What is the term for a type of analysis that does not influence a persons behavior?

Health Belief and Health Promotion Models: Theories of Reasoned Action and Planned Behavior

The health belief model includes the motivational, attitudinal, and self-efficacy components of various theories. The theory of reasoned action (TRA) and theory of planned behavior (TPB) as developed by Ajzen and Fishbein20 and Ajzen21 take into account the individual’s attitude and social norms as well as the individual’s perceived control as accurate predictors of behavioral intentions. TRA is most successful when applied to behaviors that are under an individual’s voluntary control. If behaviors are not fully under voluntary control, even though individuals may be highly motivated by their own attitudes and subjective norms, they may not actually perform the behavior due to intervening environmental conditions. The TPB was developed to predict behaviors in which individuals have incomplete voluntary control. Taking self-esteem and self-efficacy into consideration, the TPB expands on the concept of perceived behavioral control. Perceived behavioral control indicates that an individual’s motivation is influenced by how difficult the behaviors are perceived to be, as well as the perception of how successfully the individual can (or cannot) perform the activity. It is easy to see how this theory may relate to the concept of motivation and adherence to physical activity and/or exercise, especially in the rehabilitation setting. If a patient’s perceived control or self-efficacy or self-esteem is low, the perception and belief that he or she can influence own behaviors in a positive manner is undermined. In a study assessing risk behavior following coronary heart disease diagnosis, planned behavior was found to be the main factor in predicting self-reported exercise and observed fitness levels.24 When exercise intention and behavior were assessed in a sample of 225 older women aged 65 years and older, significant predictors of exercise intention were behavioral beliefs, normative beliefs, and perceived control beliefs.25 In other words these women were more likely to exercise if they perceived more positive than negative consequences of performing the behavior (i.e., behavior beliefs), if they believed that people close or important to them approved versus disapproved of their behavior (i.e., normative beliefs), and, lastly, if they believed the difficulty of the task was manageable by them (i.e., perceived control belief).25

Individual behaviour change

Social cognition models, developed within social and health psychology, have sought, for many years, to predict and explain health behaviours. Some widely used models are:

the Health Belief model

the Theory of Planned Behaviour

the Transtheoretical model.

These models, and related health behaviour research studies, are critically explored by Conner and Norman (1996). From the late 1990s, increasing emphasis has been placed on using social cognition models to design and implement intervention studies that explicitly look for modification of health behaviours. Rutter and Quine (2002) bring together a number of such studies where empirical work is advanced or has been completed. These include investigations of behaviour modification in relation to health-enhancing behaviours, such as reducing dietary fat intake, increasing intake of vitamin C, and reducing driving speeds, and in relation to the uptake of health screening behaviours and opportunities, such as breast self-examination and screening investigations for cervical and colorectal cancer. The studies help to identify where, and when, behaviour change interventions may be successful, but they also point out some of their limitations. Sustained behaviour change is more difficult to achieve than short-term change.

From the mid-1980s, the notion of empowerment has been an important concept in relation to seeking behaviour change by individuals and social groups. At an individual level, empowerment is taken to mean that people are more likely to act:

when they feel that their actions may have an impact

when they feel personally able to carry through and sustain any changes they, themselves, choose.

It is important that health professionals recognize that empowered individuals may make different behavioural choices from those advised in health risk advice. Such different choices might reflect different life priorities or constrained choices for action, rather than being the product of misunderstandings or simple disregard for expert advice. Empowerment is also important in relation to the social change approach to health promotion.

Current Sexual Health Interventions Outside of Schools

There are also sexual health interventions aimed at teenagers that operate externally outside of schools. Ingram and Salmon (2007) reviewed the “no worries clinics”. These are sexual health clinics designed for teenagers inside existing GP surgeries and health clinics. These clinics are in the South West of England and cover all areas of sexual health advice and screening. Ingram and Salmon concluded that teenagers who attended these clinics felt more confident about sex, were informed about sex, and reported less intention to take risks.

There are also the adolescent pregnancy prevention clinics, which are privately funded clinics for adolescents and young adults (Yoost, Hertweck, & Barnett, 2014). These clinics provide female family planning and sexual education to females aged 11–24 years. They concentrate on contraception methods and sexual health information and work on building a positive relationship between the patient and healthcare provider so that confidential information and advice can be sought. A review of these clinics found that they had a significant influence on knowledge and sexual intentions in younger adolescents 11–16 years. However, they had less of an effect on older adolescents.

Even though these clinics are more effective for younger adolescents, the majority of younger adolescents do not feel comfortable accessing these types of clinics and worry about confidentiality and judgment when visiting (Mulholland & Wersch, 2007). The biggest worries for teens are confidentiality and anonymity as well as staff members being unfriendly or critical (Iyer & Baxter-MacGregor, 2010). Also, teenagers are only likely to access these clinics when they are already sexually active (Jones & Biddlecom, 2011). Only a third of young people use a service prior to having sex for the first time (Stone & Ingham, 2002). As early sex is linked with more risky behaviors (Zimmer-Gembeck & Helfand, 2008), it is important to target teens at age-appropriate times. While drop-in clinics are effective, there also needs to be a way to ensure that teens can feel comfortable accessing information before they become sexually active. Ingram and Salmon (2010) found that delivering services within schools and communities makes them more accessible. However, many low SES schools and areas cannot afford to have these types of drop-in services available.

The recommended standard for sexual health provision in the United Kingdom is to provide individuals with safe sex information and access to free contraceptives (Recommended standards for sexual health services, 2011), and for teenagers to have access to free contraceptives throughout the United Kingdom. Yet as mentioned, many teenagers are uncomfortable visiting sexual health professionals. Previous sexual health interventions that have been underpinned by theoretical models such as the theory of planned behavior have tried to increase the number of teenagers visiting sexual health clinics. The Department of Education in the United Kingdom ran a national campaign called “Sex. Worth Talking About” (SWTA) (Goodwin, Smith, Davies, & Perry, 2011). Although this campaign was not based on the TPB, it was developed from extensive evidence of the role of health communication on behavior change (Brown, Burton, Nikolin, & Crooks, 2012; NHS Choices, 2012). This intervention was aimed at sexually active adolescents under the age of 25 years, using posters and television advertisements (Ajzen, 2006). Brief health messages were provided in speech bubbles, which directed the reader to a website with further contraception information. Research investigating the impact of the campaign found that the number of young adolescents requesting sexual health appointments increased (NHS Choices, 2012). Therefore, brief messages can have an impact on changing behavior, but the content of the message (DiClemente, Marinilli, & Singh, 2001), and mode of delivery, need to be carefully considered (Abraham & Michie, 2008). Using this approach, teenagers are encouraged to make informed decisions about health behaviors, and be aware of negative consequences of not performing these behaviors (Broadstock & Michie, 2000). However, nudging a person to change their behavior by increasing their knowledge about safe sex and providing free condoms only has a modest effect on changing an individual's behavior (Ajzen, 2011; Marteau, 2011).

Another intervention widely discussed in the literature is the Positive Youth Development (PYD) program. The aim of PYD programs is to provide teenagers with the confidence to be able to refuse sex or practise safer sexual behaviors (Gavin, Catalano, David-Ferdon, Gloppen, & Markham, 2010). This is achieved by helping teenagers strengthen their relationships and skills and develop a more positive view about their future (Mji, 2016; Turner, 2017). PYD programs aim to provide a holistic view of adolescent development that reinforces skills needed for safer sex (Schwartz et al., 2010). Bonding and relationships are an important part of PYD programs and the atmosphere is supportive so that the program staff and teenagers can connect and a sense of belonging with the other program participants can be achieved (Eccles & Gootman, 2007). In this format, prosocial behaviors are encouraged and peer pressure toward problem behaviors is minimized, with positive and safe behaviors being actively promoted.

There have been mixed results from PYD programs. There have been significant gender differences, with male students reporting less sexual intercourse and more condom use after a PYD program, but no significant differences in sexual behavior for females (Clark, Miller, Nagy, Avery, & Roth, 2005; Flay, Graumlich, & Segawa, 2004). However, another study found that female participants were significantly less likely to have sex or get pregnant than the control group, yet there were no differences for males (Quinn & Fromme, 2010). A further study found similar results with no significant differences for males but females were significantly less likely than controls to have sex under pressure, to have ever had sex, and to have a pregnancy or birth. Female participants were also significantly more likely to use hormonal contraception than those in the control group, but the groups did not differ significantly on condom use (Philliber, Kaye, Herrling, & West, 2002). Furthermore in a longitudinal study on PYD youth, PYD teens were significantly less likely to be parents at age 20 years than the control group (Campbell, Ramey, & Pungello, 2002). A further two studies found no significant differences on sexual behavior and pregnancy rates between the PYD teens and control group (Melchior, 1998; Piper, Moberg, & King, 2000). However, a large systematic review of the literature concluded that overall PYD programs do significantly improve condom use and frequency of sex (Gavin et al., 2010).

One of the reasons for these contrasting results might be the definitions used to describe PYD programs. PYD programs have many different definitions developed by academic researchers, program providers, and funding organizations who have worked in the area. A literature review of PYD programs identified 15 different definitions; ranging from specific goal setting to spirituality and volunteer work (Catalano, Berglund, & Ryan, 2004). It is difficult to assess how these programs work due to the definitional differences. It is also difficult to assess whether each program is targeting the same behaviors and skills. Consequently, it is not clear if all of the programs discussed are actually PYD programs.

PYD programs tend to last for an entire school year or longer, so that teens have adequate time to benefit from the program (Gavin et al., 2010). Because of their heavy emphasis on human resources and length of program, they have a large upfront cost (Schulman & Davies, 2007) often rendering them inaccessible to low SES areas.

There are also interventions with parents that aim to improve the sexual health of their children, as research has shown that parental communication is important in shaping teenager's early sexual health attitudes. Wight and Fullterton (2013) reviewed 44 programs that involved parents, to evaluate if these types of interventions were effective in improving teenagers' sexual health. It was concluded that parent-child interaction and teenagers' sexual health knowledge and attitudes did improve, but sexual behavior outcomes only improved in half the studies. However, Wight and Fullterton (2013) noted that the review was limited by lack of rigorous evaluations, therefore, while parental communication is important for shaping teenagers' sexual health knowledge and attitudes, further research needs to establish when and how parents should discuss sexual health with their children. A further review of parent-based sexual health education programs found that parental involvement did increase parent-teenager communication about sexual health (Santa, Markham & Mullen, 2015). However, the researchers highlighted that there are clear gaps in the range of programs published, often missing out sexual minority youths, grandparents, and faith-based services, and further research is needed before any firm conclusions are made (Table 3.2).

Table 3.2. Summary Points of Sexual Health Education Delivered Outside of Schools.

1.3.3 The theory of planned behaviour

The Theory of Planned Behaviour (TPB) (Ajzen, 1985, 1991) was developed from the earlier Theory of Reasoned Action (Fishbein & Ajzen, 1975). The two theories share the assumption that intentions are the immediate antecedents to behaviour. That is, the stronger the intention to perform a behaviour, the greater the likelihood of the behaviour actually occurring (Doll & Ajzen, 1992). The TPB is designed to predict and explain human behaviours in specific situations (Ajzen, 1991).

According to the TPB, behavioural intentions are influenced by attitude toward the behaviour, subjective norm, and perceived behavioural control (Ajzen, 2002; Madden, Ellen, & Ajzen, 1992). Attitude toward the behaviour refers to how positively or negatively a person evaluates the target behaviour, whilst subjective norm refers to perceived social pressure to perform or not perform the behaviour (Ajzen, 1991). Perceived behavioural control refers to the ease or difficulty with which the individual believes they can perform the behaviour. These three antecedents to intentions are argued to develop from beliefs, such as behavioural beliefs, normative beliefs and control beliefs (Ajzen, 1991).

According to the TPB, client intentions will be predictive of treatment adherence provided that clients have volitional control over treatment behaviours. Client intentions toward engaging in treatment behaviours may be improved by assessing client beliefs about subjective norms and perceived behavioural control, as well as implementing interventions to increase positive attitudes toward the treatment behaviours.

The TPB has been used for research in the prediction of health behaviours, such as diet (Conner, Kirk, Cade, & Barrett, 2003; White, Terry, Troup, Rempel, & Norman, 2010), child immunisation rates (Tickner, Leman, & Woodcock, 2010), exercise (Nguyen, Potvin, & Otis, 1997), condom use (Albarracin, Johnson, Fishbein, & Muellerleile, 2001), and smoking behaviours (Kam, Matsunaga, Hecht, & Ndiaye, 2009; Nehl et al., 2009). The efficacy of the TPB has been supported by empirical studies (e.g., Armitage & Talibudeen, 2010; Doll & Ajzen, 1992), and a meta analysis (Armitage & Conner, 2001). Doll and Ajzen (1992) has also found that direct experience with a behaviour increases the predictive ability of behavioural intentions as well as the temporal stability of attitudes. Over the past 20 years the TPB has been a popular and influential behavioural theory within psychology and healthcare, and has shown strong predicative abilities for healthcare behaviours.

Background

HIV/AIDS affect all populations cross-culturally. The African-American population is severely impacted with new individuals becoming infected with HIV at an alarming rate. HIV infection remains a substantial problem for minority women, particularly African-American women. In 2009, African-American women accounted for 30% of the estimated new HIV cases among all Blacks.1

Current standard HIV treatment, referred to as Highly Active Antiretroviral Therapy (HAART), is a combination of different HIV medications. HAART does not cure HIV, but it can lower the level of the virus in the body and prevent destruction of the immune system. In addition to HAART, many infected persons consider the use of other methods of health care to help them deal with their HIV infection and/or the side effects of HAART itself. In general, many patients who suffer from chronic illnesses turn to other methods such as alternative medicine because of a desire to become more involved with their healthcare decisions and because of dissatisfaction with conventional medications.2,3

Generally speaking, complementary and alternative medicine (CAM) is defined as a broad range of healing therapies (e.g., nutritional supplements, herbal remedies, yoga) that are currently not integrated with conventional medicine and are not widely taught in Western medical schools.4 The use of CAM among HIV/AIDS infected individuals has gained increasing popularity, with utilization rates between 30% and 80%.5–7 One study found that the most frequent CAM therapies used among HIV-infected populations were aerobic exercise (64%), prayer (56%), massage (54%), and needle acupuncture (48%).8 Research has shown that among HIV-infected individuals, new users of alternative therapies were significantly more likely to be African-American.9 A similar study found that among HIV-infected individuals, 46% of African-Americans used CAM more frequently, compared to 38% of Caucasians and 27% of Latinos.10

Dietary supplements have been used as a type of CAM treatment among HIV-positive individuals. Dietary supplements were used to provide energy and nutritional substances to the body to aid in the prevention of gastrointestinal problems such as severe diarrhea and weight loss. Severe anorexia and Wasting Syndrome (involuntary loss of more than 10% of body weight) were at one point common illnesses in people with advanced-stage HIV.11 Since the introduction of HAART and other antiretrovirals, HIV-related wasting is now less common and is frequently rapidly reversed with nutritional supplementation.12,13 However, even in the era of antiretrovirals, weight loss associated with the virus remains prevalent.12

Scientifically, studies have shown that dietary supplements may have an effect on HIV viral load as well as the CD4+ T cells. A prospective randomized controlled study found that participants who were given a micronutrient supplement had a CD4+ T cell count that significantly increased at the end of a 12-week intervention.14 The authors of this study noticed, in addition, changes in HIV-1 RNA viral load level(s). There was a decrease in viral load in the micronutrient group, although the decrease was not significant. Another randomized controlled study found that participants in a selenium supplement intervention group had significantly less viral load and greater CD4+ T cell count increase when compared to the placebo group.15 Combined, these results show that dietary supplements may be effective in managing HIV.

Introduction

Of all the systems that people have to deal with on a daily basis, Road transport is the most complex and the most dangerous.22 In 1990, traffic crashes were the ninth most common cause of death in the world.28

Road traffic injuries cause a significant amount of injury-related mortality and morbidity around the world with an estimated 1.2 million people killed and about 20–50 million injured on the roads annually33; road traffic injuries are ranked among the top 10 leading causes of death worldwide.33,23,28 Projections estimate that these accidents will be the third most common cause of death by 2020.28 Nearly 85% of the global burden of road traffic injuries is accounted for by the low- and middle-income countries.33

Each year about 28,000 people die on Iran roads and the highway police say that every 3 min there is a crash and every 19 min someone dies in a crash.20 Road traffic crashes are considered to be the second highest cause of mortality in Iran27 next to coronary heart disease. Based on the Ministry of Health and Medical Education death registry data, in 23 out of 28 provinces in Iran, road traffic injuries (RTI) caused 31,800 deaths in 2003, which accounted for 9.9% of total deaths and 17.4% of years of life lost (YLLs). The cause-specific death rate due to traffic injuries is 47.8 in 100,000 (76.5 and 17.9 in males and females, respectively). The victims’ average age is 35.6 years.29

Among the cases of injury caused by traffic crashes, victims of motorcycle accidents and the pedestrian group had higher percentage of relatively severe head injury.8,30 For example, per vehicle mile (or kilometre) of travel (VMT), motorcycle riders in the US are 34 times more likely than car occupants to die in a traffic crash and eight times more likely to be injured.31 Approximately 42% of the injuries in men are due to motorcycle accident in Iran.37 WHO (2004) considers traffic crashes to be predictable and targetable by interventions consisting of multidisciplinary efforts aiming at their prevention, which means that the main cause of traumatic death in the world can be considerably avoided.44

The main risk factor for motorized two-wheeler users is the non-use of crash helmets. Use of helmets has been shown to reduce fatal and serious head injuries between 20% and 45% and to be the most successful approach for preventing injury among motorized two-wheeler riders.39 Motorcycle helmets significantly reduce the risk of death attributable to head injury. Riders with helmets have a 69% reduction in their risk of head injury (OR 0.31, 95% CI 0.25–0.38) and a 42% reduction in their risk of death (OR 0.58, 95% CI 0.50–0.68).42 Despite these evidences that helmet use can prevent motorcyclists from serious injuries and death, unfortunately, in the study done in Tehran in 2004 the helmet use rate was only 6% among motorcycle riders.37

Enforcement of the helmet use law put into action and concurrently initiated in March 2005 in Iran. Law enforcement strictly have been on penalties for motorcyclists who do not obey traffic laws including helmet use (50,000 Rials = 5 Dollar) and even seizing their vehicles. This law covers both, riders and pillion passengers.40 Despite this helmet use law, the rate of helmet use is still rather low in Iran. For example, in a cross-sectional interview-based study on victims’ characteristics and pre-hospital care in West Azarbaijan province of Iran, in 2009, among the motorcyclists, only 18% were said to be habitual helmet-wearers.21

Although having safety helmet is a precondition for using it, several studies have been shown that it does not automatically lead to high wearing rate.13 As Jacques stated, helmet use seems to depend mostly on a cyclist's motivation to use bicycle helmets rather than environmental, exposure, or cost related factors.19

The theory of planned behaviour (TPB)

The TPB (Fig. 1) is an important social cognitive model that aims to explain variance in volitional behaviours.4,5,9 The central premise of this theory is that people make decisions rationally by systematically using accessible information. The theoretical model hypothesizes that the causal antecedents of behaviour are a logical sequence of cognitions.14 The theory hypothesizes that an individual's overtly stated intention to act is the most proximal predictor of behaviour.5 TPB was developed as an extension of the Theory of Reasoned Action (TRA) model.2 Glanz et al. reported that the TRA components might not be sufficient for predicting behaviours in which volitional control is reduced. A person who has a high motivation to perform the behaviour may not actually perform the behaviour due to intervening environmental conditions. Environmental conditions may have an impact on the use of supplements. Access and economic factors may interrupt actually attaining supplements. Addressing that concern specifically is the extension to the original TRA model, with the theory of planned behaviour.16

Fig. 1. Conceptual representation of the theory of planned behaviour. Behavioural beliefs influence attitude, normative beliefs form subjective norm, and control beliefs influence perceived behavioural control. Attitude, subjective norms, and perceived behaviour control influence intention, which in turn, influences behaviour. In addition, perceived behaviour control may influence behaviour directly.

Ajzen.1

The basic premise of the TPB is that the most proximal predictor of behaviour is behavioural intention (i.e., a person's readiness to perform a given behaviour). Intention is hypothesized to mediate the influence of three sets of personal, social, and control-related judgments on the target behaviour5. Behavioural intention, in turn, is predicted by attitudes toward the behaviour (i.e., one's affective and instrumental evaluations of performing the behaviour); subjective norms (i.e., one's perceived social pressure to perform a behaviour or not); and perceived behavioural control (PBC) (i.e., the perceived ease or difficulty of performing the behaviour). Furthermore, each of these three major variables reflects a set of underlying accessible beliefs. These are behavioural beliefs (i.e., the perceive advantages and disadvantages of performing a behaviour) in the case of attitudes; normative beliefs (i.e., one's perceptions of the extent to which significant others want him or her to perform the behaviour) for subjective norm, and control beliefs (i.e., the perceived barriers and facilitators of engaging in a behaviour) for PBC.4 The theory of planned behaviour (TPB) has been successfully applied to the prediction of bicycle helmet use and wearing of seatbelts.15,24,32,34,35

Quine et al. in a previous study noted that theoretically driven intervention based studies on multiple determinants of helmet use are the most successful at inducing behaviour change.35 The first step in designing effective interventions is conducting basic research to explore and identify fundamental determinants of helmet use intention and behaviour among motorcyclists that are amenable to change.7 Efforts to understand the determinants of helmet use among Iranian motorcyclists using a theoretical framework, however, have been scarce. To our knowledge, no study has tested the utility of a theoretical framework in an Iranian context. This paper reports on predictors of helmet use behaviour, using variables based on the TPB model among the employed motorcycle riders in Yazd-Iran, in an attempt to identify influential factors that may be addressed through intervention efforts.

4.2 The Theory of Planned Behaviour

The Theory of Planned Behaviour (Ajzen, 1991) has been used to understand patients' decision-making about clinical trial participation (Quinn et al., 2011). The core concepts from the Theory of Planned Behaviour, attitudes, subjective norms, and perceived behavioural control, are evident within the three themes. As described above, when weighing up the decision to participate or not, patients were influenced by their attitudes towards clinical trials and the treatments available to them. They also drew upon a range of sources when considering their treatment and participation, echoing the influence of subjective norms on behaviour. Patients' decisions were influenced by their family and friends, their trust in the healthcare professionals involved in the trial, and a desire to help future patients, which is likely to be perceived as socially desirable behaviour. Patients' perceived behavioural control over their decision and ability to overcome barriers to participation were also reflected within these themes. Qualitative and quantitative studies highlighted potential barriers or burdens of participation such as the time and effort involved, which patients needed to overcome to participate. The studies also demonstrated perceived behavioural control over decision-making, with some patients explaining that they would withdraw should they not receive their preferred treatment or others agreeing to participate as this provided them with an opportunity to receive an otherwise unavailable treatment.

The application of health behaviour models such as the Theory of Planned Behaviour to trial participation could be valuable. Research into health behaviour shows that changing attitudes, the influence of others, and perceived control over behaviour play a more important role in achieving behaviour change than providing information (Ajzen, 1991). The findings of this review suggest that this may also be the case for trial participation. As these factors will vary between patients, a tailored approach to recruitment is needed to allow patients' attitudes towards trials and treatments to be understood and addressed.

2 Social-cognitive determinants of physical activity and socioeconomic status

The Theory of Planned Behavior (TPB) (Ajzen, 1991) and the Reasoned Action Approach (RAA) (Fishbein & Ajzen, 2010) incorporate many of the key determinants of health behaviors such as physical activity and propose that behavior is directly predicted by behavioral intentions, whereas the influence of other cognitions, in particular attitudes, subjective norm, and perceived behavioral control is mediated through intentions (with a residual direct effect of perceived behavioral control on behavior). Both the TPB and RAA have been widely used to examine physical activity (Hagger & Chatzisarantis, 2009; McEachan, Conner, Taylor, & Lawton, 2011; McEachan et al., 2016), which provides a substantial database of studies that have employed similar means to measure key health cognitions, ideal for review purposes.

The key assumption of the present review is that SES facets act as moderators of the relations between TPB variables and physical activity, that is, as factors that determine the degree to which these variables are associated with physical activity. In particular the relationship between intentions and physical activity is likely to be affected by SES. As noted above, income and occupational status might facilitate access to activity, which could lead to greater effects of intention on activity. This assumption is supported by at least two previous studies that found higher intention-activity relations in participants with higher income (Amireault, Godin, Vohl, & Pérusse, 2008; Pan et al., 2009), but see Vasiljevic, Ng, Griffin, Sutton, and Marteau (2015) as an example to the contrary. With regard to education, higher educational attainment has been linked to more stable intentions for physical activity (Godin et al., 2010), which in turn have been associated with higher intention-behavior relations. Two recent studies report conflicting findings on moderating effects of occupational status on the intention-activity relation. Conner et al. (2013) find the relationship between intentions and physical activity to be higher in individuals with higher-status professions, whereas Vasiljevic et al. (2015) found no moderating effects of occupational status.

With regard to perceived behavioral control, at least one study suggests moderating effects of income (Amireault et al., 2008): Here, the effects of control on activity are higher in participants with higher incomes. One study (Schüz et al., 2012) further found the relation between attitudes and physical activity to be moderated by area-level SES. Taken together, these studies suggest that SES might moderate the relation between social cognitions as outlined in the TPB and physical activity, but at the same time report heterogeneous findings that warrant a more thorough examination of the role of SES in the relationship between social-cognitive predictors of physical activity and activity.