NATIONWIDE NEWSPAPER

COVERAGE OF ALTERNATIVE

MEDICINE:A COMMUNITY STRUCTURE

APPROACHTeegan Conti

Maria MontroniJenny Smith

Introduction

•2002 National Health Interview Survey:

•Over one third of adults in the United States are using some form of Complementary and Alternative medicine (CAM).

•Alternative medicines, unlike many prescription drugs, have no specific target audience.•Overall goal is to attain a healthy lifestyle.

Research Questions

•Do cities with higher percents of college educated citizens offer more favorable coverage of CAM?

•Will cities with high proportions of families with incomes upwards of $100,000 exhibit more favorable coverage of CAM?

Research Questions

•Will cities with a large 18-30 population show more favorable coverage to CAM?

•Will cities with a higher percent of voting Republicans display less favorable coverage of CAM?

Framing in Newspapers•Newspapers read by economic and political leaders•Newspaper readers active in their communities•Well suited for systematic coding and analysis•Leads to higher predictability and reliability in results•More community/regionally focused than internet; more in-depth than TV news

The Community Structure Approach

Definition: Structural approaches linking community context to reporting on critical events have been pioneered by Tichener, Donohue, & Olien (1973-1980) McCleod & Hertog (1990, 1992, 1999), Demers & Viswanath (1999), & Hindman (1996, 1999). The “Community Structure Approach,” extensively tested in a nationwide sample by Pollock and colleagues (1977, 1978, 1994-2004) has consistently shown relations between structural characteristics of U.S. cities and newspaper coverage of political and social change.

Alternative Approach: Complements explanations for news coverage based on such conventional factors as attitudes/personalities of journalists, newsroom diversity (ethnicity, gender) or newspaper ownership patterns.

Literature Review

Extensive research on CAM in biology, psychology, and business databases.

Very little research on CAM in field of communication

– ComAbstracts and Communication & Mass Media Complete

– Search term “Alternative Medicine” combined with “media,” and “‘news coverage”

– Yielded five articles total in CMMC, zero articles in ComAbstracts.

Buffer Hypothesis•According to Pollock & colleagues, the “buffer” hypothesis expects that the larger the proportion of privileged groups in a city, (privilege defined as portion of those in a city with college educations, family incomes of $100,000 or more, or professional/technical occupational status), the more favorable the coverage of CAM.

H1: The higher the percentage of college educated citizens in a city, the more favorable the coverage of CAM (Lifestyle Market Analyst, 2007).H2: The higher the percentage of families with incomes of $100,000 or more in a city, the more favorable the coverage of CAM (Lifestyle Market Analyst, 2007).H3: The higher the percentage of people with professional or technical status in a city, the more favorable the coverage of CAM (Lifestyle Market Analyst, 2007).

Healthcare Access Hypothesis

•Research (on topics such as physician-assisted suicide and stem-cell research) has shown a positive relationship between the proportion of physicians in a given community or percentage of municipal spending on healthcare and favorable newspaper coverage on advances in medicine, science and healthcare (Pollock & Yulis, 2004).

H4: The higher the percentage of municipal spending on healthcare in a city, the more favorable the coverage of CAM (Lifestyle Market Analyst, 2007).

 

H5: The higher the percentage of physicians/100,000, the more favorable the coverage of CAM (County and City Extra, 2007).

Vulnerability Hypothesis•Also termed the “unbuffered” or “guardian” hypothesis, it expects that the larger the percent of people in a city living under the poverty level, or unemployed, the more newspapers will reflect the interests of these groups (Pollock, 2007, p. 56).•Previous research using the community structure approach indicates a correlation between the portion of city residents below the poverty level and favorable coverage of a Patients’ Bill of Rights (Pollock, 2007, p. 256).

H13: The higher the percentage below the poverty level, the more favorable the coverage of CAM (Lifestyle Market Analyst, 2007).

 H14: The higher the percentage unemployed, the more favorable the coverage of CAM (County and City Extra, 1999).

Stakeholder HypothesisPrevious research suggests that when a “stakeholder,” or large groups with a stake in a particular social or political issue, emerges in a given community, newspapers tend to increase coverage of that issue. (Mcleod & Hertog, 1999). This finding is supported by studies of same sex marriage (Pollock & Dantas, 1998) and physician assisted suicide (Pollock & Yulis, 2004).•Stakeholders for CAM can be grouped into the following categories: 1. Position in the life cycle2. Age/Generation3. Belief System4. Political Partisanship

Methodology

•Cross-section national sample of 21 newspapers.

•The NewsBank database was used to collect articles of 150 words or more from the sample period January 1, 2002, to January 1, 2008.

•All articles were coded for Prominence and Directional coverage.

Prominence Score*Direction 4 3 2 1

Placement Front page of first section

Front page of inside section

Inside page of first section

Other

Headline Size (# of words)

10+ 8-9 6-7 5 or fewer

Article length (# of words)

1,000 + 750-999 500-749 499 or fewer

Photos/Graphics

2 or more 1

* copyright John C. Pollock, 1994-2008

Article DirectionArticles coded favorable:

Positive coverage of CAM; showed general support for various forms of

alternative medicineArticles coded unfavorable:

Negative coverage of CAM; opposed various forms of alternative medicineArticles coded balanced/neutral:Presented both sides of the argument

objectively; reported general information regarding CAM

Media Vectorf = sum of the prominence scores coded “favorable”

u = sum of the prominence scores coded “unfavorable”n = sum of the prominence scores coded “balanced/neutral”

r = f + u + nIf f > u (the sum of the favorable prominence scores is greater than the

sum of the unfavorable prominence scores), the following formula is used:

Favorable Media Vector (FMV):FMV = (f² - fu) (Answer lies between 0 and

+1.00) r²

If f < u (the sum of the unfavorable prominence scores is greater than the sum of the favorable scores), the following formula is used:

Unfavorable Media Vector (UMV):UMV = (fu - u²) (Answer lies between 0 and -

1.00) r²

*Media Vector copyright John C. Pollock (2000-2008)

Results: Media VectorCity, State Newspaper

Media Vector

Kansas City, MO Kansas City Star 0.933

Manchester, NH New Hampshire Union Leader 0.7287

Milwaukee, WI Milwaukee Journal Sentinel 0.4498

Denver, CO The Denver Post 0.4439

Portland, OR The Oregonian 0.4008

Phoenix, AZ Arizona Republic 0.3331Albuquerque, NM Albuquerque Journal 0.333

Columbus, OH Columbus Dispatch 0.2655

Albany, NY The Times Union 0.2513New Orleans, LA

The New Orleans Time-Picayune 0.2206

City, State Newspaper Media Vector

Chicago, IL Chicago Sun-Times 0.2188

Orlando, FL Orlando Sentinel 0.2118

Tulsa, OK Tulsa World 0.1712

St. Petersburg, FL St. Petersburg Times 0.1278

St. Louis, MI St. Louis Post-Dispatch 0.1263

Bismarck, ND The Bismarck Tribune 0.0984

San Francisco, CA San Francisco Chronicle 0.0495

Pittsburgh, PA Pittsburgh Post-Gazette 0.0272

Richmond, VARichmond Times Dispatch -0.0042

Salt Lake City, UT

The Deseret Morning News -0.0481

Boston, MA The Boston Globe -0.187

Regional Media Vector Averages

Region Media Vector

Midwest .3486

West .2520

Northeast .2051

Southeast .1454

Scott’s Pi Average: 77.2135

Pearson Correlation

•A Pearson Correlation exemplifies the relationship between a particular city characteristic and the media vector. For instance, if a Pearson Correlation is positive, that city characteristic correlates with a favorable outlook of Alternative Medicine.

•Results are not considered relevant unless they prove to be significant at the .05 level or better.

Results: Pearson Correlations

City Characteristic (%) Pearson Correlation

Significance

Municipal Spending on Healthcare .407 .034*

Family Income $100,000+ .399 .037*

Unemployed .405 .043*

Generation 25-44 -.393 .043*

Generation 45-64 -.376 .051

Generation 18-24 -.355 .062

Children 11-14 .306 .095

Children 15-19 .251 .142

Physicians per 100,000 -.238 .150

Generation 65+ -.224 .171

* = Significant at the .05 level

City Characteristic (%)

Pearson Correlation

Significance

Professionals .211 .180

Catholics -.212 .192

College Educated .193 .201

Children 5-10 .193 .208

Below Poverty .158 .252

Protestants -.149 .271

Children under 5 -.107 .327

Democratic .078 .369

Republican -.064 .391

Devotional Reading -.026 .458

Evangelicals .014 .477

Results: Regression

Model R

R Squar

e

R Square Change

F Change

Sig. F Change

Generation 25-44 .434 .188 .188 3.480 .082

Generation 25-44, Income

.620 .384 196 4.461 .053

Generation 25-44,

Income, Generation

45 - 64

.758 .575 .190 5.814 .031

Regression: Top Predictors

•Generation 25-44•Income over $100,000•Generation 45 - 64

Results: Hypotheses•Healthcare Access (confirmed): The higher the percentage of municipal spending on healthcare in a city, the more favorable the coverage of CAM. •Buffer (confirmed): The higher the percentage of families with incomes of $100,000 or more in a city, the more favorable the coverage of CAM.•Vulnerability (confirmed): The higher the percentage unemployed, the more favorable the coverage of CAM.•Age/Generation (confirmed): The higher the percentage of residents 25-44 in a community, the less favorable the coverage of CAM.

Implications for Further Research

•Examine frequency of newspaper coverage of CAM•Compare cross national newspaper coverage to national newspaper coverage of CAM•Compare international newspaper coverage to national newspaper coverage of CAM•Re-examine CAM coverage post Presidential election 2008•Analyze the coverage of CAM in other forms of media (TV, radio, Internet)•Specify categories of Alternative Medicine (yoga, acupuncture, herbal remedies, etc.)