Abstract

Introduction

Methodology

References

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Image of the Nurse on Internet Greeting Cards

Sheryl Pierce, Karolyn Grodal, Linda S. Smith, Shannon Elia-Tyvoll,
Aaron Miller, Crystal Tallman

And

Nursing 470: Research in Nursing Practice Class Members
OHSU School of Nursing, Klamath Falls Campus
Research Advisor: Linda S. Smith, MS, DSN, RN


Abstract

Purpose:   To describe the image of the nurse as demonstrated on Internet greeting cards.

Problem/Significance:   The image of the nurse as found on greeting cards can be problematic if that image is deprecating, offensive, and unrealistic. The authors found no published studies related to the image of the nurse on Internet greeting cards.
Ho: There is no difference between reality and the image of the nurse on Internet greeting cards. 

Theory:   King’s Theory of Goal Attainment provided theoretical foundation. Perception patients have about the nurse will impact the relationship.

Methodology:

Setting:  World Wide Web/Internet

Design:  Descriptive survey, cross-sectional sampling. An original Greeting Card Analysis Tool (GCAT) was developed, piloted, and successfully implemented.

Data Analysis:  Unstructured data were quantified using content analysis. Descriptive and Chi Square statistical analyses were used. Three trained student-raters evaluated each of the 101 units with 88% inter-rater reliability.

Results:  The Internet greeting card nurse image was generally incongruent with reality.

Recommendations:  Political strategies need to create a more realistic image and portrayal of nurses and nursing.

Introduction 

The senior nursing class of Oregon Health & Science University (OHSU) in Klamath, Falls, Oregon, completed a class project to examine nursing’s image on the Internet. During spring term, five of these students agreed to complete the study.

Problem Statement

The image of the nurse on Internet greeting cards impacts the nurse-patient relationship and the relationship nurses have with other professionals. This image may influence communication with and perception of the nurse and thus impact patient care goals and outcomes.  The research problem can be investigated through the collection of Internet greeting cards that pertain to nursing.

Purpose

The purpose of this investigation was to describe the image of the nurse on Internet greeting cards. The setting of the study was the Internet and units of measure were Internet greeting cards.

Significance

Images portrayed on the Internet may affect the public’s view or image of the nurse, which may affect relationships and interactions with these persons. Therefore, nurses want the most realistic image of the nurse to be presented.  If realistic images of the nurse were presented on the Internet, then a more fulfilling nurse-patient relationship may be promoted. Thus, it is in nursing’s interest to review and describe portrayed images.

The image of the nurse as found on Internet greeting cards can be problematic if the view is derogatory. This becomes troublesome when the view of the nurse is different from the portrayed image visualized by patients nurses have contact with. It is possible for misunderstanding by either nurses or patients, resulting in poor outcomes. No published studies were found regarding nursing’s Internet image.

Hypothesis:

Ho:  There is no difference between reality and the image of the nurse as portrayed on greeting cards found on the Internet.

Theoretical Framework

King’s Theory of Goal Attainment

In her Theory of Goal Attainment, King proposed the focus of nursing is the care of human beings resulting in the health of individuals and groups.  These groups are viewed as open systems in constant interaction with their environment.  King believed that individuals actively interact with others as a result of prior experiences. King’s theory is reflected in the nursing process of perception, judgment, action, reaction, interaction, and transaction (King, 1992, 1997, 1999).

“The greater the degree of perceptual congruency between nurse and patient related to the illness situation and nursing care required, the greater the degree of goal attainment or satisfaction with nursing care” (King, 1997, p.182).  Perceptions patients have about the nurse will impact the way the nurse is viewed by that patient.  “Events inferred from one’s perceptions give meaning to a person’s experiences and represent an individual’s image of the real world” (King, 1999, p. 293).

Definition of Terms

Greeting card:  a card sent to express personal greetings (i.e.: get well, nursing day, thanks, humor, etc.).

Image:  a visual or mental representation of a person, thing, or idea.

Internet:  an electronic communications network that connects computer networks worldwide.

Perception:  an act of awareness obtained through the senses, particularly sight or hearing.

Nurse:  a post-secondary health care provider who performs the duty of the nurse as defined by the region in which he/she practices.

Unit:  The term used to identify a located Internet greeting card containing with a nurse image. For this study and because greeting cards are not human, the term “subject” is replaced with unit.

Assumptions

1.      There is a relationship-building process between nurse and patient and that relationship is based on perceptions.

2.      There is a negative impact on this relationship between nurse and patient when perceptions do not match reality.

3.      When an individual views an Internet greeting card, the image enters the individual’s perceptions.

4.      There is accurate identification of the image of the nurse based on the Greeting Card Analysis Tool (GCAT) developed for this purpose (Appendix A).

Limitations

1.      The Internet is vast and in constant change; therefore, all perspective images may not be accessed for analysis.

2.      When analyzing images, the data may be subjective individual perceptions. 

3.      Language and cultural barriers may influence study results

Literature Review

Kalisch and Kalisch found that the image of the nurse had been portrayed both positively and negatively in motion pictures, novels, and television.  Importantly, nurses were positively portrayed during wartime. During World War I and World War II, nurses were shown as having traits of heroism, good moral/ethical behaviors, and dedication (1982a,b,c,d; 1983).

Negative images of the nurse began after WWII and persist today. Media have portrayed nurses as predominately female, performing mindless tasks. During the 1960s-1970s, nurses were often portrayed as sex symbols (Kalisch & Kalisch). The lack of recent investigation on nursing’s media image reinforces the need for further scientific research in this area.

Only a few published studies relate to greeting card images.  Dillon and Jones (1981) found that elders portrayed on greeting cards were negative and stereotypical.  Peloquin (1991) found that images on greeting cards were persuasive to the audience and capable of providing subconscious impact. Finn (1980) found that alcohol use portrayed on greeting cards was promoted through humorous themes. 

Methodology

Setting

The Internet, and within it the worldwide web, is a vast network of computer servers that host information at specific addresses known as websites.  Websites have units of electronic memory, where files and programs of various types are stored (Muller, 1999). Goods and services (such as electronic greeting cards) have become accessible with minimal or no charge to Internet end users.  Like goods within more tangible markets, electronic media (such as greeting cards) reflect society’s values, norms, perceptions, and humor (Helmstetter, 1997). For minimal cost, student researchers collected greeting cards from the Internet, using school facilities.

Units

The units for this study were Internet greeting cards conceptualizing nursing. For the initial pilot study and subsequent research investigation, a cross-sectional sample of greeting card units were collected using a meta Internet search engine called Metacrawler  (www.metacrawler.com). 

Design

The question: “What is the image of the nurse on greeting cards, as found on the Internet?” For consistent and reliable data analysis, quantification of data was conducted using content analysis techniques. Content analysis describes and organizes characteristics of message content into meaningful analyzable groups (Polit & Hungler, 1999). Coder training ensures consistency (Waltz, Strickland, & Lenz, 1991).

Tool Development, Pilot Study

A greeting card analysis tool (GCAT) was developed based on existing content image categories identified in image research literature. The GCAT was presented to 18 senior nursing students who provided suggestions and recommendations; two doctorally prepared, research-experienced nurses also critiqued the tool.

Ten randomly chosen units were used for pilot study. Three raters evaluated each unit independently. GCAT was found to be an effective instrument. However, clear and specific rater training was deemed important to reduce bias.

Ethical clearance was not required because Internet greeting cards are publicly available and displayed.  No animal or human subjects are involved in the study.

Data Collection for Research Investigation

Two groups of three researchers collected units on two consecutive conducted data gathering and printing in the Computer Learning Center at Oregon Institute of Technology. Each researcher used MetaCrawler because that search engine combines 13 different search engines.  Keywords used were “nurse + greeting card.”   Inclusion criteria: English, portrayed nurse image; exclusion criteria: pornographic or ‘adults only’ sites. The sample of 101 non-duplicated units was collected on April 3 and 4, 2001 between 1200 and 1800 hours. When possible, investigators identified and documented animation (yes or no) and website access count numbers.  It was believed that animated cards attract a longer viewing time. Web access count numbers identify how many different people have looked at that card. Unfortunately, many units did not include an access number. 

Data Analysis

Frequency tables quantified categories as identified on GCAT (see Appendix C).  The non-parametric Chi-square statistical test (apriori alpha of .05) helped determine how well observed and expected category frequencies compared.  According to Health Resources and Services Administration (HRSA) (2001), 86.6% of nurses are white, approximately 94% are female, and the average nurse is 45.2 years of age. Current US population is 51% female.

Three trained student-investigators rated each unit. Initially, five trained raters analyzed four units. This was followed by additional training. Ultimately, an 88% inter-rater agreement was attained and remained throughout the study. This test of equivalence compares favorably to Cronbach alpha reliability score (J. Fields, personal communication, April 26, 2001).

Findings and Interpretation

Using GCAT, categories assessed were: the square centimeter size of the greeting card, cost, card theme, age, race, nurse expression, and more than one nurse depicted on the card.  Dichotomous categories included: pronounced secondary sex characteristics, hat, smile, uniform, gender, animation, human, cartoon, and music.  Units were assessed to determine presence of patients and patient characteristics.  These included male, female, and patient expression (Appendix A). Specific detailed coding criteria facilitated objective interpretation.

Most of the nurse images were female (92.1%) with pronounced secondary sex characteristics (59.4%).  Ethnicity was predominately Caucasian  (82.2%). Nurse images wore white (66.7%) uniforms (95%) with caps (90.1%) (Appendix C).

Themes were: get well, 12.9%; nursing day, 15.8%; thanks, 4%, humor, 13.9%; other, 4%; undetermined, 49.5%. Approximately 63.4% of the nurse-images had a benevolent expression, with 10.9% displaying hostility. Most images portrayed one nurse (90.1%). Smile was displayed on 58.4% of the units. Animation was available with 46.5% of the units and music was available on 37.6%. A patient image was found on 31 units with 90.3% of those patients male and 9.6% female. When a patient was included, 36.4% were smiling, 4.5% were frowning, 29.5% displayed fear/anxiety, and 29.5% had undetermined expression (see Appendix C).

In the category of age (n=101), young nurses (45.5%) were depicted more frequently than middle-aged (37.6%) or older.  Units displayed human nurse images (n=101)  87.1% of the time, majority in cartoon form (80.2%) (See Appendix C).

The null hypothesis was rejected (with 95% certainty) for the following categories: age, secondary sex characteristics, hat, smile, uniform, uniform color, and patient gender. The null hypothesis was retained in the following categories: race, and nurse gender. Data for expected frequencies were obtained from US Census data, the US Department of Health and Human Services (HRSA, 2000, 2001) and a 13-member expert panel.

Composition of the 13-member expert nurse panel included 20.5 mean number of years nursing experience; 46% holding specialty nursing certification, and 62% with education beyond the baccalaureate degree. This expert panel identified expected frequencies in the following categories: secondary sex characteristics, hat, smile, uniform, and uniform color.

Interpretation

Internet nurse images were stereotypical and generally incongruent with reality. Findings support prior greeting card image research regarding aging (Dillon & Jones, 1981) and alcohol use (Finn, 1980). That is, the images displayed on greeting cards conflict with reality. Comparatively, stereotypic Internet greeting card images may suggest to people that nurses are young, Caucasian, female – with pronounced secondary sex characteristics; nurses inflict pain or provide care with sexual overtones to male patients.

Recommendations, Conclusions, Implications

To support the best possible patient outcomes, media images of the nurse need to be congruent with reality. Depictions may suggest sexual appeal and prowess, cruelty, or coercion.  Humorous depictions may impress an unprofessional or incompetent image. King (1992, 1997, 1999) believed that individuals actively interact with others as a result of prior experiences.  Consequently, nurses need to counter-influence the stereotypical and negative images in the interest of facilitating optimal health outcomes. Each and every day, nurses also need to be role models for the professional image we need and want. Of course, additional research is needed to further validate the use of GCAT. Thus, study replication and expansion is recommended on this GCAT and the content analysis process used to quantify Internet greeting card images.

The more nurses write and publish for lay and professional media sources, the more likely the public is to develop an appropriate vision of the nurse. The solution to improving nursing’s image may mean proactive community involvement and public education. Legislative influence and consciousness-raising efforts aimed at eliminating pornographic depictions need to be investigated. Nurses may also affect public opinion in a positive way by working in the community, voicing opinions in editorials, participating in health fairs and screenings, lecturing and speaking, and educating. Nurses may create their own Internet greeting cards and present positive, realistic, and professional portrayals. Furthermore, when nurses believe a patient is operating with stereotypic expectations, through word and deed, nurses must inform and correct that stereotype. Nursing’s image is at stake and efforts to educate the public from within the profession are indicated.

References

Dillon, K.M., & Jones, B.S. (1981).  Attitudes toward aging portrayed by birthday cards.  International Journal of Aging & Human Development, 13(1), 79-84.

Finn, P. (1980).  Attitudes toward drinking conveyed in studio greeting cards.  American Journal of Public Health, 70(8), 826-829.

Health Resources and Services Administration [HRSA] (2000, December). HRSA state health workforce profile. Bureau of Health Professions, National Center for Health Workforce Information & Analysis HRSA US Department of Health and Human Services, Rockville, MD: Author.

Health Resources and Services Administration [HRSA]. (2001, February). The registered nurses population: National sample survey of Registered Nurses. US Department of Health and Human Services [USDHHS] HRSA, Division of Nursing. Retrieved May 1, 2001 from the HRSA data base on the World Wide Web. http://phpr.hrsa.gov/.

Helmstetter, G. (1997). Increasing hits and selling more on your web site. New York: Wiley Computer Publications  http://internet.oit.edu/~halll/packetblaster.oit.edu.35.html

Kalisch, B.J., & Kalisch, P.A.  (1983). An analysis of the impact of authorship on the image of the nurse presented in novels.  Research in Nursing and Health, 6(1), 17-24.

Kalisch, P.A., & Kalisch, B.J.  (1982a).  Nurses on prime-time television.  AJN, 82(2), 264-270.

Kalisch, P.A., & Kalisch, B.J.  (1982b). The image of nurses in novels.  AJN, 82(8), 1220-1224.

Kalisch, P.A., & Kalisch, B. J.  (1982c). The image of the nurse in motion pictures.  AJN, 82(4), 605-611.

Kalisch, B. J., Kalisch, P.A., & McHugh, M. L.  (1982d). The nurse as a sex object in motion pictures, 1930 to 1980.  Research in Nursing and Health, 5(3), 147-154.

King, I. M.  (1992).  King's theory of goal attainment.  Nursing Science Quarterly, 5(1), 19-26.

King, I. M.  (1997).  King's theory of goal attainment in practice.  Nursing Science Quarterly, 10(4), 180-185.

King, I. M.  (1999).  A theory of goal attainment: Philosophical and ethical implications.  Nursing Science Quarterly, 12(4), 292-296.

Mulller, N.J. (1999). Desktop encyclopedia of the Internet. Norwood, MA: Artech House Publishers, Inc.

Peloquin, S. M.  (1991).  Time as a commodity:  Reflections and implications.  The American Journal of Occupational Therapy, 45(2), 147-154.

Polit, D. F., & Hungler, B. P. (1999).  Nursing research principles and methods (pp.209-210).  Philadelphia: Lippincott Williams & Wilkins

Waltz, C.F., Strickland, O. L., & Lenz, E. R. (1991). Measurement in nursing research (2nd ed., pp. 299-310). Philadelphia: F.A. Davis.


Appendix A

Greeting Card Analysis Tool - GCAT

Length and width of card (cm):
Cost if any:

 Theme of card:

  1. Get well
  2. Nursing Day
  3. Thanks
  4. Humor
  5. Other
  6. Undetermined

 Approximate age of nurse:

  1. Young
  2. Middle age
  3. Older
  4. Other

Race of nurse:

1.  White     2.  Black      3.  Hispanic     4.  Asian      5.  Other      6. Undetermined     

Appearance of nurse:  pronounced secondary sex characteristics:   Yes     No 

Expression of nurse:  1.  Benevolent     2.   Hostile      3.  Neutral

More than one nurse depicted?     Yes     No

 Dichotomous categories

  Hat/cap         Yes     No

  Smile:    Yes     No

  Uniform:       Yes     No     If yes:  1.  White     2.  Multicolor     3.  Unable to determine

  Gender:        1. Male    2. Female

  Animated:     Yes     No

  Human:        Yes     No

  Cartoon:       Yes     No

 

Cards: 1.  With patient        2.  Without patient

       Patient:   1.  Female     2.  Male     3.   Undetermined

Expression of patient:

       1.  Smile     2.  Frown      3.  Fear/Anxiety      4.  Sad       5.  Unable to determine

 

Is music available with card?  1.  Yes     2.  No     3.  Unable to determine

 

Copyright: year________________ Company/organization: _______________________

Name of site?____________________________________________________________

How many people have accessed site (if available)? 


Appendix B

Test of null hypotheses using Chi Square

Goodness of fit test: Unequal expected frequencies

Category

Observed
Frequencies

Expected
Frequencies

Chi Square
Value

Critical Value at p=<0.05

Age

91

 

 

 

Young

46

30.8

 

 

Middle

38

55.6

 

 

Old

7

4

*17.57

5.99

Race

88

 

 

 

White

83

77.18

 

 

Non-White

5

10.82

3.56

3.84

Secondary Sex Characteristics

 

 

Yes

60

9.18

 

 

No

41

91.81

*309.46

3.84

Cap

101

 

 

 

Yes

91

2.99

 

 

No

10

98.01

*338.08

3.84

Smile

101

 

 

 

Yes

59

41

 

 

No 

42

60

*13.3

3.84

Uniform

101

 

 

 

Yes

97

71.54

 

 

No 

4

29.46

*31.06

3.84

Uniform Color

95

 

 

 

White

64

6.79

 

 

Non-White

31

88.2

*519.12

3.84

Nurse Gender

101

 

 

 

Male

8

5.45

 

 

Female 

93

95.55

1.26

3.84

Patient Gender

31

 

 

Male

28

15.19

 

 

Female

3

15.81

*19.18

3.84

 


Appendix C

 GCAT
Research Frequency Analyses

Length times width of card (in square cms)            107.74  square cms (mathematical mean)
Cost:          All were free

Frequency Modal
response
%
Theme of card 
Get well 13 12.9
Nursing day 16 15.8
Thanks 4 4.0
Humor 14 13.9
Other 4 4.0
Undetermined 50 X 49.5
Approximate age of nurse
Young 46 X 45.5
Middle 38 37.6
Older  7 6.9
Other 10 9.9
Race
White 83 X 82.2
Black 5 5.0 
Hispanic
     Asian
     Other
     Undetermined 13  12.9
Appearance of nurse: 
            Pronounced secondary sex characteristics
Yes 60 X 59.4
No 41 40.6
Expression of nurse:
Benevolent  64 X 63.4
Hostile 11 10.9
Neutral  26 25.7
More than one nurse depicted
Yes 10 9.9
No 91 X 90.1
Wearing a cap
Yes 91 X  90.1
No 10  9.9
Smiling
Yes 59  X 58.4
No 42 41.6
Uniform
Yes 97  X 96.0
No 4 4.0
If yes, color of uniform
White 64 X 63.4
Multi 31 32.3
Unable to determine 1 1.0
Gender
Male 8 7.9
Female 93 X 92.1
Animated
Yes 47 46.5
No 54 X 53.5
Human
Yes 88 X 87.1
No 13 12.9
Cartoon Image
Yes  81 X 80.2
No 20 19.8
Card with patient
Yes 44 43.6
No 57 X 56.4
If yes patient, gender of patient
        Female 3 3.0
        Male 28 X 27.7
        Undetermined 13 12.9
If yes, what is the expression of the patient?
         Smile 16 X 15.8
         Frown 2 2.0
         Fear/anxiety 13 12.9
         Sad
         Unable to determine 13 12.9
Music available
No 61 X 60.4
Yes 38 37.6
Unable to determine 2 2.0
Copyright year: (when available)
1998 1 1.0
1999 1 1.0
2000 3 3.0
2001 25 X 24.8

 

 

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