Background
Before embarking on further studies, the belief-basis measure was in need of refinement. It was not used in the previous study because of the need to avoid varying too many parameters in the study, so that confidence could be placed in the results when comparing real-world belief change effects with self-predictions measured in the lab; moving from the laboratory to the real world is a big enough change in itself and modifying a measure is also non-trivial. It was reassuring to know that the belief-basis findings were still replicated and that the study was all but identical to the non-intervention study. However, there remained a number of issues with the current measure that were addressed for use in further studies in the series.
Firstly, it can be observed that the original belief-basis measure is not balanced in terms of the number of items (Griffin, 2008; Griffin & Ohlsson, 2001). There are three items for intuitive reasons, but only two items for rational reasons. A second issue is that the evidence-based reason presented for participants to rate is not specified as being rational or intuitive. However, people can perceive their personal experiences as
‘evidence’ (Clarke, 1995) or they might be referring to scientific evidence. This clearly confounds the meaning of the item. Indeed, Griffin (2008) does note that types of evidence are collapsed within the belief-basis measure, but cites this as an advantage, since it does not limit participants to only rational evidence. However, it is unclear how this achieves the aims of measuring the relative contribution of intuitive and rational reasons for beliefs since it is not possible to determine if a participant’s response to that item is intended as relating to rational or intuitive evidence. In fact, Griffin (2008) goes on to state that:
“It is important to note that while the last item refers specifically to “Science”, the item labeled “Evidence” provides no constraints on how respondents interpret the meaning of “evidence” and the phrase “that I am personally aware of” was
included to encourage respondents to include anything they would consider a type of “evidence”. Testing revealed that the Evidence and Science items are only correlated at r = .50, meaning that 75% of the variance in Evidence ratings is independent from the Science item.” (p.3)
Here the correlation confirms the suspicions that the evidence item is confounding the two types of evidence that a path-dependent model of belief change would be seeking to separate.
Finally, from the replication data it was noted that the faith item was essentially a subset of ‘head versus heart’. Only 7% of responses rated faith as higher than head/heart as a reason for belief or disbelief. This implies that the two items need conflating into a single item rather than doubling up on the intuitive belief-basis scoring and artificially influencing the overall score.
The refinement proposed in the present chapter therefore aimed to provide a more balanced belief-basis measure. In doing so, the free-response text from the replication study was also drawn upon, similarly to how Griffin and Ohlsson (2001) did in their original study to produce their original items. The aim was not to develop a completely new measure, however, it was merely to refine the existing one in a logical and careful way. Part of this process involved qualitative analysis of the free-response text, but it was not limited to this.
Materials
As a convenience to the reader the original belief-basis items are replicated in Table 11, for ease of reference. This was the base from which the present refinement developed.
Table 11 - Original belief-basis measure items
Intuitive Rational
My belief about [topic] makes me feel good or is comforting.
When it comes to issues like [topic], I trust my 'heart', not my 'head' to tell me the truth.
I don't need proof, I have faith that my belief about [topic] is correct.
My belief about [topic] is a result of examining all of the evidence I'm aware of and choosing the most convincing explanation.
My belief about [topic] is supported by current scientific knowledge.
The only other material used directly in the revision was the free-response text from Study 1, which can be found in full in Appendix 3. As stated in Study 1 the sample size for the study was 72, consisting of 30 men and 42 women, ranging in age from 20 to 70 (mean 36.16, SD = 14.873). All free-text responses by participants were checked for anonymity before including in Appendix 3 (no redactions were required).
Analysis
The responses were analysed using an inductive (bottom-up) thematic analysis, looking for semantic (explicit-level) themes, following the basic process outlined in Braun and Clarke (2006). Points of interest in the responses were noted before bringing them together under initial higher level themes, trying to allow the data to speak for itself and not fall into the trap of using the question/prompts as ready-made categories, although it must be acknowledged that the original items from Griffin and Ohlsson
(2001) could not be completely ignored. Indeed, one would expect to find similarity.
The responses were then recoded in terms of the themes, before revisiting the responses and distilling the themes further (what Braun and Clarke refer to as ‘define and refine’). At this point, typical thematic analysis would proceed to attempt to link the themes together into an overarching ‘story’ that explains the results. However, for the purposes of the present study it was sufficient to identify key themes that might form the foundation of any new items. In the end only one such additional theme was produced by the analysis and this was “internal consistency”. This was a rational reason for not holding competing points of view or for disbelieving in a particular view. This kind of thinking often centred around contradictions in Bible scripture, for example, with participants stating that:
“The Bible is even internally inconsistent. There are two creation stories in Genesis that contradict each other.”
“The bible stories of creation have internal contradictions.”
This was not a theme that emerged due to being numerous in the responses, but it was one that came out as critical to some reasons for belief or disbelief and thus had importance overall. In thematic analysis the importance of a theme needs to be considered rather than just frequency (which is a different kind of analysis). The ultimate aim in a typical thematic analysis is to tell a meaningful, and hopefully accurate, story. Individual items can carry more weight than multiple other items in such a scenario therefore and internal consistency was deemed to be one such theme.
In addition to analysing the free-response data there was also some modification of the existing belief-basis items. The original scale is unbalanced, with 3 intuitive items and 2 rational items, as well as omitting personal experience, which is a known correlate of paranormal belief. One of the aims was therefore to balance the items and also include personal experience. It was also noted that the item on evidence did not specify what type of evidence, however, so this was split into two items, one on subjective evidence (including personal experience) and one on objective evidence, because ‘evidence’ may mean different things to different people, as illustrated by the colloquial parlance of
believing the evidence of one’s own eyes. This provided an item on personal experience while at the same time separating out the types of evidence. In contrast, two of the intuitive items were collapsed down to one item. The original item on faith was removed as this was deemed to be a subset of ‘head versus heart’ (only 7% of responses rated faith as higher than head/heart as a reason for belief/disbelief). The internal contradiction theme found in the thematic analysis was also added as a rational item, balancing out the number of items of each type. Also influenced by the free-response Study 1, the ‘scientific knowledge’ item was changed to just ‘science’ to allow a broader scope of application. Finally, the question prompt itself was changed from using the term ‘belief’ to using the term ‘view’. This was done to bring the usage more in line with academic operationalisation of belief and avoid cultural connotations the term may hold for some people, such as conflating it with ‘faith’. In the colloquial sense, some people may argue that one does not ‘believe’ in a scientific theory, for example, since faith is not required. Table 12 (see next page) presents the final items used in the revised belief-basis measure.
Table 12 - Predefined reasons for belief and disbelief
Intuitive Rational
I hold my particular view about [topic]
because that view of things makes me feel good or is comforting.
Personal experience or observation is the reason for my particular view about [topic].
When it comes to issues like [topic], I trust my 'heart', not my 'head' to tell me the truth.
I have arrived at my particular view about [topic] after careful evaluation of the i.e. the arguments contain contradictions within themselves and so cannot be true.
Discussion
The aim of this chapter was to modify the belief-basis measure to allow participants to better express their reasons for belief. The refined measure achieved the aims set out for it. It is balanced in terms of the number of items. Conflated items have been separated and ‘doubled’ items have been conflated. And where necessary new elements have been introduced, such as personal experience and internal consistency.
The terminology has also been changed from ‘belief’ to ‘view’ in order to use a more neutral term that does not imply any of the cultural connotations that some people may associate with the term, such as faith versus knowledge. Academics may
from participants, that appropriate terms for the audience are used – this is long known as an issue in cross-cultural studies (van de Vijver & Leung, 2016) and it could be argued that academia is itself a culture with its own language, so care is needed.
There is, of course, with any qualitative analysis or measure refinement, a tension between letting the data speak for itself and the agenda of the researcher in creating a new scale. So, in this instance, for example, the free-response text could not be neutrally analysed, since there was already knowledge of the existing items from the original belief-basis measure, and there was also some expectation of developing a scale with an equal number of items for intuitive and rational belief-basis. It is hoped, however, that the resulting treatment of the belief-basis measure has achieved the balance of fairly representing the data, whilst also achieving refinement of the measure. The full list of free-response texts is included in Appendix 3, so that the reader is free to draw their own judgments upon this matter.
In conclusion, the belief-basis measure is now arguably more balanced than the original, and suitable for use in further intervention studies in the research programme. The present chapter only covers the refinement of the measure and has not included any testing of it. The measure has good face validity, however, and was tested in the next intervention study. That study was almost identical to the first intervention study other than the inclusion of a new factor (inhibition of intuitive cognition) and the self-predicted belief change question being reinstated. It was not expected that the results would change dramatically. It was expected that the same belief-profiles would be seen, since the general belief-basis finding is robust not just within Griffin and Ohlsson’s (2001) paradigm, but within the wider literature as well.
However, the revised measure would hopefully provide a greater chance of detecting real effects due to the revised construction of the measure in terms of intuitive and rational belief-basis items.
Study 3 – Does Inhibition of Intuition Contribute to Belief Change?
Background
It has been argued in this thesis that dual-process accounts of cognition have good empirical support. In this respect, the present research programme has so far added to this body of literature by providing support for the idea that beliefs have varying belief-bases – in particular, that paranormal belief, in ESP, is associated with a greater intuitive component to belief-basis. Furthermore, the path-dependent belief change hypothesis has received some early support, albeit that this needs interpreting with a note of caution. The path-dependent model proposed was deliberately simple, however, only introducing the factors that were thought to be needed to predict variation in belief change, whereas, dual-process accounts of cognition include another key factor that was not included in the original model. This factor is the evolutionary primacy of intuitive cognition. In dual-process accounts it is generally agreed that intuitive cognitive processing comes more easily and/or prior to any rational cognitive processing (see the General Background chapter for a detailed discussion of this). With regards to the present study, it will be argued that in order for rational cognition to take centre stage and have an effect, intuitive cognition must be inhibited and that therefore this factor will need to be included in the model if it is to accurately predict belief change.
The classic incarnation of rational thinking is critical thinking, defined by Ennis (Ennis, 1991, 2018) as “... reasonable reflective thinking focused on deciding what to believe or do ...” (p.1). Indeed, Aarnio and Lindeman (2005) argue, based upon their study on educational level and paranormal beliefs, that it is the stronger preference for analytical thinking (i.e. critical thinking) that leads to a reduction in levels of paranormal belief as educational level gets higher. However, while their data did find the association between educational level and thinking style, it remains an assumption that education
or educational ability is associated with a greater tendency for analytical thinking style.
There is also the problem that the assumption refers only to preferences for an analytical thinking style, rather than a tendency to actually apply it. Under academic conditions of study or examination it seems obvious that people’s thinking style might be cued (Inbar et al., 2010) and the person could choose to apply their preferred style of analytical thinking. However, paranormal beliefs may not necessarily form in situations where cueing is available within the situational context and in this sense it would be better to talk of a tendency to apply rational thinking. Indeed, it is possible to read Aarnio and Lindeman’s (2005) ‘preference for analytical thinking’ as equating to ‘tendency for analytical thinking’. Semantically it may be clearer to avoid the implication that people are consciously choosing the type of thinking to apply.
Interpreted in this way, Aarnio and Lindeman‘s (2005) suggestion finds some support from a study by Rogers, Davis, and Fisk (2009). They tested believers and believers in the paranormal on conjunction tasks relating to both paranormal and non-paranormal events. They found that believers made more errors on both topics, implying that they had a lesser tendency to apply rational thinking to the problems, as suggested by Aarnio and Lindeman. Indeed, this is interesting in relation to the inverse association with educational level that Aarnio and Lindeman found. While educational level does, of course, act as a proxy for intellectual ability in many cases, Aarnio and Lindeman did not conclude that it was intellectual ability that correlated with lower paranormal belief. Instead, they refer to a preference or tendency, or simply a difference in thinking style, but not a difference in ability.
There is good reason for such a hesitancy to equate paranormal belief with intellectual mediocrity, largely because the body of literature on thinking skills and thinking errors demonstrates that the two tend to dissociate more often than not. In short, it is one thing to have thinking skills, but it is quite another thing to actually apply them. This dissociation is evidenced again and again in the literature. For example, Blackmore (1997) found that the thinking error of misjudging probabilities is not correlated with greater paranormal belief. This suggests that there is no difference in the abilities of the believers and non-believers. Similarly, Dagnall et al. (2007) found few differences
between believers and sceptics on a range of probabilistic reasoning tasks. The only exception was on the perception of randomness, in which believers tend to see more meaning. This is arguably less of a thinking error, however, and more one of perception. Indeed, they refer to the test as being “perception of randomness” and it was conducted by asking participants to make judgments about the likelihood of various sequences of coin tosses. However, they also tested participants on the use of base rate information, the conjunction fallacy, and derivation of expected value, all of which are very much non-perceptual tasks. There was no difference between sceptics and believers on these tasks, suggesting they share similar thinking abilities on these particular problems.
Critical thinking and reasoning skills are also found to dissociate from thinking errors.
Hergovich and Arendasy (2005) found no relationship between critical thinking skills and paranormal belief, using the Cornell Critical Thinking Test and Watson–Glaser Critical Thinking Appraisal. And while they do claim an inverse correlation between reasoning skills (measured on the Wiener Matrizen-Test), this was only true for a few of the paranormal beliefs that were investigated, making it less likely that this is a real effect rather than a statistical artefact, since the specific pattern of correlations and non-correlation was not predicted in advance. Similarly, Royalty (1995) looked at critical thinking skills (measured on the Cornell Critical Thinking Test) in relation to paranormal belief and concluded that there is indeed a difference between having such skills and applying them.
In addition to the above examples, the general background chapter of the present thesis also presented evidence that thinking ability is independent of the likelihood of falling foul of thinking errors (Stanovich & West, 2007, 2008a, 2008b). Furthermore, in the same chapter, it was seen that even experts fall foul of these types of errors (Schwitzgebel & Cushman, 2015), such as the ethics philosophers who did no better than lay participants on reframed, structurally identical versions of classic ethical problems, such as the trolley problem or the Asian disease problem. All it took was a change of framing or ordering of the scenarios. Nor was there any pressure for a speeded response; the experts were free to take their time. This suggests that intuitive
cognition has primacy over rational cognition and that the former is not easily suppressed. Speeded response tests add further weight to the argument for evolved primacy of intuitive cognition, however (e.g. Kelemen et al., 2013). The general finding here was that when cognitive resources were reduced due to time constraints, experts did no better than lay people on physics problems. In short, rational thinking takes time. However, by the time the rational system has put its boots on, the intuitive system has already arrived with an answer, unless the intuitive system is inhibited somehow. An alternative solution is to reject the initial intuitive answer once the rational system catches up. However, in a speeded test, this means that the rational
cognition has primacy over rational cognition and that the former is not easily suppressed. Speeded response tests add further weight to the argument for evolved primacy of intuitive cognition, however (e.g. Kelemen et al., 2013). The general finding here was that when cognitive resources were reduced due to time constraints, experts did no better than lay people on physics problems. In short, rational thinking takes time. However, by the time the rational system has put its boots on, the intuitive system has already arrived with an answer, unless the intuitive system is inhibited somehow. An alternative solution is to reject the initial intuitive answer once the rational system catches up. However, in a speeded test, this means that the rational