This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
The importance of effective communication during public health emergencies has been highlighted by the World Health Organization, and it has published guidelines for effective communication in such situations. With video being a popular medium, video communication has been a growing area of study over the past decades and is increasingly used across different sectors and disciplines, including health. Health-related video communication gained momentum during the SARS-CoV-2 pandemic, and video was among the most frequently used modes of communication worldwide. However, although much research has been done regarding different characteristics of video content (the message) and its delivery (the messenger), there is a lack of knowledge about the role played by the characteristics of the recipients for the creation of effective communication.
The aim of this review is to identify how health video communication outcomes are shaped by recipient characteristics, as such characteristics might affect the effectiveness of communication. The main research question of the study is as follows: do the characteristics of the recipients of health videos affect the outcomes of the communication?
A scoping review describing the existing knowledge within the field was conducted. We searched for literature in 3 databases (PubMed, Scopus, and Embase) and defined eligibility criteria based on the relevance to the research question. Recipient characteristics and health video communication outcomes were identified and classified.
Of the 1040 documents initially identified, 128 (12.31%) met the criteria for full-text assessment, and 39 (3.75%) met the inclusion criteria. The included studies reported 56 recipient characteristics and 42 communication outcomes. The reported associations between characteristics and outcomes were identified, and the potential research opportunities were discussed. Contributions were made to theory development by amending the existing framework of the Integrated-Change model, which is an integrated model of motivational and behavioral change.
Although several recipient characteristics and health video communication outcomes were identified, there is a lack of robust empirical evidence on the association between them. Further research is needed to understand how the preceding characteristics of the recipients might affect the various outcomes of health video communication.
Effective communication in public health emergencies is crucial, as people need to not only know but hopefully also understand the health risks they face and what actions they can take to protect themselves, their close ones, and the society from health hazards. The importance of communication in public health emergencies has been highlighted by the World Health Organization in the guidelines for risk communication in public health emergencies policy and practice [
In recent years, video communication has received increased attention across multiple fields, from education to science, risk, and health communication. Video allows rapid communication, is flexible and able to incorporate empathy, and has good outreach potential. Video communication gained further momentum during the COVID-19 pandemic, and most of the communication aimed at the population was through video. The effectiveness of delivering education through video has been widely investigated even before 2019 [
Health communication, which is defined as the dissemination and interpretation of health-related messages [
Although much research has been conducted on video communication itself, there is less evidence regarding whether the outcomes (eg, knowledge, attitudes, compliance, and behavior) of health video communication are affected by the various characteristics (eg, sociodemographic, personality and values, and environmental factors) of the
For this study, we chose the Integrated-Change (I-Change) model (
The model assumes that the communication outcomes (awareness, motivation, action, and behavior) depend on 2 determinants: information factors and preceding factors.
The information factors (
The preceding factors (
The Integrated-Change model.
The literature on recipient characteristics is heterogenous with regard to subject groups, methods, research questions, and disciplines. Thus, a scoping review approach was chosen to identify the nature and degree of evidence available in the international literature. Our review followed the five stages according to the methodological framework developed by Arksey and O’Malley [
This scoping review aimed to explore the role that recipient characteristics (biological, psychological, behavioral, and environmental factors) play in the outcomes of health video communication by (1) identifying which recipient characteristics and outcomes of health video communication were reported in peer-reviewed literature, (2) adapting the I-Change model to health video communication [
What are the characteristics of recipients that might influence the outcomes of health video communication?
What are the outcomes of health video communication?
What relationships exist between the recipient characteristics and the outcomes of health video communication?
We searched three main databases for public health, social sciences, and biomedical studies on health video communication: PubMed, Scopus, and Embase. Additional literature was identified using the snowball method [
The string referring to the concept was (
The string for the context component was (
Data from the 3 databases were extracted on December 12, 2020. The search was limited to results published in English only, whereas no restriction was applied to the publication year. The complete search strategy was validated by 2 of the coauthors and is available in
The first step of the selection process comprised removing duplicates (approximately one-third) to confirm the completeness of the search string and strategy. In addition to incomplete or unavailable studies, studies were excluded based on title and abstract assessment if (1) they did not focus on recipient characteristics or on specific populations (eg, people who are visually impaired or deaf), (2) they did not focus specifically on health video communication (video used for other purposes, eg, video as a recording tool, referred to video games, video teleconference, video for the education of medical students, video calls, video physician–patient communication, or video simulation), or (3) they did not use video as the main communication method. Studies were included if they met both of the following criteria: (1) they focused on health video communication, and (2) they took into account at least one recipient characteristic. No inclusion or exclusion criteria were set for the design of the identified studies. Studies included in this phase went through full-text assessment, and the final inclusion depended on their coherence with respect to the 2 inclusion criteria mentioned above. The criteria and the results of each stage were made available to all the coauthors, and their feedback was used to solve potential inconsistencies among the scope of the study, the inclusion and exclusion criteria, and the selected articles.
Microsoft Excel was used to create data extraction forms. For title and abstract assessment, the information stored were the digital object identifier, inclusion or exclusion status, and reason for exclusion. In the second stage of full-text assessment, the information about the publication year, journal, authors, title, document type, country, research domain, recipient characteristics, and reported outcomes were added. All the selected papers were saved using Mendeley, and the library was shared among all the coauthors.
The extracted data were imported into the NVivo (version 12 Pro; QSR International). The relevant topics, both regarding the recipient characteristics and communication outcomes, were coded. A nested coding methodology [
After the completion of the coding process, we moved on to define a conceptual framework, starting with the I-Change model and the way it highlights how the 4 dimensions of health communication outcome (awareness, motivation, action, and behavior) are influenced by information factors (eg, message, channel, and source) and preceding factors (biological, psychological, behavioral, and environmental factors). The existence of prior research allowed us to conduct a directed content analysis aimed at validating or conceptually extending the existing theoretical framework, as suggested by Hsieh and Shannon [
The need to adapt the original model emerged at the first attempt to allocate the coded nodes to model categories, as some nodes lacked a fitting category in the original I-Change model. A similar approach of using content analysis to conduct knowledge building and theory development was described by Finfgeld-Connett [
The final stage of data analysis was to assign nodes to the categories of the refined model. This process was conducted independently by 2 of the coauthors (KKB and DAL), and the divergencies were solved through discussion. In case the discussion did not lead to consensus, a third coauthor (SHB) was involved to have a majority. Finally, the relationships between the nodes reported in the literature were charted.
The database search strategy yielded 1040 records (331/1030, 32.13% from Scopus; 392/1030, 38.05% from PubMed; and 307/1030, 29.81% from the Embase). Approximately 34.66% (357/1030) were duplicates and thus removed, and the title and abstract assessment was performed for the remaining 65.34% (673/1030) of articles. Of the 673 articles, 555 (82.5%) were removed according to the eligibility criteria. A total of 10 additional documents were identified through cross-checking the references. In total, 128 documents were assessed for full-text. Of the 128 papers, 39 (30.5%) met the inclusion criteria and were included in the content analysis. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) chart of the selection process is presented in
All the included studies were published between 2000 and 2020. There is an increasing worldwide publication trend over the past years. As highlighted in
PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) chart of the selection process.
Cumulative number of papers published (worldwide and included in this study). Note that the x- and y-axes have different scales.
The included studies reported 56 different recipient characteristics. Some characteristics were frequently reported, with age (reported in 33/39, 85% of analyzed articles), ethnicity or race (26/39, 67%), gender or sex (25/39, 64%), and education (24/39, 62%) being the most investigated, whereas others such as sexual orientation, social network, emotional factors, or decisional control preferences being reported only by 3% (1/39) of studies each. Some characteristics were reported by a fair number of studies, such as income or socioeconomic status (SES; 13/39, 33%), beliefs and attitudes (12/39, 31%), level of knowledge (11/39, 28%), disease severity (10/39, 26%), previous experience (10/39, 26%), and health literacy (7/39, 18%). A complete overview of all the characteristics and the number of reporting documents is available in
The analysis identified 56 different recipient characteristics. Of the 56 characteristics, 48 (86%) could be assigned to a corresponding category in the I-Change model. However, some factors could not be naturally fitted in the I-Change model and were assigned to a new category termed
The category of biological factors encompassed 14% (8/56) of the recipient characteristics, namely age, comorbidities, ethnicity or race, gender or sex, self-reported health status, disease severity, current symptoms, and clinical factors. Most of these characteristics were frequently reported by the analyzed studies, with age, ethnicity or race, and gender or sex being the most investigated by international literature. Clinical factors, current symptoms, and comorbidities were rarely investigated as preceding factors that influence health video communication outcomes.
Almost half of the identified factors (27/56, 48%) were attributed to the category of psychological factors such as anxiety, depression, decisional control preferences, influential personal factors, information priorities, preferences, values, expectations, psychological distress, beliefs, attitudes, emotional factors, ability to process information, motivation, perception of treatment efficacy, treatment concerns, self-efficacy, trust in information sources, confidence, empathy, trust in health care, health locus of control, regulatory focus, confidence, hesitancy, sexual orientation, hope, and personal relevance. Furthermore, 13% (7/56) factors that were attributed to other categories could also have been included in this category, as they also have psychological implications but were a better fit into other categories. For example, comorbidities, self-reported health, disease severity, current symptoms, and clinical factors were assigned to the biological factors category; risk estimation was attributed to the knowledge factors category; and social norms were assigned to the environmental factors category.
Only 4% (2/56) of the recipient characteristics were ascribed to the category of behavioral factors: involvement and self-reported adherence.
The environmental factors category encompassed 20% (11/56) of the identified characteristics. The most recurrent ones were income and SES (reported by 13/39, 33% of the studies), marital status (7/39, 18%), and type of health insurance (6/39, 15%). The remaining factors, generally seldom reported, were the level of information and support that people can rely on, employment, financial comfort, living with someone, social network, social norms, culture, and geographical location.
The added category of knowledge factors contained 14% (8/56) of the factors. Similar to the biological factors, a significant degree of within-group variation was observed for these factors. Of the 39 included studies, the education level, knowledge, and previous experience were reported by 24 (62%), 11 (28%), and 10 (26%) studies, respectively. On the other hand, information, perceived knowledge, and health history were reported only by 3% (1/39) of the studies analyzed. The category also included 2 relevant factors that received an average amount of coverage in the international literature: health literacy and risk estimation and perception.
The included studies reported 42 different health video communication outcomes that covered a wide range of topics. The most frequently reported outcomes were knowledge, including an increase in knowledge and knowledge transfer (15/39, 38%), attitudes (9/39, 23%), behavior (9/39, 23%), and intentions (8/39, 21%). The least frequently included outcomes were awareness, compliance, activation, and attention, reported by only 3% (1/39) of studies each. Some of the outcomes that were reported by a fair number of studies included acceptance (7/39, 18%), beliefs (5/39, 13%), usefulness of the communication (4/39, 10%), and choice of treatment (4/39, 10%). A complete overview of all the health video communication outcomes is available in
The 42 health video communication outcomes reported by the included studies were attributed to the categories of the I-Change model as follows: 28 (66%) outcomes were attributed to awareness and motivation (14/42, 33% of outcomes to each), 5 (12%) outcomes were attributed to a new category termed emotions, and the remaining 9 (21%) outcomes were attributed to the category of action that encompassed the original categories of action and behavior. These decisions will be further discussed in
The most frequently reported outcomes belonged to the awareness category, which encompassed 33% (14/42) of the identified outcomes. Most of the included studies focused on elements of the awareness category as the main outcome of health video communication. The most frequently reported outcome was knowledge, which was explored in 38% (15/39) of the studies. The other included outcomes were expectations, usefulness, recall of information, uncertainty, comprehension, beliefs, perceived benefit, information, information processing, information seeking, perceived risk, perceived prevalence, and awareness.
Most of the reported evidence on awareness was focused on beliefs, knowledge gain, risk and prevalence perception, recall of information, and usefulness of communication. Syrjala et al [
The generation and transfer of knowledge is one of the main health video communication outcomes investigated in international literature and reported by the studies included in this review [
When analyzing the perceived smoking prevalence as an outcome of peer smoking cessation communication, Romer et al [
The final communication outcome belonging to the awareness category is perceived usefulness, and some studies have reported it to be relevant in the context of educational videos for patients with advanced gastrointestinal cancers [
The motivation category encompassed 33% (14/42) of the identified outcomes. Attitudes and intentions were the most investigated outcomes, being explored by 9 (23%) and 8 (21%) of the 39 analyzed studies, respectively. Acceptance, perceived self-confidence, perceived response efficacy, treatment preference, satisfaction, compliance, engagement, confidence, self-efficacy, and relevance are the remaining outcomes, and all of them were reported by less than 10% (4/42) of the selected studies.
More positive attitudes after exposure to video communication have been reported by the included studies in the context of outpatient surgical care and breast, prostate, and colorectal cancer [
The topic of confidence after exposure to health videos has been investigated in the United States regarding vaccinations, which is a topic that has been increasingly debated in the context of the COVID-19 pandemic. Nowak et al [
Literature from health communication has investigated the effect of individual characteristics on intentions, focusing mainly on biological factors [
The added category of emotions received fair attention in previous studies, with 12% (5/42) of the identified outcomes belonging to the emotions category. The identified outcomes were emotional response, decisional conflict, decision quality, decision satisfaction, and reactions. Moreover, each emotional outcome was reported by a very limited number of studies, which highlighted the limited amount of focus these factors have attracted and a potential gap in the literature.
There is a general lack of evidence about how emotional factors affect communication outcomes. Although there is some evidence regarding emotional reactions and trust, nothing was reported regarding the acceptance of health messages or the effects on the decision-making process (eg, decision satisfaction and decisional conflict) of recipients in the studies that were eligible for inclusion in this review.
The emotional response to health video communication has been reported to be significantly influenced by the age and gender of the recipients. A study by Prieto-Pinto et al [
The action category, which was obtained by merging the categories of action and behavior of the original I-Change model, encompassed 21% (9/42) of the identified health video communication outcomes. Outcomes belonging to this category received little attention in the literature, with all of them reported by less than 10% (4/42) of the included studies. Capabilities, time to treatment, quality of communication, participation, activation, spreading the message, and behavior complete the list of outcomes included in the action category.
Adherence to treatment is one of the main action outcomes of health video communication. Although adherence was often reported by the studies included in this review, there is little evidence of how the preceding factors affect it. In a study that investigated the risk of nonadherence to antiplatelet medication at the time of coronary stent placement, Palacio et al [
In the context of maternal vaccine information communication in the United States, Dudley et al [
None of the included studies reported any associations between the preceding factors and the other action outcomes such as activation, behavior, participation, time to treatment, or treatment choice.
Almost one-third (12/39, 31%) of the papers included in this analysis focused on both preceding factors and health video communication outcomes but did not investigate the relationship between them. Information about the preceding factors was collected and used mainly for descriptive purposes rather than explanatory variables [
It is noteworthy to observe how the action category received relatively low attention from the included studies, as health videos are often designed and used to drive behavior and behavioral change (eg, smoking cessation, vaccination decisions, and weight loss). Indeed, a tendency to focus on awareness and motivation rather than on the actual behavioral outcome of the recipients emerged from the included studies.
When analyzing the included studies—coding the content and identifying relevant nodes regarding both recipient characteristics and communication outcomes—some gaps emerged in the I-Change model when applied to health video communication. Thus, we revised the I-Change model to adapt it to health video communication and obtained an adapted version (
The inclusion of a fifth category termed knowledge factors within the preceding factors
The merging of the action and behavior outcome categories into a single category termed action
The inclusion of an emotions category among the outcomes
The revised Integrated-Change model.
The category of knowledge factors was included as 1 of the preceding factors categories as many included studies reported multiple characteristics associated with knowledge that did not meaningfully belong to biological, psychological, behavioral, or environmental factors. Examples of such characteristics include the recipients’ level of knowledge, health literacy, level of information, ability to process information, and information priorities.
The original model foresees action and behavior as distinct communication outcomes, whereas our analysis demonstrated an overlap between the 2 categories using the data from the 39 studies included in this review. Thus, we decided to merge them into a single category termed as action.
The emotional dimension has been shown to play an important role in multiple outcomes of communication: risk perception, judgment, and decision-making [
The included studies provide an extensive overview of the recipients’ preceding characteristics that might affect a wide range of health video communication outcomes and present evidence on the relationship between them. The trend observed in
Although subsequent analysis revealed that many of the preceding factors belong to the psychological category, only a limited number of papers reported evidence of their impact on outcomes, inviting further research in the area. Biological factors were often reported by the analyzed studies.
Although knowledge and environmental factors received fair attention in international literature, systematic and robust evidence of their effect on communication outcomes is scarce. Moreover, the recipients’ first language and their ability to speak and understand the content of videos were surprisingly not identified as relevant factors. This is because the selected studies included only people who were able to speak the language presented in the communication. Further research investigating the magnitude of the impact of linguistic skills on outcomes would positively contribute to the effectiveness of health communication.
The category of behavioral factors appears to be underinvestigated, with only 2 factors identified in all 39 studies and no evidence available on the relationship with outcomes. Although the awareness and motivation categories included the most communication outcomes, those belonging to the action and emotions categories were less reported by the included studies, and there is very little evidence of how they are affected by the preceding factors. Communication and health research would benefit from further efforts focusing on the action category, as it currently represents less than 10% (4/42) of the outcomes identified in our study, with most studies preferring to focus on awareness and motivation outcomes. This number appears low with respect to the general aim of most health communication interventions aimed at changing behavior.
The scarcity of evidence regarding emotions is particularly relevant for effective health communication. Feelings and moods motivate people to reproduce those feelings and moods, whereas, in risk communication, the topic communicated (eg, earthquakes and other natural disasters) usually evokes negative feelings and moods, motivating people to act to avoid them. Emotions are states that are not under voluntary control but are shaped and learned associatively through experiences while being partly innate at birth. Emotions affect attention, memory, motivation, and action [
Our contribution to theory development followed the research approach, in which the theory is understood as emerging from data [
As we decided to conduct a scoping review, we are aware of the common limitations of this approach [
Further understanding of the gaps presented in this review could have a great impact on the effectiveness of public health emergency communication strategies, as in these contexts, the psychological and behavioral factors of people are key, and emotions are able to significantly affect their decisions and behavior.
Although some evidence of associations between recipients’ preceding factors and health video communication has been reported in the literature, our analysis revealed a significant gap in the literature, with many health video communication outcomes and factors not yet explored. This scoping review of the available evidence demonstrated a potential research gap, especially concerning the emotional outcomes of communication and the behavioral and psychological preceding factors of recipients. The review showed that, currently, only a partial picture of the role of recipient characteristics on the outcomes of health video communication is available. Moreover, this study also contributed to the theoretical development of the I-Change model to adapt it to the needs of health video communication.
Complete search strategy and results.
Overview of included studies.
Overview of characteristics and outcomes.
Integrated-Change
odds ratio
Preferred Reporting Items for Systematic Reviews and Meta-Analyses
socioeconomic status
The COVID Communication: Fighting a Pandemic through Translating Science project has received funding from the Trond Mohn Foundation, under grant agreement number TMS2020TMT10 and the University of Stavanger.
This study was conducted by an interdisciplinary team of researchers. DAL and KKB conceived the study, discussed the methodological approach, and analyzed the data. DAL drafted the initial manuscript. All the authors (JR, FF, HT, SW, SHB, and MTS) provided critical feedback on the manuscript and approved the final version.
None declared.