The attitude-behaviour gap in biosecurity: Applying social theories to understand the relationships between commercial chicken farmers' attitudes and behaviours

Introduction Traditionally, it is believed that people's behaviours align with their attitudes; however, during COVID-19 pandemic, an attitude-behaviour gap in relation to preventive measures has been observed in recent studies. As such, the mixed-methods research was used to examine the relationships between farmers' biosecurity attitudes and behaviours in Taiwan's chicken industry based on the cognitive consistency theory. Methods Content analysis of face-to-face interviews with 15 commercial chicken farmers identified their biosecurity responses to infectious disease threats. Results The results indicated the mismatch of farmers' attitudes and behaviours towards specific biosecurity measures, in that they act differently than they think. The findings of the qualitative research allowed the research team to conduct the subsequent quantitative, confirmatory assessment to investigate the mismatch of farmers' attitudes and behaviours in 303 commercial broiler farmers. Survey data were analyzed to discover the relationships between farmers' attitudes and behaviours in relation to 29 biosecurity measures. The results show a mixed picture. The percentage of the farmers who had the attitude-behaviour gap towards 29 biosecurity measures ranged from 13.9 to 58.7%. Additionally, at the 5% significant level, there is an association between farmers' attitudes and behaviours for 12 biosecurity measures. In contrast, a significant association does not exist for the other 17 biosecurity measures. Specifically, out of the 17 biosecurity measures, the disconnection of farmers' attitudes and behaviours was observed in three specific biosecurity measures such as using a carcass storage area. Discussion Based on a fairly large sample of farmers in Taiwan, this study confirms the existence of an attitude-behaviour gap in context and applies social theories to provide an in-depth understanding of how infectious diseases are managed in the animal health context. As the results demonstrate the necessity of tailoring biosecurity strategies to address the gap, it is time to reconsider the current approach by understanding farmers' real attitudes and behaviours in relation to biosecurity for the success of animal disease prevention and control at the farm level.

[1]  Deanna D. Sellnow,et al.  Effects of message delivery on cross-cultural biosecurity compliance: Insights from experimental simulations , 2022, Frontiers in Veterinary Science.

[2]  Julia M. Smith,et al.  Assessing strategic, tactical, and operational decision-making and risk in a livestock production chain through experimental simulation platforms , 2022, Frontiers in Veterinary Science.

[3]  Julia M. Smith,et al.  Comparing behavioral risk assessment strategies for quantifying biosecurity compliance to mitigate animal disease spread , 2022, Frontiers in Veterinary Science.

[4]  Katherine Hood,et al.  Salmonella enterica frequency in backyard chickens in Vermont and biosecurity knowledge and practices of owners , 2022, Frontiers in Veterinary Science.

[5]  E. Jackson,et al.  Determinants of farmers' biosecurity mindset: A social-ecological model using systems thinking , 2022, Frontiers in Veterinary Science.

[6]  S. Jang Social-ecological factors related to preventive behaviors during the COVID-19 pandemic in South Korea , 2022, PloS one.

[7]  D. Trafimow,et al.  Barriers to Converting Applied Social Psychology to Bettering the Human Condition , 2022, Basic and Applied Social Psychology.

[8]  R. Christley,et al.  The Role of Biosecurity in the Control of Campylobacter: A Qualitative Study of the Attitudes and Perceptions of UK Broiler Farm Workers , 2021, Frontiers in Veterinary Science.

[9]  J. Epstein,et al.  Mental Model of Malaysian Pig Farmers in Implementing Disease Prevention and Control Practices , 2021, Frontiers in Veterinary Science.

[10]  Deanna D. Sellnow,et al.  Message Delivery Strategy Influences Willingness to Comply With Biosecurity , 2021, Frontiers in Veterinary Science.

[11]  Allison R. Casola,et al.  Mask Use During COVID-19: A Social-Ecological Analysis , 2021, Health promotion practice.

[12]  Nainan Wen,et al.  What motivates Chinese consumers to avoid information about the COVID-19 pandemic?: The perspective of the stimulus-organism-response model , 2020, Information Processing & Management.

[13]  Julia M. Smith,et al.  Emulating Agricultural Disease Management: Comparing Risk Preferences Between Industry Professionals and Online Participants Using Experimental Gaming Simulations and Paired Lottery Choice Surveys , 2021, Frontiers in Veterinary Science.

[14]  C. Saegerman,et al.  Cattle farmers' perception of biosecurity measures and the main predictors of behaviour change: the first European-wide pilot study. , 2020, Transboundary and emerging diseases.

[15]  T. Campbell,et al.  Barriers and facilitators of adherence to social distancing recommendations during COVID-19 among a large international sample of adults , 2020, PloS one.

[16]  D. Maye,et al.  Missed Opportunities? Covid-19, Biosecurity and One Health in the United Kingdom , 2020, Frontiers in Veterinary Science.

[17]  Sebastian J. Goerg,et al.  The behavioural challenge of the COVID-19 pandemic: indirect measurements and personalized attitude changing treatments (IMPACT) , 2020, Royal Society Open Science.

[18]  Deepak L. Bhatt,et al.  Association Between Universal Masking in a Health Care System and SARS-CoV-2 Positivity Among Health Care Workers. , 2020, JAMA.

[19]  Xueying Du,et al.  Hand Hygiene, Mask-Wearing Behaviors and Its Associated Factors during the COVID-19 Epidemic: A Cross-Sectional Study among Primary School Students in Wuhan, China , 2020, International journal of environmental research and public health.

[20]  Luke Trinity,et al.  Effects of Social Cues on Biosecurity Compliance in Livestock Facilities: Evidence From Experimental Simulations , 2019, Frontiers in Veterinary Science.

[21]  Dominik J. Leiner Too Fast, too Straight, too Weird: Non-Reactive Indicators for Meaningless Data in Internet Surveys , 2019 .

[22]  A. Allepuz,et al.  Dairy farmers’ decision‐making to implement biosecurity measures: A study of psychosocial factors , 2019, Transboundary and emerging diseases.

[23]  L. D. Wang,et al.  Chinese poultry farmers' decision‐making for avian influenza prevention: a qualitative analysis , 2019, Zoonoses and public health.

[24]  D. Kelton,et al.  Canadian dairy farmers' perception of the efficacy of biosecurity practices. , 2019, Journal of dairy science.

[25]  Laurens Klerkx,et al.  To cluster or not to cluster farmers? Influences on network interactions, risk perceptions, and adoption of aquaculture practices , 2019, Agricultural Systems.

[26]  Julia M. Smith,et al.  Risk Attitudes Affect Livestock Biosecurity Decisions With Ramifications for Disease Control in a Simulated Production System , 2019, Front. Vet. Sci..

[27]  A. Goodridge,et al.  Control of paratuberculosis: who, why and how. A review of 48 countries , 2019, BMC Veterinary Research.

[28]  Deanna D. Sellnow,et al.  Willingness to Comply With Biosecurity in Livestock Facilities: Evidence From Experimental Simulations , 2019, Front. Vet. Sci..

[29]  Kin Wing Chan,et al.  The Suzhi farmer: Constructing and contesting farming Subjectivities in post-Socialist China , 2019, Journal of Rural Studies.

[30]  Chia-Chen Chen,et al.  What drives impulse buying behaviors in a mobile auction? The perspective of the Stimulus-Organism-Response model , 2018, Telematics Informatics.

[31]  J. Houdmont,et al.  Application of multiple behaviour change models to identify determinants of farmers' biosecurity attitudes and behaviours. , 2018, Preventive veterinary medicine.

[32]  J. Dewulf,et al.  Perception, motivators and obstacles of biosecurity in cattle production , 2018, Vlaams Diergeneeskundig Tijdschrift.

[33]  Robert M. Christley,et al.  Modeling Dynamic Human Behavioral Changes in Animal Disease Models: Challenges and Opportunities for Addressing Bias , 2018, Front. Vet. Sci..

[34]  K. Kirkwood Review: Directed qualitative content analysis: the description and elaboration of its underpinning methods and data analysis process , 2018, Journal of research in nursing : JRN.

[35]  M. Vaismoradi,et al.  Directed qualitative content analysis: the description and elaboration of its underpinning methods and data analysis process , 2018, Journal of research in nursing : JRN.

[36]  E. Fèvre,et al.  Identification of production challenges and benefits using value chain mapping of egg food systems in Nairobi, Kenya , 2018, Agricultural systems.

[37]  M. Hernandez-Jover,et al.  Devolved responsibility and on-farm biosecurity: practices of biosecure farming care in livestock production , 2018 .

[38]  Luciana de Cássia Nunes Nascimento,et al.  Theoretical saturation in qualitative research: an experience report in interview with schoolchildren. , 2018, Revista brasileira de enfermagem.

[39]  M. Dione,et al.  Risk Factors for African Swine Fever in Smallholder Pig Production Systems in Uganda , 2017, Transboundary and emerging diseases.

[40]  B. Vicari,et al.  Validating Earnings in the German National Educational Panel Study - Do Interviewers Have an Impact on Measurement Accuracy? , 2017, International Journal of Population Data Science.

[41]  Zeying Huang,et al.  Factors affecting Chinese broiler farmers' main preventive practices in response to highly pathogenic avian influenza. , 2016, Preventive veterinary medicine.

[42]  H. Buchanan,et al.  Exploring Attitudes and Beliefs towards Implementing Cattle Disease Prevention and Control Measures: A Qualitative Study with Dairy Farmers in Great Britain , 2016, Animals : an open access journal from MDPI.

[43]  A. Mankad Psychological influences on biosecurity control and farmer decision-making. A review , 2016, Agronomy for Sustainable Development.

[44]  Z. Liu,et al.  Determinants of Knowledge and Biosecurity Preventive Behaviors for Highly Pathogenic Avian Influenza Risk Among Chinese Poultry Farmers , 2016, Avian Diseases.

[45]  Carolyn A. Young,et al.  Achieving saturation in thematic analysis: development and refinement of a codebook. , 2014 .

[46]  David A. Hennessy,et al.  Biosecurity and disease management in China’s animal agriculture sector , 2015 .

[47]  Michael D Fetters,et al.  Achieving integration in mixed methods designs-principles and practices. , 2013, Health services research.

[48]  P. Farrelly,et al.  Community and Public Health Nursing , 2013 .

[49]  R. Christley,et al.  Cattle producers’ perceptions of biosecurity , 2013, BMC Veterinary Research.

[50]  Tristan L. Davison TheEffect of the Recession of 2007-2009 in the Community Bank Environment , 2013 .

[51]  Kirsi-Maarit Siekkinen,et al.  Measuring the costs of biosecurity on poultry farms: a case study in broiler production in Finland , 2012, Acta Veterinaria Scandinavica.

[52]  Elliot T. Berkman,et al.  The neural basis of rationalization: cognitive dissonance reduction during decision-making. , 2011, Social cognitive and affective neuroscience.

[53]  E. Kristensen,et al.  Danish dairy farmers' perception of biosecurity. , 2011, Preventive veterinary medicine.

[54]  L. Toma,et al.  Utilising a farmer typology to understand farmer behaviour towards water quality management: Nitrate Vulnerable Zones in Scotland , 2011 .

[55]  Henk Hogeveen,et al.  Perceptions, circumstances and motivators that influence implementation of zoonotic control programs on cattle farms. , 2010, Preventive veterinary medicine.

[56]  Anthony J. Onwuegbuzie,et al.  Mixed Research as a Tool for Developing Quantitative Instruments , 2010 .

[57]  M. Sully,et al.  The Effect of Trust on West Australian Farmers' Responses to Infectious Livestock Diseases , 2009 .

[58]  G. Gunn,et al.  An exploration of the drivers to bio-security collective action among a sample of UK cattle and sheep farmers. , 2008, Preventive veterinary medicine.

[59]  Helvi Kyngäs,et al.  The qualitative content analysis process. , 2008, Journal of advanced nursing.

[60]  Rob J.F. Burton,et al.  Exploring Farmers' Cultural Resistance to Voluntary Agri-environmental Schemes , 2008 .

[61]  Adam Kowol The theory of cognitive dissonance By , 2008 .

[62]  J. Casal,et al.  Biosecurity measures on swine farms in Spain: perceptions by farmers and their relationship to current on-farm measures. , 2007, Preventive veterinary medicine.

[63]  V. Papavassiliou,et al.  Emerging zoonoses and vector-borne infections affecting humans in Europe , 2007, Epidemiology and Infection.

[64]  John W. Creswell,et al.  Designing and Conducting Mixed Methods Research , 2006 .

[65]  Qing Chang,et al.  How Low Should You Go? Low Response Rates and the Validity of Inference in IS Questionnaire Research , 2006, J. Assoc. Inf. Syst..

[66]  V. Braun,et al.  Using thematic analysis in psychology , 2006 .

[67]  J. Stegeman,et al.  Risk factors for the introduction of high pathogenicity Avian Influenza virus into poultry farms during the epidemic in the Netherlands in 2003. , 2005, Preventive veterinary medicine.

[68]  E. Hallerman,et al.  Fish Disease and Biosecurity: Attitudes, Beliefs, and Perceptions of Managers and Owners of Commercial Finfish Recirculating Facilities in the United States and Canada , 2005 .

[69]  D. Wegener,et al.  The Structure of Attitudes. , 2005 .

[70]  A. Halmi Strategies of qualitative research , 2004 .

[71]  Melanie C. Green,et al.  Telephone versus Face-to-Face Interviewing of National Probability Samples with Long Questionnaires: Comparisons of Respondent Satisficing and Social Desirability Response Bias , 2003 .

[72]  James Price Dillard,et al.  The Persuasion Handbook: Developments in Theory and Practice , 2002 .

[73]  E. Harmon-Jones,et al.  PERSONALITY AND SOCIAL PSYCHOLOGY BULLETIN Harmon-Jones, Harmon-Jones / COGNITIVE DISSONANCE MODEL Testing the Action-Based Model of Cognitive Dissonance: The Effect of Action Orientation on Postdecisional Attitudes , 2002 .

[74]  E. Harmon-Jones,et al.  A Cognitive Dissonance Theory Perspective on Persuasion , 2002 .

[75]  M E Woolhouse,et al.  Risk factors for human disease emergence. , 2001, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[76]  J. N. Bassili Meta-judgmental versus operative indexes of psychological attributes: The case of measures of attitude strength. , 1996 .

[77]  S. Yantis,et al.  Amount of information about the attitude object and attitude-behavior consistency. , 1985, Journal of personality and social psychology.

[78]  C. Brodsky The Discovery of Grounded Theory: Strategies for Qualitative Research , 1968 .

[79]  J. Creswell Qualitative inquiry and research design: Choosing among five approaches, 2nd ed. , 2007 .

[80]  L. Festinger,et al.  Cognitive consequences of forced compliance. , 2011, Journal of abnormal psychology.

[81]  Elliot Aronson,et al.  The effect of severity of initiation on liking for a group. , 1959 .

[82]  F. Heider The psychology of interpersonal relations , 1958 .

[83]  Bilge Mutlu,et al.  Qualitative Analysis , 1928, Nature.

[84]  K. Shadan,et al.  Available online: , 2012 .