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The Journal of Development Communication (JDC) is an international publication to examine the role of communication in promoting national and regional development. Published by the Asian Institute for Development Communication (Aidcom), JDC is a non-profit peer-reviewed journal published since 1990. Currently UNISEL Press  is our co-publisher.

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The use of social media for development communication and social change: a review.

1. Introduction

2. materials and methods, 3. results and discussion, 3.1. literature research profile, 3.1.1. year and method, 3.1.2. social media researched, 3.1.3. research locations and subjects, 3.1.4. development sector and participants in development communication and social change, 3.2. types of research on the use of social media for development communication and social change, 3.2.1. type 1 and type 2 research, 3.2.2. type a and type b research, 3.2.3. type x, type y, and type z research, 3.3. theories and variables in research on the use of social media for development communication and social change.

3.3.1. The Theories Used in Research on the Use of Social Media for Development Communication and Social Change

3.3.2. variables used in research on the use of social media for communication of development and social change, 3.3.3. pro and contrary to previous research variables, 4. conclusions and implications, 5. research limitations, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.

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Ihsaniyati, H.; Sarwoprasodjo, S.; Muljono, P.; Gandasari, D. The Use of Social Media for Development Communication and Social Change: A Review. Sustainability 2023 , 15 , 2283. https://doi.org/10.3390/su15032283

Ihsaniyati H, Sarwoprasodjo S, Muljono P, Gandasari D. The Use of Social Media for Development Communication and Social Change: A Review. Sustainability . 2023; 15(3):2283. https://doi.org/10.3390/su15032283

Ihsaniyati, Hanifah, Sarwititi Sarwoprasodjo, Pudji Muljono, and Dyah Gandasari. 2023. "The Use of Social Media for Development Communication and Social Change: A Review" Sustainability 15, no. 3: 2283. https://doi.org/10.3390/su15032283

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Development communication: The state of research in an era of ICTs and globalization

/ Through the technique of meta-analysis, this study investigates the scholarly articles appearing in peer-reviewed online and offline journals that address the topic of communication and development from 1998 to 2007 to determine publication trends in the field. The research was prompted by the sense that development was moving off the research agenda of most communi-cation scholars. This seemed surprising in the era of globalization and it was decided to examine the literature for evidence. The study finds that published studies have moved away from mass com-munication and toward ICTs ’ role in development, that they infrequently address development in the context of globalization and often continue to embrace a modernization paradigm despite its many criticisms. In addition, International Communication Gazette was found to be the only mainstream communication journal to include a significant number of articles on development communication.

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Developmental Communication Research Paper Topics

• Advertising Responses across the Life-Span
• Age Identity and Communication
• Attention to Media Content across the Life-Span
• Children’s Responses to Educational Television
• Communication Skills across the Life-Span
• Computer Games and Child Development
• Conflict and Cooperation across the Life-Span
• Death, Dying, and Communication
• Family Communication Patterns
• Family Decision-Making
• Fantasy-Reality Distinction
• Fear Induction through Media Content in Children
• Friendship and Communication
• Intergenerational Communication
• Internet Use across the Life-Span
• Language Acquisition in Childhood
• Media Regulations for Child Protection
• Media Use across the Life-Span
• Media Use and Child Development
• Media Use by Children
• News Processing across the Life-Span
• Parental Mediation Strategies
• Personality Development and Communication
• Pornography Use across the Life-Span
• Violence as Media Content Effects on Children

Significance of Developmental Communication Research

First, they note that it is important to recognize that communication is, by nature, developmental. In other words, communication is a process over time rather than a single event. Second, they advocate acknowledging multiple influences in order to obtain a comprehensive understanding of interactive behavior. Their third proposition asserts that when scholars examine communication change over the life-span, they must appreciate both quantitative and qualitative change because quantitative changes are useful in depicting “a difference in degree,” whereas qualitative changes display a “fundamental departure in the meaning of an event or a relationship” (Pecchioni et al. 2005).

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In their final two propositions, they address theory and method. The fourth proposition advocates including all theories that are testable. Most communication theories lack any consideration of development, yet life-span scholars fully appreciate that any theory may be useful in expanding knowledge of communication behavior. Moreover, this perspective does not exclude any theory of behavior or development. As a result, developmental communication studies have been firmly grounded in communication theory (Nussbaum & Friedrich 2005).

Incorporating Communication Theory

Developmental communication studies can incorporate theory from all paradigms of thought (Pecchioni et al. 2005). Pecchioni and colleagues note that, at one end of the spectrum, interpretive and critical theories are useful in attributing meaning to social interaction as well as in unveiling factors that influence these experiences. For instance, an interpretive perspective is useful in examining how we communicatively make sense of our social experiences across time through the use of stories. Similarly, critical approaches, such as power and language studies, aid in illuminating factors, like power, that impact communication over the life-span. At the other end of the spectrum, scientific theories enable scholars to examine more universal communicative patterns by using scientific methods to control variables in order to reach more generalizable conclusions from multiple data sets (Pecchioni et al. 2005). The latter approach is more common in the communication discipline as communication theory has typically been generated from this approach.

In addition to the above-mentioned scientific theories, communication accommodation theory (CAT) has greatly contributed to developmental communication research as well as to the communication discipline as a whole (Ryan et al. 1986). Like many life-span studies, CAT views age as a marker related to change. In this case, age is a group identifier that influences behavior leading to generational differences in attitude and behavior. CAT posits that younger adults influenced by negative age stereotypes will over-accommodate their speech with elderly adults. As a result, older adults may encounter negative social experiences with younger generations, which may lead to their avoidance of future interactions. Scholars have also used CAT to advance various models of communication and aging stereotypes. Ryan et al. (1986) introduced the communication predicament of aging model (CPA) to demonstrate that in social interactions, age-related cues (i.e., physical appearance, age, behavior, and socio-cultural signs) activate age-related stereotypes that negatively affect intergenerational interactions, leading for example to over- or under-accommodation results (Coupland et al. 1988). Hummert, Wiemann, & Nussbaum (1994), on the other side, discovered that some stereotypes are positive.

Capturing Communication Development over Time

While developmental communication scholars should be attuned to integrating theory in their investigations, they must also choose methodologies that enable them to capture change over time (Nussbaum et al. 2002; Nussbaum & Friedrich 2005; Pecchioni et al. 2005). A critical area of concern is the issue of capturing intra- versus interindividual change. To date, most life-span communication research has examined interindividual change. These researchers typically utilize cross-sectional designs to compare communicative behavior between age groups. By doing so, scholars can only suggest behavioral change over the life-span. Consequently, cross-sectional studies often produce findings that lead to misinterpretations of intra- versus interindividual changes over time (Schaie & Hofer 2001; Nussbaum et al. 2002; Pecchioni et al. 2005), illustrating the point that in order to fully appreciate, examine, and interpret communication change, designs and methodologies need to capture developmental change utilizing longitudinal methods.

References:

• Baltes, P. B. (1987). Theoretical propositions of life-span developmental psychology: On the dynamics between growth and decline. Developmental Psychology, 23, 611–626.
• Baltes, P. B. & Nesselroade, J. R. (1979). The developmental analysis of individual differences on multiple measures. In J. R. Nesselroade & H. W. Reese (eds.), Life-span developmental psychology: Methodological issues. New York: Academic Press, pp. 1–40.
• Baltes, P. B., Reese, H. W., & Nesselroade, J. R. (1988). Life-span developmental psychology: Introduction to research methods. Hillsdale, NJ: Lawrence Erlbaum.
• Coupland, J., Coupland, N., Giles, H., Henwood, K., & Wiemann, J. (1988). Elderly self disclosure: Interactional and intergroup issues. Language and Communication, 8, 109–133.
• Hummert, M. L. (1994). Stereotypes of the elderly and patronizing speech. In M. L. Hummert, J. M. Wiemann, & J. F. Nussbaum (eds.), Interpersonal communication in older adulthood: Interdisciplinary theory and research. Thousand Oaks, CA: Sage, pp. 162–184.
• Hummert, M. L., Wiemann, M., & Nussbaum, J. F. (1994). (eds.), Interpersonal communication in older adulthood: Interdisciplinary theory and research. Thousand Oaks, CA: Sage.
• Nussbaum, J. F. & Friedrich, G. (2005). Instruction/ developmental communication: Current theory, research, and future trends. Journal of Communication, 55, 578–593.
• Nussbaum, J. F., Pecchioni, L., Robinson, J. D., & Thompson, T. (2000). Communication and aging, 2nd edn. Mahwah, NJ: Lawrence Erlbaum.
• Nussbaum, J. F., Pecchioni, L., Baringer, D., & Kundrat, A. L. (2002). Lifespan communication. In W. B. Gudykunst (ed.), Communication yearbook 26. Mahwah, NJ: Lawrence Erlbaum, pp. 366–389.
• Pecchioni, L. L., Wright, K., & Nussbaum, J. F. (2005). Life-span communication. Mahwah, NJ: Lawrence Erlbaum.
• Ryan, E. B., Giles, H., Bartolucci, G., & Henwood, K. (1986). Psycholinguistics and social psychological components of communication by and with the elderly. Language and Communication, 6, 1–24.
• Schaie, K. W. & Hofer, S. M. (2001). Longitudinal studies in research on aging. In J. E. Birren & K. W. Schaie (eds.), Handbook of the psychology of aging, 5th edn. San Diego, CA: Academic Press, pp. 55–77.
• Williams, A. & Nussbaum, J. F. (2001). Intergenerational communication across the life span. Mahwah, NJ: Lawrence Erlbaum.

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Making science of influencing : assessing the impact of development research

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• Published: 23 August 2024

Using wiki surveys to rapidly test messages promoting COVID-19 vaccination boosters and child vaccination among Philadelphia residents

• Brittany A. Zulkiewicz 1 ,
• Allison Li 2 ,
• Gretel Tassah 2 ,
• Minnie Kim 2 ,
• Karen Glanz 3 , 4 ,
• Antonia Villarruel 4 ,
• Jose A. Bauermeister 4 ,
• Terri Lipman 4 ,
• Stephen Bonett 4 ,
• Ufuoma Oyiborhoro 4 &
• Andy S. L. Tan 1 , 5  

Scientific Reports volume  14 , Article number:  19611 ( 2024 ) Cite this article

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Formative research is an important component of health communication campaign development. Rapid message testing approaches are useful for testing new messaging quickly and efficiently during public health emergencies, such as COVID-19, when guidance and recommendations are rapidly changing. Wiki surveys simultaneously collect quantitative message testing data and qualitative feedback on potential social media campaign messages. Philly CEAL used wiki surveys to test messages about COVID-19 vaccinations for dissemination on social media. A cross-sectional survey of Philadelphia residents (N = 199) was conducted between January and March 2023. Wiki surveys were used to assess the perceived effectiveness of messages promoting the updated COVID-19 booster and child vaccination. In each wiki survey, participants were presented with two messages and asked to select the one that they perceived as most effective. Participants could alternatively select “can’t decide” or submit their own message. A score estimating the probability of selection was calculated for each message. Participant-generated messages were routinely reviewed and incorporated into the message pool. Participants cast a total of 32,281 votes on messages seeded by the research team (n = 20) and participants (n = 43). The highest scoring messages were those that were generated by participants and spoke to getting your child vaccinated to protect them against serious illness and getting the booster to protect your health and that of your community. These messages were incorporated into social media posts disseminated by Philly CEAL’s social media accounts. Wiki surveys are a feasible and efficient method of rapid message testing for social media campaigns.

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Introduction.

Public health communication is a key strategy used throughout the COVID-19 pandemic to combat misinformation 1 , promote health behaviors 2 , and address inequities 3 . Health communication campaigns are more likely to be successful when formative research is conducted to understand the beliefs and behaviors of the intended audience and to pretest messages for appropriateness and effectiveness 4 . COVID-19 campaigns have used long-established formative research approaches such as observational surveys 5 , 6 , survey experiments 7 , 8 , individual interviews 6 , and focus groups 5 , 9 . While technology can accelerate formative research, many of these established methods can take months to develop research instruments, collect and analyze data, and disseminate final campaign materials.

Because of the formative research timeline and the rapidly changing environment of COVID-19 and other emergent outbreaks 10 , 11 , findings can become outdated before campaigns are activated. Conducting no formative research, however, can lead to ineffective or harmful messaging. Rapid and responsive message testing approaches are most promising to quickly develop effective campaigns, especially in the context of a pandemic such as COVID-19 12 . Multiple rapid message testing studies for COVID-19 utilized digital survey platforms 12 , 13 and text ads 14 . These approaches hold promise for effectively eliciting relevant beliefs and disseminating messaging for clinical and healthcare topics 12 .

Wiki surveys are a rapid message testing approach that allow researchers to conduct quantitative testing similar to A/B testing, a user experience research methodology that consists of randomized experiments that compare the perceived effectiveness of two different messages 12 . A novel feature of wiki surveys is the integration of user-generated messages into the experimental design. In this way, users can rate existing messages and suggest new messages in the same platform through a seamless user experience. Then, future users give ratings for these user-generated messages as well as researcher-generated messages. Wiki surveys investigating message strength in the areas of the legalization of marijuana and sustainability and education policy found that user-generated messages were among the highest-rated 15 , 16 .

We used wiki surveys hosted on the All Our Ideas (allourideas.org) platform in January to March 2023 to rapidly test messages promoting pediatric COVID-19 vaccination and booster vaccinations for dissemination on Philly CEAL’s social media accounts. Philly CEAL, part of the National Institutes of Health’s (NIH) Community Engagement Alliance against COVID-19 Disparities (CEAL) 17 , is a community-wide alliance working to provide the Philadelphia community with resources to reduce COVID-19 disparities in testing, vaccination, and participation in clinical trials and to prevent the spread of misinformation. At the time of the study, CDC recommended the COVID-19 vaccine for all adults and children 6 months and older 18 and the bivalent COVID-19 booster for immunized adults and children over 12 years old 19 . For the wiki surveys, adults who lived or worked in Philadelphia were randomly presented with one of two messages and asked to select the message they thought would be most effective for promoting pediatric or booster COVID-19 vaccinations. Each message received score quantifying the probability that the message would be perceived as more effective than a randomly selected alternative. This paper describes the results of the wiki surveys, how these results were translated into subsequent Philly CEAL’s social media messaging, and how wiki surveys were implemented to conduct rapid message testing.

Participant characteristics

Of the 544 people invited, 199 (36.6%) completed the survey and are included in the analysis. Table 1 summarizes the characteristics of our sample. The mean age was 37.4 years (SD = 11.3). Most participants identified as women (74%) and heterosexual or straight (73%). Most (60%) participants were White; 27% were Black or African American, 13% were Asian, and 3% were American Indian or Alaska Native. Almost 10% identified as Hispanic or Latino ethnicity. Three-quarters of participants had at least a Bachelor’s degree. Nearly all participants were fully vaccinated (94%), and among those fully vaccinated, about half had received two boosters (49%). Table 2 summarizes the vaccination status of the participants’ children. Approximately one-third (37%) of participants had at least one child under the age of 18. Most (62%) reported that all their children were fully vaccinated, and 16% reported not vaccinating any of their children.

Booster messages

Participants voted a total of 13,897 times on 9 seed and 10 participant-generated messages. Table 2 presents the voting results and the message scores for the top 10 booster messages. The three highest performing messages were participant-generated and focused on the health protection provided by the boosters and the importance of community protection (e.g., “Don’t gamble with your health. Stay up to date with your Covid-19 boosters” and “Each reinfection increases chances of serious and long term COVID complications. Get the booster to protect yourself and your community”). Results for all seed and participant-generated messages are available in Appendix 3. Seven of the 8 messages that had less than a 50% chance of being chosen over a randomly selected message were about COVID-19 variants ( e.g., “Many COVID-19 variants are connected to Omicron, which the booster shot helps protect against!”).

Child vaccination messages

Participants cast a total of 18,384 votes on 11 seed and 33 participant-generated messages. Table 3 presents the results for the 10 child vaccination messages with the highest message ratings. Of the nine highest performing messages, 7 were participant-generated and all addressed child vaccine protection from serious illness (e.g., “Vaccination is the best way to protect your child from serious illness against COVID-19” and “Protect your children from serious health complications of COVID-19 by getting them vaccinated”). Message scores and voting results for all seed and participant-generated messages are available in Appendix 4. Messages that focused solely on eligibility for and availability of vaccinations had less than a 50% chance of being chosen over a randomly selected message (e.g., “On November 2, 2021, all Philadelphians 5–11 years became eligible for the vaccine. Thousands of children have since been vaccinated”).

We conducted wiki surveys in January-March 2023 to rapidly generate and test messages to promote COVID-19 boosters and child vaccinations among Philadelphia residents and incorporated highly rated messages into social media posts on Philly CEAL accounts. Notably, participant-generated messages were consistently perceived as more effective than investigator-generated seed messages in our study. This finding is consistent with results of previous wiki surveys 15 , 16 and underscores the importance of obtaining qualitative feedback during rapid message testing. While some participant-generated messages were novel (e.g., “COVID damage can be silent and stealthy”), others reflected arguments from seed messages in participants’ own words. These messages usually outperformed the seed message. For example, the participant-generated message “Vaccination is the best way to protect your child from serious illness against COVID-19” was rated more highly than the seed message “COVID-19 vaccines prevent children in Philadelphia from getting seriously sick if they do get COVID-19.”

Wiki surveys have been previously used to generate ideas for New York City’s sustainability plan 15 and to assess the strength of arguments for marijuana legalization 16 . To our knowledge, this is the first published study to use wiki surveys to rapidly evaluate perceived effectiveness of and generate messages for promoting COVID-19 vaccinations and disseminate highly rated messages through a social media campaign. Examples of the resulting posts on Philly CEAL’s social media accounts are shown in Appendix 5. The study establishes the feasibility and advantages of using wiki surveys for rapid message testing, especially when time and resources for formative research may be limited.

Using wiki surveys for rapid message testing has several advantages compared to other formative research approaches. First, community partners and residents were able to contribute messages and these messages were iteratively incorporated into the messaging testing pool. Second, other message testing surveys have a fixed set of items. Adding new items would increase the length of the survey, prevent comparisons over time, and require time for revisions and publishing of updated versions. Messages can be added to wiki surveys quickly and efficiently, and doing so does not add to participant burden because participants control how many votes they cast. Third, the message score statistically accounts for the fact that some participants would not have been able to vote on messages that were added to the pool after their votes were cast.

There are several important limitations to the wiki survey approach. The seed messages based on contemporaneous Philly CEAL and NIH CEAL social media posts may have constrained the range of arguments and themes that participants thought of when generating additional messages. Only brief messages that are less than 140 characters and include only text can be tested in the All Our Ideas platform’s current version. While this is acceptable for testing messages for social media, the wiki survey approach may not be feasible for other avenues of dissemination. Currently, the wiki survey data cannot be linked to survey platforms by passing embedded variables. We are therefore unable to compare how message ratings differed by participant characteristics or determine how many votes individual participants cast. Although the wiki survey platform reduces the burden of updating the message pool and analyzing data, resources are still required to stagger recruitment so that there is sufficient time for messages to be generated by participants, added to the pool, and voted on by subsequent participants. New messages also needed to be reviewed before being added to the pool for appropriateness and clarity.

In addition to the limitations of wiki surveys generally, our study has several limitations. The community partners and prior survey participants are not representative of all Philadelphia residents nor of our target audiences. Our sample was highly educated, with 44% having a college degree and 31% an advanced degree. More than 94% of our sample were fully vaccinated, so the wiki survey did not yield input from unvaccinated groups. Our messages aimed to reach Philadelphia residents who had not been boosted or had their children vaccinated, but only 11% of our sample had not received a booster, 16.2% of those with children under 18 had not had their children at least partially vaccinated, and all participants contributed to the child vaccination wiki survey even though 63% did not have children under 18. Due to the platform limitations, messages designed to resemble social media posts (i.e., images and captions) based on the wiki survey results could not be tested. Finally, our findings cannot be generalized to other time periods given the changing landscape of COVID-19 outbreaks and vaccine recommendations. As new vaccines become available and COVID-19 variants emerge, messages will need to be re-tested using formative research methods like wiki surveys to ensure that they are appropriate and effective in the current context.

Wiki surveys could be applied to other formative research aims. For example, they could be implemented over extended periods of time to examine shifts in messaging strategies that are perceived as effective and the evolution of preferred messages instead of using multiple cross-sectional surveys. This is important because the type of messages that would be effective at changing behavior may change as the pandemic progresses. For example, those who chose to delay receiving the COVID-19 vaccines during the first few months of vaccine availability may have different beliefs and motivations influencing their health behaviors when compared to individuals who have remained unvaccinated for several years. Wiki surveys could also be used to compare different geographic locations or groups if the same user-generated messages were added to both pools. To address the limitation of the maximum message length that could be tested, new tools on Qualtrics, OpinionX, and other survey platforms could also be used to do A/B testing with images.

Wiki surveys are a feasible and efficient method for rapidly testing and obtaining audience feedback on short messages for social media campaigns. This study demonstrated how Philly CEAL used wiki surveys to develop social media campaign messaging to promote COVID-19 boosters and child vaccinations among Philadelphia residents. Participant-generated messages were perceived as more effective than messages seeded by the research team. These messages were incorporated into social media posts and shared through Philly CEAL’s X (formerly Twitter) and Facebook accounts. Future research should test the comparative effectiveness of higher versus lower ranked messages and participant- versus researcher-generated messages at increasing uptake of COVID-19 boosters and child vaccinations.

Sampling and recruitment

Participants in the present study were primarily recruited from respondents who had completed a previous study conducted by Philly CEAL. The study recruited Philadelphia residents ages 13 and older to complete an online survey through online and community-based outreach between September 2021 and February 2022. Responses were validated using a multi-step fraud detection protocol to enhance data integrity.

For the present study, e-mail invitations were sent between January and March 2023 to a randomly selected subset of verified respondents to the previous survey who had agreed to be recontacted for future studies (N = 493), Philly CEAL community partner organization representatives (N = 27), and VaxUpPhillyFamilies Ambassadors (N = 24) who engaged with local parents and caregivers to promote vaccination for children on social media and at in-person events. To be eligible for the wiki survey study, participants needed to be at least 18 years of age and currently living or working in the city of Philadelphia. We randomly sampled verified respondents of the previous survey and sent follow-ups to previously invited participants until we reached 200 completes. Because participants in previous wiki surveys had cast an average of 55 and 43 votes 16 , we estimated that 200 participants would result in 8600 to 11,000 votes per wiki survey. Of the 544 individuals invited, 264 (48.5%) started the screener, 256 (47.1%) were eligible (seven participants were ineligible because they did not work or live in Philadelphia and one was ineligible because they were under 18), 252 (46.3%) provided informed consent, 200 (36.8%) responded to all Qualtrics survey items, and 199 (36.6%) were verified to have completed the wiki surveys and included in the analysis.

Figure  1 describes the protocol for this cross-sectional study and Appendix 1 includes the full questionnaire. Participants completed the screener and informed consent in Qualtrics, were directed to two wiki surveys hosted on All Our Ideas, and then returned to Qualtrics to complete demographic and COVID-19 vaccination status questions.

Survey workflow.

Email invitations included a unique link to a Qualtrics survey where participants first completed screener questions to assess eligibility (age, ZIP codes where they live and work). Eligible participants then provided informed consent and were randomized (using Qualtrics’ built-in randomizer function) to view either the booster or the child vaccination wiki survey first. For each wiki survey, participants were instructed to click a link that would open the appropriate wiki survey on the All Our Ideas website in a separate window, vote on messages for at least 3 min, and return to Qualtrics to continue the survey. Once the participant clicked the link, a three-minute countdown timer was displayed on the Qualtrics survey. Participants could not continue to the next screen until three minutes elapsed. To ensure that participants visited both wiki surveys, clicks on the wiki survey links were tracked using Qualtrics’ built-in click count variable and a JavaScript function that updated an embedded variable when the link was clicked on each instruction page.

On the All Our Ideas website, participants were presented with two messages randomly selected from a pool of messages and asked to rate the messages by selecting the message that they thought “would most encourage parents to get their child vaccinated against COVID-19” or “would most encourage someone to get the updated COVID-19 booster.” They could also select “can’t decide” or provide their own message (see Appendix 2). The initial pool included 11 messages for child vaccination and 9 messages for boosters based on the text obtained from Philly CEAL’s previous social media posts and contemporaneous social media toolkits from the NIH CEAL 20 . Three study team members (BZ, MK, GT) reviewed participant-submitted messages three times per week for appropriateness and grammar. Participant-submitted messages that were relevant to and not duplicative were added to the message rating pool. Recruitment was staggered so that there was approximately one week between each round of invitations to allow sufficient opportunity for participant-submitted messages to be added and voted on by subsequent participants.

After completing both wiki surveys, participants returned to Qualtrics and completed questions assessing demographic characteristics, COVID-19 vaccination status, and availability of COVID-19 information in respondents’ preferred language(s). Participants received a $10 gift card for completing the survey. The study was reviewed and approved by the University’s Institutional Review Board (protocol no. 848650). The research protocol was performed in accordance with the relevant guidelines and regulations.

Demographics. In addition to providing their age in the screener, participants were asked to indicate their gender identity, sexuality identity, race, ethnicity, education, and whether they worked with a community-based organization that partnered with Philly CEAL.

COVID-19 vaccination status. Participants’ COVID-19 vaccination status was assessed using two items. The first item asked if participants had received the COVID-19 vaccine. Response options included “Yes, I am fully vaccinated (one dose of Johnson and Johnson or two doses of Moderna or Pfizer)”, “I am partially vaccinated (i.e., one dose of Moderna or Pfizer)”, and “No, I am not vaccinated against COVID-19.” Participants who were fully vaccinated were then asked if they had received one, two, three or more, or no boosters. Participants were also asked to indicate the ages of each of their children and whether each of their children under the age of 18 were fully, partially, or not vaccinated against COVID-19, if applicable.

Data analysis

Participant characteristics. Participants who completed the demographic and COVID-19 vaccination status measures at the end of the survey and were verified to have completed both wiki surveys were included in the descriptive analyses of participant characteristics (N = 199). Descriptive statistics for demographic characteristics and COVID-19 vaccination status were generated.

Message score. The All Our Ideas website collects data on every vote cast, including a unique respondent ID, a session ID, the two contending messages, and the resulting vote. All Our Ideas also provides aggregated statistics for each message summarizing the total number of votes; how many times the message won, lost, or resulted in a ‘can’t decide’ vote; and a message score 15 that estimates the probability that the message would be chosen over a randomly selected competing message by a randomly selected participant. Scores range from 0 (the message is always expected to lose) to 100 (the message is always expected to win). The All Our Ideas website generates a message score using a two-step process. In the first step, an opinion matrix is generated that uses Bayesian inference to estimate how much each respondent values each message. Message values are imputed for participants who did not encounter the given message either because they did not encounter the message while casting votes or they could not have seen the message because it was participant-generated or they cast their votes prior to the message being added to the pool. This approach assumes that the votes reflect participants’ relative preferences for messages and that preferences for each item follow a normal distribution across respondents. The opinion matrix is then summarized to generate a message-level score for each item that estimates the probability of a message being chosen over a randomly selected message by a randomly selected participant. Because we cannot link votes to individual participants, all votes from all participants are included in the message score analysis regardless of whether they completed the study.

No financial disclosures were reported by the authors of this paper.

Data availability

Data are not available in a repository. Because we did not specify in the online consent that the data could be used for secondary data analyses, we are not able to make the data public. All message score data are available in the appendices. A restricted dataset including voting data, demographic characteristics, and vaccination status data may be requested from Brittany Zulkiewicz ([email protected]) and should include a plan for its use. Data may be made available to qualified researchers after the main findings are published in a peer-reviewed journal. All data sharing will comply with local, state, and federal laws and regulations and may be subject to appropriate human subjects institutional review board approvals.

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Acknowledgements

Research reported in this publication was supported by the National Institutes of Health/CEAL (grant number 10T2HL161568). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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B.Z.: Conceptualization, Methodology, Formal analysis, Investigation, Data curation, Writing—Original draft, Writing—Review & editing, Visualization, Project administration. A.L.: Writing—Original draft, Writing—Review & editing. G.T.: Investigation, Writing—Review & editing, Project administration. M.K.: Investigation, Writing—Review & editing, Project administration. K.G.: Writing—Review & editing. A.V.: Writing—Review & editing, Funding acquisition. J.B.: Writing—Review & editing, Funding acquisition. T.L.: Writing—Review & editing, Funding acquisition. S.B.: Writing—Review & editing. U.O.: Writing—Review & editing, Project administration. A.T.: Conceptualization, Methodology, Writing—Review & editing, Supervision, Project administration.

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Zulkiewicz, B.A., Li, A., Tassah, G. et al. Using wiki surveys to rapidly test messages promoting COVID-19 vaccination boosters and child vaccination among Philadelphia residents. Sci Rep 14 , 19611 (2024). https://doi.org/10.1038/s41598-024-70554-9

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