Two Key Studies of Dispositional Factors & Health Beliefs (HL IB Psychology)

Key study one: Rasmussen et al. (2009)

Aim: 

• To determine the strength of the relationship between optimism and physical health

Procedure: 

• This was a meta-analysis of findings from 83 studies, with 108 effect sizes 

• Researchers performed computerised literature searches of the MedLINE and PsycINFO databases and online journals 

• Only research published in English language peer-reviewed journals were selected

• Studies needed to contain:

  • measure[s] of dispositional optimism

  • measure[s] of a physical health outcome

  • a measurement of effect size

  • a reported sample size

Results:

• A significant effect size was found between dispositional optimism and health (r = 0.17)

• An even stronger significant effect size was found for optimism and self-reported (subjective) measures of health (r=0.21)

• However, the effect size for optimism and objective measures of health was weaker (r=0.11)

• Analyses of studies grouped by types of outcome (such as mortality, cardiovascular disease or immune function) all showed the same correlation

Conclusion:

• There is a correlation between dispositional optimism and physical health, as standardised measures identified that the most optimistic participants in the studies reviewed had the best health outcomes

• The strongest correlation is between optimism and subjective measures of health, as the most optimistic participants’ perception of their own health was as even better than the their medical test would suggest

Evaluation of Rasmussen et al. (2009)

Strengths

• Careful control of the selection criteria and standardisation of the statistical analysis increase the reliability of the findings

• The separation of physical health outcomes into subjectively and objectively demonstrate construct validity 

Limitations

• There are common problems with self-report health questionnaires to gain data on subjective health:

  • Social desirability effect - participants may underestimate their own health problems

  • Different interpretation of the question from that intended

• A correlation can only suggest association rather than cause-and-effect i.e. those who felt the healthiest became the most optimistic, rather than vice-versa (bi-directional ambiguity)

Key study two: Masiero et al. (2015)

Aim: 

• To analyse the influence of the optimism bias and consequent health beliefs on:

  • smoking initiation (when smoking is first taken up), 

  • consolidation (when smoking becomes a habit) 

  • maintenance of smoking over time

Participants: 

• 633 (345 female; 288 male) participants 

• Aged between 19 and 74 years old (mean age 48.01)

• Volunteer sample recruited through internet sites

• The sample was composed of:

  • smokers - 35.7%

  • ex-smokers - 32.2%

  • non-smokers - 32.1%

Procedure: 

• Each participant filled out two questionnaires:

  • The Fagerström test 

  • A questionnaire designed to evaluate the strength of their intention to give up smoking or to maintain their non-smoking status

• Participants also completed a set of items measured on a Likert scale to evaluate their health beliefs

Results:

• 63% smokers had a moderate to high nicotine dependence level, with a mean of daily cigarettes smoked being just over 20

• 41.7% of smokers reported a high motivation to quit, with most falling between the high and middle level. 

• Smokers reported doubt that the cigarette smoking could be a possible cause of death for themselves

• However, smokers did see smoking as a risk of death for others

• Ex-smokers and non-smokers reported more realistic judgments regarding the risks of smoking

• Smokers underestimated the following:

  • The power of their own nicotine dependence

  • The association between tobacco consumption and lung cancer

• Smokers (especially younger smokers under 40 years old) overestimated the following:

  • Their own control over their behaviour

  • The power of physical activity to counteract the negative effects of smoking 

• Male smokers aged over 60 showed the greatest awareness of their own nicotine dependence

• Female smokers consistently showed less perception of the risk of smoking than did male smokers

Conclusion:

• Optimism bias in risk perception may influence health behaviours in negative ways and reinforce cigarette smoking over time

Females are more likely than males to underestimate the dangers to health of smoking

Evaluation of Masiero et al. (2015)

Strengths

• Measures of nicotine addiction, motivation and risk perception were carried out with all participants, allowing for comparisons between smokers, ex-smokers and non-smokers

• The data can be used to inform health protection strategies and aid smokers to quit

Limitations

• Self-report measures may affect the validity of responses as participants may underestimate the numbers of cigarettes they smoke daily

• The volunteer sample was recruited through internet sites and so it may not be representative of most smokers, reducing the generalisability of the findings