Vaccination Against COVID-19: A Longitudinal Trans-Theoretical Study to Determine Factors that Predict Intentions and Behavior

BACKGROUND

Despite the clear benefits of vaccination, their uptake against common infectious diseases is suboptimal. In December 2020, vaccines against COVID-19 became available.

PURPOSE

To determine factors that predict who will take the COVID-19 vaccine based on a conceptual model.

METHODS

An online survey was administered twice: prior to public vaccination, and after vaccinations were available. Participants were 309 Israelis with initial data and 240 at follow-up. Baseline questionnaires measured intentions to be vaccinated and hypothesized predictors clustered in four categories: background, COVID-19, vaccination, and social factors. Self-reported vaccination uptake was measured at follow-up.

RESULTS

Sixty-two percent of the sample reported having been vaccinated. Intentions were strongly associated with vaccination uptake and mediated the effects of other predictors on behavior. Eighty-six percent of the variance in vaccination intentions was explained by attitudes toward COVID-19 vaccination, regret for having declined vaccination, trust in vaccination, vaccination barriers, past flu vaccination, perceived social norms, and COVID-19 representations.

CONCLUSIONS

Beliefs related directly to the COVID-19 vaccine explained most of the variance in intentions to vaccinate, which in turn predicted vaccination uptake.

Evaluation of the B.strong Queensland Indigenous Health Worker Brief Intervention Training Program for Multiple Health Risk Behaviours

Queensland’s B.strong brief intervention training program was a complex intervention developed for Aboriginal and Torres Strait Islander health workers to assist clients address multiple health risks of smoking, poor nutrition and physical inactivity. This study evaluates program effectiveness by applying the Kirkpatrick four-level evaluation model: (1) Reaction, participants’ satisfaction; (2) Learning, changes in participants’ knowledge, confidence, attitudes, skills and usual practice; (3) Behaviour, application of learning to practice; and (4) Results, outcomes resulting from training. A retrospective analysis was conducted on data for respondents completing pre-training, post-workshop and follow-up surveys. Changes in domains such as training participant knowledge, confidence, attitudes, and practices between survey times were assessed using paired-samples t-tests. From 2017–2019, B.strong trained 1150 health professionals, reaching targets for workshop and online training. Findings showed statistically significant improvements from baseline to follow-up in: participants’ knowledge, confidence, and some attitudes to conducting brief interventions in each domain of smoking cessation, nutrition and physical activity; and in the frequency of participants providing client brief interventions in each of the three domains. There was a statistically significant improvement in frequency of participants providing brief interventions for multiple health behaviours at the same time from pre-workshop to follow-up. Indigenous Queenslander telephone counselling referrals for smoking cessation increased during the program period. B.strong improved practitioners’ capacity to deliver brief interventions addressing multiple health risks with Indigenous clients.

The Association Between Healthy Lifestyle Behaviours and Coronavirus Protective Behaviours

BACKGROUND

Based on models of cross-behavioural associations and the role of past behaviour in predicting behaviour, an association was hypothesized between healthy lifestyle behaviours prior to the COVID-19 pandemic and adherence to coronavirus protective behaviours. Self-assessed health was also examined as a potential moderator.

METHODS

A cross-sectional sample (N = 463) completed online questionnaires during a COVID-19-related lockdown that measured engagement in healthy lifestyle behaviours (e.g., exercising and eating fruits and vegetables), adherence to coronavirus protective behaviours (e.g., wearing a face mask and practicing social distancing), and self-assessed health (subjective evaluation of overall health).

RESULTS

As predicted, higher engagement in healthy lifestyle behaviours prior to the pandemic was significantly correlated with higher adherence to coronavirus protective behaviours (Pearson r(459) = .308, p < .001). Adherence levels were higher than engagement in healthy lifestyle behaviours, and self-assessed health was related to the latter but not to the former. Moderation was examined using model 1 in PROCESS for SPSS; as expected, the association was stronger among individuals with higher levels of self-assessed health (coefficient 95% CI [.04, .20]).

CONCLUSIONS

The findings highlight cross-behavioural facilitating processes, specifically between lifestyle behaviours and adherence to recommended protective behaviours during the pandemic. They also draw attention to the need to address individuals whose poorer evaluations of their general health might prevent them from implementing their behavioural intentions.

Riding the Wave of Digital Transformation in Behavioral Medicine

BACKGROUND

Digital technologies provide a platform for accelerating science and broadening impact in behavioral medicine.

PURPOSE

The objective of this invited keynote presentation or paper is to offer a blueprint for navigating the rapidly changing waters of digital health.

METHODS

A strategic literature review on digital health technologies in behavioral medicine was combined with a review of relevant policy initiatives to yield insights on: (a) knowledge building, (b) collaboration, and (c) public health stewardship.

RESULTS

Digital platforms offer unprecedented leverage for accelerating science, facilitating collaboration, and advancing public health. Early successes in behavioral medicine demonstrated how digital platforms could extend the reach of theory-based behavioral therapeutics through increases in efficiency and scale. As medical investments in health information technology increased, the field of behavioral informatics emerged as the collaborative glue binding behavioral theory into a new generation of patient-facing applications, clinical decision support tools, evidence-based communication programs, and population health management strategies. As a leader within the interstitial space between medicine, psychology, and engineering, the Society of Behavioral Medicine is in a distinct position to exert influence on the ways in which our science is utilized to eliminate health disparities; improve support for patients, caregivers, and communities; to promote general health and well-being; and to offer relief when confronted with psychological pain or addiction.

CONCLUSION

Riding the wave of digital transformation has less to do with mastering the complexities of the latest technologies and more to do with adhering closely to established principles for navigating a rapidly changing information environment.

Living with a Smoker and Multiple Health-Risk Behaviors

BACKGROUND

Behavioral medicine is showing growing theoretical and applied interest in multiple health-risk behaviors. Compared to engaging in a single health-risk behavior, multiple health-risk behaviors are linked to increased morbidity and mortality. A contextual determinant of multiple risk behaviors may be living with a smoker.

PURPOSE

This study investigated the role of living with a smoker in predicting multiple health-risk behaviors compared to a single health-risk behavior, as well as whether these multiple risk behaviors occur across both physical activity and dietary domains. Moreover, the study tested these effects across 3 years in longitudinal and prospective (controlling for health-risk behaviors at baseline) analyses.

METHODS

Participants were 82,644 women (age M = 63.5, standard deviation = 7.36, age range = 49-81) from the Women's Health Initiative Observational Study. Analyses used multinomial and binary logistic regression.

RESULTS

Living with a smoker was more strongly associated with multiple health-risk behaviors than with a single health-risk behavior. These multiple risk behaviors occurred across both physical activity and dietary domains. The effects persisted across 3 years in longitudinal and prospective analyses. Living with a smoker, compared to not living with a smoker, increased the odds of multiple health-risk behaviors 82% cross-sectionally and, across 3 years, 94% longitudinally and 57% prospectively.

CONCLUSIONS

These findings integrate research on multiple health-risk behaviors and on living with a smoker and underscore an unrecognized public health risk of tobacco smoking. These results are relevant to household-level interventions integrating smoking-prevention and obesity-prevention efforts.

Self-compassion, physical health, and health behaviour: a meta-analysis

This meta-analysis investigated relationships between self-compassion and (1) physical health and (2) health-promoting behaviour in a large pooled sample (N = 29,588) sourced from 94 peer-reviewed articles. As hypothesised, omnibus analyses revealed positive associations between self-compassion and both physical health (r = .18) and health behaviour (r = .26). Moderation analyses using 290 effects found that both associations varied according to health domain, participant age, intervention duration, and self-compassion measure. Self-compassion predicted outcomes in most health domains, with the strongest effects observed on global physical health, functional immunity, composite health behaviour, sleep, and danger avoidance. It did not predict frailty, maladaptive bodily routines, and substance abuse. Multi-session interventions designed to boost self-compassion predicted increased physical health and health behaviour, thereby supporting causal links between self-compassion and health outcomes. The effects of single-session inductions were non-significant. The mean effect of self-compassion on physical health was non-significant for young participants (12.00-19.99) and its effect on health behaviour was weakest among older participants (40.00+). Results support the proposition that self-compassion can promote better physical health. Practical implications of these findings are discussed.

Worse or even better than expected? Outcome expectancies and behavioral experiences in the context of physical activity among cancer patients

Expectancies of cancer patients regarding their physical activity before they took part in a behavior change intervention were compared with their experiences during the intervention period. A total of 66 cancer patients completed either a randomly assigned 4-week physical activity or a stress-management counseling intervention. On average, participants had positive expectancies toward physical activity. Outcome expectancies predicted outcomes (e.g. physical activity) at a 10-week follow-up. Outcome realization (discrepancy between expectancies and experiences) further increased explained variance in self-efficacy and physical activity enjoyment. In conclusion, not only initial outcome expectancies but also their realizations seem to be important for subsequent behavior and cognitions.

Feel good now or regret it later? The respective roles of affective attitudes and anticipated affective reactions for explaining health-promoting and health risk behavioral intentions

Evidence supporting the incorporation of affective constructs, such as affective attitudes and anticipated regret, into theoretical models of health behavior has been mounting in recent years; however, the role of positive anticipated affective reactions (e.g., pride) has been largely unexplored. The purpose of the present investigation was to assess how affective attitudes and anticipated affective reactions (both pride and regret for performing a behavior or not) may provide distinct utility for understanding intentions to perform health-promoting and health risk behaviors over and above cognitive attitudes and other established theoretical constructs from the theory of planned behavior (TPB). Participants (N = 210) were recruited via Amazon's Mechanical Turk to complete a one-time online battery assessing TPB and affective constructs. Self-reported intentions served as the main outcome measure, and hierarchical linear modeling was used to examine the effects of TPB and affective constructs across behaviors. Controlling for TPB constructs, more positive affective attitudes and greater anticipated regret, but not anticipated pride, predicted intentions to engage in future health behaviors. Anticipated affective reactions contributed explanatory variance for intentions to perform health risk behaviors, but anticipated pride and regret were not associated with intentions to perform health risk behaviors. Contributions made via the inclusion of both positively and negatively valence anticipated affective reactions for both action and inaction (performing a behavior or not) across a range of health promoting and health risk behaviors are discussed, as well as implications for future intervention work.