Consciousness and Cognition · Neo-dissociation theory (see Hilgard, 1991) also highlights a role for altered executive functioning in hypnotic responding. It states that during hypnosis,

Impulsivity, self-control, and hypnotic suggestibility

V.U. Ludwig a,b,c,⇑, C. Stelzel a,b,c, H. Krutiak a,d, C.E. Prunkl a, R. Steimke a,b,c, L.M. Paschke a,b,c,N. Kathmann b,c, H. Walter a,b

aDepartment of Psychiatry & Psychotherapy, Charité Universitätsmedizin Berlin, Charitéplatz 1, D-10117 Berlin, GermanybBerlin School of Mind and Brain, Humboldt-Universität zu Berlin, Luisenstraße 56, D-10117 Berlin, GermanycDepartment of Psychology, Humboldt-Universität zu Berlin, Rudower Chaussee 18, D-12489 Berlin, Germanyd Fortbildungszentrum OST der Deutschen Gesellschaft für Hypnose und Hypnotherapie e.V., Fuggerstraße 35, D-10777 Berlin, Germany

a r t i c l e i n f o

Article history:

Received 20 September 2012

Keywords:

Hypnosis

Hypnotic suggestibility

Hypnotisability

Impulsivity

Self-control

Gender

Frontal lobe

Personality

a b s t r a c t

Hypnotic responding might be due to attenuated frontal lobe functioning after the hyp-

notic induction. Little is known about whether personality traits linked with frontal func-

tioning are associated with responsiveness to hypnotic suggestions. We assessed whether

hypnotic suggestibility is related to the traits of self-control and impulsivity in 154 partic-

ipants who completed the Brief Self-Control Scale, the Self-Regulation Scale, the Barratt

Impulsiveness Scale (BIS-11), and the Harvard Group Scale of Hypnotic Susceptibility

(HGSHS:A). BIS-11 non-planning impulsivity correlated positively with HGSHS:A (Bonfer-

roni-corrected). Furthermore, in the best model emerging from a stepwise multiple regres-

sion, both non-planning impulsivity and self-control positively predicted hypnotic

suggestibility, and there was an interaction of BIS-11 motor impulsivity with gender. For

men only, motor impulsivity tended to predict hypnotic suggestibility. Hypnotic suggest-

ibility is associated with personality traits linked with frontal functioning, and hypnotic

responding in men and women might differ.

� 2013 Elsevier Inc. All rights reserved.

1. Introduction

1.1. Research question

During hypnosis, the hypnotised individual allows his or her own body and thoughts to follow the suggestions of the hyp-

notist. Upon suggestion a hypnotised person may move body parts without consciously intending to do so (Blakemore, Oak-

ley, & Frith, 2003), be unable to carry out ordinary movements (Cojan et al., 2009; Halligan, Athwal, Oakley, & Frackowiak,

2000), experience amnesia (Mendelsohn, Chalamish, Solomonovich, & Dudai, 2008), or have auditory hallucinations (Szecht-

man, Woody, Bowers, & Nahmias, 1998). Responses to hypnotic suggestions typically feel involuntary, as if they were hap-

pening on their own or guided by an external force (Weitzenhoffer, 1980). Individuals differ in their propensity to respond to

suggestions given during hypnosis, which is termed hypnotic suggestibility (see Kirsch & Braffman, 2001).

From an observer’s perspective, it may seem as if hypnotic responding involves voluntarily giving up self-control and

passing control to the hypnotist (although hypnotised individuals are in fact still able to control their own actions; Coe,

Kobayashi, & Howard, 1973). Moreover, hypnotic responding might be described as impulsive in the sense that some of

1053-8100/$ - see front matter � 2013 Elsevier Inc. All rights reserved.

http://dx.doi.org/10.1016/j.concog.2013.04.001

⇑ Corresponding author at: Department of Psychiatry & Psychotherapy, Charité Universitätsmedizin Berlin, Charitéplatz 1, D-10117 Berlin, Germany. Fax:

+49 30 450 517906.

E-mail addresses: [email protected] (V.U. Ludwig), [email protected] (C. Stelzel), [email protected] (H. Krutiak), CarinaPrunkl@

gmail.com (C.E. Prunkl), [email protected] (R. Steimke), [email protected] (L.M. Paschke), [email protected] (N. Kathmann),

[email protected] (H. Walter).

Consciousness and Cognition 22 (2013) 637–653

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the actions or experiences during hypnosis appear to be directly triggered by suggestions rather than by conscious control or

thought processes. It is therefore conceivable that individuals who tend to exhibit less self-control in general and who act

more impulsively in everyday life might respond better to hypnotic suggestions than those who exhibit greater control

and are less impulsive. This hypothesis was tested in the current study.

1.2. Self-control, impulsivity, and the frontal lobe

Self-control refers to a set of processes by which individuals control their own responses, states, or thoughts, typically in

the pursuit of long-term goals. Self-control may involve overriding impulsive behaviours and unwanted thoughts, breaking

habits, resisting temptations, making oneself persist and concentrate on a task, and deliberately changing one’s own moods

or emotions (Tangney, Baumeister, & Boone, 2004). There are some behavioural tasks that measure individual differences in

the ability or propensity to apply self-control. For example, in the delay-of-gratification paradigm, participants can choose

either to receive an immediate small reward (e.g., one marshmallow) or to wait for a larger reward (e.g., two marshmallows;

Mischel, Shoda, & Rodriguez, 1989). Moreover, questionnaires have been developed, including the Brief Self-Control Scale by

Tangney et al. (2004) and the Self-Regulation Scale by Schwarzer, Diehl, & Schmitz (1999). Questionnaires assessing self-con-

trol have, for example, been shown to predict academic success, quality of relationships, wealth, health and success in weight

loss (Moffitt et al., 2011; Tangney et al., 2004; Will Crescioni et al., 2011).

Impulsivity, on the other hand, can broadly be defined as the propensity to act on arising impulses without engaging in

much thinking. However, going beyond such a simple definition, research has shown that impulsivity is a much more com-

plex, multifaceted construct (Evenden, 1999). For example, Patton, Stanford, and Barratt (1995) identified three subtraits of

impulsivity in a factor analysis on a commonly used scale, the Barratt Impulsiveness Scale. These subtraits included atten-

tional impulsivity (the difficulty to focus on tasks, having racing or intrusive thoughts), motor impulsivity (acting without

thinking and inconsistency of lifestyle), and non-planning impulsivity (being present-focussed rather than future-oriented,

not enjoying challenging mental tasks). Research often focuses on the negative consequences of being impulsive. Higher

scores on questionnaires measuring impulsivity have, for example, been associated with alcohol consumption, aggression

and risky driving (Dahlen, Martin, Ragan, & Kuhlman, 2005; Hair & Hampson, 2006; Stanford, Greve, Boudreaux, Mathias,

& Brumbelow, 1996). However, impulsive behaviour can also be useful, for example when quick decisions for action are

needed (e.g., see Dickman, 1990; Gullo & Dawe, 2008).

Self-control and impulsivity are often considered to be opposites of each other (Duckworth & Kern, 2011; Evenden, 1999;

Kalenscher, Ohmann, & Güntürkün, 2006). However, this is likely not entirely true, at least in the way these concepts are

currently measured. For example, Friese and Hofmann (2009) reported correlations of around r = �.60 between trait self-

control and trait impulsivity, corresponding to 36% shared variance (see also Nebioglu, Konuk, Akbaba, & Eroglu, 2012). Thus,

although high impulsivity and low self-control overlap in large parts, these two concepts are not redundant.

The frontal lobe has been shown to be important for self-control abilities (Casey et al., 2011), while attenuated frontal

functioning might be related to impulsivity (Chen et al., 2007; Crews & Boettiger, 2009; Spinella, 2004). Patients with

frontal lobe damage may, for example, have difficulties suppressing habitual responses (Perret, 1974), and/or their actions

may be highly influenced by environmental stimuli (Lhermitte, 1986). In general, regions in the lateral part of the frontal

lobe are important for executive functions (Miyake et al., 2000; Norman & Shallice, 1986). These include planning, problem

solving, inhibition, attention, switching between tasks or monitoring actions (Chan, Shum, Toulopoulou, & Chen, 2008). In

a meta-anaysis, Duckworth and Kern (2011) found that self-report measures assessing self-control (or low impulsivity)

correlate weakly but significantly with performance on tasks of executive functioning. Weak correlations between ques-

tionnaires and behavioural tasks are relatively common in psychology (Meyer et al., 2001), and it has been argued that

questionnaires and tasks, at least in part, measure different things (Dougherty, Mathias, Marsh, & Jagar, 2005; Reynolds,

Ortengren, Richards, & de Wit, 2006; Stanford et al., 2009). That is, behavioural tasks assess particular abilities or pref-

erences in specific contexts (e.g., the ability to focus on a visual target while distractors are presented in the periphery),

and performance may depend to a substantial degree on participants’ mental state (e.g., mood, fatigue). In contrast, ques-

tionnaires assess how participants rate their own behaviour and preferences over a broad range of situations over a long

time span.

1.3. Hypnosis and the frontal lobe

As discussed above, impulsivity and low self-control have been related to diminished frontal lobe functioning (Casey

et al., 2011; Chen et al., 2007; Crews & Boettiger, 2009). The frontal lobe also plays a key role in many theories of hypnotic

responding. In the dissociated-control theory, Woody and Bowers (1994) propose that hypnotic responding is associated

with dissociated or attenuated frontal lobe functions in responsive individuals (see also Bowers, 1992; Woody & Sadler,

1998, 2008). Similarly, the neurophysiological theory of hypnosis by Gruzelier (1998) posits that hypnotic responding results

from the exhaustion of frontal lobe functions after an induction. Neo-dissociation theory (see Hilgard, 1991) also highlights a

role for altered executive functioning in hypnotic responding. It states that during hypnosis, a part of the executive ego con-

trols behaviour while another part is unaware of this. Finally, in the cold control theory, Dienes and Perner (2007) propose

that hypnotised participants form inaccurate higher order thoughts (HOTs, Rosenthal, 2005) about their intentions. That is,

this theory states that hypnotised participants are not aware of their intention to – for example – carry out a certain move-

638 V.U. Ludwig et al. / Consciousness and Cognition 22 (2013) 637–653

ment and that is why their movement feels involuntary. The capacity to form accurate HOTs might also depend on frontal

brain regions (Lau & Passingham, 2006; Rounis, Maniscalco, Rothwell, Passingham, & Lau, 2010).

Based on the central role of frontal functioning in theories of hypnotic responding, studies have assessed whether frontal

functioning is altered during hypnosis. Using electroencephalogram (EEG) measurements, Terhune, Cardeña, and Lindgren

(2011a) showed that individuals with high hypnotic suggestibility (highs) but not those with low suggestibility (lows) exhib-

ited lowered fronto-parietal functional connectivity following a hypnotic induction without any additional suggestions be-

sides those relevant for the induction (specifically: lowered frontal-parietal alpha2 synchronization; see also Egner,

Jamieson, & Gruzelier, 2005). Furthermore, highs show reduced activation of the anterior ‘‘default mode’’ network (prefrontal

cortex) during hypnosis without additional suggestions compared to normal rest (McGeown, Mazzoni, Venneri, & Kirsch,

2009). However, effects on frontal functions may differ when specific suggestions are given during hypnosis (e.g., sugges-

tions to move an arm). For example, using EEG sLORETA functional imaging, Cardeña et al. (2012) demonstrated stronger fast

frequency activity (interpreted as excitatory activity) in frontal regions when participants lifted their arms following a hyp-

notic suggestion compared to when they lifted the arm voluntarily.

Other studies have shown that highs perform worse on tasks of frontal functioning after hypnotic inductions without

additional specific suggestions compared to before, although the evidence for this is inconsistent (e.g., Gruzelier & Warren,

1993; Kallio, Revonsuo, Hämäläinen, Markela, & Gruzelier, 2001; Wagstaff, Cole, & Brunas-Wagstaff, 2007). The inconsisten-

cies might partly be due to the existence of different subtypes of highs. For example, Terhune, Cardeña, and Lindgren (2011b)

showed that only highs with high dissociative tendencies (measured by the Dissociative Experiences Scale; Carlson & Put-

nam, 1993; Putnam, Helmers, & Trickett, 1993) exhibited decreased cognitive control after a hypnotic induction. In contrast,

low dissociative highs and lows tended to exhibit increased cognitive control (see also Marcusson-Clavertz, Terhune, & Card-

eña, 2012). Importantly, when hypnotic suggestions are given that aim at increasing executive abilities, performance on

executive tasks may indeed improve during hypnosis (e.g., Iani, Ricci, Baroni, & Rubichi, 2009; Raz, Fan, & Posner, 2005).

Important further evidence regarding the role of the frontal lobe for hypnotic responding comes from two recent studies

that measured the effect of disrupting frontal functioning on hypnotic responding. First, Semmens-Wheeler and Dienes (in

press) showed that drinking alcohol as opposed to a placebo increases hypnotic suggestibility. Alcohol impairs frontal func-

tions including the ability for inhibitory control and planning (Fillmore & Vogel-Sprott, 1999; Lyvers, 2000; Peterson, Roth-

fleisch, Zelazo, & Pihl, 1990; Schweizer et al., 2005). Second, disrupting frontal functioning via transcranial magnetic

stimulation (TMS) also increases hypnotic responding (Dienes & Hutton, 2013). In sum, there is substantial evidence dem-

onstrating an association between altered frontal functioning and hypnotic responding.

1.4. Behavioural evidence regarding a potential relation between hypnotic suggestibility and self-control or impulsivity

Many studies have used behavioural tasks to assess whether highs and lows differ in terms of their baseline executive

skills, in particular in terms of attentional skills. These skills, in turn, are potentially related to trait self-control and trait

impulsivity (Duckworth & Kern, 2011). Somewhat contrary to the argument put forward in the current article, authors of

these studies often predict that baseline executive (specifically attentional) skills will be better in highs than in lows. The

idea is that entering a hypnotic state requires the ability to focus on the hypnotic induction procedure and to inhibit distract-

ing thoughts and sensory input. According to this proposal, executive functions will only be disturbed after a successful

induction (e.g., see Gruzelier, 1998).

The evidence is mixed. In favour of a relation of hypnotic suggestibility with lower baseline executive functioning, Farv-

olden and Woody (2004) found that highs performed worse than lows on certain memory tasks that are sensitive to frontal

lobe functions, such as free recall and source amnesia tasks. This was true both outside and within the hypnotic state. On the

other hand, many studies did not find baseline differences regarding executive (attentional) functions between highs and

lows (Dienes et al., 2009; Iani, Ricci, Gherri, & Rubichi, 2006; Kaiser, Barker, Haenschel, Baldeweg, & Gruzelier, 1997; Kallio

et al., 2001; Varga, Németh, & Szekely, 2011), and some studies found better baseline executive functioning in highs (Aiktns

& Ray, 2001; Rubichi, Ricci, Padovani, & Scaglietti, 2005). Again, discrepancies could partly be due to the existence of sub-

types of highs. For example, Terhune, Cardeña, and Lindgren (2011c) found that only high dissociative highs exhibited lower

baseline working memory performance compared to low dissociative highs and lows.

Some further studies have investigated whether the behaviour of highs is more automatic than that of lows. Indeed, highs

exhibit enhanced verbal automaticity (Dixon & Laurence, 1992); and hypnotic suggestibility correlates with quicker reaction

times on a simple task requiring clicking with a mouse upon seeing a picture (Braffman & Kirsch, 2001; see also Crawford,

Harrison, & Kapelis, 1995; Wallace & Persanyi, 1993). These findings indicate that hypnotic suggestibility could indeed be

related to impulsivity.

1.5. Evidence from questionnaire measures regarding a potential relation between hypnotic suggestibility and self-control or

impulsivity

The relation between hypnotic suggestibility and trait impulsivity/self-control has, to our knowledge, not been explicitly

studied by means of psychometric questionnaires. However, some studies have assessed related personality constructs. Lich-

tenberg, Bachner-Melman, Ebstein, and Crawford (2004) reported that hypnotic suggestibility is positively predicted by par-

ticipants’ self-reported perseverance as measured by the Tridimensional Personality Questionnaire (TPQ; Cloninger, 1987).

V.U. Ludwig et al. / Consciousness and Cognition 22 (2013) 637–653 639

TPQ perseverance assesses an aspect of self-control since it measures the degree to which people persevere on tasks despite

frustration and difficulty. Thus, this study provides evidence which counters the idea that highs exhibit lower trait self-con-

trol. Moreover, Kihlstrom et al. (1980) found no correlation between hypnotic suggestibility and Synder’s self-monitoring

scale, which measures self-observation and self-control of expressive behaviours and self-presentation in social situations

(Snyder, 1974). However, there are some indications for a link between impulsivity and hypnotic suggestibility in the liter-

ature. Lichtenberg et al. (2004) reported that for men the TPQ novelty-seeking subscale of ‘impulsivity versus reflection’ cor-

related moderately with hypnotic suggestibility. Also of note is that highs may experience more intrusive thoughts than lows

(Bryant & Idey, 2001). Moreover, experiential indices and potentially also behavioural indices of hypnotisability correlate

with emotional contagion (Cardeña, Terhune, Lööf, & Buratti, 2008; see also Wickramasekera & Szlyk, 2003). Since this is

the tendency to automatically mimic other people’s emotional expressions and to feel their emotions with them, this pro-

vides evidence for increased automaticity (or impulsivity) in highs. Finally, yet unpublished results from the University of

Sussex indicate that hypnotic suggestibility correlates negatively with mindfulness (see Semmens-Wheeler & Dienes,

2012). Mindfulness means being aware of one’s immediate experience, while adopting an ‘‘orientation that is characterized

by curiosity, openness, and acceptance’’ (p. 232; Bishop et al., 2004). This finding speaks in favour of a correlation of hypnotic

suggestibility with impulsivity because mindfulness is expected to correlate negatively with impulsivity (see Murphy &

MacKillop, 2012; Stratton, 2006): that is, someone mindful is unlikely to act impulsively.

1.6. Aim and hypotheses

The idea that frontal functions are compromised during hypnosis plays a pivotal role in theories of hypnotic responding.

Some authors have therefore argued that differences in frontal functioning might explain individual differences concerning

hypnotic suggestibility. Even though the relation of hypnotic suggestibility with frontal abilities (e.g., executive attention)

has been widely studied, almost nothing is known about the relation of hypnotic suggestibility with personality traits asso-

ciated with frontal functioning. In the current study, we assessed whether hypnotic suggestibility correlates with two key

personality traits that have been related to frontal functioning, namely self-control and impulsivity. We used self-report

scales concerning self-control and impulsivity, as well as the Harvard Group Scale of Hypnotic Suggestibility, Form A

(HGSHS:A), to assess our research question. We hypothesised that people who describe themselves as more impulsive or less

self-controlled will respond best to hypnotic suggestions.

2. Method

2.1. Procedure

This study used a data set acquired during the course of a screening in our research group. This screening was conducted

in order to create a database of potential participants for future studies. Participants who wished to be included in this data-

base took part in both a hypnosis session (lasting between 1 and 1.5 h) and completed several online questionnaires unre-

lated to hypnosis (0.5 h). Participants were informed that this procedure was carried out because we intended to select

participants for future studies based on their specific profiles (e.g., age, gender, scores on certain personality questionnaires,

hypnotic suggestibility). Participants were made aware that some future studies would involve hypnosis, while others would

not. With regard to studies that did involve hypnosis, they were informed that we would require all kinds of participants,

that is participants with high, medium, and low hypnotic suggestibility. This information was given in order to ensure that

participants would not simulate high hypnotic suggestibility in an attempt to increase their chances to be invited for studies.

The information given to participants was worded in a way that assured that people were very unlikely to suspect that we

were interested in the correlations between some of the online questionnaires (those reported below) and participants’

behaviour during the hypnosis session.

In the hypnosis session, participants were tested in groups of 3–17 participants (Mean = 8.94, standard deviation

[SD] = 4.45). They were seated on comfortable chairs that were standing along the walls of the experimental room. Partici-

pants first completed informed consent forms. An experimenter introduced the study to participants and provided an oppor-

tunity for them to ask questions. Following this introduction an audio tape of the HGSHS:A was played to the participants.

The experimenters were female (either author V.U.L. or C.E.P.), while the speaker of the audio tape was male. After the hyp-

nosis, participants completed the HGSHS:A questionnaire.

2.2. Participants

We analysed data of 154 healthy participants (91 female) between the ages of 18 and 34 (Mean = 25.01, SD = 4.02). 7

additional participants were excluded from the analysis due to a failure to complete the questionnaires (n = 3), leaving

the hypnosis session early due to dizziness (n = 1), and falling asleep during the hypnosis session (n = 3). The sample size

gives a statistical power of .97 for detecting meaningful effects (rP .30). Participants were all either current or former stu-

dents and native German speakers. Exclusion criteria were: a history of psychiatric or neurological disorders, use of hard

drugs, and excessive drinking or smoking. Furthermore, participants could only take part if they were right-handed and if


they were not currently on a diet. These two latter criteria were used because data collection took place in the context of a

screening for potential participants for other studies, as described above. These other studies included functional magnetic

resonance imaging (fMRI) studies about reward processing, and for these studies participants were required to be right-

handed and to eat normally. In contrast to many other studies, our sample was not restricted to psychology students but

consisted of (former and current) students from a wide range of subject areas. This was achieved by recruiting from many

different departments and universities in the Berlin area. Participants received 8€ for participation in the hypnosis session

and for completing the online questionnaires.

2.3. Measures

2.3.1. Hypnotic suggestibility

The German version of the HGSHS:A (Shor & Orne, 1962; German version by Bongartz, 1980) was used to measure hyp-

notic suggestibility. It consists of a trance induction followed by 12 suggestions involving, for example, arm levitation, lock-

ing fingers, a post-hypnotic suggestion, and an auditory hallucination. Suggestions were scored as 1 if participants reported

to have followed them; and otherwise they were scored as 0 (Bongartz, 1985; Shor & Orne, 1962). One suggestion involves

amnesia. This suggestion was scored as 1 if participants remembered less than four previous suggestions before the sugges-

tion of amnesia was lifted. Total HGSHS:A scores varied between 0 and 12. The HGSHS:A has adequate internal consistency

reliability with reported Kuder–Richardson Formula 20 values or the analogous Cronbach’s a varying between about 0.70–

0.80 (Angelini, Kumar, & Chandler, 1999; Kirsch, Council, & Wickless, 1990; Sheehan & McConkey, 1979; Shor & Orne, 1963).

In a German sample, however, a lower value of .62 was reported (Bongartz, 1985). The HGSHS:A correlates highly with scores

on the individually administered Stanford Scale of Hypnotic Susceptibility, Form C (SSHS:C), with reported r-values around

.60 to .70 (Bentler & Roberts, 1963; Bongartz, 1985; Coe, 1964).

2.3.2. Self-control

Questionnaire data assessing self-control, namely the Brief Self-Control Scale (BSC; Tangney et al., 2004; German trans-

lation by Renner, Salewski, Strohbach, & Sproesser, 2009), and the Self-Regulation Scale (SR; Schwarzer et al., 1999) were

collected and analysed. The BSC and SR correlate around r = .50 (Bertrams & Dickhäuser, 2009). The BSC, however, is some-

what more general and covers a wider range of topics concerning self-control compared to the SR scale. The SR specifically

focuses on the abilities to regulate one’s emotions and attention when difficulties arise during the pursuit of a goal.

The BSC consists of 13 items (e.g., ‘‘I am good at resisting temptations’’, and ‘‘I am able to work effectively toward long-

term goals’’). Response options range from 1 (not at all) to 5 (very much). The BSC has a good internal consistency with a

Cronbach’s a = .83–.85, and a test–retest reliability of .87 after 3 weeks (Tangney et al., 2004). The SR consists of 10 items

(e.g., ‘‘If an activity requires a problem-oriented attitude, I can control my feelings’’, and ‘‘I stay focused on my goal and don’t

allow anything to distract me from my plan of action’’). Response options here range from 1 (not at all) to 4 (exactly true). In

a German sample, the SR scale has been reported to have an internal consistency of Cronbach’s a = .76 and a test–retest sta-

bility of .62 after six weeks (Schwarzer et al., 1999).

2.3.3. Impulsivity

For measuring impulsivity, we used a German version of the Barratt Impulsiveness Scale (BIS-11; Patton et al., 1995). This

30-item scale assesses general impulsivity. Three subscale scores can be computed measuring attentional impulsivity, motor

impulsivity, and non-planning impulsivity. Example items include: ‘‘I concentrate easily’’ (attentional impulsivity, scored in-

versely), ‘‘I act ‘on impulse’’’ (motor impulsivity), and ‘‘I am more interested in the present than the future’’ (non-planning

impulsivity). Response options range from 1 (rarely/never) to 4 (almost always/always). Higher scores on the BIS-11 have

been associated with reduced performance on tasks of frontal functioning (Spinella, 2004). The BIS-11 has been reported

to have an internal consistency of Cronbach’s a = .83, and a test–retest reliability at one month of Spearman’s Rho = .83 in

an American sample (Stanford et al., 2009). In a German sample, Cronbach’s a was .69 (Preuss et al., 2008).

2.4. Statistical analysis

We assessed our question using two approaches. First, we calculated Pearson’s correlation coefficients r between hyp-

notic suggestibility and all the self-control and impulsivity measures, while correcting for multiple comparisons using Bon-

ferroni-correction. Second, we adopted a stepwise backward elimination multiple regression approach to analyse the data

using SPSS.

For the backward regression approach, initially all predictors were entered into the model and the model was estimated.

The regressor that contributed the least to predicting the outcome variable was then removed (if pP .05) and the model was

re-estimated. This procedure was repeated until only significant regressors remained in the model (a = .05). Thus, the back-

ward method allows determining which predictors are redundant and can be dropped from the model. Specifically, we en-

tered the predictors SR, BSC, BIS-11 attentional impulsivity, BIS-11 motor impulsivity, and BIS-11 non-planning. BIS-11 total

score was not entered as this would have led to unacceptably high levels of multicollinearity (since BIS-11 total is the sum of

the scores on the three subscales). Since previous studies have found gender differences concerning the correlates of hyp-

notic suggestibility (Barber & Calverley, 1964; Bentler, 1963; Bowers, 1971; Dienes et al., 2009; Gur & Gur, 1974; Lichtenberg


et al., 2004), we also entered gender and the interactions of gender with each of the five scales as predictors. This resulted in

11 predictors in total.

All questionnaire scores were centred by subtracting the mean of each scale from each score, so that the mean of each

scale was 0. In models that contain interactions, centring reduces multicollinearity between the single term predictors

and their interaction terms, and it is valuable for theoretical and interpretative reasons (Hayes, Glynn, & Huge, 2012; West,

Aiken, & Krull, 1996). For gender, unweighted effect coding was used (�1 for men, and 1 for women). We chose unweighted

instead of weighted effect coding, because our sample size differences for men and women do not reflect meaningful differ-

ences concerning the proportion of genders in the population (West et al., 1996, pp. 26–30). Note that since the standardized

betas calculated by SPSS for models containing interactions are incorrect (Aiken & West, 1991, pp. 40–47), we determined

standardized coefficients as recommended by Friedrich (1982, p. 824).

At the end of the stepwise procedure, we assessed whether the assumptions of multiple regression had been met and

whether there were any influential cases or outliers (see Text S1 in the Supplementary data for details). To explore the nature

of significant interactions in the model, we carried out standard post-hoc procedures (Aiken & West, 1991; pp. 130–133;

Richter, 2007; West et al., 1996), which are described in detail in Text S2 in the Supplementary data.

3. Results

3.1. Descriptive statistics and gender comparisons for all questionnaires

Table 1 shows means, SDs, and reliability coefficients for all questionnaires for the overall sample. There were no signif-

icant gender differences on any of the questionnaires after Bonferroni-correction, as indicated by independent t-tests (see

Supplementary data, Table S1). Genders also did not differ in terms of variances on their questionnaire scores, as indicated

by Levene’s tests (all uncorrected ps > .05). Moreover, genders did not differ significantly in terms of their responses to spe-

cific suggestions on the HGSHS:A, although women tended to respond better to the eye catalepsy suggestion (see Table S2).

3.2. Correlations between self-control and impulsivity

Table 2 shows Pearson’s correlations r between BSC, SR, and BIS-11. As predicted by the theory, BSC and SR were highly

positively correlated, and both were negatively correlated with BIS-11.

3.3. Correlations between hypnotic suggestibility and measures of self-control and impulsivity

Zero-order Pearson’s correlations revealed a weak positive correlation between BIS-11 non-planning impulsivity and hyp-

notic suggestibility, and this was significant after Bonferroni-correction (see Table 3). No other correlations were significant

after correction. At an uncorrected level, BIS-11 total score also correlated positively with hypnotic suggestibility.

3.4. Stepwise multiple regression to predict hypnotic suggestibility

3.4.1. Main results

The model emerging from the stepwise regression procedure contained the regressors BIS-11 non-planning impulsivity,

BSC, and the interaction of gender with BIS-11 motor impulsivity. In the final step, we re-inserted the non-significant single

terms gender and BIS-11 motor impulsivity. This is important, because any model that includes an interaction also needs to

include the single terms that make up the interaction (West et al., 1996, p. 5). The single terms are crucial for interpreting the

nature of their interaction. Regression diagnostics indicated that the assumptions of multiple regression had been met and

that the model was not unduly influenced by a small number of cases (see Text S1 in the Supplementary data for details).

The final model is shown in Table 4 (see Table A1 in the Appendix for all steps of the model selection process). The model

successfully predicted HGSHS:A scores and accounted for 13% of the variance in the data (F = 4.27, p = .001). Non-planning

impulsivity and BSC positively predicted HGSHS:A (see Fig. 1A and B), while the effect of motor impulsivity on HGSHS:A de-

pended on gender (see Fig. 1C). Non-planning impulsivity was the best predictor.

Table 1

Descriptive statistics and reliability coefficients for all questionnaires used.

BSC SR BIS-11 total BIS-11 attention BIS-11 motor BIS-11 non-planning HGSHS:A

Mean 41.87 29.53 61.63 15.79 22.78 23.06 6.42

SD 6.4 3.96 8.65 2.86 4.14 4.18 2.55

Cronbach’s a .73 .77 .76 .51 .63 .59 .70

Note: SD: standard deviation. BSC: Brief Self-Control Scale. SR: Self-Regulation Scale. BIS-11: Barratt Impulsiveness Scale. HGSHS:A: Harvard Group Scale of

Hypnotic Susceptibility.


Fig. 1 shows HGSHS:A values as predicted by the different regressors in the final model. To visualise our results further,

we split our participants in four groups using median splits on non-planning impulsivity and BSC (i.e. those two variables

that were significant predictors of HGSHS:A independent of gender): (i) low non-planning impulsivity & low BSC, (ii) low

non-planning impulsivity & high BSC, (iii) high non-planning impulsivity & low BSC, and (iv) high non-planning impulsivity

& high BSC. Fig. 2 shows mean HGSHS:A values for the four groups. As reflected in the results of the regression, participants

high on both non-planning impulsivity and BSC had the highest HGSHS:A scores, while participants low on both scales had

the lowest HGSHS:A scores. Note that the figure is for visualisation only and that no statistics were calculated on these

groups (as this would be problematic, since the groups were formed based on the results of the regression analysis).

3.4.2. Post-hoc tests concerning the interaction with gender

We used the standard recommended post-hoc procedures to explore the significant interaction of motor impulsivity with

gender (Aiken & West, 1991, pp. 130–133; Richter, 2007; West et al., 1996). See Text S2 in the Supplementary data for all

details of the procedure. We carried out four post-hoc tests in total and Bonferroni-corrected for multiple comparisons (cor-

rected a = .013).

First, we determined if motor impulsivity is a significant predictor of hypnotic suggestibility for men and/or for women

separately by calculating simple slopes for both genders (Aiken & West, 1991, p. 131). We found that for men, motor impul-

sivity was a predictor of hypnotic suggestibility, but this was true at an uncorrected significance level only (unstandardized

beta for motor impulsivity: 0.15, SE = .07, p = .04 uncorrected). For women, in contrast, motor impulsivity was far from being

a significant predictor (unstandardized beta for motor impulsivity = �.06, SE = .07, p = .39 uncorrected).

Second, we approached the interaction from the opposite perspective by determining the effect of gender at very low and

very high levels of motor impulsivity (Aiken & West, 1991, pp. 132–133). We found that for participants very low in motor

impulsivity (Mean – 2SD), gender significantly predicted hypnotic suggestibility (unstandardized beta for gender = 2.37,

Table 2

Correlations among self-control and impulsivity measures.

Questionnaire BSC SR BIS-11 Total BIS-11 Attention BIS-11 Motor

SR .54 (<.001*) _

BIS-11 total �.52 (<.001*) �.39 (<.001*) _

BIS-11 attention �.51 (<.001*) �.63 (<.001*) .63 (<.001*) _

BIS-11 motor �.26 (<.001*) �.04 (.62) .77 (<.001*) .15 (.06) _

BIS-11 non-planning �.47 (<.001*) �.33 (<.001*) .87 (<.001*) .47 (<.001*) .49 (<.001*)

Note: Values in the table are Pearson’s correlation coefficients r. p-values are given in brackets.* significant after Bonferroni-correction for all tests reported in this table (a = .003). N = 154. BSC: Brief Self-Control Scale. SR: Self-Regulation Scale. BIS-11:

Barratt Impulsiveness Scale.

Table 3

Correlations between hypnotic suggestibility and measures of self-control and impulsivity.

Questionnaire BSC SR BIS-11 total BIS-11 attention BIS-11 motor BIS-11 non-planning

HGSHS:A .03 (.70) �.04 (.61) .19 (.02) �.01 (.94) .16 (.055) .23 (.003*)

Note: Values in the table are Pearson’s correlation coefficients r. p-values are given in brackets.* significant after Bonferroni-correction for all tests reported in this table (a = .008). N = 154. HGSHS:A: Harvard Group Scale of Hypnotic Susceptibility,

Form A. BSC: Brief Self-Control Scale. SR: Self-Regulation Scale. BIS-11: Barratt Impulsiveness Scale.

Table 4

Final model for predicting hypnotic suggestibility emerging from the stepwise multiple regression procedure.

Independent variables B SE B ß p

Constant 6.35 0.20 �.01 <.001

BSCc 0.08 0.04 .20 .03

BIS-11 motorc 0.04 0.05 .04 .42

BIS-11 non-planningc 0.17 0.06 .28 .004

Gender 0.31 0.20 .12 .13

BIS-11 motorc x Gender �0.11 0.05 �.17 .03

Note: Bs are unstandardized, ß are standardized coefficients; SE: standard error. N = 154. Since the standardized betas calculated by SPSS for models

containing interactions are incorrect (Aiken and West, 1991, pp. 40–47), standardized coefficients were determined as recommended by Friedrich (1982, p.

824). Due to this procedure, the standardized ß for the intercept is not exactly 0. The c-subscript indicates that variables were centred. See Table A1 in the

Appendix for all steps of the stepwise regression. BSC: Brief Self-Control Scale. BIS-11: Barratt Impulsiveness Scale.


Fig. 1. Visualisation of the results of the multiple regression. Graphs show the HGSHS:A scores that are predicted by the model for men and women

separately for specific values of the different predictor variables while the other variables are held at their average level (calculated from the regression

parameters). (A) Predicted HGSHS:A scores for different values of non-planning impulsivity for participants with average scores on BSC and motor

impulsivity, (B) predicted HGSHS:A scores for different values of BSC for participants with average scores on non-planning impulsivity and motor

impulsivity and (C) predicted HGSHS:A scores for different values of motor impulsivity for participants with average scores on BSC and non-planning

impulsivity. SD: Standard deviation. HGSHS:A: Harvard Group Scale of Hypnotic Susceptibility, Form A.

Fig. 2. Mean HGSHS:A values for groups of participants that differ in terms of their levels of non-planning impulsivity and trait self-control. Figure serves to

visualize the results only. Statistics were calculated on the continuous values of the scales as reported in the text, and not on these groups. Groups were

formed by median splits. 95% confidence intervals of the mean are shown. NPI: non-planning impulsivity (Barratt Impulsiveness Scale). BSC: Brief Self-

Control Scale. HGSHS:A: Harvard Group Scale of Hypnotic Susceptibility, Form A.


SE = 0.88, p = .008) with women showing higher levels of HGSHS:A scores. Note that this is significant after Bonferroni-cor-

rection for all post-hoc tests. For participants scoring very high in motor impulsivity (Mean + 2SD), gender did not predict

hypnotic suggestibility (p = .20). Thus, gender only predicted HGSHS:A scores for participants low in motor impulsivity

(see Fig. 1C).

3.5. Point-biserial correlations between non-planning impulsivity/motor impulsivity/BSC and all individual suggestions

We conducted an exploratory analysis to determine if the relations between HGSHS:A scores and the scales motor impul-

sivity, non-planning impulsivity, and BSC differed between direct motor suggestions (i.e., suggestions for movement) and

motor challenge suggestions (i.e., suggestions involving the inhibition of movement; see McConkey, Sheehan, & Law,

1980; Peters, Dhanens, Lundy, & Landy, 1974). For this purpose, we calculated point-biserial correlations between each indi-

vidual suggestion of the HGSHS:A and the three scales that were associated with the HGSHS:A. For motor impulsivity, this

was done separately for men and women due to the gender difference concerning this scale. Detailed results of this analysis

can be found in the Supplementary data (Tables S3–S5). No correlation survived Bonferroni-correction. At an uncorrected

level, motor impulsivity in men correlated with the motor challenge suggestions arm immobilization and eye catalepsy. Also

at an uncorrected level, non-planning impulsivity in all participants correlated with the motor challenge suggestions arm

immobilization, eye catalepsy, and communication inhibition.

4. Discussion

4.1. Summary of the results

This study shows that subtraits of impulsivity and trait self-control positively predict hypnotic suggestibility and it dem-

onstrates significant gender differences for predictors of hypnotic suggestibility. We carried out a backward stepwise multi-

ple regression procedure starting with a range of predictor variables measuring aspects of self-control and impulsivity, as

well as their interactions with gender. After dropping predictors that did not contribute significantly to predicting hypnotic

suggestibility, the best model contained the significant predictors non-planning impulsivity, BSC and an interaction of motor

impulsivity with gender. Post-hoc tests showed that the interaction was due to the fact that motor impulsivity did not pre-

dict hypnotic suggestibility for women, while it tended to positively predict it for men. When exploring this further, we

found that for participants with low motor impulsivity, women were predicted to have higher hypnotic suggestibility scores

than men. In contrast, for participants with average or high motor impulsivity, gender did not significantly predict hypnotic

suggestibility.

The finding that non-planning impulsivity (and, trend-wise, motor impulsivity in men) predicted hypnotic suggestibility

is in line with theories and evidence pointing to a relation of attenuated frontal lobe functioning with hypnotic responding.

That is because impulsivity has been associated with reduced frontal functioning (Chen et al., 2007; Crews & Boettiger, 2009;

Spinella, 2004). However, the picture is more complex than that because also trait self-control positively predicted hypnotic

suggestibility (when holding non-planning impulsivity constant). This is surprising because trait self-control and impulsivity

are often considered to be opposites of each other (e.g., Duckworth & Kern, 2011). Our findings support the claim that self-

control and impulsivity are neither redundant concepts nor perfect opposites, at least in the way they are currently mea-

sured (Friese & Hofmann, 2009). Exhibiting both high self-control and high non-planning impulsivity appears to be advan-

tageous for high hypnotic suggestibility (see Fig. 2). We discuss each of our findings below.

4.2. Explanations for the link between non-planning impulsivity and hypnotic suggestibility

What might explain the positive link between non-planning impulsivity and hypnotic suggestibility? Non-planning

impulsivity refers to the tendency to focus on the present rather than to plan for the future (Patton et al., 1995). For example,

individuals with high non-planning impulsivity tend to choose earlier smaller rewards as opposed to delayed bigger rewards

(de Wit, Flory, Acheson, McCloskey, & Manuck, 2007; Koff & Lucas, 2011; Mobini, Grant, Kass, & Yeomans, 2007; but see Rey-

nolds et al., 2006). The non-planning impulsivity scale also contains items concerning the degree to which one does not enjoy

complex mental tasks. Importantly, non-planning impulsivity and self-control predicted HGSHS:A simultaneously in the fi-

nal regression model. Thus, hypnotic suggestibility is associated with an aspect of non-planning impulsivity that does not

overlap with low self-control.

The aspect of impulsivity which does not overlap with self-control, and which is related to hypnotic suggestibility, might

involve the degree to which one enjoys new and diverse experiences. All subtraits of impulsivity of the BIS-11 correlate pos-

itively with the boredom susceptibility, disinhibition, and experience-seeking scales on the Zuckerman Sensation-Seeking

Scale (SSS-V; Mobini, Pearce, Grant, Mills, & Yeomans, 2006; Quilty & Oakman, 2004; Stanford et al., 2009; Zuckerman, Ey-

senck, & Eysenck, 1978). Sensation seeking, in turn, correlates with openness to experience (Zuckerman, 1994; although Hair

& Hampson, 2006, did not find a significant correlation between impulsivity and openness to experience). Most studies have

largely failed to find a correlation between sensation seeking and hypnotic suggestibility (Johnston & Jaremko, 1979; Kumar,

Pekala, & Cummings, 1996; Zuckerman, Bone, Neary, Mangelsdorff, & Brustman, 1972). However, high sensation seekers are


more likely than low sensation seekers to participate in experiments involving hypnosis (Zuckerman, Schultz, & Hopkins,

1967). Moreover, links between openness to experience and hypnotic suggestibility have been reported (Glisky & Kihlstrom,

1993; Glisky, Tataryn, Tobias, Kihlstrom, & McConkey, 1991; Milling, Miller, Newsome, & Necrason, 2013; Nordenstrom,

Council, & Meier, 2002; Radtke & Stam, 1991). Even though the evidence is mixed, it is conceivable that participants with

high non-planning impulsivity respond better to hypnotic suggestions partly because they are more curious about the

new experience.

Our findings may also be due to the fact that impulsive individuals worry less about possible harms or risks (Stanford

et al., 1996). Sensation seeking – a key correlate of impulsivity – correlates negatively with TPQ harm avoidance (Earleywine,

Finn, Peterson, & Pihl, 1992), a tendency which can entail excessive worry, fear of uncertainty, or shyness (Cloninger, Svrakic,

& Przybeck, 1993). Thus, in a hypnosis setting, impulsive participants might be more open to follow suggestions because

they worry less about potential harm (e.g., doing something embarrassing; but see Lichtenberg et al., 2004). Moreover,

impulsive individuals are more likely to be extraverted (Eysenck, Pearson, Easting, & Allsopp, 1985; Zuckerman et al.,

1972; see also Eysenck & Zuckerman, 1978; Farley & Farley, 1970). Therefore, impulsive individuals might feel more com-

fortable in certain social situations compared to less impulsive individuals. This might make it easier for them to relax in

a hypnosis group setting and to follow the hypnotist’s suggestions. Indeed, extraversion tends to correlate with hypnotic

suggestibility (Malinoski & Lynn, 1999; Nordenstrom et al., 2002).

A final possible explanation for the link between hypnotic suggestibility and non-planning impulsivity relates to

absorption, ‘‘a disposition for having episodes of ‘total’ attention that fully engage one’s representational [. . .] resources.’’

(Tellegen & Atkinson, 1974, abstract). Absorption has been reported as a correlate of hypnotic suggestibility (e.g., Dixon,

Labelle, & Laurence, 1996; Nadon, Hoyt, Register, & Kihlstrom, 1991; Zachariae, Jorgensen, & Christensen, 2000; but see

Milling, Kirsch, & Burgess, 2000). As previously discussed, non-planning impulsivity is the tendency to focus on the

present rather than to plan for the future. One could speculate that individuals who are present-focussed might be

particularly good at being completely immersed in the present moment (i.e., absorbed); and this might be useful for

responding to hypnotic suggestions. To our knowledge, the relationship between absorption and non-planning impulsiv-

ity has not yet been investigated. However, absorption correlates positively, albeit weakly, with novelty seeking and with

persistence (Cloninger, 1996; Waller, Lilienfeld, Tellegen, & Lykken, 1991). If our results are partly mediated by absorp-

tion, this could explain why we find positive associations of hypnotic suggestibility with both non-planning impulsivity

and self-control.

4.3. Explanations for the link between hypnotic suggestibility and trait self-control

We found that trait self-control positively predicted hypnotic suggestibility, but only when controlling for non-planning

impulsivity in the regression model. Thus, amongst individuals with the same level of non-planning impulsivity, those who

reported themselves to be more self-controlled responded better to hypnotic suggestions. This finding was contrary to our

predictions, but it is in line with a previous study showing a positive association of hypnotic suggestibility with self-reported

perseverance (Lichtenberg et al., 2004). As Cloninger, Zohar, Hirschmann, and Dahan (2012) point out, individuals high in

persistence (related to self-control) tend to be perfectionists and attempt to be very good at everything they do (see also

Tangney et al., 2004). Thus, a potential explanation for the positive link between self-control and hypnotic suggestibility

is that participants with high trait self-control are more motivated to ‘‘perform well’’ during the hypnotic session. They

may therefore pay more attention to the procedure (see also discussion in Lichtenberg et al., 2004). Specifically, self-control

may help individuals to stay focussed on the hypnotic induction allowing them to experience stronger subsequent effects

(e.g., see Gruzelier, 1998).

4.4. Discussion of the lack of a link between attentional impulsivity and hypnotic suggestibility

Attentional impulsivity, the third subtrait of impulsivity, did not predict hypnotic suggestibility. This partly fits with a

number of previous findings showing equal or even better attentional skills in highs compared with lows (e.g., Dienes

et al., 2009; Iani et al., 2006; Kaiser et al., 1997; Kallio et al., 2001; Rubichi et al., 2005; Varga et al., 2011). Moreover, hypnotic

suggestibility has been shown to correlate with scores on the Differential Attention Processes Inventory which includes self-

descriptions of experiences of focused attention and ignoring distractions (Crawford, Brown, & Moon, 1993; Kallio et al.,

2001; Lichtenberg et al., 2004). It makes sense that attentional impulsivity does not positively predict hypnotic suggestibil-

ity, since focused attention is arguably needed during the induction procedure (e.g., see Gruzelier, 1998). However, we also

did not find a negative link between attentional impulsivity with hypnotic suggestibility, indicating that highs do not per-

ceive themselves as being particularly good at concentrating.

4.5. Explanations for the link between motor impulsivity and hypnotic suggestibility in men

Motor impulsivity refers to the tendency to ‘‘act on the spur of the moment’’ and to live an inconsistent lifestyle

(Patton et al., 1995). We found that motor impulsivity tended to predict hypnotic suggestibility in men (with BSC and

non-planning impulsivity held constant). An explanation for this could be that men with high motor impulsivity simply

move impulsively when suggestions for movement are given. However, if this was true, one would expect that motor


impulsivity correlates exclusively with responses to those five suggestions of the HGSHS:A which involve active move-

ment (i.e., direct motor suggestions). Our exploratory analysis did not reveal such a pattern. Instead, the only trend-wise

correlations of impulsivity subtraits with individual suggestions were found for motor challenge/inhibition suggestions

(note, however, that no strong conclusions can be drawn here, as p-values did not survive corrections for multiple

comparisons). Moreover, despite the way it is termed, motor impulsivity is only partly about impulsive movements in

the literal sense. This subscale also includes items about consistency of lifestyle and about more complex impulsive behav-

iours (e.g., ‘‘I buy things on impulse’’, ‘‘I change jobs’’, or ‘‘I make up my mind quickly’’). As such, the link between motor

impulsivity and hypnotic suggestibility in men might also be mediated by high sensation seeking, low harm avoidance, or

high extraversion in men high on motor impulsivity, as argued above for non-planning impulsivity. Nevertheless, it would

be interesting to test for a correlation of hypnotic suggestibility with impulsivity using a scale that contains less motor

suggestions and more perceptual or cognitive suggestions, such as the Waterloo-Stanford Group C Scale of Hypnotic

Susceptibility (Bowers, 1993).

4.6. Possible reasons for the gender difference

For men, motor impulsivity tended to predict HGSHS:A scores (with BSC and non-planning impulsivity held constant),

while it did not predict them for women. Gender differences for the correlates of hypnotic suggestibility have been reported

by several authors (Barber & Calverley, 1964; Bentler, 1963; Bowers, 1971; Dienes et al., 2009; Gur & Gur, 1974). Interest-

ingly, already Lichtenberg et al. (2004) found a correlation of hypnotic suggestibility with the TPQ novelty-seeking subscale

of ‘impulsivity versus reflection’ for men only. Our analyses further showed that men with very lowmotor impulsivity exhib-

ited lower hypnotic suggestibility scores than women with the same level of motor impulsivity (with BSC and non-planning

impulsivity held constant). This may indicate that hypnotic responding partly differs between genders. There is evidence

that the mechanisms of hypnosis may differ for different subtypes of highs (e.g. high dissociative vs. low dissociative highs;

Marcusson-Clavertz et al., 2012; Terhune et al., 2011b). It is therefore also conceivable that the mechanisms of hypnotic

responding differ between men and women. Specifically, for men, hypnotic responding may partly consist of the tendency

to spontaneously and impulsively follow external suggestions. For women, such impulsive processes might not be as

relevant.

Another possibility is that there is a third variable that differentially correlates with motor impulsivity in men and wo-

men, and which correlates with hypnotic suggestibility. Indeed, Eysenck et al. (1985) reported stronger correlations of

impulsivity with extraversion in males than in females. Thus, men with low motor impulsivity might be less extraverted

than women with low motor impulsivity. As discussed above, extraversion tends to correlate with hypnotic suggestibility

(Malinoski & Lynn, 1999; Nordenstrom et al., 2002). This may then explain why men with low motor impulsivity exhibit

lower HGSHS:A scores than women with low motor impulsivity.

A final possible explanation for the discovered gender difference is that participants were influenced by the sex of the

speaker of the hypnosis tape and/or the experimenter interacting with the participants. It has, for example, been shown that

participants tend to help experimenters of the opposite sex more than experimenters of their own sex (Bickman, 1974), and

that male participants behave more competitively when an experiment is led by a woman rather than a man (Deutsch, Can-

avan, & Rubin, 1971). Such effects may also have played a role in the current study. However, it is difficult to guess how ex-

actly they may have led to gender differences in our results, because in this study the experimenters were female and the

speaker of the hypnosis tape was male. Both the sex of the experimenter and of the hypnotist might have influenced

men and women differentially.

4.7. Limitations and suggestions for future research

One limitation of our study is that our sample was restricted to right-handed participants and that the results may not

generalise to left-handed individuals. This is relevant because hypnotic suggestibility and hypnosis might interact with

handedness (e.g., Gur & Gur, 1974; Wallace & Persanyi, 1989). For example, left-handed individuals have been reported

to be more likely to score at the extreme ends of the HGSHS:A (high and low; Baran, 1970).

Regarding the results of the regression analysis, one also needs to keep in mind some limitations. The regressors that are

selected by stepwise multiple regression may sometimes depend on small variations in the data, and there is a risk of over-

fitting, as the procedure automatically selects (one of) the best possible regressor combinations to explain the sample data

(e.g., see Agresti & Finlay, 2009, Chapter 14). Even though the exact composition and the parameters of the final model

should not be over-interpreted, our conclusions are supported by the fact that our results were largely consistent with those

of Lichtenberg et al. (2004). That is, we identified self-control as a predictor of hypnotic suggestibility, while Lichtenberg

et al. identified TPQ persistence as a predictor; and we found that motor impulsivity tended to predict hypnotic suggestibility

in men only, while Lichtenberg et al. found a correlation between impulsivity (a subscale of the TPQ novelty seeking scale)

and hypnotic suggestibility in men only. Moreover, we found a zero-order correlation between non-planning impulsivity and

hypnotic suggestibility without any stepwise regression procedure, and this was significant after stringent correction for

multiple comparisons.

Concerning future research investigating the link between trait impulsivity/self-control and hypnotic suggestibility, we

suggest taking into account whether participants are high or low in dissociative tendencies. Possibly, the relation between


impulsivity subscales and hypnotic suggestibility is more pronounced in high dissociative individuals, as it has been

proposed that altered executive functioning during hypnosis might exclusively play a role in high dissociative highs

(Terhune et al., 2011b). It should also be assessed whether non-planning impulsivity also correlates with suggestibility

outside a hypnotic context. Non-hypnotic suggestibility is highly correlated with hypnotic suggestibility (see Kirsch &

Braffman, 2001).

5. Conclusion

Our findings indicate that hypnotic suggestibility relates to personality traits linked with frontal functioning. That is, indi-

viduals with high non-planning impulsivity (i.e., those who are present-focused and who tend to dislike challenging mental

tasks) and those with high self-control (when holding non-planning impulsivity constant) respond best to hypnotic sugges-

tions. Moreover, in men only, motor impulsivity (i.e., the tendency to act on the spur of the moment and to live an incon-

sistent life style) might be positively linked with hypnotic suggestibility.

Acknowledgments

We thank Professor Walter Bongartz for providing the audio tape and the German questionnaire for the HGSHS:A. We

also thank Brian Tuohy, Andrew Wold, and Lloyd Murdoch for proof-reading and commenting on the manuscript. VUL

was funded by the VW-Foundation, the Berlin School of Mind and Brain and the German National Academic Foundation.

Appendix A.

See Table A1.

Table A1

All steps of the backward stepwise multiple regression procedure.


Model 1 (R2 = .15, F = 2.20, p = .02)

Constant 6.36 0.20 .00 <.001

SRc �0.08 0.07 �.12 .25

BSCc 0.08 0.04 .20 .07

BIS-11 attentionc �0.13 0.10 �.13 .19

BIS-11 motorc 0.04 0.06 .03 .55


Gender 0.29 0.20 .11 .16

SRc � Gender 0.03 0.07 .04 .72

BSCc � Gender 0.02 0.04 .04 .69

BIS-11 attentionc � Gender 0.09 0.10 .10 .35

BIS-11 motorc � Gender �0.08 0.06 �.13 .18

BIS-11 non-planningc � Gender �0.05 0.07 �.08 .43

Model 2 (R2 = .14, F = 2.42, p = .01)

Constant 6.35 0.20 �.01 <.001

SRc �0.08 0.07 �.12 .27

BSCc 0.08 0.04 .20 .07

BIS-11 attentionc �0.12 0.10 �.12 .20

BIS-11 motorc 0.03 0.06 .03 .55


Gender 0.29 0.20 .11 .15

BSCc � Gender 0.02 0.04 .05 .58




Model 3 (R2 = .14, F = 2.67, p = .007)

Constant 6.34 0.20 �.01 <.001

SRc �0.07 0.07 �.11 .29

BSCc 0.08 0.04 .19 .06

BIS-11 attentionc �0.12 0.10 �.12 .21

BIS-11 motorc 0.04 0.06 .33 .51


Gender 0.30 0.20 .06 .15



Table A1 (continued)




Model 4 (R2 = .14, F = 2.96, p = .004)

Constant 6.34 0.20 �.01 <.001

SRc �0.07 0.07 �.11 .32

BSCc 0.07 0.04 .19 .07

BIS-11 attentionc �0.12 0.10 �.12 .20

BIS-11 non-planningc 0.22 0.06 .32 <.001

Gender 0.29 0.20 .11 .15




Model 5 (R2 = .14, F = 3.31, p = .003)

Constant 6.36 0.20 .00 <.001

SRc �0.06 0.07 �.10 .34

BSCc 0.07 0.04 .19 .07

BIS-11 attentionc �0.12 0.10 �.14 .19


Gender 0.29 0.20 .11 .15



Model 6 (R2 = .13, F = 3.76, p = .002)

Constant 6.36 0.20 �.01 <.001

SRc �0.06 0.07 �.10 .36

BSCc 0.08 0.04 .19 .06

BIS-11 attentionc �0.12 0.10 �.14 .19


Gender 0.30 0.20 .12 .14


Model 7 (R2 = .13, F = 4.34, p = .001)

Constant 6.35 0.20 �.01 <.001

BSCc 0.06 0.04 .16 .09

BIS-11 attentionc �0.08 0.08 �.09 .32


Gender 0.32 0.20 .12 .12


Model 8 (R2 = .12, F = 5.19, p < .001)

Constant 6.35 0.20 �.01 <.001

BSCc 0.08 0.04 .20 .03


Gender 0.30 0.20 .12 .13


Model 9 (R2 = .11, F = 6.10, p < .001)

Constant 6.41 0.20 �.01 <.001

BSCc 0.07 0.04 .18 .04



Model 10 (R2 = .13, F = 4.27, p = .001)

Constant 6.35 0.20 �.01 <.001

BSCc 0.08 0.04 .20 .03

BIS-11 motorc 0.04 0.05 .04 .42


Gender 0.31 0.20 .12 .13


Note: Bs are unstandardized, ß are standardized coefficients; R2 are unadjusted; SE: standard error. N = 154. Since the standardized betas calculated by SPSS

for models containing interactions are incorrect (Aiken and West, 1991, pp. 40–47), standardized coefficients were determined as recommended by

Friedrich (1982, p. 824). Due to this procedure, the standardized coefficients for the intercepts are not exactly 0. The c-subscript indicates that variables

were centred. BSC: Brief Self-Control Scale. SR: Self-Regulation Scale. BIS-11: Barratt Impulsiveness Scale.


Appendix B. Supplementary material

Supplementary data associated with this article can be found, in the online version, at http://dx.doi.org/10.1016/

j.concog.2013.04.001.

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Ludwig et al. Supplementary data

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Supplementary data

Text S1. Checking assumptions and validity of the regression model.

We checked the validity and the assumptions of the regression model as follows. To make sure

multicollinearity was in an acceptable range, we checked whether all tolerance values were above .20,

the maximum variance inflation factor (VIF) was not higher than 10, and the average VIF was not

substantially higher than 1 (e.g., see Field, 2005; Menard, 1995). We further assessed the assumption

of homoscedasticity by visual inspection of relevant plots (Field, 2005), and we checked whether

residuals were normally distributed by visual inspection and by a Kolmogorov-Smirnoff test.

Independency of errors was assessed using the Durbin-Watson statistic (Durbin & Watson, 1951).

Finally, we checked for outliers and influential cases by looking for participants fulfilling any of the

following criteria: absolute standardised residuals > 3, Cook’s distance > 1 (Cook & Weisberg, 1982),

centred leverage values > 3 * (k+1)/n , DFBeta values > 1, or Mahalanobis distance > 15 (Barnett &

Lewis, 1978; Field, 2005).

Regression diagnostics indicated that the assumptions of multiple regression had been met and

that the model was not influenced by a small number of cases. That is, multicollinearity was in a very

acceptable range, there was no heteroscedasticity, residuals were normally distributed, and error terms

were independent. Cook’s distances and DFBeta values were all in a very good range, and there were

no outliers concerning the standardised residuals. The only issue arose for 3 participants who had high

Mahalanobis distances (> 15), indicating that they were multivariate outliers. Two of these cases also

had centred leverage values three times higher than average, indicating that they had a relatively high

influence on the model. When exploratively estimating the model again without these three cases, the

same regressors were significant as before. Therefore the cases are not problematic for our

conclusions.


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Text S2. Detailed explanation of the post-hoc procedures for the interaction of motor impulsivity x

gender.

We used the standard recommended post-hoc procedures to explore the significant interaction

of motor impulsivity x gender (Aiken & West, 1991, pp. 130-133; Richter, 2007; West, Aiken, &

Krull, 1996). We carried out four post-hoc tests in total and corrected for multiple comparisons using

Bonferroni-correction (corrected � = .013).

First, we determined if motor impulsivity is a significant predictor of hypnotic suggestibility

for men and/or for women separately by calculating simple slopes for both genders. This was done by

re-estimating the final model again twice using dummy-coding for gender (first, men were coded as 0

and women as 1, and second, women were coded as 0 and men as 1). In regression models containing

an interaction, the single terms that are part of the interaction are conditional effects. That is, they hold

true when the other variable involved in the interaction equals 0 (Hayes, Glynn, & Huge, 2012; West

et al., 1996). Thus, when using dummy-coding for gender, the single term BIS-11 motor impulsivity is

the effect of BIS-11 motor impulsivity for the group coded as 0 (Aiken & West, 1991; p. 131; Hayes

et al., 2012; Richter, 2007). In this way it was possible to determine the effect of motor impulsivity on

HGSHS:A score for men and for women.�

Second, we approached the interaction from the opposite perspective by determining the effect

of gender at very low and very high levels of motor impulsivity (Aiken & West, 1991, pp. 132-133).

In our final model reported in the main text, the beta for the single term gender is the effect of gender

for participants with an average level of motor impulsivity. This is due to centring of our regressors,

which ensured that 0 on the motor impulsivity scale equals an average level of motor impulsivity. As

noted above, the single terms that are part of the interaction hold true when the other variable involved

in the interaction is 0. The fact that the single term gender was non-significant in our final model

therefore means that gender had no effect for participants with an average level of motor impulsivity.

Another way of looking at this is that gender had – on average across all levels of motor impulsivity –

no effect (West et al., 1996). For our post-hoc tests, we rescaled motor impulsivity before estimating

the final model again (these times using dummy coding for gender) to determine the effect of gender


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for participants very high and very low in motor impulsivity (Aiken & West, 1991, p. 132-133). In one

analysis, motor impulsivity was scaled such that 0 was equivalent to the mean of motor impulsivity

minus 2SD; and in the other analysis it was scaled such that 0 was equivalent to the mean of motor

impulsivity plus 2SD. In this way it was possible to determine the effect of gender for participants with

high and with low motor impulsivity.


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Table S1. Descriptive statistics arranged by gender concerning the average scores on the

questionnaires.

Males

(n = 63)

Females

(n = 91)

Gender comparison

Questionnaire Mean SD Mean SD t(152) p Cohen’s d

BSC 42.62 6.39 41.35 6.39 1.21 .23 -.20

SR 30.32 3.83 28.99 3.98 2.069 .04 -.34

BIS-11 Total 61.43 9.15 61.77 8.33 -0.24 .81 .04

- Attention 15.43 3.06 16.03 2.7 -1.292 .20 .21

- Motor 22.94 4.61 22.67 3.81 0.391 .70 -.06

- Non-Planning 23.06 4.16 23.07 4.22 -0.004 1.00 .00

HGSHS:A 6.13 2.74 6.63 2.4 -1.199 .23 .20

Note. SD: standard deviation. BSC: Brief Self-Control Scale. SR: Self-Regulation Scale. BIS-11:

Barratt Impulsiveness Scale. HGSHS:A: Harvard Group Scale of Hypnotic Susceptibility. None of the

p-values survived Bonferroni-correction for multiple comparisons (� = .007). Note that also a

multivariate ANOVA with the outcome variables BSC, SR, BIS-11 Attention, BIS-11 Motor, BIS-11

Non-Planning, and HGSHS:A did not reveal an effect of gender (p = .32).


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Table S2. Number of participants passing each individual suggestion arranged by gender.

Subjects passing

suggestion Difference

Suggestion Type of suggestion Men

Women

�2(1) and

associated p

Odds

ratio

Postural alteration direct motor 65% 78% 3.14, p = .10 0.52

Eye closure direct motor 73% 70% 0.13, p = .86 1.14

Hand lowering direct motor 86% 90% 0.70, p = .45 0.66

Arm immobilization motor challenge/inhibition 48% 49% 0.05, p = .87 0.93

Finger lock motor challenge/inhibition 71% 63% 1.29, p = .30 1.49

Arm rigidity motor challenge/inhibition 49% 47% 0.06, p = .87 1.08

Hands moving direct motor 75% 84% 1.84, p = .22 0.58

Communication

inhibition

motor challenge/inhibition 46% 55% 1.18, p = .33 0.70

Hallucination factorially complex 17% 19% 0.04, p = 1.00 0.92

Eye catalepsy motor challenge/inhibition 40% 59% 5.76, p = .02 0.45

Post-hypnotic

suggestion

factorially complex 33% 46% 2.53, p = .13 0.58

Amnesia factorially complex 10% 2% 4.06, p = .06a 4.68

Note. Nmen = 63, Nwomen = 91. a: an assumption of the chi-square test was not met for this comparison,

because expected frequencies in two cells of the contingency tables were lower than 5. P-values are

two-tailed. No correlation survived Bonferroni-correction for multiple comparisons (� = .004). The

comparison that is significant at an uncorrected level is marked in bold. The reported odds ratio is the

odds ratio for passing a suggestion for men divided by the odds ratio for passing a suggestion for

women.


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Table S3. Point-biserial correlations of motor impulsivity with each individual suggestion for men and

women separately.

Men (n = 63) Women (n = 91)

Suggestion Type of suggestion rpb p rpb p

Postural alteration direct motor .17 .18 .07 .49

Eye closure direct motor .16 .22 .00 1.00

Hand lowering direct motor .19 .13 -.12 .27

Arm immobilization motor challenge/inhibition .29 .02 .05 .63

Finger lock motor challenge/inhibition .14 .26 -.01 .95

Arm rigidity motor challenge/inhibition .06 .63 -.03 .75

Hands moving direct motor .20 .12 -.15 .16

Communication

inhibition

motor challenge/inhibition .24 .06 .05 .64

Hallucination factorially complex .12 .36 -.03 .76

Eye catalepsy motor challenge/inhibition .30 .02 .13 .22

Post-hypnotic

suggestion

factorially complex .18 .16 -.11 .32

Amnesia factorially complex .03 .83 -.15 .17

Note. None of the correlations survive Bonferroni-correction for multiple comparisons within groups

(� = .004). Correlations that are significant at an uncorrected level are marked in bold.


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Table S4. Point-biserial correlations of non-planning impulsivity with each individual suggestion for

all subjects.

Suggestion Type of suggestion rpb p

Postural alteration direct motor .12 .15

Eye closure direct motor -.04 .64

Hand lowering direct motor .16 .053

Arm immobilization motor challenge/inhibition .21 .009

Finger lock motor challenge/inhibition .14 .08

Arm rigidity motor challenge/inhibition .11 .18

Hands moving direct motor .11 .18

Communication inhibition motor challenge/inhibition .16 .045

Hallucination factorially complex -.04 .59

Eye catalepsy motor challenge/inhibition .21 .008

Post-hypnotic suggestion factorially complex .09 .28

Amnesia factorially complex .12 .15

Note. N = 154. None of the correlations survive Bonferroni-correction for multiple comparisons (� =

.004). Correlations that are significant at an uncorrected level are marked in bold.

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Table S5. Point-biserial correlations of the brief self-control scale with each individual suggestion for

all subjects.

Suggestion Type of suggestion rpb p

Postural alteration direct motor -.11 .18

Eye closure direct motor .02 .78

Hand lowering direct motor -.12 .16

Arm immobilization motor challenge/inhibition .05 .53

Finger lock motor challenge/inhibition .15 .07

Arm rigidity motor challenge/inhibition .11 .18

Hands moving direct motor -.05 .53

Communication inhibition motor challenge/inhibition .02 .84

Hallucination perceptual .01 .85

Eye catalepsy motor challenge/inhibition .00 .99

Post-hypnotic suggestion direct motor .03 .76

Amnesia cognitive -.01 .91

Note. N = 154.


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Literature for supplementary data

Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions.

Thousand Oaks, CA: Sage Publications.

Barnett, V., & Lewis, T. (1978). Outliers in statistical data. New York: Wiley.

Cook, R. D., & Weisberg, S. (1982). Residuals and influence in regression. New York: Chapman &

Hall.

Durbin, J., & Watson, G. S. (1951). Testing for serial correlation in least squares regression, II.

Biometrika, 30, 159-178.

Field, A. (2005). Discovering Statistics Using SPSS (2nd ed.). London: Sage Publications Ltd.

Hayes, A. F., Glynn, C. J., & Huge, M. E. (2012). Cautions regarding the interpretation of regression

coefficients and hypothesis tests in linear models with interactions. Communication Methods

and Measures, 6(1), 1-11.

Menard, S. (1995). Applied logistic regression analysis. Sage university paper series on quantitative

applications in the social sciences, 07-106. Thousand Oaks, CA: Sage.

Richter, T. (2007). Wie analysiert man Interaktionen von metrischen und kategorialen Prädiktoren?

Nicht mit Median-Splits! [How to analyze interactions of metric and categorical predictors?

Not with median splits!]. Zeitschrift für Medienpsychologie, 19(3), 116-125.

West, S. G., Aiken, L. S., & Krull, J. L. (1996). Experimental personality designs: Analyzing

categorical by continuous variable interactions. Journal of Personality, 64(1), 1-48.

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Documents

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