hesse, 2006, for a complete report on characteristics of those who did and who did not search for cancer information). 1

Though some research on attentional bias has shown depressed individuals to display increased attention to threat or negative stimuli (Bradley, Mogg, & Lee, 1997; Gotlib et al., 2004), these results are less consistent than those seen in the context of anxiety (Bradley, Mogg, Milar, & White, 1995; Gotlib & MacLeod, 1997), particularly among persons with subclinical depressive disruptions in mood (Gotlib & McCabe, 1992).

INFORMATION PROCESSING AND NEGATIVE AFFECT

Survey Items: Information Processing Attention to health information. Attention was operationalized using five items that asked about attention paid to health information on five media sources: TV, radio, newspapers, magazines, and the Internet (see Shim et al., 2006, for an analysis of these HINTS 2003 items operationalized as “scanning”). Respondents indicated amount of attention paid on a 4-point scale, 1 (not at all) to 4 (a lot). The five attention items had adequate internal consistency (␣ ⫽ .70). The summed score of the five items was used in analyses with higher scores indicating more attention to health information. Information-seeking experiences. Experiences seeking cancer information were assessed using the Information Seeking Experiences Scale (ISEE; Arora et al., 2006). ISEE has six items that assess experiences with attaining and understanding cancer-related information: 1.

You wanted more information, but did not know where to find it.

2.

It took a lot of effort to get the information you needed.

3.

You did not have the time to get all the information you needed.

4.

You felt frustrated during your search for the information.

5.

You were concerned about the quality of the information.

6.

The information you found was too hard to understand.

Respondents indicated agreement with the six statements on a 4-point scale, 1 (strongly disagree) to 4 (strongly agree) regarding their most recent search for cancer information. The six ISEE items had good internal consistency (␣ ⫽ .82). The mean score of the six items was used in analyses with higher scores indicating worse cancer information-seeking experiences.

Survey Items: Negative Affect Cancer worry. Cancer worry was measured using the single item “How often do you worry about getting cancer?” on a 4-point scale, 1 (never) to 4 (all the time). Symptoms of depression. Symptoms of depression were measured using a six-item psychological distress scale borrowed from the National Health Interview Survey, 1997, Adult Core Questionnaire (item ACN.471). Respondents rated the frequency of six depressive symptoms (sadness, nervousness, restlessness, hopelessness, feeling everything is an effort, worthlessness) in the past month on a 5-point scale, 1 (none of the time) to 5 (all of the time). The six distress items had good internal consistency (␣ ⫽ .82). The summed score of the six items was used in analyses with higher scores indicating worse depressive symptoms.

Survey Items: Sociodemographic Characteristics Based on a literature review, variables shown to be associated with either information processing, negative affect, or both were

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entered in multivariate models. These included age, gender, annual income, level of education (Finney Rutten, Arora, Bakos, Aziz, & Rowland, 2005; Shim et al., 2006), race/ethnicity (Breslau, Kendler, Su, Gaziola-Aguilar, & Kessler, 2005; Nguyen & Bellamy, 2006), and family history of cancer (Erblich, Montgomery, Valdimarsdottir, Cloitre, & Bovbjerg, 2003).

Data Analysis Analyses were conducted using Statistical Analysis Software (SAS) Version 9.1 (SAS Institute Inc., Cary, NC) and SAScallable SUDAAN Version 9.0 (Research Triangle Institute, 2004) to account for the complex survey design of HINTS 2003 and to obtain appropriate standard errors and 95% confidence intervals (CIs) for point estimates. Cross-tabulations and bivariate correlations were used to obtain descriptive statistics for information processing and negative affect and their bivariate associations. Mean comparisons (t tests or analyses of variance) were used to examine differences in information processing and negative affect by sociodemographic characteristics. Multivariate analyses used linear regression to model the two indices of information processing separately. These models used a forced-entry method of variable selection wherein sociodemographic characteristics were entered with negative affect (cancer worry and symptoms of depression) in one step. As estimates of effect size for the multivariate analyses, Adjusted R2 and f2 are reported (Cohen, 1993). Responses to survey items classified as “refused” or “don’t know” were counted as missing. Respondents with missing values for relevant variables were excluded from analyses, resulting in sample sizes ranging from 5,589 to 5,173 for analyses involving attention and from 2,627 to 2,148 for analyses involving experiences seeking cancer information.2

Results Descriptive Statistics: Information Processing and Negative Affect Regarding information processing, most respondents reported attention to health or medical topics; over 50% reported some or more attention to health information on TV, newspapers, or magazines. However, many respondents who searched for cancer information reported difficulty with their most recent search: about half or more somewhat to strongly agreed with the statements on the ISEE scale describing difficulty obtaining and understanding cancer information. Regarding negative affect, most people rarely or never worried about cancer; about 40% worried sometimes or more often. Symptoms of depression were also low: only about 30% of the sample reported to feel nervous, fidgety, or that everything was an effort, and less than 20% reported to feel sad, hopeless, or worthless some or more of the time. 2 Given the differences in sample size for analyses of attention and information seeking experiences, a sensitivity analysis was conducted in which the multivariate analysis of attention was repeated with only those participants who were included in the multivariate analysis of information seeking experiences (n ⫽ 2,418). Results regarding associations between attention and negative affect were consistent with the results of the reported analysis using data from the whole study sample (n ⫽ 5,173).

BECKJORD ET AL.

252 Bivariate Analyses

Table 1 shows sample frequencies and associations between categorical study covariates (all covariates except age) and information processing or negative affect (significance tests refer to an overall effect). Our a priori covariate selection was well supported: all sociodemographic variables were significantly associated with information processing and negative affect. Specifically, women reported more attention to health messages and higher levels of negative affect compared to men, and married respondents reported the most attention to health messages, the best experiences seeking cancer-related information, and the lowest levels of depressive symptoms compared to unmarried respondents. Higher levels of education and annual income were associated with more attention to health information, better experiences with information seeking, and less negative affect. Among racial/ethnic subgroups, African Americans reported the most attention to health messages; Hispanic respondents reported the least. White respondents had the most positive experiences seeking cancer information. Asians reported the highest

levels of cancer worry, and Hispanics reported the highest levels of depressive symptoms. Finally, respondents with a family history of cancer paid more attention to health messages, had worse experiences seeking cancer information, and reported more negative affect than those with no family history. Table 2 shows descriptive statistics and bivariate associations between continuous study variables: age, information processing, and negative affect. Age was not associated with information processing; however, older age was associated with lower levels of negative affect. The information processing indices were modestly associated—more attention to health messages was associated with better reported experiences seeking cancer information (r ⫽ ⫺0.04, p ⬍ .05). Further, higher levels of cancer worry were associated with higher levels of depressive symptoms (r ⫽ .21, p ⬍ .01). With respect to the study hypotheses, at the bivariate level, information processing and negative affect were associated in expected ways: higher levels of cancer worry were associated with more attention to health information (r ⫽ .09, p ⬍ .01) and worse information-seeking

Table 1 Descriptive Statistics and Bivariate Associations for Sociodemographic Characteristics, Information Processing, and Negative Affecta Information processingb

Attention Range ⫽ (5–20)

Gender Male Female Marital status Married/partnered Separated/widowed/divorced Single Education ⱕHigh school Some college ⱖCollege Annual income ⬍$25 K $25 K to ⬍ $35 K $35 K to ⬍ $50 K $50 K to ⬍ $75 K ⱖ$75 K Refused/don’t know/missing Race/ethnicity White Hispanic/Latino African American Asian/Pacific Islander Multiple categories or other Family history of cancer Yes No a

N (%)

M (SD)

2,284 (40.87) 3,305 (59.13)

11.30 (.08) 12.68 (.06)

3,055 (56.82) 1,324 (24.62) 998 (18.56)

12.20 (.07) 11.52 (.14) 11.81 (.15)

2,236 (41.58) 1,447 (26.91) 1,695 (31.52)

11.08 (.07) 12.64 (.10) 13.17 (.09)

1,457 (26.07) 687 (12.29) 852 (15.24) 854 (15.28) 1,094 (19.57) 645 (11.54)

11.40 (.11) 11.69 (.18) 11.87 (.14) 12.57 (.16) 12.85 (.12) 11.48 (.20)

3,650 (68.62) 725 (13.63) 664 (12.48) 129 (2.43) 151 (2.84)

12.08 (.08) 11.13 (.14) 12.77 (.17) 12.03 (.53) 11.93 (.33)

2,949 (52.89) 2,627 (47.11)

12.23 (.08) 11.65 (.11)

pd

Negative affectb Information seeking experiencesc Range ⫽ (6–24) M (SD)

⬍ .01 ⬍ .01

⬍.01

⬍.01

⬍.01

p

Cancer worry Range ⫽ (1–4) M (SD)

2.33 (.02) 2.49 (.04) 2.43 (.05) 2.55 (.03) 2.34 (.03) 2.21 (.03) 2.52 (.04) 2.44 (.06) 2.44 (.05) 2.34 (.04) 2.20 (.04) 2.38 (.06)

⬍ .01

⬍.01

⬍.01

⬍.01

2.33 (.02) 2.56 (.06) 2.43 (.07) 2.58 (.11) 2.36 (.09) ⬍.01

1.49 (.03) 1.60 (.02)

1.61 (.03) 1.47 (.02) 1.47 (.02) 1.69 (.04) 1.48 (.03) 1.50 (.03) 1.48 (.02) 1.48 (.03) 1.55 (.07)

⬍.01

⬍.01

⬍.01

1.48 (.01) 1.89 (.09) 1.49 (.04) 1.75 (.15) 1.48 (.08)

10.22 (0.08) 11.40 (0.18) 11.39 (0.19) 11.26 (0.12) 10.59 (0.13) 9.51 (0.08) 12.22 (0.16) 10.89 (0.20) 10.61 (0.17) 9.73 (0.14) 9.33 (0.10) 10.74 (0.28)

c

⬍.01

⬍.01

⬍.01

⬍.01 10.81 (0.09) 10.40 (0.11)

Percentages were calculated as percent of total sample size (5,589) for each subcategory; due to missing values not all categories sum to 5,589. Higher scores indicate more attention, worse experiences with cancer information seeking, and more cancer worry or symptoms of depression. Only those who reported to search for cancer information (self or proxy) were asked about information seeking experiences (n ⫽ 2,627). d Significance value refers to t test results for dichotomous variables and to ANOVA results for covariates with n ⬎ 2 categories. b

⬍ .01

10.27 (0.07) 11.75 (0.22) 11.49 (0.27) 11.19 (0.40) 11.40 (0.52) .07

1.58 (.01) 1.50 (.04)

p ⬍ .01

10.27 (0.10) 11.02 (0.08) .73

1.55 (.02) 1.51 (.04) 1.53 (.05)

⬍.05 2.39 (.02) 2.31 (.04)

M (SD)

⬍ .01

.16 2.34 (.03) 2.39 (.02)

p

Symptoms of depression Range ⫽ (6–30)

INFORMATION PROCESSING AND NEGATIVE AFFECT

253

Table 2 Descriptive Statistics and Bivariate Correlations Between Age, Information Processing, and Negative Affect Information processinga 1. Age 1 2 3 4 M (SD) a *

46.39 (.69)

Negative affecta

2. Attention to health information

3. Information-seeking experiences

4. Cancer worry

5. Symptoms of depression

⫺.00

⫺.01 ⫺.04*

⫺.03* .09** .14**

12.00 (.05)

2.37 (.02)

1.55 (.02)

⫺.05** .01 .21** .21** 10.65 (.07)

Higher scores indicate more attention, worse experiences with cancer information seeking, more cancer worry or symptoms of depression. Bivariate correlation coefficient significant at p ⬍ 0.05. **p ⬍ 0.01.

experiences (r ⫽ .14, p ⬍ .01). More symptoms of depression were associated with worse information-seeking experiences (r ⫽ .21, p ⬍ .01), but not with attention.

Multivariate Analyses Table 3 displays the results of multivariate regressions where attention to health information and information-seeking experiences were modeled separately. In the multivariate analyses our hypotheses were supported: in the model of attention to health information, higher levels of cancer worry were significantly associated with more attention to health messages after adjustment for relevant

sociodemographic variables ( p ⬍ .01), but symptoms of depression were not. Female gender, higher level of education, and greater annual income were also associated with more attention to health information. Further, married respondents reported more attention to health information than those separated, divorced, or widowed. Finally, compared to White respondents, African Americans reported more attention to health information and Hispanics/Latinos reported less. In contrast to the model of attention, higher levels of cancer worry ( p ⬍ .05) and more depressive symptoms ( p ⬍ .01) were both associated with worse information-seeking experiences. In addition, lower levels of education were associated with worse

Table 3 Multivariate Linear Regressions for Attention to Health Messages and Information Seeking Experiences (ISEE) Attention to health informationa,b Model Adj. R2 ⫽ 0.13; f2 ⫽ 0.15 Unstandardized B a

Cancer worry Symptoms of depressiona Age Gender Attention: ␹2 1df ⫽ 169.61, p ⬍ 0.01 ISEE: ␹2 1df ⫽ 0.00, p ⫽ 0.99 Marital status Attention: ␹2 2df ⫽ 7.84, p ⬍ 0.05 ISEE: ␹2 2df ⫽ 0.49, p ⫽ 0.74 Education Attention: ␹2 2df ⫽ 214.03, p ⬍ 0.01 ISEE: ␹2 2df ⫽ 21.05, p ⬍ 0.01 Annual income Attention: ␹2 5df ⫽ 21.23, p ⬍ 0.01 ISEE: ␹2 5df ⫽ 7.31, p ⫽ 0.16

Race/ethnicity Attention: ␹2 4df ⫽ 39.54, p ⬍ 0.01 ISEE: ␹2 4df ⫽ 8.61, p ⫽ 0.06 Family history of cancer Attention: ␹2 1df ⫽ 2.07, p ⫽ 0.15 ISEE: ␹2 1df ⫽ 6.80, p ⬍ 0.01 a b

Male (ref) Female Married/partnered (ref) Separated/widow/divorced Single ⱕHigh school (ref) Some college ⱖCollege ⬍$25 K (ref) $25 K to ⬍$35 K $35 K to ⬍$50 K $50 K to ⬍ $75 K ⱖ$75 K Refuse/don’t know/missing White (ref) Hispanic/Latino African American Asian/Pacific Islander Multiple categories/other No (ref) Yes

p

Information-seeking experiencesa,b Model Adj. R2 ⫽ 0.09; f2 ⫽ 0.10 Unstandardized B

p

.47 .03 .00

⬍.01 .08 .59

.08 .02 .00

⬍.05 ⬍.01 .29

1.34

⬍.01

.00

.99

⫺.57 ⫺.18

⬍.01 .30

.04 .01

.38 .79

1.33

⬍.01

⫺.17

⬍.01

1.84

⬍.01

⫺.23

⬍.01

.05 .15 .66 .63 ⫺.28

.78 .41 ⬍.01 ⬍.01 .28

⫺.01 .02 ⫺.01 ⫺.12 .05

.89 .75 .82 .05 .54

⫺.36 1.09 ⫺.51 .42

⬍.05 ⬍.01 .16 .22

.12 .02 .27 ⫺.06

.06 .78 ⬍.05 .53

.20

.16

.11

⬍.05

Higher scores indicate more attention, worse experiences with cancer information seeking, more cancer worry or symptoms of depression. n ⫽ 5,173 for the model of attention to health information; n ⫽ 2,148 for the model of information-seeking experiences.

BECKJORD ET AL.

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experiences seeking cancer information, as was reporting a family history of cancer. Finally, Asian/Pacific Islander respondents reported marginally worse information-seeking experiences compared to Whites. Though statistically significant, it should be noted that the magnitudes of association between negative affect and information-seeking experiences were small; thus, these results should be interpreted with some caution.

Discussion Negative affect was associated with the two indices of information processing considered in this study, and types of negative affect operated in different ways. Consistent with previous research, cancer worry was positively associated with attention to health information (e.g., Owens et al., 2004). However, both cancer worry and symptoms of depression were associated with a worsening sense of success in searching for cancer-related information. That is, those experiencing higher levels of negative affect commonly associated with cancer had the most difficulty with their attempts to access, obtain, and understand cancer information. This finding emphasizes the debilitative role that negative affect can play on the perceived efficacy of information-seeking behaviors— behaviors that are increasingly becoming essential in a health system that depends on active patient self-management (Hesse & Shneiderman, in press; Nelson, Stefanek, Peters, & McCaul, 2005; Wagner et al., 2005). In general, attention to health information was relatively high among American adults, likely reflecting the prevalence of health information available via the mass media channels queried in HINTS (Viswanath, 2005). Promoting attention to health information is important, given its association with positive health behaviors (e.g., Shim, Kelly, & Hornik, 2006; Seligman, Rashid, & Parks, 2006). Conversely, cancer information-seeking among American adults was relatively low (47%), and for those who sought cancer information, suboptimal search experiences were common. Given this finding and the observation that the public is being increasingly called upon to take an active role in obtaining and processing information relevant to their health (Cayton, 2006; Institute of Medicine [IOM], 2004), continued research is needed not only to identify determinants of searching for cancer information (e.g., Finney Rutten, Squiers, & Hesse, 2006; Ramanadhan & Viswanath, 2006), but also on how to improve the public’s cancer information-seeking experiences. Our results highlight negative affect as important to consider in strategies aimed at improving the public’s experience of the cancer information environment. Though decreasing negative affect at the population level is not always a feasible strategy for improving the public’s cancer information-seeking experiences, determining ways to minimize negative affect specifically associated with cancer communication may be. For example, recent health communication research has examined the effect of interventions on negative affect in cancer-related areas. Results have suggested that interpersonal, communication-based interventions can facilitate information processing and decrease negative affect among those at genetic risk for cancer (Miller et al., 2005). The use of new eHealth interventions to provide avenues of ongoing informational and emotional support offer a promising population-level approach to decreasing negative affect and facilitating processing of cancer communication (Gustafson, McTavish, Stengle, Ballard, Hawkins,

et al., 2005; Gustafson, McTavish, Stengle, Ballard, Jones, et al., 2005). Finally, theory-driven work on the Risk Perception Attitude framework (Rimal & Real, 2003) suggests that promoting health self-efficacy may minimize distress associated with health risks and facilitate processing of health information (Rimal & Real, 2003; Turner, Rimal, Morrison, & Kim, 2006). Though previous studies have mostly focused on anxiety in relation to health information processing (e.g., McKay, 2005; Owens et al., 2004; Turner et al., 2006), we found evidence that symptoms of depression may play a role as well. Further, cancer worry and symptoms of depression were moderately associated (r ⫽ .21; p ⬍ .01), and given the high rate of comorbidity between anxiety and depression (American Psychiatric Association, 2000), future studies investigating affect in relation to health information processing should examine both anxiety- and depression-related symptoms. Though the generalized assessment of negative affect in HINTS lacks the precision optimal for testing an interaction between cancer worry and symptoms of depression (Aiken & West, 1991), in future studies that employ more thorough measures, examining this interaction may further a more comprehensive understanding of relationships between negative affect and health information processing. Though not the focus of this study, it is worth noting that our results also describe associations between information processing and sociodemographic covariates. For example, more years of education were associated with more attention to health information and better experiences with cancer information seeking, suggesting that education is associated with greater awareness and understanding of cancer communication. This finding supports the need for continued research on disparities in access to cancer information (Viswanath, 2005) and health literacy (IOM, 2004). More in-depth discussions of sociodemographic variables in relation to information processing and negative affect in HINTS 2003 can be found elsewhere (Arora et al., 2006; Cerully, Klein, & McCaul, 2006; Han, Moser, & Klein, 2006; Moser, McCaul, Peters, Nelson, & Marcus, 2007; Shim et al., 2006; Viswanath et al., 2006; Zajac, Klein, & McCaul, 2006). This study expands on traditional levels of analysis in health psychology to provide an investigation of associations between negative affect and information processing in the general population using a nationally representative dataset. This expansion, from an individual- to a population-level of analysis, has been identified as a hallmark of the next era of behavioral research in health (Smith, Orleans, & Jenkins, 2004). Nevertheless, use of HINTS to examine information processing and negative affect has limitations as well. In using a crosssectional survey, we are unable to draw conclusions about causal relationships between information processing and negative affect. The generalizability of our results may be limited given the relatively low survey response rates of HINTS 2003; however, HINTS response rates are comparable to those of other national random digit dial surveys (Nelson, PowellGriner, Twon, & Kovar, 2003). There are limitations to our measurement of negative affect and information processing: given the retrospective, generalized nature of the survey, with more thorough measures of negative affect our results may have differed; however, our findings regarding information processing are consistent with research that has used mood induction to

INFORMATION PROCESSING AND NEGATIVE AFFECT

generate negative affect (e.g., Lench & Levine, 2005) and with studies that have used more comprehensive affective measures (McKay, 2005). Compared to studies that used computerized tasks to assess attention based on response latency measured during experimental tasks of stimulus recognition (e.g., Glinder, Beckjord, Kaiser, & Compas, 2007; Owens et al., 2004), the self-report methodology used in HINTS is a far less sensitive measure of attention. Finally, the negative wording of items in the ISEE scale (e.g., felt frustrated, were concerned) could account for some of the observed association between information seeking experiences and negative affect.

Conclusions With the proliferation of health information available via mass media channels, a population-level assessment offers an important perspective on how negative affect commonly associated with cancer is associated with health information processing. Information plays a vital role in promoting public health; given the fast pace of scientific advances in cancer prevention and control, information availability is not a limiting factor so much as information processing is. To achieve a maximum impact of information on health behaviors and outcomes, we must continue to identify strategies for promoting successful engagement with and processing of available cancer information. Negative affect has long been a focus of intervention in cancer survivorship research (Bultz & Carlson, 2006). Our results contribute to growing evidence that negative affect has important implications for cancer information processing as well.

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