the theory of planned behaviour and exercise: an investigation into the role of prior behaviour,...

European Journal of Social Psychology, Vol. 25, 403-415 (199.5)

The theory of planned behaviour and exercise: an investigation into the role of

prior behaviour, behavioural intentions and attitude variability

PAUL NORMAN Department of Psychology, University of Wales Swansea, U.K.

and

LAWRENCE SMITH MRCIESRC Social & Applied Psychology Unit, University of Sheffield, U.K.

Abstract

This paper reports a prospective study which applied the Theory of Planned Behaviour (TPB) to the prediction of exercise behaviour over a six-month period. The study addressed a number of issues which have been identlJied in the literature on the TPB; these being the role of prior behaviour in the TPB, the distinction between desires and selfpredictions, and the question of attitude variability. The findings showed prior behaviour to be the strongest predictor of exercise behaviour at six months. Contrary to expectations, the self-prediction measure was not found to be a better predictor of behaviour than the desire measure. Attitude variability was found to be related to perceptions of control. However, attitude variability was not found to moderate relationships between components of the TPB. The implications of the results for the development of the TPB are discussed.

INTRODUCTION

The Theory of Reasoned Action (TRA: Ajzen and Fishbein, 1980) continues to dominate attitude-behaviour research (Olson and Zanna, 1993). Developed in response to earlier criticisms of attitude research which had focused on the lack of a consistent relationship between attitudes and behaviour (Wicker, 1969), the TRA provides a theoretical account of the way in which attitudes, subjective norms and behavioural intentions combine to predict behaviour. It has been successfully Addressee for correspondence: Dr. P. Norman, Department of Psychology, University of Wales Swansea, Singleton Park, Swansea SA2 8PP.

CCC 0046-2772/95/040403- 13 0 1995 by John Wiley & Sons, Ltd.

Received 17 March 1993 Accepted 30 March 1994

404 P. Norman and L. Smith

applied to the prediction of a range of behaviours (Sheppard, Hartwick and Warshaw, 1988).

According to the TRA, the primary determinant of behaviour is not the person’s attitude towards the behaviour, but his or her intention to perform the behaviour. Behavioural intention is in turn seen to be determined by two factors. First, the person’s attitude towards the behaviour, which refers to the extent to which the person has a favourable or unfavourable evaluation of the behaviour. Second, the subjective norm, or perceived social pressure to perform or not perform the behaviour. These two factors are underpinned by sets of beliefs. For the attitude component the beliefs are behavioural beliefs concerned with the perceived likelihood that performing the behaviour will lead to certain outcomes and the extent to which these outcomes are valued. For the subjective norm component the beliefs are normative beliefs focusing on the perceived social pressure from certain referents and the person’s motivation to comply with these referents.

The TRA is only intended to be applied to the prediction of volitional behaviour. However, the performance of many behaviours is not under complete volitional control. As Ajzen (1988) argues, every behavioural choice is subject to some degree of uncertainty. Thus, in order to extend the TRA to the prediction of non-volitional behaviour, Ajzen (1988, 1991) put forward the Theory of Planned Behaviour (TPB). In addition to the variables to be found in the TRA, the TPB includes a measure of perceived behavioural control which taps the degree to which the behaviour is seen to be under the person’s control. This measure has similarities with a range of constructs including locus of control (Rotter, 1966) and self-efficacy (Bandura, 1986). According to Ajzen (1988), perceived behavioural control should predict behavioural intention and, when people are correct in perceiving that they have control over the behaviour, actual performance of the behaviour. As with the other determinants of behavioural intention, the perceived behavioural control component is underpinned by a set of beliefs. These control beliefs focus on the presence or absence of obstacles, impediments, resources and opportunities.

A number of studies lend support to the inclusion of a measure of perceived behavioural control in the TPB. These have covered several different behaviours including job search activities (van Ryn and Vinokur, 1990), problem drinking (Sche- legel, d’Averna, Zanna, DeCourville and Manske, 1992), biscuit consumption (Sparks Hedderley and Shepherd, 1992), mothers’ infant-feeding behaviour (Beale and Man- stead, 1991) and leisure activities (Ajzen and Driver, 1992). Nevertheless, there are still a number of issues which warrant further investigation.

First, tests of the sufficiency of the TPB are still needed. Earlier tests of the TRA revealed prior behaviour to have an independent influence on behaviour (Bentler and Speckart, 1979; Fredricks and Dossett, 1983). However, Ajzen (1988) argues that the effect of prior behaviour should be mediated by perceived behavioural control. This is consistent with Bandura’s (1986) claim that prior behaviour provides an important source of information about a person’s sense of control. Recent studies examining a range of behaviours including leisure activities (Ajzen, 1991), job search activities (van Ryn and Vinokur, 1990), cheating and lying (Beck and Ajzen, 1991), have found that the addition of prior behaviour has increased the prediction of behaviour over and above that explained by behavioural intention and perceived behavioural control, although the increases in explained variance have been small.

Second, Sheppard et al. (1988) have questioned the way in which behavioural

The theory ofplanned behaviour and exercise 405

intention is measured. Drawing on the work of Warshaw and Davis (1985) which pointed out that behavioural intention has been measured in a number of different ways across different studies, they made the distinction between desires (e.g. ‘I want to . . .’) and self-predictions (e.g. ‘I will . . .). So for example, I may want to take up regular exercise but at the same time think it unlikely that I will do so. Sheppard et al. (1988) argue that self-predictions should provide better predictions of behaviour as they are likely to include considerations of those factors which may facilitate or inhibit performance of a behaviour. For example, if I believe that taking regular exercise is going to be difficult to do (i.e. low perceived behavioural control), then I am unlikely to predict that I will do it. A consequence of this is that perceptions of control should have an important role to play in determining self-predictions. In contrast, to the extent that desire measures reflect motivational factors, attitudes and subjective norms should be better predictors of desires, although perceptions of control may also have a role to play in determining desires. The results of Sheppard et al.’s (1988) meta-analysis of the TRA support these arguments. Measures of self- predictions were found to show the stronger relationship with behaviour, and the attitude and subjective norm components of the TRA were found to be more predictive of desires than of self-predictions. Similar findings are reported by Fishbein and Stasson (1990) who found that the attitude and subjective norm components showed a stronger relationship with a desire measure while perceived behavioural control showed a stronger relationship with a self-prediction measure. However, contrary to the findings of Sheppard et al. (1988), they also found the desire measure to be the stronger predictor of behaviour.

Third, writers interested in discourse processes have pointed to the substantial variation in people’s discourse and the expression of their attitudes (Austin, 1962; Billig, 1989; Gergen and Davis, 1985; Potter and Wetherell, 1987). While some have questioned the utility of the attitude concept (Potter and Wetherell, 1987), the chal- lenge for those working with attitude models such as the TPB is to assess the determinants of attitude variability and the effects this might have on attitude-behaviour relations (Abraham and Sheeran, 1993). At the very least, variability in the expression of attitudes is likely to attenuate any relationships between attitudes, behavioural intentions and behaviour. Unfortunately there have been few studies in this area which have examined the issue of attitude variability. In a recent study looking at the consumption of two common foods, Sparks et al. (1992) compared the attitude- intention correlations obtained for respondents who reported high and low variability in their attitudes and found the correlations to be higher for those respondents reporting low variability. Sparks et al. (1992) also looked at attitude variability and perceptions of control and found the two to be correlated, such that greater attitude variability was associated with lower perceived behavioural control and greater perception of control problems. Thus, Sparks et al. (1992) conclude that perceived behavioural control may be related to attitude variability which may, in turn, modify the relationships between various components of the TPB.

These issues are explored further in the present paper which reports a study apply- ing the TPB to the prediction of exercise behaviour over a six-month period. The issue of exercise behaviour has received a lot of attention in recent years and is seen to be a key component of a healthy lifestyle which people in the U.K. are being encouraged to adopt (DOH), 1989). Various long-term health benefits have been linked with regular exercise. These include reduced cardiovascular morbidity


and mortality (Oberman, 1985) and lowered blood pressure (Blair, Goodyear, Gib- bons and Cooper, 1984) as well as improved self-esteem (Sachs, 1984), positive mood states (Folkins and Sime, 1981) and reduced life stress (Brown, 1991).

On the basis of the literature on the TPB to date a number of specific predictions were made. First, the addition of prior behaviour should increase the amount of variance explained in future behaviour over and above that explained by the TPB (Bentler and Speckart, 1979). Second, self-predictions should be better predictors of behaviour than desires (Warshaw and Davis, 1985). Third, perceived behavioural control should show a strong relationship with self-predictions (Fishbein and Stasson, 1990). Fourth, perceptions of control should be related to attitude variability, such that low perceived behavioural control may be associated with high attitude variability (Sparks et al., 1992). Fifth, attitude variability should modify the relationships between components of the TPB such that stronger relationships should be found among respondents reporting low attitude variability (Sparks et al., 1992).

METHOD

Respondents and procedure

Initial open-ended questionnaires, based on the procedure outlined by Ajzen and Fishbein (1980), were distributed to 18 people in order to elicit salient behavioural, normative and control beliefs. From these responses, questionnaires based on the Theory of Planned Behaviour were distributed to a further 250 people who had been recruited by members of an undergraduate psychology class to participate in the study. Completed questionnaires were returned, in prepaid envelopes, to the authors by 182 respondents (72.8 per cent). Of these respondents, 122 indicated that they would be willing to receive a second questionnaire and gave their name and address so that they could be contacted again. The second questionnaire was sent six months later. Completed questionnaires were returned by 83 respondents (68.0 per cent).

Measures

The first questionnaire sent to respondents contained the following measures. Unless otherwise indicated, all items were rated on seven-point response scales.

Prior behaviour

Respondents were asked to indicate, on average, how frequently they took exercise. Exercise was defined to ‘include activities such as aerobics, badminton, jogging, etc., but not activities which form part of your everyday life, such as walking to the bus stop, dancing at discos, etc. ’ Respondents were asked to indicate how frequently, if at all, they took exercise by circling one of 11 responses ranging from once per month to every day. For analysis, these responses were recoded so that reported frequency was expressed as frequency of exercise per week.


Desires and self-predictions

In line with Fishbein and Stasson (1990), respondents were asked to indicate their desire to take regular exercise (‘I want to take exercise during the next six months), and their self-prediction concerning exercise behaviour (‘I will take exercise during the next six months’) on response scales ranging from extremely unlikely ( - 3 ) to extremely likely (+ 3).

A t t itude

A direct measure of attitude toward taking regular exercise was obtained through the use of six semantic differential scales: worrying-reassuring, unpleasant-pleasant, punishing-rewarding, unenjoyable-enjoyable, useless-useful, and unattractive- attractive (scored -3 to +3) . The coefficient alpha for the summed scale was 0.83.

Attitude variability

Attitude variability was measured using four items (alpha = 0.79); these being, ‘My feelings about taking exercise are sometimes favourable and sometimes unfavourable’, ‘At times, my feelings about taking exercise are more favourable than at others’, ‘I have conflicting feelings about taking exercise’, followed by response scales ranging from disagree very strongly to agree very strongly. The fourth item asked ‘My feelings about taking exercise . . . do not vary at allhary a great deal’.

Subjective norm

In order to obtain a direct measure of subjective norm, respondents indicated whether ‘Most people who are important to me think I should take regular exercise’ on a response scale ranging from extremely unlikely (- 3 ) to extremely likely (+ 3 ) .

Perceived behavioural con fro1

Perceived behavioural control was measured using three items (scored -3 to + 3 ) (alpha = 0.75): ‘For me to take regular exercise is . . , extremely difficult/extremely easy’, ‘How much control do you feel you have over taking regular exercise? (very little controlkomplete control)’, and ‘If I wanted to, I could easily take regular exercise (extremely likely/extremely unlikely)’.

Behavioural beliefs

Seven belief items were employed. The strength of the beliefs (e.g. ‘Taking regular exercise increases agility and suppleness’) was assessed using response scales ranging from extremely unlikely (- 3 ) to extremely likely (+ 3) . For each belief statement there was a corresponding outcome evaluation item (e.g. ‘Increasing agility and suppleness is . . . extremely bad/extremely good’) (scored - 3 to + 3 ) . The products of these ratings were summed to produce an overall measure of behavioural beliefs (alpha = 0.94).


Normative be lie fs

Four referents were identified, these being: members of my family, my friends, the media, and people I know who exercise regularly. Respondents were asked to indicate the likelihood that each of these referents would think that they should take regular exercise (scored - 3 to +3), and whether they were motivated to comply with what they thought (scored 1 to 7). The products of these ratings were summed to produce an overall measure of normative beliefs (alpha = 0.79).

Control beliefs

Respondents were asked to indicate the extent to which a range of factors might prevent them from taking regular exercise. Respondents were asked ‘Which of the following reasons would be likely to stop you from taking regular exercise?’: the factors being, a lack of time, other commitments, laziness, too much effort to do so, too tiring to do so, not being near to facilities, and the possibility of getting aches and pains. Response scales ranged from extremely unlikely (+ 3) to extremely likely ( - 3 ) . The coefficient alpha for the scale was 0.75.

Demographic information

Respondents were asked to indicate their age and sex. The second questionnaire sent out six months later, contained only one measure.

Exercise behaviour

This measure was the same as that asked in the first questionnaire (a), and asked respondents to indicate how frequently they took exercise.

RESULTS

Correlations

The first stage in the analysis of the data was to correlate the variables under consider- ation with future exercise behaviour (see Table 1). With the exception of the normative belief component, all variables from the TPB correlated highly with future exercise behaviour, as did prior exercise behaviour. Thus frequent exercisers at time 2 were more likely at time 1 to believe that they would take regular exercise, to hold a strong desire to take regular exercise, to have a positive attitude towards taking regular exercise, to perceive social pressure from important others to take exercise, to believe that taking exercise would be under their control and lead to positive outcomes, to perceive few barriers to taking exercise, and to have exercised frequently in the past.

Regressions

In order to assess the predictive value of the components of the TPB in more detail, an hierarchical regression analysis was conducted on the data. Five ‘blocks’ of vari-

Tabl

e 1.

Zer

o-or

der c

orre

latio

ns b

etw

een

varia

bles

(n =

83)

BE

HA

V

SP

DE

S A

TT

SN

PB

C

BB

NB

C

B

PRIO

R A

GE

SE

X

SP

0.38

***

DES

0.

43**

* A

TT

0.52

***

SN

0.24

* PB

C

0.50

***

BB

0.37

***

NB

0.

02

CB

0.38

***

PRIO

R

0.68

***

AG

E

0.11

SE

X

0.14

M

ean

2.82

S.

D.

2.25

0.51

***

0.42

***

0.27

" 0.

51**

* 0.

30**

0.

27*

0.28

**

0.55***

0.20

-0

.19

1.66

1.

77

0.56

***

0.30

**

0.37

***

0.39

***

0.16

0.

28**

0.

48**

* 0.

06

-0.0

1 2.

23

1.35

0.42

***

0.41

***

0.58***

0.28

**

0.45

***

0.50

***

0.17

0.

05

1.91

0.

92

0.15

0.

32**

0.

67**

* 0.

30**

0.

33**

0.

18

0.04

1.

27

1.75

0.20

0.

05

0.15

0.

47**

* 0.

27*

0.62

***

0.26

* 0.

04

0.32

**

0.19

0.

10

1.20

5.

87

1.48

2.

91

2

i? 0.

07

2 F m 0 5

5.12

0.

61

2.71

29

.89

1.39

%

0.14

0.

44**

* 0.

17

0.21

0.

16

0.02

0.

20

0.16

0.

02

6.70

1.

15

2.26

9.

27

0.47

~~

~ *p

< 0

.05;

**

p <

0.0

1; *

**p

< 0.

001.

g 6'

P

0

\o


Table 2. Multivariate hierarchical regression of T2 exercise behaviour

Steplpredictor R2 h R2 F Beta

1. SP DES

2. ATT SN

3. PBC

4. BB NB CB

5. PRIOR AGE SEX

-0.05 0.22 0.22 11.16*** 0.03

0.18 0.31 0.09 8.80*** 0.04

0.38 0.07 9.30*** 0.08

0.12 -0.14

0.41 0.03 6.39*** -0.01

-0.02 0.54 0.13 7.61*** 0.01

0.53***

* * * p < 0.001.

ables were used in order to predict time 2 exercise behaviour: (i) self-predictions and desires, (ii) attitude and subjective norm, (iii) perceived behavioural control, (iv) behavioural, normative and control beliefs, and (v) prior exercise behaviour, age and sex. The data was first examined to assess potential problems of multicolli- nearity (Bryman and Cramer, 1990). No evidence was found to suggest that this might be a serious problem in the present data set.

The results of the regression analysis are presented in Table 2. The self-prediction and desire measures accounted for 22 per cent of the variance in time 2 exercise frequency. The addition of the attitude and subjective norm components contributed a further 9 per cent (Fchange = 5 . 2 5 , ~ < 0.01). The addition ofperceived behavioural control increased the amount of variance explained by 7 per cent ( F change = 8.03, p < 0.01) to 38 per cent. At this stage, only attitude (beta = 0.31, p < 0.05) and perceived behavioural control (beta = 0.32, p < 0.01) made significant contributions to the equation. The addition of the belief-based measures failed to produce a significant increment (3 per cent) ( F change = 1.33, n.s.), but the addition of prior behaviour, age and sex led to an increment of 13 per cent ( F change = 6.80, p c 0.001) bringing the total amount of variance explained to 54 per cent. Only prior behaviour (beta = 0.53, p < 0.05) made a significant contribution to the final equation.

Desires and self-predictions

It was hypothesized that the self-prediction measure would be a better predictor of behaviour than the desire measure. Both measures were found to correlate with time 2 exercise behaviour, with the desire measure showing a slightly stronger correlation (see Table 1). However, the two correlations were not found to be significantly different ( t = 0.51, n.s.).

The correlates of desires and self-predictions were considered next. Both measures were correlated with attitude, subjective norm and perceived behavioural control using the full data set for the time 1 measures (n = 182) (see Table 3). Considering self-predictions firstly, significant correlations were obtained with each variable with the attitude component producing the highest correlation. However, more detailed

The theory ofplanned behaviour and exercise 41 1

analysis revealed the attitude correlation to only be higher than the subjective norm correlation (t = 3.06, p < 0.01). Each component was also found to correlate with the desire measure. The correlation with attitude was found to be higher than both the subjective norm ( t = 3.29, p < 0.01) and perceived behavioural control ( t = 2.39, p < 0.05) correlations. Finally, the correlations obtained for self-predictions and desires for each component were compared. These were found to be of a similar magnitude; no significant differences were found between the correlations.

Table 3.Zero-order correlations between attitudes, subjective norms and perceived behavioural control and self-predictions and desires (n = 182)

SP DES ATT 0.51*** 0.52*** SN 0.27** 0.25** PBC 0.43** 0.35** **p < 0.01; ***p < 0.001.

Table 4. Comparison of correlations for low (n = 93) and high (n = 88) attitude variability groups

Correlations Low A.V. High A. V. Z..h ATT-SP 0.43*** 0.54*** 0.93 n.s. ATT-DES 0.39*** 0.54*** 1.26 n.s. ATT-BB 0.64*** 0.49*** 1.45 n.s.

***p < 0.001.

Attitude variability

The analyses with attitude variability were conducted on the full time 1 data set (n = 182). Attitude variability was found to correlate with both perceived behavioural control ( r = -0.29, p < 0.001) and control beliefs ( r = -0.39, p < 0.001), such that greater reported attitude variability was associated with lower perceived control and the perception of more potential barriers to taking regular exercise.

The next stage in the analysis was to examine the relationships between the attitude, desire, self-prediction and behavioural belief measures for respondents who reported themselves to have either high or low attitude variability. Respondents were therefore separated into two groups on the basis of a median split on the attitude variability measure. As can be seen from Table 4, no differences were found between the size of the attitude-desire, attitude-self-prediction and attitude-behavioural belief correlations obtained for the low (n = 93) and high (n = 90) attitude variability groups.

DISCUSSION

The present study sought to apply the Theory of Planned Behaviour (TPB) to the prediction of exercise behaviour over a six-month period. Particular attention was


paid to the role of prior behaviour in the TPB, and to the distinction between desires and self-predictions. In addition, the issue of attitude variability and how it might modify the relationships within the TPB was also addressed.

The results of the study showed that the self-prediction and desire measures together with the attitude, subjective norm and perceived behavioural control components of the TPB were able to predict 38 per cent of the variance in time 2 exercise frequency, with the attitude and perceived behavioural control making significant contributions to the regression equation. So, those respondents who held a positive attitude towards taking exercise and believed that taking exercise would be under their own control, were more likely to take regular exercise six months later. However, the addition of prior behaviour improved the prediction of time 2 exercise frequency. In fact, prior behaviour was found to be the only variable to make a significant contribution to the final regression equation. Thus, prior behaviour was found to have a direct influence on future exercise behaviour, which is in line with earlier studies (Bentler and Speckart, 1979; Fredricks and Dossett, 1983) which have examined the role of prior behaviour in the Theory of Reasoned Action. Bentler and Speckart (1979) have suggested that prior behaviour should be considered as an independent variable in the model. However, Ajzen (1987) has argued that prior behaviour cannot be considered to be a causal factor in the same way as the other variables in the model, as it has no explanatory value. Furthermore, according to Ajzen (1988), the addition of perceived behavioural control should allow for the mediation of the effects of prior behaviour, although this was not found to be the case in the present study. Nevertheless, the perceived behavioural control component does appear to represent a useful addition to the TRA inasmuch as its inclusion led to a significant increment in the amount of variance explained over and above that explained by the TRA variables.

The role of prior behaviour in the TPB is an issue which clearly warrants further investigation. Dishman (1982), in relation to clinical exercise programmes, has made the distinction between the initiation and maintenance of behaviour, arguing that only the initiation of behaviour is determined by cognitive variables. Moreover, there is evidence to suggest that continued exercise enhances the neurotransmission of norepinephrine, serotonin and dopamine (Ransford, 1982) which leads to improved mood and therefore reinforces exercise behaviour. Thus, there may be a strong habitual influence on exercise behaviour. This coincides with the views of Ronis, Yates and Kirscht (1989), who, in examining the determinants of repeated behaviour, made the distinction between habits and decisions. They argued that the performance of certain behaviours may be based on habit rather than cognition. However, in terms of the TPB, it is necessary to disentangle the influences of habit and prior behaviour. Prior behaviour may influence reasoned responses (Ajzen, 199 1); for example, it can give information about the ease or difficulty of performing a behaviour. Alternatively, when repeated on many occasions prior behaviour may lead habitual responses (Ronis et al., 1989); that is, it may lead to behaviour being performed without conscious thought. As Ronis et al. (1989) suggest, future work needs to develop measures of habit which show discriminant validity with respect to frequency of prior behaviour.

The present study addressed the distinction between desires and self-predictions (Warshaw and Davis, 1985). In their meta-analysis of the TRA, Sheppard et al. (1988) found self-prediction measures to be better predictors of behaviour. However,


Fishbein and Stasson (1990) assessed the predictive role of desires and self-predictions within a single study and found the desire measure to be a better predictor than the self-prediction measure. In the present study no difference was found between the measures in the extent to which they correlated with time 2 exercise behaviour. In relation to the determinants of self-predictions and desires, each measure was found to correlate with the attitude, subjective norm and perceived behavioural control components of the TPB. Thus, no special role was found for perceived behavioural control in determining self-predictions. It should be noted though that in the present study the two behavioural intention measures were moderately correlated, so while it may be possible to make the distinction between desires and self- predictions on conceptual grounds it may be more difficult to make the distinction empirically. The operationalization of these constructs is clearly an issue which warrants further investigation.

Sparks et al. (1992) argued that perceptions of control should be related to attitude variability. As with their study, the present results showed that those respondents who reported greater variability in their attitudes were likely to perceive less behavioural control and more potential barriers to taking regular exercise. As such, the perception of control problems may lead to more variable attitudes. In relation to the TPB, the important point to make about attitude variability is that it may modify the relationships between the model’s variables. In particular, attitude variability may attenuate the relationship between the attitude and behavioural intention measures. However, the present study failed to find any differences between the size of these correlations obtained for respondents who reported high or low attitude variability. These results contrast with those of Sparks et al. (1992), although in their study attitude variability only consistently moderated the attitude-intention relationship for the consumption of biscuits and not for wholemeal bread consumption. Future empirical work needs to focus on the conditions which may lead to attitude variability and the consequences of this for attitude-behaviour relations (Abraham and Sheeran, 1993).

In conclusion, the current findings have a number of implications for the development and continued use of the TPB. First, there is a clear need for further theoretical and empirical work on the role of prior behaviour and habit in the TPB. Second, the distinction between desires and self-predictions is one which is worthy of further investigation, particularly in relation to predicting behaviour, but also in relation to understanding the relationships between constructs within the TPB. Finally, future work may also address the issue of attitude variability in more detail.

ACKNOWLEDGEMENT

The authors would like to thank Mark Conner and the anonymous reviewers for their comments on an earlier draft of this article.

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