Cancer patient interest and perceptions of health behavior change programs.

2018 ◽  
Vol 36 (7_suppl) ◽  
pp. 98-98
Author(s):  
Lawson Eng ◽  
Sophia Yijia Liu ◽  
Qihuang Zhang ◽  
Delaram Farzanfar ◽  
Sabrina Yeung ◽  
...  
Keyword(s):  
Smoking Cessation ◽  
Health Behavior ◽  
Behavior Change ◽  
Health Behavior Change ◽  
Routine Care ◽  
Second Hand Smoke ◽  
Drinking Alcohol ◽  
Logistic Regression Models ◽  
Survey Results

98 Background: Health behavior change including smoking cessation, physical activity (PA) and alcohol moderation are important aspects of cancer survivorship. We assessed cancer pt interest and perceptions of programs for these behaviours. Methods: 501 cancer pts were surveyed on their smoking, PA and alcohol use along with their interest and perceptions for programs for these behaviors. Multivariate logistic regression models identified factors associated with pt interest and perceptions. Results: At diagnosis, 115 pts smoked; 184 were exposed to second hand smoke (SHS); 313 did not meet PA guidelines; 238 were drinking alcohol. At risk pts’ (e.g, smokers for smoking cessation, SHS exposed for household smoking cessation) survey results are shown in the table. Most pts perceived smoking (90%), SHS (83%) and alcohol (56%) to be harmful on quality of life, survival and fatigue while PA (77%) was felt to improve these outcomes. These perceptions were not associated with program interest ( P> 0.05). However, pts perceiving that alcohol worsened and PA improved these outcomes were more to likely believe associated programs are beneficial (alcohol aORs = 2.1-2.2 P< 0.03; PA aORs = 1.9-3.2 P< 0.02) and should be routine care (alcohol aORs = 1.9-3.5 P< 0.03; PA aORs = 1.7-2.4 P< 0.1). Pts with more pack-yrs smoked less likely perceived a benefit in a household smoking cessation program (aOR = 1.02 P< 0.007). Pts preferred discussing programs with doctors ( > 35%) or counsellors ( > 42%). Conclusions: About half of pts feel that health behavior change programs would be beneficial and should be part of routine care. These factors were more important than perception of the behaviors on outcomes in influencing pt interest. Initial discussions with pts should focus on discussing benefits of these programs. [Table: see text]

Smokers' Engagement Behavior on Facebook regarding to Smoking Cessation Verbalization and Facebook Reaction Usage: Content Analysis (Preprint)

2022 ◽  
Author(s):  
Jezdancher Watti ◽  
Máté Millner ◽  
Kata Siklósi ◽  
Hedvig Kiss ◽  
Oguz Kelemen ◽  
...  
Keyword(s):  
Smoking Cessation ◽  
Health Behavior ◽  
Behavior Change ◽  
Language Change ◽  
Health Behavior Change ◽  
Processes Of Change ◽  
Change Talk ◽  
Significant Difference ◽  
Linguistic Categories ◽  
The Relationship

BACKGROUND The Transtheoretical Model recommends "processes of change", while the Motivational Interviewing approach offers “motivational language” as indicators of health behavior change. The relationship between these indicators and the usage of Facebook reaction buttons is little known. However, this relationship may highlight how to evaluate one of the most popular engagement indicators (Facebook reactions) in online health behavior change interventions. OBJECTIVE The study aim was to understand the relationship between processes of change, motivational language, Facebook users’ gender, and the Facebook reaction buttons. METHODS A total of 821 comments were analyzed in the current study (N=821), which came from different Facebook users, and responded to image-based, smoking cessation support contents. The processes of change (experiential and behavioral processes) and the motivational language (change talk and sustain talk) in the investigated comments were identified. The presence, the number, and the proportion of these linguistic categories were compared with the Facebook users’ gender and the usage of reaction buttons. RESULTS The Facebook users who used the “Haha” reaction button wrote significantly higher proportion of sustain talk than those who used the “Like” or “Love” reaction (P=.011). No significant difference in the number or proportion of linguistic categories was found between those who used the "Like" reaction button, and those who did not use reaction buttons. The Facebook users who combined the comment and “Love” reaction wrote significantly more change talk than those who used the “Haha” and “Like” reactions, or those who did not utilize these buttons (P<.001). Significant female dominance was observed in the presence, the number, and the proportion of experiential processes and change talk (P<.05). In addition, significant male predominance was found in the presence, the number, and the proportion of sustain talk (P<.05). CONCLUSIONS The "Haha" reaction may be a negative engagement indicator, the "Like" reaction may be a neutral engagement indicator, and the "Love" reaction may be a positive engagement indicator in terms of the smoking cessation during Facebook-based interventions. Furthermore, female engagement may be characterized by utilizing the terms of experiential processes and change talk, while the usage of sustain talk can be typical for male engagement. We recommend the evaluation of processes of change and motivational utterances in participants' comments during online public health interventions.

Self-administered programs for health behavior change: Smoking cessation and weight reduction by mail

1982 ◽  
Vol 7 (1) ◽  
pp. 57-63 ◽  
Author(s):  
Robert W. Jeffery ◽  
Brian G. Danaher ◽  
John Killen ◽  
John W. Farquhar ◽  
Richard Kinnier
Keyword(s):  
Smoking Cessation ◽  
Health Behavior ◽  
Behavior Change ◽  
Weight Reduction ◽  
Health Behavior Change

A Procedural Model for Planning and Evaluating Behavioral Interventions

2005 ◽  
Vol 44 (02) ◽  
pp. 299-302
Author(s):  
G. C. Hyner
Keyword(s):  
Health Behavior ◽  
Behavior Change ◽  
Behavioral Interventions ◽  
Health Behavior Change ◽  
Behavior Changes ◽  
Change Strategies ◽  
Innovative Strategies ◽  
Proposed Model ◽  
Influence Behavior

Summary Objective: A model for planning, implementing and evaluating health behavior change strategies is proposed. Variables are presented which can be used in the model or serve as examples for how the model is utilized once a theory of health behavior is adopted. Results: Examples of three innovative strategies designed to influence behavior change are presented so that the proposed model can be modified for use following comprehensive screening and baseline measurements. Three measurement priorities: clients, methods and agency are subjected to three phases of assessment: goals, implementation and effects. Conclusion: Lifestyles account for the majority of variability in quality-of-life and premature morbidity and mortality. Interventions designed to influence healthy behavior changes must be driven by theory and carefully planned and evaluated. The proposed model is offered as a useful tool for the behavior change strategist.

scholarly journals Impact of the Method of Delivering Electronic Health Behavior Change Interventions in Survivors of Cancer on Engagement, Health Behaviors, and Health Outcomes: Systematic Review and Meta-Analysis (Preprint)

2019 ◽  
Author(s):  
Kate Furness ◽  
Mitchell N Sarkies ◽  
Catherine E Huggins ◽  
Daniel Croagh ◽  
Terry P Haines
Keyword(s):  
Quality Of Life ◽  
Physical Activity ◽  
Health Behavior ◽  
Behavior Change ◽  
Health Outcomes ◽  
Meta Analysis ◽  
Health Behavior Change ◽  
Patients With Cancer ◽  
Behavior Change Interventions

BACKGROUND Increased accessibility to the internet and mobile devices has seen a rapid expansion in electronic health (eHealth) behavior change interventions delivered to patients with cancer and survivors using synchronous, asynchronous, and combined delivery methods. Characterizing effective delivery methods of eHealth interventions is required to enable improved design and implementation of evidence-based health behavior change interventions. OBJECTIVE This study aims to systematically review the literature and synthesize evidence on the success of eHealth behavior change interventions in patients with cancer and survivors delivered by synchronous, asynchronous, or combined methods compared with a control group. Engagement with the intervention, behavior change, and health outcomes, including quality of life, fatigue, depression, and anxiety, were examined. METHODS A search of Scopus, Ovid MEDLINE, Excerpta Medica dataBASE, Cumulative Index to Nursing and Allied Health Literature Plus, PsycINFO, Cochrane CENTRAL, and PubMed was conducted for studies published between March 2007 and March 2019. We looked for randomized controlled trials (RCTs) examining interventions delivered to adult cancer survivors via eHealth methods with a measure of health behavior change. Random-effects meta-analysis was performed to examine whether the method of eHealth delivery impacted the level of engagement, behavior change, and health outcomes. RESULTS A total of 24 RCTs were included predominantly examining dietary and physical activity behavior change interventions. There were 11 studies that used a synchronous approach and 11 studies that used an asynchronous approach, whereas 2 studies used a combined delivery method. Use of eHealth interventions improved exercise behavior (standardized mean difference [SMD] 0.34, 95% CI 0.21-0.48), diet behavior (SMD 0.44, 95% CI 0.18-0.70), fatigue (SMD 0.21, 95% CI −0.08 to 0.50; SMD change 0.22, 95% CI 0.09-0.35), anxiety (SMD 1.21, 95% CI: 0.36-2.07; SMD change 0.15, 95% CI −0.09 to 0.40), depression (SMD 0.15, 95% CI 0.00-0.30), and quality of life (SMD 0.12, 95% CI −0.10 to 0.34; SMD change 0.14, 95% CI 0.04-0.24). The mode of delivery did not influence the amount of dietary and physical activity behavior change observed. CONCLUSIONS Physical activity and dietary behavior change eHealth interventions delivered to patients with cancer or survivors have a small to moderate impact on behavior change and a small to very small benefit to quality of life, fatigue, depression, and anxiety. There is insufficient evidence to determine whether asynchronous or synchronous delivery modes yield superior results. Three-arm RCTs comparing delivery modes with a control with robust engagement reporting are required to determine the most successful delivery method for promoting behavior change and ultimately favorable health outcomes.

scholarly journals Toward a Digital Platform for the Self-Management of Noncommunicable Disease: Systematic Review of Platform-Like Interventions

10.2196/16774 ◽  
2020 ◽  
Vol 22 (10) ◽  
pp. e16774
Author(s):  
Sarah A Tighe ◽  
Kylie Ball ◽  
Finn Kensing ◽  
Lars Kayser ◽  
Jonathan C Rawstorn ◽  
...  
Keyword(s):  
Health Behavior ◽  
Behavior Change ◽  
Health Behavior Change ◽  
Self Management ◽  
Evidence Based ◽  
Digital Platform ◽  
Digital Interventions ◽  
Disease Specific ◽  
Specific Health

Background Digital interventions are effective for health behavior change, as they enable the self-management of chronic, noncommunicable diseases (NCDs). However, they often fail to facilitate the specific or current needs and preferences of the individual. A proposed alternative is a digital platform that hosts a suite of discrete, already existing digital health interventions. A platform architecture would allow users to explore a range of evidence-based solutions over time to optimize their self-management and health behavior change. Objective This review aims to identify digital platform-like interventions and examine their potential for supporting self-management of NCDs and health behavior change. Methods A literature search was conducted in January 2020 using EBSCOhost, PubMed, Scopus, and EMBASE. No digital platforms were identified, so criteria were broadened to include digital platform-like interventions. Eligible platform-like interventions offered a suite of discrete, evidence-based health behavior change features to optimize self-management of NCDs in an adult population and provided digitally supported guidance for the user toward the features best suited to their needs and preferences. Data collected on interventions were guided by the CONSORT-EHEALTH (Consolidated Standards of Reporting Trials of Electronic and Mobile Health Applications and Online Telehealth) checklist, including evaluation data on effectiveness and process outcomes. The quality of the included literature was assessed using the Mixed Methods Appraisal Tool. Results A total of 7 studies were included for review. Targeted NCDs included cardiovascular diseases (CVD; n=3), diabetes (n=3), and chronic obstructive pulmonary disease (n=1). The mean adherence (based on the number of follow-up responders) was 69% (SD 20%). Of the 7 studies, 4 with the highest adherence rates (80%) were also guided by behavior change theories and took an iterative, user-centered approach to development, optimizing intervention relevance. All 7 interventions presented algorithm-supported user guidance tools, including electronic decision support, smart features that interact with patterns of use, and behavior change stage-matching tools. Of the 7 studies, 6 assessed changes in behavior. Significant effects in moderate-to-vigorous physical activity were reported, but for no other specific health behaviors. However, positive behavior change was observed in studies that focused on comprehensive behavior change measures, such as self-care and self-management, each of which addresses several key lifestyle risk factors (eg, medication adherence). No significant difference was found for psychosocial outcomes (eg, quality of life). Significant changes in clinical outcomes were predominately related to disease-specific, multifaceted measures such as clinical disease control and cardiovascular risk score. Conclusions Iterative, user-centered development of digital platform structures could optimize user engagement with self-management support through existing, evidence-based digital interventions. Offering a palette of interventions with an appropriate degree of guidance has the potential to facilitate disease-specific health behavior change and effective self-management among a myriad of users, conditions, or stages of care.

scholarly journals The Impact of Racial and Non-racial Discrimination on Health Behavior Change Among Visible Minority Adults During the COVID-19 Pandemic

2021 ◽  
Author(s):  
Cheryl L. Currie ◽  
Erin K. Higa
Keyword(s):  
Health Behavior ◽  
Behavior Change ◽  
Racial Discrimination ◽  
Health Behavior Change ◽  
Short Version ◽  
Visible Minority ◽  
Logistic Regression Models ◽  
Stress Eating ◽  
Health Behavior Changes ◽  
The Impact

Abstract Introduction Pre-pandemic health behavior has been put forward as a reason for excess COVID-19 infection and death in some racialized groups. At the same time, scholars have labeled racism the other pandemic and argued for its role in the adverse COVID-19 outcomes observed. The purpose of this study was to examine the impact of discrimination on health behavior change among racialized adults in the early stages of the pandemic. Methods Data were collected from 210 adults who identified as a visible minority in Alberta, Canada, in June 2020. The Everyday Discrimination Scale (Short Version) was adapted to examine past-month experiences. Four questions asked if alcohol/cannabis use and stress eating had significantly increased, and if sleep and exercise had significantly decreased in the past month. Logistic regression models examined associations between discrimination attributed to racial and non-racial causes and health behavior change adjusted for covariates. Results The majority of adults (56.2%) reported past-month discrimination including 26.7% who attributed it to their race. Asian adults reported more racial discrimination and discrimination due to people believing they had COVID-19 than other visible minorities. Racial discrimination during the pandemic was strongly associated with increased substance use (OR: 4.0, 95% CI 1.2, 13.4) and decreased sleep (OR: 7.0, 95% CI 2.7, 18.4), and weakly associated with decreased exercise (OR: 2.2, 95% CI 1.1, 4.5). Non-racial discrimination was strongly associated with decreased sleep (OR: 4.8, 95% CI 1.8, 12.5). Conclusion Racial discrimination may have a particularly important effect on intensifying adverse health behavior changes among racialized adults during a time of global crisis.

scholarly journals On the Usefulness of Narratives: An Interdisciplinary Review and Theoretical Model

2018 ◽  
Vol 52 (5) ◽  
pp. 429-442 ◽  
Author(s):  
Victoria A Shaffer ◽  
Elizabeth S Focella ◽  
Andrew Hathaway ◽  
Laura D Scherer ◽  
Brian J Zikmund-Fisher
Keyword(s):  
Health Behavior ◽  
Behavior Change ◽  
Health Behavior Change ◽  
Theoretical Understanding ◽  
Narrative Processing ◽  
Behavior Change Interventions ◽  
Narrative Intervention ◽  
And Behavior ◽  
Attitudes And Behavior

Abstract Background How can we use stories from other people to promote better health experiences, improve judgments about health, and increase the quality of medical decisions without introducing bias, systematically persuading the listeners to change their attitudes, or altering behaviors in nonoptimal ways? More practically, should narratives be used in health education, promotion, or behavior change interventions? Method In this article, we address these questions by conducting a narrative review of a diverse body of literature on narratives from several disciplines to gain a better understanding about what narratives do, including their role in communication, engagement, recall, persuasion, and health behavior change. We also review broad theories about information processing and persuasion from psychology and more specific models about narrative messaging found in the health communication and marketing literatures to provide insight into the processes by which narratives have their effect on health behavior. Results To address major gaps in our theoretical understanding about how narratives work and what effects they will have on health behavior, we propose the Narrative Immersion Model, whose goal is to identify the parameters that predict the specific impact of a particular narrative (e.g. persuade, inform, comfort, etc.) based on the type of narrative message (e.g. process, experience, or outcome narrative). Further, the Narrative Immersion Model describes the magnitude of the effect as increasing through successive layers of engagement with the narrative: interest, identification, and immersion. Finally, the Narrative Immersion Model identifies characteristics of the narrative intervention that encourage greater immersion within a given narrative. Conclusions We believe there are important communication gaps in areas areas of behavioral medicine that could be addressed with narratives; however, more work is needed in order to employ narrative messaging systematically. The Narrative Immersion Model advances our theoretical understanding about narrative processing and its subsequent effects on knowledge, attitudes, and behavior.

scholarly journals Toward a Digital Platform for the Self-Management of Noncommunicable Disease: Systematic Review of Platform-Like Interventions (Preprint)

2019 ◽  
Author(s):  
Sarah A Tighe ◽  
Kylie Ball ◽  
Finn Kensing ◽  
Lars Kayser ◽  
Jonathan C Rawstorn ◽  
...  
Keyword(s):  
Health Behavior ◽  
Behavior Change ◽  
Health Behavior Change ◽  
Self Management ◽  
Evidence Based ◽  
Digital Platform ◽  
Digital Interventions ◽  
Disease Specific ◽  
Specific Health

BACKGROUND Digital interventions are effective for health behavior change, as they enable the self-management of chronic, noncommunicable diseases (NCDs). However, they often fail to facilitate the specific or current needs and preferences of the individual. A proposed alternative is a digital platform that hosts a suite of discrete, already existing digital health interventions. A platform architecture would allow users to explore a range of evidence-based solutions over time to optimize their self-management and health behavior change. OBJECTIVE This review aims to identify digital platform-like interventions and examine their potential for supporting self-management of NCDs and health behavior change. METHODS A literature search was conducted in January 2020 using EBSCOhost, PubMed, Scopus, and EMBASE. No digital platforms were identified, so criteria were broadened to include digital platform-like interventions. Eligible platform-like interventions offered a suite of discrete, evidence-based health behavior change features to optimize self-management of NCDs in an adult population and provided digitally supported guidance for the user toward the features best suited to their needs and preferences. Data collected on interventions were guided by the CONSORT-EHEALTH (Consolidated Standards of Reporting Trials of Electronic and Mobile Health Applications and Online Telehealth) checklist, including evaluation data on effectiveness and process outcomes. The quality of the included literature was assessed using the Mixed Methods Appraisal Tool. RESULTS A total of 7 studies were included for review. Targeted NCDs included cardiovascular diseases (CVD; n=3), diabetes (n=3), and chronic obstructive pulmonary disease (n=1). The mean adherence (based on the number of follow-up responders) was 69% (SD 20%). Of the 7 studies, 4 with the highest adherence rates (80%) were also guided by behavior change theories and took an iterative, user-centered approach to development, optimizing intervention relevance. All 7 interventions presented algorithm-supported user guidance tools, including electronic decision support, smart features that interact with patterns of use, and behavior change stage-matching tools. Of the 7 studies, 6 assessed changes in behavior. Significant effects in moderate-to-vigorous physical activity were reported, but for no other specific health behaviors. However, positive behavior change was observed in studies that focused on comprehensive behavior change measures, such as self-care and self-management, each of which addresses several key lifestyle risk factors (eg, medication adherence). No significant difference was found for psychosocial outcomes (eg, quality of life). Significant changes in clinical outcomes were predominately related to disease-specific, multifaceted measures such as clinical disease control and cardiovascular risk score. CONCLUSIONS Iterative, user-centered development of digital platform structures could optimize user engagement with self-management support through existing, evidence-based digital interventions. Offering a palette of interventions with an appropriate degree of guidance has the potential to facilitate disease-specific health behavior change and effective self-management among a myriad of users, conditions, or stages of care.

Normative Beliefs of Health Behavior Professionals regarding the Psychosocial and Environmental Factors That Influence Health Behavior Change Related to Smoking Cessation, Regular Exercise, and Weight Loss

1996 ◽  
Vol 10 (5) ◽  
pp. 371-379 ◽  
Author(s):  
Mary Beth Love ◽  
Gerald W. Davoli ◽  
Quint C. Thurman
Keyword(s):  
Weight Loss ◽  
Smoking Cessation ◽  
Environmental Factors ◽  
Health Behavior ◽  
Behavior Change ◽  
Survey Design ◽  
Health Behavior Change ◽  
Work Place ◽  
Regular Exercise ◽  
Positive Elements

Purpose. To examine the degree of consensus among health behavior change professionals regarding the personal and environmental factors they believe most strongly influence health behavior decisions related to smoking cessation, regular exercise, and weight loss. Design. A factorial survey design was implemented. This method combines the positive elements from simple sample surveys and factorial experiment designs. A total of 44 independent psychosocial and environmental variables are used to randomly construct vignettes, or short stories, to collect dependent variable data. Subjects. A probability sample of 311 health behavior change professionals was selected from the Society for Public Health Education, Inc., the Society of Behavioral Medicine, and faculty from the 1986 Harvard University Symposium on Health Promotion in the Work Place. Measures. Judgment ratings on the probability that the person described in each vignette would initiate the behavior in question. Results. Multivariate analysis indicates that the multidimensional model explained approximately one half of the variance in the judgments across the three health behaviors (smoking cessation, R2 = .52; weight loss, R2 = .49; and regular exercise, R2 = .49). Conclusions. These data suggest a high degree of consensus among the sample regarding the personal and environmental factors that influence health behavior judgments. Here, the subjects perceive both behavioral intentions and self-efficacy as the most powerful determinants of judgments to initiate weight loss, regular exercise, and smoking cessation.

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