Health Psychology. Michael Murray

Health Psychology - Michael  Murray


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is the integration of actor and context and the developmental perspective. Thus, the phenomenon under investigation is not dissected but rather maintains its integrity or wholeness and it is possible to map its changes over time.

      There are several different types of case study. The empirical case study is grounded in the data. The theoretical case is an exemplar for a process that has already been clarified. The researcher can conduct interviews, or repeat interviews and observe the case in different settings. The process of analysis can be considered the process of shaping the case. Thus, the researcher selects certain pieces of information and discards others so as to present a more integrated case. One example is De Visser and Smith’s (2006) investigation of the links between masculine identity and social behaviour with a 19-year-old man living in London.

      Confidence Interval

      A confidence interval (CI) is the interval around the mean of a sample that one can state with a known probability contains the mean of the population. A population parameter is always estimated using a sample. The reliability of the estimate varies according to sample size. A confidence interval specifies a range of values where a parameter is estimated to lie. The narrower the interval, then the more reliable the estimate. Typically, the 95% or 99% CI is stated in the results of a study that has obtained a representative sample of values, e.g., the mean heart rate for a sample might be 75.0 with a 95% CI of 72.6 to 77.4. Confidence intervals are normally reported in tables or graphs, along with point estimates of the parameters, to indicate the reliability of the estimates.

      Conflicts of Interest

      Conflicts of interest (also known as ‘competing interests’) occur when an investigator is affected by personal, company or institutional bias towards a conclusion that is favourable to a treatment yet unsubstantiated by research findings. Authors are expected to declare any conflicts of interest at the point of publication. One can argue that this may already be too late in the process to trust the findings.

      Cross-over or Within-participants Designs

      The cross-over or within-participants design is used when the same people provide measures of a dependent variable at more than one time and differences between the measures at the different times are recorded. An example would be a measure taken before an intervention (pre-treatment) and again after the intervention (post-treatment). Such a design minimizes the effect of individual differences as each person acts as his/her own control.

      There are a number of problems with this design. Any change in the measure of the dependent variable may be due to other factors having changed. For example, an intervention designed to improve quality of life among patients in a long-stay ward of a hospital may be accompanied by other changes, such as a new set of menus introduced by the catering department. In addition, the difference may be due to some aspect of the measuring instrument. If the same measure is being taken on both occasions, the fact that it has been taken twice may be the reason that the result has changed.

      Failure to find a difference between the two occasions doesn’t tell you very much; in a worsening situation, the intervention still might have been effective in preventing things from worsening more than they have already. The counterfactual scenario in which nothing changed is an unknown entity.

      Cross-sectional Designs

      Cross-sectional designs obtain responses from respondents on one occasion only. With appropriate randomized sampling methods, the sample can be assumed to be a representative cross-section of the population under study and it is possible to make comparisons between sub-groups (e.g., males versus females, older versus younger people, etc.). However, cause and effect can never be inferred between one variable and another and it is impossible to say whether the observed associations are caused by a third background variable not measured in the study.

      Cross-sectional designs are popular because they are relatively inexpensive in time and resources. However, there are problems of interpretation; not only can we say nothing about causality, but generalizability is also an issue whenever there is doubt about the randomness or representativeness of the samples. Many studies are done with students as participants and we can never be sure that the use of a non-random, non-representative sample of students is methodologically rigorous. The ecological validity of the findings is strongly contentious in the sense that they are unlikely to be replicated in a random sample from the general population. Any study with a non-random student sample should be repeated with a representative sample from a known population. Cross-sectional designs are also unsuited to studies of behaviour change and provide weak evidence in the testing of theories.

      Diaries and Blogs

      Diaries and diary techniques have been used frequently as a method for collecting information about temporal changes in health status. These diaries can be prepared by the researcher or participant or both, and can be quantitative or qualitative, or both. They can be compared to the time charts that have been used by health professionals for generations to track changes in the health status of individuals. Blogs also provide a rich source of data on different illnesses and conditions and lay ideas on ‘healthy living’.

      A summary of the current uses of the diary in health research is reproduced in Table 7.1.

      Diaries and blogs have benefits for the participant irrespective of the researcher (Murray, 2009). Research by Pennebaker (1995) and others has demonstrated that expressive writing can be psychologically beneficial. A series of studies has provided evidence that journal writing can lead to a reduction in illness symptoms and in the use of health services (e.g., Smyth et al., 1999). There are a number of explanations for this, including the release of emotional energy, cognitive processing and assistance with narrative restructuring. However the effects are small, and not always easy to replicate.

      The internet provides a resource for blogs, diaries and forums in which individuals share their experiences, seek information and provide virtual social support. Anonymity may be used by bloggers to foster self-disclosure in describing embarrassing conditions. Chiu and Hsieh (2013), using focus group interviews with 34 cancer patients, explored how cancer patients’ writing and reading on the internet play a role in their illness experience. They found that personal blogs enabled cancer patients to reconstruct their life stories, and express closure of life and how they expected to be remembered after death. Reading fellow patients’ stories significantly influenced their perceptions and expectations of their illness prognosis, which was sometimes a greater influence than their doctors.

      Direct Observation

      The simplest kind of study involves directly observing behaviour in a relevant setting, for example patients waiting for treatment in a doctor’s surgery or clinic. Direct observation may be accompanied by recordings in written, oral, auditory or visual form. Several investigators may observe the same events so that reliability checks can be conducted. Direct observation includes casual observation, formal observation and participant observation. However, ethical issues are raised by planned formal observational study of people who have not given informed consent to such observations.

      Discourse Analysis

      Discourse analysis is a set of procedures for analysing language as used in speech or texts. It focuses on the language and how it is used to construct versions of ‘social reality’ and what is gained by constructing events using particular terms. It has links with ethnomethodology, conversation analysis and the study of meaning (semiology). There are two forms of discourse analysis. The first, discursive psychology, evolved from the work of Potter and Wetherell (1987) and is concerned with the discursive strategies people use to further particular actions


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