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Increasing Attendance for Psychotherapy: Implementation Intentions andthe Self-Regulation of Attendance-Related Negative Affect

Paschal SheeranUniversity of Sheffield

Richard AubreyBradford Hospital

Stephen KellettKeresforth Centre, Barnsley

The present study evaluated an implementation intention intervention that aimed to increase attendanceat scheduled, initial appointments for psychotherapy by helping clients to manage negative feelings aboutattendance. Participants received a postal questionnaire that measured their views about attendingpsychotherapy. One half of the sample was randomly assigned to an implementation intention inductionthat was embedded in the questionnaire. Intention-to-treat analysis (N � 390) indicated that participantswho formed implementation intentions were more likely to attend compared to controls (75% vs. 63%),and this effect was even stronger among participants who returned the questionnaire (83% vs. 57%).Whereas anticipated affective costs (e.g., shame) had a negative impact on attendance for mostparticipants, this effect was attenuated when participants formed implementation intentions and perceivedthat attendance would be beneficial. Thus, implementation intention formation can help clients to dealeffectively with negative feelings that might otherwise prevent them attending their 1st psychotherapyappointment.

Keywords: implementation intention, affect regulation, dropout, psychotherapy

Nonattendance for psychotherapy (also termed unilateral orpremature termination, client attrition, or therapy dropout) is asignificant problem for mental health services (e.g., Garfield,1994). Nonattendance rates for psychotherapy are substantial (e.g.,Wierbicki & Pekarik, 1993) and have serious, negative clinical andfinancial consequences (Pekarik, 1985). Most research concernedwith understanding premature termination of psychotherapy hasexamined associations between demographic factors (e.g., socio-economic status, education) and attendance (see Wierbicki &Pekarik, 1993, for a review); few studies have used relevantpsychosocial theories to understand clients’ motivation to attend.There is also a paucity of experimental (intervention) studies inthis area. For instance, a recent review of intervention strategies toprevent premature termination found that only 15 empirical studieshad been published since 1970 (Ogrodniczuk, Joyce, & Piper,2005). Although techniques such as pretherapy preparation wereeffective in reducing rates of nonattendance in some studies (e.g.,Lambert & Lambert, 1984; Larsen, Nguyen, Green, & Attkisson,1983; Reis & Brown, 2006), a similar number showed no signif-icant effect on attendance (Ogrodniczuk et al., 2005). The presentresearch attempts to redress the dearth of theory-based and inter-

vention studies on attendance for psychotherapy. We use an es-tablished model of the psychosocial predictors of behavior—thetheory of planned behavior (TPB; Ajzen, 1991)—to measure par-ticipants’ motivation to attend psychotherapy prior to a theory-based intervention designed to increase attendance rates. The in-tervention tests the utility of implementation intention formation,or if–then planning (Gollwitzer, 1993, 1999; Gollwitzer & Shee-ran, 2006), in helping people to attend their psychotherapy ap-pointment.

Nonattendance for Psychotherapy

Although not all individuals who fail to attend scheduled psy-chotherapy appointments have negative outcomes, accumulatedevidence suggests that initiating and maintaining psychotherapyoffers clinical benefits (e.g., Bleiberg, Devlin, Croan, & Briscoe,1994; Heilbrun, 1982; Howard, Kopta, Krause, & Orlinsky, 1986).As well as the costs to clients of missing an opportunity to obtainpsychotherapy, nonattendance also has financial and other costsfor clinicians and mental health services (Baekeland & Lundwall,1975; Carpenter, Del Gaudio, & Morrow, 1979; Pekarik, 1985).Despite these considerations, a meta-analysis of 125 studies ob-tained a mean dropout rate of 47% (Wierbicki & Pekarik, 1993).The average length of stay in treatment appears to be 6 sessions(e.g., Garfield, 1994; National Institute of Mental Health, 1981),and approximately 80% of clients cease attending before their 10thsession (Pekarik, 1991). Thus, even though remaining in treatmentis beneficial, attending all recommended psychotherapy sessions isrelatively uncommon.

It is important to note that definitions of attendance, unilateraltermination, attrition, and dropout are not uniform across studies,

Paschal Sheeran, Department of Psychology, University of Sheffield,Sheffield, England; Richard Aubrey, Bradford Hospital, Bradford, En-gland; Steven Kellett, Keresforth Centre, Barnsley, England.

We thank Gillian Hardy and Tom Webb for comments on a draft of thearticle.

Correspondence concerning this article should be addressed to PaschalSheeran, Department of Psychology, University of Sheffield, Sheffield S102TP, England. E-mail: p.sheeran@sheffield.ac.uk

Journal of Consulting and Clinical Psychology Copyright 2007 by the American Psychological Association2007, Vol. ●, No. ●, 000–000 0022-006X/07/$12.00 DOI: 10.1037/0022-006X.●.●.000

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and different researchers have used different cutoff points to definethese terms. Garfield (1994) drew an important distinction betweenattrition and treatment refusal (i.e., individuals who fail to attendtheir initial appointment). Garfield claimed that individuals who donot attend their initial appointment represent a distinct groupcompared to clients who decide to cease attending once treatmentis properly underway (see also Pekarik, 1983, 1992). A recentreview indicated that treatment refusal is a significant problem.Hampton-Robb, Qualls, and Compton (2003) found that, on aver-age, 40% of clients failed to attend their initial appointment forpsychotherapy across 12 studies. It might be argued that peoplewho do not follow up on referral to treatment and fail to attendeven a first appointment are a particularly vulnerable group be-cause no treatment at all is obtained. The present research isexplicitly concerned with understanding the factors that influenceattendance among this group and with testing the utility of imple-mentation intention formation in facilitating their attendance.Thus, in the current study, attendance versus nonattendance isdefined by whether individuals come to their initial appointmentfor psychotherapy.

The TPB: A Model of Motivation to AttendPsychotherapy

Phillips (1995) argued that solving the problem of nonatten-dance for psychotherapy requires an understanding of the psycho-logical factors that underpin the problem (see also Harris, 1998).The TPB (Ajzen, 1991) is perhaps the most widely used model ofthe psychosocial determinants of behavior and has been used tounderstand and predict attendance in a variety of health settings(e.g., Norman & Conner, 1993; Sheeran & Silverman, 2003; seethe review by McEachan, Conner, & Lawton, 2007). Thus, theTPB seems to provide a useful framework for understandingpeople’s motivation to attend appointments for psychotherapy.

According to the TPB, the most immediate and important pre-dictor of behavior is the person’s decision or intention to performit (e.g., “I intend to attend my psychotherapy appointment”).Intentions are assumed to capture the motivational factors thatinfluence behavior and indicate how hard people will try and howmuch effort they will devote to performing the behavior (Ajzen,1991; Webb & Sheeran, 2005). Intentions, in turn, are determinedby three factors—namely, attitude, subjective norm, and perceivedbehavioral control (PBC). Attitude refers to people’s overall eval-uation of performing the behavior and appears to have four keycomponents (e.g., Abraham, Sheeran, & Johnston, 1998; Bandura,1998; Dijkstra, Bakker, de Vries, 1997; Richard, van der Pligt, &de Vries, 1995; Sparks, 2000): (a) affective attitudes (e.g., “At-tending my psychotherapy appointment would make me feel em-barrassed”), (b) cognitive attitude (e.g., “I think that attending mypsychotherapy appointment would be worthwhile”; Trafimow &Sheeran, 1998), (c) anticipated regret (e.g., “If I did not attend mypsychotherapy appointment, I would regret it”; Richard et al.,1995; Sheeran & Orbell, 1999), and (d) self-evaluative outcomes(e.g., “Attending my psychotherapy appointment would make mesee myself as mature”; Bandura, 1997). Subjective norm refers topeople’s perceptions of social pressure from significant others toperform, or not to perform, a behavior (e.g., “Most people who areimportant to me think that I should attend my psychotherapyappointment”). Finally, PBC is conceptually similar to Bandura’s

(1997) construct of self-efficacy and refers to people’s appraisal oftheir ability to perform a behavior (e.g., “I am confident that I willbe able to attend my psychotherapy appointment”). Ajzen (1991)claimed that variables that are not specified by the TPB shouldaffect behavior only indirectly (i.e., through their influence onattitude, subjective norm, PBC, and, ultimately, intention). Thus,the effects of demographic factors that are associated with atten-dance for psychotherapy, such as socioeconomic status (SES) oreducation, should be mediated by the behavior-specific psycho-social variables specified by the theory.

Meta-analytic reviews support TPB predictions (e.g., Armitage& Conner, 2001; Conner & Sparks, 2005; Godin & Kok, 1996;Sheeran, 2002). For instance, a meta-analysis of 422 studies indi-cated that intention explained 28% of the variance in behavior inprospective studies (Sheeran, 2002). Attitude, subjective norm,and PBC typically account for 30%–40% of the variance inintentions (Armitage & Conner, 2001; Godin & Kok, 1996; Shee-ran & Taylor, 1999). These proportions of variance in intentionsand behavior constitute large effect sizes according to Cohen’s(1992) power primer. Reviews also support the TPB’s claim thatintention mediates the influence on behavior of both the theory’spredictors (attitude, subjective norm, and PBC) and its extraneousvariables (demographic and personality variables; e.g., Ajzen &Fishbein, 2005; Conner & Sparks, 2005).

Implementation Intentions: Nature, Effects, and Processes

Although meta-analytic reviews show that intentions have alarge effect on subsequent behavior, evidence also indicates thateven strong intentions do not guarantee behavioral performance(Sheeran, 2002; Webb & Sheeran, 2006). For instance, studies thatanalyzed the relationship between intention and behavior in termsof a 2 (intend to act: yes vs. no) � 2 (subsequently act: yes vs. no)matrix have shown that approximately 50% of people who intendto perform respective behaviors fail to translate their good inten-tions into action (Orbell & Sheeran, 1998; review by Sheeran,2002). To understand this gap between intention and action, Goll-witzer (1993) drew a distinction between two different types ofintention—namely, goal intentions versus implementation inten-tions. Goal intentions specify the behavior that one will try toperform or the goal that one wants to achieve and have the format“I intend to achieve X.” Implementation intentions, conversely,spell out the exact response that one will initiate to reach one’sgoal and the precise situational context in which that response willbe instigated (e.g., “If it is situation Y, then I will initiate goal-directed response Z”). For example, whereas a goal intentionmight state “I intend to exercise this week,” a correspondingimplementation intention might be “If it is 5 pm on Monday, thenI will jog home from work.” Thus, a goal intention specifies whatone intends to do, whereas an implementation intention specifiesthe when, where, and how of what one intends to do.

Accumulated evidence indicates that forming implementationintentions increases rates of behavioral performance and goalattainment compared to merely forming respective goal intentions(e.g., Gollwitzer, 1999; Gollwitzer, Bayer, & McCulloch, 2005;Sheeran, 2002). A meta-analysis of 94 studies showed that imple-mentation intention formation had a medium to large effect acrossa wide range of behaviors (d � 0.65; Gollwitzer & Sheeran, 2006).This type of planning proved effective in managing key self-

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regulatory problems that can undermine the translation of inten-tions into behavior. For instance, participants who formed imple-mentation intentions were more likely to initiate goal striving andshield ongoing goal pursuits from unwanted influences comparedto participants who held equivalent goal intentions but did notform respective implementation intentions (Gollwitzer & Sheeran,2006).

Implementation intention formation has proved effective in pro-moting attendance behaviors in previous research. For instance,Sheeran and Silverman (2003) asked one half of a sample ofuniversity employees to plan when and where they would attend aworkplace health and safety training session. Attendance recordsindicated that, whereas only 14% of control participants attendeda training session over the subsequent 3 months, 35% of partici-pants who formed if–then plans did so. Sheeran and Orbell (2000)randomized women to an implementation intention induction inwhich the participants specified when, where, and how they wouldmake an appointment for cervical cancer screening (or to a no-plancontrol condition). Chart review of attendance indicated that 69%of control participants attended for screening; among participantswho planned how to make an appointment, however, the atten-dance rate was 92%. These findings indicate that forming anif–then plan that is geared toward initiating goal striving (e.g.,specifying that one will attend a particular health and safetytraining session or that one will make an appointment for cancerscreening) is effective in promoting attendance behavior.

However, in the case of attending an initial appointment forpsychotherapy, the key self-regulatory problem that might preventattendance is not to do with difficulties in deciding what session toattend or with failing to make the necessary appointment (i.e.,problems to do with initiating goal striving). These problems areresolved by the fact that in the United Kingdom the mental healthservice provides an appointment at a particular time on a particulardate.1 Insights into the types of self-regulatory problems thathinder attendance for psychotherapy can be gleaned from analysesof the stigmatization of mental illness (e.g., Corrigan, 2004; Sand-ers Thompson, Bazile, & Akbar, 2004) and from qualitative re-search on nonattendance (e.g., Anderson & White, 1994). Corrigan(2004) argued that stigma is a key factor in preventing uptake ofmental health services; people are motivated to avoid the label ofmental illness that comes from being associated with psychologi-cal health services and therefore stay away from treatment. Beinglabeled mentally ill can engender public harm (i.e., prejudice,discrimination) and diminish people’s sense of self, and evidenceindicates that there is a significant relationship between shame andavoiding treatment (e.g., Sirey et al., 2001). Consistent with thisanalysis, Anderson and White (1994) reported that 40% of partic-ipants cited “a fear of being labeled ‘silly’ or ‘mad’” as a reasonfor their failure to attend their first scheduled psychotherapy ap-pointment (p. 29). However, Anderson and White also drew at-tention to several other affective concerns about attendance. Forinstance, 48% of participants reported that they “were too embar-rassed to discuss their problems with a psychologist,” and 44%“were worried about what treatment would consist of” (p. 29).These findings suggest that negative affect in relation to atten-dance (i.e., feelings of embarrassment, shame, or exposure) mayconstitute a significant problem in preventing psychotherapy at-tendance (see also Edlund et al., 2002; Morton, 1995).

On the basis of the assumption that attendance for psychother-apy would be increased if participants could shield their intentionto attend from unwanted feelings of shame or embarrassment, theimplementation intention induction used in the present studyaimed to help participants to manage their attendance-related neg-ative affect. Evidence indicates that implementation intention for-mation aids self-regulation of negative affect. For instance, partic-ipants who formed implementation intentions were better able tocontrol their affective reactions to disgusting stimuli compared toparticipants who only formed respective goal intentions(Schweiger Gallo, McCulloch, & Gollwitzer, 2005). Similarly,spider-phobic participants showed reductions in fearful respondingto spider stimuli according to both cognitive and electrocortical(P100) indexes when they formed if–then plans to control theirfear (Schweiger Gallo, Keil, Rockstroh, & Gollwitzer, 2006;Schweiger Gallo et al., 2005).

In the present study, a subset of participants were asked to forman if–then plan to self-regulate negative affect in relation to atten-dance. The if component of the plan specified, “As soon as I feelconcerned about attending my appointment . . .” because pilotwork indicated that the term concern captured the variety ofnegative affective reactions engendered by thinking about atten-dance. The then component of the plan emphasized that it isnormal and understandable to feel concerned about one’s appoint-ment and also indicated that it was legitimate for people not toelaborate their negative feelings (e.g., “I will ignore that feelingand tell myself this is perfectly understandable”). Thus, the com-ponents of the implementation intention draw on Metcalfe andMischel’s (1999) hot/cool systems model of self-regulation byspecifying that the moment participants experience a concrete,arousing, “hot” emotion (e.g., concern), they immediately instigatean abstract, informational, “cool” response (e.g., “Ignore it, it’sunderstandable”).

Hypotheses

The first and key hypothesis tested in the present study is thatparticipants who form an implementation intention to self-regulatetheir attendance-related negative affect will be more likely toattend their initial appointment for psychotherapy compared toparticipants who do not form an if–then plan. Second, becauseprevious research on correlates of attendance mainly examineddemographic characteristics rather than factors specified by rele-vant theoretical frameworks (Harris, 1998; Phillips, 1995), thisstudy tests how well psychosocial variables specified by a prom-inent framework (the TPB) predict attendance. We also assesswhether implementation intention formation promotes attendanceafter TPB and demographic variables have been taken into account(Orbell, Hodgkins, & Sheeran, 1997). Finally, we examine themechanism by which if–then plan formation promotes attendance.On the basis of past research indicating that implementation in-tention effects are goal dependent (e.g., Gollwitzer & Sheeran,2006; Sheeran, Webb, & Gollwitzer, 2005), we predict that im-plementation intention formation will mainly benefit participantswho believe that attending their psychotherapy appointment is a

1 Clients can change the date and time of their appointment if they sodesire. They can also request a particular therapist or therapist gender.

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good idea (i.e., participants who hold positive cognitive attitudes);if participants do not perceive attendance as being worthwhile,then they are unlikely to encode a plan designed to aid attendance,so implementation intention effects will be weaker (see Sheeran,Milne, Webb, & Gollwitzer, 2005; Webb & Sheeran, 2007).Among participants who hold positive cognitive attitudes towardattendance, we anticipate that forming an if–then plan will promoteattendance by helping participants to deal effectively with negativefeelings about keeping their psychotherapy appointment. Thus, thespecific prediction tested in this article involves a three-way in-teraction (Implementation Intention � Cognitive Attitude � Af-fective Attitude), such that affective attitude should have lessimpact on attendance among participants who both have formed anif–then plan and hold a positive cognitive attitude, compared to allother participants.

Method

Participants and Procedure

The sample comprised all individuals who were offered aninitial assessment appointment at a public sector mental healthservice (the Adult Mental Health Department, PsychologicalHealth Care, Barnsley Primary Care National Health ServiceTrust, South Yorkshire, England) during an 8-month period (July2002 to February 2003). The service consists of a multiprofes-sional team of clinical psychologists, counselors, and (cognitive–behavioral, cognitive–analytic, and psychodynamic) psychothera-pists who deliver assessments and psychological interventions toclients referred from primary or secondary care. The service issituated in one of most economically deprived areas of England(Rooker, 2004), and clients show elevated levels of associateddistress (e.g., Kellett & Newman, 1999, 2003). Clients in primarycare are referred to the service by general practitioners and com-munity psychiatric nurses. Clients in secondary care are alreadypart of the mental health system and are referred by psychiatrists,community psychiatric nurses who specialize in enduring mentalhealth problems, and social workers from the local communitymental health teams. Seventy-one percent of referrals come fromprimary care, and 29% come from secondary care (self-referral ispossible, but it is extremely rare in practice).

Clients present the typical range of mental health problems. Thelocal audit and evaluation system shows that the following diag-noses or presenting problems are most common (percentages arefor primary care and secondary care referrals, respectively): de-pression (25%, 29%), generalized anxiety (26%, 17%), body ap-pearance concerns (7%, � 1%), interpersonal problems (7%, �1%), eating disorders (6%, � 1%), posttraumatic stress disorder(5%, 12%), bereavement (5%, 3%), obsessive–compulsive disor-der (3%, 6%), child sex abuse (3%, 3%), phobias (2%, 2%),personality disorders (0%, 15%), sexual dysfunction (� 1%, 3%),and anger (� 1%, 2%). Ninety percent of clients who attend theirinitial appointment are offered therapy.

The research was approved by Barnsley National Health ServiceTrust Research Ethics Committee prior to data collection. Figure 1shows the flow of participants through the study. A total of 479individuals were offered appointments over the 8-month periodand were sent an information sheet describing the study at thesame time as the letter confirming their appointment. Three indi-

viduals declined to take part in the research. The remaining 476individuals were randomly assigned to the implementation inten-tion versus control conditions (via a random number generator thatlinked condition to the number that identified the questionnaire).Participants in both conditions completed a questionnaire; how-ever, the questionnaire for participants in the experimental condi-tion contained an implementation intention induction (describedbelow).

Because age, gender, and time on the waiting list were extractedfrom participants’ records, it was possible to use these variables toassess whether randomization of participants to condition wassuccessful.2 Findings indicated that there was an equivalent pro-portion of men and women in the implementation intention andcontrol conditions (65% and 69%, respectively, were women),�2(1, N � 476) � 0.71, and there were no differences on age,t(321) � 1.08, or length of time on the waiting list, t(351) � 0.57.These findings suggest that randomization was successful. All 476individuals were sent a questionnaire through the mail 2 weeksbefore they were due to attend their appointment, along with aprepaid return envelope.

Eighty-six individuals (18%) cancelled their scheduled appoint-ment and thus were lost to follow-up (i.e., we were unable to tracewhether these participants ultimately attended a psychotherapyappointment within the time frame of the present research). Therate of cancellation did not differ for the implementation intentionversus control conditions (16% vs. 20%, respectively), �2(1, N �476) � 1.81, p � .18, or for men versus women (15.9% vs. 19.2%,respectively), �2(1, N � 475) � 0.75, p � .39. Compared to thosewho did not cancel their appointment, individuals who cancelledwere younger (Ms � 32.04 and 35.56, SDs � 10.98 and 11.83,respectively), t(320) � 2.02, p � .05, and had waited fewer weeksfor an appointment (Ms � 12.25 and 15.42, SDs � 10.39 and12.13, respectively), t(350) � 1.93, p � .054. This meant that thefinal sample comprised 390 participants (199 were assigned to theexperimental condition and 191 to the control condition).

Questionnaires were returned by 139 individuals, for a responserate of 29%. Respondents to the questionnaire were predominantlyfemale (65%) and ranged in age from 16 to 61 years (M � 35.59,SD � 11.39). The average waiting time between referral forpsychotherapy and receipt of an appointment to see a therapist was14.82 weeks (SD � 10.57). To assess representativeness, wecompared respondents (N � 139) versus nonrespondents to thequestionnaire (n � 251) on background variables. There was anequivalent proportion of men and women in the overall samplerelative to the sample that returned the questionnaire, �2(1, N �389) � 0.001, ns. There were also no differences on age, t(266) �0.04, or length of time on the waiting list, t(291) � 0.63. Thesefindings suggest that participants who returned the questionnaireadequately represent the population from which they were drawn.

Questionnaire

The questionnaire used standard items to measure variablesfrom the TPB (e.g., Ajzen, 1991; Conner & Sparks, 2005). Unless

2 Because records contained missing data for age, gender, and time onthe waiting list, respective sample sizes and degrees of freedom vary indifferent analyses.

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otherwise stated, items all were measured on 5-point scales(strongly disagree to strongly agree). Intention was measured bytwo items, “I intend to attend the appointment I’ve been given” and“I will attend the appointment I’ve been given.” Reliability wassatisfactory (� � .93). PBC was measured by the items “I amcertain I can attend the appointment I’ve been given,” “Howconfident are you that you will be able to attend the appointmentyou’ve been given?” (rated from very confident to very unconfi-dent), and “I think that attending the appointment I’ve been givenwould be . . .” (rated from easy to difficult; � � .71). Subjectivenorm was measured with the single item recommended by Ajzenand Fishbein (1980): “People who are important to me think thatI should attend the appointment I’ve been given.”

Four components of attitude were measured in the question-naire. Cognitive attitude was measured by responses to the stem “Ithink that attending the appointment I’ve been given would be . . .”on three semantic differential scales (helpful–unhelpful, useful–useless, worthwhile–pointless). Affective attitude was assessed byresponses to the stem “Attending my appointment would make mefeel . . .” on seven scales (relieved, upset, supported, ashamed,reassured, exposed, embarrassed). Self-evaluative outcomes weremeasured by responses to the stem “Attending my appointmentwould make me see myself as . . .” on three semantic differentialscales (wise–foolish, strong–weak, mature–immature). Finally, an-ticipated regret was measured by responses to the stem “If I did notattend the appointment I’ve been given I would . . .” on 2 scales

(feel guilty, regret it). (The discriminant and convergent validityand reliability of the four attitude components are examined in theResults section.)

Background information was requested in items that came aftermeasures of the TPB variables. Participants were asked to indicatetheir level of educational attainment (none, secondary school up to16 years, secondary school up to 18 years, university degree;coded 0–4, respectively), their SES (participants’ occupation wascoded according to the Registrar General’s Classification of Oc-cupations), marital status, whether they had their own transport(yes–no), and whether they had child care commitments (yes–no).

Implementation Intention Induction

Participants were randomly assigned to experimental (imple-mentation intention formation) or control conditions. The imple-mentation intention induction comprised the following paragraph,which came at the end of the questionnaire for participants in theexperimental condition (after all other questionnaire items hadbeen presented):

People can sometimes feel concerned about attending their appoint-ment. To help you to manage these concerns, please read the state-ment below 3 times and repeat it silently to yourself one more time:

As soon as I feel concerned about attending my appointment, Iwill ignore that feeling and tell myself this is perfectly understand-able!

Randomizedn = 476

Lost to Follow-up (Cancelled Appointment)

n = 37 (16%)

Experimental Condition n = 236

Control Condition n = 240

Refused to Participate n = 3

Intention to Treat Analysis

n = 191 (80%)

Explanatory Analysis (Returned Questionnaire)

n = 63 (27%)

Intention to Treat Analysis

n = 199 (84%)

Lost to Follow-up (Cancelled Appointment)

n = 49 (20%)

Explanatory Analysis (Returned Questionnaire)

n = 76 (32%)

Eligible for Inclusion N = 479

Figure 1. Flow diagram of progress through the phases of the present trial.

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Now please tick the box below if you have read the statement 3times and said it to yourself once (please be honest, do not tick thebox until you have read and repeated the statement).The questionnaire for the control group was identical in all re-spects except for the omission of this paragraph.

Attendance Behavior

Attendance for the psychotherapy appointment was determinedfrom mental health service records. Attendance status was classi-fied as either attendance (i.e., attended the scheduled appointment)or nonattendance (i.e., did not attend the appointment and did notcancel it).

Results

Data analysis proceeded in four stages. First, the impact ofimplementation intention formation on attendance for psychother-apy was assessed via intention-to-treat analysis (N � 390). Sec-ond, the effect of implementation intention formation on atten-dance was tested among the 139 participants who returned thequestionnaire (explanatory analysis). Third, the discriminant andconvergent validity of the four attitude components were assessed,and scales were constructed. Finally, regression analyses wereconducted to (a) determine how well the TPB variables predictedattendance, (b) examine whether implementation intention forma-tion affected attendance after TPB and demographic variables hadbeen taken into account, and (c) test the predicted interactionbetween implementation intentions and attitude components.

Intention-to-Treat Analysis

Intention-to-treat analysis refers to a type of analysis of data inrandomized controlled trials in which all patients are included inthe analysis on the basis of their original assignment to experi-mental or control groups, regardless of whether they failed to fullyparticipate in the trial for any reason (e.g., failed to receive orundergo the treatment, dropped out of the trial). Intention to treatis regarded as the gold standard for analyzing clinical trials be-cause it gives an unbiased estimate of treatment effect and becauseit permits noncompliance and protocol deviations that are likely toreflect real clinical situations (Fisher et al., 1990; Moher, Schulz,& Altman, 2001). The disadvantage of intention-to-treat analysis isthat it generally produces a conservative estimate of treatmenteffect because of dilution due to noncompliance. This type ofanalysis also requires outcome data from all randomized partici-pants (Hollis & Campbell, 1999).

Data from the 390 participants who did not cancel their appoint-ment were used in the intention-to-treat analysis. Cross-tabulationof attendance by condition indicated that participants who formedimplementation intentions were more likely to attend compared tocontrols. Whereas 63% of control participants (121 out of 191)attended their scheduled appointment for psychotherapy, 75% ofparticipants who formed if–then plans (156 out of 199) did so,�2(1, N � 390) � 6.65, p � .01. It is important to note that theimpact of implementation intention formation on attendance is notexaggerated by poor attendance by control participants. The rate ofattendance for the first appointment for psychotherapy by controlparticipants was consistent with the usual general rate at the clinic.

A chart review of attendance during the 6-month period before thepresent study showed that rate to be 60%. Thus, findings from theintention-to-treat analysis indicate that the mere receipt of thepostal questionnaire containing the implementation intention in-duction increased attendance compared to receiving an equivalentquestionnaire that did not contain the if–then plan.

It is possible to argue that intention-to-treat analysis shouldproperly involve the attendance data from all 476 participants whowere randomized to conditions. We therefore conducted theseanalyses (attending one’s scheduled appointment was coded 1, andnonattendance or cancellation was coded 0). Findings showed thatimplementation intention formation still exerted an important in-fluence on keeping the appointment, even when it was assumedthat cancellation was equivalent to nonattendance. Whereas 50%of control participants (121 out of 240) attended their appointment,64% of participants who formed implementation intentions (150out of 236) did so. This difference was highly reliable, �2(1, N �476) � 8.38, p � .004. In sum, findings from both types ofanalyses indicate that forming an if–then plan was effective inpromoting attendance for psychotherapy.

Explanatory Analysis

Explanatory analysis refers to the type of analysis that is tradi-tionally used in psychological studies in which only participantswho take part in the research (in the present context, individualswho returned the questionnaire) are included in the analysis. Weused this type of analysis to examine rates of attendance amongparticipants who did and did not form implementation intentions.Ninety-four percent of participants (59 out of 63) in the experi-mental condition ticked the box indicating that they had completedthe implementation intention induction in line with instructions.Cross-tabulation of attendance by condition indicated that 83% ofparticipants who formed if–then plans (52 out of 63) attended theirpsychotherapy appointment compared to 57% of control partici-pants (43 out of 76). Thus, there was a highly significant effect ofimplementation intention formation on attendance among partici-pants who returned the questionnaire, �2(1, N � 139) � 10.73,p � .001.

Discriminant Validity of the Attitude Components

Before assessing the predictive validity of the TPB and testingthe predicted interaction, we used exploratory factor analysis todetermine the discriminant and convergent validity of the fourattitude components measured in the questionnaire (i.e., cognitiveattitude, affective attitude, self-evaluative outcomes, and antici-pated regret). An iterative principal axis factor extraction methodwith an oblique rotation (SPSS oblimin command) was usedbecause it was reasonable to expect that factors might be correlatedabove .30 (Tabachnick & Fidell, 2000). Contrary to expectations,three factors (not four) with eigenvalues greater than 1.0 wereextracted that accounted for 74% of the item variance (see Table1). Factor 1 comprised the cognitive attitude items, the anticipatedregret items, and the positive affective attitude items. Because thisfactor captured favorable anticipated consequences of attendance,it was labeled Perceived Benefits. The second factor comprised thefour negative affective attitude items and was labeled AffectiveCosts of attendance. The final factor was composed of the three

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original self-evaluative outcomes, and was therefore labeled Self-Evaluative Outcomes. Thus, findings from the factor analysis areconsistent with theoretical analyses that suggest that valence is aprimary dimension underlying attitudinal judgments (e.g., Duran& Trafimow, 2000) and with models that divide attitudes intopositive versus negative components (e.g., costs and benefits in thehealth belief model; Becker, 1974; or pros and cons in the trans-theoretical model; Prochaska, DiClemente, & Norcross, 1992).The findings also suggest that self-evaluative outcomes are adistinct component of attitudes (Bandura, 1997). Scales were con-structed via the mean of items within factors. Cronbach’s alpha

coefficients indicated that the Perceived Benefits, Affective Costs,and Self-Evaluative Outcomes scales were highly reliable (� �.92, .87, and .88, respectively).

Regression Analyses: Predictive Validity of the TPB andInteractions With Implementation Intentions

In the light of findings from the exploratory factor analysis, wereformulated our hypothesis concerning the interaction amongimplementation intentions, affective attitude, and cognitive atti-tude by substituting affective costs and perceived benefits for theoriginal attitude components. Thus, the revised prediction is thataffective costs should not affect attendance among participantswho have formed implementation intentions and who see benefitsin attending psychotherapy, whereas affective costs should beassociated with reduced attendance among the other groups.

Hierarchical logistic regression analysis was used to test thishypotheses and to assess the predictive validity of TPB and de-mographic variables. First we computed correlations between at-tendance and the measured variables (see Table 2). The followingvariables had significant bivariate associations with attendance andtherefore were included in the first step of the regression equation:intention, perceived control, perceived benefits, affective costs,self-evaluative outcomes, subjective norm, and SES. Condition(dummy coded; implementation intention � 1, control � 0) en-tered the regression equation on the second step. At Step 3, alltwo-way interactions among condition, affective costs, and per-ceived benefits as well as the three-way interaction entered theequation. Scores on affective costs and perceived benefits werestandardized prior to computation of interaction terms to reducepotential multicollinearity (Aiken & West, 1991).

Table 3 presents the findings from the hierarchical regression.Intention and affective costs were significant predictors of atten-dance at Step 1, and there was a marginally significant betacoefficient for perceived benefits. Stronger intentions to attend andmore positive perceived outcomes of attending were associated

Table 1Pattern Matrix for Oblique Rotation of Attitude Items

Item Factor 1 Factor 2 Factor 3

Worthwhilea .88 �.04 .01Usefula .87 �.08 .04Helpfula .86 �.04 .02Regretb .73 .27 .24Relievedc .73 �.26 .02Supportedc .71 �.22 .06Guiltyb .70 .34 .12Reassuredc .68 �.46 �.13Exposedc .03 .83 �.09Embarrassedc �.13 .75 �.11Upsetc .02 .74 �.15Ashamedc �.25 .66 �.17Matured .01 .01 .89Strongd �.01 �.09 .88Wised .08 �.23 .75Eigenvalue 8.13 1.99 1.02R2 .54 .13 .07

Note. Italics indicate the highest factor loading for each questionnaireitem.a Originally construed as a cognitive attitude item. b Originally construedas an anticipated regret item. c Originally construed as an affective atti-tude item. d Originally construed as a self-evaluative outcome item.

Table 2Means, Standard Deviations, and Correlations for Measured Variables

Variable 1 2 3 4 5 6 7 8 9 10 11 12 13 14

1. Attendance —2. Intention .69*** —3. Perceived control .58*** .80*** —4. Perceived benefits .66*** .78*** .74*** —5. Affective costs �.52*** �.42*** �.44*** �.47*** —6. Self-evaluative outcomes .49*** .61*** .58*** .63*** �.55*** —7. Subjective norm .29*** .37*** .34*** .39*** �.22** .30*** —8. SES .24* .14 .16 .16 �.16 .02 .06 —9. Education .13 .24** .19* .19* �.13 .18* .04 �.51*** —

10. Own transport .09 �.04 .01 .05 �.10 �.03 �.14 .23* .18* —11. Child care commitments �.13 �.15 �.16 �.07 �.04 �.18* .02 �.12 �.04 .09 —12. Age .14 �.05 .03 .05 .01 �.01 �.05 �.02 �.09 .23* �.04 —13. Gender �.10 .02 �.06 �.06 .13 �.04 .05 �.05 .12 �.07 .23** �.17 —14. Time on waiting list �.08 �.14 �.26** �.20* .05 �.11 �.08 .09 �.01 .01 .03 .05 �.01 —M 4.23 3.81 3.79 2.85 3.30 4.16 2.01 0.96 35.59 14.82SD 0.98 0.85 0.88 1.12 1.10 1.02 0.99 0.91 11.39 10.57

Note. N � 139 for all correlations except background characteristics (variables 8–14), for which Ns � 101 to 138. Means and standard deviations arenot presented for dichotomous variables. SES � socioeconomic status.* p � .05. ** p � .01. *** p � .001.

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with increased attendance, whereas anticipating greater affectivecosts was associated with reduced attendance. These three predic-tors accounted for 63% of the variance in attendance at Step 1.These findings support the predictive validity of the theory ofplanned behavior and indicate that the one demographic charac-teristic that was significantly correlated with behavior (i.e., SES)was no longer associated with behavior when these predictors hadbeen taken into account.

Entering condition at Step 2 significantly improved the fit of themodel (��2 � 7.35, p � .01) and increased the variance explainedto 70%. Thus, implementation intention formation increased atten-dance even after motivational variables (intention, attitude) hadbeen controlled. The interaction terms entered the regression equa-tion at the final step and led to a significant improvement in modelfit. In the final equation, intention, affective costs, and implemen-tation intention formation were significant predictors of atten-dance. The three-way interaction among implementation intention,affective costs, and perceived benefits was marginally significant(B � �3.74, p � .07). The final model explained 75% of thevariance in attendance.

We decomposed the interaction using the procedures recom-mended by Aiken and West (1991). Because the three-way inter-action was significant at p � .07, we first tested whether thepredicted interaction between affective costs and perceived bene-fits was present among participants who formed implementationintentions (but absent among control participants). Regression ofattendance on affective costs, perceived benefits, and their inter-action among the experimental group revealed that the interactionterm was the only significant predictor of behavior (B � 3.33, p �.02). In contrast, for control participants, there were significantmain effects for affective costs and perceived benefits (Bs ��2.16 and 1.80, respectively, ps � .01), but the interaction wasnot significant (B � 0.49). These findings are consistent with thethree-way interaction that was anticipated and justify further de-composition of the interaction.

To understand the nature of the interaction, we computed simpleslopes for the affective costs–attendance relation at high (meanplus one standard deviation) and low (mean minus one standarddeviation) levels of perceived benefits for both the implementationintention and the control conditions (see Figure 2). Findings sup-ported our predictions. For participants in the control condition,greater affective costs were associated with reduced attendance forpsychotherapy, and this was true whether participants perceivedhigh benefits (B � �1.67, p � .05) or low benefits of keeping theappointment (B � �2.65, p � .01). Greater affective costs werealso associated with reduced attendance among participants whoformed implementation intentions and who had low perceivedbenefits of attendance (B � �5.14, p � .05). However, amongparticipants who both formed an implementation intention andscored highly on perceived benefits of attendance, affective costs

Figure 2. Simple slopes predicting attendance from affective costs athigh and low levels of perceived benefits for implementation intention andcontrol conditions. Implementation intention is coded 1 � formed (if–thenplan), 0 � not formed (no plan).

Table 3Hierarchical Logistic Regression of Behavior on Theory of Planned Behavior Variables, SES,Implementation Intention, and Interactions Between Implementation Intention and AttitudeComponents

Step Variable entered B B B

1 Intention 2.08** 2.23* 2.96**

Perceived control �0.90 �0.99 �1.10AC �1.30** �1.65** �2.23**

PB 1.03† 1.07 �0.13Self-evaluative outcomes �0.29 �0.34 �0.08Subjective norm 0.07 0.11 0.25SES 0.63 0.66 1.03

2. IMP 0.96* 1.64*

3. IMP � AC �0.09IMP � PB 0.60AC � PB �0.45IMP � AC � PB �3.74†

�2 log likelihood 61.66 58.31 47.71��2 61.85*** 7.35** 10.60*

Nagelkerke R2 .63 .70 .75

Note. Standard errors are omitted for clarity. Implementation intention was coded 1 � formed, 0 � not formed.SES � socioeconomic status; AC � affective costs; PB � perceived benefits; IMP � implementation intention.† p � .07. * p � .05. ** p � .01. *** p � .001.

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did not predict attendance (B � 1.51, p � .16). Thus, whenparticipants saw benefits in attending psychotherapy and formedan if–then plan to self-regulate their negative affect, anticipatedfeelings of shame and embarrassment no longer prevented themfrom attending their scheduled psychotherapy appointment.

Discussion

The present study provides the first evidence that implementa-tion intention formation increases rates of attendance for sched-uled, initial appointments for psychotherapy. Previous researchindicated that individuals are liable to experience negative affect inrelation to attending their psychotherapy appointment. In particu-lar, people may feel ashamed about needing psychological treat-ment and worry about the nature of that treatment; they may alsoanticipate embarrassment about discussing their problems or fore-see stigmatization arising from contact with mental health services(Anderson & White, 1994; Corrigan, 2004; Morton, 1995). Be-cause these negative feelings hold the potential to prevent atten-dance, the implementation intention induction used in the presentstudy was designed to shield the goal of attendance from suchunwanted negative affect. Participants formed an if–then plangeared at the effective self-regulation of their attendance-relatedconcerns. The plan specified the initiation of a “cooling” self-regulatory response as soon as concern was felt.

Chart review of attendance provided strong evidence that if–then plan formation helped participants attend their appointment.When we used the gold standard of intervention evaluation—intention-to-treat analysis—to evaluate the impact of implementa-tion intention formation on attendance, we found that the effectwas significant and substantial. Whereas only 63% of controlparticipants attended their appointment (similar to the rate ob-tained in Hampton-Robb et al.’s, 2003, review), 75% of partici-pants who formed implementation intentions did so. Even whenwe assumed that cancellation was the same as nonattendance, agreater proportion of participants who formed if–then plans turnedup for their appointment compared to controls (50% vs. 64%).Explanatory analyses that examined attendance only among thoseparticipants who returned the questionnaire also revealed a signif-icant effect of implementation intention formation (57% vs. 83%).These findings indicate that merely mailing a self-completionquestionnaire that contained the if–then plan induction served toincrease the rate of attendance by 12%–26% compared to mailingthe equivalent questionnaire with no plan induction. Even thoughmost people who were mailed the questionnaire did not respond(71%) and equivalent numbers of experimental and control ques-tionnaires were distributed, the if–then plan induction still had animportant impact on attendance.

The regression analyses provided evidence that implementa-tion intention formation promoted attendance in the manner thatwe had predicted—namely, by helping people to manage neg-ative feelings about attendance. On the basis of the idea thatif–then planning would be especially advantageous when par-ticipants believed that psychotherapy would benefit them, wepredicted—and obtained—a three-way interaction among im-plementation intention formation, perceived benefits, and affec-tive costs. Decomposition of the interaction showed that affec-tive costs had a negative impact on attendance amongparticipants who did not form implementation intentions, re-

gardless of whether they perceived attending psychotherapy asbeneficial. That is, the more embarrassed, exposed, upset, orashamed these participants expected that attending their ap-pointment would make them feel, the less likely they were tosubsequently attend. Greater affective costs were also associ-ated with reduced attendance among experimental participantswho did not see much benefit in attending. However, whenparticipants thought that attendance for psychotherapy would bebeneficial and had formed an if–then plan to manage theirattendance-related negative affect, affective costs had no bear-ing on whether they kept their appointment. In other words,anticipated feelings of shame or embarrassment no longer un-dermined the goal of attendance when participants had formedan implementation intention to help them manage these feelingseffectively.

Implementation intention formation is likely to have improvedattendance because if–then plans equipped participants to avoidpaying undue attention to their negative attendance-related affect(unlike control participants). Implementation intention participantshad identified—in advance—that concerns about their appoint-ment could be an obstacle to attendance and had specified theexperience of concern in the if component of their plan (i.e., “Assoon as I feel concerned about attending my appointment . . .”).If–then planners had also specified in the then component of theirplan a cooling self-regulatory response that stressed the legitimacyof not paying too much heed to feelings of concern about theirappointment. Thus, when participants who formed implementationintentions experienced concern about attending their appointment,they did not have to deliberate about how to manage these negativefeelings in situ. They knew exactly how to respond, and theirplanned response could be initiated swiftly and effortlessly (seeGollwitzer & Sheeran, 2006, and Webb & Sheeran, 2007, forevidence that implementation intentions promote automatic initi-ation of behavior). For these participants, negative feelings aboutattendance should no longer be elaborated or provide informationabout the decision to attend their appointment (see Schwarz &Clore, 1996, for a recent review of the feelings-as-informationhypothesis).

Although our principal research aim was to test whether andhow implementation intention formation promotes attendance forscheduled initial appointments for psychotherapy, the findingsconcerning predictors of attendance also warrant discussion. Thepresent study indicates that variables specified by the TPB couldpredict attendance for psychotherapy. TPB variables explained63% of the variance in attendance behavior, with intention andaffective costs emerging as the key predictors. Stronger intentionsto attend and weaker beliefs that attendance would engenderfeelings of embarrassment and shame were associated with keep-ing one’s appointment. It is interesting to note that barriers toattendance (child care commitments, transport) and time on thewaiting list were not significantly correlated with attendance.Demographic factors also were not generally associated with keep-ing the appointment, and although SES was significantly corre-lated with attendance, the influence of this variable appeared to bemediated by TPB variables in the regression analyses. Thesefindings are consistent with the proposal that TPB variables are themost immediate and important predictor of behavior (Ajzen, 1991)and contribute to evidence that the TPB is a good predictive model

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of attendance for health-relevant appointments (e.g., Norman &Conner, 1993; Sheeran & Orbell, 2000).

The present findings have clear, practical implications for in-creasing attendance for psychotherapy. For instance, one potentialapplication of the present work is to provide the implementationintention induction used in this research alongside the letter thatoffers clients their initial psychotherapy appointment. The sameinduction might also prove useful in relation to other client groupswhen concerns about their appointment militate against attendance(e.g., attendees at sexually transmitted infection or illicit drug useclinics). Although the present study is concerned with individuals’attendance for their first appointment for psychotherapy, imple-mentation intention formation could also prove helpful in ensuringcontinued attendance after clients have kept their initial appoint-ment. Future studies should therefore test the utility of if–thenplanning in reducing premature termination among clients who arealready receiving treatment, so that these individuals obtain thegreatest possible benefit from psychotherapy (Howard et al.,1986).

Conclusion

The present research has three important limitations. First, all ofthe participants came from a single mental health service. Second,we were unable to determine (within the time frame of the study)whether participants who cancelled their scheduled appointmentultimately attended an alternative appointment. Third, the possi-bility that if–then planning only benefited individuals with partic-ular diagnoses or presenting problems (but did not help peoplewith other kinds of problems) could not be tested. Although furtherresearch is needed to overcome these problems and to determinethe generality of the present results, the findings nonetheless holdthe promise that implementation intention formation could proveuseful in helping people attend scheduled, initial appointments forpsychotherapy.

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Received October 31, 2006Revision received May 18, 2007

Accepted June 1, 2007 �

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