Mechanisms of Mindfulness in Those with Higher and Lower Levels of Autism Traits

Mechanisms of Mindfulness in Those with Higher and Lower Levels of Autism Traits The effects of brief mindfulness induction on a central trait of autism spectrum disorder (over-selective attention) were examined in order to assess whether different mechanisms act in those with lower and higher levels of autism traits, and determine which intervention may be most appropriate for individuals with different sets of symptoms. Two hundred and 24 volunteer participants (110 male; 114 female) were assessed for levels of autism traits (autism quotient; AQ), anxiety and depression (Hospital Anxiety and Depression Scales), and mindful awareness (Toronto Mindfulness Scale). They were randomly assigned to mindfulness, relaxation, or no-intervention groups. After three 10-min sessions, held on alternate days, participants underwent simultaneous discrimination training between two two-element compound stimuli (AB+ CD−), followed by an extinction test (AvC, AvD, BvC, BvD) to determine the amount of over-selectivity present. Levels of depression, anxiety, and mindfulness were re-assessed. Participants with greater autism traits demonstrated greater over-selectivity, than those with lower autism traits. Mindfulness reduced over-selectivity, and did so independently of the level of AQ displayed by the participants. For lower scoring AQ participants, mindfulness worked more effectively than relaxation. In contrast, for participants with higher AQ scores, there was little difference between the impact of mindfulness and relaxation. The latter group displayed no improvement in mindful awareness. Mindfulness induction can be effective, but may work through different mechanisms for those with higher and lower autism traits, and consideration should be given as to whether this intervention may be the most suitable in all cases where autism traits are present. . . . . . Keywords Mindfulness Brief-induction Over-selectivity Autism quotient Anxiety Relaxation Mindfulness has been suggested as an intervention beneficial problems (Zeidan et al. 2010) and attentional difficulties for a range of emotional problems, such as depression (McHugh et al. 2010). (Hofmann and Gómez 2017;Spek et al. 2013; Winnebeck et However, there are also suggestions that the widespread al. 2017) and anxiety (Hoge et al. 2017; Hofmann and Gómez usage of mindful techniques may not be fully supported by 2017;Kiep et al. 2015); as well as improving aspects of cog- the literature (Van Dam et al. 2018). In some cases, this is nitive functioning, such as attention (Chesin et al. 2016; claimed because mindfulness may be less effective than Morrison and Jha 2015) and memory (Zeidan et al. 2010). other available treatment procedures for some subsets of a Positive impacts have been claimed for a range of populations, population (see Arch and Ayers 2013, for a discussion). In including individuals with clinical problems (see Cachia et al. other cases, because mindfulness may be actually damaging 2016, Hofmann and Gómez 2017, for reviews), and those with to the individuals (Briggs and Killen 2013). Importantly for problems of a non-clinical nature who are affected by issues, clinical practice, these concerns arise, in part, as it is not such as performance or test anxiety (Cho et al. 2016), memory fully established which populations may be able to benefit from mindful techniques (Arch and Ayers 2013;Van Dam et al. 2018). Similarly, it is not established precisely how mindful techniques produce their effects, and it is far from * Phil Reed clear that mindfulness works through the same mechanism p.reed@swansea.ac.uk for different groups of individuals. This latter consideration is also important for clinical practice, as understanding the Department of Psychology, Swansea University, Singleton Park, mechanisms of action of any intervention can help to Swansea SA2 8PP, UK Mindfulness develop and refine that intervention and tailor it for usage in Lee and Orsillo (2014) noted that both mindfulness and relax- particular cases. ation produced improvements with an emotional Stroop task One set of individuals who have received contemporary compared to a control group. Indeed, it may be important that research effort with regard to the effectiveness of mindful- mindfulness sometimes does not work as well as other forms ness, and who straddle both the clinical and non-clinical of talking therapy for those with high levels of anxiety (Arch population, is those scoring high in autism traits (Cachia et and Ayers 2013), although the degree to which this finding al. 2016; Higuchi et al. 2017; Singh et al. 2011). A number generalises across functioning areas and populations is not of reports have suggested that mindfulness does impact clear (cf. Arch and Craske 2006). beneficially on this population along some dimensions of This lack of evidence for the specific impact of mindful- their functioning (Kiep et al. 2015;Speketal. 2013). ness in a population with high-functioning ASD, including Current evidence is suggestive for a positive impact on those scoring high on autism traits but without a formal clin- reducing rumination (de Bruin et al. 2015;Kiepetal. ical diagnosis (i.e., those high on the broad autistic pheno- 2015) and anxiety (Spek et al. 2013; see Cachia et al. type), contrasts with a range of studies for other populations 2016, for a review). However, the picture with regard to that have shown an impact of mindfulness relative to relaxa- other emotional problems associated with this population tion. For example, Arch and Craske (2006)demonstrated a is not so clear(seedeBruin et al. 2015;Speketal. 2013). positive impact of a brief mindfulness training programme Importantly, it has not been established which, if any, of the on anxiety, over and above the effects of relaxation, for a many of the central cognitive aspects of autism apectrum dis- group with anxiety disorder. Similarly, McHugh et al. (2010) order (ASD), such as attentional problems, are helped by noted greater improvements in performance on an attentional mindfulness (see de Bruin et al. 2015). Neither has it been over-selectivity task for older individuals. Over-selectivity oc- established, whether any such impacts are actually a direct curs when one aspect of the environment controls behaviour at effect of mindfulness or due to its impact on other areas of the expense of other equally salient and/or important aspects functioning, such as anxiety, which then helps with the symp- of the environment (see Dube 2009; Kelly et al. 2015). This toms under investigation (cf. Maisel et al. 2016, for a related latter task may be of particular importance to the ASD popu- discussion). While emotional problems, such as anxiety and lation, as they are known to display very high levels of over- depression, are clearly important issues for those with higher selectivity and narrowed attention (Kelly et al. 2015). functioning ASD (Posserud et al. 2016;Reed 2016), and those Thus, it may be that mindfulness produces benefits with high levels of autism traits who are non-clinical (Reed et across a range of populations, but may do so through al. 2016; Towbin et al. 2005), they are not a diagnostic criteria different mechanisms. In those with lower anxiety levels, for ASD (DSM-5; APA 2013). mindfulness may impact directly on a range of cognitive A further difficulty about making judgments about the im- and emotional domains (Zeidan et al. 2010). However, for pact of mindfulness for those with high levels of autism traits those with higher anxiety, which may include those with is that many reports do not include control groups to isolate high-functioning ASD (MacNeil et al. 2009), mindfulness specific effects of mindfulness, relative to other nonspecific may work to reduce anxiety through some nonspecific aspects of a very complex intervention (e.g., relaxation). For aspect of the intervention, and this impacts levels of func- example, both de Bruin et al. (2015), and Singh et al. (2011), tioning (Lee and Orsillo 2014;Maiselet al. 2016). had only a before and after measure of rumination, and Spek et Certainly, in terms of over-selectivity, it is known that al. (2013) compared a group with mindfulness to a waiting list increasing levels of cognitive (Groden et al. 1994)and control. Given the impact of mindfulness on anxiety-related psychological (Reed and Gibson 2005) stress increases issues for ASD (de Bruin et al. 2015;Kiepetal. 2015; Spek et over-selectivity responding. Given this, a reduction in al. 2013) and the relatively high levels of anxiety reported by anxiety may serve to reduce over-selective attention— those with high-functioning ASD (MacNeil et al. 2009; Reed and it may be that this reduced anxiety, rather than some 2016), it is unclear whether mindfulness has its impact specific mindful mechanism is responsible for improve- through specific mindfulness-related mechanisms or through ments in performance. some of the associated nonspecific process involved, like re- The current study aimed to explore these possibilities with laxation (see Arch and Craske 2006; Maiseletal. 2016;Van regard to the impact of mindfulness on over-selective atten- Dam et al. 2018). tion. The level of autism traits was measured in a volunteer Research with individuals with ASD has not reported uni- sample, along with their levels of anxiety, depression, and versally positive results in regard to the mindful-specific mindfulness before and after a brief mindfulness intervention mechanisms responsible for improvements produced through (modelled on that employed by Arch and Craske 2006). Based mindfulness interventions. Although de Bruin et al. (2015) on previous literature, it was predicted that mindfulness would reported a reduction in rumination after mindfulness training, reduce over-selective responding in those with lower autism they noted no greater mindful awareness in those participants. traits, compared to relaxation and a no-intervention control, Mindfulness but both relaxation and mindfulness would work to reduce participants were presented with the experimental procedure over-selectivity in those with higher autism traits. It was also via a Dell Latitude E6540 laptop (display size: 15.5″), pro- predicted that mindful awareness would not increase after the grammed in E-Prime®. After this, they completed the HADS mindfulness intervention in the group with higher autism traits and TMS again. as much as in the former groups, but anxiety (being higher to start with) would reduce in the relaxation and mindfulness Interventions There were two separate exercises—arelaxation interventions for those with higher autism traits. This pattern (unfocused attention) induction (relaxation) and a focused at- of results would suggest that mindfulness works through dif- tention induction (mindfulness) that were based on the exer- ferent mechanisms for different groups of individuals. cises used by Arch and Craske (2006), and which have been shown to remediate over-selectivity in non-clinical popula- tions (McHugh et al. 2010). Each exercise was delivered by Method a recording of a female voice, who was clinically qualified, and lasted 10 min. Participants experienced three sessions of Participants their allotted exercise, each separated from one another by 1 day, making the study last 5 days in total. This procedure Two hundred and 24 volunteer adult participants (110 male; was based on the brief-mindfulness intervention constructed 114 female) were recruited from the general public and uni- by Lee and Orsillo (2014) for cognitive flexibility. The exer- versity students. The study adopted an exclusion criterion of cises were completed alone by the participants while sitting in anybody currently or previously in receipt of a diagnosis or a dimly lit small room, and they were encouraged to practice treatment for a psychological problem, including ASD, which the exercises at home in between the sessions. was specified on the advert for the study, and through self- report at the start of the study. No payment or course-credit Mindfulness (Focused Attention) Induction The instructions was given to the participants. Participants had a mean age of for the mindfulness induction were BFocus your attention on 24.50 (± 6.02 SD; range = 18 to 49) years. Participants under your breathing. Notice the sensation of breathing air in. the age of 18 years were excluded for ethical reasons, and Notice the sensation of breathing air out. As you breathe air those over the age of 55 years were excluded on the basis of into your body, fill your mind with the thought ‘just this one previous research showing different levels of over-selectivity breath’. As you breathe air out of your body, fill your mind occurs in older individuals (McHugh and Reed 2007). with the thought ‘just this one exhale.^ Whenever any other Participants who had a history of self-reported psychiatric thoughts came into the participants’ minds, they were problems were excluded, as were those who reported that they instructed to try and push them aside, and continue to focus only on their breathing patterns. had previously engaged in meditation or mindfulness tech- niques, as pilot studies had shown that previous meditational experience overwhelms any experimental manipulations. A Relaxation (Unfocused Attention) Induction The participant priori power analysis (G*Power; Faul et al. 2007) for the instructions for the exercise were BLet your mind wander free- overall analysis of variance (ANOVA) indicated that this ly amongst thoughts about past and present future events. was sufficient sample size to detect medium effect sizes. Start by allowing your mind to roam. Don’t try to focus on Ethical approval was given by the Ethics Committee of the your thoughts; just let them drift without hesitation. There is University Psychology Department in which this research was no need to focus on anything in particular. Allow yourself to conducted, and all participants gave fully informed consent to think freely. Try not to focus on any one thing. Just let your their participation. mind wander.^ Procedure Experimental Training Phase Training commenced with the instructions BPlease select one of the two stimuli presented Participants were randomly assigned to one of three groups: as soon as ‘respond now’ appears on the screen. You will be mindfulness (n =74), relaxation (n = 74) and control (n =76). given feedback indicating whether you selected the correct or Each participant completed all parts of the study separately, in incorrect stimulus. Your aim is to select the correct stimulus.^ a small, quiet, dimly lit experimental room. During the first All participants were then presented with two simple discrim- session, participants completed the AQ, HADS and TMS by ination tasks consisting of the compound stimuli (AB vs. CD; hand, and then experienced their exercise (mindfulness or re- EF vs. GH). For each participant, the stimuli used as the ele- laxation) or sat in the room for 10 min. They then returned ments (A, B, C, etc.) was constant throughout the experiment, twice for additional sessions, each 2 days after the preceding but the assignment of stimuli as these elements differed across the session, during which they experienced their assigned ex- participants to avoid any effects being the results of overall differences between the actual physical stimuli. Two separate ercise. Immediately after the exercise on the third session, the Mindfulness discrimination tasks were presented, as this has been shown to Test Phase Immediately after completing the training phase, induce higher levels of over-selectivity in non-clinical popu- the test phase instructions appeared on the screen. Participants lations than one such discrimination task alone (Reed and were instructed BPlease select one of the two pictures present- Gibson 2005). The two tasks were interspersed, so that com- ed. The computer will not tell you whether you are correct or pound stimulus AB appeared on the screen paired with com- incorrect.^ All participants were then presented with one stim- pound stimulus CD, intermixed with trials of EF paired with ulus from the previously reinforced compound (e.g., A or B; GH (see Fig. 1 to demonstrate an AB vs. CD trial). Trials from or E or F) paired with a stimulus from the previously punished each discrimination task (AB vs. CD and EF vs. GH) were compound (e.g., C or D; or G or H). Each combination (A vs. randomly intermixed. C, Avs. D, B vs. C, B vs. D, E vs. G, E vs. H, F vs. G, F vs. H) Participants selected one of the compounds when ‘Respond was presented five times. Thus, there were 40 trials in total. Now’ appeared on the screen by clicking the mouse cursor on Participants were required to select one of the stimuli using the one of the compounds. The ‘Respond Now’ instructions ap- mouse cursor. They were provided with no feedback, and each peared after the trial had been presented for 2 s. ‘Correct’ or trial appeared on the screen immediately after a response had ‘Incorrect’ then appeared on the screen immediately after a been given. Participants were given 1.5 s to respond, as in the response, and the next trial commenced. Thus, one compound training phase, and, if no response was made, then neither in each task (e.g., AB and EF) was always reinforced in the element was scored as having been selected (this never presence of the other compound (e.g., CD and GH) for that occurred). task. The positions of the stimuli were randomised, with the correct stimulus appearing on the left for approximately 50% Measures of the trials, and on the right for approximately 50% of the trials. If participants did not respond within 1.5 s (to keep the Autistic Spectrum Quotient Questionnaire AQ (Baron-Cohen length of each trial relatively constant), the next trial com- et al. 2001) measures levels of autism traits. The questionnaire menced, and the response was scored as incorrect. consists of 50 items. The test–retest reliability of the scale is Training continued until the participant selected each cor- .70 (Baron-Cohen et al. 2001), and the internal consistency rect compound consecutively five times (e.g., AB was select- (Cronbach α) is .82 (Austin 2005). There are sub-scales; how- ed five consecutive times, and EF was also selected five con- ever, there is some debate about the appropriate factor solution secutive times). Once five consecutive, correct trials had been for the AQ, and the reliabilities of the sub-scales are uncertain completed for one compound (e.g., AB vs. CD), trials for this (Austin 2005; Hurst et al. 2007). Given these concerns, only discrimination task ceased, and only trials for the remaining the overall AQ score was employed. task (e.g., EF vs. GH) continued until five consecutive correct responses for this task were also given. Hospital Anxiety and Depression Scale HADS (Zigmond and Snaith 1983) is a self-assessment questionnaire regarding levels of anxiety and depression. It contains seven items for anxiety and seven for depression over the past week. These scales give scores ranging from 0 to 21; 0–7= ‘normal’;8– 11 = ‘mild’;12–14 = ‘moderate’;and 15+ = ‘severe’.It has an internal reliability (α) of .84 for anxiety and .82 for depression (Bjelland et al. 2002). Toronto Mindfulness Scale Toronto mindful scale (Lau et al. 2006) consists of 13 statements about how participants feel towards their thoughts during a mindfulness session. The items are scored on a 5-point Likert scale (0–4; 0 = not at all in agreement; and 4 = very much in agreement. It has an in- ternal reliability (α) of .95 (Lau et al. 2006). Compound and Elemental Stimuli Stimuli used during the procedure included eight abstract pictorial symbols taken from various fonts from Microsoft Word 2010 (Wingdings, Wingdings 2 and Symbol). Stimuli were either presented as a compound for training or an elemental stimulus during test- Fig. 1 An example of the compound stimuli used during the training ing. Participants received different symbols for each stimulus phase, followed by an example of the elemental stimuli used during the testing phase to control for saliency effects. Additionally, the symbols have Mindfulness been successfully used in previous research using a sim- Results ilar over-selectivity paradigm with no evidence of differ- ing a-priori salience (e.g., Reed et al. 2012). In all phases, Table 1 shows the group-means for anxiety (HADS-A), de- each symbol appeared in black and measured approx. pression (HADS-D), and mindfulness (TMS), before and after 5cm×5cm(seeFig. 1). the interventions. These sample means are displayed for those participants who scored lower and higher in terms of their Data Analyses autism traits scores (AQ) in order to enable an initial analysis of the potential impact of autism traits on the effects of the The over-selectivity data were analysed in a number of interventions. For the initial analyses, the sample was split into ways. Initially, data were organised into the percentage lower and higher autism traits using a median split on the AQ of times that the most-selected and least-selected stimuli variable. This produced a set of lower scoring autism partici- were chosen during test. Two-way repeated-measures pants (n = 133, mean = 10.35 ± 2.71; range = 3–15), and a set analysis of variances (ANOVA) were performed on these of higher scoring autism quotients participants (n = 91, data with condition and stimulus type (most vs. least) as mean = 20.10 ± 4.43; range = 16–39). factors. It is reasonable to suggest that such an analysis Inspection of Table 1 for the anxiety scores shows that will tend to produce a difference between the most and participants with higher autism scores had greater levels of least-selected stimulus, and is not intended to show that anxiety than those who had lower autism scores. In neither there is over-selectivity per se, but that there is a differ- autism group did the control condition produce a strong re- ence in the relative amount of difference between the most duction in anxiety. There was, however, a reduction in anxiety and least-selected stimulus according to the condition. in both the relaxation and the mindfulness conditions, which However, recognition of potential problems in using the was greater in size for the higher autism group. A three-factor above analysis, has led to additional analysis of the data mixed-model analysis of variance (ANOVA) with interven- using binomial theory (Reynolds and Reed 2011). In this tion group and AQ group as between-subject factors, and anx- test, data were explored to test whether the distribution of iety before and after as a within-subject factor, was conducted the most and least-selected stimuli is statistically greater on these data and revealed no significant main effect of inter- than would be expected by random chance around an av- vention group, F(2,218) = 1.93, p = .148, η = .017[95% erage probability of selection of the two stimuli; thus, CI = .000–.060], but there were significant main effects of indicating whether the difference from this expected level AQ level, F(1,218) = 21.10, p <.001, η = .088[.029–.165], of choice differs from what would be expected if this were and anxiety before-after, F(1,218) = 131.33, p < .001, just random variation around a mean probability. In the η = .376[.279–.460]. There were significant interactions be- absence of any a priori method of assessing what the mean tween intervention group and anxiety before-after, F(2,218) = probability of choosing a stimulus is, the combined mean 54.61, p <.001, η = .334[.233–.418], AQ level and anxiety of choice for A and B at test was employed, and the dis- before- a fter , F (1, 218 ) = 43. 42, p < .00 1, crepancy from this mean tested according to binomial the- η = .166[.085–.253], but not intervention group and AQ ory. Only one discrepancy for each condition will be test- level, F <1, η = .005[.000–.038], but there was a significant ed, asthetwovalues(most-selected and least-selected) are three-way interaction, F(2,218) = 13.09, p < .001, symmetrical around the mean. η = .107[.038–.183]. Table 1 Mean (standard Control Relaxation Mindfulness deviation) for psychological variables before and after the Before After Before After Before After study for the lower and higher autism trait groups Lower AQ Anxiety 6.58 (2.67) 6.86 (2.67) 6.28 (2.81) 5.77 (2.97) 6.33 (3.19) 5.44 (3.23) Depression 3.00 (2.69) 3.21 (2.49) 4.27 (2.46) 4.22 (2.22) 3.47 (2.43) 3.53 (2.79) Mindfulness 24.63 (7.75) 24.72 (7.61) 25.33 (6.25) 25.69 (6.42) 24.20 (5.81) 35.51 (5.73) Higher AQ Anxiety 8.88 (3.66) 9.09 (4.07) 8.78 (4.21) 6.20 (4.05) 9.48 (4.08) 7.58 (4.38) Depression 3.91 (2.21) 5.69 (3.06) 4.59 (2.50) 6.55 (2.43) 5.65 (3.27) 5.69 (3.06) Mindfulness 22.52 (8.07) 20.27 (7.79) 22.83 (8.62) 22.66 (8.23) 23.03 (4.87) 22.76 (3.56) Mindfulness To further analyse the three-way interaction, separate two- significant main effects of anxiety before-after, F(1,88) = factor mixed-model ANOVAs (intervention group × anxiety 36.87, p < .001, η = .295[.145–.429], and intervention before-after) were conducted for each AQ level group, as rec- group, F(2,88) = 3.52, p <.05, η = .074[.000–.182], and a ommended by Howell (1997). For the lower AQ level group, significant interaction between the two factors, F(2,88) = this analysis revealed a significant main effect of anxiety be- 19.73, p <.001, η = .310[.149–.435]. Simple effect analyses fore-after, F(1,130) = 16.70, p <.001, η = .114[.031–.220], conducted on depression before-after for each intervention- but not of intervention group, F(2,130) = 1.04, p > .30, condition revealed no significant change for the control group, 2 2 η = .016[.000–.070]. There was a significant interaction F(1,88) = 3.27, p = .07, η = .034[.000–.137], a significant p p between the two factors, F(2,130) = 7.84, p < .001, increase in depression for relaxation, F(1,88) = 71.54, p 2 2 η = .108[.022–.206]. Simple effect analyses conducted on <.001, η = .449[.294–.563], and no change for mindfulness, p p anxiety before-after for each intervention-condition revealed F < 1 (.02), η = .001[.000–.009]. no significant change for the control group, F(1,130) = 2.98, Inspection of Table 1 for the mindfulness scores shows that, p >.30, η = .022[.000–.094], but significant reductions in for the lower autism group, the control and relaxation condi- anxiety for the relaxation, F(1,130) = 18.31, p < .001, tions did not produce a change in mindfulness, but there was an η = .124[.037–.231], and mindfulness, F(1,130) = 30.76, increase in mindfulness for the mindfulness condition. There p <.001, η = .191[.083–.305], groups. For the higher AQ was no increase in mindfulness for the higher autism group in level group, this analysis revealed a significant main effect of any of the conditions. A three-factor mixed-model ANOVA anxiety before-after, F(1,88) = 115.80, p < .001, (intervention group × AQ level × mindfulness before-after) η = .568[.429–.662], but not of intervention group, conducted on these data revealed significant main effects of F(2,88) = 1.15, p >.30, η = .025[.000–.105]. There was a intervention group, F(2,218) = 4.55, p < .05, significant interaction between the two factors, F(2,88) = η = .040[.002–.097], mindfulness before-after, F(1,218) = 2 2 41.98, p <.001, η = .488[.330–.591]. Simple effect analyses 129.00, p < .001, η = .391[.274–456], and AQ level, p p conducted on anxiety before-after for each intervention- F(1,218) = 22.03, p < .001, η = .092[.032–.169]. There were condition revealed no significant change for the control group, significant interactions between intervention group and mind- F <1, η = .011[.000–.087], but significant reductions in fulness before-after, F(2,218) = 251.82, p < .001, anxiety for the relaxation, F(1,88) = 120.89, p < .001, η = .698[.633–.743], AQ level and mindfulness before-after, 2 2 η = .579[.441–.670], and mindfulness, F(1,88) = 66.78, p F(1,218) = 355.19, p < .001, η = .620[.543–.677], but not in- p p <.001, η = .432[.276–.549], groups. tervention group and AQ level, F(2,218) = 2.06, p = .136, Inspection of Table 1 for the depression scores shows that η = .018[.000–.062], but there was a significant three-way participants with higher autism scores had slightly greater interaction, F(2,218) = 177.16, p < .001, η = .619[.541–.675]. levels of depression than those who had lower autism scores. A two-factor mixed-model ANOVA (intervention group × In neither autism group did any of the interventions produce a mindfulness before-after) conducted for the lower AQ level strong reduction in depression. A three-factor mixed-model group revealed significant main effects of mindfulness before- ANOVA (intervention group × AQ level × depression before after, F(1,130) = 880.52, p <.001, η = .871[.832–.896], in- and after) conducted on these data revealed a significant main tervention group, F(2,130) = 7.94, p < .001, effect of intervention group, F(2,218) = 5.32, p <.01, η = .109[.023–.201], and a significant interaction between η = .047[.005–.106], depression before-after, F(1,218) = the two factors, F(2,130) = 788.97, p < .001, 2 2 25.17, p < .001, η = .103[.039–.183], and AQ level, η = .924[.899–.938]. Simple effect analyses conducted on p p F(1,218) = 19.19, p <.001, η = .081[.025–.156]. There were mindfulness before-after for each intervention condition re- significant interactions between intervention group and de- vealed no significant change in mindfulness for the control pression before-after, F(2,218) = 9.52, p < .001, group, F < 1 (.16), η = .001[.000–.039], or the relaxation 2 2 η = .080[.021–.151], AQ level and depression before-after, group, F(1,130) = 2.41, p =.244, η = .018[.000–.086], but p p F(1,218) = 17.07, p <.001, η = .073[.020–.146], but not in- a significant increase in the mindfulness group, F(1,130) = tervention group and AQ level, F(2,218) = 1.04, p > .30, 2481.03, p <.001, η = .950[.934–.960]. For the higher AQ η = .009[.000–.043]. There was a significant three-way in- level group, this analysis revealed a significant main effect of teraction, F(2,218) = 13.61, p <.001, η = .111[.041–.188]. mindfulness before-after, F(1,88) = 13.77, p <.001, A two-factor mixed-model ANOVAs (intervention group × η = .135[.029–.268], but not of intervention group, F <1, depression before-after) conducted for the lower AQ level η = .006[.000–.077], but there was a significant interaction group revealed no significant main effect of depression be- between the two factors, F(2,88) = 8.11, p < .001, 2 2 fore-after, F <1, η = .004[.000–.049], or intervention group, η = .156[.034–.281]. Simple effect analyses conducted on p p F(2,130) = 2.49, p =.087, η = .037[.000–.109], nor interac- mindfulness before-after for each intervention-condition re- tion between the two factors, F <1, η = .006[.000–.039]. vealed a significant reduction for the control group, For the higher AQ level group, this analysis revealed F(1,88) = 33.72, p < .001, η = .277[.129–.411], but no p Mindfulness significant change for the relaxation group, F <1, groups (control, relaxation, and mindfulness) for the lower η = .002[.000–.056], or the mindfulness group, F <1, and higher autism participants in those groups. Inspection η = .005[.000–.071]. of these data reveals that there was a large differences be- tween the most- and least-selected stimuli in the control group for both the higher AQ and lower AQ groups. For Trials to Criterion During Discrimination Training the relaxation groups, there was a difference between the most- and least-selected stimulus for the lower scoring AQ Participants in the control group took a mean 18.01 (± 2.91) group, but not for the higher scoring AQ group. For the trials during training to reach the criterion for choosing AB mindfulness group, there was little most versus least dif- and EF, those in the relaxation group took 18.76 (± 4.16) trials, ference for either AQ group. and those in the mindfulness group took 17.72 (±2 .77) A three-factor mixed-model analysis of covariance trials. An ANOVA revealed no statistically significant (ANCOVA) with group and AQ as between-subject factors, main effect of group, F(1,221) = 1.91, p> .1, stimulus as a within-subject factor, and anxiety-, depression-, η = .008 [95%CI = .000–.048]. There were no signif- and mindfulness after as covariates (i.e., these scores at the icant correlations between trials to criterion and autism time of testing) was conducted on these data. This analysis quotient, r = − .035, p > .60; anxiety before, r = −.013, revealed a significant main effect of group, F(2,215) = 16.84, p > .80; anxiety after, r = −.006, p > .9; depression be- p <.001, η = .135[.056–.216], stimulus, F(1,215) = 17.51, fore, r = −.050, p > .40; depression after, r = −.089, p < .001, η = .075[.021–.150], but not AQ, F <1, p > .10; mindfulness before, r = .028, p > .60; or mind- η = .001[.000–.002]. There were significant interactions be- fulness after, r = .004, p > .60. tween group and AQ, F(2,215) = 10.26, p < .001, η = .087[.025–.160], stimulus and group, F(2,215) = Most vs. Least-Selected Elements During Test 68.82, p <.001, η = .390[.289–.471], but not stimulus and (Over-Selectivity) AQ, F <= 1, η = .001[.000–.068], but there was a signifi- cant three-way interaction, F(2,215) = 33.89, p < .001, The mean percentage times that the most-selected and least- η = .236[.144–.327]. selected stimuli were chosen from reinforced compounds AB To further analyse the three-way interaction, separate two- and EF during the test were calculated. The number of times factor ANCOVAs (AQ × stimulus, with depression, anxiety, that the individual elements of each previously reinforced el- and mindfulness—after as covariates) were conducted for ement (A or B and E and F) were calculated. The element that each group. For the control group this analysis revealed sig- was selected more times from each compound, was designat- nificant effects of AQ, F(1,71) = 12.56, p < .001, ed the ‘most-selected’ element; providing a most-selected η = .150[.029–.299], and stimulus, F(1,71) = 25.16, p (e.g., A) and least-selected stimulus (e.g., B) from AB, as well < .001, η = .262[.108–.410], and a significant interaction as a most-selected (e.g., E) and least-selected stimulus (e.g., F) between stimulus and AQ, F(1,71) = 18.62, p < .001, from EF. The mean most-selected (e.g., A and E) and least- η = .208[.063–.358]. Simple effect analyses conducted on selected (e.g., B and F) mean was then calculated. the most vs. least stimulus difference for the lower AQ group Figure 2 shows the group-mean percentage times that the revealed a significant difference, F(1,72) = 15.73, p < .001, most- and least-selected stimuli were chosen for the three η = .179[.046–.329], and a much greater difference for the higher scoring group, F(1,72) = 300.73, p < .001, 100 Most Least η = .808[.723–.854]. For the relaxation group this analysis revealed a significant effect of AQ, F(1,69) = 6.43, p <.05, η = .085[.003–.224], no significant main effect of stimulus, F <1, 60 η = .009[.000–.099], but a significant interaction between stimulus and AQ, F(1,69) = 15.88, p < .001, η = .187[.049–.340]. Simple effect analyses conducted on the most vs. least stimulus difference for the lower AQ group revealed a significant difference, F(1,72) = 115.78, p <.001, η = .617[.471–.707], and a much lower difference for the higher scoring group, F(1,72) = 15.73, p < .001, Mindful Relax Control Mindful Relax Control η = .179[.046–.329]. Low AQ High AQ For the mindfulness group this analysis revealed a signifi- cant main effect of stimulus, F(1,69) = 6.40, p <.05, Fig. 2 Percentage times most and least-selected elements were chosen for each group at test η = .085[.003–.224], but no significant effect of AQ, F < Percent mes selected Mindfulness 1, η = .001[.000–.085], or interaction between stimulus and over-selectivity) as the outcome, revealed a significant regres- 2 2 AQ, F (1,69) = 3.96, p >0.05, η = .054[.000–.182]. sion, − 2LL =66.00, X (4) = 25.72, p < .001. There was a sig- nificant negative relationships between autism quotient and Most vs. Least-Selected Elements During Test the presence of over-selectivity (odds ratio = .828, p < .05), (Over-Selectivity) and a significant positive relationship between anxiety (β = 1.273, p < .05), and mindfulness (β =1.139, p <.05), but not The analysis above will produce a numeric difference between between depression (odds ratio =.731, p =.194). the most- and least-selected stimuli, and this analysis will not show that there is over-selectivity per se. Given this consider- Mindfulness Group The criteria level for over-selectivity, cal- ation, further analysis of the data was undertaken, based on culated using the Reynolds/Reed methods (above), for this binomial theory, to determine whether the deviation in the group was 8.10, and a paired t test between the actual differ- times that the most-selected and least-selected stimuli were ences and this criterion value revealed no statistically signifi- chosen was statistically greater than would be expected by cant difference from chance, t(73) = 1.73, p >.08, d =.24,sug- random chance around an average probability of selection of gesting no over-selectivity was present. A logistic regression the two stimuli (Reynolds and Reed 2011). This analysis was also revealed no significant prediction by these variables to the undertaken to indicate whether the difference from the level of presence of over-selectivity, −2LL = 98.39, X (4) = 2.89, choice that would be expected if both stimuli had the same p >.50. probability of being chosen was statistically significant—i.e., whether there was absolute over-selectivity, as opposed to relative differences in stimulus selection. Paired t tests were then used to test this sum against the obtained data, in order to Discussion investigate whether significant over-selectivity occurred in each of the groups. The results demonstrated that without any form of interven- tion (mindfulness or relaxation), participants with higher Control Group The criteria level for over-selectivity, calculat- levels of autism traits demonstrated greater over-selectivity ed using the Reynolds/Reed methods (above), for this group than those with lower autism and anxiety scores. This finding was 18.23, and a paired t test between the actual differences is novel with respect to AQ scores, but is consistent with and this criterion value revealed a statistically significant dif- previous findings for those with ASD (Kelly et al. 2015; ference from chance, t(75) = 5.51, p <.001, d =.63, suggest- Leader et al. 2009), and also replicates previous findings that ing over-selectivity occurred for this group. Participants were have shown greater levels of anxiety or stress associated with categorised into those who demonstrated over-selectivity (i.e., over-selective responding (Groden et al. 2005). The finding had a difference score of greater than the criterion value) and that those with higher AQ scores perform similarly to those those who did not. A logistic regression was conducted with with clinical-ASD also extend the suggestion that ASD could anxiety (HADS-A), depression (HADS-D), mindfulness be regarded as a broad phenotype with traits distributed across (TMS) after the intervention, and the AQ scores, as predictors, the population (Couteur et al. 1996;Reed etal. 2011). and the binary categorisation (0 = no over-selectivity; 1 = The mindfulness intervention removed a tendency to over- over-selectivity) as the outcome. This revealed a significant select, and did so independently of the level of AQ displayed regression, −2LL =61.54, X (4) = 28.06, p <.001. Therewere by the participants. This suggests that mindfulness may well significant relationships between the autism quotient and pres- be a useful intervention in this regard, and further substantiates ence of over-selectivity, with more autism traits meaning a previous findings that have shown its effectiveness for some greater chance of over-selectivity (odds ratio = 1.444, p populations (Hofmann and Gómez 2017). This also suggests < .001), but not between the presence of over-selectivity and that mindfulness may be effective in dealing with some of the anxiety (odds ratio =.923, p > .50), depression (odds ratio = core symptoms of ASD. However, the current results also 1.064, p > .60), or mindfulness (odds ratio =1.080, p =.074). suggest that the mechanisms through which such a mind- fulness intervention works could differ between those with Relaxation Group The criteria level for over-selectivity, calcu- lower and higher levels of autism traits. Considering the lated using the Reynolds/Reed methods (above), for this data from the lower scoring AQ participants, it is apparent group was 15.78, and a paired t test between the actual differ- that the mindfulness intervention worked much more ef- ences and this criterion value revealed no statistically signifi- fectively than the relaxation (unfocused attention) inter- cant difference from chance, t <1, d = .02,suggestingnoover- vention in terms of reducing over-selective responding. all level of over-selectivity for this group. A logistic regres- This is in line with previous studies that have compared sion, conducted with the psychological variables as predictors, mindfulness with relaxation for a population without ASD and the binary categorisation (0 = no over-selectivity; 1 = (Arch and Craske 2006;McHugh et al. 2010). Mindfulness In contrast, for the participants with higher AQ scores, it is period than might be given in a clinical context. However, that apparent that there was little difference between the impact of brief interventions of a similar length have been successful in the mindfulness and the relaxation interventions, and both reducing clinically relevant symptoms (Arch and Craske 2006), produced less over-selectivity than the control condition. and that even shorter mindful interventions have been success- This is a novel finding with respect to the impact of mind- ful in reducing over-selectivity in other populations (McHugh fulness on over-selectivity—where in other groups mind- et al. 2010), suggests that time-alone is not a key factor in the fulness has produced a stronger reduction in over- impact of mindful interventions. None of the participants were selectivity than relaxation (Arch and Craske 2006). It is drawn from a clinical population (in so far as they failed to also novel with respect to the impact of mindfulness on a report any current or previous psychiatric problems). This population with higher levels of ASD traits. Previous stud- might mean that the current results may not generalise to those ies of this latter group often have lacked such a relaxation populations —this will require further exploration. However, control (de Bruin et al. 2015; Singh et al. 2011). Although it mindfulness has been suggested as an important approach to has been shown that mindfulness works for a group with tackle many non-clinical problems,and,tothisextent, thecur- ASD, especially with regard to ritualistic behaviours (de rent results are directly relevant. Finally, the degree to which Bruin et al. 2015;Kiepet al. 2015), it has not been shown these findings would generalise to populations with other cog- that this effect is due to the specific effects of mindfulness, nitive or emotional problems, or who receive longer duration or rather than to the possible effects of relaxation. greater numbers of mindfulness sessions, is also uncertain. Thus, the current results suggest that mindfulness may well In summary, the current study demonstrated that over- be beneficial with regard to reducing an over-focused atten- selective responding is associated with higher levels of AQ tion in those with lower and higher levels of autism traits, but and anxiety, and that it can be reduced by mindfulness inter- that it may well work through different mechanisms in each ventions. However, it is unclear whether these mindfulness case. The precise mechanisms of this action will require fur- interventions impact over-selectivity through the same mech- ther exploration. However, some tentative suggestions may be anisms in those with lower and higher levels of autism traits. It made on the bases of these data. Mindfulness reduced over- seems that mindfulness may initially act to reduce anxiety selectivity, better than relaxation, for the lower scoring AQ levels which are associated with over-selectivity, and then participants. This latter group showed higher levels of mind- exert a more specific effect on attention. fulness after the mindful intervention than the other two inter- vention groups. Together, these findings suggest a specific Compliance with Ethical Standards mindful mechanism for these participants. Conflict of Interest The author declare that they have no conflicts of That those with higher levels of AQ showed no differential interest. over-selectivity reduction in the mindfulness compared to the relaxation treatment, and also showed no higher levels of Ethics Statement Ethical approval for this research was given by the mindfulness after the mindfulness intervention than after the Department of Psychology, Swansea University, Ethics Committee. other interventions, suggests that the relaxation induced by the mindfulness condition may have been the key component of Informed Consent Statement All participants were given information about the study, told that they could withdraw at any point without giving action for this group. That anxiety levels were higher in the a reason, and signed a consent form after receiving this information. higher AQ participants, might also suggest that this aspect was exerting a strong effect on their over-selectivity performance Open Access This article is distributed under the terms of the Creative (Groden et al. 2005), and that any intervention that reduces Commons Attribution 4.0 International License (http:// creativecommons.org/licenses/by/4.0/), which permits unrestricted use, anxiety may help this group to reduce over-selective attention- distribution, and reproduction in any medium, provided you give appro- al responses (see also Maisel et al. 2016, for a similar priate credit to the original author(s) and the source, provide a link to the discussion). Indeed, anxiety has been shown to be reduced Creative Commons license, and indicate if changes were made. in groups with ASD traits (MacNeil et al. 2009). 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Mechanisms of Mindfulness in Those with Higher and Lower Levels of Autism Traits

Mindfulness , Volume OnlineFirst – Jun 1, 2018
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Psychology; Cognitive Psychology; Pediatrics; Child and School Psychology; Psychology, general; Public Health; Social Sciences, general
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1868-8527
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10.1007/s12671-018-0964-6
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Abstract

The effects of brief mindfulness induction on a central trait of autism spectrum disorder (over-selective attention) were examined in order to assess whether different mechanisms act in those with lower and higher levels of autism traits, and determine which intervention may be most appropriate for individuals with different sets of symptoms. Two hundred and 24 volunteer participants (110 male; 114 female) were assessed for levels of autism traits (autism quotient; AQ), anxiety and depression (Hospital Anxiety and Depression Scales), and mindful awareness (Toronto Mindfulness Scale). They were randomly assigned to mindfulness, relaxation, or no-intervention groups. After three 10-min sessions, held on alternate days, participants underwent simultaneous discrimination training between two two-element compound stimuli (AB+ CD−), followed by an extinction test (AvC, AvD, BvC, BvD) to determine the amount of over-selectivity present. Levels of depression, anxiety, and mindfulness were re-assessed. Participants with greater autism traits demonstrated greater over-selectivity, than those with lower autism traits. Mindfulness reduced over-selectivity, and did so independently of the level of AQ displayed by the participants. For lower scoring AQ participants, mindfulness worked more effectively than relaxation. In contrast, for participants with higher AQ scores, there was little difference between the impact of mindfulness and relaxation. The latter group displayed no improvement in mindful awareness. Mindfulness induction can be effective, but may work through different mechanisms for those with higher and lower autism traits, and consideration should be given as to whether this intervention may be the most suitable in all cases where autism traits are present. . . . . . Keywords Mindfulness Brief-induction Over-selectivity Autism quotient Anxiety Relaxation Mindfulness has been suggested as an intervention beneficial problems (Zeidan et al. 2010) and attentional difficulties for a range of emotional problems, such as depression (McHugh et al. 2010). (Hofmann and Gómez 2017;Spek et al. 2013; Winnebeck et However, there are also suggestions that the widespread al. 2017) and anxiety (Hoge et al. 2017; Hofmann and Gómez usage of mindful techniques may not be fully supported by 2017;Kiep et al. 2015); as well as improving aspects of cog- the literature (Van Dam et al. 2018). In some cases, this is nitive functioning, such as attention (Chesin et al. 2016; claimed because mindfulness may be less effective than Morrison and Jha 2015) and memory (Zeidan et al. 2010). other available treatment procedures for some subsets of a Positive impacts have been claimed for a range of populations, population (see Arch and Ayers 2013, for a discussion). In including individuals with clinical problems (see Cachia et al. other cases, because mindfulness may be actually damaging 2016, Hofmann and Gómez 2017, for reviews), and those with to the individuals (Briggs and Killen 2013). Importantly for problems of a non-clinical nature who are affected by issues, clinical practice, these concerns arise, in part, as it is not such as performance or test anxiety (Cho et al. 2016), memory fully established which populations may be able to benefit from mindful techniques (Arch and Ayers 2013;Van Dam et al. 2018). Similarly, it is not established precisely how mindful techniques produce their effects, and it is far from * Phil Reed clear that mindfulness works through the same mechanism p.reed@swansea.ac.uk for different groups of individuals. This latter consideration is also important for clinical practice, as understanding the Department of Psychology, Swansea University, Singleton Park, mechanisms of action of any intervention can help to Swansea SA2 8PP, UK Mindfulness develop and refine that intervention and tailor it for usage in Lee and Orsillo (2014) noted that both mindfulness and relax- particular cases. ation produced improvements with an emotional Stroop task One set of individuals who have received contemporary compared to a control group. Indeed, it may be important that research effort with regard to the effectiveness of mindful- mindfulness sometimes does not work as well as other forms ness, and who straddle both the clinical and non-clinical of talking therapy for those with high levels of anxiety (Arch population, is those scoring high in autism traits (Cachia et and Ayers 2013), although the degree to which this finding al. 2016; Higuchi et al. 2017; Singh et al. 2011). A number generalises across functioning areas and populations is not of reports have suggested that mindfulness does impact clear (cf. Arch and Craske 2006). beneficially on this population along some dimensions of This lack of evidence for the specific impact of mindful- their functioning (Kiep et al. 2015;Speketal. 2013). ness in a population with high-functioning ASD, including Current evidence is suggestive for a positive impact on those scoring high on autism traits but without a formal clin- reducing rumination (de Bruin et al. 2015;Kiepetal. ical diagnosis (i.e., those high on the broad autistic pheno- 2015) and anxiety (Spek et al. 2013; see Cachia et al. type), contrasts with a range of studies for other populations 2016, for a review). However, the picture with regard to that have shown an impact of mindfulness relative to relaxa- other emotional problems associated with this population tion. For example, Arch and Craske (2006)demonstrated a is not so clear(seedeBruin et al. 2015;Speketal. 2013). positive impact of a brief mindfulness training programme Importantly, it has not been established which, if any, of the on anxiety, over and above the effects of relaxation, for a many of the central cognitive aspects of autism apectrum dis- group with anxiety disorder. Similarly, McHugh et al. (2010) order (ASD), such as attentional problems, are helped by noted greater improvements in performance on an attentional mindfulness (see de Bruin et al. 2015). Neither has it been over-selectivity task for older individuals. Over-selectivity oc- established, whether any such impacts are actually a direct curs when one aspect of the environment controls behaviour at effect of mindfulness or due to its impact on other areas of the expense of other equally salient and/or important aspects functioning, such as anxiety, which then helps with the symp- of the environment (see Dube 2009; Kelly et al. 2015). This toms under investigation (cf. Maisel et al. 2016, for a related latter task may be of particular importance to the ASD popu- discussion). While emotional problems, such as anxiety and lation, as they are known to display very high levels of over- depression, are clearly important issues for those with higher selectivity and narrowed attention (Kelly et al. 2015). functioning ASD (Posserud et al. 2016;Reed 2016), and those Thus, it may be that mindfulness produces benefits with high levels of autism traits who are non-clinical (Reed et across a range of populations, but may do so through al. 2016; Towbin et al. 2005), they are not a diagnostic criteria different mechanisms. In those with lower anxiety levels, for ASD (DSM-5; APA 2013). mindfulness may impact directly on a range of cognitive A further difficulty about making judgments about the im- and emotional domains (Zeidan et al. 2010). However, for pact of mindfulness for those with high levels of autism traits those with higher anxiety, which may include those with is that many reports do not include control groups to isolate high-functioning ASD (MacNeil et al. 2009), mindfulness specific effects of mindfulness, relative to other nonspecific may work to reduce anxiety through some nonspecific aspects of a very complex intervention (e.g., relaxation). For aspect of the intervention, and this impacts levels of func- example, both de Bruin et al. (2015), and Singh et al. (2011), tioning (Lee and Orsillo 2014;Maiselet al. 2016). had only a before and after measure of rumination, and Spek et Certainly, in terms of over-selectivity, it is known that al. (2013) compared a group with mindfulness to a waiting list increasing levels of cognitive (Groden et al. 1994)and control. Given the impact of mindfulness on anxiety-related psychological (Reed and Gibson 2005) stress increases issues for ASD (de Bruin et al. 2015;Kiepetal. 2015; Spek et over-selectivity responding. Given this, a reduction in al. 2013) and the relatively high levels of anxiety reported by anxiety may serve to reduce over-selective attention— those with high-functioning ASD (MacNeil et al. 2009; Reed and it may be that this reduced anxiety, rather than some 2016), it is unclear whether mindfulness has its impact specific mindful mechanism is responsible for improve- through specific mindfulness-related mechanisms or through ments in performance. some of the associated nonspecific process involved, like re- The current study aimed to explore these possibilities with laxation (see Arch and Craske 2006; Maiseletal. 2016;Van regard to the impact of mindfulness on over-selective atten- Dam et al. 2018). tion. The level of autism traits was measured in a volunteer Research with individuals with ASD has not reported uni- sample, along with their levels of anxiety, depression, and versally positive results in regard to the mindful-specific mindfulness before and after a brief mindfulness intervention mechanisms responsible for improvements produced through (modelled on that employed by Arch and Craske 2006). Based mindfulness interventions. Although de Bruin et al. (2015) on previous literature, it was predicted that mindfulness would reported a reduction in rumination after mindfulness training, reduce over-selective responding in those with lower autism they noted no greater mindful awareness in those participants. traits, compared to relaxation and a no-intervention control, Mindfulness but both relaxation and mindfulness would work to reduce participants were presented with the experimental procedure over-selectivity in those with higher autism traits. It was also via a Dell Latitude E6540 laptop (display size: 15.5″), pro- predicted that mindful awareness would not increase after the grammed in E-Prime®. After this, they completed the HADS mindfulness intervention in the group with higher autism traits and TMS again. as much as in the former groups, but anxiety (being higher to start with) would reduce in the relaxation and mindfulness Interventions There were two separate exercises—arelaxation interventions for those with higher autism traits. This pattern (unfocused attention) induction (relaxation) and a focused at- of results would suggest that mindfulness works through dif- tention induction (mindfulness) that were based on the exer- ferent mechanisms for different groups of individuals. cises used by Arch and Craske (2006), and which have been shown to remediate over-selectivity in non-clinical popula- tions (McHugh et al. 2010). Each exercise was delivered by Method a recording of a female voice, who was clinically qualified, and lasted 10 min. Participants experienced three sessions of Participants their allotted exercise, each separated from one another by 1 day, making the study last 5 days in total. This procedure Two hundred and 24 volunteer adult participants (110 male; was based on the brief-mindfulness intervention constructed 114 female) were recruited from the general public and uni- by Lee and Orsillo (2014) for cognitive flexibility. The exer- versity students. The study adopted an exclusion criterion of cises were completed alone by the participants while sitting in anybody currently or previously in receipt of a diagnosis or a dimly lit small room, and they were encouraged to practice treatment for a psychological problem, including ASD, which the exercises at home in between the sessions. was specified on the advert for the study, and through self- report at the start of the study. No payment or course-credit Mindfulness (Focused Attention) Induction The instructions was given to the participants. Participants had a mean age of for the mindfulness induction were BFocus your attention on 24.50 (± 6.02 SD; range = 18 to 49) years. Participants under your breathing. Notice the sensation of breathing air in. the age of 18 years were excluded for ethical reasons, and Notice the sensation of breathing air out. As you breathe air those over the age of 55 years were excluded on the basis of into your body, fill your mind with the thought ‘just this one previous research showing different levels of over-selectivity breath’. As you breathe air out of your body, fill your mind occurs in older individuals (McHugh and Reed 2007). with the thought ‘just this one exhale.^ Whenever any other Participants who had a history of self-reported psychiatric thoughts came into the participants’ minds, they were problems were excluded, as were those who reported that they instructed to try and push them aside, and continue to focus only on their breathing patterns. had previously engaged in meditation or mindfulness tech- niques, as pilot studies had shown that previous meditational experience overwhelms any experimental manipulations. A Relaxation (Unfocused Attention) Induction The participant priori power analysis (G*Power; Faul et al. 2007) for the instructions for the exercise were BLet your mind wander free- overall analysis of variance (ANOVA) indicated that this ly amongst thoughts about past and present future events. was sufficient sample size to detect medium effect sizes. Start by allowing your mind to roam. Don’t try to focus on Ethical approval was given by the Ethics Committee of the your thoughts; just let them drift without hesitation. There is University Psychology Department in which this research was no need to focus on anything in particular. Allow yourself to conducted, and all participants gave fully informed consent to think freely. Try not to focus on any one thing. Just let your their participation. mind wander.^ Procedure Experimental Training Phase Training commenced with the instructions BPlease select one of the two stimuli presented Participants were randomly assigned to one of three groups: as soon as ‘respond now’ appears on the screen. You will be mindfulness (n =74), relaxation (n = 74) and control (n =76). given feedback indicating whether you selected the correct or Each participant completed all parts of the study separately, in incorrect stimulus. Your aim is to select the correct stimulus.^ a small, quiet, dimly lit experimental room. During the first All participants were then presented with two simple discrim- session, participants completed the AQ, HADS and TMS by ination tasks consisting of the compound stimuli (AB vs. CD; hand, and then experienced their exercise (mindfulness or re- EF vs. GH). For each participant, the stimuli used as the ele- laxation) or sat in the room for 10 min. They then returned ments (A, B, C, etc.) was constant throughout the experiment, twice for additional sessions, each 2 days after the preceding but the assignment of stimuli as these elements differed across the session, during which they experienced their assigned ex- participants to avoid any effects being the results of overall differences between the actual physical stimuli. Two separate ercise. Immediately after the exercise on the third session, the Mindfulness discrimination tasks were presented, as this has been shown to Test Phase Immediately after completing the training phase, induce higher levels of over-selectivity in non-clinical popu- the test phase instructions appeared on the screen. Participants lations than one such discrimination task alone (Reed and were instructed BPlease select one of the two pictures present- Gibson 2005). The two tasks were interspersed, so that com- ed. The computer will not tell you whether you are correct or pound stimulus AB appeared on the screen paired with com- incorrect.^ All participants were then presented with one stim- pound stimulus CD, intermixed with trials of EF paired with ulus from the previously reinforced compound (e.g., A or B; GH (see Fig. 1 to demonstrate an AB vs. CD trial). Trials from or E or F) paired with a stimulus from the previously punished each discrimination task (AB vs. CD and EF vs. GH) were compound (e.g., C or D; or G or H). Each combination (A vs. randomly intermixed. C, Avs. D, B vs. C, B vs. D, E vs. G, E vs. H, F vs. G, F vs. H) Participants selected one of the compounds when ‘Respond was presented five times. Thus, there were 40 trials in total. Now’ appeared on the screen by clicking the mouse cursor on Participants were required to select one of the stimuli using the one of the compounds. The ‘Respond Now’ instructions ap- mouse cursor. They were provided with no feedback, and each peared after the trial had been presented for 2 s. ‘Correct’ or trial appeared on the screen immediately after a response had ‘Incorrect’ then appeared on the screen immediately after a been given. Participants were given 1.5 s to respond, as in the response, and the next trial commenced. Thus, one compound training phase, and, if no response was made, then neither in each task (e.g., AB and EF) was always reinforced in the element was scored as having been selected (this never presence of the other compound (e.g., CD and GH) for that occurred). task. The positions of the stimuli were randomised, with the correct stimulus appearing on the left for approximately 50% Measures of the trials, and on the right for approximately 50% of the trials. If participants did not respond within 1.5 s (to keep the Autistic Spectrum Quotient Questionnaire AQ (Baron-Cohen length of each trial relatively constant), the next trial com- et al. 2001) measures levels of autism traits. The questionnaire menced, and the response was scored as incorrect. consists of 50 items. The test–retest reliability of the scale is Training continued until the participant selected each cor- .70 (Baron-Cohen et al. 2001), and the internal consistency rect compound consecutively five times (e.g., AB was select- (Cronbach α) is .82 (Austin 2005). There are sub-scales; how- ed five consecutive times, and EF was also selected five con- ever, there is some debate about the appropriate factor solution secutive times). Once five consecutive, correct trials had been for the AQ, and the reliabilities of the sub-scales are uncertain completed for one compound (e.g., AB vs. CD), trials for this (Austin 2005; Hurst et al. 2007). Given these concerns, only discrimination task ceased, and only trials for the remaining the overall AQ score was employed. task (e.g., EF vs. GH) continued until five consecutive correct responses for this task were also given. Hospital Anxiety and Depression Scale HADS (Zigmond and Snaith 1983) is a self-assessment questionnaire regarding levels of anxiety and depression. It contains seven items for anxiety and seven for depression over the past week. These scales give scores ranging from 0 to 21; 0–7= ‘normal’;8– 11 = ‘mild’;12–14 = ‘moderate’;and 15+ = ‘severe’.It has an internal reliability (α) of .84 for anxiety and .82 for depression (Bjelland et al. 2002). Toronto Mindfulness Scale Toronto mindful scale (Lau et al. 2006) consists of 13 statements about how participants feel towards their thoughts during a mindfulness session. The items are scored on a 5-point Likert scale (0–4; 0 = not at all in agreement; and 4 = very much in agreement. It has an in- ternal reliability (α) of .95 (Lau et al. 2006). Compound and Elemental Stimuli Stimuli used during the procedure included eight abstract pictorial symbols taken from various fonts from Microsoft Word 2010 (Wingdings, Wingdings 2 and Symbol). Stimuli were either presented as a compound for training or an elemental stimulus during test- Fig. 1 An example of the compound stimuli used during the training ing. Participants received different symbols for each stimulus phase, followed by an example of the elemental stimuli used during the testing phase to control for saliency effects. Additionally, the symbols have Mindfulness been successfully used in previous research using a sim- Results ilar over-selectivity paradigm with no evidence of differ- ing a-priori salience (e.g., Reed et al. 2012). In all phases, Table 1 shows the group-means for anxiety (HADS-A), de- each symbol appeared in black and measured approx. pression (HADS-D), and mindfulness (TMS), before and after 5cm×5cm(seeFig. 1). the interventions. These sample means are displayed for those participants who scored lower and higher in terms of their Data Analyses autism traits scores (AQ) in order to enable an initial analysis of the potential impact of autism traits on the effects of the The over-selectivity data were analysed in a number of interventions. For the initial analyses, the sample was split into ways. Initially, data were organised into the percentage lower and higher autism traits using a median split on the AQ of times that the most-selected and least-selected stimuli variable. This produced a set of lower scoring autism partici- were chosen during test. Two-way repeated-measures pants (n = 133, mean = 10.35 ± 2.71; range = 3–15), and a set analysis of variances (ANOVA) were performed on these of higher scoring autism quotients participants (n = 91, data with condition and stimulus type (most vs. least) as mean = 20.10 ± 4.43; range = 16–39). factors. It is reasonable to suggest that such an analysis Inspection of Table 1 for the anxiety scores shows that will tend to produce a difference between the most and participants with higher autism scores had greater levels of least-selected stimulus, and is not intended to show that anxiety than those who had lower autism scores. In neither there is over-selectivity per se, but that there is a differ- autism group did the control condition produce a strong re- ence in the relative amount of difference between the most duction in anxiety. There was, however, a reduction in anxiety and least-selected stimulus according to the condition. in both the relaxation and the mindfulness conditions, which However, recognition of potential problems in using the was greater in size for the higher autism group. A three-factor above analysis, has led to additional analysis of the data mixed-model analysis of variance (ANOVA) with interven- using binomial theory (Reynolds and Reed 2011). In this tion group and AQ group as between-subject factors, and anx- test, data were explored to test whether the distribution of iety before and after as a within-subject factor, was conducted the most and least-selected stimuli is statistically greater on these data and revealed no significant main effect of inter- than would be expected by random chance around an av- vention group, F(2,218) = 1.93, p = .148, η = .017[95% erage probability of selection of the two stimuli; thus, CI = .000–.060], but there were significant main effects of indicating whether the difference from this expected level AQ level, F(1,218) = 21.10, p <.001, η = .088[.029–.165], of choice differs from what would be expected if this were and anxiety before-after, F(1,218) = 131.33, p < .001, just random variation around a mean probability. In the η = .376[.279–.460]. There were significant interactions be- absence of any a priori method of assessing what the mean tween intervention group and anxiety before-after, F(2,218) = probability of choosing a stimulus is, the combined mean 54.61, p <.001, η = .334[.233–.418], AQ level and anxiety of choice for A and B at test was employed, and the dis- before- a fter , F (1, 218 ) = 43. 42, p < .00 1, crepancy from this mean tested according to binomial the- η = .166[.085–.253], but not intervention group and AQ ory. Only one discrepancy for each condition will be test- level, F <1, η = .005[.000–.038], but there was a significant ed, asthetwovalues(most-selected and least-selected) are three-way interaction, F(2,218) = 13.09, p < .001, symmetrical around the mean. η = .107[.038–.183]. Table 1 Mean (standard Control Relaxation Mindfulness deviation) for psychological variables before and after the Before After Before After Before After study for the lower and higher autism trait groups Lower AQ Anxiety 6.58 (2.67) 6.86 (2.67) 6.28 (2.81) 5.77 (2.97) 6.33 (3.19) 5.44 (3.23) Depression 3.00 (2.69) 3.21 (2.49) 4.27 (2.46) 4.22 (2.22) 3.47 (2.43) 3.53 (2.79) Mindfulness 24.63 (7.75) 24.72 (7.61) 25.33 (6.25) 25.69 (6.42) 24.20 (5.81) 35.51 (5.73) Higher AQ Anxiety 8.88 (3.66) 9.09 (4.07) 8.78 (4.21) 6.20 (4.05) 9.48 (4.08) 7.58 (4.38) Depression 3.91 (2.21) 5.69 (3.06) 4.59 (2.50) 6.55 (2.43) 5.65 (3.27) 5.69 (3.06) Mindfulness 22.52 (8.07) 20.27 (7.79) 22.83 (8.62) 22.66 (8.23) 23.03 (4.87) 22.76 (3.56) Mindfulness To further analyse the three-way interaction, separate two- significant main effects of anxiety before-after, F(1,88) = factor mixed-model ANOVAs (intervention group × anxiety 36.87, p < .001, η = .295[.145–.429], and intervention before-after) were conducted for each AQ level group, as rec- group, F(2,88) = 3.52, p <.05, η = .074[.000–.182], and a ommended by Howell (1997). For the lower AQ level group, significant interaction between the two factors, F(2,88) = this analysis revealed a significant main effect of anxiety be- 19.73, p <.001, η = .310[.149–.435]. Simple effect analyses fore-after, F(1,130) = 16.70, p <.001, η = .114[.031–.220], conducted on depression before-after for each intervention- but not of intervention group, F(2,130) = 1.04, p > .30, condition revealed no significant change for the control group, 2 2 η = .016[.000–.070]. There was a significant interaction F(1,88) = 3.27, p = .07, η = .034[.000–.137], a significant p p between the two factors, F(2,130) = 7.84, p < .001, increase in depression for relaxation, F(1,88) = 71.54, p 2 2 η = .108[.022–.206]. Simple effect analyses conducted on <.001, η = .449[.294–.563], and no change for mindfulness, p p anxiety before-after for each intervention-condition revealed F < 1 (.02), η = .001[.000–.009]. no significant change for the control group, F(1,130) = 2.98, Inspection of Table 1 for the mindfulness scores shows that, p >.30, η = .022[.000–.094], but significant reductions in for the lower autism group, the control and relaxation condi- anxiety for the relaxation, F(1,130) = 18.31, p < .001, tions did not produce a change in mindfulness, but there was an η = .124[.037–.231], and mindfulness, F(1,130) = 30.76, increase in mindfulness for the mindfulness condition. There p <.001, η = .191[.083–.305], groups. For the higher AQ was no increase in mindfulness for the higher autism group in level group, this analysis revealed a significant main effect of any of the conditions. A three-factor mixed-model ANOVA anxiety before-after, F(1,88) = 115.80, p < .001, (intervention group × AQ level × mindfulness before-after) η = .568[.429–.662], but not of intervention group, conducted on these data revealed significant main effects of F(2,88) = 1.15, p >.30, η = .025[.000–.105]. There was a intervention group, F(2,218) = 4.55, p < .05, significant interaction between the two factors, F(2,88) = η = .040[.002–.097], mindfulness before-after, F(1,218) = 2 2 41.98, p <.001, η = .488[.330–.591]. Simple effect analyses 129.00, p < .001, η = .391[.274–456], and AQ level, p p conducted on anxiety before-after for each intervention- F(1,218) = 22.03, p < .001, η = .092[.032–.169]. There were condition revealed no significant change for the control group, significant interactions between intervention group and mind- F <1, η = .011[.000–.087], but significant reductions in fulness before-after, F(2,218) = 251.82, p < .001, anxiety for the relaxation, F(1,88) = 120.89, p < .001, η = .698[.633–.743], AQ level and mindfulness before-after, 2 2 η = .579[.441–.670], and mindfulness, F(1,88) = 66.78, p F(1,218) = 355.19, p < .001, η = .620[.543–.677], but not in- p p <.001, η = .432[.276–.549], groups. tervention group and AQ level, F(2,218) = 2.06, p = .136, Inspection of Table 1 for the depression scores shows that η = .018[.000–.062], but there was a significant three-way participants with higher autism scores had slightly greater interaction, F(2,218) = 177.16, p < .001, η = .619[.541–.675]. levels of depression than those who had lower autism scores. A two-factor mixed-model ANOVA (intervention group × In neither autism group did any of the interventions produce a mindfulness before-after) conducted for the lower AQ level strong reduction in depression. A three-factor mixed-model group revealed significant main effects of mindfulness before- ANOVA (intervention group × AQ level × depression before after, F(1,130) = 880.52, p <.001, η = .871[.832–.896], in- and after) conducted on these data revealed a significant main tervention group, F(2,130) = 7.94, p < .001, effect of intervention group, F(2,218) = 5.32, p <.01, η = .109[.023–.201], and a significant interaction between η = .047[.005–.106], depression before-after, F(1,218) = the two factors, F(2,130) = 788.97, p < .001, 2 2 25.17, p < .001, η = .103[.039–.183], and AQ level, η = .924[.899–.938]. Simple effect analyses conducted on p p F(1,218) = 19.19, p <.001, η = .081[.025–.156]. There were mindfulness before-after for each intervention condition re- significant interactions between intervention group and de- vealed no significant change in mindfulness for the control pression before-after, F(2,218) = 9.52, p < .001, group, F < 1 (.16), η = .001[.000–.039], or the relaxation 2 2 η = .080[.021–.151], AQ level and depression before-after, group, F(1,130) = 2.41, p =.244, η = .018[.000–.086], but p p F(1,218) = 17.07, p <.001, η = .073[.020–.146], but not in- a significant increase in the mindfulness group, F(1,130) = tervention group and AQ level, F(2,218) = 1.04, p > .30, 2481.03, p <.001, η = .950[.934–.960]. For the higher AQ η = .009[.000–.043]. There was a significant three-way in- level group, this analysis revealed a significant main effect of teraction, F(2,218) = 13.61, p <.001, η = .111[.041–.188]. mindfulness before-after, F(1,88) = 13.77, p <.001, A two-factor mixed-model ANOVAs (intervention group × η = .135[.029–.268], but not of intervention group, F <1, depression before-after) conducted for the lower AQ level η = .006[.000–.077], but there was a significant interaction group revealed no significant main effect of depression be- between the two factors, F(2,88) = 8.11, p < .001, 2 2 fore-after, F <1, η = .004[.000–.049], or intervention group, η = .156[.034–.281]. Simple effect analyses conducted on p p F(2,130) = 2.49, p =.087, η = .037[.000–.109], nor interac- mindfulness before-after for each intervention-condition re- tion between the two factors, F <1, η = .006[.000–.039]. vealed a significant reduction for the control group, For the higher AQ level group, this analysis revealed F(1,88) = 33.72, p < .001, η = .277[.129–.411], but no p Mindfulness significant change for the relaxation group, F <1, groups (control, relaxation, and mindfulness) for the lower η = .002[.000–.056], or the mindfulness group, F <1, and higher autism participants in those groups. Inspection η = .005[.000–.071]. of these data reveals that there was a large differences be- tween the most- and least-selected stimuli in the control group for both the higher AQ and lower AQ groups. For Trials to Criterion During Discrimination Training the relaxation groups, there was a difference between the most- and least-selected stimulus for the lower scoring AQ Participants in the control group took a mean 18.01 (± 2.91) group, but not for the higher scoring AQ group. For the trials during training to reach the criterion for choosing AB mindfulness group, there was little most versus least dif- and EF, those in the relaxation group took 18.76 (± 4.16) trials, ference for either AQ group. and those in the mindfulness group took 17.72 (±2 .77) A three-factor mixed-model analysis of covariance trials. An ANOVA revealed no statistically significant (ANCOVA) with group and AQ as between-subject factors, main effect of group, F(1,221) = 1.91, p> .1, stimulus as a within-subject factor, and anxiety-, depression-, η = .008 [95%CI = .000–.048]. There were no signif- and mindfulness after as covariates (i.e., these scores at the icant correlations between trials to criterion and autism time of testing) was conducted on these data. This analysis quotient, r = − .035, p > .60; anxiety before, r = −.013, revealed a significant main effect of group, F(2,215) = 16.84, p > .80; anxiety after, r = −.006, p > .9; depression be- p <.001, η = .135[.056–.216], stimulus, F(1,215) = 17.51, fore, r = −.050, p > .40; depression after, r = −.089, p < .001, η = .075[.021–.150], but not AQ, F <1, p > .10; mindfulness before, r = .028, p > .60; or mind- η = .001[.000–.002]. There were significant interactions be- fulness after, r = .004, p > .60. tween group and AQ, F(2,215) = 10.26, p < .001, η = .087[.025–.160], stimulus and group, F(2,215) = Most vs. Least-Selected Elements During Test 68.82, p <.001, η = .390[.289–.471], but not stimulus and (Over-Selectivity) AQ, F <= 1, η = .001[.000–.068], but there was a signifi- cant three-way interaction, F(2,215) = 33.89, p < .001, The mean percentage times that the most-selected and least- η = .236[.144–.327]. selected stimuli were chosen from reinforced compounds AB To further analyse the three-way interaction, separate two- and EF during the test were calculated. The number of times factor ANCOVAs (AQ × stimulus, with depression, anxiety, that the individual elements of each previously reinforced el- and mindfulness—after as covariates) were conducted for ement (A or B and E and F) were calculated. The element that each group. For the control group this analysis revealed sig- was selected more times from each compound, was designat- nificant effects of AQ, F(1,71) = 12.56, p < .001, ed the ‘most-selected’ element; providing a most-selected η = .150[.029–.299], and stimulus, F(1,71) = 25.16, p (e.g., A) and least-selected stimulus (e.g., B) from AB, as well < .001, η = .262[.108–.410], and a significant interaction as a most-selected (e.g., E) and least-selected stimulus (e.g., F) between stimulus and AQ, F(1,71) = 18.62, p < .001, from EF. The mean most-selected (e.g., A and E) and least- η = .208[.063–.358]. Simple effect analyses conducted on selected (e.g., B and F) mean was then calculated. the most vs. least stimulus difference for the lower AQ group Figure 2 shows the group-mean percentage times that the revealed a significant difference, F(1,72) = 15.73, p < .001, most- and least-selected stimuli were chosen for the three η = .179[.046–.329], and a much greater difference for the higher scoring group, F(1,72) = 300.73, p < .001, 100 Most Least η = .808[.723–.854]. For the relaxation group this analysis revealed a significant effect of AQ, F(1,69) = 6.43, p <.05, η = .085[.003–.224], no significant main effect of stimulus, F <1, 60 η = .009[.000–.099], but a significant interaction between stimulus and AQ, F(1,69) = 15.88, p < .001, η = .187[.049–.340]. Simple effect analyses conducted on the most vs. least stimulus difference for the lower AQ group revealed a significant difference, F(1,72) = 115.78, p <.001, η = .617[.471–.707], and a much lower difference for the higher scoring group, F(1,72) = 15.73, p < .001, Mindful Relax Control Mindful Relax Control η = .179[.046–.329]. Low AQ High AQ For the mindfulness group this analysis revealed a signifi- cant main effect of stimulus, F(1,69) = 6.40, p <.05, Fig. 2 Percentage times most and least-selected elements were chosen for each group at test η = .085[.003–.224], but no significant effect of AQ, F < Percent mes selected Mindfulness 1, η = .001[.000–.085], or interaction between stimulus and over-selectivity) as the outcome, revealed a significant regres- 2 2 AQ, F (1,69) = 3.96, p >0.05, η = .054[.000–.182]. sion, − 2LL =66.00, X (4) = 25.72, p < .001. There was a sig- nificant negative relationships between autism quotient and Most vs. Least-Selected Elements During Test the presence of over-selectivity (odds ratio = .828, p < .05), (Over-Selectivity) and a significant positive relationship between anxiety (β = 1.273, p < .05), and mindfulness (β =1.139, p <.05), but not The analysis above will produce a numeric difference between between depression (odds ratio =.731, p =.194). the most- and least-selected stimuli, and this analysis will not show that there is over-selectivity per se. Given this consider- Mindfulness Group The criteria level for over-selectivity, cal- ation, further analysis of the data was undertaken, based on culated using the Reynolds/Reed methods (above), for this binomial theory, to determine whether the deviation in the group was 8.10, and a paired t test between the actual differ- times that the most-selected and least-selected stimuli were ences and this criterion value revealed no statistically signifi- chosen was statistically greater than would be expected by cant difference from chance, t(73) = 1.73, p >.08, d =.24,sug- random chance around an average probability of selection of gesting no over-selectivity was present. A logistic regression the two stimuli (Reynolds and Reed 2011). This analysis was also revealed no significant prediction by these variables to the undertaken to indicate whether the difference from the level of presence of over-selectivity, −2LL = 98.39, X (4) = 2.89, choice that would be expected if both stimuli had the same p >.50. probability of being chosen was statistically significant—i.e., whether there was absolute over-selectivity, as opposed to relative differences in stimulus selection. Paired t tests were then used to test this sum against the obtained data, in order to Discussion investigate whether significant over-selectivity occurred in each of the groups. The results demonstrated that without any form of interven- tion (mindfulness or relaxation), participants with higher Control Group The criteria level for over-selectivity, calculat- levels of autism traits demonstrated greater over-selectivity ed using the Reynolds/Reed methods (above), for this group than those with lower autism and anxiety scores. This finding was 18.23, and a paired t test between the actual differences is novel with respect to AQ scores, but is consistent with and this criterion value revealed a statistically significant dif- previous findings for those with ASD (Kelly et al. 2015; ference from chance, t(75) = 5.51, p <.001, d =.63, suggest- Leader et al. 2009), and also replicates previous findings that ing over-selectivity occurred for this group. Participants were have shown greater levels of anxiety or stress associated with categorised into those who demonstrated over-selectivity (i.e., over-selective responding (Groden et al. 2005). The finding had a difference score of greater than the criterion value) and that those with higher AQ scores perform similarly to those those who did not. A logistic regression was conducted with with clinical-ASD also extend the suggestion that ASD could anxiety (HADS-A), depression (HADS-D), mindfulness be regarded as a broad phenotype with traits distributed across (TMS) after the intervention, and the AQ scores, as predictors, the population (Couteur et al. 1996;Reed etal. 2011). and the binary categorisation (0 = no over-selectivity; 1 = The mindfulness intervention removed a tendency to over- over-selectivity) as the outcome. This revealed a significant select, and did so independently of the level of AQ displayed regression, −2LL =61.54, X (4) = 28.06, p <.001. Therewere by the participants. This suggests that mindfulness may well significant relationships between the autism quotient and pres- be a useful intervention in this regard, and further substantiates ence of over-selectivity, with more autism traits meaning a previous findings that have shown its effectiveness for some greater chance of over-selectivity (odds ratio = 1.444, p populations (Hofmann and Gómez 2017). This also suggests < .001), but not between the presence of over-selectivity and that mindfulness may be effective in dealing with some of the anxiety (odds ratio =.923, p > .50), depression (odds ratio = core symptoms of ASD. However, the current results also 1.064, p > .60), or mindfulness (odds ratio =1.080, p =.074). suggest that the mechanisms through which such a mind- fulness intervention works could differ between those with Relaxation Group The criteria level for over-selectivity, calcu- lower and higher levels of autism traits. Considering the lated using the Reynolds/Reed methods (above), for this data from the lower scoring AQ participants, it is apparent group was 15.78, and a paired t test between the actual differ- that the mindfulness intervention worked much more ef- ences and this criterion value revealed no statistically signifi- fectively than the relaxation (unfocused attention) inter- cant difference from chance, t <1, d = .02,suggestingnoover- vention in terms of reducing over-selective responding. all level of over-selectivity for this group. A logistic regres- This is in line with previous studies that have compared sion, conducted with the psychological variables as predictors, mindfulness with relaxation for a population without ASD and the binary categorisation (0 = no over-selectivity; 1 = (Arch and Craske 2006;McHugh et al. 2010). Mindfulness In contrast, for the participants with higher AQ scores, it is period than might be given in a clinical context. However, that apparent that there was little difference between the impact of brief interventions of a similar length have been successful in the mindfulness and the relaxation interventions, and both reducing clinically relevant symptoms (Arch and Craske 2006), produced less over-selectivity than the control condition. and that even shorter mindful interventions have been success- This is a novel finding with respect to the impact of mind- ful in reducing over-selectivity in other populations (McHugh fulness on over-selectivity—where in other groups mind- et al. 2010), suggests that time-alone is not a key factor in the fulness has produced a stronger reduction in over- impact of mindful interventions. None of the participants were selectivity than relaxation (Arch and Craske 2006). It is drawn from a clinical population (in so far as they failed to also novel with respect to the impact of mindfulness on a report any current or previous psychiatric problems). This population with higher levels of ASD traits. Previous stud- might mean that the current results may not generalise to those ies of this latter group often have lacked such a relaxation populations —this will require further exploration. However, control (de Bruin et al. 2015; Singh et al. 2011). Although it mindfulness has been suggested as an important approach to has been shown that mindfulness works for a group with tackle many non-clinical problems,and,tothisextent, thecur- ASD, especially with regard to ritualistic behaviours (de rent results are directly relevant. Finally, the degree to which Bruin et al. 2015;Kiepet al. 2015), it has not been shown these findings would generalise to populations with other cog- that this effect is due to the specific effects of mindfulness, nitive or emotional problems, or who receive longer duration or rather than to the possible effects of relaxation. greater numbers of mindfulness sessions, is also uncertain. Thus, the current results suggest that mindfulness may well In summary, the current study demonstrated that over- be beneficial with regard to reducing an over-focused atten- selective responding is associated with higher levels of AQ tion in those with lower and higher levels of autism traits, but and anxiety, and that it can be reduced by mindfulness inter- that it may well work through different mechanisms in each ventions. However, it is unclear whether these mindfulness case. The precise mechanisms of this action will require fur- interventions impact over-selectivity through the same mech- ther exploration. However, some tentative suggestions may be anisms in those with lower and higher levels of autism traits. It made on the bases of these data. Mindfulness reduced over- seems that mindfulness may initially act to reduce anxiety selectivity, better than relaxation, for the lower scoring AQ levels which are associated with over-selectivity, and then participants. This latter group showed higher levels of mind- exert a more specific effect on attention. fulness after the mindful intervention than the other two inter- vention groups. Together, these findings suggest a specific Compliance with Ethical Standards mindful mechanism for these participants. Conflict of Interest The author declare that they have no conflicts of That those with higher levels of AQ showed no differential interest. over-selectivity reduction in the mindfulness compared to the relaxation treatment, and also showed no higher levels of Ethics Statement Ethical approval for this research was given by the mindfulness after the mindfulness intervention than after the Department of Psychology, Swansea University, Ethics Committee. other interventions, suggests that the relaxation induced by the mindfulness condition may have been the key component of Informed Consent Statement All participants were given information about the study, told that they could withdraw at any point without giving action for this group. That anxiety levels were higher in the a reason, and signed a consent form after receiving this information. higher AQ participants, might also suggest that this aspect was exerting a strong effect on their over-selectivity performance Open Access This article is distributed under the terms of the Creative (Groden et al. 2005), and that any intervention that reduces Commons Attribution 4.0 International License (http:// creativecommons.org/licenses/by/4.0/), which permits unrestricted use, anxiety may help this group to reduce over-selective attention- distribution, and reproduction in any medium, provided you give appro- al responses (see also Maisel et al. 2016, for a similar priate credit to the original author(s) and the source, provide a link to the discussion). Indeed, anxiety has been shown to be reduced Creative Commons license, and indicate if changes were made. in groups with ASD traits (MacNeil et al. 2009). 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MindfulnessSpringer Journals

Published: Jun 1, 2018

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