Lessons Learned from Diverse Efforts to Change Social Norms and Opportunities and Strategies to Promote Behavior Change in Behavioral Health: Proceedings of Two Workshops (2017)
Chapter: 5 case studies in changing social norms, 5 case studies in changing social norms.
Joanne Silberner introduced the last panel of the workshop, which focused on media and communication campaign strategies used to improve social norms, beliefs, and attitudes in health-related arenas in which negative social norms, chronicity, and behavior change are relevant. Joan Austin, professor emeritus, Indiana University, addressed stigma and negative attitudes toward epilepsy and efforts to change them. Janet Turan, associate professor of public health, University of Alabama at Birmingham, presented her research on HIV-related stigma in different settings, globally and in the United States. Kay Cofrancesco, who was scheduled to speak on the stigma of lung cancer, was unable to attend.
EPILEPSY: SOURCES OF STIGMA AND CAMPAIGN EFFORTS
Attitudes and beliefs.
Austin introduced herself as a psychiatric mental health nurse who works with children who are trying to decide whether to tell their friends they have epilepsy. She began her presentation by providing background on the scope of the problem. Gallup Polls carried out every 5 years from the 1950s to 1980s showed improvement in attitudes toward epilepsy ( Caveness and Gallup, 1980 ). The last survey was done in 1987 and although it showed better awareness, two-thirds of the respondents reported that they would put something in the mouth of a person having a seizure; one-third continued to think less of people with epilepsy and their
families; and one-sixth thought they could identify people with epilepsy just by looking at them ( LaMartina, 1989 ).
It was not until the early 2000s, Austin said, that the field began to understand the dimensions of attitudes related to epilepsy, and through use of the Centers for Disease Control and Prevention’s instrument Attitudes and Beliefs about Living with Epilepsy, four dimensions were examined. The first dimension, Negative Stereotypes, has such items as “not as smart” and “should not marry.” Second, the Risk and Safety Concerns dimension has such items as “do not let your child ride in the car if the driver has epilepsy” or “you would not hire a babysitter with epilepsy.” The third dimension, Work and Role Expectations, has such items as people with epilepsy are “not able to cope with everyday life” and “not as successful at work as others.” The fourth dimension, Personal Fear and Social Avoidance, has items assessing whether people “feel nervous when they’re around people with epilepsy” or “would not date a person with epilepsy.”
Austin pointed out that surveys with nationally representative samples have shown that people are least likely to agree now with those negative stereotypes, but they are most likely to agree with risk and safety concerns. There is moderate agreement on work and role expectations, with some expectation that individuals with epilepsy are not going to do as well on the job and some discomfort around people with epilepsy ( Diiorio et al., 2004 ). Research is currently ongoing to examine how these attitudes and beliefs may have changed between 2005 and 2013.
Since 2000, Austin reported, the Epilepsy Foundation has conducted yearly multifaceted campaigns to increase awareness and public education about epilepsy. Because of limited funds coming only from donations, it has targeted groups with the lowest awareness, the most negative perceptions, or the most negative attitudes. The foundation has worked with teens, tweens, and young adults and with ethnic minority groups, including African Americans, Hispanic Americans, and Asian Americans. Austin noted that the methods used have varied but have included mass media, such as DVD, the Internet, print, radio, social media, and television, as well as celebrity endorsement ( Price et al., 2015 ).
Entitled to Respect Campaign
Austin identified the most successful campaign as one conducted in 2001 to 2004 with the theme of Entitled to Respect. The main goals, she said, were to increase teens’ awareness of epilepsy and to increase self-esteem among teens with epilepsy. The campaign started with teens ages 13 to 18 and then was extended to tweens and then African American youth under the theme of Get the Word Out. Austin explained that one of the reasons for targeting teens was that, prior to the launch, a survey conducted
nationwide among approximately 20,000 teens found that two-thirds knew either nothing or very little about epilepsy. Five different conditions were compared (asthma, breast cancer, diabetes, HIV, Parkinson’s) against epilepsy, and knowledge about epilepsy was the lowest at 8 percent. Two-thirds of respondents did not know what to do if someone had a seizure. Austin asserted that, given that epilepsy is most prevalent among young people and those over 65, the fact that most young people did not know what to do when someone is having a seizure was not a good thing (especially because children with epilepsy may have their first seizure at school). She reported further that half of respondents were not sure whether epilepsy is contagious, and less than one-third would date a person with epilepsy ( Austin et al., 2002 ).
The campaign’s message, Austin said, was that youth with epilepsy are entitled to respect just like everyone else. She characterized this as an awareness and educational campaign, focused primarily on outreach through teen media channels. With support from the popular music group NSYNC, the campaign used “E2R” public-service radio messages with music from NSYNC’s recently released CD so teens could hear the music they liked with a message about epilepsy. The campaign’s webpage was linked to NSYNC’s website and six other sites that were popular with teens, and television, posters, brochures, and contests also were used.
A postcampaign survey in 2007 showed overall improvement, Austin reported, with Latino and Hispanic youth improving the most. The lack of awareness decreased from two-thirds to less than one-fourth; knowledge that epilepsy was not contagious increased from one-half to two-thirds; and teens were more informed that people with epilepsy could work and drive. Austin noted that one of the areas that did not improve was uncertainty and misinformation as to what to do if someone has a seizure. Youth with epilepsy were still seen by their peers as being less likely to be popular.
Regular Education and Outreach
Austin added that the Epilepsy Foundation also has ongoing efforts to educate specific groups of people who have regular contact with individuals with epilepsy and those who need to know how to handle seizures. These targeted groups include child and adult daycare workers, first responders, law enforcement personnel, middle and high school students, parents of children with epilepsy, and school nurses. Austin has been most involved in the effort for school nurses. She reported that regular evaluations have shown that school nurses have shown increased confidence in recognizing and handling seizures after the training ( Austin et al., 2002 ).
Progress in the Field and Challenges
According to Austin, a major event in the epilepsy field was the 2012 release of an Institute of Medicine (IOM) report on the public health dimensions of epilepsy ( Institute of Medicine, 2012 ). She asserted that the study’s recommendations had major impacts on the field. One recommendation was to inform the media to improve awareness and eliminate stigma by promoting more accurate storylines and depictions of epilepsy. A second was to coordinate public awareness efforts to develop shared messages, an area in which Austin said the IOM report had a large impact. There are about 30 voluntary organizations involved in various aspects of epilepsy. In the last year and for the first time, Austin said, they have all been working together. She added that because of all of the inaccurate information among the public, the IOM committee developed eight key messages with accurate information about epilepsy for use by health educators.
Austin also discussed the challenges that persist in the field. First, epilepsy is a spectrum disorder with a wide range of severity, seizure types, and co-occurring conditions. Two out of three people with epilepsy seizures are very well controlled and are able to function well. Others struggle with epilepsy, having frequent seizures that are not controlled and having tried every medication and every treatment. Austin explained that, given this wide spectrum, messaging is very complicated. The objectives can vary, she said, and messages can appear to conflict depending on the subgroups being targeted.
Another issue Austin noted is that campaigns often are not evaluated for change in follow-up surveys because of cost. In addition, she said, evaluations focus mainly on process outcomes, such as campaign reach ( Price et al., 2015 ).
An additional challenge Austin highlighted concerns two studies conducted 25 years apart, in 1981 and 2006 ( Collins et al., 2007 ). Findings showed that about one-half of the respondents believed that violence is possible or likely during a seizure. The results were unsettling, Austin said, because respondents were medical students, law students, and people with epilepsy. The items included such questions as how likely respondents thought certain violent acts were to be caused by seizures. Austin said there clearly is a great deal of work ahead. Despite years of educational campaigns about proper response to seizure, she noted, the field continues to be challenged by common myths that persist, such as putting something in someone’s mouth during a seizure and calling an ambulance for the person. She said the Centers for Disease Control and Prevention is currently considering new communication methods, and she emphasized the need for research in the field to help identify appropriate messages.
REDUCING HIV-RELATED STIGMA IN HEALTH CARE SETTINGS: FROM AFRICA TO ALABAMA
Turan spoke about efforts to change and reduce HIV-related stigma and discrimination through face-to-face, hands-on, grassroots approaches in health care settings. She noted that people who live with stigmatized health conditions often have frequent contact with health care providers, and a large body of literature suggests that fears of stigma and discrimination and of lack of confidentiality can discourage people from accepting testing and diagnosis for their condition and linking to the services they need.
Turan showed a slide of a framework developed by Laura Nyblade of the Research Triangle Institute that summarizes some of the key lessons learned in the HIV field on the components of effective stigma reduction interventions. The first is to address the immediately actionable drivers of stigma and discrimination, such as lack of awareness, values that cause shame and blame, and fears and misconceptions (e.g., about how HIV is transmitted). The second is putting affected groups at the center of the response by developing and strengthening networks of people living with the condition, empowering them and strengthening their capacity, and addressing the issue of internalized or self-stigma. The third is creating partnerships between the affected groups and opinion leaders, service providers, or policy makers. According to Turan, the most successful interventions include all three components.
A Health Setting-Based Stigma Reduction Intervention in Five African Countries
Turan then described an intervention developed in sub-Saharan Africa that was adapted for a setting in the United States. The principal investigator of the study was William Holzemer, a committee member (see Uys et al., 2009 , for more information). The intervention has three important components, which correspond to those described above.
The first component, Turan said, is sharing information. During workshops, she reported, results of local data on HIV-related stigma are shared, and general information about how stigma impacts the lives of people living with HIV is provided. The second component involves increasing contact by bringing together the affected group and a group of health workers to plan stigma reduction activities. The third component is improving coping through empowerment. People who are living with HIV are involved in an activity in which they can address stigma directly, not just accept it, live with it, or cope with it.
Being inspired by this intervention and after discussing it with Holzemer, Turan, and colleagues decided to adapt the intervention for their setting
in Birmingham, Alabama. She noted that other pilots were being conducted to see how well the intervention would work in the United States. In Birmingham, local data were collected and analyzed initially to learn the current status of stigma and discrimination around HIV. Turan and colleagues also examined data on at-risk populations, and a large survey of public health and primary health care workers and focus groups with people living with HIV were conducted in the state.
Turan said she did not have time to describe all the modifications made to the original workshop model, but the workshop did have to be shortened to accommodate the busy schedules of the health workers and consumers. Importantly, a module on other intersecting stigmas and discrimination was added, addressing racism, stigma attached to poverty, and discrimination according to sexual orientation. Turan noted that the workshop also was adapted to include the development of stigma reduction projects that could reach the larger population of health workers in the region.
As implemented in Birmingham, Turan reported, the workshop was attended by health workers and consumers and was facilitated by a health worker (or social worker) and a consumer. It was conducted at the University of Alabama at Birmingham School of Public Health for a full day, followed by a half-day 2 weeks later. Topics addressed included understanding stigma, different intersecting stigmas, outcomes of stigma, coping with stigma, why stigma is difficult to change, stigma reduction strategies, and the design of a tool to reach public health and primary health care workers. According to Turan, a powerful part of the workshop was when people worked in pairs and told each other a story about when they experienced stigma and discrimination. Everyone, she said, had such a story to share.
In designing a tool to reach a wider group of public health and primary health care workers in the state, Turan said, attendees worked in small groups of health workers and consumers. Two iterations of the workshop have been conducted, the first with 13 participants and the second with 23. The health workers were from local and state health departments, local AIDS service organizations, and university clinics. Turan added that the workshops were evaluated with pre and post questionnaires.
Preliminary Results of the Birmingham Pilot
In terms of the demographics of attendees, Turan reported, ages ranged from 23 to 70, 73 percent were African American/black, 27 percent were Caucasian/white, and 67 percent were women. She noted that the definition of health workers was broad and included physicians, nurses, health educators, social workers, research coordinators and staff, administrative support personnel, and radiology technicians. She explained that this array of health workers was included because it was recognized that much of the
stigma and discrimination faced in health care settings does not necessarily come from nurses or doctors but from receptionists, record keepers, or lab personnel. She noted that clients often reported stigma from administrative staff or receptionists.
Turan added that the sample size was very small for this pilot, but it was found to be feasible to recruit and engage both health workers and consumers (people living with HIV). Fully 87 percent of consumers and 89 percent of health workers rated their workshop experience as “excellent.” According to Turan, preworkshop and postworkshop comparisons showed that consumers’ scores on negative self-image, disclosure concerns, and enacted stigma tended to be lower in the post-test than in the pretest. However, she said their concern about public attitudes was higher. She suggested that perhaps they were more aware of some of the public attitudes after the workshop. Among providers, empathy scores tended to be higher in the post-test than in the pretest. Turan said these were promising initial results that could be taken further. 1
Turan added that the ideas for reducing stigma in health care settings that emerged from the workshops focused on reaching medical personnel early, when they are in training, through interactive workshops, TED talks, or roleplay experiences. She closed by saying that combining informational, contact, and empowerment strategies holds promise for use in other areas involving stigma and discrimination that hinder the psychological well-being, health care utilization, and health outcomes of people living with the stigmatized conditions.
The discussant of this workshop session was William Holzemer, committee member. He noted first that the two presentations had brought out issues related to internalized stigma, whereas previous sessions had focused more on external, socially based, and structural stigma. Effecting change in social norms at these external, social, and structural levels may still be elusive in communities, he said, but the presentations had showed how it is possible to reach out to people and help them address how they react to the stigma themselves in terms of self-worth and self-care. He remarked that an important remaining frontier is to confront the large number of people who are living with HIV who do not receive the testing, care, and medications they need. Similarly, he asserted, much more work needs to be done to overcome the challenges in achieving real behavior change even though attitudes may change in desired directions.
1 Results from these pilot workshops have subsequently been further analyzed and published in Batey et al. (2016) .
Topics discussed at the end of this panel focused primarily on intersecting stigma. Others included approaches to promoting positive behaviors and the postcampaign survey of the Entitled to Respect campaign. The session ended with brief final remarks from the chair of the Committee on the Science of Changing Behavioral Health Social Norms.
In response to a question about how to address intersecting stigma in primary care, Turan replied that this is currently a cutting-edge area of intervention and research and is extremely complex. For example, if a black woman living with HIV who is poor and is also a lesbian presents in a primary care clinic, how does one understand her experience, and how do those different identities contribute to that experience? Turan noted that the University of Alabama has a study of this issue under way using mixed methods. A major focus is in-depth qualitative interviews with such women to try to understand how this experience of having multiple identities affects them and their health, well-being, and service utilization. Quantitative measures of poverty, stigma, racism, and homophobia are also being used to examine how these factors are associated with outcomes.
Austin said she deals with some populations in which mental health issues are very prominent in people with epilepsy, especially mood disorders in adults and attention deficit disorder and autism spectrum disorder in children. Families often will say that the seizures are not the problem, she explained, but rather the behavioral issues they are dealing with. Intervention starts with where the families’ issues are, she said.
Pescosolido remarked that conducting research on intersecting stigma is very challenging because every time a factor is added, whether in qualitative, experimental, or social survey research, there must be a corresponding increase in the number of cases, which makes studies more difficult to carry out. The other issue, she said, is that people themselves may have difficulty reporting accurately on their experiences of intersecting stigma because they may not be able to differentiate the effects of the stigma arising from each source.
An audience member commented that research is lacking at the national level concerning stigma itself, let alone multiple intersecting types. This speaker’s national surveys have included items about attitudes toward psychiatric medications and mental health. The surveys have found very few differences between Caucasians and African Americans, except with respect to medical research, a topic that elicited skepticism and evoked the history and trajectory of Tuskegee. People who had or saw serious problems with mental health wanted treatment regardless of their race. This same speaker also said that research on attention deficit hyperactivity
disorder and African American parents suggests there is certainly a stigma, but how it compares with that experienced by other groups is unknown. National surveys do not include large enough numbers of participants in different groups for comparison, this speaker noted, especially in panethnic communities.
Turan added that the study her group is conducting on this topic is within the Women’s Interagency HIV study, which includes a large national cohort of women living with HIV and a large representation of minorities. So at least for women, she said, there may be opportunities to examine some of these issues in a large dataset.
Audience member Vanessa Wellbery commented that she has learned from people working in the field of domestic violence that introducing the subject of intersecting mental illness further stigmatizes women who are suffering from domestic violence. Pescosolido responded that she sees this a great deal in the mental health community. At Indiana University, she is conducting a college toolbox project that is sponsored by Bring Change to Mind. The idea is to address differences in general, with mental illness being one of the prominent differences portrayed.
Promoting Positive Behaviors
The discussion of this topic started with a question about whether there is any research on the efficacy of promoting positive behaviors instead of discouraging negative ones. William Holzemer replied first, saying that Kate Lorig from Stanford had published a great deal on self-management, which really is an orchestrated training program on total health management with an emphasis on wellness, even for people with diagnosed chronic illnesses. Turan commented that in the HIV/AIDS arena, positive role models are now being used, with greater focus on such topics as coping, resilience, and how many people are doing well living with HIV/AIDS. From the research point of view, effort is focusing on how to measure such indicators as resilience, coping, social support, and other factors that help people deal with these conditions. Austin agreed, noting that her group’s interventions with people with epilepsy are more self-management oriented, focusing on their whole lives and using some of the material from Lorig’s research.
Follow-up Question on the Postcampaign Survey of the Entitled to Respect Campaign
Austin was asked to provide more information about the rationale and methods used for the 2007 survey conducted to follow up on the Entitled to Respect campaign. She replied that it was a Harris Interactive survey with a stratified sample. She added that no follow up had been carried out since
then, which she finds unfortunate. She added that this is another reason why it is good news that all of the organizations focused on epilepsy are coming together now to coordinate planning and programs, which she said will also help support and sustain communication initiatives.
Austin was asked about the different approaches that have been used for messaging and which ones may be best, especially with lower resource levels. She replied that the focus is more on depth than on breadth. Part of the issue is money, but her group also is targeting those most at risk for poor care and is getting involved more with the community, churches, and health care providers.
The last session of the day was to be a panel of committee members reflecting on the lessons learned during the workshop. However, because all of the prior discussions had been rich and the end of the day was near, it was decided that the workshop would be adjourned following brief remarks from David Wegman, chair of the Committee on the Science of Changing Behavioral Health Social Norms. Wegman remarked that the day’s presentations and discussions about the basic and applied science behind communication campaigns, as well as the implementation and evaluation of campaigns in various areas of public health, had indeed been very complex and thought provoking. He noted that it is apparent how challenging it would be to synthesize the multilayered evidence on planning communication strategies for changing social norms in behavioral health. He closed by saying that the April 2015 workshop would focus on applications of the science directly to campaigns and approaches in behavioral health.
In 2015, the National Academies of Sciences, Engineering, and Medicine convened two workshops with oversight from the Committee on the Science of Changing Behavioral Health Social Norms. The workshops provided input to the committee’s deliberations and contributed to the development of the report Ending Discrimination against People with Mental and Substance Use Disorders . That report was issued to help the Substance Abuse and Mental Health Services Administration and the Office of the Assistant Secretary for Planning and Evaluation, U.S. Department of Health and Human Services, utilize the scientific evidence base in improving public attitudes toward and understanding of behavioral health, specifically in the areas of mental health and substance use disorders. This publication summarizes the presentations and discussions at the two workshops.
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- Published: 17 December 2018
Social norms and how they impact behaviour
- Katherine J. Reynolds 1
Nature Human Behaviour volume 3 , pages 14–15 ( 2019 ) Cite this article
- Human behaviour
There is wide interest in the social norms construct across psychology, economics, law and social marketing. Now a study investigates an important missing piece in the social norms’ puzzle: what is the underlying process that explains how norms impact behaviour? The answer: self–other similarity (self-categorization) and internalization.
In another example of a successful social norms intervention, Nolan and colleagues 2 found that household energy use was reduced the most when people were presented with a descriptive normative message (‘most people in your community are finding ways to conserve energy’) compared with messages that highlighted self-interest (‘the time is right to save money on your home energy bills’), environmental protection (‘the time is right for reducing greenhouse gases’) or social responsibility (‘we need to work together to save energy’). There are numerous other examples across a wide range of behaviours (for example, tax compliance and binge drinking), showing that knowledge of what others do affects people’s own behaviour in significant and important ways.
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- Systematic review
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- Published: 07 January 2021
How effective are social norms interventions in changing the clinical behaviours of healthcare workers? A systematic review and meta-analysis
- Mei Yee Tang ORCID: orcid.org/0000-0002-3116-6025 1 , 2 ,
- Sarah Rhodes 1 ,
- Rachael Powell 3 ,
- Laura McGowan 3 ,
- Elizabeth Howarth 1 ,
- Benjamin Brown 4 , 5 &
- Sarah Cotterill 1
Implementation Science volume 16 , Article number: 8 ( 2021 ) Cite this article
Healthcare workers perform clinical behaviours which impact on patient diagnoses, care, treatment and recovery. Some methods of supporting healthcare workers in changing their behaviour make use of social norms by exposing healthcare workers to the beliefs, values, attitudes or behaviours of a reference group or person. This review aimed to evaluate evidence on (i) the effect of social norms interventions on healthcare worker clinical behaviour change and (ii) the contexts, modes of delivery and behaviour change techniques (BCTs) associated with effectiveness.
Systematic review and meta-analysis of randomised controlled trials. Searches were undertaken in seven databases. The primary outcome was compliance with a desired healthcare worker clinical behaviour and the secondary outcome was patient health outcomes. Outcomes were converted into standardised mean differences (SMDs). We performed meta-analyses and presented forest plots, stratified by five social norms BCTs ( social comparison , credible source , social reward , social incentive and information about others’ approval ). Sources of variation in social norms BCTs, context and mode of delivery were explored using forest plots, meta-regression and network meta-analysis.
Combined data from 116 trials suggested that social norms interventions were associated with an improvement in healthcare worker clinical behaviour outcomes of 0.08 SMDs (95%CI 0.07 to 0.10) ( n = 100 comparisons), and an improvement in patient health outcomes of 0.17 SMDs (95%CI 0.14 to 0.20) ( n = 14), on average. Heterogeneity was high, with an overall I 2 of 85.4% (healthcare worker clinical behaviour) and 91.5% (patient health outcomes). Credible source was more effective on average, compared to control conditions (SMD 0.30, 95%CI 0.13 to 0.47, n = 7). Social comparison also appeared effective, both on its own (SMD 0.05, 95%CI 0.03 to 0.08, n = 33) and with other BCTs, and seemed particularly effective when combined with prompts/cues (0.33, 95%CI 0.22 to 0.44, n = 5).
Social norms interventions appeared to be an effective method of changing the clinical behaviour of healthcare workers and have a positive effect on patient health outcomes in a variety of health service contexts. Although the overall result is modest and variable, there is the potential for social norms interventions to be applied at large scale.
PROSPERO CRD42016045718 .
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This is the first systematic review and meta-analysis on the use of social norms interventions to change the clinical behaviour of healthcare workers, and the results suggest that, on average, these interventions are effective.
Social norms interventions may be effective across a range of health service contexts and modes of delivery, but the effects are variable.
These findings contribute to a recognised gap in the literature, by highlighting which social norms interventions may be most effective: this can inform the design of future interventions aimed at improving health professional practice.
Healthcare workers routinely perform behaviours in clinical settings which impact all aspects of patient care including diagnoses, treatment and recovery. There are best-practice guidelines for many of these clinical behaviours. For example, regular blood glucose testing for diabetic patients. Healthcare workers face many challenges in following evidence-based professional practice such as lack of time, competing demands and requests from patients. Although there are no reliable published estimates of how well healthcare workers follow best clinical practices, 1 in 20 hospital admissions is caused by adverse drug events [ 1 ], and approximately half of these globally are believed to be due to lapses in best practice in terms of prescribing or monitoring behaviours by clinicians [ 2 ].
Social influences are important in clinical practice: prescribers of antibiotics have reported that pressure from patients and other prescribers in their networks influence their prescribing behaviours [ 3 ]. Social norms can be broadly considered as the perceived implicit or explicit behavioural rules that one uses to determine the appropriate and/or typical expectations, beliefs, attitudes and behaviours of a social reference person or group [ 4 ]. We have defined a social norms intervention as one which seeks to change the clinical behaviour of a target healthcare worker by exposing them to the values, beliefs, attitudes or behaviours of a reference group or person. The target healthcare worker is the person at whom a social norms intervention is aimed, with a view to changing their clinical behaviour. The reference person or group describes a person or group whose values, beliefs or behaviours are exposed to the target. Social norms interventions sometimes report a peer benchmark, such as the top 10% of the reference group or the average performance: the downside of the average approach is that the above-average performers will receive feedback suggesting that they are already performing better than their peers, and this may lead them to reduce their effort [ 5 ].
Behaviour change interventions based on social norms may help overcome barriers to healthcare workers implementing recommended practice through: persuasion, encouraging collaboration to achieve change, observing good practice from elsewhere and support from management [ 6 ]. There are various explanations of the processes through which social norms impact on behaviour according to social and health psychology theories. Social comparison theory [ 7 ] proposes that individuals draw on social comparisons to evaluate one’s abilities and perform behaviours which will bring one's abilities in line with those of others in the group. According to the social identity perspective [ 8 ], people make evaluations about their own group (‘in group norms’) against other groups (‘out group norms’). They are motivated to preserve their social identity (as part of their ‘in group’) by behaving in similar ways to the group’s normative behaviour. ‘Subjective norm’ is a construct within the Theory of Planned Behaviour [ 9 ], which describes an individual’s perception of whether valued others think they should perform a behaviour, combined with a motivation to comply with others’ beliefs.
A social norms intervention with a descriptive norms [ 10 ] message provides the target with information about the behaviour of others in the reference group (such as providing a nurse with information about the behaviours of nurses regarding wound dressing). An injunctive norms message provides the target worker with information about the values, beliefs or attitudes of the reference group towards a particular behaviour, conveying social approval or disapproval (e.g. saying that colleagues disapprove of ordering unnecessary tests). This includes approval, praise, commendation, applause or thanks.
Audit and feedback (A&F) is a quality improvement technique used by health services, where data is collected on healthcare worker performance and then a summary is reported back to the individual [ 11 ]. Social norms interventions are sometimes included as one component of A&F, usually by providing descriptive norms of others’ behaviour [ 12 , 13 ]. A&F has already been shown to be effective in changing healthcare worker behaviour, but with large variation in outcomes depending on the context and the intervention design [ 14 ]. There is a need to understand the ingredients for successful A&F [ 11 , 15 ], and the effects or mechanisms of the ‘social influence’ constituents of A&F have been identified as topics for further research [ 11 ]. Our review contributes to this important research agenda by systematically examining the evidence for using social norms interventions with healthcare workers.
Identification of the individual components within social norms interventions can aid understanding of the precise aspects that influence behaviour. The Behaviour Change Techniques Taxonomy v1 (BCTTv1) [ 16 ] is a framework for classifying BCTs, which are the ‘active ingredients’ of behaviour change interventions. The taxonomy defines 93 distinct BCTs, grouped into categories. There is no explicit category that relates to social norms. For this review, five BCTs were considered to involve social norms: ‘ 6.2. Social Comparison’ , ‘6.3. Information about Others’ Approval’ , ‘9.1. Credible Source’ , ’10.4. Social Reward’ , and ’10.5. Social Incentive’. The numbers follow the BCTTv1 labelling and definitions are listed in Table 1 .
The aim was to conduct a systematic review to assess the impact on healthcare workers’ compliance with professional practice recommendations of interventions delivering social norms BCTs, compared to controls. Two research questions were addressed:
What is the effect of interventions containing social norms BCTs on (a) the clinical behaviour of healthcare workers, and (b) resulting patient health outcomes?
Which contexts, modes of delivery and behaviour change techniques are associated with the effectiveness of social norms interventions on healthcare worker clinical behaviour change?
The study design was a systematic review with meta-analysis [ 18 ], meta-regression [ 19 ] and network meta-analysis [ 20 ]. This paper follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement [ 21 ]. Six members of the public attended workshops to discuss the relevance of the review to patients and carers, study design and dissemination. The group felt that patients can potentially have a role in changing healthcare worker behaviour, for example by reminding healthcare workers to wash their hands; or telling the General Practitioner (GP) they do not want antibiotics for a cold, although they were cynical about whether doctors would listen. In response, we changed our data collection to record whether any studies considered patients’ role in social norms interventions. Their advice on how to interpret our results to a broad audience will influence our future dissemination plans. An independent study steering committee, including a member of the public, provided encouragement and counsel throughout the project.
Protocol and registration
The study was registered on PROSPERO (CRD42016045718) and a protocol is available [ 17 ].
A search strategy was developed, following an iterative process of scoping searches. In July 2018, searches were undertaken in MEDLINE, PsycINFO, EMBASE, CINAHL, BNI, Cochrane CENTRAL and Web of Science (see Appendix 1 ). Backward and forward citation searching was not conducted, as per the protocol, due to time constraints.
Study inclusion criteria
Studies were included if they met the criteria in Table 2 .
Covidence was used to facilitate screening and data extraction [ 22 ]. One reviewer screened all titles and abstracts against the inclusion criteria; a second reviewer screened a 20% random sample to assess reliability. Studies included to the full-text stage were independently screened by two researchers. Any disagreements were resolved through discussion, moderation of a third researcher or team review.
Data from included studies were extracted using a tailored data extraction form ( Appendix 2 ) [ 23 ]. Information relating to the population and setting, methods, participant characteristics, intervention characteristics (delivery and BCT content), comparators, outcomes and results were extracted.
For the primary outcome (healthcare worker clinical behaviour), we extracted all available summary data on compliance of the healthcare worker with the desired behaviour at the time point closest to 6 months post-randomisation. Where multiple measures of compliance were reported we followed this list of priorities: (a) reported in sufficient detail to calculate standardised mean difference, (b) observed rather than self-report, (c) appropriate adjustment for clustering, (d) continuous measure, (e) final score rather than change from baseline, (f) described as primary outcome, (g) used to calculate sample size and (h) reported first. A similar approach was followed for patient health outcomes.
All identified BCTs (including both social norms and non-social norms) in all control and intervention arms of included studies were independently coded by two trained researchers using the BCTTv1 [ 16 ] and recorded on a BCT extraction form ( Appendix 3 ). The intervention descriptions from all relevant papers (including protocols, process evaluations or additional sources cited in the included studies) were coded to capture the BCTs as closely as possible. Inter-rater reliability for each of the BCTs that were present at least once across all arms was assessed using the prevalence and bias-adjusted kappa (PABAK) statistic (see Appendix 4 ), which adjusts for both the prevalence and occurrence of BCTs [ 24 ]. In circumstances where prevalence is low, the widely used chance-corrected kappa statistic is likely to underestimate reliability as it is highly dependent on prevalence [ 25 ].
Study quality assessment
Risk of bias was independently assessed by two researchers using the Cochrane Collaboration risk of bias tool. The percentages of high/low/unclear judgements for each criterion across included studies were calculated.
Any observed measure of healthcare worker behaviour was converted into a standardised mean difference (SMD, Cohen’s D ) comparing intervention and control groups [ 26 ]. Odds ratios were converted to SMDs [ 27 ]. Where necessary, the sign of the SMD was changed to ensure that a positive SMD represented an improvement in compliance with the desired behaviour.
Where data were from appropriately analysed cluster randomised trials or stepped wedge trials the reported adjusted standard errors were used. Where adjusted standard errors were not reported, we inflated them ourselves to account for clustering [ 28 ].
Where data were missing, we searched for companion papers. Missing standard deviations were estimated using any available information (e.g. p values, confidence intervals, range, interquartile range) or by searching for trials with similar outcome measures. For cluster randomised trials, we estimated the intracluster correlation coefficient (ICC) where necessary by taking the average of results from similar studies.
Where studies, including factorial trials, assessed more than one intervention, data were extracted for any comparisons that were relevant to the review, avoiding double-counting by dividing the number of participants in the control arm evenly between comparisons. Where there was more than one control arm, the comparison that was the purest test of a social norms intervention was utilised. Where a study was an appropriately analysed factorial trial the covariate and standard error that best estimated the effect of a social norms intervention was extracted.
All studies that reported a primary or secondary outcome measure that could be converted into an SMD were included in meta-analyses. The approach to utilising the five social norms BCTs in the analysis was to subtract the control arm BCTs from those in the intervention arm, to identify those BCTs that were the active ingredients being tested in the trial. The BCT feedback on behaviour was present alongside a social norm BCT in 88 of 100 comparisons and so we combined feedback on behaviour with the social norm BCT with which it appeared for the purpose of primary meta-analyses.
Fixed effects meta-analysis [ 29 ] and forest plots, stratified by BCT were used to assess the effect of social norms on the clinical behaviour of healthcare workers and patient health outcomes. Sources of variation in the type of social norm, context and mode of delivery were explored using both exploratory subgroup analysis and meta-regression [ 30 ]. Network meta-analysis [ 20 ] was used to (a) utilise all available data and therefore maximise power by including trials that compared two or more different types of social norms (in addition to those that compared a social norm intervention to a control) and (b) rank the different types of social norms intervention in order of effectiveness. A fixed effects approach to meta-analysis was adopted to yield a summary of the evidence in these trials (i.e. the average effect), rather than an estimate of a common underlying treatment effect. Random effects analyses are also reported.
Pre-planned sensitivity analyses assessed the robustness of the conclusions by excluding studies: at high risk of bias on key domains (allocation concealment, sequence generation, selective outcome reporting, attrition, other biases); with ‘mean percentage’ < 20% or > 80% (due to expected skewed distribution)’ with imputed standard deviations; using estimated ICCs; with and without feedback on desired behaviour.
There were 4428 citations screened at the title and abstract stage; 477 full-text papers were screened, of which 116 unique trials met the inclusion criteria. Ten of these trials did not report usable outcome data; therefore, a total of 106 trials contributed findings to the review (Fig. 1 , Appendix 5 ). Some studies had more than one trial arm, resulting in 117 included comparisons. The trial and intervention characteristics are summarised in Table 3 , and characteristics of each individual comparison are provided in Appendix 6 . There were 100 comparisons suitable for meta-analysis. These included studies testing social comparison ( n = 79) credible source ( n = 7) and social reward ( n = 2) against control. Other studies tested more than one social norm together: social comparison and credible source ( n = 6), social comparison and social reward ( n = 2), multiple social norms (more than two) together ( n = 4). Over half of the included trials were conducted in North America; most studies were set in primary care and hospitals, targeting doctors. A broad range of behaviours were targeted including prescribing, management of conditions and test ordering. Two thirds of the trials were cluster RCTs. The interventions were delivered in a variety of formats; a third was delivered on one occasion and the rest on multiple occasions. Most were delivered by someone outside of the target organisation, often an investigator, and three quarters aimed to increase, rather than decrease the behaviour. Some intervention characteristics were poorly reported; format and frequency of delivery were missing in a third of studies (Table 3 ).
Effects of interventions
Overall effects on clinical behaviours and patient outcomes.
Combined data from fixed effects meta-analysis suggested that social norms interventions were associated with an improvement in healthcare worker clinical behaviour of 0.08 SMDs (95%CI 0.07 to 0.10, n = 100 comparisons), and an improvement in patient health outcomes of 0.17 SMD (95%CI 0.14 to 0.20), on average. There was a large amount of heterogeneity with an overall I 2 value of 85.4% (primary) and 91.5% (secondary) suggesting that some studies reported substantially higher or lower effects than the average. However, I 2 is related to precision and rapidly approaches 100% when the number of studies is high [ 31 ]. Similar conclusions were drawn from random effects meta-analysis an overall improvement in healthcare worker clinical behaviour of 0.16 SMD (95%CI 0.11 to 0.21, I 2 = 85.4%, τ 2 = 0.043). Note that the random effects analysis was associated with a larger effect size and wider confidence interval because more weight is given to smaller trials. These results remained robust after all of our pre-planned sensitivity analyses ( Appendix 7 ).
Social norms behaviour change techniques
Meta-analysis, stratified by social norms BCTs indicated that two of the social norms BCTs had a positive effect on healthcare worker clinical behaviour (Fig. 2 ): credible source (with or without other BCTs) (SMD 0.30, 95%CI 0.13 to 0.47, n = 7) and social comparison (with or without other BCTs) (SMD 0.06, 95%CI 0.04 to 0.08, n = 77). Social reward may not be effective (SMD 0.03, 95%CI − 0.08 to 0.13, n = 2), based on a small sample. We did not find sufficient evidence to examine the effect of the other two social norm BCTs ( information about others’ approval and social incentive ). Multiple social norms delivered together were also effective on average (SMD 0.13, 95%CI 0.10 to 0.16). When we looked at the most common combinations of social norms BCTs alongside other BCTs, three types of social norms intervention were most effective, on average, compared to control (Table 4 ): credible source (0.30, 95%CI 0.13 to 0.47); social comparison combined with social reward (0.39, 95%CI 0.15 to 0.64); and social comparison combined with prompts and cues (0.33, 95%CI 0.22 to 0.44). Social comparison delivered with credible source (0.16, 95%CI 0.12 to 0.19), on its own (0.05, 95%CI 0.03 to 0.08) or with social support (unspecified) (SMD 0.10, 95%CI 0.04 to 0.16) were all effective, on average, compared to control. This was confirmed by network meta-analysis. Table 5 shows the different contexts and settings for the social norms BCTs and there does not appear to be any obvious patterns of use of the BCTs in particular contexts: social comparison, credible source and social reward are each used in multiple different contexts either alone or alongside other BCTs. Regression analysis suggests that results were consistent even after adjustment for context and setting. Illustrative case studies providing examples of the three intervention types found to be most effective (credible source, social comparison with prompts/cues, social comparison and social reward) are shown in Table 6 .
Fixed effects forest plot summarised by alternative categorisation of BCTs
Context and mode of delivery
Meta-analysis suggested that social norms interventions were effective in a variety of different contexts. The effect was seen with doctors on average (SMD 0.08, 95%CI 0.07 to 0.10, n = 68) and other healthcare workers (SMD 0.08, 95%CI 0.04 to 0.12, n = 12), but not with nurses and allied healthcare workers (SMD − 0.01, 95%CI − .012 to 0.11, n = 5). They appeared successful across a range of clinical behaviours, including prescribing (SMD 0.11, 95%CI 0.09 to 0.13, n = 21), arranging, conducting or administering tests/assessments (SMD 0.10, 95%CI 0.06 to 0.13, n = 21), and management and communication around health conditions (SMD 0.06, 95%CI 0.01 to 0.12, n = 23), but may be less effective with handwashing (SMD 0.04, 95%CI − 0.05 to 0.13, n = 3) and referrals to other health services (SMD − 0.08, 95%CI − 0.23 to 0.07, n = 3). The effects were similar in primary (SMD 0.07, 95%CI 0.05 to 0.09, n = 56) and secondary care (SMD 0.12, 95%CI 0.07 to 0.18, n = 27) but may be less effective in community (SMD 0.02, 95%CI − 0.05 to 0.10, n = 4) and care home (SMD 0.03, 95%CI − 0.05 to 0.10, n = 4) settings. The effect appears to be consistent, regardless of whether a peer benchmark (0.06, 95%CI 0.02 to .011, n = 13) or the average (0.11, 95%CI 0.09 to 0.13, n = 67) is included. On average, they were slightly less effective in increasing behaviours (e.g. increasing diabetes testing) than at reducing behaviours (e.g. reducing antibiotic prescriptions). The effect was similar regardless of who delivered the intervention and whether it came from within the organisation or from an external source. Interventions that were delivered once (0.25, 95%CI 0.21 to 0.30, n = 28) were more effective than those delivered more frequently (0.06, 95%CI 0.04 to 0.08, n = 47). Delivery by website was most effective (0.23, 95%CI 0.15 to 0.31, n = 8); delivery by email, in writing, and in mixed format were all consistent with the average effect, but face-to-face appeared to be ineffective (− 0.01, 95%CI − 0.06 to 0.03, n = 14). The number of studies in some of these categories was low (nurses and allied healthcare workers, handwashing, referrals to other services, community and care homes), and none of the pre-planned covariates for context and setting appeared to explain much of the heterogeneity in meta-regression, suggesting that any conclusions about context and mode of delivery should remain cautious.
Risk of bias
A summary of each risk of bias item across the studies is shown in Fig. 3 . Risk of bias was high in 80% of trials for the blinding of participants and personnel domain and so we cannot rule out the possibility of response bias. This high risk of bias was mainly due to the nature of the interventions (i.e. many of the studies were cluster trials, randomised at the hospital or clinic level, making blinding impractical). In a sensitivity analysis restricting the meta-analysis to trials at low risk of bias for each key domain, the overall treatment effect changed little, suggesting the results were robust. There were five studies at high risk of bias for outcome reporting and 59 with unclear risk of bias. A funnel plot (Fig. 4 ) identified that the review may be missing some unpublished negative trials, or including more positive trials than expected, suggesting selective outcome reporting.
Review authors’ judgements about each risk of bias item (%)
Summary of evidence
Social norms interventions can be an effective approach to changing the clinical behaviours of healthcare workers. Meta-analysis showed social norms interventions were associated with an improvement in healthcare worker clinical behaviour outcomes of 0.08 SMDs (95%CI 0.07 to 0.010, n = 100 comparison) and an improvement in patient health outcomes of 0.17 SMD (95%CI 0.14 to 0.20, n = 14 comparisons), on average.
There was a large amount of heterogeneity, with some studies reporting substantially higher or lower effects. There was strong evidence from multiple studies that interventions involving social comparison or credible source, with and without other BCTs, were effective on average, both separately and together. Social comparison is effective when combined with various other BCTs including social support (unspecified) but it appears to be most effective when combined with prompts/cues . Social reward appeared not to be effective when used alone but had an above-average effect when combined with social comparison. The effect of social norms interventions remained clear in the meta-regression, even after taking into account context and setting.
Meta-analyses exploring context and delivery showed that social norms were effective with a variety of healthcare workers, in primary and secondary care, and across a range of clinical behaviours. On average, social norms interventions were more effective for reducing than increasing behaviours. Interventions appeared equally effective regardless of whether they came from an internal or external source. In contrast to previous studies [ 14 ], delivering the intervention once appeared to be more effective than frequent delivery: one explanation for this, which warrants further investigation, is whether frequent delivery is associated with attempts to change intractable behaviours.
Sensitivity analyses found the overall treatment effect to be robust and not strongly influenced by trials which scored high/unclear risk of bias across key domains. There is a possibility of response bias due to lack of blinding. While it is difficult to blind healthcare workers in these trials, there were examples where the risk of response bias was minimised, e.g. cluster trials where the healthcare worker was not informed of the existence of the trial.
Discussion of findings in relation to the literature
A Cochrane systematic review ( n = 140) of the effect of A&F on healthcare worker behaviour and patient health outcomes [ 14 ] found a wide variation in the effect of A&F and recommended future research to explore how this variation, related to the intervention design, context and recipient [ 11 ]. The results of our review contribute to this agenda by suggesting aspects of the design of A&F interventions that are associated with positive outcomes: (1) highlighting that a credible source approves of the desired behaviour; (2) feedback on an individual’s behaviour is likely to be more effective if accompanied by social comparison ; (3) complex interventions involving multiple social norms seem to be effective; (4) social comparison seems to be enhanced by the use of prompts and cues , such as computerized pop-ups recommending actions to GPs when particular symptoms or diagnoses are entered into an electronic system [ 35 ], but the benefit of prompts and cues may only hold when the healthcare worker understands how to do the behaviour. The effects of social norms were reasonably consistent across a range of healthcare workers, behaviours and settings. In contrast to an earlier review of A&F [ 14 ], delivering the intervention once appeared to be sufficient and sending the intervention by website or other computerised format was most effective. Our results align with findings from a recent synthesis of qualitative literature on A&F which found that letting healthcare workers know how their performance relates to that of their peers ( social comparison ) and providing opportunities for peer discussion ( social support (unspecified) ) were valuable in changing behaviour [ 6 ]. However, our finding that face-to-face interventions were less effective than remotely delivered interventions contrasts with results for meta-analyses of smoking cessation interventions where personalised interventions were associated with greater effectiveness [ 36 ]. Recent literature suggests that de-implementation is often even more challenging than implementation due to a number of psychological biases: health professionals tend to focus on information that confirms their established beliefs; people are more concerned about losses than gains; and a sense of professional autonomy strengthens attachment to established practices [ 37 , 38 ]. Given the challenges of de-implementation our finding that social norms interventions were more effective in increasing behaviour than decreasing it are perhaps not surprising.
A recent overview of 67 systematic reviews on promoting professional behaviour change in healthcare found that the most effective interventions were educational outreach using academic detailing, A&F and reminders [ 39 ]. Using normalization process theory as a theoretical lens, the authors concluded that interventions that seek to ‘restructure and reinforce new practice norms’ (opinion leaders, educational meetings and materials/guidelines) and those which ‘associate practice norms with peer and reference group behaviours’ (including A&F and academic detailing, where a target healthcare worker receives individual support or advice from someone else with expertise in that area) are most likely to be successful in changing clinical behaviour. Combining the two approaches together may be particularly effective, by creating clear rules of conduct and encouraging individuals to follow their peers [ 39 ]. Interventions that seek to change attitudes were less likely to be successful. The importance given to peer and reference group behaviours in this previous study justifies our efforts to identify which social norms interventions are associated with success.
The effect sizes seen in this review appear to be similar to other reviews of interventions to change health professional behaviour [ 40 ]. Baskerville et al found that practice facilitation was associated with an improvement of 0.56 SMD (95% CI 0.43 to 0.68) in guideline adoption in primary care. Baker [ 41 ] reported that tailored interventions to overcome barriers to change are associated with an odds ratio for the improvement in professional behaviour of 1.51 (95% CI 1.16 to 2.01) which corresponds to an SMD of approximately 0.24 (95% CI 0.09 to 0.39). The modest effects size seen for social comparison appears in line with that observed by Ivers who found that Audit and feedback improved binary behavioural outcomes by a median of 4.3 percentage points and continuous outcomes by a median of 1.3 percentage points. In a meta-synthesis of systematic reviews of health behaviour change in general, Johnson found effect sizes between 0.08 to 0.45 [ 42 ].
Strengths and limitations
Our search strategy was developed through an iterative process, with input from an Information Scientist. However, it is possible that the strategy may have missed some relevant interventions if social norms BCTs or behaviour change theories were not mentioned in the title or abstract.
We included studies regardless of outcome measure, and we converted any available outcome into a standardized mean difference: this meant we were able to summarise all the available evidence in one analysis. The included trials incorporated a variety of contexts and settings; trial designs and units of analysis. This has led to a heterogeneous review; and we acknowledge the limitations of this approach. The magnitude of effects for the most promising behaviour change interventions were around 0.3 SMDs, which relative to the between study variability τ(0.2) does seem to indicate an important effect.
Trials were excluded from the review where the intervention did not target a specific behaviour: for example, if the intervention was aimed at a healthcare worker with the intention of reducing patient blood pressure, but did not make explicit what behaviour(s) were expected of the healthcare worker to achieve the reduction. These exclusions occurred because, if a behaviour is not specified, it is not possible to determine whether or not an intervention actually targeted that behaviour and change in that behaviour (our primary outcome) cannot be assessed. This approach is consistent with the coding instructions of the BCTTv1 [ 16 ]. There is a potential risk that we have excluded some studies where there was a target behaviour but it was poorly reported.
We used the BCTTv1 [ 16 ], which has been based on a significant body of research, to code for BCTs that could be associated with the effectiveness of interventions. However, BCTs were only coded based on published reports and we did not ask study authors for intervention manuals due to time constraints. Therefore, it is possible that our coding did not represent all actual BCTs as designed and delivered. The authors of the BCTTv1 have also acknowledged that extension or modification of the BCTTv1 could be appropriate in the future. It is therefore possible that some BCTs that do not yet feature in the BCTTV1 could have been presented alongside social norms BCTs and were missed during the BCT coding exercise.
Ten small studies without suitable outcome measures were omitted from the meta-analysis and some missing information (such as ICCs and standard deviations) were imputed, but sensitivity analyses suggested no significant impact on the review.
The primary approach to meta-analysis was fixed effects [ 43 ], which summarises the evidence in these trials, rather than estimating a common underlying treatment effect [ 44 ]. This topic is highly contested, so random effects was also undertaken for the most important analyses, as planned. In all analyses the fixed and random effects approaches produced a result in the same direction, with the random effects approach resulting in a higher effect for the intervention because it gives greater weight to smaller studies. The conclusions of the review would be similar, regardless of whether fixed or random effects were used.
All of the meta-analysis was undertaken on the basis of comparisons: the BCTs in the control arm were subtracted from those in the intervention arm to capture BCTs that were actively tested in each study. The active ingredient was what is left of the intervention when the control arm is taken away. This is a suitable approach to examining the effect of the various social norm BCTs, but a limitation is that some interaction effects may have been missed.
The asymmetry of the funnel plot suggested that the review may have missed some unpublished negative trials or be at risk of bias from selective outcome reporting. The resources were not available for translation or to request unpublished material from authors of included studies, so some relevant studies may have been omitted. A single behaviour outcome was selected from every trial using published reports which may have put the review at risk from selective outcome reporting; priority was given to the pre-specified primary outcome. Sensitivity analysis including only those trials with either a relevant pre-specified primary outcome or single relevant behavioural outcome suggested that results were robust to selective outcome reporting.
Credible source has been identified as an effective intervention component. Yet, it is not commonly used in the health setting to change the behaviour of healthcare workers (only 18% of the comparisons identified in the present review). This may be due to credible source lacking formal conceptualisation in the health setting so, whilst it may be used in practice, it is not well-reported. Additional work is needed to develop credible source interventions for use in the NHS, such as, whom the target audience would consider as credible sources : for example, seniority may not necessarily be perceived as the same as credible. As a first step, a narrative synthesis of the trials using credible source in this review, together with the qualitative papers, process evaluations and protocols associated with those trials, would provide further insights into the credible source interventions that are associated with more successful outcomes. Qualitative work with healthcare workers, managers and policymakers is also needed to understand the acceptability and feasibility of credible source , social comparison and social reward interventions and to understand who the most credible sources are.
Social comparison is currently used more frequently with healthcare workers than credible source . We identified a high level of heterogeneity in the effectiveness of social comparison . We have started to unravel this heterogeneity, and this research suggests that social comparison can successfully be enhanced by the addition of social reward , prompts and cues or social support (unspecified); but further research is warranted. The heterogeneity could potentially be explained by differences in how social comparisons are facilitated and what kind of comparisons are made, and not simply by the combination of BCTs it is delivered with or without. For example, social comparisons may have a different effect depending on the reference frame (e.g. whether one identifies with those compared to) or depending on the direction of the comparison (i.e. upward or downward comparison). Further investigation into the factors that moderate the effect of social comparison is warranted.
The methodological quality of trials was mixed. The review included some large factorial trials that tested several behaviour change interventions simultaneously, which can be an efficient design for exploring different components of behaviour change interventions and their interactions. Multiphase Optimization Strategy may be a useful framework that can be applied to factorial designs for identifying which combination and sequence of components (e.g. BCTs and mode of delivery) can produce optimal outcomes [ 45 ]. Some trials also used novel methods to minimize bias such as ‘attention’ controls where participants were given the identical behaviour change intervention for an alternative target behaviour: this type of design is to be encouraged.
Social norms interventions are an effective method of changing healthcare worker clinical behaviour. Although the overall result is modest and very variable, there is the potential for social norms interventions to be applied at scale and have a significant effect on clinical behaviour and resulting patient health outcomes. Both credible source and social comparison were effective. Social comparison was particularly effective when combined with prompts and cues . These interventions were found to be effective in a variety of NHS contexts and across a range of modes of delivery.
Availability of data and materials
The datasets used and analysed during the current study are available from the corresponding author on reasonable request.
Audit and Feedback
Behaviour Change Technique
Behaviour Change Techniques Taxonomy Version 1
British Nursing Index
Cumulative Index of Nursing and Allied Health Literature
Cochrane Central Register of Controlled Trials
Excerpta Medica dataBASE
Intra-class correlation coefficient
Medical Literature Analysis and Retrieval System Online
Medical Subject Headings
Prevalence-Adjusted and Bias-Adjusted Kappa
Preferred Reporting items for Systematic Reviews
The International Prospective Register of Systematic Reviews
Randomised controlled trial
Standard mean difference
- Social norm
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We thank the independent members of the Study Steering Committee: Robbie Foy (Chair), Professor of Primary Care, University of Leeds; Marie Johnston, Professor of Health Psychology, University of Aberdeen, Sofia Dias, Professor in Health Technology Assessment, University of York, and Manoj Mistry, lay member. They were very generous with their time and provided encouragement and wise counsel throughout the project. Marie Johnston came all the way from Aberdeen to run a training workshop on BCT coding, and we are also grateful to her for providing comments on an earlier draft of this manuscript. Thank you to Jane Roberts for writing and conducting the searches and double-coding the BCTs. We are grateful to Jack Wilkinson who was employed as a researcher in the early stages of the review until he was successful in winning a University of Manchester presidential fellowship.
This project is funded by the National Institute for Health Research (NIHR) Health Services and Delivery Research, reference 17/06/06—The impact of social norms interventions on clinical behaviour change among healthcare workers: a systematic review. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.
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Centre for Biostatistics, Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology Medicine and Health, University of Manchester, Oxford Road, Manchester, M13 9PL, UK
Mei Yee Tang, Sarah Rhodes, Elizabeth Howarth & Sarah Cotterill
National Institute of Health Research Behavioural Science Policy Research Unit, Population Health Sciences, Baddiley-Clark Building, Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne, NE2 4AX, UK
Mei Yee Tang
Manchester Centre for Health Psychology, Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology Medicine and Health, University of Manchester, Manchester, M13 9PL, UK
Rachael Powell & Laura McGowan
Health e-Research Centre, Farr Institute for Health Informatics Research, Faculty of Biology Medicine and Health, University of Manchester, Manchester, M13 9PL, UK
Centre for Primary Care, School of Health Sciences, Faculty of Biology Medicine and Health, University of Manchester, Manchester, M13 9PL, UK
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MYT (Research Associate, Health Psychology) wrote the first draft; all authors commented on drafts and approved the manuscript. SC (Senior Lecturer, Health Services Research and Statistics) conceived of the idea for the review and managed the project. SC, RP (Senior Lecturer, Health Psychology), SR, BB (Senior Academic GP and Honorary Consultant) and MYT contributed to the protocol. RP was the lead for health psychology, SR was the lead statistician and BB was the clinical lead. MYT, SC and SR were involved in the screening of studies. MYT, SC, SR and EH (Research Associate, Statistics) did the data extraction. MYT, SC and RP (with Jane Roberts) did the BCT coding. SR (Senior Research Fellow, Statistics) converted all the outcome measures to SMDs, conducted the meta-analysis, meta-regression and network meta-analysis of the healthcare worker behaviour outcomes and prepared the results for publication. EH conducted the meta-analysis of patient health outcomes. MYT, LM (PhD student, Psychology) and SC helped to prepare the data for analysis and undertook other descriptive analysis. The author(s) read and approved the final manuscript.
Correspondence to Mei Yee Tang .
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Additional file 1:.
Appendix 1. Search Strategy. Appendix 2. Data Extraction Form. Appendix 3. Behaviour Change Techniques (BCTs) Extraction Form. Appendix 4. Inter-Rater Agreement for BCT Coding. Appendix 5. Included Study References. Appendix 6. Study and Intervention Characteristics of Included Comparisons. Appendix 7. Sensitivity Analyses.
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Tang, M.Y., Rhodes, S., Powell, R. et al. How effective are social norms interventions in changing the clinical behaviours of healthcare workers? A systematic review and meta-analysis. Implementation Sci 16 , 8 (2021). https://doi.org/10.1186/s13012-020-01072-1
Received : 12 May 2020
Accepted : 09 December 2020
Published : 07 January 2021
DOI : https://doi.org/10.1186/s13012-020-01072-1
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