research a definition of tourism from academic literature

Literature Review

• First Online: 24 April 2021

Cite this chapter

• Julian Michael Hodson 7  

Part of the book series: Entrepreneurial Management und Standortentwicklung ((EMUS))

678 Accesses

This chapter provides an extensive review of the branding, brand identity, consumer-based brand equity, and related concepts in the academic marketing, consumer behavior, and tourism literature. Strong theoretical and empirical support for a conceptualization of leisure visitors’ destination brand associations is presented.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

• Available as PDF
• Read on any device
• Instant download
• Own it forever
• Available as EPUB and PDF
• Compact, lightweight edition
• Dispatched in 3 to 5 business days
• Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Author information

Authors and affiliations.

Aachen, Germany

Julian Michael Hodson

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Julian Michael Hodson .

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Fachmedien Wiesbaden GmbH, part of Springer Nature

About this chapter

Hodson, J.M. (2021). Literature Review. In: Connecting Brand Identity and Consumer-Based Brand Equity for Tourism Destinations. Entrepreneurial Management und Standortentwicklung. Springer Gabler, Wiesbaden. https://doi.org/10.1007/978-3-658-33057-6_2

Download citation

DOI : https://doi.org/10.1007/978-3-658-33057-6_2

Published : 24 April 2021

Publisher Name : Springer Gabler, Wiesbaden

Print ISBN : 978-3-658-33056-9

Online ISBN : 978-3-658-33057-6

eBook Packages : Business and Management Business and Management (R0)

Share this chapter

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Publish with us

Policies and ethics

• Find a journal
• Track your research

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Int J Environ Res Public Health

Bibliometric Analysis and Literature Review of Tourism Destination Resilience Research

1 State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; nc.ca.sacu.sliam@181naitgnaw (T.W.); nc.ca.sacu.sliam@181gnodoaixnehc (X.C.); nc.ca.bjx.sm@gnafnah (F.H.)

2 University of Chinese Academy of Sciences, Beijing 100049, China

Zhaoping Yang

Xiaodong chen, associated data.

The dataset is provided by the Web of Science dataset ( https://www.webofscience.com/ ), accessed on 27 February 2022.

The application of resilience thinking to tourism destination research is a new perspective on sustainable tourism and has gradually become a popular research topic. Some literature has been conducted on tourism destination resilience, but there has not been a comprehensive review and analysis of the whole field. This study was based on the literature from 2000 to 2021 in the Web of Science core collection database. The collaboration analysis, literature co-citation analysis, keyword co-occurrence, burst detection analysis in CiteSpace, and qualitative analysis were adopted to conduct a holistic tourism destination resilience research review. The results indicated that the United States, Australia, China, and the United Kingdom were the primary countries involved in tourism destination resilience research. Five hot research themes were obtained. (1) concept and connotation of tourism destination resilience, (2) drivers of tourism destination resilience, (3) sustainable management framework and practices, (4) perception of tourism destination resilience, and (5) the resilience of the tourism community. Furthermore, four research gaps and future directions were proposed in this study, including the theoretical framework of tourism destination resilience, assessment of tourism destination resilience, sustainable management and resilience, and application of advanced technology in tourism destination resilience. This study assists researchers in understanding the development and future research directions in tourism destination resilience research.

1. Introduction

With increased uncertainty in the natural and social environment and the increased frequency of disasters and crises, building resilience has become an effective way to promote sustainable development [ 1 ]. Resilience was initially defined as “the ability of a system to absorb disturbances and reorganize in response to changes to maintain substantially the same functions, structures, attributes, and feedback as before the disturbances occurred [ 2 ]”. Subsequently, the resilience of the social-ecological system was emphasized to reach a new state. Resilience is not a new concept, but its introduction into tourism research is still nascent [ 3 ].

In recent years, economic crises, terrorist attacks, earthquakes, and other social crises and natural disasters have threatened tourism destinations, especially the COVID-19 epidemic since 2020. In 2020, 100% of destinations worldwide had implemented travel restrictions, and 27% had closed their borders entirely to international tourism [ 4 ]. As an essential basis for crisis management and sustainable development in tourism destinations, destination resilience research has become a focus of intergovernmental organizations and academia [ 5 , 6 ].

Tourism destination resilience is the ability of tourism destinations to resist, adapt and self-organize against disturbances. It is a new way and perspective for tourism destinations to cope with threats posed by various natural or human-induced crises and uncertainties [ 7 , 8 ]. Although there is no uniform definition of tourism destination resilience, researchers have reached a consensus to shift the perspective from crisis management to resilience research in tourism studies [ 9 ]. Enhancing the resilience of tourism destinations can be helpful for tourism destinations to better adapt to changes and achieve sustainable development. Hence, it is urgent and vital to strengthen the research on tourism destination resilience.

With the introduction of resilience into tourism research and the growing prominence of sustainable development issues in tourism destinations, research on tourism destination resilience has been enhanced. Since the 21st century, scholars have focused on tourism destination resilience research, and research outputs have emerged especially over the last decade. There have been some research advances on tourism destination resilience in concepts, frameworks, management, and assessment. Several reviews were conducted on crisis management in tourism destinations. To some extent, tourism destination crisis management is also part of destination resilience. For example, Ritchie [ 10 ] reviewed papers published in tourism risk, crisis, and disaster management from 1960 to 2018 and critically analyzed three research themes. Jiang [ 11 ] used CiteSpace to analyze and visualize the knowledge structure in tourism crisis and disaster management and found that tourism crisis and disaster management research has shifted from broader themes to more specific issues, most recently focusing on resilience. However, although previous reviews have reviewed tourism destination resilience research from some specific perspectives, a systematic and comprehensive analysis of this research area seems to be lacking.

It is necessary and meaningful to conduct a holistic and systematic review of past research, especially at a time when destination resilience research is still emerging. Therefore, this study aims to systematically summarize the research content, generalize the main research strengths and research hotspots, the gaps, and the future research directions on tourism destination resilience. Specifically, this study hopes to solve the following three research questions in the research of tourism destination resilience. RQ1. What are the research strengths and their collaborations on tourism destination resilience during the past two decades? RQ2. What are the hot research themes in tourism destination resilience? RQ3. What are the research gaps and future research directions in tourism destination resilience?

The paper is structured as follows. The first part is an introduction to the resilience of tourism destinations and existing research. Next, the Section 2 describes the analysis methodology and data collection. Then, the Section 3 analyzes the bibliometric results, including collaboration network analysis, literature co-citation analysis, keyword co-occurrence analysis, and burst detection analysis. The Section 4 discusses the analysis results in depth and describes hot research themes, research gaps, and future research directions. Finally, the Section 5 summarizes the findings and implications of this study and discusses shortcomings and prospects for future research.

2. Materials and Methods

2.1. scientific knowledge mapping.

Scientific knowledge mapping, also known as knowledge domain visualization, visualizes the development process and structural relationship of knowledge with the knowledge domain as the object [ 12 , 13 ]. It is intuitive and efficient to adopt knowledge mapping to analyze the research hotspots and frontiers in a specific field. Generally, there are four steps in scientific knowledge mapping [ 14 ]. The first step is to build a base database by downloading relevant documents on specific topics from literature databases. Then, the second step is to utilize the bibliometric software to develop the co-occurrence, co-citation, and co-authorship matrices. The third step is data visualization. Finally, the fourth step is to conduct an in-depth analysis of the scientific knowledge map with background knowledge. Some software has been available for building knowledge mapping. Moreover, the knowledge mapping in this study was implemented on CiteSpace 5.8 R3, for reasons described in Section 2.2 .

2.2. Data Analysis Method

CiteSpace is a knowledge mapping software based on quantitative analysis developed by Prof. Chaomei Chen [ 12 ]. CiteSpace has been widely adopted by researchers from various fields for its powerful features and effective visualization [ 15 , 16 , 17 ]. This study mainly used collaboration network analysis, co-citation analysis, keyword co-occurrence analysis, and burst detection analysis in CiteSpace [ 14 ].

The collaboration networks contribute to the analysis of the distribution of research strength and their collaboration in a particular research field. This analysis aims to facilitate potential research collaborations better. CiteSpace provides scientific network analysis at the macro, medium, and micro levels, including national/regional, institutional, and author collaboration networks [ 14 ].

The concept of co-citation was first introduced by Henry Small, an American intelligence scientist, in 1973 [ 18 ]. Co-citation analysis is a highlight feature that distinguishes CiteSpace from other metrics software, which helps researchers track the evolution of the research field [ 19 ]. Clustering analysis of literature co-citation allows exploration of common themes in similar literature.

The co-word analysis is based on the frequency distribution of word occurrences. The co-occurrence analysis tools in CiteSpace include keyword co-occurrence, term co-occurrence, and category co-occurrence. In this study, keyword co-occurrence analysis and burst detection analysis was used [ 14 ]. Keywords are a highly concise summary of the content of the literature. Keyword co-occurrence and burst detection analysis are essential tools for identifying research hotspots and development trends in the research field.

2.3. Material

Data collection is the basis of literature analysis. Publications in academic journals can reflect the cutting-edge dynamics of academic research, so it is essential to obtain abundant literature for the literature review. The Web of Science (WoS) core collection databases (Social Science Citation Index (SSCI), Science Citation Index Expanded (SCIE)) were selected as data sources for this study. WoS database is a worldwide recognized comprehensive database containing authoritative and influential journals. The authority of the WoS database in bibliometrics has been proven by many studies, including those in the field of tourism research [ 20 , 21 ]. Hence, the selection of the WoS database for this study will guarantee the reliability of the data.

Several search criteria were required to be set in WoS to screen the literature related to the study topic. This study identified the topic as destination resilience, with the search formula: TS = (touris* AND resilience) or TS = (destination AND resilience). The time span was set to “2000–2021”. Because research on destination resilience was scarce and not very relevant before the 21st century, it began to develop gradually after the 2000s. The language was set to English. Only journal articles and reviews were collected to search for more influential literature. The search was conducted on 27 February 2022, and the database was last updated on 27 February 2022, with a total of 310 documents collected. The search results included some literature that was not relevant to tourism destination resilience, so it was necessary to conduct a second round of screening to exclude the irrelevant results manually. Finally, 207 valid results were retained as the research sample.

3.1. Overview

The annual number of publications serves as a good indicator of evolutionary tendency in the research field. The analysis of the number of publications per year is also the basis of the bibliometric analysis [ 22 , 23 ]. There was a continuous growth trend in the number of publications on tourism destination resilience from 2000 to 2021, indicating an increasing interest of scholars in tourism destination resilience research ( Figure 1 ). Until 2012, the average number of publications was below ten annually, with a slight and flat interannual variation. From 2012 to 2018, the number of publications showed a fluctuating upward trend.

Trends in the number of publications during 2000–2021.

In contrast, the number of publications increased significantly and rapidly in 2019–2021. It is worth mentioning that the number of publications has reached 68 in 2021, which is four times more than in 2018. Such a positive trend of continued growth dramatically indicated that destination resilience research would remain promising in the future.

3.2. Collaboration Analysis

3.2.1. countries and regions.

There were 66 nodes and 127 links in the collaboration network between countries or regions ( Figure 2 ). Regarding the continental distribution of countries or regions, Europe, Asia, Oceania, and North America have been relatively well studied for destination resilience. On the other hand, Africa and the North and South continents were relatively weak. Judging from the ranking of the number of publications by country or region, the United States (44), Australia (35), China (28), and the United Kingdom (24) have relatively more research on this topic, with the United States accounting for 13.37% of the publications. Regarding centrality, the United Kingdom, the United States, Australia, and New Zealand ranked in the top four, indicating that these four countries were more cooperative externally than others, shown by the purple ring in Figure 2 . Remarkably, although China has published much research on tourism destination resilience, the low centrality demonstrated that there is still a lack in the degree of international cooperation in China. This is essential to strengthening external collaboration and communication in the future. By the end of 2021, 66 countries or regions had participated in tourism destination resilience research, accounting for roughly a third of the total number of countries and regions worldwide, revealing the lack of attention given to tourism destination resilience research in the majority of countries and regions.

Collaborative network between countries or regions.

3.2.2. Institutions and Authors

From the perspective of research institutions, 220 research institutions have conducted tourism destination resilience research, of which they have collaborated 241 times. The network density of 0.01 suggested, to some extent, that there is significant potential for collaboration between research institutions. It was interesting to note that the top three institutions, the University of Queensland, James Cook University, and Massey University, were all located in the New Zealand region. In contrast, the other research institutions were scattered around the world. Furthermore, the University of Queensland and James Cook University’s centrality were higher than the other institutions, demonstrating that these two universities demonstrate significant research power in collaborative research on destination resilience.

The density of the author collaboration network was 0.0082, reflecting the relative lack of collaboration among researchers. There were 269 researchers in the field of tourism destination resilience. The studies of BRENT W RITCHIE, CAROLINE ORCHISTON, and C MICHAEL HALL have been cited relatively more frequently, suggesting that the studies of these scholars have received relatively high recognition and attention. The academic backgrounds of these scholars are complex, covering various fields such as tourism, economics, management, and disasters. Thus, it reflects, to some extent, the multidisciplinary characteristics of tourism destination resilience research.

3.3. Co-Citation Analysis

Literature co-citation analysis is a crucial method for tracking the frontiers of science and the research base, and its effectiveness has been demonstrated in a variety of studies [ 24 , 25 ]. In this study, the co-citation of tourism destination resilience research was clustered and analyzed with the more commonly employed LLR algorithm [ 21 ]. The nodes in the co-citation network represented the cited literature, and the links between the nodes described the co-citation relationships between the literature. There were 567 nodes and 1550 links in the co-citation network, and 12 clusters were generated. The modularity Q value of the network was 0.8832, which is greater than 0.3, implying that the clustering structure is significant ( Figure 3 ). The silhouette values ranged from 0.838 to 1, and the weighted mean silhouette value was 0.9195, demonstrating that the clustering results were convincing.

Clustering network of literature co-citations.

Cluster #0 “destination recovery” is the largest cluster containing 67 members. The tourism industry has contributed to economic and sustainable development, and tourism destinations are a vital component of tourism. However, tourism destinations are significantly vulnerable to disturbances. Thus, destination recovery has become an essential issue in tourism destination research. After suffering the disturbances, do tourist destinations return to their original state, or do they reach a new equilibrium? This question has attracted attention [ 1 , 26 ]. Resilience plays a vital role in the recovery of tourism destinations and is the goal of destination recovery [ 27 ]. Therefore, the discussion of the goals of destination recovery provides an insight into the connotation of tourism destination resilience. Most studies have concluded that destination recovery prefers destinations to reach a healthier state of systemic equilibrium after recovery, revitalizing them. The representative literature of this research cluster constructed a multidimensional framework of destination recovery based on vulnerability, resilience, and adaptation, and analyzed the factors affecting resilience and adaptation [ 1 ].

Cluster #1 “regional tourism destinations” and Cluster #2 “tourism destinations” are related to tourism destinations. Researchers have studied the resilience of tourism destinations across different scales and types, such as coastal zones, protected areas, national parks, and even a country. These studies have generally emphasized the characteristics of natural and human systems in tourism destinations, analyzed the dynamic processes and mutual feedback mechanisms between systems, and explored the processes and mechanisms of tourism destination resilience [ 28 , 29 , 30 ]. Although there is a basic consensus to consider tourism destinations as an eco-social system, the study of destination resilience requires site-specific thinking due to the differences among tourism destinations.

Cluster #3 “COVID-19” focuses on some studies on COVID-19and tourism destination resilience. COVID-19was a global public health outbreak that had a tremendous impact on tourism destinations worldwide and generated significant academic interest in destination resilience. The representative literature of this cluster reviewed publications within the first year of the pandemic, summarized the concentrated research themes, and suggested directions for future research [ 31 ]. The impact of COVID-19on tourism and destinations has reinforced the call for resilient and sustainable tourism destinations.

Cluster #4 “system thinking” emphasizes the importance of system thinking in tourism destination resilience research. Many researchers agreed that tourism destinations should be viewed as complex systems and that tourism areas are made up of complementary products, sectors, and institutions and their interactions [ 32 ]. Social-ecological system theory and complexity theory have served as the basis for research on tourism destination resilience. Resilience and adaptability were also emphasized since destination systems are subject to change due to diverse factors, including internal system influences and external disturbances.

Cluster #5 “marine conservation” focuses on conserving marine tourism destinations. The oceans are essential but vulnerable tourism destinations. Magnus Nyström [ 33 ] found that human activities have altered the resilience of coral reefs while disturbing them and emphasized the resilience of coral reef ecosystems by focusing on the concepts of resistance, self-organization, and reorganization. Ryan Jopp [ 29 ] developed and validated a framework for adaptive management of coastal tourism sites under the background of climate change.

Cluster #6 “destination image” concerns destination image issues, mainly including the impact of disasters on destination image and ways to recover destination image. Many studies have shown that disasters and crises can harm the image of a destination, thus influencing tourists’ choice of destination [ 34 , 35 ]. Of course, some studies have found that developing black tourism after a disaster is also a positive direction for tourism destination development [ 36 , 37 ]. The representative literature of this cluster examined the changing destination image of Thailand as a tourism destination during the crisis and tested stakeholder resilience [ 38 ].

Cluster #7 “shocks” is associated with shocks to tourism destinations. The characteristics and processes of shocks and the response process of destinations must be considered in destination resilience research. Of course, different shocks have different impacts on tourism destinations, and how to measure the impact of shocks on tourism destinations is still a concern for researchers. Besides, more literature is needed to focus on the resilience of tourism destinations to specific shocks and the factors that influence this resilience. Representative literature of this cluster empirically examined coral reef perceived resilience of tourism enterprises on the Great Barrier Reef in Australia to significant disturbances or shocks. Furthermore, it demonstrated that human capital is vital for enhancing enterprise resilience [ 39 ].

Cluster #8 “research outlook” includes some literature on research outlook literature. The representative literature of this cluster focused on the disturbance and resilience of coral reef destinations. This study highlighted the shift in perspective that such studies have undergone over the last few decades, from the nature of disturbance itself to the ability of coral reefs to recover from disorder [ 33 ].

Cluster#9 “planning” relates to planning for tourism destination resilience. Destination resilience planning is an essential tool for destination management. The processes of change and their interrelationships have become more complex in a globalized and accelerating world, leading to pressure on tourism to respond and adapt to various factors. However, there is still a lack of work on tourism governance and resilience [ 40 ]. Actions should be taken at different levels of government to enable the assessment, planning, and management of long-term destination resilience [ 41 , 42 ].

Cluster #10 “multivariate analysis” is a cluster of literature related to resilience research methods in tourism destinations. Representative literature of this cluster employed multivariate analysis to infer the intensity of visitor impacts and predicted the resilience of tourism based on physical and biological variables [ 43 ].

Cluster #11 “total economic value” concentrates on the economic value of tourism destinations. The representative literature compared the total monetary value of ecosystem goods and services in coastal destinations in Kenya [ 44 ]. This study found that appropriate government involvement in conservation can protect high-value beach destinations. However, the absence of social and community-level values led to the loss of economic and destination resilience.

3.4. Co-Occurrence Analysis

According to the analysis results, this study attempts to classify the keywords into four categories. The first category refers to the study object, specifically shocks, and disasters faced by tourism destinations, such as “climate change”, “crisis”, and “risk”. The second category refers to research subjects, like “tourism”, “community”, and others. The third category refers to the research questions, including “governance”, “knowledge”, “management”, “adaptation”, “impact”, and “perspective”. The fourth category refers to research methods, like “models”, “frameworks”, and others. Observing the size of the nodes in Figure 4 , it is evident that research questions and research methods were popular topics with a high level of attention.

Keywords co-occurrence network during 2000–2021.

The research themes in tourism destination resilience have changed over time ( Figure 5 ). During 2000–2008, the study of destination resilience had not yet formed a prominent research hotspot. Resilience started to become a hot topic of interest between 2008and 2009. From 2011 to 2016, scholars generally focused on adaptability, and the close relationship between adaptability and resilience received more attention and recognition. Between 2016 and 2018, there was a gradual increase in research on destination resilience management. Recently resilience perceptions and knowledge have started to become important concerns, and of course, some other important research themes still exist. Generally speaking, the research theme of destination resilience has been constantly developed and deepened, and the concerns are more closely related to the sustainable development of tourism destinations.

Top five keywords with the strongest citation bursts.

4. Discussion

4.1. hot research themes.

With the above co-citation analysis and co-occurrence analysis, it was found that tourism destination resilience research has made certain progress over the past two decades. More scholars have joined in the study of tourism destination resilience, which to some extent indicates the important research significance of tourism destination resilience research. Tourism destination resilience research has undergone an evolutionary process from shallow to deep, gradually shifting from initial conceptual exploration to assessment methods, cognition of resilience, management, and application. The following five hot research themes were derived from a summary of the same research themes from 2000 to 2021.

4.1.1. Concept and Connotation of Tourism Destination Resilience

The term “resilience” was originally a concept in the field of physics, meaning “bouncing back to its original place” [ 27 ]. Afterward, resilience was gradually introduced to the study of ecosystems, social systems, and socio-ecological systems [ 2 , 45 ]. Nevertheless, tourism destination resilience is a combination of resilience and tourism geography. The understanding of the concept and connotation of destination resilience has undergone an evolutionary process. Early studies considered destination resilience as the ability of tourism destinations to recover after a disturbance [ 43 , 46 ]. However, more studies later stressed the need to view destinations as complex systems, defining destination resilience as a destination’s ability to resist, adapt, and restructure in the face of disruptions or changes [ 8 , 47 , 48 , 49 ]. Compared to earlier studies interpreting the connotations of tourism destination resilience, later studies were relatively more developed and received more recognition.

Additionally, the conceptual distinction between vulnerability and resilience was a popular topic [ 50 ]. The understanding of scholars on the connotations of vulnerability and resilience can be broadly divided into two categories. One view believed that vulnerability and resilience were two sides of the same coin and were antonyms of each other. Specifically, destinations with high vulnerability had low resilience, and vice versa [ 48 , 51 ]. Another view held that the distinction between the two could not simply be generalized as antonyms. Both vulnerability and resilience are essential concepts in sustainable development, and destinations with high vulnerability do not necessarily lead to low resilience, which also involves other issues such as destination adaptation [ 5 , 7 , 52 ]. Vulnerability and resilience were two independent and highly synergistic concepts that were not mutually exclusive. The systematic relationship between vulnerability and resilience can help analyze tourism in protected areas in a globally changing environment [ 53 ].

4.1.2. Drivers of Tourism Destination Resilience

Drivers are factors that cause changes in a system. There are many drivers of tourism destination resilience, either endogenous to the system or external perturbations that pressure the system [ 54 , 55 ]. In the past, the methods used to study the drivers of tourism destination resilience were mainly qualitative and quantitative, where qualitative analysis was more compared to quantitative analysis. The complexity of tourism destination systems increases the difficulty of quantitative research.

Of course, the drivers of destination resilience vary by destination. Colin Arrowsmith [ 43 ] examined the relationship between biophysical variables and the environmental resilience of the national park by adopting the principal components method, and the results showed that the resilience increased with increasing elevation. Esteban Ruiz-Ballesteros [ 48 ] found that tourism activities have a crucial influential role in the resilience of tourism communities and noted that sustainable development could only be achieved in resilient communities. Diana Kutzner [ 8 ] conducted qualitative interviews with tour operators, conservation organizations, and local governments and discovered that tour operator perceptions significantly impact the resilience of birding tourism sites. This study also proposed a conceptual framework that highlights coping strategies for operators to address perceived drivers of change. Chloe King [ 56 ] found that livelihood capital plays a vital role in tourism destination resilience and that in Indonesia, tourism planners have overly focused on the development of “high-end” tourism forms at the expense of livelihood capital, resulting in destinations that are vulnerable to damage like COVID-19.

4.1.3. Sustainable Management Framework and Practices

The study of tourism destination resilience is often closely related to sustainable management. Some researchers argued that sustainability and resilience were essentially the same and that resilience is either a critical index of sustainability or a way of achieving sustainability [ 57 ]. However, other scholars hold a different view. Stephen Espiner [ 9 ] proposed a conceptual model to debate critical research on the relationship between tourism sustainability and resilience and argued that sustainability and resilience are based on different worldviews. The study concluded that sustainable tourism might mean that tourism destination systems maintain their current state over time, while resilience implies that tourism destination systems adapt to environmental complexity, uncertainty, and change. In an era of change and uncertainty, resilience may be a more appropriate framework for tourism destination management. Indeed, more scholars have incorporated resilience into sustainable management to guide the sustainable development of tourism destinations. Emma Calgaro [ 50 ] applied the destination sustainability framework to identify the integrated factors and socio-ecological processes of vulnerability and resilience within and across destinations. The practices from different tourism destinations in Thailand illustrated the differences in vulnerability and resilience because of geographical context and background. Based on an analysis of the similarities and differences between sustainability and resilience, Alan A. Lew [ 58 ] clarified the respective roles and pointed out that the new ideal tourism destination community is sustainable and resilient.

4.1.4. Perception of Tourism Destination Resilience

The perception of tourism destination resilience is one of the directions of tourism destination resilience research. Perception research is an essential method for tourism destination resilience research. Scholars have conducted studies on the perceived resilience of tourism destinations in different study regions, including the Southern Alps, the Egyptian Red Sea, urban tourism sites, and others [ 59 , 60 , 61 ].

Perception studies of tourism destination resilience can be broadly divided into two categories, one to assess destination resilience and the other to understand the factors that influence destination resilience [ 38 , 54 , 62 , 63 ]. Patrick Joseph Holladay [ 63 ] investigated the perceptions of social and ecological resilience of residents in six tourism communities based on a scale approach, suggesting that communities need to strengthen investment and institutional capacity to control infrastructure development. Yu Ting Joanne Khew [ 64 ] assessed the contribution of infrastructure to disaster resilience through interviews with residents.

4.1.5. The Resilience of the Tourism Community

The community can be seen as an element in the tourism place system and an essential type of social-ecological system. The vulnerability of communities has become more apparent in global disasters and crises. Scholars have attempted to quantify resilience in tourism communities and applied the concept of resilience to explain how to develop community-based tourism. Natural resources are significant to communities on Minnesota’s north shore of Lake Superior. Furthermore, studies have found that the effects of global climate change on the region’s natural resources have significantly impacted the livelihoods of those who rely on these resources to provide essential ecosystem services and support the regional economy [ 65 ]. Australia’s coastal tourism industry overgrew, and its excessive exploitation of cultural and natural landscapes has put pressure on the social and ecological foundations of the surrounding communities [ 66 ].

Hence, strengthening the resilience of the tourism community has become an urgent issue to be addressed. Angelo Jonas Imperiale [ 67 ] presented a social impact assessment (SIA) framework to build community resilience, divided into four stages: understanding the local context, recognizing local concerns and capacities, engaging the local community, and empowering sustainable transformation. Ladan Ghahramani [ 68 ] found that Gullah Geechee’s cultural heritage can also enhance community resilience, promote more sustainable community ownership, and suggested that the various dimensions of community loss be incorporated into decision-making. Existing studies remained dominated by qualitative analysis regarding the enhancement of resilience in tourism communities.

4.2. Research Gaps and Future Research Directions

Research gaps and future research directions were identified based on a combination of quantitative and qualitative analysis. After the co-citation analysis, keyword co-occurrence analysis, and research theme analysis described above, the extensive literature was analyzed and summarized. This study identified four research gaps and future research directions through qualitative analysis, including the theoretical framework of tourism destination resilience, assessment of tourism destination resilience, sustainable management and resilience, and application of advanced technology in tourism destination resilience.

4.2.1. Theoretical Framework of Tourism Destination Resilience

Establishing a theoretical framework is an abstraction of the actual phenomenon and a basis for research. The theoretical framework helps distill the structural features and interrelationships of events and better understand these processes. There have been some studies in the past that have attempted to explore the theoretical framework of tourism destination resilience. Yet, these studies have generally focused on specific tourism destinations or specific disaster scenarios and lack systematic and comprehensive analyses [ 27 , 69 , 70 ]. Hence, there has not been a universally accepted theoretical framework for tourism destination resilience.

Future research on the theoretical framework of tourism destination resilience may consider the following aspects. Firstly, the tourism destination is a complex system, and it is crucial to analyze the components and characteristics of the tourism destination system. Tourism destination systems could be divided into ecological, social, economic, and cultural sub-systems. Secondly, the disturbance factors that a tourism destination system may encounter are various and complex, and the simple classification of disturbances into natural and human disturbances is still open to question. In addition, it is essential to analyze the processes in the resilience of tourism destinations. Theories including social-ecological system theory, adaptive cycle theory, chaos theory, and human-earth system theory will also provide references for studying the theoretical framework of tourism destination resilience.

4.2.2. Assessment of Tourism Destination Resilience

The second research gap is the assessment of tourism destination resilience, and this work is a prerequisite for the regulation and management of tourism destination resilience. Nevertheless, the existing studies on tourism destination resilience assessment mainly were qualitative, focusing on theoretical models or assessment frameworks in practice [ 51 ]. The methods of evaluation were primarily based on qualitative methods, including semi-structured interviews and scale methods, and a few studies have attempted to quantify the degree of tourism destination resilience. Thus, these studies were generally subjective [ 40 , 55 , 61 ]. Tourism destinations are complex, typically characterized by multi-scale, multi-stage, and multi-types. Furthermore, difficulties and limitations, including data collection, will be encountered in actual assessment operations. Thus, establishing a systematic and comprehensive resilience assessment model for tourism destinations is challenging.

Several aspects of future tourism destination resilience assessment could be studied. Firstly, it is meaningful to establish an index system for tourism destination resilience assessment. Through refining the characteristics of tourism destination resilience and analyzing the systematic perturbation factors of the destination, an operable tourism destination resilience evaluation system can be developed. The ecological, social-economic, resistance, resilience, and self-organization capability aspects of tourism destinations should all be considered when choosing evaluation indicators. Secondly, it is very promising to introduce more models to assess tourism destination resilience. Models such as the Pressure-State-Response model, Driving force-State-Response model, system dynamics, structural equations, and scenario simulation may be applied to evaluate tourism destination resilience. However, it should be emphasized that the complexity of the model should not be pursued one-sidedly, but the problem-solving capability of the model should be pursued.

In addition, the assessment of tourism destination resilience should pay attention to the spatial and temporal scales. On the one hand, large- and medium-scale tourism destinations are richer in elements, and the composite indicator method can consider multidimensional factors more comprehensively. However, small-scale tourism destinations are more microscopic and experimental, and interview methods may be easier to operate. On the other hand, it is possible to better achieve destination monitoring and management by concentrating on the temporal dynamics of tourism destination resilience. It is also an issue worth exploring to conduct a prediction of tourism destination resilience.

4.2.3. Sustainable Management and Resilience

The third research direction is the study of sustainable management and resilience. While several studies have analyzed the relationship between destination sustainable management and resilience, sustainable management and resilience have become complementary and synergistic [ 9 , 58 ]. From the definition of vulnerability and resilience, the sustainability of the destination can be achieved by reducing vulnerability and increasing resilience. However, past research has focused on conducting vulnerability assessment studies in the context of sustainable management of destinations [ 5 , 50 ], and not enough attention has been paid to resilience assessment.

Several areas may be worth considering in the future. Firstly, it is crucial to establish a systematic and holistic-oriented sustainable management framework that incorporates resilience assessment and management. Secondly, strengthening destination resilience in terms of destination sustainable management-oriented aspects, such as stakeholder collaboration and destination crisis management, remains a challenge. In addition, it is necessary to conduct more empirical case studies because different case sites have other conditions, and case studies can help better verify the validity of the research and be more instructive.

4.2.4. Application of Advanced Technology in Tourism Destination Resilience

The fourth research direction is the application of new technologies in the resilience of tourism destinations. Especially with the advent of COVID-19, increasing attention has been paid to applying new technologies in tourism. The relationship between technology and tourism products, destination management, and visitor behavior is increasingly close. There is a gap in the application and research of technology for resilience in tourism destinations.

There are still many issues to explore with technology in the management of tourism destination resilience. At first, the application of modern technology to develop destination products like virtual tourism and these technology products can improve the diversity of tourism destination supply products. Moreover, it is meaningful to diversify product supply to enhance tourism destination resilience. Secondly, future research might analyze the role that improving the knowledge and skills of tourism practitioners in destinations plays in destination resilience and how to improve the knowledge and skills of destination staff. Thirdly, advanced technology might be utilized to monitor tourism destinations more comprehensively. On the one hand, technology can facilitate the emergency management of tourism destinations. On the other hand, it can provide multiple sources of data to assess the disaster resilience of tourism destinations.

5. Conclusions

Based on literature published in the WoS core collection from 2000 to 2021, the bibliometric and qualitative analyses were applied to analyze the progress of research on tourism destination resilience. A comprehensive review was achieved through collaborative network analysis, co-citation analysis, and keyword co-occurrence analysis in CiteSpace. The results revealed that the United States, Australia, China, and the United Kingdom are the leading countries for tourism destination resilience research. Both co-citation clustering networks and keyword co-occurrence networks were generated for the study. Moreover, five hot research themes were identified: (1) concept and connotation of tourism destination resilience, (2) drivers of tourism destination resilience, (3) sustainable management framework and practices, (4) perception of tourism destination resilience, (5) the resilience of the tourism community. This study also identified four research gaps and future research directions: theoretical framework of tourism destination resilience, assessment of tourism destination resilience, sustainable management and resilience, and application of advanced technology in tourism destination resilience.

Nevertheless, there are still a few aspects for improvement in this study. Only literature from the WoS database was selected for this study, which would inevitably ignore relevant literature from other databases. Future studies could try to expand the data sources to other databases to obtain a more comprehensive analysis. Nevertheless, it should also be recognized that the authority and representativeness of the WoS core collection database, to a certain extent, ensures that the results of this study are reliable.

Overall, this study conducted a comprehensive and systematic review of tourism destination resilience research, which provided a valuable reference for future research, especially when tourism destination resilience research has become so urgent and heated.

Funding Statement

This research was funded by the Second Tibetan Plateau Scientific Expedition and Research Program, grant number 2019QZKK1004, and the National Natural Science Foundation of China, grant number No. 41971192.

Author Contributions

Conceptualization, T.W. and Z.Y.; methodology, Author Contributions: T.W.; software, T.W.; validation, T.W. and X.C.; formal analysis, T.W.; writing—original draft preparation, T.W.; writing—review and editing, X.C.; visualization, T.W.; supervision, Z.Y.; project administration, Z.Y. and F.H.; funding acquisition, Z.Y. and F.H. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

Conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

• Search Menu
• Sign in through your institution
• Advance Articles
• Editor's Choice
• Supplements
• E-Collections
• Virtual Roundtables
• Author Videos
• Author Guidelines
• Submission Site
• Open Access Options
• About The European Journal of Public Health
• About the European Public Health Association
• Editorial Board
• Advertising and Corporate Services
• Journals Career Network
• Self-Archiving Policy
• Terms and Conditions
• Explore Publishing with EJPH
• Journals on Oxford Academic
• Books on Oxford Academic

Article Contents

Introduction, conclusions, recommendations and limitations of the study, supplementary data, data availability.

• < Previous

A systematic review of literature examining the application of a social model of health and wellbeing

• Article contents
• Figures & tables
• Supplementary Data

Rachel Rahman, Caitlin Reid, Philip Kloer, Anna Henchie, Andrew Thomas, Reyer Zwiggelaar, A systematic review of literature examining the application of a social model of health and wellbeing, European Journal of Public Health , Volume 34, Issue 3, June 2024, Pages 467–472, https://doi.org/10.1093/eurpub/ckae008

• Permissions Icon Permissions

Following years of sustained pressure on the UK health service, there is recognition amongst health professionals and stakeholders that current models of healthcare are likely to be inadequate going forward. Therefore, a fundamental review of existing social models of healthcare is needed to ascertain current thinking in this area, and whether there is a need to change perspective on current thinking.

Through a systematic research review, this paper seeks to address how previous literature has conceptualized a social model of healthcare and, how implementation of the models has been evaluated. Analysis and data were extracted from 222 publications and explored the country of origin, methodological approach, and the health and social care contexts which they were set.

The publications predominantly drawn from the USA, UK, Australia, Canada and Europe identified five themes namely: the lack of a clear and unified definition of a social model of health and wellbeing; the need to understand context; the need for cultural change; improved integration and collaboration towards a holistic and person-centred approach; measuring and evaluating the performance of a social model of health.

The review identified a need for a clear definition of a social model of health and wellbeing. Furthermore, consideration is needed on how a model integrates with current models and whether it will act as a descriptive framework or, will be developed into an operational model. The review highlights the importance of engagement with users and partner organizations in the co-creation of a model of healthcare.

Following years of sustained and increasing pressure brought about through inadequate planning and chronic under-resourcing including the unprecedented challenges of the Covid-19 pandemic, the UK NHS is at crisis point. 1 The incidents of chronic disease continue to increase alongside an ageing population who have more complex health and wellbeing needs, whilst recruitment and retention of staff continue to be insufficient to meet these increased demands. 1 Furthermore, the Covid-19 pandemic has only served to exacerbate pressures, resulting in delays in; patient presentation, 2 poor public mental health 3 strain and burnout amongst workforce. 4 However, preceding the pandemic there was already recognition of a need for a change to the current biomedical model of care to better prevent and treat the needs of the population. 5

While it is recognized that demands on the healthcare system are increasing rapidly, the biomedical model used to deal with these issues (which is the current model of healthcare provision in the UK) has largely remained unchanged over the years. The biomedical model takes the perspective that ill-health stems from biological factors and operates on the theory that good health and wellbeing is merely the absence of illness. Application of the model therefore focuses treatment on the management of symptoms and cure of disease from a biological perspective. This suggests that the biomedical approach is mainly reactive in nature and whilst rapid advancements in technology such as diagnostics and robotics have significantly improved patient outcomes and identification of early onset of disease, it does not fully extend into managing the social determinants that can play an important role in the prevention of disease. Therefore, despite its contribution in advancing many areas of biological and health research, the biomedical model has come under increasing scrutiny. 6 This is in part due to the growing recognition of the impact of those wider social determinants on health, ill-health and wellbeing including physical, mental and social wellbeing which moves the focus beyond individual physical abilities or dysfunction. 7–9 In order to address these determinants, action needs to be taken through developing policies in a range of non-medical areas such as social, economic and environment so that they regulate the commercial and corporate determinants. In this sense, we can quickly see that the traditional biological model rapidly becomes inadequate. With the current model, health care and clinical staff can do little to affect these determinants and as such can do little to assist the individual patient or society. The efficiency and effectiveness of clinical work will undoubtedly improve if staff have the ability to observe and understand the wider social determinants and consequences of the individual patients’ condition. Therefore, in order to provide a basis for understanding the determinants of disease and arriving at rational treatments and patterns of health care, a medical model must also take into account the patient, the social context in which they live, and a system devised by society to deal with the disruptive effects of illness, that is, the physician’s role and that of the health care system. Models such as Engel’s biopsychosocial model, 9 , 10 the social model of disability, social–ecological models of health 10 , 11 including the World Health Organisation’s framework for action on social determinants of health 8 , 9 are all proposed as attempting to integrate these wider social determinants.

However, the ability of health systems to effectively transition away from a dominant biomedical model to the adoption of a social model of health and care have yet to be fully developed. Responsibility for taking action on these social determinants will need to come from other sectors and policy areas and so future health policy will need to evolve into a more comprehensive and holistic social model of health and wellbeing. Wales’ flagship Wellbeing of Future Generations Act 12 for instance outlines ways of working towards sustainable development and includes the need to collaborate with society and communities in developing and achieving wellbeing goals. However, developing and implementing an effective operational model that allows multi-stakeholder integration will prove far more difficult to achieve than creating the polices. Furthermore, if the implementation of a robust model of social health is achievable, it’s efficiency, effectiveness and ability to deliver has yet to be proven. Therefore, any future model will need to extend past its conceptual development and provide an ability to manage the complex interactions that will exist between the stakeholders and polices.

Therefore, the use of the term ‘model’ poses its own challenges and debates. Different disciplines attribute differing parameters to what constitutes a model and this in turn may influence the interpretations or expectations surrounding what a model should comprise of or deliver. 13 According to numerous authors, a model has no ontological category and as such anything from physical entities, theoretical concepts, descriptive frameworks or equations can feasibly be considered a model. 14 It appears therefore, that much discussion has focussed on the move towards a ‘descriptive’ Social Model of Health and Wellbeing in an attempt to view health more holistically and identify a wider range of determinants that can impact on the health of the population. However, in defining an operational social model of health that can facilitate organizational change, there may be a need to consider a more systems- or process-based approach.

As a result, this review seeks to systematically explore the academic literature in order to better understand how a social model of health and wellbeing is conceptualized, implemented, operationalized and evaluated in health and social care.

The review seeks to address the research questions:

How is ‘a social model of health and wellbeing’ conceptualized?

How have social models of health and wellbeing been implemented and evaluated?

A systematic search of the literature was carried out between 6 January 2022 and 20 January 2022. Using the search terms shown in table 1 , a systematic search was carried out using online databases PsycINFO, ASSIA, IBSS, Medline, Web of Science, CINHAL and SCOPUS. English language and peer-reviewed journals were selected as limiters.

Search terms

Selection and extraction criteria

The search strategy considered research that explicitly included, framed, or adopted a ‘social model of health and wellbeing’. Each paper was checked for relevance and screened. The authors reviewed the literature using the Preferred Reporting Items for Systematic Reviews and Meta Analysis (PRISMA) method using the updated guidelines from 2020. 15   Figure 1 represents the process followed.

PRISMA flow chart.

Data extraction and analysis

A systematic search of the literature identified 222 eligible papers for inclusion in the final review. A data extraction table was used to extract information regarding location of the research, type of paper (e.g. review, empirical), service of interest and key findings. Quantitative studies were explored with a view to conducting a quantitative meta-analysis; however, given the disparate nature of the outcome measures, and research designs, this was deemed unfeasible. All included papers were coded using NVivo software with the identified research questions in mind, and re-analysed using Thematic Analysis 16 to explore common themes of relevance.

The majority of papers were from the USA (34%), with the UK (28%), Australia (16%), Canada (6%) and wider Europe (10%) also contributing to the field. The ‘other’ category (6%) was made up of single papers from other countries. Papers ranged in date from 1983 to 2021 with no noticeable temporal patterns in country of origin, health context or model definition. However, the volume of papers published relating to the social model for healthcare in each decade increased significantly, thus suggesting the increasing research interest towards the social model of healthcare. Table 2 shows the number of publications per decade that were identified from this study.

Publications identifying social models of healthcare.

Most of the papers were narrative reviews ( n  = 90) with a smaller number of systematic reviews ( n  = 9) and empirical research studies including qualitative ( n  = 47), quantitative ( n  = 39) and mixed methods ( n  = 14) research. The remaining papers ( n  = 23) comprised small samples of, for example, clinical commentaries, cost effectiveness analysis, discussion papers and impact assessment development papers. The qualitative meta-analysis identified five overarching themes in relation to the research questions, some with underlying sub-themes, which are outlined in figure 2 .

Overview of meta-synthesis themes.

The lack of a clear and unified definition of a social model of health and wellbeing

There was common recognition amongst the papers that a key aim of applying a social model of health and wellbeing was to better address the social determinants of health. Papers identified and reviewed relevant frameworks and models, which they later used to conceptualize or frame their approach when attempting to apply a social model of health. Amongst the most commonly referenced was the WHO’s framework. 17 Engel’s biopsychosocial model 9 which was referred to as a seminal framework by many of the researchers. However, once criticism of the biopsychosocial model was its inability to fully address social needs. As a result, a number of papers reported the development of new or enhanced models that used the biopsychosocial model as their underpinning ‘social model’ 18 , 19 but then extended their work by including a wider set of social elements in their resulting models. 20 The Social ecological model, 11 the Society-Behaviour-Biology Nexus, 21 and the Environmental Affordances Model are such examples. 22 Further examples of ‘Social Models’ included the Model of Social Determinants of Health 23 which framed specific determinants of interest (namely social gradient, stress, early life, social exclusion, work, unemployment, social support, addiction, food and transport). Similarly, Dahlgren and Whitehead’s ‘social model’ 10 illustrates social determinants via a range of influential factors from the individual to the wider cultural and socioeconomic influences. However, none of these papers formally developed a working ‘definition’ of a social model of health and wellbeing, instead applying guiding principles and philosophies associated with a social model to their discussions or interventions. 24 , 25

The need to understand context

Numerous articles highlight that in order to move towards a social model of health and wellbeing, it is important to understand the context of the environment in which the model will need to operate. This includes balancing the needs of the individual with the resulting model to have been co-created, developed and implemented within the community whilst ensuring that the complexity of interaction between the social determinants of health and their influence on health and wellbeing outcomes are delivered effectively and efficiently.

The literature identified the complex multi-disciplinary nature of a variety of conditions or situations involving medical care. These included issues such as, but not exclusively, chronic pain, 26 cancer, 27 older adult care 28 and dementia, 29 thus indicating the complex arrangement of medical issues that a model will need to address and, where many authors acknowledged that the frequently used biomedical models failed to fully capture the holistic nature and need of patients. Papers outlined some of the key social determinants of health affecting the specific population of interest in their own context, highlighting the interactions between wider socioeconomic and cultural factors such as poverty, housing, isolation and transport and health and wellbeing outcomes. Interventions that had successfully addressed individual needs and successful embedded services in communities reported improved outcomes for end users and staff in the form of empowerment, agency, education and belonging. 30 There was also recognition that the transition to more community-based care could be challenging for health and social care providers who were having to work outside of their traditional models of care and accept a certain level of risk.

The need for cultural change

A number of papers referred to the need for a ‘culture change’ or ‘cultural shift’ in order to move towards a social model of health and wellbeing. Papers identified how ‘culture change models’ were implemented as a way of adapting to a social model. It was recognized that for culture change models to be effective, staff and the general public needed to be fully engaged with the entire move towards a social model, informing and shaping the mechanisms for the cultural shift as well as the application of the model itself.

Integration and collaboration towards a holistic and person-centred approach

The importance of integration and collaboration between health professionals, (which includes public, private and third sector organizations), services users and patients were emphasized in the ambition to achieve best practice when applying a social model of health and wellbeing. Papers identified the reported benefits of improved collaboration between, and integration of services which included improved continuity of care throughout complex pathways, 31 improved return to home or other setting on discharge, 25 and social connectedness. 32 Numerous papers discussed the importance of multi-disciplinary teams who were able to support individuals beyond the medicalized model.

A number of papers suggested specific professional roles or structures that would be ideal to act as champions or integrators of collaborative services and communities. 25 , 33 These could act as a link between secondary, primary and community level care helping to identify patient needs and supporting the integration of relevant services.

Measuring and evaluating a social model of health

Individual papers applying and evaluating interventions based on a social model used a variety of methods to evaluate success. Amongst these, some of the most common outcome measures included; general self-report measures of outcomes such as mental health and perceptions of safety, 34 wellbeing, 35 life satisfaction and health social networks and support 19 Some included condition specific self-report outcomes relevant to the condition in question (e.g. pregnancy, anxiety) and pain inventories. 36 Other papers considered the in-depth experiences of users or service implementers through qualitative techniques such as in-person interviews. 37 , 38

However, the complexity of developing effective methods to evaluate social models of health were recognized. The need to consider the complex interactions between social determinants, and health, wellbeing, economic and societal outcomes posed particular challenges in developing consistency across evaluations that would enable a conclusive evaluation of the benefits of social models to wider health systems and societal health. Some criticized the over-reliance of quantitative and evidence-based practice methods of evaluation highlighting how these could fail to fully capture the complexity of human behaviour and the manner in which their lives could be affected.

The aim of this systematic review was to better understand how a social model of health and wellbeing is conceptualized, implemented and evaluated in health and social care. The review sought to address the research questions identified in the ‘Introduction’ section of this paper.

With regards to the conceptualization of a social model of health and wellbeing, analysis of the literature suggests that whilst the ethos, values and aspirations of achieving a unified model appears to have consensus. However, a fundamental weakness exists in that there is no single unified definition or operational model of a social model of health and wellbeing applied to the health and social care sector. The decision about how best to conceptualize a ‘social model’ is important both in terms of its operational value but also the implication of the associated semantics. However, without a single or unified definition then implementation or further, operationalization of any model will be almost impossible to develop. Furthermore, use of the term ‘social model’ arguably loses site of the biological factors that are clearly relevant in many elements of clinical medicine. Furthermore, there is no clarification in the literature about what would ‘not’ be considered a social model of health and wellbeing, potentially leading to confusion within health and social care sectors when addressing their wider social remit. This raises questions and requires decisions about whether implementation of a social model of health and wellbeing will need to work alongside or replace the existing biomedical approach.

Authors have advocated that a social model provides a way of ‘thinking’ or articulating an organization’s values and culture. 24 Common elements of the values associated with a social model amongst the papers reviewed included recognition and awareness of the social determinants of health, increased focus on preventative rather than reactive care, and similarly the importance of quality of ‘life’ as opposed to a focus on quality of ‘care’. However, whilst this approach enables individual services to consider how well their own practices align with a social model, the authors suggest that this does not provide large organizations such as the NHS, with multifaceted services and complex internal and external connections and networks, sufficient guidance to enable large scale evaluation or transition to a widespread operational model of a social model of health and wellbeing. This raises questions about what the model should be: whether its function is to support communication of a complex ethos to encourage reflection and engagement of its staff and end users, or to develop the current illustrative framework into a predictive model that can be utilized as an evaluative tool to inform and measure the success of widespread systems change.

Regarding the potential implementation of a future social model of health and wellbeing, none of the papers evaluated the complex widespread organizational implementation of a social model, instead focusing on specific organizational contexts of services such as long-term care in care homes, etc. Despite this, common elements of successful implementation did emerge from the synthesis. This included the need to wholeheartedly engage and be inclusive of end users in policy and practice change to fully understand the complexity of their social worlds and to ensure that changes to practice and policy were ‘developed with’, as opposed to ‘create for’, the wider public. This also involved ensuring that health, social care and wider multi-disciplinary teams were actively included in the process of culture change from an early stage.

Implications for future research

The analysis identifies that a significant change of mindset and removal of perceived and actual hierarchical structures (that are historically embedded in health and social care structures) amongst both staff and public is needed although, eradicating socially embedded hierarchies will pose significant challenges in practice. Furthermore, the study revealed that many of the models proposed were conceptually underdeveloped and lacked the capability to be operationalized which in turn compromised their ability to be empirically tested. Therefore, in order that a future ‘implementable and operational’ model of social care and wellbeing can be created, further research into organizational behaviours, organizational learning and stakeholder theory (amongst others) applied to the social care and health environment is needed.

Towards defining a social model of health and wellbeing

In attempting to conceptualize a definition for a social model of health and wellbeing, it is important to note that the model needs to be sufficiently broad in scope in order to include the prevailing biomedical while also including the need to draw in the social determinants that provide a view and future trajectory towards social health and wellbeing. Therefore, the authors suggest that the ‘preventative’ approach brought by the improvements in the social health determinants (social, cultural, political, environmental ) need to be balanced effectively with the ‘remedial/preventative’ focus of the biomedical model (and the associated advancements in diagnostics, technology, vaccines, etc), ensuring that a future model drives cultural change; improved integration and collaboration towards a holistic and person-centred approach whilst ensuring engagement with citizens, users, multi-disciplinary teams and partner organizations to ensure that transition towards a social model of health and wellbeing is undertaken.

Through a comprehensive literature analysis, this paper has provided evidence that advocates a move towards a social model of health and wellbeing. However, the study has predominantly considered mainly literature from the USA, UK, Canada and Australia and therefore is limited in scope at this stage. The authors are aware of the need to consider research undertaken in non-English speaking countries where a considerable body of knowledge also exists and which will add to further discussion about how that work dovetails into this body of literature and, how it aligns with the biomedical perspective. There is a need for complex organizations such as the NHS and allied organizations to agree a working definition of their model of health and wellbeing, whether that be a social model of health and wellbeing, a biopsychosocial model, a combined model, or indeed a new or revised perspective. 39

One limitation seen of the models within this study is that at a systems level, most models were conceptual models that characterized current systems or conditions and interventions to the current system that result in localized improvements in systems’ performance. However, for meaningful change to occur, a ‘future state’ model may need to focus on a behavioural systems approach allowing modelling of the complete system to take place in order to understand how the elements within the model 40 behave under different external conditions and how these behaviours affect overall system performance.

Furthermore, considerable work will be required to engage on a more equal footing with the public, health and social care staff as well as wider supporting organizations in developing workable principles and processes that fully embrace the equality of a social model and challenging the ‘power’ imbalances of the current biomedical model.

Supplementary data are available at EURPUB online.

This research was funded/commissioned by Hywel Dda University Health Board. The research was funded in two phases.

Conflicts of interest: None declared.

The datasets generated and/or analysed during the current study are available in the Data Archive at Aberystwyth University and have been included in the supplementary file attached to this submission. A full table of references for studies included in the review will be provided as a supplementary document. The references below refer to citations in the report which are in addition to the included studies of the synthesis.

The review identified five themes namely: the lack of a clear definition of a social model of health and wellbeing; the need to understand context; the need for cultural change; improved integration and collaboration towards a holistic and person-centred approach; measuring and evaluating the performance of a social model of health.

The review identified a need for organizations to decide on how a social model is to be defined especially at the interfaces between partner organizations and communities.

The implications for public policy in this paper highlights the importance of engagement with citizens, users, multi-disciplinary teams and partner organizations to ensure that transition towards a social model of health and wellbeing is undertaken with holistic needs as a central value.

British Medical Association (ND). An NHS under pressure. Accessed via An NHS under pressure (bma.org.uk). https://www.bma.org.uk/advice-and-support/nhs-delivery-and-workforce/pressures/an-nhs-under-pressure (26 June 2023, date last accessed).

Nuffield Trust ( 2022 ). NHS performance summary. Accessed via NHS performance summary | The Nuffield Trust. https://www.nuffieldtrust.org.uk/news-item/nhs-performance-summary-january-february-2022 (26 June 2023, date last accessed).

NHS confederation , ( 2022 ) Running hot: The impact of the Covid-19 pandemic on mental health services. Accessed via Running hot | NHS Confederation. https://www.nhsconfed.org/publications/running-hot (26 June 2023, date last accessed).

Gemine R , Davies GR , Tarrant S , et al.    Factors associated with work-related burnout in NHS staff during COVID-19: a cross-sectional mixed methods study . BMJ Open   2021 ; 11 : e042591 .

Google Scholar

Iacobucci G.   Medical models of care needs updating say experts . BMJ   2018 ; 360 : K1034 .

Podgorski CA , Anderson SD , Parmar J.   A biopsychosocial-ecological framework for family-framed dementia care . Front Psychiatry   2021 ; 12 : 744806 .

Marmot M.   Social determinants of health inequalities . Lancet   2005 ; 365 : 1099 – 104 .

World Health Organisation ( 1946 ) Preamble to the Constitution of the World Health Organization as adopted by the International Health Conference . New York: World Health Organization, 19–22 June, 1946.

World Health Organisation ( 2010 ). A conceptual framework for action on the social determinants of health. Accessed via A Conceptual Framework for Action on the Social Determinants of Health (who.int) (26 June 2023, date last accessed).

Engel G.   The need for a new medical model: a challenge for biomedicine . Science   1977 ; 196 : 129 – 36 .

Dahlgren G , Whitehead M. ( 2006 ). European strategies for tackling social inequities in health: Levelling up part 2. Studies on Social Economic Determinants of Population Health, 1–105. Available at: http://www.euro.who.int/__data/assets/pdf_file/0018/103824/E89384.pdf (12 October 2023, date last accessed).

McLeroy KR , Bibeau D , Steckler A , Glanz K.   An ecological perspective on health promotion programs . Health Educ Q   1988 ; 15 : 351 – 77 .

Welsh Government , Wellbeing of Future Generations Act 2015. Available at: https://www.gov.wales/sites/default/files/publications/2021-10/well-being-future-generations-wales-act-2015-the-essentials-2021.pdf (12 October 2023, date last accessed).

Stanford Encyclopaedia of Philosophy ( 2006 , 2020). Models in Science. Available at: https://plato.stanford.edu/entries/models-science/ (26 June 2023, date last accessed).

Page MJ , McKenzie JE , Bossuyt PM , et al.    The PRISMA 2020 statement: an updated guideline for reporting systematic reviews . BMJ   2021 ; 372 : n71 .

Braun V , Clarke V.   Using thematic analysis in psychology . Qual Res Psychol   2006 ; 3 : 77 – 101 .

Thomas J , Harden A.   Methods for the thematic synthesis of qualitative research in systematic reviews . BMC Med Res Methodol   2008 ; 8 : 45 .

Solar O , Irwin A. ( 2016 ) “A conceptual framework for action on the social determinants of health. Geneva, Switzerland: WHO; 2010”. (Social determinants of health discussion paper 2 (policy and practice)). Available at: http://www.who.int/sdhconference/resources/ConceptualframeworkforactiononSDH_eng.pdf (12 October 2023, date last accessed).

Farre A , Rapley T.   The new old (and old new) medical model: four decades navigating the biomedical and psychosocial understandings of health and illness . Healthcare   2017 ; 5 : 88 .

Smedema SM.   Evaluation of a concentric biopsychosocial model of well-being in persons with spinal cord injuries . Rehabil Psychol   2017 ; 62 : 186 – 97 . PMID: 28569533.

Robles B , Kuo T , Thomas Tobin CS.   What are the relationships between psychosocial community characteristics and dietary behaviors in a racially/ethnically diverse urban population in Los Angeles county? . Int J Environ Res Public Health   2021 ; 18 : 9868 .

Glass TA , McAtee MJ.   Behavioral science at the crossroads in public health: extending horizons, envisioning the future . Soc Sci Med   2006 ; 62 : 1650 – 71 .

Mezuk B , Abdou CM , Hudson D , et al.    "White Box" epidemiology and the social neuroscience of health behaviors: the environmental affordances model . Soc Ment Health   2013 ; 3 : 10.1177/2156869313480892

Wilkinson RG , Marmot M , editors. Social Determinants of Health: The Solid Facts . Copenhagen, Denmark: World Health Organization , 2003 .

Google Preview

Mannion R , Davies H.   Understanding organisational culture for healthcare quality improvement . BMJ   2018 ; 363 : k4907 .

Blount A , Bayona J.   Toward a system of integrated primary care . Fam Syst Health   1994 ; 12 : 171 – 82 .

Berger MY , Gieteling MJ , Benninga MA.   Chronic abdominal pain in children . BMJ   2007 ; 334 : 997 – 1002 . PMID: 17494020; PMCID: PMC1867894.

Berríos-Rivera R , Rivero-Vergne A , Romero I.   The pediatric cancer hospitalization experience: reality co-constructed . J Pediatr Oncol Nurs   2008 ; 25 : 340 – 53 .

Doty MM , Koren MJ , Sturla EL. ( 2008 ). Culture change in nursing homes: How far have we come? Findings from the Commonwealth Fund 2007 National Survey. The Commonwealth Fund, 91. Available at: http://www.commonwealthfund.org/Content/Publications/Fund-Reports/2008/May/Culture-Change-in-NursingHomes-How-Far-Have-We-Come-Findings-FromThe-Commonwealth-Fund-2007-Nati.aspx (16 October 2023, date last accessed).

Robinson L , Tang E , Taylor J.   Dementia: timely diagnosis and early intervention . BMJ   2015 ; 350 : h3029 .

Baxter S , Johnson M , Chambers D , et al.    Understanding new models of integrated care in developed countries: a systematic review . Health Serv Deliv Res   2018 ; 6 : 1 .

Seys D , Panella M , VanZelm R , et al.    Care pathways are complex interventions in complex systems: new European Pathway Association framework . Int J Care Coord   2019 ; 22 : 5 – 9 .

Agarwal G , Brydges M.   Effects of a community health promotion program on social factors in a vulnerable older adult population residing in social housing” . BMC Geriatr   2018 ; 18 : 95 . PMID: 29661136; PMCID: PMC5902999.

Franklin CM , Bernhardt JM , Lopez RP , et al.    Interprofessional teamwork and collaboration between community health workers and healthcare teams: an integrative review . Health Serv Res Manag Epidemiol   2015 ; 2 : 2333392815573312 . PMID: 28462254; PMCID: PMC5266454.

Gagné T , Henderson C , McMunn A.   Is the self-reporting of mental health problems sensitive to public stigma towards mental illness? A comparison of time trends across English regions (2009-19) . Soc Psychiatry Psychiatr Epidemiol   2023 ; 58 : 671 – 80 . PMID: 36473961; PMCID: PMC9735159.

Geyh S , Nick E , Stirnimann D , et al.    Biopsychosocial outcomes in individuals with and without spinal cord injury: a Swiss comparative study . Spinal Cord   2012 ; 50 : 614 – 22 .

Davies C , Knuiman M , Rosenberg M.   The art of being mentally healthy: a study to quantify the relationship between recreational arts engagement and mental well-being in the general population . BMC Public Health   2016 ; 16 : 15 . PMID: 26733272; PMCID: PMC4702355.

Duberstein Z , Brunner J , Panisch L , et al.    The biopsychosocial model and perinatal health care: determinants of perinatal care in a community sample . Front Psychiatry   2021 ; 12 : 746803 .

The King’s Fund , ( 2021 ). Health inequalities in a nutshell. Accessed via Health inequalities in a nutshell | The King's Fund (kingsfund.org.uk) https://www.kingsfund.org.uk/projects/nhs-in-a-nutshell/health-inequalities (23 October 2023, date last accessed)

Blount A.   Integrated primary care: organizing the evidence . Fam Syst Health   2003 ; 21 : 121 – 33 .

Email alerts

Citing articles via.

• Contact EUPHA
• Recommend to your Library

Affiliations

• Online ISSN 1464-360X
• Print ISSN 1101-1262
• Copyright © 2024 European Public Health Association
• About Oxford Academic
• Publish journals with us
• University press partners
• What we publish
• New features  
• Open access
• Institutional account management
• Rights and permissions
• Get help with access
• Accessibility
• Advertising
• Media enquiries
• Oxford University Press
• Oxford Languages
• University of Oxford

Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide

• Copyright © 2024 Oxford University Press
• Cookie settings
• Cookie policy
• Privacy policy
• Legal notice

This Feature Is Available To Subscribers Only

Sign In or Create an Account

This PDF is available to Subscribers Only

For full access to this pdf, sign in to an existing account, or purchase an annual subscription.