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With the increasing health care burden of cancer, public health organizations are increasingly emphasizing the importance of calling people to engage in long-term prevention and periodical detection. How to best deliver behavioral recommendations and health outcomes in messaging is an important issue.
This study aims to disaggregate the effects of gain-framed and loss-framed messages on cancer prevention and detection behaviors and intentions and attitudes, which has the potential to inform cancer control programs.
A search of three electronic databases (Web of Science, Scopus, and PubMed) was conducted for studies published between January 2000 and December 2020. After a good agreement achieved on a sample by two authors, the article selection (κ=0.8356), quality assessment (κ=0.8137), and data extraction (κ=0.9804) were mainly performed by one author. The standardized mean difference (attitude and intention) and the odds ratio (behaviors) were calculated to evaluate the effectiveness of message framing (gain-framed message and loss-framed message). Calculations were conducted, and figures were produced by Review Manager 5.3.
The title and abstract of 168 unique citations were scanned, of which 53 were included for a full-text review. A total of 24 randomized controlled trials were included, predominantly examining message framing on cancer prevention and detection behavior change interventions. There were 9 studies that used attitude to predict message framing effect and 16 studies that used intention, whereas 6 studies used behavior to examine the message framing effect directly. The use of loss-framed messages improved cancer detection behavior (OR 0.76, 95% CI 0.64-0.90;
Research has shown that it is almost impossible to change people's attitudes or intentions about cancer prevention and detection with a gain-framed or loss-framed message. However, loss-framed messages have achieved preliminary success in persuading people to adopt cancer detection behaviors. Future studies could improve the intervention design to achieve better intervention effectiveness.
Cancer accounts for 1 in 6 deaths globally. The number of cancer cases worldwide may increase by 60%, especially in low-income and middle-income countries where the increase may be as high as 81%, as estimated by the latest World Cancer Report [
Message framing is an effective technique to change health behavior [
Health behaviors include disease prevention and detection behavior [
The concept of message framing is an essential strategy in health promotion, but research on how to optimally frame cancer prevention and detection messaging is scarce. Furthermore, while the effectiveness of message framing in cancer prevention and detection remains unclear, there is still an increasing number of related studies that combine message framing with other variables (ie, color) to verify the strengthening or weakening of the framing effect. Therefore, a thorough examination of the effectiveness of the message framing in the context of cancer is needed.
This review mainly aims to systematically summarize the characteristics of the relevant intervention studies and then pool the effect sizes from the relevant studies to quantify the effects of those interventions on attitude, intention, and behavior change. The findings of this review can provide recommendations for researchers and clinicians to design effective messages in cancer communication.
This review was conducted and is reported according to the PRISMA (preferred reporting items for systematic reviews and meta-analyses) guidelines. As mentioned in the initial registration (registration ID CRD42021252658), a series of structured electronic searches were performed in three English databases, including Web of Science, Scopus, and PubMed, focusing on the effectiveness of message framing related to a cancer topic and dated from January 1, 2000, to December 31, 2020. The procedures guiding article inclusion are presented in the flow chart in
All articles identified in the search strategy were exported into reference management software (version 2.48.0; Mendeley) for duplicate checking and further screening. The reference lists of eligible articles were further reviewed to identify other relevant studies. Relevant reviews that emerged from the search strategy were checked for any additional studies. Grey literature (ie, working papers, unpublished studies, conference proceedings or abstracts, and dissertations) was not considered eligible. The preliminary retrieval process was taken as the total literature volume combining the reviews independently completed by two authors. The authors selected a sample of eligible studies after achieving good agreement (κ=0.8356), with the remainder being selected by one author.
Preferred reporting items for systematic reviews and meta-analysis flowchart.
Studies were included if they met the following criteria: (1) participants (not cancer patient or survivors) of both genders and any age range exposed to either the loss-framed or the gain-framed cancer prevention or detection (not treatment) message in experimental research; (2) interventions that have been delivered via either emphasizing the expected benefits of taking specific health behaviors (gain-framed message) or the possible loss of not taking specific health behaviors (loss-framed message); (3) the gain-framed and loss-framed message must come in pairs as a comparison and related to a specific cancer topic, not cancer in general; (4) the effectiveness of cancer-related messages was measured in terms of change in attitude (by scale), intention (by scale), and behavior (by yes or no), and the analysis of primary data was reported, and sufficient quantitative data was provided for estimating the total effect size. In addition, only randomized controlled trials (RCTs) were included. Finally, published studies that repeatedly used the same data were excluded, leaving only one study that reported the most complete results.
Data from a sample of eligible studies was extracted by two authors, and after they achieved good agreement (κ=0.9804), the remainder was extracted by one author. The main framework of the extraction criteria was drawn by the authors altogether. The following information was extracted: (1) basic study characteristics including the first author, publication date, country, and funding of the study; (2) participant characteristics including sample size, age, ethnic, and gender ratio (female); (3) intervention characteristics including cancer type, research setting (lab or not), message contents, message resources, message delivery channel, intervention duration, and underpinning theories; (4) outcome measures including measurement of the outcomes; and (5) main results including intervention completion ratio and converted effect size (standardized mean difference [SMD] and odds ratio [OR]).
The risk of bias for RCTs was independently assessed by two authors (κ=0.8137) using the Cochrane Collaboration tool for assessing bias [
All meta-analyses were performed with Review Manager 5.3 (version 5.3; The Cochrane Collaboration) [
The literature search identified a total of 319 studies extracted by two authors. After deduplication, a total of 168 studies’ titles and abstracts were screened, with 53 remaining for full-text screening. Among those, 24 articles met the inclusion criteria, and 4 studies met the inclusion criteria but did not meet the exclusion criteria. The authors attempted to obtain the research data of 8 studies that met the first two inclusion criteria but failed to provide usable data by contacting their corresponding authors via email and received 2 replies [
The total sample size was 11,637, ranging from n=85 (intervention group) to n=752 (control group). The participants’ average age ranged from 12 to 91 years. Because some cancers are associated with a particular sex, 2 studies notably recruited all-male participants [
Most of the experiments were conducted online, through email [
As shown in
Risk of bias summary of the individual studies (k=24).
Risk of bias graph.
In the following sections, the synthesized results regarding attitude-related, intention-related, and behavior-related outcomes are introduced individually. The main results are visualized in the forest plot.
Attitudes are commonly defined as “a psychological tendency that is expressed by evaluating a particular entity with some degree of favor or disfavor.” In this study, an attitude refers to the tendency towards engaging in a particular behavior or object targeted by a study's intervention.
The attitude was used to indicate the persuasiveness of cancer-related messages in 9 studies. The relevant data involved a total of 3277 participants, including 1647 in the gain group and 1630 in the loss group. As seen in
The medium heterogeneity can be attributed to the study by Kim [
The funnel plot (
Forest plots of cancer detection attitude and cancer prevention attitude.
Intention refers to a state of wanting, planning, or expecting to act in a given way. It can be general (ie, intending to mammogram) or specific (i.e., intending to mammogram in 3 months). In this study, the difference between intentions and other related cognitions such as expectations or willingness was not distinguished.
The intention was used to indicate the persuasiveness of cancer-related messages in 16 studies. The relevant data involved a total of 5289 participants, including 2763 in the gain group and 2526 in the loss group. As shown in
Because the large heterogeneity can also be attributed to the study by Kim [
The funnel plot (
Forest plots of cancer detection intention and cancer prevention intention.
In most cases, behavioral measures are obtained by researchers using self-reported data from participants through follow-up surveys. However, it does not rule out the existence of special access to behavioral data (eg, a health insurance database record).
Behavior was used to indicate the persuasiveness of messages about cancer detection in 6 studies. The relevant data involved a total of 3071 participants, including 1543 in the gain group and 1528 in the loss group. It should be mentioned that cancer detection behavior was measured twice in Schneider et al [
There was often a time interval between cancer detection behavior and the experiment in which the participants read the framed messages. For the five measurements of cancer detection behavior that were performed within 6 months after the experiments, loss-framed messages were still significantly more persuasive than gain-framed ones (OR 0.76, 95% CI 0.61-0.95;
The funnel plot (
Forest plots of cervical cancer detection behavior and breast cancer detection behavior.
Given that significant results were obtained for cervical or breast cancer detection behavior, 4 studies of detection attitude or intention focusing on either of these two cancers were extracted to examine the relationships between behavior and attitude or intention. Excluding Kim [
This study meta-analyzed 24 empirical studies on the persuasive effect of message framing in cancer prevention and detection. By subdividing the convincing effect into three dimensions, attitude, intention, and behavior, the results show that gain-framed and loss-framed messages have no significant differences in people's attitudes and intentions to change their cancer prevention or detection behavior. However, for cancer detection behavior, especially breast and cervical cancer detection, loss-framed messaging is more persuasive than gain-framed messaging, and this effect gradually weakens over time.
This meta-analysis did not identify any advantages of gain-framed messaging. Previous studies have proposed that gain-framed messaging is more persuasive than loss-framed in disease prevention, especially preventative behavior [
This meta-analysis also supports some of the results of previous studies. Neither gain-framed nor loss-framed messaging can exert the framing effect of changing people's attitudes or intentions [
One interesting finding of this meta-analysis is that the message framing effect is time-limited. Others have questioned the duration of the framing effect in explaining the declining return rate [
Another notable result of this study is the disconnect between people's attitudes, intentions, and behavior. When reorganizing data related to attitudes and intention for breast and cervical cancer prevention and detection, these results also show that attitudes and intentions cannot effectively predict behavior, indicating that there may indeed be a disconnect between people's attitudes, intentions, and behavior. This conclusion has also been confirmed by previous studies [
As with all meta-analyses, this study was limited by the included literature measurement indicators and provided data. For example, the measurement data of attitude and intention included in the literature far exceed behavior-related data. Cancer detection behavior data were obtained only due to the lack of actual behavioral data related to cancer prevention. Also, the data are limited to two types of cancer (breast cancer and cervical cancer). Its generalizability also needs to be further verified based on more relevant research. Due to the low email response rate (2 out of 8), this meta-analysis excluded some studies meeting the inclusion criteria.
This meta-analysis shows that gain framing and loss framing have no significant difference in attitudes and intentions about cancer prevention and detection. On the other hand, loss framing can promote breast cancer and cervical cancer detection better than gain framing. However, the effect of the loss framing gradually weakens over time. Therefore, when constructing a message to promote cancer detection, more considerations can be given to loss framing’s promised short-term effects. People can be screened for related cancers quickly by emphasizing the possible risk of not performing cancer detection.
Detailed records of eligible studies.
Funnel plot depicting the publication bias of attitude-related studies.
Funnel plot depicting the publication bias of intention-related studies.
Funnel plot depicting the publication bias of behavior-related studies.
odds ratio
preferred reporting items for systematic reviews and meta-analyses
randomized controlled trial
standardized mean difference
AA acknowledges financial support from the National Natural Science Foundation of China (grant 71661167007).
AA and FM conceptualized the study design. AA and SZ collected and analyzed the data. AA, SZ, and XA interpreted the results and wrote the manuscript. AA and SZ revised the manuscript. All authors have read and approved the final draft of the manuscript.
None declared.