A content analysis was designed and conducted for this study to determine the representation and overall role of elderly people in prime time television commercials. The sample was drawn from one week of nightly broadcasts from 8:00 PM until 11:00 PM, taken from four major networks: ABC, CBS, NBC, and Fox, yielding a total of 60 hours of programming. This pool was recorded during the November 1994 sweeps, in the three week window between the end of political ad campaigns and Thanksgiving, which signals the start of Christmas advertising. From this population, a sample was drawn by randomly choosing a broadcast date, then coding the programming shown on each network for the given time slots. Swayne and Greco (1987) coded 36 hours of network programming for a total of 814 commercials; a smaller study of approximately 300 commercials was used here.
The unit of analysis was the individual character or actor appearing in each ad. As suggested by Swayne and Greco, body parts or bodies without faces were not counted; however, close-up shots of faces with incomplete bodies were counted. Each individual with a discernible face was coded for gender, race and age group categories. Elderly characters were coded for role emphasis, and the type of product being advertised and locale of the commercial was noted. Ads containing discernible faces were then analyzed for presence of elderly characters. “Elderly” was defined as appearing age 65 or older. Following subjective criteria established by Swayne and Greco (1987), among others, characters were defined as elderly if they appeared within a context suggesting retirement, if their hair color was primarily gray or white, if they had skin wrinkles apparent in the face and hands, if they used ambulatory aids (canes, walkers or wheelchairs), hearing aids or obvious bifocal glasses, and if they appeared with or displayed evidence of middle-aged children or grandchildren. Gender categories were defined as male and female.
Age group categories were defined as follows:
1. 0 – 17 years = young (child, adolescent or late teen years).
2. 18 – 64 years = adult (parent, homeowner, position of authority).
3. 65 and up = elderly (as above).
When examining the broad category of race, it becomes next to impossible to assign such a wide variety of social identifiers to one overarching term. For example, those who initially fall into the African-American category may actually be of South American or Caribbean origin. Similarly, those classified as Hispanics may be from Cuba, Puerto Rico, Mexico, South America, Portugal, Spain, or even Italy. In the researcher’s limited observation capacity, it is not possible to question the subjects appearing in the ads, which prevents precise definition in almost every case. In view of these difficulties, the term culture group was chosen, in order to sort subjects into generalized but more socially accurate descriptions, for the purposes of data analysis.Culture group categories were defined as:
1. White = Anglo/European, fair-skinned.
2. African American = distinguished by dark skin color.
3. Hispanic = distinguished by medium/olive skin tone, audible accent or Hispanic surname.
4. Other visible minority = (Asian, Native American, etc.) distinguished by accent, dress, skin color, facial features
Role emphasis was defined as:
1. Major role = elderly person functions as main character or spokesperson, appears on camera throughout the ad and has a speaking role.
2. Minor role = elderly person speaks seldom or not at all, remains on screen for less than half the duration of the ad, or appears in a supporting role to the major characters.
3. Background role = one in which the elderly person appears more or less as scenery, with no speaking part and a fleeting appearance on camera, such as in a sweeping camera pan or wide shot of scene.
Negative stereotypes of the elderly frequently place them in home settings, or in hospitals, doctors offices and retirement facilities. By examining the locale of the commercial, one can determine whether the elderly appear in stereotypical settings, or whether they are shown with economic clout in retail or business scenes, for example. Similarly, one can determine whether elders are seen as reclusive or sedentary by observing appearances in recreational/social settings.Locale was coded by determining the apparent location for the ad:
1. Home setting = a room in a house, domestic scenery.
2. Recreational/social setting = indoor locations include parties, sporting events, movies or theater, restaurants or lounges, health clubs, K of C or Elks lodges, and the like. Outdoor locations include parks, yards, natural outside settings or any outside location featuring grass, trees, or water.
3. Professional/corporate setting = indoor locations would include retail stores, factories or service-oriented businesses, offices or boardrooms, airports, anyplace involving meetings, charts, briefcases and business suits. Outdoor locations include any downtown/exterior office building setting, inside a limousine or airplane, construction site, or any outdoor business ventures.
4. Health care setting = this very specific category includes any setting in which the elderly appear as patients or as receivers of health care, advise, or information, or where an elderly character is voicing a complaint. Scenes portraying elderly characters as doctors, nurses or any health care provider would be coded as professional. This is intended to examine the previously-reported image of elderly as sickly or frail.
5. Other setting = any other location not described here.
As suggested by Moore and Cadeau (1985), the product types were broken down into five broad categories: food items, major purchases, household goods, hygiene and health aids, and beauty/appearance enhancing products. These category divisions yielded some interesting data regarding negative stereotypes of aging, including subtext messages equdtitigage with ugliness, illness, poverty, and sedentary lifestyles.The product categories were defined as follows:
1. Food items = including grocery items, candy, alcoholic and non-alcoholic beverages.
2. Major purchases = including furniture, cars, vacations, homes, insurance, computers, audio/video equipment, recreational vehicles, investment products (stocks, CD’s) and other big ticket items. (ex: diamond anniversary jewelry).
3. Household goods = including home or car cleaning products, videos, compact discs or tapes, clothing, personal accessories (beepers, radar detectors, Walkman-type personal tape players) small sporting goods, (golf balls, tennis shoes), or entertainment purchases such as Nintendo-type video games, home video rentals or movie theater tickets.
4. Hygiene/health aids = including soap, personal cleansers, denture care items, laxative, vitamins, nutritional or diet supplements (such as Ensure or Susta-Cal), cold remedies, over-the-counter pain relievers, prescription drugs, hearing aids (like Whisper 2000 or Beltone) eye care including bifocals, radial-keratotomy or laser cataract surgery ads, ambulatory aids including canes, walkers, wheelchairs, Craftmatic beds and lift-chairs, digestive aids (Mylanta, Turns), bladder control products and any other personal care products not related to superficial or appearance needs.
5. Beauty/appearance enhancing products = including perfumes, creams, moisturizers, hair removers or replacements, hair care products including shampoos and hair colors.
Therefore, the proposed categories of analysis were listed as follows:
1. Total number of characters in commercial (up to 10).
2. Number of elderly characters in commercial.
3. Age group of each character in commercial.
4. Culture group of each character in commercial.
5. Role emphasis of elderly characters in commercial.
6. Locale or setting of commercial.
7. Type of product being advertised.Coders received instruction with regard to the coding process, observation, and completing the coding sheet. A pilot study drawn from one hour of programming was conducted to determine the effectiveness of the coding process and to check coding form definitions. The reliability coefficient was found to be .91 based on the completed coding forms from the pilot study. Having tested the coding procedure and form, the actual study did commence with two initial coders. The researcher attempted to ensure reliability by carefully and clearly defining category boundaries and instructing the coders accordingly.