There has been an academic interest in psychological myths and misconceptions for nearly a hundred years (Amsel, Baird, & Ashley, 2011; Brown, 1983; Furnham, 1992, 1993; Gaze, 2014; Hughes, Lyddy, & Lambe, 2013; Kowalski & Taylor, 2009; Nixon, 1925; Lamal, 1979; McKeachie, 1960; Taylor & Kowalski, 2004; Tupper & Williams, 1986; Vaughan, 1977). Studies have assessed student’s psychological knowledge with a view to evaluating the success of introductory courses (Arntzen, Lokke, Lokke, & Eilertsen, 2010; Gardner & Dalsing, 1986; Griggs & Ransdell, 1987; Lamal, 1979; McKeachie, 1960; Standing & Huber, 2003; Vaughan, 1977). Results have shown high levels of misconception (40% - 70%) prior to education, which are reduced, but only slightly, following education methods (LaCaille, 2015). Similarly, Hughes, Lyddy & Kaplan (2015) found years of university education and psychology courses completed were related to fewer misconceptions about psychology.
This research area has been stimulated by Lilienfeld, Lynn, Ruscio, and Beyerstein (2010), 50 Great Myths of Popular Psychology which reviewed and dispelled 50 myths. Numerous studies have used the 50 and 250 myths to test various hypotheses in this area (Furnham & Hughes, 2014; Furnham, 2018; Swami et al., 2015). Further other recent books have been published looking at specific myths (DeBruyckere, Kirschner, & Hulshof, 2015).
The study has encouraged researchers to develop new scales such as Gardner and Brown (2013) who developed a new 55-item measure of psychological misconceptions. Overall scores on this test were significantly and negatively correlated with reported reading of news magazines. Bensley, Lilienfeld and Powell (2014) also developed a 40-item measure based on the same source. They showed believing in psychological misconceptions was predicted by measures of paranormal belief, faith in intuition, the ability to distinguish scientific fields and practices from pseudoscientific ones, and academic scores.
Lilienfeld et al. (2010) inspired various other more specialised books with a very similar title and format. This study is based on two of these books. The first was entitled Great Myths of Adolescence (Jewell et al., 2019) which lists (and explains) 50 myths categorised under four headings: Development of the Body, Brain and Mind; Development of the Self; The Social Environment; and Problems in Modern Society. The second was Great Myths of Intimate Relationships (Johnson, 2016) which lists 25 myths under six headings: Sex; Attraction and courtship; Online dating; Same sex relationships; Predicting success and failure in relationships; Differences, discord and dissolution. In this study we followed Funrham (2018) who used the myths set out in these two books using the methodology of Furnham and Hughes (2014) who asked participants to rate each myth as Definitely True, Probably True, Probably False, Definitely False or Don’t Know. He hypothesised and demonstrated, based on previous results, that for over 50% of the myths in both categories participants would rate them as Definitely or Probably True. Overall it seemed that participants were better at identifying Brain Myths compared to Child Developmental myths. The results also showed that similar to the study of Furnham and Hughes (2014) that around 15% - 20% answered Don’t Know to the questions. Both the correlational and regression results did indicate one individual difference marker of myth detection. Those who rated themselves higher on “having common sense” were better detectors of myths.
A total of 517 participants completed the questionnaire: 259 were men and 258 were women. A power analysis suggested that this was sufficient to test our hypotheses. They ranged in age from 18 to 70 years with the mean age was 21.48 years and SD = 8.3 years. All participants had at least a secondary school education and 37% were graduates. 46.4% of the sample had children. Additionally, they rated themselves on three scales: How religious are you? (Not all at 1 to Very 8) and they scored 2.09 (SD = 2.75); How would you describe your political beliefs? (Very Left Wing 1 to Very Right Wing 8); they scored 5.38 (SD = 1.97); How Optimistic are you (Not at all 1 to Very 8) they scored 5.68 (SD = 1.94).
The myths and misconceptions were derived from two books, as noted above. Response options were broken down into “Probably” and “Definitely” True or False allowing for greater information to be gleaned regarding the kinds of True and False responses. In addition, the “Don’t Know” option improves upon some previous tests as participants could indicate a lack of knowledge, rather than guessing or leaving items unanswered (Arntzen et al., 2010).
Departmental ethical approval, based on UCL guidelines was gained prior to data collection (CEHP/2017/514). Data was collected on Prolific and participants were compensated for their time. The questionnaire took an average of 40 minutes to complete.
3.1. Prevalence of Misconceptions
All of the items presented were myths, thus for all items, the “correct” answer was False (Probably or Definitely). Participants’ False responses were summed in order to create a myth recognition score for each of the two questionnaires.
Myths About Adolescence: Table 1 shows the results for the 50 developmental myths. In all 6 were identified by more than 50% of the participants as Definitely False: 3, 22, 23, 27, 45 and 49. When the Definitely and Probably False were combined 22 of the myths were correctly identified as false by over 50% of the sample.
On the other hand, there were no items where over 40% of the respondents said that the following items were Definitely True. However, there were 11 where more than 200 respondents (40%) said they were Probably True. They were items 2, 5, 9, 10, 12, 15, 26, 28, 29, 38, 41. When the Definitely and Probably True were combined 11 of the myths were incorrectly identified by the sample.
On 18 items over 100 respondents (20%) said that they Don’t Know: The highest scores were for items 6, 8, 44, and 47.
Relationship Myths: Table 2 shows the results for the 25 relationship myths. In all 4 were identified by more than 50% of the participants as Definitely False. They were items 2, 4, 13 and 22. When the Definitely and Probably False were combined 12 of the myths were correctly identified as false by over 50% of the sample.
On the other hand there were 5 items where over 30% of the respondents
Table 1. Item level analyses for Myths about Adolescence.
Table 2. Item level analyses for Myths about Relationships.
selected Definitely True: 14, 16, 17, 19, and 20. When the Definitely and Probably True were combined 9 of the myths were incorrectly identified by the sample.
On 4 items a fifth or more of the respondents said that they Don’t Know: 10, 23, 24, 25.
Two scores were then computed for each individual: the total scores in each questionnaire in which they had marked Definitely False. For the first questionnaire the score was 18.89 (SD = 8.12) and the second 17.79 (SD = 8.12). The correlation between the two was r = .79 indicating considerable similarity in responses to the two questionnaires. These scores were then correlated with the various demographic and belief variables. There was no relationship between the total scores and age, gender, education, whether they had children and whether or not they had taken a course in psychology. Indeed, scores of those who had and had not some education in psychology were almost identical. Three variables were significant however for both total scores: they indicated that the more religious people rated themselves the higher their score: test 1, r = .24, test 2, r = .19; the more politically conservative people rated themselves the higher their score (test 1, r = .23; test 2, r = .18) and the more they believed they had common sense the higher their score (test 1, r = .22; test 2, r = .26).
A number of regressions were then computed, with both test total scores as the criterion variable. In the first set age, gender, taken a psychology course and self-assessed common sense was entered as predictor variables. The regression was significant for both tests: test 1 (F(4, 219) = 3.40, p < .01; AdjR2 = .04) and test 2 (F(4, 219) = 4.57, p < .001; Adj R2 = .06). In both cases only self-assessed common sense was significant Test 1 Beta-.22, t = 3.37, p < .001; Test 2 Beta .26, t = 4.05, p < .001). Those with higher self-assessed common sense were indeed more able to detect myths.
The two scores were then combined to produce a total score which served as a criterion variable. There were eight predictor variables: age, gender, education, taken a psychology course, self-assessed common sense, having children, religious beliefs and political beliefs. This was significant (F(8,211) = 4.50, p < .001, Adj R2 = .11). Two variables were significant predictors: common sense (Beta = .21, t = 3.13, p < .01) and religious beliefs (Beta = .18, t = 2.47, p < .01). Those with higher self-rated common sense and greater religious beliefs were better able to detect these myths.
The current results replicated findings of earlier studies on misconception prevalence (Arntzen et al., 2010; Furnham & Hughes, 2014) showing that a large number of myths were widely believed. This paper adds to the growing literature that is dedicated to exploring various myths and misconceptions about particular psychological concepts. Indeed this study was provoked by a series of books all dedicated to this endeavor (Hupp & Jewell, 2015; Jarrett, 2014; Jewell, Axelrod, Prinstein, & Hupp, 2019; Johnson, 2016).
Overall it seemed that participants were better at identifying Myths about Relationships compared to Myths about Adolescence, though this may be for methodological reasons. Many researchers have categorized myths into various topics like learning and neuromyths (De Bruyckere et al., 2015) though the research tends to show that participants are not particularly better informed and better “myth-detectors” in some areas rather than others.
It should be pointed that when authors list myths of various kinds such as in the book series Great Myths in Psychology commissioned by Wiley they do not indicate the extent to which they believe (or have any data) on the extent to which people would endorse the myths. Nor do they write the statements in such a way as they may be easily understood without reading the subsequent text. In this sense the myths are not all equal which is the finding of this and other studies.
One interesting finding that was similar to the study of Furnham and Hughes (2014) was the fact that around 15% - 20% answered Don’t Know to the questions. This number varied question by question but on average less than a fifth of respondents were prepared to admit that they did not know. We calculated the total scores for individuals on Don’t Know but this was not systematically related to any of the demographic variables. It could be that people were too embarrassed to admit they did not know when indeed the evidence shows quite clearly that they did not.
This, like other studies in the area, failed to find any strong, clear or logical demographic correlates of myth accepting or rejecting. Age, gender and education were not related to total correct scores, nor education in psychology. Some, but not all, previous studies did establish a small but significant relationship between education in psychology and myth recognition (Furnham & Hughes, 2014). This study found no such relationship; however this may be because of the lack of detail about that education. The question was simply “Did you ever take a course in psychology/psychiatry: Yes…No…”. As a result, we did not have details about the nature, depth and duration of the course, nor when and where it was undertaken.
Both the correlational and regression results did indicate one individual difference marker of myth detection. Those who rated themselves higher on “having common sense” were better detectors of myths. Descartes observed that common sense is the most widely distributed human characteristic because everybody believes they have a great deal of it which was reflected in the strong skew on this dimension. There was also some indication that religious and political beliefs were linked to myth detection though the correlations were low. The results were rather surprising showing that more religious and right-wing people tended to be better at myth detection.
Like all studies this had a number of limitations. First, the sample was heterogeneous but not fully representative in terms of age, religious views, marital status and educational attainment. It was also relatively small. We believe that a more representative sample would have more older people and those with less educational achievement; two factors that are associated with accepting more myths. It would however be most desirable to have collected data on whether the participants were parents of adolescence and how much contact they had with them. Similarly it would have been desirable to know more about the “relationship experiences” of the participants such as whether they had been divorced or indeed their parents had.
Next, in this study all the myths were indeed myths and therefore False. It may have been better to combine myths with “facts” to see if participants could distinguish the two. Third, not all of the myths were always clearly expressed or in the same style, no doubt because they were not written as questionnaire items.
Studies such as this provide useful historical data on psychological myth prevalent in society. They nearly always provide the “shocking truth” about the widespread acceptance of myths which nearly always concerns experts and educationists who call for attempt to dispel or debunk those myths.
The current study has shown that psychological myths and misconceptions (about adolescence and relationships) are abundant and persistent as well as potentially harmful and socially divisive. It is possible that myth-debunking campaigns designed around refutational methods akin to those used by Kowalski and Taylor (2009), Lilienfeld et al. (2010), and LaCaille (2015) have the potential to reduce levels of misconception. The current study can be used to identify myths and misconceptions in need of refutation.
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