scholarly journals Understanding Farmers' Behavior and Their Decision-Making Process in the Context of Cattle Diseases: A Review of Theories and Approaches

2021 ◽  
Vol 8 ◽  
Author(s):  
Marit M. Biesheuvel ◽  
Inge M. G. A. Santman-Berends ◽  
Herman W. Barkema ◽  
Caroline Ritter ◽  
John Berezowski ◽  
...  
Keyword(s):  
Behavior Change ◽  
Disease Control ◽  
Actual Behavior ◽  
Theoretical Frameworks ◽  
Behavioral Determinants ◽  
Behavior Change Interventions ◽  
Cattle Diseases ◽  
Control And Prevention ◽  
Stakeholder Behavior ◽  
Successful Change

Understanding farmers' behavior regarding disease control is essential to successfully implement behavior change interventions that improve uptake of best practices. A literature review was conducted to identify theoretical underpinnings, analytical methodologies, and key behavioral determinants that have been described to understand farmers' behavior in disease control and prevention on cattle farms. Overall, 166 peer-reviewed manuscripts from studies conducted in 27 countries were identified. In the past decade, there were increasing reports on farmers' motivators and barriers, but no indication of application of appropriate social science methods. Furthermore, the majority (58%) of reviewed studies lacked a theoretical framework in their study design. However, when a theoretical underpinning was applied, the Theory of Planned Behavior was most commonly used (14% of total). The complexity of factors impacting farmers' behavior was illustrated when mapping all described key constructs of the reviewed papers in behavior change frameworks, such as the socioecological framework and the Capability, Opportunity and Motivation Behavior (COM-B) model. Constructs related to personal influences and relationships between farmers and veterinarians were overrepresented, whereas constructs related to other interpersonal and contextual environments were not extensively studied. There was a general lack of use of validated scales to measure constructs and empirically validated theoretical frameworks to understand and predict farmers' behavior. Furthermore, studies mainly focused on measurements of intention of stakeholder behavior rather than actual behavior, although the former is a poor predictor of the latter. Finally, there is still a lack of robust evidence of behavior change interventions or techniques that result in a successful change in farmers' behavior. We concluded that for a sustainable behavior change, studies should include wider constructs at individual, interpersonal, and contextual levels. Furthermore, the use of empirically validated constructs and theoretical frameworks is encouraged. By using coherent frameworks, researchers could link constructs to design interventions, and thereby take the first step toward theory-driven, evidence-based interventions to influence farmers' behavior for disease control.

scholarly journals Understanding Health Behavior Technology Engagement: Pathway to Measuring Digital Behavior Change Interventions

10.2196/14052 ◽  
2019 ◽  
Vol 3 (4) ◽  
pp. e14052 ◽  
Author(s):  
Heather Cole-Lewis ◽  
Nnamdi Ezeanochie ◽  
Jennifer Turgiss
Keyword(s):  
Health Behavior ◽  
Behavior Change ◽  
User Experience ◽  
User Engagement ◽  
User Interactions ◽  
Behavior Change Intervention ◽  
Behavioral Determinants ◽  
Behavior Change Interventions ◽  
Frequency Of Use ◽  
Measurement And Evaluation

Researchers and practitioners of digital behavior change interventions (DBCI) use varying and, often, incongruent definitions of the term “engagement,” thus leading to a lack of precision in DBCI measurement and evaluation. The objective of this paper is to propose discrete definitions for various types of user engagement and to explain why precision in the measurement of these engagement types is integral to ensuring the intervention is effective for health behavior modulation. Additionally, this paper presents a framework and practical steps for how engagement can be measured in practice and used to inform DBCI design and evaluation. The key purpose of a DBCI is to influence change in a target health behavior of a user, which may ultimately improve a health outcome. Using available literature and practice-based knowledge of DBCI, the framework conceptualizes two primary categories of engagement that must be measured in DBCI. The categories are health behavior engagement, referred to as “Big E,” and DBCI engagement, referred to as “Little e.” DBCI engagement is further bifurcated into two subclasses: (1) user interactions with features of the intervention designed to encourage frequency of use (ie, simple login, games, and social interactions) and make the user experience appealing, and (2) user interactions with behavior change intervention components (ie, behavior change techniques), which influence determinants of health behavior and subsequently influence health behavior. Achievement of Big E in an intervention delivered via digital means is contingent upon Little e. If users do not interact with DBCI features and enjoy the user experience, exposure to behavior change intervention components will be limited and less likely to influence the behavioral determinants that lead to health behavior engagement (Big E). Big E is also dependent upon the quality and relevance of the behavior change intervention components within the solution. Therefore, the combination of user interactions and behavior change intervention components creates Little e, which is, in turn, designed to improve Big E. The proposed framework includes a model to support measurement of DBCI that describes categories of engagement and details how features of Little e produce Big E. This framework can be applied to DBCI to support various health behaviors and outcomes and can be utilized to identify gaps in intervention efficacy and effectiveness.

scholarly journals Exploring the Behavioral Determinants of COVID-19 Vaccine Acceptance among an Urban Population in Bangladesh: Implications for Behavior Change Interventions

2021 ◽  
Author(s):  
Md Abul Kalam ◽  
Thomas P. Davis ◽  
Shahanaj Shano ◽  
Nasir Uddin ◽  
Md. Ariful Islam ◽  
...  
Keyword(s):  
Behavior Change ◽  
Health Belief Model ◽  
Health Belief ◽  
Negative Consequences ◽  
Vaccine Acceptance ◽  
Perceived Safety ◽  
Behavioral Determinants ◽  
Behavior Change Interventions ◽  
Belief Model ◽  
The Health Belief Model

AbstractBackgroundWhile vaccines ensure individual protection against COVID-19 infection, delay in receipt or refusal of vaccines will have both individual and community impacts. The behavioral factors of vaccine hesitancy or refusal are a crucial dimension that need understanding to implicate appropriate interventions. The aim of this study was to assess the behavioral determinants of COVID-19 vaccine acceptance and to provide recommendations to increase the uptake of COVID-19 vaccines in Bangladesh.MethodsWe employed a Barrier Analysis (BA) approach to examine twelve potential behavioral determinants (drawn from the Health Belief Model and Theory of Reasoned Action [TRA]) of intended vaccine acceptance. We conducted 45 interviews with those who intended to take the vaccine (Acceptors) and another 45 interviews with those who did not have that intention (Non-acceptors). We performed data analysis to find statistically significant differences and to identify which beliefs were most highly associated with acceptance and non-acceptance with COVID-19 vaccines.ResultsCOVID-19 vaccine Acceptors in Dhaka were different from Non-acceptors in terms of many of their beliefs and responses. The behavioral determinants associated with the behavior included perceived social norms, perceived safety of COVID-19 vaccines and trust in them, perceived risk/susceptibility, perceived self-efficacy, perceived positive and negative consequences, perceived action efficacy, perceived severity of COVID-19, access, and perceived divine will. In line with the Health Belief Model, beliefs about the disease itself were highly correlated with vaccine acceptance, although not the only determinant. Other responses of Acceptors provide clues such as providing vaccination through government health facilities, schools, and kiosks, and having vaccinators maintain proper COVID-19 health and safety protocols as to ways to make it easier to boost acceptance.ConclusionAn effective behavior change strategy for COVID-19 vaccines uptake will need to address multiple beliefs and behavioral determinants, reducing barriers and leveraging enablers identified in this study. The national plans on COVID-19 vaccination should adopt culturally and community label acceptable and appropriate evidence-based behavior change interventions strategies to promote high vaccination coverage and acceptance in all societal structures across the country.

scholarly journals Understanding Health Behavior Technology Engagement: Pathway to Measuring Digital Behavior Change Interventions (DBCI) (Preprint)

2019 ◽  
Author(s):  
Heather Cole-Lewis ◽  
Nnamdi Ezeanochie ◽  
Jennifer Turgiss
Keyword(s):  
Health Behavior ◽  
Behavior Change ◽  
User Experience ◽  
User Engagement ◽  
User Interactions ◽  
Behavior Change Intervention ◽  
Behavioral Determinants ◽  
Behavior Change Interventions ◽  
Frequency Of Use ◽  
Measurement And Evaluation

UNSTRUCTURED Researchers and practitioners of Digital Behavior Change Interventions (DBCI) use varying and oftentimes incongruent definitions of the term “engagement;” thus, leading to lack of precision in DBCI measurement and evaluation. The objective of this paper is to propose discrete definitions for various types of user-engagement and explain why precision in the measurement of these engagement types is integral to ensuring intervention effectiveness. Additionally, this paper presents a framework and practical steps for how engagement can be measured in practice and used to inform DBCI design and evaluation. The key purpose of a DBCI is to influence change in a target health behavior of a user, which may ultimately improve a health outcome. Using available literature and practice-based knowledge of DBCI, the framework conceptualizes two primary categories of engagement that must be measured in DBCI. The categories are health behavior engagement, referred to as “Big E” and digital behavior change intervention (DBCI) engagement, referred to as “Little e.” DBCI engagement is further bifurcated into two sub-classes: 1) user interactions with features of the intervention designed to encourage frequency of use (i.e., simple login, games, social interactions) and make the user experience appealing; and 2) user interactions with behavior change intervention components (i.e., behavior change techniques) which influence determinants of health behavior-- and subsequently, influence health behavior. Achievement of Big E, health behavior engagement, in an intervention delivered via digital means, is contingent upon Little e, DBCI engagement. If users do not interact with DBCI features and enjoy the user experience, exposure to behavior change intervention components will be limited and less likely to influence the behavioral determinants that lead to Big E, health behavior engagement. Big E, health behavior engagement, is also dependent upon the quality and relevance of the behavior change intervention components within the solution. Therefore, the combination of user interactions and behavior change intervention components create Little e, DBCI engagement, which in turn is designed to improve Big E, health behavior engagement. The proposed framework includes a model to support measurement of DBCI that describes categories of engagement, and details how features of Little e produce Big E. This framework can be applied to DBCI supporting various health behaviors and outcomes; and can be utilized to identify gaps in intervention efficacy and effectiveness.

scholarly journals Exploring the behavioral determinants of COVID-19 vaccine acceptance among an urban population in Bangladesh: Implications for behavior change interventions

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0256496
Author(s):  
Md. Abul Kalam ◽  
Thomas P. Davis ◽  
Shahanaj Shano ◽  
Md. Nasir Uddin ◽  
Md. Ariful Islam ◽  
...  
Keyword(s):  
Behavior Change ◽  
Social Norms ◽  
Perceived Risk ◽  
Vaccine Hesitancy ◽  
Negative Consequences ◽  
Vaccine Acceptance ◽  
Perceived Safety ◽  
Behavioral Determinants ◽  
Behavior Change Interventions ◽  
The Impact

Background While vaccines ensure individual protection against COVID-19 infection, delay in receipt or refusal of vaccines will have both individual and community impacts. The behavioral factors of vaccine hesitancy or refusal are a crucial dimension that need to be understood in order to design appropriate interventions. The aim of this study was to explore the behavioral determinants of COVID-19 vaccine acceptance and to provide recommendations to increase the acceptance and uptake of COVID-19 vaccines in Bangladesh. Methods We employed a Barrier Analysis (BA) approach to examine twelve potential behavioral determinants (drawn from the Health Belief Model [HBM] and Theory of Reasoned Action [TRA]) of intended vaccine acceptance. We conducted 45 interviews with those who intended to take the vaccine (Acceptors) and another 45 interviews with those who did not have that intention (Non-acceptors). We performed data analysis to find statistically significant differences and to identify which beliefs were most highly associated with acceptance and non-acceptance with COVID-19 vaccines. Results The behavioral determinants associated with COVID-19 vaccine acceptance in Dhaka included perceived social norms, perceived safety of COVID-19 vaccines and trust in them, perceived risk/susceptibility, perceived self-efficacy, perceived positive and negative consequences, perceived action efficacy, perceived severity of COVID-19, access, and perceived divine will. In line with the HBM, beliefs about the disease itself were highly predictive of vaccine acceptance, and some of the strongest statistically-significant (p<0.001) predictors of vaccine acceptance in this population are beliefs around both injunctive and descriptive social norms. Specifically, Acceptors were 3.2 times more likely to say they would be very likely to get a COVID-19 vaccine if a doctor or nurse recommended it, twice as likely to say that most people they know will get a vaccine, and 1.3 times more likely to say that most close family and friends will get a vaccine. The perceived safety of vaccines was found to be important since Non-acceptors were 1.8 times more likely to say that COVID-19 vaccines are “not safe at all”. Beliefs about one’s risk of getting COVID-19 disease and the severity of it were predictive of being a vaccine acceptor: Acceptors were 1.4 times more likely to say that it was very likely that someone in their household would get COVID-19, 1.3 times more likely to say that they were very concerned about getting COVID-19, and 1.3 times more likely to say that it would be very serious if someone in their household contracted COVID-19. Other responses of Acceptors on what makes immunization easier may be helpful in programming to boost acceptance, such as providing vaccination through government health facilities, schools, and kiosks, and having vaccinators maintain proper COVID-19 health and safety protocols. Conclusion An effective behavior change strategy for COVID-19 vaccines uptake will need to address multiple beliefs and behavioral determinants, reducing barriers and leveraging enablers identified in this study. National plans for promoting COVID-19 vaccination should address the barriers, enablers, and behavioral determinants found in this study in order to maximize the impact on COVID-19 vaccination acceptance.

Understanding Practice: Factors That Influence Physician Hand Hygiene Compliance

2014 ◽  
Vol 35 (12) ◽  
pp. 1511-1520 ◽  
Author(s):  
Janet E. Squires ◽  
Stefanie Linklater ◽  
Jeremy M. Grimshaw ◽  
Ian D. Graham ◽  
Katrina Sullivan ◽  
...  
Keyword(s):  
Hand Hygiene ◽  
Behavior Change ◽  
Hand Hygiene Compliance ◽  
Tertiary Care ◽  
Theoretical Domains Framework ◽  
Behavioral Determinants ◽  
Behavior Change Interventions ◽  
Health Related ◽  
Change Framework ◽  
Hygiene Compliance

Objective.To identify the behavioral determinants—both barriers and enablers—that may impact physician hand hygiene compliance.Design.A qualitative study involving semistructured key informant interviews with staff physicians and residents.Setting.An urban, 1,100-bed multisite tertiary care Canadian hospital.Participants.A total of 42 staff physicians and residents in internal medicine and surgery.Methods.Semistructured interviews were conducted using an interview guide that was based on the theoretical domains framework (TDF), a behavior change framework comprised of 14 theoretical domains that explain health-related behavior change. Interview transcripts were analyzed using thematic content analysis involving a systematic 3-step approach: coding, generation of specific beliefs, and identification of relevant TDF domains.Results.Similar determinants were reported by staff physicians and residents and between medicine and surgery. A total of 53 specific beliefs from 9 theoretical domains were identified as relevant to physician hand hygiene compliance. The 9 relevant domains were knowledge; skills; beliefs about capabilities; beliefs about consequences; goals; memory, attention, and decision processes; environmental context and resources; social professional role and identity; and social influences.Conclusions.We identified several key determinants that physicians believe influence whether and when they practice hand hygiene at work. These beliefs identify potential individual, team, and organization targets for behavior change interventions to improve physician hand hygiene compliance.Infect Control Hosp Epidemiol2014;35(12):1511–1520

scholarly journals Using Community-Based Prevention Marketing to Generate Demand for Healthy Diets in Jordan

Nutrients ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 3068
Author(s):  
Rowena K. Merritt ◽  
Jacqueline de de Groot ◽  
Lama Almajali ◽  
Nitesh Patel
Keyword(s):  
Behavior Change ◽  
Child Nutrition ◽  
Dietary Habits ◽  
Overweight And Obesity ◽  
Micronutrient Deficiencies ◽  
Community Based ◽  
Behavioral Determinants ◽  
Attitudes And Practices ◽  
Behavior Change Interventions ◽  
Healthy Diets

Jordan has been experiencing a nutrition transition with high rates of micronutrient deficiencies and rising overweight and obesity rates. This highlights the need to generate demand for healthy diets. This study used a community-based prevention marketing approach and worked with local communities as partners to develop a set of behavior change interventions to improve healthy eating within vulnerable communities. Individual, family, and paired-friendship interviews, and co-creation workshops were conducted with 120 people. The aim of these interviews was to gain an in-depth understand of school-aged children and their families’ nutrition knowledge, attitudes, and practices, including social and cultural norms and behavioral determinants, and then use this information to co-create interventions, activities and materials targeted at supporting school-aged child nutrition. Analysis of the interviews revealed that dietary habits are both deeply personal and profoundly entwined by emotions and social norms, and that parents often gave in to their children’s demands for unhealthy foods and beverages due to their perception of what a ‘good parent’ looks like and the desire to see their child ‘smile’. These key insights were then shared during the co-creation workshops to develop behavior change interventions—ensuring that interventions were developed by the community, for the community.

scholarly journals Sustainable Change Sequence: A framework for developing behavior change interventions for patients with long-term conditions

2014 ◽  
Vol 2 (2) ◽  
pp. 212 ◽  
Author(s):  
Glyn Elwyn ◽  
Katy Marrin ◽  
Dominick L Frosch ◽  
James White
Keyword(s):  
Behavior Change ◽  
Behavioural Change ◽  
Intervention Development ◽  
Healthcare Applications ◽  
Theoretical Frameworks ◽  
Long Term Conditions ◽  
Appropriate Behavior ◽  
Behavior Change Interventions ◽  
Healthcare Interventions

ObjectiveInteractive interventions are increasingly advocated to support behavior change for patients who have long-term conditions. Such interventions are most likely to achieve behavior change when they are based on appropriate theoretical frameworks. Developers of interventions are faced with a diverse set of behavioral theories that do not specifically address intervention development. The aim of our work was to develop a framework to guide the developers of interactive healthcare interventions that was derived from relevant theory, and which guided developers towards appropriate behavior change techniques.MethodsWe reviewed theories that inform behavior change interventions, where relevant to the management of long-term conditions. Theoretical constructs and behavior change techniques were grouped according to similarity in aims.ResultsWe developed a logic model that operationalizes behavior change theories and techniques into five steps likely to lead to sustained behavior change. The steps are: 1) create awareness of need; 2) facilitate learning; 3) enhance motivation; 4) prompt behaviour change; and 5) ensure sustainability of behaviour change.Conclusion and Practice implicationsA framework that sequences behavioural change techniques along a sustainability model provides a practical template for the developers of interactive healthcare applications and interventions.

The Speech-Language Pathologists' Role in Mild Traumatic Brain Injury for Middle and High School–Age Children: Viewpoints on Guidelines From the Centers for Disease Control and Prevention

2019 ◽  
Vol 28 (3) ◽  
pp. 1363-1370 ◽  
Author(s):  
Jessica Brown ◽  
Katy O'Brien ◽  
Kelly Knollman-Porter ◽  
Tracey Wallace
Keyword(s):  
High School ◽  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Disease Control ◽  
Mild Traumatic Brain Injury ◽  
School Age Children ◽  
School Age ◽  
Speech Language Pathologists ◽  
Control And Prevention ◽  
Centers For Disease Control

Purpose The Centers for Disease Control and Prevention (CDC) recently released guidelines for rehabilitation professionals regarding the care of children with mild traumatic brain injury (mTBI). Given that mTBI impacts millions of children each year and can be particularly detrimental to children in middle and high school age groups, access to universal recommendations for management of postinjury symptoms is ideal. Method This viewpoint article examines the CDC guidelines and applies these recommendations directly to speech-language pathology practices. In particular, education, assessment, treatment, team management, and ongoing monitoring are discussed. In addition, suggested timelines regarding implementation of services by speech-language pathologists (SLPs) are provided. Specific focus is placed on adolescents (i.e., middle and high school–age children). Results SLPs are critical members of the rehabilitation team working with children with mTBI and should be involved in education, symptom monitoring, and assessment early in the recovery process. SLPs can also provide unique insight into the cognitive and linguistic challenges of these students and can serve to bridge the gap among rehabilitation and school-based professionals, the adolescent with brain injury, and their parents. Conclusion The guidelines provided by the CDC, along with evidence from the field of speech pathology, can guide SLPs to advocate for involvement in the care of adolescents with mTBI. More research is needed to enhance the evidence base for direct assessment and treatment with this population; however, SLPs can use their extensive knowledge and experience working with individuals with traumatic brain injury as a starting point for post-mTBI care.

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