Combining motivational and volitional interventions to promote exercise participation: Protection motivation theory and implementation intentions

Combining motivational and volitionalinterventions to promote exercise participationProtection motivation theory andimplementation intentions

Sarah Milne1 Sheina Orbell2 and Paschal Sheeran3

1University of Bath UK2University of Essex UK3University of Shef eld UK

Objective This study compared a motivational intervention based on protectionmotivation theory (PMT Rogers 1975 1983) with the same motivational interventionaugmented by a volitional intervention based on implementation intentions (Gollwitzer1993)

Design The study had a longitudinal design involving three waves of data collectionover a 2-week period incorporating an experimental manipulation of PMT variables atTime 1 and a volitional implementation intention intervention at Time 2

Method Participants (N = 248) were randomly allocated to a control group orone of two intervention groups Cognitions and exercise behaviour were measured atthree time-points over a 2-week period

Results The motivational intervention signi cantly increased threat and copingappraisal and intentions to engage in exercise but did not bring about a signi cantincrease in subsequent exercise behaviour In contrast the combined protectionmotivation theoryimplementation intention intervention had a dramatic effect onsubsequent exercise behaviour This volitional intervention did not in uence behav-ioural intention or any other motivational variables

Conclusions It is concluded that supplementing PMT with implementationintentions strengthens the ability of the model to explain behaviour This hasimplications for health education programmes which should aim to increase bothparticipantsrsquo motivation and their volition

163

British Journal of Health Psychology (2002) 7 163ndash184copy 2002 The British Psychological Society

wwwbpsorguk

Requests for reprints should be addressed to Sarah Milne Department of Psychology University of Bath Claverton DownBath BA2 7AY UK (e-mail SEMilnebathacuk) Sarah Milne has also published articles relating to this subject under thename of Sarah Hodgkins

Coronary heart disease (CHD) is one of the most signicant causes of death in modernindustrial societies Indeed 44 of all deaths of the UK in 1994 were attributed tocardiovascular disease (British Heart Foundation 1996) Approximately 300 000 heartattacks are experienced in the UK (British Heart Foundation 1996) and 11

2million in

the USAeach year (American Heart Association 1995) Of these more than a third willresult in death In a recent review Miller Balady and Fletcher (1997) reported anaccumulation of evidence to show that a physically inactive lifestyle doubles the risk ofdeveloping CHD Regular exercise has been shown to prevent CHDby decreasing levelsof cholesterol and fat in the bloodstream and by lowering blood pressure This in turndramatically reduces the primary cause of CHD atherosclerosis the build-up of fattydeposits on the artery walls (Bouchard amp Despres 1995) Although atherosclerosisoften leads to CHD in middle age the process occurs throughout life Thus to havethe best chance of lowering the risk of CHD preventive habits need to be developedat an early age (Clarkson Manuck amp Kaplan 1986) The greatest decrease in exerciseparticipation throughout life occurs during late adolescence (Stephens Jacobs ampWhite 1985) Bauman Owen and Rushworth (1990) found that only25of Australiansunder 20 years of age engaged in regular exercise Makrides Veinot Richard McKeeand Gallivan (1998) found that fewer than half of the students in a Canadian universityparticipated in regular exercise This suggests that an intervention designed to increaseexercise participation among young adults would be of considerable value

Many researchers and practitioners aiming to develop health education interven-tions to promote precautionaryactions such as exercise have turned to social cognitivemodels of behaviour One such model which has been shown to be useful in theprediction of and intervention in health-related behaviours is protection motivationtheory (PMT Rogers 1975 1983 For recent literature reviews see Boer amp Seydel 1996Rogers amp Prentice Dunn 1997 For meta-analytic reviews see Floyd Prentice-Dunn ampRogers 2000 Milne Sheeran amp Orbell 2000)

The model proposes that protection motivation is the variable that lsquoarouses sustainsand directs activityrsquo and is operationalized in terms of peoplesrsquo intentions to performa recommended precautionary behaviour Intention is inuenced by two processesthreat appraisal and coping appraisal Threat appraisal concerns the evaluation of thecomponents of a fear appeal relevant to an individualrsquos perception of how endangeredhe or she feels by a threat disease(s) The PMT variables involved in threat appraisalare perceived vulnerability perceived severity and fear arousal An individual perceiv-ing the threat to be high will be more likely to be motivated to adopt the recom-mended protective behaviour Coping appraisal evaluates the components of a fearappeal that are relevant to an individualrsquos assessment of the recommended copingresponse to the appraised threat Coping appraisal involves beliefs about responseefcacy self-efcacy and response costs An individual will be more likely to intendto adopt the recommended coping response if he or she believes that the response willbe effective feels able to perform the recommended behaviour and perceives thebehaviour to be low in cost (see Boer amp Seydel 1996 Floyd et al 2000 Milne et al2000 Rogers amp Prentice-Dunn 1997 for more detailed description of the model andits measurement)

Unlike other social cognitive models of health-related behaviour such as the theoryof reasoned action (TRA Ajzen amp Fishbein 1980) and the theory of planned behaviour(TPB Ajzen 1985) PMT has been subjected to several experimental tests Studies havemanipulated PMT variables within a fear-arousing communication in order to explorethe effects of the intervention on subsequent beliefs intentions and behaviour Three

164 Sarah Milne et al

studies have explored the effects of manipulating PMT variables on exercise cognitionsintention and behaviour (Fruin Pratt ampOwen 1991 StanleyampMaddux 1986 Wurtele ampMaddux 1987) Fruin et al and Stanley and Maddux examined cognitions and intentionswhile Wurtele and Maddux also included a measure of subsequent behaviour All threeinterventions were successful in changing PMT cognitions Self-efcacy was found topredict intention to exercise in all three studies whereas Stanleyand Maddux found thatperceived response efcacyalso inuenced intention to exercise Perceived vulnerabilityto heart disease and stroke was the onlythreat or coping appraisal variable that predictedparticipation in aerobic exercise (Wurtele ampMaddux 1986) These ndings indicate thatexperimental manipulations are generally very effective in inuencing subsequentcognitions and intention However in a recent review Milne et al (2000) have shownthat their effectiveness in inuencing subsequent behaviour is more limited

Difculties arise in applying such experimental manipulations to real-world healtheducation intervention programmes This is because it is not generally practical orethical in health education settings to provide participants with false information inorder to manipulate the levels of a variable (eg to tell participants that heart disease isnot a serious condition in order to produce lsquolowrsquo perceived severity) There is also thedifculty that most experimental tests of PMT involve two experimental groups (onereceiving eg a lsquohighrsquo severity communication and the other receiving a lsquolowrsquo severitycommunication) but do not include a control condition in which participants receiveno information (eg Fruin et al 1991 Maddux amp Rogers 1983 Rippetoe amp Rogers1987 Wurtele 1988) Thus it is unclear how successful the interventions are relativeto not receiving the intervention (see however Sturges amp Rogers 1996 Tanner Day ampCrask 1989) In a real-world health education intervention the effects of providingfactual information would be compared with a no information condition

Three studies have examined the effects on behavioural intentions of a PMT-basedhealth education intervention employing factual information (Boer amp Seydel 1996Seydel Taal amp Weigmen 1990 Steffen 1990) In these studies one group receivedinformation about the health threat and recommended response and a control groupreceived no information (eg Seydel et al showed an experimental group an educa-tional TV lm about cancer while the control group watched a programme about anunrelated topic) These interventions have not been as successful in bringing aboutcognition or intention change as interventions involving two experimental groups(Milne et al 2000) To our knowledge only one factually based health interventionstudy (Seydel et al 1990) examined subsequent behaviour They found that a healtheducation communication based on PMT variables had no effect on the behaviourof ordering leaets about cancer Thus research is needed to nd the best ways ofmanipulating PMT variables within a factual health education intervention and toestablish the effect of such a health education intervention on subsequent behaviourThe rst aim of the present study was to examine the effects of a factual healtheducation intervention based on all PMT variables on subsequent PMT cognitionsintention and behaviour

Another important issue is that the success of the intervention tends to be mea-sured immediately following the manipulation in PMT intervention studies Thuscognitive change is measured when the information is still fresh in the minds of theparticipants (Wurtele amp Maddux 1987) In real-life health education settings it isimportant to establish that the effects of an intervention last over time The presentstudy is the rst to include all PMT variables in a longitudinal health educationintervention study (cf Milne et al 2000) and to measure the stability of the effects

Motivation and volition 165

of the intervention on subsequent changes in cognitions intention and behaviour ina longitudinal design

As discussed above PMT has been found to account well for intention to changebehaviour However the modelrsquos ability to explain subsequent behaviour is morelimited (Floyd et al 2000 Milne et al 2000) This reects accumulating evidence tosuggest that social cognitive models of health-related behaviour are generally moresuccessful at predicting intention than behaviour (Norman amp Conner 1996) Thusthese accounts can be viewed as adequate accounts of motivation (intention) How-ever motivation to perform a behaviour does not automatically translate into action andresearch has recently turned to an investigation of the volitional processes involvedin behavioural enactment

According to Gollwitzer (1993) and Heckhausen (1991) motivation is just thestarting point for behavioural performance They propose a model of action phaseswhich suggests that adopting a behaviour has two distinct stages The rst is amotivational or deliberative phase during which the individual weighs up the costsand benets of performing the behaviour This phase parallels the view of intentionformation offered byPMTand culminates in the development of a behavioural intentionUnlike PMT Gollwitzer and Heckhausen (Gollwitzer 1993 Gollwitzer Heckhausenamp Steller 1990 Heckhausen 1991 Heckhausen amp Gollwitzer 1987) also posit a post-intentional or volitional phase during which the individual develops strategies andplans in order to ensure that their intention will be enacted Thus the model of actionphases suggests that behaviour is most likely when the individual is both motivatedto act and has developed strategies and plans which promote behavioural enact-ment This suggests that a motivational model such as PMT could usefully be supple-mented by volitional strategies in order to increase the likelihood of performing healthbehaviours

One volitional strategy that has received empirical support over recent years is theconcept of implementation intentions (Gollwitzer 1993 1996 Gollwitzer amp Brand-statter 1997 For a discussion of implementation intentions in relation to health goals seeGollwitzer amp Oettingen 2000) Gollwitzer (1993) draws a distinction between a goalintention (eg lsquoI intend to exercisersquo) and an implementation intention which isa specic action plan concerning exactlyhow when and where an intended goal-directedbehaviourwill be enacted (eg lsquoIwill exercise bydoing mystep-aerobic video in the livingroom at 600 pm when I get in from workrsquo) Implementation intentions have been foundto dramatically increase the likelihood of performing health behaviours in many experi-mental studies (for a discussion of the role of implementation intentions in healthpsychology see Gollwitzer amp Oettingen 2000) The TPB (Ajzen 1985) to predictbehaviour has been found to greatly increase with the addition of an implementationintention intervention For example in an earlier study Orbell Hodgkins and Sheeran(1997) we found that 100 of women who formed an implementation intentionconcerning where and when they would perform breast self-examination subsequentlyperformed the examination compared with just 53 of the control group SimilarlySheeran and Orbell (1999) found that participants were less likelyto miss taking vitaminsupplements if they were induced to form implementation intentions concerning whereand when they would take a pill each day TPB was also found to predict cervical smearscreening attendance when augmented with implementation intentions (Sheeran ampOrbell 2000) Other studies have shown implementation intentions to be effective inincreasing functional activity following joint replacement surgery (Orbell amp Sheeran2000) and in increasing healthy eating (Verplanken amp Faes 1999)


According to Gollwitzer (1993 1996) the formation of implementation intentionsserves to delegate control of the behaviour to the environmental cues specied in theimplementation intention Thus implementation intentions aid performance of beha-viour because when the specied conditions are met the environmental cues stimulateautomatic activation of behaviour Thus the opportunity for action is not missed even ifit presents itself for only a eeting moment This view is supported by ndings showingthat participants are extremely likely to perform the behaviour at the time and in thelocation they had previously specied in their implementation intentions (eg Orbell etal 1997 Sheeran amp Orbell 1999) The formation of a goal intention on its own is notsufcient to produce this effect (Gollwitzer 1993 Gollwitzer amp Brandstatter 1997)Moreover forming an implementation intention will not on its own inuencebehaviour Implementation intentions must be preceded by a goal intention This isbecause implementation intentions work in the service of goal intentions (Gollwitzer1993)

As discussed previously PMT has an advantage over TPB in health research as ithas often been implemented in experimental manipulation studies Thus the successof implementation intentions in increasing prediction of behaviour within the TPBframework suggests that combining a motivational intervention based on PMT with avolitional intervention based on implementation intentions would be more likely toincrease exercise behaviour than a motivational intervention alone This study addsto the growing literature on the role of implementation intentions in health psy-chology by assessing their utility within the framework of PMT It is also the rststudy to augment a motivational manipulation with an implementation intentionintervention

The specic aims of the study were

(i) To assess the effect of a motivational intervention employing a health edu-cation leaet which addresses all PMT variables (ie perceived vulnerability per-ceived severity fear response efcacy self-efcacy and response-costs) on subsequentchanges in exercise cognitions intention and behaviour The following hypotheseswere tested

Hypothesis 1 The PMT-based motivational intervention will increase perceptionsof vulnerability perceived severity fear self-efcacy and response efcacy andreduce perceived response costsHypothesis 2 The motivational intervention will increase intention to engage inat least one 20-minute session of exercise over the following weekHypothesis 3 The effects of the motivational intervention on PMT cognitionsand intention will remain stable over the three time points of the study

(ii) To determine whether supplementing a motivational PMT-based interventionwith an implementation intention intervention will improve the likelihood of adoptingexercise behaviour We formed two hypotheses

Hypothesis 4 The addition of a volitional intervention forming an imple-mentation intention to the PMT-based motivational intervention will increaseparticipation in at least one 20-minute session of exercise over the followingweekHypothesis 5 Participants who form implementation intentions will engage inexercise on the day and at the time and place specied in their implementationintention


Method

Sample detailsThe sample comprised undergraduate students at a UK university Participation wasvoluntary with course credits offered to those who participated at all three time pointsTwo hundred and ninety-six questionnaires were distributed at Time 1 of which 273were completed Two hundred and fty participants completed the questionnaires at allthree time points Two participants were eliminated from the sample for medicalreasons The nal sample was N= 248 a response rate of 84 of the questionnairesdistributed at Time 1 T-tests were carried out to ensure that participants who droppedout of the study at Time 2 or Time 3 did not differ on previous behaviour intention andthe PMT variables compared with those who completed all three questionnaires Therewere no signicant differences on any variables which suggests that the nal samplewas representative Seventy-three per cent of the sample were women The age rangewas 18ndash34 years (M= 2004 SD= 223) Participants were randomly allocated to one ofthree groups experimental group 1 who received only the motivational intervention(N= 93) experimental group 2 who received both the motivational intervention andthe volitional intervention (N= 79) and a control group (N= 76) who received neitherintervention

Study design and procedureThe study took the form of a longitudinal study involving three waves of datacollection over a 2-week period The study incorporated an experimental manipula-tion of PMT variables at Time 1 and a volitional intervention at Time 2 The studywas presented to participants as an investigation of young adultsrsquo attitudes andbehaviour patterns concerning regular exercise At Time 1 participants were askedto complete background questions concerning their age gender and exercisebehaviour patterns over the previous week month and year They were told thatan exercise session must be at least 20 minutes long and should be enough to causea noticeable increase in heart rate ie lsquoa pounding sensationrsquo In addition theywere told that an exercise session longer than 20 minutes (eg 1 hour of exercise)counts as one session

The motivational intervention was administered in the Time 1 questionnaire follow-ing the background questions Participants in experimental groups 1 and 2 were askedto read a health education leaet The leaet provided factual information about CHDand the benets of exercise and was based on PMT variables The control group wereasked to read the opening three paragraphs of a novel

At Time 1 PMT variables and intention were measured immediately after themotivational intervention One week later (Time 2) participants were asked howmany times they had engaged in at least one 20-minute session of exercise over thelast week All participants then completed the PMT and intention measures a secondtime Experimental group 2 was also asked to form an implementation intentionregarding when and where they would carry out exercise in the following week Allthree groups received the third questionnaire 1 week later (Time 3) which againassessed PMT variables intention and behaviour In addition participants were askedwhen and where they had engaged in exercise and why they had not exercised if theyhad intended to do so


Interventions

Protection motivation theory variablesThe PMT constructs were manipulated using a factual health education leaet contain-ing information about the prevalence and nature of CHD and the effects of exercise onpreventing the disease The leaet was checked for validity by a hospital consultant inpulmonary function and general medicine Each PMT variable was manipulated in theleaet Participants in experimental groups 1 and 2 were told that lsquoThe followingpassage presents a true account of the effect exercise has on reducing the risk ofcoronary heart diseasersquo

Perceived severity was manipulated by outlining the painful and debilitating effectsof CHD

The effects of angina can cause severe pain and distress and lead to the inability to walkfor even short distances When a coronary artery has become narrowed due to CHDit can more easily become blocked by an obstructing deposit or a blood clot This causesthe heart muscle to become sufcientlyshort of blood for part of it to die This is the cause ofa heart attack This is a medical emergency and often proves fatal in severe cases

Perceived vulnerability was manipulated using two statements to increase thebelief that young adults who do not exercise are vulnerable to developing CHD in thefuture

the process (atherosclerosis the process of fatty deposit build-up on the coronary arterywall) occurs throughout life This means that the arteries are progressively narrowing untiltheyare so narrow that CHDoccurs If a young adult does not engage in regular exerciseatherosclerosis is already causing progressive narrowing of the coronary artery

Response efcacy was manipulated by explaining the effectiveness of exercise inpreventing CHD

Preventative action can be taken and the earlier in life it starts the quicker the processof atherosclerosis will halt and the lower the risk of CHD will be Regular (at least one20-minute session a week) vigorous exercise such as sports swimming aerobics dancingrunning or walking briskly has been shown to prevent CHD by decreasing the levels ofcholesterol and fat in the bloodstream and lowering blood pressure Reduced blood levelsof fat and cholesterol and lower blood pressure have both been shown to dramatically slowdown the build-up of fatty deposits on the artery walls

Participants were also told that lsquoMost young adults who have stuck to a regularexercise program have found it to be very effective in reducing their chances ofdeveloping CHDrsquo

Self-efcacy was manipulated in two ways rst by suggesting that it would be easyfor participants to engage in exercise lsquoMost young adults have the cognitive andphysical ability to engage in regular exercise Indeed the Sports Council hold thatanyone can nd an exercise that they are able to dorsquo

Bandura (1991) suggests that the best way to increase an individualrsquos perceived self-efcacy is to provide direct experience It is not always practical to incorporate directexperience into health education Another way of inducing experience is by use ofimagination

The following tactic was therefore also used to manipulate self-efcacy lsquoIf anindividual doubted their ability to nd an exercise they could do it would be useful toimagine themselves doing a few different exercises and they would soon nd one theyfelt condent in tryingrsquo


Response costs were manipulated by the statement lsquoAlthough adopting a regularexercise does have its costs most young adults nd these to be very minor and easilyovercome and nd that the benets of a regular exercise programme far outweigh thecostsrsquo

Implementation intentionsFollowing previous studies (Gollwitzer 1993 Gollwitzer amp Brandstatter 1997 Orbellet al 1997) participants in experimental group 2 were asked to form an implementa-tion intention specifying where and when they would engage in exercise over thecoming week The following passage was presented after the measures of PMTvariables intention and behaviour at Time 2

Manypeople nd that they intend to take at least one 20-minute session of vigorous exercisebut then forget or lsquonever get around to itrsquo It has been found that if you form a denite planof exactly when and where you will carry out an intended behaviour you are more likely toactually do so and less likely to forget or nd you donrsquot get round to doing it It would beuseful for you to plan when and where you will exercise in the next week

They were then asked to complete the following statements

During next week I will partake in at least 20 minutes of vigorous exercise on (day ordays)______________ _ at ______________ _ (time of day) ator in (place)_______________

Measures

Protection motivation theory variablesPMT variables were measured on 7-point Likert scales comprising belief statementscoupled with appropriate response items Items measuring the PMT constructs andintention were randomized in such a way that patterns of questions were less obviousto the participants (cf Sheeran amp Orbell 1996) Measures of PMT variables were thesame at all three time points (see Appendix 1 for measures of PMT constructs includingintention) In addition to the PMT items 4 items assessed previous exercise behaviourat Time 1 lsquoHow many times did you partake in vigorous exercise for at least 20 minutesover the last month (eg sport swimming aerobics dancing running or walkingbriskly)rsquo lsquoDid you engage in vigorous exercise for at least 20 minutes last week(yesno)rsquo lsquoIf so how many timesrsquo and lsquoOver the last year I have engaged in vigorousexercise for at least 20 minutes (every weekndashnever)rsquo These measures were taken priorto the manipulation of PMT variables There were also two measures of subsequentbehaviour taken before the implementation intention intervention at Time 2 and againat Time 3 lsquoDid you engage in at least one 20-minute session of vigorous exercise lastweek (yesno)rsquo and lsquoIf so how many sessions did you partake inrsquo

Other measuresAt Time 3 participants were asked when and where they participated in exercise inorder to compare actual times and places in which the exercise took place with thosespecied in their implementation intentions An open-ended question was also includedat Time 3 asking participants lsquoIf you intended to partake in at least one 20-minutesession of vigorous exercise last week but did not do so why notrsquo


Scale reliabilitiesCronbachrsquos alphas (Cronbach 1951) were computed in order to check that variablesmeasured by multiple items formed reliable scales The 2 items measuring perceivedseverity (as = 54 55 and 55 for Times 1ndash3 respectively) and the 2 items measuringresponse efcacy (as = 38 43 and 58 for Times 1ndash3 respectively) were not reliableand were included as separate items in subsequent analyses All other PMTvariables andintention formed reliable scales with as ranging from 73 to 95 Reliabilities meansand standard deviations for study variables are shown in Table 1


Table 1 Variables scale reliabilities mean and standard deviations for the whole sample

ItemsVariables Time (N ) a Range M SD

Threat appraisalPerceived vulnerability T1 2 87 1ndash7 416 143

T2 2 73 1ndash7 422 127T3 2 75 1ndash7 421 126

Perceived severity 1 (premature death) T1 1 mdash 1ndash7 545 173T2 1 mdash 1ndash7 543 165T3 1 mdash 1ndash7 548 156

Perceived severity 2 (pain) T1 1 mdash 1ndash7 575 122T2 1 mdash 1ndash7 560 125T3 1 ndash 1ndash7 567 125

Fear T1 4 93 1ndash7 462 142T2 4 95 1ndash7 466 141T3 4 95 1ndash7 476 133

Coping appraisalResponse ef cacy 1 (lessen chances of CHD) T1 1 mdash 1ndash7 577 123

T2 1 mdash 1ndash7 575 116T3 1 mdash 1ndash7 573 109

Response ef cacy 2 (positive effects reduce T1 1 mdash 1ndash7 531 170risk of CHD) T2 1 mdash 1ndash7 534 160

T3 1 mdash 1ndash7 550 143

Self-ef cacy T1 4 78 1ndash7 559 143T2 4 78 1ndash7 565 144T3 4 80 1ndash7 554 143

Response costs T1 4 73 1ndash6 229 119T2 4 76 1ndash6 232 122T3 4 76 1ndash6 231 231

Intention T1 2 82 1ndash7 546 176T2 2 80 1ndash7 548 168T3 2 85 1ndash7 552 175

Behaviour (No of sessions) T1 1 mdash 0ndash7 118 069T2 1 mdash 0ndash7 101 066T3 1 mdash 0ndash7 111 050

Results

Randomization checksThere were no signicant differences between the three groups in terms of pre-vious frequency of exercise behaviour over the year (F(1247) = 026 ns) month(F(1247) = 113 ns) or week (F(1247) = 030 ns) prior to the study There werealso no signicant differences in age (F(1247) = 025 ns) or gender (x2(2) = 150

ns) Finally there were no signicant differences in intention or any of the PMTvariables between experimental groups 1 and 2 either at Time 1 or at Time 2 (seeTable 2) Thus the volitional intervention was not confounded by differences onintentions or variables inuencing intentions

Descriptive ndingsThe means and standard deviations for study variables at all three time points are shownin Table 1 Overall the participants agreed that CHDis a serious disease that could bringabout premature death and would cause pain The participants felt moderately afraid ofthe disease However they did not feel very vulnerable to developing CHD in later lifeAt lease one 20-minute session of exercise a week was seen as being very effective inreducing the risk of CHD and as being low in cost Participants generally felt able tocarry out one session of exercise per week The mean intention scores indicate thatthe participants generally intended to carry out the exercise at each time of assessmentHowever only 45of the overall sample had engaged in a 20-minute session of exercisein the week before the study whereas 36reported having exercised at Time 2 and 52reported having engaged in one session of exercise at Time 3

Analytic strategyThe main hypotheses were tested by conducting a mixed model MANOVA with onebetween-subjects factor (3 levels control motivational intervention motivational plusvolitional intervention) and one within-subjects factor (3 levels Time 1 Time 2 Time 3)Means and standard deviations for the three groups at each time point are presentedin Table 2

Effects of the motivational intervention on subsequent cognitions and intentionMANOVA showed a signicant effect for experimental condition (F(1247) = 445p lt 001) time (F(1247) = 19894 p lt 001) and for the condition acute time interaction(F(2245) = 321 p lt 001) The univariate F values for PMT variables intention andbehaviour frequency showed signicant differences between the three groups on allthe PMT variables and on intention at Time 1 (see Table 2) Pairwise comparisons ofmeans revealed that the differences were between those participants who received themotivational intervention and those who did not The motivational interventionproduced greatest changes in response efcacy (operationalized as the opinion that atleast one 20-minute session of exercise a week would lessen chances of developingCHD) (F(1247) = 3693 p lt 001) intention (F = 2287 p lt 001) and self-efcacy(F(1247) = 1511 p lt 001) The smallest change in belief found following the motiva-tional manipulation was for fear (F(1247) = 385 p lt 05) A signicant effect of timewas obtained for just one of the variables perceived severity (F(1247) = 600 p lt 01)However pairwise comparisons failed to show anysignicant difference in mean scoresacross the three time points


Thus ndings show that Hypothesis 1 (the motivational intervention will increaseperceived vulnerability perceived severity fear self-efcacy and response efcacy andreduce perceived response cost) was supported Hypothesis 2 (the motivational inter-vention will increase intention to engage in at least one 20-minute session of exercisein the following week) was also conrmed Hypothesis 3 (the effects of the motivationalintervention will be stable over time) was also supported with all cognitive changesinduced by the health education leaet on PMT variables and intention remaining stableover the 2-week period (see Table 2)

Effects of the motivational and volitional interventions on subsequent behaviourThe MANOVA revealed a signicant condition acute time interaction (F(2245) = 308p lt 05) on the frequency of 20-minute sessions of exercise (see Table 2) We conductedsimple effects analyses between groups at each time point and between time points foreach group in order to decompose the interaction Whereas the three groups did notdiffer on the number of exercise sessions at Time 1 or Time 2 there was a signicantdifference at Time 3 Pairwise comparisons revealed that experimental group 2 (whoreceived both the motivational and volitional intervention) engaged in more exercisethan either experimental group 1 (the motivational intervention only group) or thecontrol group ( p lt 01 for both comparisons) Experimental group 1 and the controlgroup did not differ in their exercise behaviour

ANOVAs were conducted to examine the effect of time on exercise participationwithin each group There was no signicant effect of time on exercise behaviour ineither experimental group 1 (F(2245) = 195 ns) or the control group (F(2245) =

158 ns) However time was found to have signicant effect on behaviour in experi-mental group 2 (F(2) = 953 p lt 0001) Pairwise comparisons revealed that thevolitional (implementation intention) intervention was entirely responsible for thiseffect Thus provision of the motivational intervention alone had no signicant effectson exercise behaviour However our Hypothesis 4 that the addition of a volitionalintervention in the form of an implementation intention to the PMT-based motivationalintervention will increase participation in at least one 20-minute session of exercisewas strongly supported

In order to further investigate the effects of the motivational and volitional inter-ventions on behaviour a chi-squared test was employed to compare the percentage ofparticipants in each group who engaged in at least one 20-minute exercise session ateach time point (see Fig 1)

It is interesting to note that among both the control group and the motivationalmanipulation group exercise participation decreased between Time 2 and Time 3 Theimplementation intention group showed a slight decrease in participation betweenTime 1 and Time 2 (38 and 35 respectively) but at Time 3 following the volitionalintervention exercise participation increased dramatically to 91 Chi-squared testsshowed that there were no signicant differences between the three groups in exerciseparticipation at Time 1 (x2(2) = 393 ns) or Time 2 (x2(2) = 089 ns) There was ahighly signicant difference due to the increase in exercise behaviour in the imple-mentation intention group at Time 3 (x2(2) = 7128 p lt 001) Thirty-eight per centof the control group 35 of the motivational intervention only group and 91 ofexperimental group 2 the motivational plus volitional intervention group engaged inexercise Thus Hypothesis 4 was strongly supported in two analyses


174 Sarah Milne et alT

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431

(16

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(14

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23

87(1

03)

x4

44(1

39)

y4

30(1

29)

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T3

386

(10

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437

(14

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436

(11

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14

75(1

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501

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570

(14

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568

(15

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88(1

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x5

92(1

09)

y5

91(1

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T3

493

(13

8)x

593

(10

5)y

605

(10

1)y

Fear

T1

437

(14

9)x

481

(13

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463

(14

6)y

385

2

73n

s0

36n

sT

24

32(1

57)

x4

93(1

19)

y4

68(1

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y

T3

445

(14

8)x

501

(16

5)y

476

(13

3)y

Cop

ing

appr

aisa

lR

espo

nse

efc

acy

1(le

ssen

chan

ces

ofC

HD

)T

15

05(1

38)

x6

13(0

91)

y6

04(1

11)

y36

93

0

24n

s0

29n

sT

24

99(1

27)

x6

11(0

76)

y6

08(1

08)

y

T3

496

(12

4)x

605

(07

6)y

609

(08

8)y

Res

pons

eef

cac

y2

(red

uce

risk

ofC

HD

)T

14

74(1

45)

x5

40(1

93)

y5

77(1

48)

y10

61

2

45n

s0

41n

sT

24

88(1

50)

x5

44(1

80)

y5

67(1

39)

y

T3

492

(14

4)x

566

(15

4)y

589

(11

0)y

Self-

efc

acy

T1

494

(16

1)x

589

(12

0)y

586

(13

1)y

151

1

041

ns

046

ns

T2

486

(16

0)x

583

(13

0)y

593

(12

1)y

T3

486

(16

1)x

581

(12

3)y

586

(12

3)y

Motivation and volition 175R

espo

nse

cost

sT

12

68(1

31)

x2

15(1

09)

y2

09(1

10)

y7

15

0

27n

s1

82n

sT

22

71(1

31)

x2

19(1

16)

y2

10(1

13)

y

T3

276

(12

8)x

208

(10

6)y

217

(11

6)y

Inte

ntio

nT

14

59(2

01)

x5

92(1

67)

y6

10(1

23)

y22

87

0

33n

s0

31n

sT

24

60(1

97)

x5

91(1

49)

y6

19(1

06)

y

T3

459

(20

1)x

587

(15

2)y

616

(12

0)y

Beha

viou

r(N

oof

sess

ions

)T

11

18(1

94)

x1

41(2

06)

x1

24(1

88)

x0

80n

s5

13

3

08

T2

095

(17

4)x

117

(17

4)x

101

(16

6)x

T3

084

(15

4)x

101

(15

4)x

161

(11

9)y

Not

eEx

pt1

=m

otiv

atio

nalm

anip

ulat

ion

grou

pEx

pt2

=m

otiv

atio

nali

nter

vent

ion

and

impl

emen

tatio

nin

tent

ion

grou

pa M

eans

with

diffe

rent

subs

crip

tsw

ithin

row

sdi

ffer

sign

ica

ntly

atle

ast

plt

05

bd

f=

124

7c d

f=

224

5

Effects of the volitional intervention on intention

Did the volitional intervention change behavioural intentionsThere were no signicant differences in intention following the volitional interven-tion (Time 3 measure of intention) between the participants who received only themotivational intervention (experimental group 1) and those who received both themotivational and volitional intervention (experimental group 2) (see Table 2) Thissuggests that motivational factors were not responsible for the effects of the imple-mentation intention intervention Rather volitional factors must be responsible

In order to test Hypothesis 5 (participants who form implementation intentionswill engage in exercise on the day and at the time and place specied in theirimplementation intention) the days times and places specied in participantsrsquo imple-mentation intentions were cross-tabulated against the days times and places in whichthe exercise was enacted as shown in Table 3 (cf Orbell et al 1997)

All participants in experimental group 2 exercised at the places specied in theirimplementation intention whereas 97 exercised at the time specied and 88exercised on the day specied Thus Hypothesis 5 was supported These ndingssupport the view that implementation intentions allowed participants to delegatecontrol of behaviour to the environmental cues specied in their implementationintentions and that encountering these cues led to automatic initiation of behaviour(Orbell et al 1997 Sheeran amp Orbell 1999)

We also analysed the reasons given for failing to exercise at Time 3 among parti-cipants who intended to do so in each of the three groups Implementation intentionsresult in a strong and easily accessible memory trace of the context for initiating thebehaviour (cf Orbell et al 1997) Thus participants who formed implementationintentions should not report forgetting to exercise Indeed none of the participantsin experimental group 2 did report forgetting to exercise whereas 19 (N = 14) ofparticipants in experimental group 1 and 14 (N = 6) of the control group said they


Figure 1 Percentages of exercisers in the three experimental groups at each time point Controlgroup no intervention Expt 1 motivational (PMT) intervention only Expt 2 motivational (PMT)intervention and volitional (implementation intention) interventions

forgot to exercise (x2(2) = 1480 p lt 001) However this was not the reason mostoften given for failure to exercise Twenty-six per cent of participants in experimentalgroup 1 (N = 19) and 45(N = 19) of the control group said that they were too busyto participate in exercise at Time 3 Only one participant in the implementationintention group gave the same reason for not exercising (x2(2) = 1426 p lt 001) lsquoIdidnrsquot get round to itrsquo was another popular reason for failing to exercise amongparticipants in experimental group 1 and the control group Twenty-three per cent


Table 3 Day time and place speci ed for exercise behaviour in implementation intentions at Time 2 bytime and place of exercise enactment reported at Time 3 (n = 73)

Day of enactment Monday Tuesday Wednesday Thursday Friday Saturday Sunday

Day specied inimplementation intention

Monday 8Tuesday 23 2 2Wednesday 1 2 25 3 1 1Thursday 13Friday 1 1 11 2Saturday 8Sunday 7

Time speci ed in implementation intention Morning Lunch-time Afternoon Evening

Time of enactmentMorning 32Lunch-time 2 14Afternoon 21Evening 9

Goodwin Goodwin Other TeamPlace of sports swimming swimming Playing Tennis sportsenactment centre pool pool Gym Street Park elds courts pitch Home

Place speci edin implementationintention

Goodwin sportscentre 27

Goodwinswimming pool 48

Otherswimming pool 4

Gym 15Street 1Park 2Playing elds 1Tennis court 6Team sports pitch 9Home 6

(N = 17) of intenders in the motivation intervention group and 23 (N = 10) in thecontrol group said they did not get round to exercising No-one in experimental group 1reported not getting round to exercise (x2(2) = 1406 p lt 001) Thus participants whoformed implementation intentions were less likely to report (i) forgetting to exercise(ii) not having time to exercise and (iii) not getting round to exercise

DiscussionThis is the rst study to include all PMT variables in a longitudinal study incorporatinga factual health education intervention (cf Milne et al 2000) The interventionproduced signicant positive changes on all PMT variables and increased intentionsto exercise Previous health education interventions based on PMT variables have beenless successful in bringing about cognitive change especially for threat appraisalvariables (eg Boer amp Seydel 1996 Seydel et al 1990 Steffen 1990)

One explanation for the success of the present study in changing PMT variables isthat the health education leaet and subsequent measures were both salient to theparticipant group and involved a specic behaviourndashlsquoat least one 20-minute session ofvigorous exercise over the coming weekrsquo Previous health education studies (Boer ampSeydel 1996 Seydel et al 1990 Steffen 1990) provided a general leaet based on PMTvariables about a focal disease and behaviour It may be the case that the participantsdid not feel as personally involved in those studies as the present study Here thedesignation lsquoyoung peoplersquo was used repeatedly to involve readers in the passage andremind them that the information applied to them personally It seems likely that healtheducation needs to be specic about the focal behaviour and involve its target groupin order to ensure effectiveness (Abraham amp Sheeran 1994)

Our PMTintervention had a signicant effect on intention to engage in exercise Thisnding is consistent with results from other studies (Boer amp Seydel 1996 Steffen1990) However this motivational intervention had no signicant effect on subsequentexercise behaviour One explanation of these ndings might be that although themotivational intervention bought about a large and highly signicant change in inten-tion it did not produce sufcient change in intention to inuence behaviour Arelatedexplanation for the failure of the motivational intervention to change behaviour in thepresent study was the fact that examinations were approaching at the time of the studyand many of the participants who had received the motivational intervention on itsown reported that they were lsquotoo busyrsquo to exercise It may be that the changes inintention bought about by the motivational intervention were not strong enough toinuence behaviour in the context of competing goals associated with examinationpreparation

Wurtele and Maddux (1987) have acknowledged that PMT manipulations areeffective in increasing intention but not in increasing subsequent behaviour Theyargue that this may be due to the fact that intentions are measured immediately afterthe intervention when the information is fresh in the minds of participants By the timethe behavioural measure takes place the effects of the manipulation may have worn offTo establish whether this explanation for the inefcacy of PMT-based interventionsin changing behaviour we measured cognitive changes at three times over the 2-weekperiod of the study immediately after the manipulation (Time 1) again 1 week later(Time 2) and again 1 week later (Time 3) The effects of the PMT intervention onmeasures of PMT variables and intention were found to be similar at all time points This


indicates that the effects of such manipulations can last over time This underminesWurtele and Madduxrsquos explanation for the inability of PMT manipulations to inuencebehaviour Rather the present results show that the effects of interventions based onPMT variables although successful in inuencing intention do not alter behaviourThus PMT manipulations can be seen as motivational interventions As such they arevery successful and useful for health education interventions in which changingintention is the goal However to change behaviour something more is needed

At Time 2 after completing measures of PMT variables intention and behaviourexperimental group 2 were asked to form an implementation intention Implementationintentions were found to have a dramatic effect on increasing subsequent exercisebehaviour Findings showed that implementation intentions increased both the numberof exercise sessions engaged in by participants and also the number of participantswho engaged in at least one exercise session These results add further support to thegrowing body of evidence that implementation intentions are powerful strategies forbehavioural enactment (Gollwitzer amp Oettingen 2000) Despite its effect on increasingbehaviour the implementation intention intervention had no effect on intentions toexercise or anyof the PMT variables Post hoc tests among the two experimental groupsconrmed that making implementation intentions did not affect strength of intentionThus the effect of the implementation intention occurred only for behaviour it didnot alter motivation (intention) or the beliefs inuencing motivation This supportsGollwitzerrsquos (1993 1996) contention that the effects of implementation intentions onbehaviour are purely volitional Both the motivational and the volitional interventionswere necessary to change exercise behaviour supporting the view held by Gollwitzer(1993) and Heckhausen (1991) that motivation and volition are discrete processes

The present study also conrms previous ndings regarding the mechanisms bywhich implementation intentions inuence behaviour Evidence shows that partici-pants have very good memory for the time and place specied within their implementa-tion intention (eg Gollwitzer 1993 1996 Orbell et al 1997 Sheeran amp Orbell 1999)The present study added to this body of evidence There was a strong correspondencebetween the times and places specied in the implementation intention and when andwhere the reported behaviour took place This adds further support to the conclusionthat the situations specied in implementation intentions produce strong memorytraces that are readily accessible in memory and lead to automatic activation when thespecied cues are encountered (Gollwitzer 1993 1996 Orbell et al 1997)

The present study also supported the view that implementation intentions workby heightening perceptual readiness ensuring that good action opportunities are notmissed (Gollwitzer 1993 1996) Twenty-ve per cent of those in the control group and23 of the motivational intervention group reported not having got around to theirintended exercise None of the implementation intention group reported this Partici-pants who did not make implementation intentions may not have recognized oppor-tunities to act and hence did not get around to realizing their intentions to exercise

It has also been suggested that implementation intentions work by ensuring the goalin question has priority over other competing goals both at behaviour activation andduring behaviour completion (Gollwitzer 1993 1996) Findings from the present studyare consistent with this hypothesis Participants had strong competing goals concernedwith preparing for examinations This may explain the decrease in exercise partici-pation among the control group and the motivational intervention group Forty-sevenper cent of intenders in the control group and 24 of intenders in the motivationalintervention group reported being too busy to carry out their intentions whereas only


one participant in the implementation intention group made this report This providessuggestive evidence that implementation intentions ensured that the goal of exercisinggained precedence over other competing goals

A number of possible criticisms with the present study needs to be addressed Inintervention studies it is possible that experimenter demand may have inuenced theresults To help lessen this effect participants were anonymous to the experimenterand did not know the purpose of the study or that it involved interventions Theseconsiderations should have reduced the inuence of experimenter demand It shouldalso be acknowledged that a longer term study would also have been desirable althoughit is notable that we obtained highly signicant effects over a relatively short timeinterval and have no grounds for believing that a longer term study would have alteredour ndings (Sheeran amp Orbell 1999) Finally a convenience sample of undergraduatestudents was used Although many studies in health psychology involve under-graduate students it must be acknowledged that this is not ideal There are also somecriticisms we would now wish to make concerning our measure of exercise

Our intervention aimed to increase lsquovigorous exercisersquo Our description of vigorousexercise can be seen as misleading as activities such as walking swimming and dancingcan be moderate or vigorous depending on the level of exertion expended by theindividual However we feel that byadding that the exercise should be enough to cause anoticeable increase in heart rate we came some way towards controlling for thisproblem Recommendations for regular exercise to reduce the risk of CHDhave recentlybeen claried as lsquo30 minutes moderate intensity exercise on at least ve days a week orthree 20-minute sessions of vigorous intensity exercise a weekrsquo (Pate et al 1995) Ourintervention differs from this both in terms of intensityand regularity The implications ofthese errors are that self-efcacy and response cost measures may have been articiallyinated thus massaging the success of the PMT intervention However this problem inno way invalidates the critical nding that addition of implementation intentions greatlyincreases the ability of a PMT-based intervention to increase behaviour

ConclusionsThe motivational intervention based on PMT variables had a signicant effect in chang-ing beliefs and increasing intention to exercise These effects were stable over timeWhile the motivational intervention did not affect subsequent exercise behaviour theaddition of a volitional intervention an implementation intention produced a dramaticincrease in behaviour Implementation intentions did not alter intention to exercise orany other motivational factors From this we can conclude that the effects of imple-mentation intentions are purely volitional and motivation and volition are separatediscrete processes (eg Gollwitzer 1993 1996 Heckhausen 1991) Overall the resultsof the present study show that a PMT-based intervention combined with an implemen-tation intention can be a powerful tool for health education programmes Such aprogramme should rst increase motivation A volitional intervention should followwhen a goal intention has been formed Future research should test this type ofintervention among clinical or general populations and for other health behavioursThe impact of implementation intentions on health-related behaviour has now beenwell documented Research should now explore how best to train health professionalsand those wishing to modify their behaviour on how best to use implementationintentions for themselves and how to adapt them for different goals


AcknowledgementsThe authors would like to thank the two anonymous referees for their helpful comments on anearlier draft of this paper

ReferencesAbraham S C S amp Sheeran P (1994) Modelling and modifying young heterosexualsrsquo HIV

preventive behaviour A review of theories ndings and educational implications PatientEducation and Counseling 23 173ndash186

Ajzen I (1985) From intention to action A theory of planned behaviour In J Kuhl ampJ Beckman (Eds) Action control From cognition to behaviour (pp 11ndash39) New YorkSpringer

Ajzen I amp Fishbein M (1980) Understanding attitudes and predicting social behaviourEnglewood Cliffs NJ Prentice-Hall

American Heart Association (1994) Heart and stroke facts Dallas TX American HeartAssociation

Bandura A (1991) Social cognitive theory of self-regulation Organisational Behaviour andHuman Decision Processes 50 248 ndash287

Bauman A Owen N amp Rushworth R L (1990) Recent trends and socio-demographicdeterminants of exercise participation in Australia Community Health Studies 14 19ndash26

Boer H amp Seydel E R (1996) Protection motivation theory In M Conner amp P Norman(Eds) Predicting health behaviour Research and practise with social cognition models(pp 95ndash120) Buckingham Open University Press

Bouchard C amp Depres J P (1995) Physical activity and health Astherosclerotic metabolic andhypertensive diseases Research Quarterly for Exercise and Sport 66 268ndash275

British Heart Foundation (1996) British Heart Foundation statistics factsheet London BritishHeart Foundation

Clarkson T B Manuck S B amp Kaplan J R (1986) Potential role of cardiovascular reactivity inastherogenesis In K A Mathers et al (Eds) Handbook of stress reactivity and cardiovas-cular disease New York Wiley

Cronbach L J (1951) Coefcient alpha and the internal structure of tests Psychometrica 16 296ndash334

Floyd D L Prentice-Dunn S amp Rogers R W (2000) Ameta-analysis of research on protectionmotivation theory Journal of Applied Social Psychology 30 407ndash429

Fruin D J Pratt C amp Owen N (1991) Protection motivation theory and adolescentsrsquoperception of exercise Journal of Applied Social Psychology 22 55ndash69

Gollwitzer P M (1993) Goal achievement The role of intentions European Review of SocialPsychology 4 141ndash185

Gollwitzer P M (1996) The volitional benets of planning In P M Gollwitzer ampJ A Bargh (Eds)The psychology of action Linking cognition and motivation to behaviour (pp 287ndash312)New York Guildford Press

Gollwitzer P M amp Brandstatter V (1997) Implementation intentions and effective goal pursuitJournal of Personality and Social Psychology 73 186ndash199

Gollwitzer P M Heckhausen H amp Steller B (1990) Deliberative vs implemental mind-setsCognitive tuning toward congruous thoughts and information Journal of Personality andSocial Psychology 59 1119ndash1127

Gollwitzer P M amp Oettingen G (2000) The emergence and implementation of health goals InP Norman C Abramam ampM Conner (Eds) Understanding and changing health behaviourFrom self beliefs to self regulation (pp 229ndash260) Amsterdam Harwood

Heckhausen H (1991) Motivation and action New York SpringerHeckhausen H amp Gollwitzer P M (1987) Thought contents and cognitive functioning in

motivational versus volitional states of mind Motivation and Emotion 11 101ndash120


Maddux J E amp Rogers R W (1983) Protection motivation theory and self-efcacy A revisedtheory of fear appeals and attitude change Journal of Experimental Social Psychology 19 242 ndash253

Makrides L Veinot P Richard J McKee E amp Gallivan T (1998) A cardiovascular needsassessment of university students living in residence Canadian Journal of Public Health 89 171 ndash175

Miller T D Balady G J amp Fletcher G F (1997) Exercise and its role in the prevention andrehabilitation of cardiovascular disease Annals of Behavioural Medicine 19 220ndash229

Milne S E Sheeran P amp Orbell S (2000) Prediction and intervention in health-relatedbehaviour A meta-analytic review of protection motivation theory Journal of AppliedSocial Psychology 30 106 ndash143

Norman P amp Conner M (1996) The role of social cognition models in predicting healthbehaviours Future directions In M Conner ampP Norman (Eds) Predicting health behaviourResearch and practise with social cognition models (pp 197ndash225) Buckingham OpenUniversity Press

Orbell S Hodgkins S amp Sheeran P (1997) Implementation intentions and the theory ofplanned behaviour Personality and Social Psychology Bulletin 33 209ndash217

Orbell S amp Sheeran P (2000) Motivational and volitional processes in action initiation A eldstudy of the role of implementation intentions Journal of Applied Social Psychology 30 780 ndash797

Pate R R Pratt M Blair S N Haskell W L Macera C A Bouchard C Buchner DEttinger W Heath G W King A C Kriska A Leon A S Marcus B H Morris JPaffenbarger R S Patrick K Pollock M L Rippe J M Sallis J amp Wilmore J H (1995)Physical activity and public healthndashA recommendation from the Centers for Disease Controland Prevention and the American College of Sports Medicine Journal of the AmericanMedical Association 273 402ndash407

Rippetoe P A amp Rogers R W (1987) Effects of components of protection motivation theoryon adaptive and maladaptive coping with a health threat Journal of Personality and SocialPsychology 52 596ndash604

Rogers R W (1975) Aprotection motivation theory of fear appeals and attitude change Journalof Psychology 91 93ndash114

Rogers R W (1983) Cognitive and physiological processes in fear appeals and attitude changeA revised theory of protection motivation In B L Cacioppo amp L L Petty (Eds) Socialpsychophysiology A source book (pp 153ndash176) London Guildford Press

Rogers R W amp Prentice-Dunn S (1997) Protection motivation theory In D Gochman (Ed)Handbook of health behaviour research Vol 1 Determinants of health behaviourPersonal and social (pp 113ndash132) New York Plenum

Seydel E Taal E amp Wiegman O (1990) Risk appraisal outcome and self-efcacy expectanciesCognitive factors in previous behaviour related to cancer Psychology and Health 4 99ndash109

Sheeran P amp Orbell S (1996) How condently can we infer health beliefs from questionnaireresponses Psychology and Health 11 273 ndash290

Sheeran P ampOrbell S (1999) Implementation intentions and repeated behaviours Augmentingthe predictive validity of the theory of planned behaviour European Journal of SocialPsychology 29 349ndash369

Sheeran P amp Orbell S (2000) Using implementation intentions to increase attendance forcervical cancer screening Health Psychology 19 282ndash289

Stanley M A amp Maddux J E (1986) Cognitive processes in health enhancement Investigationof a combined protection motivation and self-efcacy model Basic and Applied SocialPsychology 7 101 ndash113

Steffen V J (1990) Menrsquos motivation to perform the testicle self-exam Effects of prior knowledgeand an educational brochure Journal of Applied Social Psychology 20 681ndash702

Stephens T Jacobs D R ampWhite C (1985) Adescriptive epidemiology of leisure-time physicalactivity Public Health Reports 100 147ndash158


Sturges J W amp Rogers R W (1996) Preventive health psychology from a developmentalperspective An extension of protection motivation theory Health Psychology 15 158ndash166

Tanner Jr J F Day E amp Crask M R (1989) Protection motivation theory An extension offear appeals theory in communication Journal of Business Research 19 267ndash276

Verplanken B amp Faes S (1999) Good intentions bad habits and effects of formingimplementation intentions on healthy eating European Journal of Social Psychology 29 591ndash604

Wurtele S K (1988) Increasing womenrsquos calcium intake The role of health beliefs intentionsand health value Journal of Applied Social Psychology 18 627 ndash639

Wurtele S K amp Maddux J E (1987) Relative contributions of protection motivationtheory components in predicting exercise intentions and behaviour Health Psychology 6453ndash466

Received 10 August 2000 revised version received 13 December 2000

Appendix 1

Measures of PMT variables including intention

Perceived severityIf I were to develop CHD I would suffer a lot of pain (strongly disagreendashstronglyagree) Developing CHD would be unlikely to cause me to die prematurely (stronglyagreendashstrongly disagree)

Perceived vulnerabilityMy chances of developing CHD in the future are (not at all strongndashvery strong) I amunlikely to develop CHD in the future (strongly disagreendashstrongly agree)

FearThe thought of developing CHD makes me feel (very frightenedndashnot at all frightenednot at all anxiousndashvery anxious not at all worriedndashvery worried very scaredndashnot atall scared)

Response ef cacyBecause of the wide range of positive effects exercising vigorously for at least 20 minutesa week has on the body it is a good wayof reducing the risk of developing CHD(stronglydisagreendashstrongly agree)

If I were to engage in at least one 20-minute session of vigorous exercise a week Iwould lessen my chances of developing CHD (strongly agreendashstrongly disagree)

Self-ef cacyI am discouraged from taking at least one 20-minute session of vigorous exercise duringthe next week because I feel unable to do so (strongly agreendashstrongly disagree)

I feel condent in my ability to partake in at least one 20-minute session of vigorousexercise during the next week (strongly agreendashstrongly disagree)

It would not be difcult for me to take at least one 20-minute session of vigorousexercise during the next week (strongly agreendashstrongly disagree)

Taking at least one 20-minute session of vigorous exercise during the next weekwould be easy for me (strongly disagreendashstrongly agree)


Response costThe benets of taking at least one 20-minute session of vigorous exercise a weekoutweigh the costs (strongly agreendashstrongly disagree)

Taking at least one 20-minute session of vigorous exercise during the next weekwould cause me too many problems (strongly disagreendashstrongly agree)

I would be discouraged from taking at least one 20-minute session of vigorousexercise during the next week as it would take too much time (strongly disagreendashstrongly agree)

I would be discouraged from taking at least one 20-minute session of vigorousexercise a week because I would feel silly doing so (strongly agreendashstrongly disagree)

IntentionI intend to partake in at least one 20-minute session of vigorous exercise (eg sportswimming aerobics dancing running or walking briskly) during the next week(strongly agreendashstrongly disagree)

I do not wish to partake in at least one 20-minute session of vigorous exercise duringthe next week (strongly agreendashstrongly disagree)


Coronary heart disease (CHD) is one of the most signicant causes of death in modernindustrial societies Indeed 44 of all deaths of the UK in 1994 were attributed tocardiovascular disease (British Heart Foundation 1996) Approximately 300 000 heartattacks are experienced in the UK (British Heart Foundation 1996) and 11

2million in

the USAeach year (American Heart Association 1995) Of these more than a third willresult in death In a recent review Miller Balady and Fletcher (1997) reported anaccumulation of evidence to show that a physically inactive lifestyle doubles the risk ofdeveloping CHD Regular exercise has been shown to prevent CHDby decreasing levelsof cholesterol and fat in the bloodstream and by lowering blood pressure This in turndramatically reduces the primary cause of CHD atherosclerosis the build-up of fattydeposits on the artery walls (Bouchard amp Despres 1995) Although atherosclerosisoften leads to CHD in middle age the process occurs throughout life Thus to havethe best chance of lowering the risk of CHD preventive habits need to be developedat an early age (Clarkson Manuck amp Kaplan 1986) The greatest decrease in exerciseparticipation throughout life occurs during late adolescence (Stephens Jacobs ampWhite 1985) Bauman Owen and Rushworth (1990) found that only25of Australiansunder 20 years of age engaged in regular exercise Makrides Veinot Richard McKeeand Gallivan (1998) found that fewer than half of the students in a Canadian universityparticipated in regular exercise This suggests that an intervention designed to increaseexercise participation among young adults would be of considerable value

Many researchers and practitioners aiming to develop health education interven-tions to promote precautionaryactions such as exercise have turned to social cognitivemodels of behaviour One such model which has been shown to be useful in theprediction of and intervention in health-related behaviours is protection motivationtheory (PMT Rogers 1975 1983 For recent literature reviews see Boer amp Seydel 1996Rogers amp Prentice Dunn 1997 For meta-analytic reviews see Floyd Prentice-Dunn ampRogers 2000 Milne Sheeran amp Orbell 2000)

The model proposes that protection motivation is the variable that lsquoarouses sustainsand directs activityrsquo and is operationalized in terms of peoplesrsquo intentions to performa recommended precautionary behaviour Intention is inuenced by two processesthreat appraisal and coping appraisal Threat appraisal concerns the evaluation of thecomponents of a fear appeal relevant to an individualrsquos perception of how endangeredhe or she feels by a threat disease(s) The PMT variables involved in threat appraisalare perceived vulnerability perceived severity and fear arousal An individual perceiv-ing the threat to be high will be more likely to be motivated to adopt the recom-mended protective behaviour Coping appraisal evaluates the components of a fearappeal that are relevant to an individualrsquos assessment of the recommended copingresponse to the appraised threat Coping appraisal involves beliefs about responseefcacy self-efcacy and response costs An individual will be more likely to intendto adopt the recommended coping response if he or she believes that the response willbe effective feels able to perform the recommended behaviour and perceives thebehaviour to be low in cost (see Boer amp Seydel 1996 Floyd et al 2000 Milne et al2000 Rogers amp Prentice-Dunn 1997 for more detailed description of the model andits measurement)

Unlike other social cognitive models of health-related behaviour such as the theoryof reasoned action (TRA Ajzen amp Fishbein 1980) and the theory of planned behaviour(TPB Ajzen 1985) PMT has been subjected to several experimental tests Studies havemanipulated PMT variables within a fear-arousing communication in order to explorethe effects of the intervention on subsequent beliefs intentions and behaviour Three




















Method






Interventions


















Measures









T2 2 73 1ndash7 422 127T3 2 75 1ndash7 421 126












Results















able

2D

iffer

ence

sin

PMT

vari

able

sin

tent

ion

and

beha

viou

rm

eans

acro

ssex

peri

men

talg

roup

stim

ean

dex

peri

men

talg

roup

acutetim

ein

tera

ctio

n

FC

ontr

olEx

pt1

Expt

2C

ondi

tionb

FF

Vari

able

Tim

eM

(SD

)aM

(SD

)aM

(SD

)a(e

xper

imen

talg

roup

)T

imeb

Con

ditio

nacute

timec

Thr

eat

appr

aisa

lPe

rcei

ved

vuln

erab

ility

T1

380

(10

9)x

431

(16

4)y

435

(14

1)y

486

0

41n

s0

60n

sT

23

87(1

03)

x4

44(1

39)

y4

30(1

29)

y

T3

386

(10

2)x

437

(14

4)y

436

(11

8)y

Perc

eive

dse

veri

ty1

(pre

mat

ure

deat

h)T

14

75(1

83)

x5

71(1

68)

y5

81(1

49)

y4

55

60

0

11n

sT

24

96(1

69)

x5

54(1

65)

y5

75(1

51)

y

T3

501

(16

0)x

570

(14

9)y

568

(15

2)y

Perc

eive

dse

veri

ty2

(pai

n)T

15

07(1

44)

x6

08(0

97)

y6

01(0

95)

y8

75

1

06n

s0

23n

sT

24

88(1

37)

x5

92(1

09)

y5

91(1

03)

y

T3

493

(13

8)x

593

(10

5)y

605

(10

1)y

Fear

T1

437

(14

9)x

481

(13

0)y

463

(14

6)y

385

2

73n

s0

36n

sT

24

32(1

57)

x4

93(1

19)

y4

68(1

45)

y

T3

445

(14

8)x

501

(16

5)y

476

(13

3)y

Cop

ing

appr

aisa

lR

espo

nse

efc

acy

1(le

ssen

chan

ces

ofC

HD

)T

15

05(1

38)

x6

13(0

91)

y6

04(1

11)

y36

93

0

24n

s0

29n

sT

24

99(1

27)

x6

11(0

76)

y6

08(1

08)

y

T3

496

(12

4)x

605

(07

6)y

609

(08

8)y

Res

pons

eef

cac

y2

(red

uce

risk

ofC

HD

)T

14

74(1

45)

x5

40(1

93)

y5

77(1

48)

y10

61

2

45n

s0

41n

sT

24

88(1

50)

x5

44(1

80)

y5

67(1

39)

y

T3

492

(14

4)x

566

(15

4)y

589

(11

0)y

Self-

efc

acy

T1

494

(16

1)x

589

(12

0)y

586

(13

1)y

151

1

041

ns

046

ns

T2

486

(16

0)x

583

(13

0)y

593

(12

1)y

T3

486

(16

1)x

581

(12

3)y

586

(12

3)y


espo

nse

cost

sT

12

68(1

31)

x2

15(1

09)

y2

09(1

10)

y7

15

0

27n

s1

82n

sT

22

71(1

31)

x2

19(1

16)

y2

10(1

13)

y

T3

276

(12

8)x

208

(10

6)y

217

(11

6)y

Inte

ntio

nT

14

59(2

01)

x5

92(1

67)

y6

10(1

23)

y22

87

0

33n

s0

31n

sT

24

60(1

97)

x5

91(1

49)

y6

19(1

06)

y

T3

459

(20

1)x

587

(15

2)y

616

(12

0)y

Beha

viou

r(N

oof

sess

ions

)T

11

18(1

94)

x1

41(2

06)

x1

24(1

88)

x0

80n

s5

13

3

08

T2

095

(17

4)x

117

(17

4)x

101

(16

6)x

T3

084

(15

4)x

101

(15

4)x

161

(11

9)y

Not

eEx

pt1

=m

otiv

atio

nalm

anip

ulat

ion

grou

pEx

pt2

=m

otiv

atio

nali

nter

vent

ion

and

impl

emen

tatio

nin

tent

ion

grou

pa M

eans

with

diffe

rent

subs

crip

tsw

ithin

row

sdi

ffer

sign

ica

ntly

atle

ast

plt

05

bd

f=

124

7c d

f=

224

5
























































































Appendix 1





































Method






Interventions


















Measures









T2 2 73 1ndash7 422 127T3 2 75 1ndash7 421 126












Results















able

2D

iffer

ence

sin

PMT

vari

able

sin

tent

ion

and

beha

viou

rm

eans

acro

ssex

peri

men

talg

roup

stim

ean

dex

peri

men

talg

roup

acutetim

ein

tera

ctio

n

FC

ontr

olEx

pt1

Expt

2C

ondi

tionb

FF

Vari

able

Tim

eM

(SD

)aM

(SD

)aM

(SD

)a(e

xper

imen

talg

roup

)T

imeb

Con

ditio

nacute

timec

Thr

eat

appr

aisa

lPe

rcei

ved

vuln

erab

ility

T1

380

(10

9)x

431

(16

4)y

435

(14

1)y

486

0

41n

s0

60n

sT

23

87(1

03)

x4

44(1

39)

y4

30(1

29)

y

T3

386

(10

2)x

437

(14

4)y

436

(11

8)y

Perc

eive

dse

veri

ty1

(pre

mat

ure

deat

h)T

14

75(1

83)

x5

71(1

68)

y5

81(1

49)

y4

55

60

0

11n

sT

24

96(1

69)

x5

54(1

65)

y5

75(1

51)

y

T3

501

(16

0)x

570

(14

9)y

568

(15

2)y

Perc

eive

dse

veri

ty2

(pai

n)T

15

07(1

44)

x6

08(0

97)

y6

01(0

95)

y8

75

1

06n

s0

23n

sT

24

88(1

37)

x5

92(1

09)

y5

91(1

03)

y

T3

493

(13

8)x

593

(10

5)y

605

(10

1)y

Fear

T1

437

(14

9)x

481

(13

0)y

463

(14

6)y

385

2

73n

s0

36n

sT

24

32(1

57)

x4

93(1

19)

y4

68(1

45)

y

T3

445

(14

8)x

501

(16

5)y

476

(13

3)y

Cop

ing

appr

aisa

lR

espo

nse

efc

acy

1(le

ssen

chan

ces

ofC

HD

)T

15

05(1

38)

x6

13(0

91)

y6

04(1

11)

y36

93

0

24n

s0

29n

sT

24

99(1

27)

x6

11(0

76)

y6

08(1

08)

y

T3

496

(12

4)x

605

(07

6)y

609

(08

8)y

Res

pons

eef

cac

y2

(red

uce

risk

ofC

HD

)T

14

74(1

45)

x5

40(1

93)

y5

77(1

48)

y10

61

2

45n

s0

41n

sT

24

88(1

50)

x5

44(1

80)

y5

67(1

39)

y

T3

492

(14

4)x

566

(15

4)y

589

(11

0)y

Self-

efc

acy

T1

494

(16

1)x

589

(12

0)y

586

(13

1)y

151

1

041

ns

046

ns

T2

486

(16

0)x

583

(13

0)y

593

(12

1)y

T3

486

(16

1)x

581

(12

3)y

586

(12

3)y


espo

nse

cost

sT

12

68(1

31)

x2

15(1

09)

y2

09(1

10)

y7

15

0

27n

s1

82n

sT

22

71(1

31)

x2

19(1

16)

y2

10(1

13)

y

T3

276

(12

8)x

208

(10

6)y

217

(11

6)y

Inte

ntio

nT

14

59(2

01)

x5

92(1

67)

y6

10(1

23)

y22

87

0

33n

s0

31n

sT

24

60(1

97)

x5

91(1

49)

y6

19(1

06)

y

T3

459

(20

1)x

587

(15

2)y

616

(12

0)y

Beha

viou

r(N

oof

sess

ions

)T

11

18(1

94)

x1

41(2

06)

x1

24(1

88)

x0

80n

s5

13

3

08

T2

095

(17

4)x

117

(17

4)x

101

(16

6)x

T3

084

(15

4)x

101

(15

4)x

161

(11

9)y

Not

eEx

pt1

=m

otiv

atio

nalm

anip

ulat

ion

grou

pEx

pt2

=m

otiv

atio

nali

nter

vent

ion

and

impl

emen

tatio

nin

tent

ion

grou

pa M

eans

with

diffe

rent

subs

crip

tsw

ithin

row

sdi

ffer

sign

ica

ntly

atle

ast

plt

05

bd

f=

124

7c d

f=

224

5
























































































Appendix 1
































Method






Interventions


















Measures









T2 2 73 1ndash7 422 127T3 2 75 1ndash7 421 126












Results















able

2D

iffer

ence

sin

PMT

vari

able

sin

tent

ion

and

beha

viou

rm

eans

acro

ssex

peri

men

talg

roup

stim

ean

dex

peri

men

talg

roup

acutetim

ein

tera

ctio

n

FC

ontr

olEx

pt1

Expt

2C

ondi

tionb

FF

Vari

able

Tim

eM

(SD

)aM

(SD

)aM

(SD

)a(e

xper

imen

talg

roup

)T

imeb

Con

ditio

nacute

timec

Thr

eat

appr

aisa

lPe

rcei

ved

vuln

erab

ility

T1

380

(10

9)x

431

(16

4)y

435

(14

1)y

486

0

41n

s0

60n

sT

23

87(1

03)

x4

44(1

39)

y4

30(1

29)

y

T3

386

(10

2)x

437

(14

4)y

436

(11

8)y

Perc

eive

dse

veri

ty1

(pre

mat

ure

deat

h)T

14

75(1

83)

x5

71(1

68)

y5

81(1

49)

y4

55

60

0

11n

sT

24

96(1

69)

x5

54(1

65)

y5

75(1

51)

y

T3

501

(16

0)x

570

(14

9)y

568

(15

2)y

Perc

eive

dse

veri

ty2

(pai

n)T

15

07(1

44)

x6

08(0

97)

y6

01(0

95)

y8

75

1

06n

s0

23n

sT

24

88(1

37)

x5

92(1

09)

y5

91(1

03)

y

T3

493

(13

8)x

593

(10

5)y

605

(10

1)y

Fear

T1

437

(14

9)x

481

(13

0)y

463

(14

6)y

385

2

73n

s0

36n

sT

24

32(1

57)

x4

93(1

19)

y4

68(1

45)

y

T3

445

(14

8)x

501

(16

5)y

476

(13

3)y

Cop

ing

appr

aisa

lR

espo

nse

efc

acy

1(le

ssen

chan

ces

ofC

HD

)T

15

05(1

38)

x6

13(0

91)

y6

04(1

11)

y36

93

0

24n

s0

29n

sT

24

99(1

27)

x6

11(0

76)

y6

08(1

08)

y

T3

496

(12

4)x

605

(07

6)y

609

(08

8)y

Res

pons

eef

cac

y2

(red

uce

risk

ofC

HD

)T

14

74(1

45)

x5

40(1

93)

y5

77(1

48)

y10

61

2

45n

s0

41n

sT

24

88(1

50)

x5

44(1

80)

y5

67(1

39)

y

T3

492

(14

4)x

566

(15

4)y

589

(11

0)y

Self-

efc

acy

T1

494

(16

1)x

589

(12

0)y

586

(13

1)y

151

1

041

ns

046

ns

T2

486

(16

0)x

583

(13

0)y

593

(12

1)y

T3

486

(16

1)x

581

(12

3)y

586

(12

3)y


espo

nse

cost

sT

12

68(1

31)

x2

15(1

09)

y2

09(1

10)

y7

15

0

27n

s1

82n

sT

22

71(1

31)

x2

19(1

16)

y2

10(1

13)

y

T3

276

(12

8)x

208

(10

6)y

217

(11

6)y

Inte

ntio

nT

14

59(2

01)

x5

92(1

67)

y6

10(1

23)

y22

87

0

33n

s0

31n

sT

24

60(1

97)

x5

91(1

49)

y6

19(1

06)

y

T3

459

(20

1)x

587

(15

2)y

616

(12

0)y

Beha

viou

r(N

oof

sess

ions

)T

11

18(1

94)

x1

41(2

06)

x1

24(1

88)

x0

80n

s5

13

3

08

T2

095

(17

4)x

117

(17

4)x

101

(16

6)x

T3

084

(15

4)x

101

(15

4)x

161

(11

9)y

Not

eEx

pt1

=m

otiv

atio

nalm

anip

ulat

ion

grou

pEx

pt2

=m

otiv

atio

nali

nter

vent

ion

and

impl

emen

tatio

nin

tent

ion

grou

pa M

eans

with

diffe

rent

subs

crip

tsw

ithin

row

sdi

ffer

sign

ica

ntly

atle

ast

plt

05

bd

f=

124

7c d

f=

224

5
























































































Appendix 1



























Method






Interventions


















Measures









T2 2 73 1ndash7 422 127T3 2 75 1ndash7 421 126












Results















able

2D

iffer

ence

sin

PMT

vari

able

sin

tent

ion

and

beha

viou

rm

eans

acro

ssex

peri

men

talg

roup

stim

ean

dex

peri

men

talg

roup

acutetim

ein

tera

ctio

n

FC

ontr

olEx

pt1

Expt

2C

ondi

tionb

FF

Vari

able

Tim

eM

(SD

)aM

(SD

)aM

(SD

)a(e

xper

imen

talg

roup

)T

imeb

Con

ditio

nacute

timec

Thr

eat

appr

aisa

lPe

rcei

ved

vuln

erab

ility

T1

380

(10

9)x

431

(16

4)y

435

(14

1)y

486

0

41n

s0

60n

sT

23

87(1

03)

x4

44(1

39)

y4

30(1

29)

y

T3

386

(10

2)x

437

(14

4)y

436

(11

8)y

Perc

eive

dse

veri

ty1

(pre

mat

ure

deat

h)T

14

75(1

83)

x5

71(1

68)

y5

81(1

49)

y4

55

60

0

11n

sT

24

96(1

69)

x5

54(1

65)

y5

75(1

51)

y

T3

501

(16

0)x

570

(14

9)y

568

(15

2)y

Perc

eive

dse

veri

ty2

(pai

n)T

15

07(1

44)

x6

08(0

97)

y6

01(0

95)

y8

75

1

06n

s0

23n

sT

24

88(1

37)

x5

92(1

09)

y5

91(1

03)

y

T3

493

(13

8)x

593

(10

5)y

605

(10

1)y

Fear

T1

437

(14

9)x

481

(13

0)y

463

(14

6)y

385

2

73n

s0

36n

sT

24

32(1

57)

x4

93(1

19)

y4

68(1

45)

y

T3

445

(14

8)x

501

(16

5)y

476

(13

3)y

Cop

ing

appr

aisa

lR

espo

nse

efc

acy

1(le

ssen

chan

ces

ofC

HD

)T

15

05(1

38)

x6

13(0

91)

y6

04(1

11)

y36

93

0

24n

s0

29n

sT

24

99(1

27)

x6

11(0

76)

y6

08(1

08)

y

T3

496

(12

4)x

605

(07

6)y

609

(08

8)y

Res

pons

eef

cac

y2

(red

uce

risk

ofC

HD

)T

14

74(1

45)

x5

40(1

93)

y5

77(1

48)

y10

61

2

45n

s0

41n

sT

24

88(1

50)

x5

44(1

80)

y5

67(1

39)

y

T3

492

(14

4)x

566

(15

4)y

589

(11

0)y

Self-

efc

acy

T1

494

(16

1)x

589

(12

0)y

586

(13

1)y

151

1

041

ns

046

ns

T2

486

(16

0)x

583

(13

0)y

593

(12

1)y

T3

486

(16

1)x

581

(12

3)y

586

(12

3)y


espo

nse

cost

sT

12

68(1

31)

x2

15(1

09)

y2

09(1

10)

y7

15

0

27n

s1

82n

sT

22

71(1

31)

x2

19(1

16)

y2

10(1

13)

y

T3

276

(12

8)x

208

(10

6)y

217

(11

6)y

Inte

ntio

nT

14

59(2

01)

x5

92(1

67)

y6

10(1

23)

y22

87

0

33n

s0

31n

sT

24

60(1

97)

x5

91(1

49)

y6

19(1

06)

y

T3

459

(20

1)x

587

(15

2)y

616

(12

0)y

Beha

viou

r(N

oof

sess

ions

)T

11

18(1

94)

x1

41(2

06)

x1

24(1

88)

x0

80n

s5

13

3

08

T2

095

(17

4)x

117

(17

4)x

101

(16

6)x

T3

084

(15

4)x

101

(15

4)x

161

(11

9)y

Not

eEx

pt1

=m

otiv

atio

nalm

anip

ulat

ion

grou

pEx

pt2

=m

otiv

atio

nali

nter

vent

ion

and

impl

emen

tatio

nin

tent

ion

grou

pa M

eans

with

diffe

rent

subs

crip

tsw

ithin

row

sdi

ffer

sign

ica

ntly

atle

ast

plt

05

bd

f=

124

7c d

f=

224

5
























































































Appendix 1



















Method






Interventions


















Measures









T2 2 73 1ndash7 422 127T3 2 75 1ndash7 421 126












Results















able

2D

iffer

ence

sin

PMT

vari

able

sin

tent

ion

and

beha

viou

rm

eans

acro

ssex

peri

men

talg

roup

stim

ean

dex

peri

men

talg

roup

acutetim

ein

tera

ctio

n

FC

ontr

olEx

pt1

Expt

2C

ondi

tionb

FF

Vari

able

Tim

eM

(SD

)aM

(SD

)aM

(SD

)a(e

xper

imen

talg

roup

)T

imeb

Con

ditio

nacute

timec

Thr

eat

appr

aisa

lPe

rcei

ved

vuln

erab

ility

T1

380

(10

9)x

431

(16

4)y

435

(14

1)y

486

0

41n

s0

60n

sT

23

87(1

03)

x4

44(1

39)

y4

30(1

29)

y

T3

386

(10

2)x

437

(14

4)y

436

(11

8)y

Perc

eive

dse

veri

ty1

(pre

mat

ure

deat

h)T

14

75(1

83)

x5

71(1

68)

y5

81(1

49)

y4

55

60

0

11n

sT

24

96(1

69)

x5

54(1

65)

y5

75(1

51)

y

T3

501

(16

0)x

570

(14

9)y

568

(15

2)y

Perc

eive

dse

veri

ty2

(pai

n)T

15

07(1

44)

x6

08(0

97)

y6

01(0

95)

y8

75

1

06n

s0

23n

sT

24

88(1

37)

x5

92(1

09)

y5

91(1

03)

y

T3

493

(13

8)x

593

(10

5)y

605

(10

1)y

Fear

T1

437

(14

9)x

481

(13

0)y

463

(14

6)y

385

2

73n

s0

36n

sT

24

32(1

57)

x4

93(1

19)

y4

68(1

45)

y

T3

445

(14

8)x

501

(16

5)y

476

(13

3)y

Cop

ing

appr

aisa

lR

espo

nse

efc

acy

1(le

ssen

chan

ces

ofC

HD

)T

15

05(1

38)

x6

13(0

91)

y6

04(1

11)

y36

93

0

24n

s0

29n

sT

24

99(1

27)

x6

11(0

76)

y6

08(1

08)

y

T3

496

(12

4)x

605

(07

6)y

609

(08

8)y

Res

pons

eef

cac

y2

(red

uce

risk

ofC

HD

)T

14

74(1

45)

x5

40(1

93)

y5

77(1

48)

y10

61

2

45n

s0

41n

sT

24

88(1

50)

x5

44(1

80)

y5

67(1

39)

y

T3

492

(14

4)x

566

(15

4)y

589

(11

0)y

Self-

efc

acy

T1

494

(16

1)x

589

(12

0)y

586

(13

1)y

151

1

041

ns

046

ns

T2

486

(16

0)x

583

(13

0)y

593

(12

1)y

T3

486

(16

1)x

581

(12

3)y

586

(12

3)y


espo

nse

cost

sT

12

68(1

31)

x2

15(1

09)

y2

09(1

10)

y7

15

0

27n

s1

82n

sT

22

71(1

31)

x2

19(1

16)

y2

10(1

13)

y

T3

276

(12

8)x

208

(10

6)y

217

(11

6)y

Inte

ntio

nT

14

59(2

01)

x5

92(1

67)

y6

10(1

23)

y22

87

0

33n

s0

31n

sT

24

60(1

97)

x5

91(1

49)

y6

19(1

06)

y

T3

459

(20

1)x

587

(15

2)y

616

(12

0)y

Beha

viou

r(N

oof

sess

ions

)T

11

18(1

94)

x1

41(2

06)

x1

24(1

88)

x0

80n

s5

13

3

08

T2

095

(17

4)x

117

(17

4)x

101

(16

6)x

T3

084

(15

4)x

101

(15

4)x

161

(11

9)y

Not

eEx

pt1

=m

otiv

atio

nalm

anip

ulat

ion

grou

pEx

pt2

=m

otiv

atio

nali

nter

vent

ion

and

impl

emen

tatio

nin

tent

ion

grou

pa M

eans

with

diffe

rent

subs

crip

tsw

ithin

row

sdi

ffer

sign

ica

ntly

atle

ast

plt

05

bd

f=

124

7c d

f=

224

5
























































































Appendix 1



















Interventions


















Measures









T2 2 73 1ndash7 422 127T3 2 75 1ndash7 421 126












Results















able

2D

iffer

ence

sin

PMT

vari

able

sin

tent

ion

and

beha

viou

rm

eans

acro

ssex

peri

men

talg

roup

stim

ean

dex

peri

men

talg

roup

acutetim

ein

tera

ctio

n

FC

ontr

olEx

pt1

Expt

2C

ondi

tionb

FF

Vari

able

Tim

eM

(SD

)aM

(SD

)aM

(SD

)a(e

xper

imen

talg

roup

)T

imeb

Con

ditio

nacute

timec

Thr

eat

appr

aisa

lPe

rcei

ved

vuln

erab

ility

T1

380

(10

9)x

431

(16

4)y

435

(14

1)y

486

0

41n

s0

60n

sT

23

87(1

03)

x4

44(1

39)

y4

30(1

29)

y

T3

386

(10

2)x

437

(14

4)y

436

(11

8)y

Perc

eive

dse

veri

ty1

(pre

mat

ure

deat

h)T

14

75(1

83)

x5

71(1

68)

y5

81(1

49)

y4

55

60

0

11n

sT

24

96(1

69)

x5

54(1

65)

y5

75(1

51)

y

T3

501

(16

0)x

570

(14

9)y

568

(15

2)y

Perc

eive

dse

veri

ty2

(pai

n)T

15

07(1

44)

x6

08(0

97)

y6

01(0

95)

y8

75

1

06n

s0

23n

sT

24

88(1

37)

x5

92(1

09)

y5

91(1

03)

y

T3

493

(13

8)x

593

(10

5)y

605

(10

1)y

Fear

T1

437

(14

9)x

481

(13

0)y

463

(14

6)y

385

2

73n

s0

36n

sT

24

32(1

57)

x4

93(1

19)

y4

68(1

45)

y

T3

445

(14

8)x

501

(16

5)y

476

(13

3)y

Cop

ing

appr

aisa

lR

espo

nse

efc

acy

1(le

ssen

chan

ces

ofC

HD

)T

15

05(1

38)

x6

13(0

91)

y6

04(1

11)

y36

93

0

24n

s0

29n

sT

24

99(1

27)

x6

11(0

76)

y6

08(1

08)

y

T3

496

(12

4)x

605

(07

6)y

609

(08

8)y

Res

pons

eef

cac

y2

(red

uce

risk

ofC

HD

)T

14

74(1

45)

x5

40(1

93)

y5

77(1

48)

y10

61

2

45n

s0

41n

sT

24

88(1

50)

x5

44(1

80)

y5

67(1

39)

y

T3

492

(14

4)x

566

(15

4)y

589

(11

0)y

Self-

efc

acy

T1

494

(16

1)x

589

(12

0)y

586

(13

1)y

151

1

041

ns

046

ns

T2

486

(16

0)x

583

(13

0)y

593

(12

1)y

T3

486

(16

1)x

581

(12

3)y

586

(12

3)y


espo

nse

cost

sT

12

68(1

31)

x2

15(1

09)

y2

09(1

10)

y7

15

0

27n

s1

82n

sT

22

71(1

31)

x2

19(1

16)

y2

10(1

13)

y

T3

276

(12

8)x

208

(10

6)y

217

(11

6)y

Inte

ntio

nT

14

59(2

01)

x5

92(1

67)

y6

10(1

23)

y22

87

0

33n

s0

31n

sT

24

60(1

97)

x5

91(1

49)

y6

19(1

06)

y

T3

459

(20

1)x

587

(15

2)y

616

(12

0)y

Beha

viou

r(N

oof

sess

ions

)T

11

18(1

94)

x1

41(2

06)

x1

24(1

88)

x0

80n

s5

13

3

08

T2

095

(17

4)x

117

(17

4)x

101

(16

6)x

T3

084

(15

4)x

101

(15

4)x

161

(11

9)y

Not

eEx

pt1

=m

otiv

atio

nalm

anip

ulat

ion

grou

pEx

pt2

=m

otiv

atio

nali

nter

vent

ion

and

impl

emen

tatio

nin

tent

ion

grou

pa M

eans

with

diffe

rent

subs

crip

tsw

ithin

row

sdi

ffer

sign

ica

ntly

atle

ast

plt

05

bd

f=

124

7c d

f=

224

5
























































































Appendix 1
























Measures









T2 2 73 1ndash7 422 127T3 2 75 1ndash7 421 126












Results















able

2D

iffer

ence

sin

PMT

vari

able

sin

tent

ion

and

beha

viou

rm

eans

acro

ssex

peri

men

talg

roup

stim

ean

dex

peri

men

talg

roup

acutetim

ein

tera

ctio

n

FC

ontr

olEx

pt1

Expt

2C

ondi

tionb

FF

Vari

able

Tim

eM

(SD

)aM

(SD

)aM

(SD

)a(e

xper

imen

talg

roup

)T

imeb

Con

ditio

nacute

timec

Thr

eat

appr

aisa

lPe

rcei

ved

vuln

erab

ility

T1

380

(10

9)x

431

(16

4)y

435

(14

1)y

486

0

41n

s0

60n

sT

23

87(1

03)

x4

44(1

39)

y4

30(1

29)

y

T3

386

(10

2)x

437

(14

4)y

436

(11

8)y

Perc

eive

dse

veri

ty1

(pre

mat

ure

deat

h)T

14

75(1

83)

x5

71(1

68)

y5

81(1

49)

y4

55

60

0

11n

sT

24

96(1

69)

x5

54(1

65)

y5

75(1

51)

y

T3

501

(16

0)x

570

(14

9)y

568

(15

2)y

Perc

eive

dse

veri

ty2

(pai

n)T

15

07(1

44)

x6

08(0

97)

y6

01(0

95)

y8

75

1

06n

s0

23n

sT

24

88(1

37)

x5

92(1

09)

y5

91(1

03)

y

T3

493

(13

8)x

593

(10

5)y

605

(10

1)y

Fear

T1

437

(14

9)x

481

(13

0)y

463

(14

6)y

385

2

73n

s0

36n

sT

24

32(1

57)

x4

93(1

19)

y4

68(1

45)

y

T3

445

(14

8)x

501

(16

5)y

476

(13

3)y

Cop

ing

appr

aisa

lR

espo

nse

efc

acy

1(le

ssen

chan

ces

ofC

HD

)T

15

05(1

38)

x6

13(0

91)

y6

04(1

11)

y36

93

0

24n

s0

29n

sT

24

99(1

27)

x6

11(0

76)

y6

08(1

08)

y

T3

496

(12

4)x

605

(07

6)y

609

(08

8)y

Res

pons

eef

cac

y2

(red

uce

risk

ofC

HD

)T

14

74(1

45)

x5

40(1

93)

y5

77(1

48)

y10

61

2

45n

s0

41n

sT

24

88(1

50)

x5

44(1

80)

y5

67(1

39)

y

T3

492

(14

4)x

566

(15

4)y

589

(11

0)y

Self-

efc

acy

T1

494

(16

1)x

589

(12

0)y

586

(13

1)y

151

1

041

ns

046

ns

T2

486

(16

0)x

583

(13

0)y

593

(12

1)y

T3

486

(16

1)x

581

(12

3)y

586

(12

3)y


espo

nse

cost

sT

12

68(1

31)

x2

15(1

09)

y2

09(1

10)

y7

15

0

27n

s1

82n

sT

22

71(1

31)

x2

19(1

16)

y2

10(1

13)

y

T3

276

(12

8)x

208

(10

6)y

217

(11

6)y

Inte

ntio

nT

14

59(2

01)

x5

92(1

67)

y6

10(1

23)

y22

87

0

33n

s0

31n

sT

24

60(1

97)

x5

91(1

49)

y6

19(1

06)

y

T3

459

(20

1)x

587

(15

2)y

616

(12

0)y

Beha

viou

r(N

oof

sess

ions

)T

11

18(1

94)

x1

41(2

06)

x1

24(1

88)

x0

80n

s5

13

3

08

T2

095

(17

4)x

117

(17

4)x

101

(16

6)x

T3

084

(15

4)x

101

(15

4)x

161

(11

9)y

Not

eEx

pt1

=m

otiv

atio

nalm

anip

ulat

ion

grou

pEx

pt2

=m

otiv

atio

nali

nter

vent

ion

and

impl

emen

tatio

nin

tent

ion

grou

pa M

eans

with

diffe

rent

subs

crip

tsw

ithin

row

sdi

ffer

sign

ica

ntly

atle

ast

plt

05

bd

f=

124

7c d

f=

224

5
























































































Appendix 1
























T2 2 73 1ndash7 422 127T3 2 75 1ndash7 421 126












Results















able

2D

iffer

ence

sin

PMT

vari

able

sin

tent

ion

and

beha

viou

rm

eans

acro

ssex

peri

men

talg

roup

stim

ean

dex

peri

men

talg

roup

acutetim

ein

tera

ctio

n

FC

ontr

olEx

pt1

Expt

2C

ondi

tionb

FF

Vari

able

Tim

eM

(SD

)aM

(SD

)aM

(SD

)a(e

xper

imen

talg

roup

)T

imeb

Con

ditio

nacute

timec

Thr

eat

appr

aisa

lPe

rcei

ved

vuln

erab

ility

T1

380

(10

9)x

431

(16

4)y

435

(14

1)y

486

0

41n

s0

60n

sT

23

87(1

03)

x4

44(1

39)

y4

30(1

29)

y

T3

386

(10

2)x

437

(14

4)y

436

(11

8)y

Perc

eive

dse

veri

ty1

(pre

mat

ure

deat

h)T

14

75(1

83)

x5

71(1

68)

y5

81(1

49)

y4

55

60

0

11n

sT

24

96(1

69)

x5

54(1

65)

y5

75(1

51)

y

T3

501

(16

0)x

570

(14

9)y

568

(15

2)y

Perc

eive

dse

veri

ty2

(pai

n)T

15

07(1

44)

x6

08(0

97)

y6

01(0

95)

y8

75

1

06n

s0

23n

sT

24

88(1

37)

x5

92(1

09)

y5

91(1

03)

y

T3

493

(13

8)x

593

(10

5)y

605

(10

1)y

Fear

T1

437

(14

9)x

481

(13

0)y

463

(14

6)y

385

2

73n

s0

36n

sT

24

32(1

57)

x4

93(1

19)

y4

68(1

45)

y

T3

445

(14

8)x

501

(16

5)y

476

(13

3)y

Cop

ing

appr

aisa

lR

espo

nse

efc

acy

1(le

ssen

chan

ces

ofC

HD

)T

15

05(1

38)

x6

13(0

91)

y6

04(1

11)

y36

93

0

24n

s0

29n

sT

24

99(1

27)

x6

11(0

76)

y6

08(1

08)

y

T3

496

(12

4)x

605

(07

6)y

609

(08

8)y

Res

pons

eef

cac

y2

(red

uce

risk

ofC

HD

)T

14

74(1

45)

x5

40(1

93)

y5

77(1

48)

y10

61

2

45n

s0

41n

sT

24

88(1

50)

x5

44(1

80)

y5

67(1

39)

y

T3

492

(14

4)x

566

(15

4)y

589

(11

0)y

Self-

efc

acy

T1

494

(16

1)x

589

(12

0)y

586

(13

1)y

151

1

041

ns

046

ns

T2

486

(16

0)x

583

(13

0)y

593

(12

1)y

T3

486

(16

1)x

581

(12

3)y

586

(12

3)y


espo

nse

cost

sT

12

68(1

31)

x2

15(1

09)

y2

09(1

10)

y7

15

0

27n

s1

82n

sT

22

71(1

31)

x2

19(1

16)

y2

10(1

13)

y

T3

276

(12

8)x

208

(10

6)y

217

(11

6)y

Inte

ntio

nT

14

59(2

01)

x5

92(1

67)

y6

10(1

23)

y22

87

0

33n

s0

31n

sT

24

60(1

97)

x5

91(1

49)

y6

19(1

06)

y

T3

459

(20

1)x

587

(15

2)y

616

(12

0)y

Beha

viou

r(N

oof

sess

ions

)T

11

18(1

94)

x1

41(2

06)

x1

24(1

88)

x0

80n

s5

13

3

08

T2

095

(17

4)x

117

(17

4)x

101

(16

6)x

T3

084

(15

4)x

101

(15

4)x

161

(11

9)y

Not

eEx

pt1

=m

otiv

atio

nalm

anip

ulat

ion

grou

pEx

pt2

=m

otiv

atio

nali

nter

vent

ion

and

impl

emen

tatio

nin

tent

ion

grou

pa M

eans

with

diffe

rent

subs

crip

tsw

ithin

row

sdi

ffer

sign

ica

ntly

atle

ast

plt

05

bd

f=

124

7c d

f=

224

5
























































































Appendix 1



















Results















able

2D

iffer

ence

sin

PMT

vari

able

sin

tent

ion

and

beha

viou

rm

eans

acro

ssex

peri

men

talg

roup

stim

ean

dex

peri

men

talg

roup

acutetim

ein

tera

ctio

n

FC

ontr

olEx

pt1

Expt

2C

ondi

tionb

FF

Vari

able

Tim

eM

(SD

)aM

(SD

)aM

(SD

)a(e

xper

imen

talg

roup

)T

imeb

Con

ditio

nacute

timec

Thr

eat

appr

aisa

lPe

rcei

ved

vuln

erab

ility

T1

380

(10

9)x

431

(16

4)y

435

(14

1)y

486

0

41n

s0

60n

sT

23

87(1

03)

x4

44(1

39)

y4

30(1

29)

y

T3

386

(10

2)x

437

(14

4)y

436

(11

8)y

Perc

eive

dse

veri

ty1

(pre

mat

ure

deat

h)T

14

75(1

83)

x5

71(1

68)

y5

81(1

49)

y4

55

60

0

11n

sT

24

96(1

69)

x5

54(1

65)

y5

75(1

51)

y

T3

501

(16

0)x

570

(14

9)y

568

(15

2)y

Perc

eive

dse

veri

ty2

(pai

n)T

15

07(1

44)

x6

08(0

97)

y6

01(0

95)

y8

75

1

06n

s0

23n

sT

24

88(1

37)

x5

92(1

09)

y5

91(1

03)

y

T3

493

(13

8)x

593

(10

5)y

605

(10

1)y

Fear

T1

437

(14

9)x

481

(13

0)y

463

(14

6)y

385

2

73n

s0

36n

sT

24

32(1

57)

x4

93(1

19)

y4

68(1

45)

y

T3

445

(14

8)x

501

(16

5)y

476

(13

3)y

Cop

ing

appr

aisa

lR

espo

nse

efc

acy

1(le

ssen

chan

ces

ofC

HD

)T

15

05(1

38)

x6

13(0

91)

y6

04(1

11)

y36

93

0

24n

s0

29n

sT

24

99(1

27)

x6

11(0

76)

y6

08(1

08)

y

T3

496

(12

4)x

605

(07

6)y

609

(08

8)y

Res

pons

eef

cac

y2

(red

uce

risk

ofC

HD

)T

14

74(1

45)

x5

40(1

93)

y5

77(1

48)

y10

61

2

45n

s0

41n

sT

24

88(1

50)

x5

44(1

80)

y5

67(1

39)

y

T3

492

(14

4)x

566

(15

4)y

589

(11

0)y

Self-

efc

acy

T1

494

(16

1)x

589

(12

0)y

586

(13

1)y

151

1

041

ns

046

ns

T2

486

(16

0)x

583

(13

0)y

593

(12

1)y

T3

486

(16

1)x

581

(12

3)y

586

(12

3)y


espo

nse

cost

sT

12

68(1

31)

x2

15(1

09)

y2

09(1

10)

y7

15

0

27n

s1

82n

sT

22

71(1

31)

x2

19(1

16)

y2

10(1

13)

y

T3

276

(12

8)x

208

(10

6)y

217

(11

6)y

Inte

ntio

nT

14

59(2

01)

x5

92(1

67)

y6

10(1

23)

y22

87

0

33n

s0

31n

sT

24

60(1

97)

x5

91(1

49)

y6

19(1

06)

y

T3

459

(20

1)x

587

(15

2)y

616

(12

0)y

Beha

viou

r(N

oof

sess

ions

)T

11

18(1

94)

x1

41(2

06)

x1

24(1

88)

x0

80n

s5

13

3

08

T2

095

(17

4)x

117

(17

4)x

101

(16

6)x

T3

084

(15

4)x

101

(15

4)x

161

(11

9)y

Not

eEx

pt1

=m

otiv

atio

nalm

anip

ulat

ion

grou

pEx

pt2

=m

otiv

atio

nali

nter

vent

ion

and

impl

emen

tatio

nin

tent

ion

grou

pa M

eans

with

diffe

rent

subs

crip

tsw

ithin

row

sdi

ffer

sign

ica

ntly

atle

ast

plt

05

bd

f=

124

7c d

f=

224

5
























































































Appendix 1



























able

2D

iffer

ence

sin

PMT

vari

able

sin

tent

ion

and

beha

viou

rm

eans

acro

ssex

peri

men

talg

roup

stim

ean

dex

peri

men

talg

roup

acutetim

ein

tera

ctio

n

FC

ontr

olEx

pt1

Expt

2C

ondi

tionb

FF

Vari

able

Tim

eM

(SD

)aM

(SD

)aM

(SD

)a(e

xper

imen

talg

roup

)T

imeb

Con

ditio

nacute

timec

Thr

eat

appr

aisa

lPe

rcei

ved

vuln

erab

ility

T1

380

(10

9)x

431

(16

4)y

435

(14

1)y

486

0

41n

s0

60n

sT

23

87(1

03)

x4

44(1

39)

y4

30(1

29)

y

T3

386

(10

2)x

437

(14

4)y

436

(11

8)y

Perc

eive

dse

veri

ty1

(pre

mat

ure

deat

h)T

14

75(1

83)

x5

71(1

68)

y5

81(1

49)

y4

55

60

0

11n

sT

24

96(1

69)

x5

54(1

65)

y5

75(1

51)

y

T3

501

(16

0)x

570

(14

9)y

568

(15

2)y

Perc

eive

dse

veri

ty2

(pai

n)T

15

07(1

44)

x6

08(0

97)

y6

01(0

95)

y8

75

1

06n

s0

23n

sT

24

88(1

37)

x5

92(1

09)

y5

91(1

03)

y

T3

493

(13

8)x

593

(10

5)y

605

(10

1)y

Fear

T1

437

(14

9)x

481

(13

0)y

463

(14

6)y

385

2

73n

s0

36n

sT

24

32(1

57)

x4

93(1

19)

y4

68(1

45)

y

T3

445

(14

8)x

501

(16

5)y

476

(13

3)y

Cop

ing

appr

aisa

lR

espo

nse

efc

acy

1(le

ssen

chan

ces

ofC

HD

)T

15

05(1

38)

x6

13(0

91)

y6

04(1

11)

y36

93

0

24n

s0

29n

sT

24

99(1

27)

x6

11(0

76)

y6

08(1

08)

y

T3

496

(12

4)x

605

(07

6)y

609

(08

8)y

Res

pons

eef

cac

y2

(red

uce

risk

ofC

HD

)T

14

74(1

45)

x5

40(1

93)

y5

77(1

48)

y10

61

2

45n

s0

41n

sT

24

88(1

50)

x5

44(1

80)

y5

67(1

39)

y

T3

492

(14

4)x

566

(15

4)y

589

(11

0)y

Self-

efc

acy

T1

494

(16

1)x

589

(12

0)y

586

(13

1)y

151

1

041

ns

046

ns

T2

486

(16

0)x

583

(13

0)y

593

(12

1)y

T3

486

(16

1)x

581

(12

3)y

586

(12

3)y


espo

nse

cost

sT

12

68(1

31)

x2

15(1

09)

y2

09(1

10)

y7

15

0

27n

s1

82n

sT

22

71(1

31)

x2

19(1

16)

y2

10(1

13)

y

T3

276

(12

8)x

208

(10

6)y

217

(11

6)y

Inte

ntio

nT

14

59(2

01)

x5

92(1

67)

y6

10(1

23)

y22

87

0

33n

s0

31n

sT

24

60(1

97)

x5

91(1

49)

y6

19(1

06)

y

T3

459

(20

1)x

587

(15

2)y

616

(12

0)y

Beha

viou

r(N

oof

sess

ions

)T

11

18(1

94)

x1

41(2

06)

x1

24(1

88)

x0

80n

s5

13

3

08

T2

095

(17

4)x

117

(17

4)x

101

(16

6)x

T3

084

(15

4)x

101

(15

4)x

161

(11

9)y

Not

eEx

pt1

=m

otiv

atio

nalm

anip

ulat

ion

grou

pEx

pt2

=m

otiv

atio

nali

nter

vent

ion

and

impl

emen

tatio

nin

tent

ion

grou

pa M

eans

with

diffe

rent

subs

crip

tsw

ithin

row

sdi

ffer

sign

ica

ntly

atle

ast

plt

05

bd

f=

124

7c d

f=

224

5
























































































Appendix 1




















able

2D

iffer

ence

sin

PMT

vari

able

sin

tent

ion

and

beha

viou

rm

eans

acro

ssex

peri

men

talg

roup

stim

ean

dex

peri

men

talg

roup

acutetim

ein

tera

ctio

n

FC

ontr

olEx

pt1

Expt

2C

ondi

tionb

FF

Vari

able

Tim

eM

(SD

)aM

(SD

)aM

(SD

)a(e

xper

imen

talg

roup

)T

imeb

Con

ditio

nacute

timec

Thr

eat

appr

aisa

lPe

rcei

ved

vuln

erab

ility

T1

380

(10

9)x

431

(16

4)y

435

(14

1)y

486

0

41n

s0

60n

sT

23

87(1

03)

x4

44(1

39)

y4

30(1

29)

y

T3

386

(10

2)x

437

(14

4)y

436

(11

8)y

Perc

eive

dse

veri

ty1

(pre

mat

ure

deat

h)T

14

75(1

83)

x5

71(1

68)

y5

81(1

49)

y4

55

60

0

11n

sT

24

96(1

69)

x5

54(1

65)

y5

75(1

51)

y

T3

501

(16

0)x

570

(14

9)y

568

(15

2)y

Perc

eive

dse

veri

ty2

(pai

n)T

15

07(1

44)

x6

08(0

97)

y6

01(0

95)

y8

75

1

06n

s0

23n

sT

24

88(1

37)

x5

92(1

09)

y5

91(1

03)

y

T3

493

(13

8)x

593

(10

5)y

605

(10

1)y

Fear

T1

437

(14

9)x

481

(13

0)y

463

(14

6)y

385

2

73n

s0

36n

sT

24

32(1

57)

x4

93(1

19)

y4

68(1

45)

y

T3

445

(14

8)x

501

(16

5)y

476

(13

3)y

Cop

ing

appr

aisa

lR

espo

nse

efc

acy

1(le

ssen

chan

ces

ofC

HD

)T

15

05(1

38)

x6

13(0

91)

y6

04(1

11)

y36

93

0

24n

s0

29n

sT

24

99(1

27)

x6

11(0

76)

y6

08(1

08)

y

T3

496

(12

4)x

605

(07

6)y

609

(08

8)y

Res

pons

eef

cac

y2

(red

uce

risk

ofC

HD

)T

14

74(1

45)

x5

40(1

93)

y5

77(1

48)

y10

61

2

45n

s0

41n

sT

24

88(1

50)

x5

44(1

80)

y5

67(1

39)

y

T3

492

(14

4)x

566

(15

4)y

589

(11

0)y

Self-

efc

acy

T1

494

(16

1)x

589

(12

0)y

586

(13

1)y

151

1

041

ns

046

ns

T2

486

(16

0)x

583

(13

0)y

593

(12

1)y

T3

486

(16

1)x

581

(12

3)y

586

(12

3)y


espo

nse

cost

sT

12

68(1

31)

x2

15(1

09)

y2

09(1

10)

y7

15

0

27n

s1

82n

sT

22

71(1

31)

x2

19(1

16)

y2

10(1

13)

y

T3

276

(12

8)x

208

(10

6)y

217

(11

6)y

Inte

ntio

nT

14

59(2

01)

x5

92(1

67)

y6

10(1

23)

y22

87

0

33n

s0

31n

sT

24

60(1

97)

x5

91(1

49)

y6

19(1

06)

y

T3

459

(20

1)x

587

(15

2)y

616

(12

0)y

Beha

viou

r(N

oof

sess

ions

)T

11

18(1

94)

x1

41(2

06)

x1

24(1

88)

x0

80n

s5

13

3

08

T2

095

(17

4)x

117

(17

4)x

101

(16

6)x

T3

084

(15

4)x

101

(15

4)x

161

(11

9)y

Not

eEx

pt1

=m

otiv

atio

nalm

anip

ulat

ion

grou

pEx

pt2

=m

otiv

atio

nali

nter

vent

ion

and

impl

emen

tatio

nin

tent

ion

grou

pa M

eans

with

diffe

rent

subs

crip

tsw

ithin

row

sdi

ffer

sign

ica

ntly

atle

ast

plt

05

bd

f=

124

7c d

f=

224

5
























































































Appendix 1




















espo

nse

cost

sT

12

68(1

31)

x2

15(1

09)

y2

09(1

10)

y7

15

0

27n

s1

82n

sT

22

71(1

31)

x2

19(1

16)

y2

10(1

13)

y

T3

276

(12

8)x

208

(10

6)y

217

(11

6)y

Inte

ntio

nT

14

59(2

01)

x5

92(1

67)

y6

10(1

23)

y22

87

0

33n

s0

31n

sT

24

60(1

97)

x5

91(1

49)

y6

19(1

06)

y

T3

459

(20

1)x

587

(15

2)y

616

(12

0)y

Beha

viou

r(N

oof

sess

ions

)T

11

18(1

94)

x1

41(2

06)

x1

24(1

88)

x0

80n

s5

13

3

08

T2

095

(17

4)x

117

(17

4)x

101

(16

6)x

T3

084

(15

4)x

101

(15

4)x

161

(11

9)y

Not

eEx

pt1

=m

otiv

atio

nalm

anip

ulat

ion

grou

pEx

pt2

=m

otiv

atio

nali

nter

vent

ion

and

impl

emen

tatio

nin

tent

ion

grou

pa M

eans

with

diffe

rent

subs

crip

tsw

ithin

row

sdi

ffer

sign

ica

ntly

atle

ast

plt

05

bd

f=

124

7c d

f=

224

5
























































































Appendix 1










































































































Appendix 1



































































































Appendix 1





















































































Appendix 1















































































Appendix 1









































































Appendix 1




































































Appendix 1













































Appendix 1

























Appendix 1


























Combining motivational and volitional interventions to promote exercise participation: Protection motivation theory and implementation intentions

Documents

Combining motivational and volitional interventions to promote exercise participation: Protection motivation theory and implementation intentions