The impact of reporting behavior to an online social network on contraception compliance in young-adult women

Justin Williams

University of Arizona

Department of Management Information Systems

October 13, 2010

The impact of reporting behavior to an online social network on contraception compliance in young-adult women

Unintended pregnancy in the United States is a widespread phenomenon with far reaching implications in a variety of aspects of personal and public life including family planning, poverty, abortion rates, and even military readiness (Brown, 2010).

Half of all pregnancies in the United States and 70% of those among single women in their 20s are unintended(Brown, 2010). In one study, 65% of babies born to women in the military were not intended (Custer M, 2008). According to a recent survey of unmarried young adults, only about half of those who are sexually active will use contraception every time (Brown, 2010).

All pregnancies, but particularly unintended ones, are a life-altering experience that can have substantial consequences. According to a 1994 report, 54% of unintended pregnancies ended in abortion (Henshaw, 1998). Other studies have demonstrated a strong link between poverty and unintended pregnancies (Henshaw, 1998).

Studies have been conducted on compliance with the use of oral contraceptives among adolescents (S. Jean Emans, Estherann Grace, Elizabeth R. Woods, Deborah E. Smith, Kayt Klein, & James Merola, 1987) looking at factors such as age, written instructions, a history of contraceptive use, education. Another studyunderway is looking into the impact of text messages on compliance with the use of oral contraceptives (P. Castaño, August 2010).

Text messaging is just one of many forms of computing that can be used to support or persuade a voluntary change in behavior in people (Fogg, Persuasive Computers: Perspectives and Research Directions, 1998). A field of study is developing around the use of persuasive technology (Fogg, Persuasive technology: using computers to change what we think and do, December 2002) and behavior change support systems (T. Ploug, 2010). Web 2.0 technologies,including online social networks like Facebook that bring together social interactions, may prove to be useful as a behavior change support system.

Behavior change can be divided into three categories: compliance (C-change), behavior change (B-change), and attitude change (A-change) (T. Ploug, 2010). In this framework, C-change represents an immediate compliance response to a system request. B-change represents a change regular compliance behavior over a longer period of time. A-change represents a long-term change in attitudetoward the behavior, which would lead to sustainable behavioral change. This proposal will look at the effects of a social networking on all three categories of change. See Figure 1.

Figure 1: C-change, B-change and A-change

A basic framework of principles for designing a behavior change support system can be clustered into four categories: primary task support, dialogue support, system credibility support and social support (Oinas-Kukkoen & Harjumaa, 2009). See Table 1.

Table 1: Framework of Design Principles for a Behavior Change Support System

Primary Task Support
Reduction / A system that reduces complex behavior into simple tasks helps users perform the target behavior, and it may increase the benefit/cost ratio of a behavior.
Tunneling / Using the system to guide users through a process or experience provides opportunities to persuade along the way.
Tailoring / Information provided by the system will be more persuasive if it is tailored to the potential needs, interests, personality, usage context, or other factors relevant to a user group.
Personalization / A system that offers personalized content or services has a greater capability for persuasion.
Self-monitoring / A system that keeps track of one’s own performance or status supports the user in achieving goals.
Simulation / Systems that provide simulations can persuade by enabling users to observe immediately the link between cause and effect.
Rehearsal / A system providing means with which to rehearse a behavior can enable people to change their attitudes or behavior in the real world.
Dialogue Support
Praise / By offering praise, a system can make users more open to persuasion.
Rewards / Systems that reward target behaviors may have great persuasive powers.
Reminders / If a system reminds users of their target behavior, the users will more likely achieve their goals.
Suggestion / Systems offering fitting suggestions will have greater persuasive powers.
Similarity / People are more readily persuaded through systems that remind them of themselves in some meaningful way.
Linking / A system that is visually attractive for its users is likely to be more persuasive.
Social role / If a system adopts a social role, users will more likely use it for persuasive purposes.
System Credibility Support
Trustworthiness / A system that is viewed as trustworthy will have increased powers of persuasion.
Expertise / A system that is viewed as incorporating expertise will have increased powers of persuasion.
Surface credibility / People make initial assessments of the system credibility based on a firsthand inspection.
Real-world feel / A system that highlights people or organization behind its content or services will have more credibility.
Authority / A system that leverages roles of authority will have enhanced powers of persuasion.
Third-party endorsements / Third-party endorsements, especially from well-known and respected sources, boost perceptions on system credibility.
Verifiability / Credibility perceptions will be enhanced if a system makes it easy to verify the accuracy of site content via outside sources.
Social Support
Social learning / A person will be more motivated to perform a target behavior if (s)he can use a system to observe others performing the behavior.
Social comparison / System users will have a greater motivation to perform the target behavior if they can compare their performance with the performance of others.
Normative influence / A system can leverage normative influence or peer pressure to increase the likelihood that a person will adopt a target behavior.
Social facilitation / System users are more likely to perform target behavior if they discern via the system that others are performing the behavior along with them.
Cooperation / A system can motivate users to adopt a target attitude or behavior by leveraging human beings’ natural drive to co-operate.
Competition / A system can motivate users to adopt a target attitude or behavior by leveraging human beings’ natural drive to compete.
Recognition / By offering public recognition for an individual or group, a system can increase the likelihood that a person/group will adopt a target behavior.

Since no study has been conducted on the use of social networking as a behavior change support system for increasing the compliance withan oral contraception regimen in young adults, I propose new research that will address the following research questions:

RQ1: What impact will a daily reminder message from an automated system have on improving compliance with an oral contraception regimen?

RQ2: What impact does the act of daily reporting of the status of compliance to an automated system have on improving compliance?

RQ3: What impact does sharing and comparing the reporting above with others in an online “support group” have on improving compliance?

For the purposes of this proposal, we focus on the principles of self-monitoring, reminders, social comparison, normative influence, social facilitation, competition, and recognition. These principles map to each research question. See Table 2.

Table 2: Mapping Research Questions to Selected Design Principles

RQ1 /
  • Reminders

RQ2 /
  • Self-monitoring

RQ3 /
  • Social Comparison
  • Normative influence
  • Social facilitation
  • Competition
  • Recognition

Method

To answer these questions, I will conduct a 3-month field study of young-adultwomen who are already being voluntarily prescribed oral contraception and are already actively using the online social network Facebook. Participants will be broken into groups and asked to install and use a Facebook application that will engage each participant group in the following distinct activities:

  1. Control: Participants will not engage in any action on Facebook
  2. Reminder: Participants are sent a simple daily reminder to take their pill
  3. Report: Participantsreport the status of their compliance to the application on a daily basis
  4. Support: Participant’s daily compliance reporting is sharedand compared with members of a social network “support group”

Behavior change will be measured based on the three categories described previously: C-change (compliance), B-change (behavioral change) and A-change (attitude change). The results of compliance activities as reported by participants will serve as a measure of C-change. B-change will be measured by the number of pills unused at the end of the 3-month period. Participants will receive a pre-study and post-study interview to establish changes in attitudes toward contraception compliance.

The following hypotheses will be tested:

H1: Reminder group with have greater compliance than Control group

H2: Reminder group will have similar compliance to Text Messaging

H3: Report group will have greater compliance than Control group

H4: Report group will have greater compliance than Reminder group

H5: Report group Support greater compliance than Text Messaging

H6: Support group will have greater compliance than Control group

H7: Support group will have greater compliance than Reminder group

H8: Support group will have greater compliance than Report group

H9: Support group will have greater compliance than Text Messaging

This research will expand the knowledge in the fields of persuasive technology, behavior change support systems, public health and preventative medicine. Additionally, understanding the ways in which social networking can effectively act as a behavior change support system can enable individuals to more effectively adopt new voluntary behaviors and will have wide impact in a broad range of domains including health, mental health, education, safety, environment, personal management andmany others (Fogg, Persuasive Computers: Perspectives and Research Directions, 1998).

References

(n.d.).

Brown, S. (2010, April). Preventing Teen and Unplanned Pregnancy. Policy and Practice, pp. 11-14.

Custer M, W. K. (2008). Unintended pregnancy rates among a US military population. Paediatric and Perinatal Epidemiology, 195–200.

Fogg, B. (1998). Persuasive Computers: Perspectives and Research Directions. CHI 98, (p. 225). Los Angeles, CA USA.

Fogg, B. (December 2002). Persuasive technology: using computers to change what we think and do. Ubiquity.

Henshaw, S. K. (1998). Family Planning Perspectives.

Oinas-Kukkoen, H., & Harjumaa, M. (2009). Persuasive Systems Design: Key Issues, Process Model, and System Features. Communiations of the Association for Information Systems, 485-500.

P. Castaño, R. M. (August 2010). Txt Now 2 Decrease Pregnancies L8r: a randomized control trial to evaluate the effect of daily educational text messages on oral contraceptive continuation in young urban women . Contraception, 189.

S. Jean Emans, M., Estherann Grace, M., Elizabeth R. Woods, M. M., Deborah E. Smith, B. B., Kayt Klein, M., & James Merola, P. (1987). Adolescents' Compliance With the Use of Oral Contraceptives. Journal of the American Medical Association, 3377-3381.

T. Ploug, P. H.-K. (2010). Behavior Change Support Systems: A Research Model and Agenda. PERSUASIVE 2010, LNCS 6137 (pp. 4-14). Springer-Verlag Berlin Heidelberg.