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Investigating the effect of conditional vs hierarchical framing on motivation
Learning and Motivation 65 (2019) 33–42
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Learning and Motivation journal homepage: www.elsevier.com/locate/l&m
Investigating the effect of conditional vs hierarchical framing on motivation Varsha Eswara Murthya, Matthieu Villatteb, Louise McHugha, a b
T
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University College Dublin, School of Psychology, Newman Building, Belfield, Ireland Bastyr University, Seattle, USA
A R T IC LE I N F O
ABS TRA CT
Keywords: Motivation Relational frame theory Hierarchical relating Conditional relating Persistence
Manipulating motivational factors is an effective method for increasing desired behavior and reducing problematic behavior, as well as for increasing satisfaction from desired but challenging actions. From the Relational Frame Theory (RFT) perspective, hierarchical networks of symbolic positive reinforcers are advantageous motivators as they provide intrinsic, overarching, and inexhaustible reinforcement to our actions, even when they cause some degree of distress. The current study aimed to investigate how motivation based on hierarchical versus conditional versus a mixed (hierarchical and conditional) framing impacts performance and psychological experiences in a distress tolerance task. Participants completed an anagram task, followed by the presentation of scripts relating to three separate framing conditions. Participants then proceeded to take part in an adapted PASAT-C to measure task persistence, followed by completion of selfreport measures evaluating mood, self-efficacy, and experiences of task participation. A final anagram task was completed to evaluate the effect of framing condition on task performance and transfer of framing conditions across different tasks. Hierarchical and mixed groups outperformed the conditional group on measures of task performance and persistence. This effect was transferred to performance on the anagram task. Significantly increased self-efficacy, comfortableness, and willingness were observed for both the hierarchical and mixed conditions over the conditional group with the hierarchical group outperforming the mixed group. This study highlights the potential differing effects that framing tasks conditionally, hierarchically or both hierarchically and conditionally can have on motivation and task performance.
1. Introduction Manipulating motivational factors is an effective method for increasing desired behavior and reducing problematic behavior (Iwata, Smith, & Michael, 2000), as well as for increasing satisfaction from desired but challenging actions (Plumb, Stewart, Dahl, & Lundgren, 2009). Relational Frame Theory (RFT; Hayes, Barnes-Holmes, & Roche, 2001) is a contextual behavioural approach to language and cognition which proposes that motivation can be altered through the use of language. According to RFT, language is a behavior consisting of building relations among stimuli not solely based on their physical or formal properties but based on socially established cues (technically referred to as relational framing or framing events relationally). Consider the relationship between the word ‘SWEATER’ and an actual sweater. We treat these two things as being similar in many contexts, despite the fact that they have
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Corresponding author. E-mail addresses: [email protected] (V. Eswara Murthy), [email protected] (M. Villatte), [email protected] (L. McHugh). https://doi.org/10.1016/j.lmot.2018.11.002 Received 9 December 2017; Received in revised form 26 November 2018; Accepted 27 November 2018 0023-9690/ © 2018 Elsevier Inc. All rights reserved.
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physically very little in common (they are put into an abstract relation of sameness with each other). As a result, if a person asks you to give her the sweater, you will likely hand her the actual sweater. Being able to relate stimuli abstractly (i.e. to build symbolic relationships between things) is what allows us to contact experiences that are not physically present in our environment, such as distant or abstract consequences of current actions (e.g. knowing that studying hard will help get a degree several months later, or smiling at a stranger as an expression of compassion). We can relate things in many different ways, other than relations of sameness. For example, we can relate things as opposite (‘Thin is opposite to fat’) different (‘medium is different from rare’) comparatively (‘Maura is smarter than Kate’) conditionally (‘If I get angry then I break something’) temporally (‘Halloween is before Christmas’), in terms of perspective (‘From where I am, I can see the mountains, and from where you are, you can see the sea’) and hierarchically (‘dog is a type of animal’; ‘valued goals and actions are part of valued living’). From a learning theory perspective studying motivation involves looking at what makes consequences more or less effective as reinforcers or as punishers (Catania, 1992). Traditionally motivational effects have been distinguished from reinforcement effects and referred to as Establishing Operations (EO; Keller & Schoenfeld, 1950). An EO is a condition of deprivation or aversion that temporarily alters the value of a particular reinforcer. Michael (2000) worked on more clearly defining motivational variables by developing and extending Skinner’s account of motivation with the term motivating operation (MO). According to Michael MOs explain variations in the effects in the consequences of behavior. For example, sleep deprivation can be considered a motivating operation. If an individual is tired, sleep is strongly reinforcing, but if an individual is well rested, sleep is less reinforcing. In the RFT literature augmenting involves relational networks that alter the degree to which events function as consequences. One form of augmenting is referred to as motivative augmenting and is defined as ‘behavior due to relational networks that temporarily alter the degree to which previously established consequences function as reinforcers or punishers’, (Hayes et al., 2001, P109). An example of a motivative augmental is, “Wouldn’t a hot cup of hot chocolate taste good right now?” An important distinction is to be made between events that are verbal establishing stimuli (establish something as a reinforcer) and verbal discriminative stimuli (have a discriminative function). Buying hot tea after the earlier statement likely functions as a verbal establishing stimulus, not a verbal discriminative stimulus, given that hot tea is available whether or not the rule is present. Motivative augmentals operate by presenting the sensory or perceptual functions of a consequence. In the earlier example the words “hot” and “tea” come to have sensory functions via a transformation of stimulus function (i.e., the listener can imagine tasting hot tea) (see Ju & Hayes, 2008 for an experimental demonstration). It has been suggested that employing different types of framing will have a differential impact on motivation (Villatte, Villatte, & Hayes, 2018). However, to date there is no empirical evidence to support this postulate. More specifically, conditional and hierarchical framing are two patterns of relational framing that can be used to build or identify symbolic functions of actions. Conditional framing could be likened to outcome based motivation (Brehm & Self, 1989; Locke & Latham, 1990). In this case, motivation to participate and complete a task can be based on achieving a ‘good score’, for example. Hierarchical framing can be likened to process based motivation (Dahl, Plumb, Stewart, & Lundgren, 2009; Deci & Ryan, 1985; Fishbach & Choi, 2012; Sansone & Harackiewicz, 1996; Shah & Kruglanski, 2000). In this case for example, motivation to participate in a task could come from a motivation to learn, such that participation in the task is viewed as serving the overarching value and purpose of learning. From the RFT perspective, hierarchical networks of this kind can provide intrinsic, overarching, and inexhaustible reinforcement by linking actions (at the bottom of the hiearchical network) to an overarching goal (e.g. sharing knowledge with others) and qualities of action (e.g. with precision) (at the top of the hiearchical network). Actions are thus guided by these symbolically contructed consequences across time and situtions, and become reinforcing independent of additional consequences. While conditional relations focusing on specific goals only allow contact with satisfaction if the goal is met (e.g. “I need to study to get my degree and make a lot of money and then I will be happy”), hierarchical relations make the process of engaging in the action reinforcing in and of itself (e.g. “Studying is part of learning, which is something I value regardless of the outcome of studying”). In a clinical context, developing motivation through hierarchical framing can be linked to work on values in therapies such as Acceptance and Commitment Therapy (ACT, Hayes, Strosahl, & Wilson, 2012). In these approaches, clients are trained to connect their actions to sources of meaningful reinforcement that are not dependent on outcomes of action. For example, before starting an exposure session (e.g. working on fear of public speaking), a therapist might ask a client to express the higher purpose of doing this exercise not in terms of a specific outcome (e.g. getting better at public speaking) but in terms of values (e.g. openness). By doing so, the client can connect to the value as soon as she is exposing herself to the fear situation rather than waiting for the outcome to happen. Even outside clinical issues, finding motivation during difficult or undesirable tasks is obviously particularly challenging. However, living a meaningful life involves times when sticking with difficult tasks is critical. All areas of life (e.g. parenting, relationships, work) involve times when motivation to engage in valued actions is low, but disengaging at these times can have negative consequences (e.g, failed marriage, job loss). The Paced Auditory Serial Addition Task (PASAT-C; Lejuez, Kahler, & Brown, 2003) is a behavioral measure of persistence, in which the participant performs serial addition of numbers under tight time constraints. PASATC scores have been related to borderline personality disorder diagnosis (Gratz, Rosenthal, Tull, Lejuez, & Gunderson, 2006) and to the length of time smokers (Brown, Lejuez, Kahler, & Strong, 2002), illicit drug abusers (Daughters, Lejuez, Strong et al., 2005), or gamblers (Daughters, Lejuez, Kahler, Strong & Brown, 2005) had remained abstinent during prior quit attempts. The current study aims to investigate how hierarchical vs. conditional vs. a mixed condition (hierarchical and conditional) framing of task participation impacts motivation on the PASAT-C. The study specifically investigates the impact of the framing conditions on task performance, transfer of framing condition functions to performance on an alternate task, task persistence, mood reactivity to tasks, self-efficacy, willingness to participate in the task again, comfortableness doing task, self-perceptions of task 34
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performance. 2. Method 2.1. Participants The sample totalled 69 participants, with 23 participants being assigned to the three different framing instruction groups. An apriori power analysis revealed that a sample size of 50 would be required to yield a moderate effect sizes. Data was collected for a set recruitment period of two months. At the end of this period it was determined that data collection would end as long as the 50 participants or more had been recruited. Thus a sample of size of 69 with 23 being assigned to each group was what was collected at the end of this period. Participants aged 18 to 48 (M = 23.25; SD = 5.44) was recruited using opportunity sampling from University College Dublin, including a student sample. The sample included 32 males and 37 females, each framing instruction group was closely balanced for gender. Informed consent was obtained prior to data collection and research was granted ethical approval from University College Dublin’s Human Research Ethics Committee. No compensation was given to participants. Participants were otherwise blind to the true nature of the study. Exclusion criteria included having a specific developmental disorder, such as dyslexia (due to the verbal-based nature of the learning task) and dyscalculia (due to the arithmetic-based nature of the PASAT-C). In order to reduce demand characteristics, the study was advertised as an experiment testing various cognitive abilities and, thus, participants were naïve to the true nature of the study as well as being blind as to which instruction they received. 2.2. Study design The study design, involved a mixed between-within design with group as the between-subject factor (Hierarchy, Conditional, and Mixed) and time (Pre- and Post-PASAT-C) as the within-subject factor to assess differences on scores on the mood reactivity scale, PANAS, and anagram task performance post completion of the PASAT-C. A between-group analysis using 8 separate ANOVAs with group as the independent variable, dependent variables include: total number of correct answers on the PASAT-C time to quit task on third trial of the PASAT-C, scores on the self-efficacy scale, scores on each of the items on the 5 item scale (comfortableness doing task, willingness to engage in the task again, positivity/negativity of experience in participating in the task, perceptions of task performance, and task difficulty). Each separate ANOVA was calculated in order to assess whether there is a significant difference between the framing conditions. 2.3. Measures 2.3.1. Mood 2.3.1.1. Positive and negative affect scale (PANAS). The PANAS (Watson, Clark, & Tellegen, 1988) is a 20-item self-report measure measuring positive and negative affect, with each item rated on a 5-point Likert scale. It consists of two scales for positive and negative affect, with the Cronbach’s alpha in the current study of participants’ ratings of 0.91 and .75, respectively, for each of the scales. Construct validity has been found to be good, and confirmatory factor analysis has yielded two factors corresponding to the PA and NA scales (Crawford & Henry, 2004). The scale was implemented as a between-groups current mood measure T1 to T4. 2.3.1.2. Mood reactivity scale. To determine whether the PASAT-C induced distress, dysphoria was measured, both prior to and after the PASAT-C, using a four-item self-report scale. Irritability, frustration, anxiety, and difficulty concentrating were each rated on a visual analogue scale ranging from 0 to 100 (0 = none; 100 = extreme). Anxiety, frustration, difficulty concentrating, and irritability are believed to be indicators of psychological distress and have been shown to be highly inter-correlated (Brown et al., 2002), these variables were summed to create the dysphoria measure. 2.3.1.3. Task performance. An anagram task served as a pre- and post-measure of task performance following induction of a framing condition and completion of the PASAT-C and also served to measure the ability of transfer of framing conditions across differing tasks. This involved 5 anagrams being individually presented via PowerPoint for a period of 1-minute each, with participants being instructed to solve the anagram and write down their answers on a blank answer sheet, this is in line with previous research conducted by Shah and Kruglanski (2000). 2.3.2. Self-Efficacy General Self-Efficacy Scale (GSES). The GSES (Scholz, Gutiérrez-Doña, Sud, & Schwarzer, 2002; Schwarzer & Jerusalem, 1995) is a measure of general self-efficacy. It consists of 10 items. Respondents rate each item on a 1 (not true at all) to 4 (exactly true) scale. Sample items include “I am confident that I could deal efficiently with unexpected events,” and “I can usually handle whatever comes my way.” Researchers have provided evidence supporting the reliability and validity of the GSES (Scholz et al., 2002). In the present sample, the GSES had a Cronbach's alpha of 0.73. 2.3.3. Distress tolerance measure 2.3.3.1. The paced auditory serial addition task (PASAT-C; Lejuez et al., 2003). This is a behavioural measure of task persistence and distress tolerance, in which the participant performs serial addition of numbers presented one at a time on a computer monitor. 35
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Participants were asked to add the most recent number presented to the previous one and to use the computer mouse to click on the correct answer from the numbers shown on the bottom of the screen. After clicking on the sum, the participants were asked to ignore the sum and to continue adding the number that is shown by the computer to the next number presented. A point is awarded for every correct answer, and an aversive “explosion” sound effect is played in response to every incorrect answer. The task includes three rounds of increasing difficulty (i.e., the latencies between numbers presented decreased and the length of the round increased). Unlike rounds 1–2, participants were given the option to “quit” the task at any time during level 3 (the most difficult round). The time (in seconds) it took for the participant to quit the task in round 3 is the behavioural index of task persistence or distress tolerance as a continuous measure. The maximum score possible is 600 (seconds), as the third round ends after 10 min. Participants will not be told of this time limit in advance. The PASAT-C was also used as a dichotomous measure (completed the entire 600 s versus quit early). PASAT-C scores have been related to borderline personality disorder diagnosis (Gratz et al., 2006) and to the length of time smokers (Brown et al., 2002), illicit drug abusers (Daughters, Lejuez, Strong et al., 2005; Daughters, Lejuez, Kahler et al., 2005), or gamblers (Daughters, Lejuez, Strong et al., 2005; Daughters, Lejuez, Kahler et al., 2005) had remained abstinent during prior quit attempts. 2.3.4. Framing instructions Framing instructions were presented before commencing the PASAT-C. Short prompts were also presented in-between trials of the PASAT-C. 2.3.4.1. Hierarchy. In the hierarchical framing group, specific hierarchical language was utilised such as “engage” and “taking part in the process”. Participants were presented with the following main instruction prior to commencing the PASAT-C: “My participation in the study will be worth it if I engage in the task because my taking part in the process is what matters most to the research.” Participants were presented with the following prompts in between PASAT-C trials; Pre-trial 1, after the instructions for the PASAT-C were presented: “Focus on engaging in the task.” Pre-trial 2, following completion of trial 1: “Focusing on what you are doing is the most important part of doing the task.” Pre-trial 3, following completion of trial 2: “Remember just engaging in the process of the task is the most important part of your participation.” 2.3.4.2. Conditional. In the conditional framing group, specific conditional language was utilised such as “getting a good score” and “focus on the outcome”. Participants were presented with the following main instruction prior to commencing the PASAT-C: “My participation will be worth it if I finish the task and make a good score, because the outcome is what matters most to the research.” Participants were presented with the following prompts in between PASAT-C trials; Pre-trial 1, after the instructions for the PASAT-C were presented: “Focus on getting a good score.” Pre-trial 2, following completion of trial 1:“Focusing on the end result of the task is what matters.” Pre-trial 3, following completion of trial 2: “Remember getting a good score is the aim of your participation.” 2.3.4.3. Mixed. In the mixed group, both hierarchical and conditional instructions were used. Participants were presented with the following main instruction prior to commencing the PASAT-C: “My participation in the study will be worth it if I engage in the task because taking part in the process is what matters, but finishing the task and getting a good score will be helpful for the research.” Participants were presented with the following prompts in between PASAT-C trials; Pre-trial 1, after the instructions for the PASAT-C were presented: “Focus on engaging in the task and getting a good score” Pre-trial 2, following completion of trial 1: “Focusing on what you are doing is part of the task but focusing on the end result of the task also matters.” Pre-trial 3, following completion of trial 2: “Remember just engaging in the task is the most important part of the task but getting a good score is also an important aim of your participation” 2.3.5. Procedure Participants were allocated to the three groups using random sampling procedure. Participants first completed the mood reactivity scale, PANAS and anagram task. Following completion of the questionnaires participants were immediately presented with their framing instructions, either hierarchical, conditional or mixed. Participants were then instructed to commence the PASAT-C task, with prompts corresponding to their framing instruction group appearing on the computer screen in-between trials. The moodreactivity scale, PANAS, anagram task, general self-efficacy, task-specific self-efficacy, comfortableness, willingness, positivity, perceptions of task difficulty and task performance, were measured post-completion of the PASAT-C. Participants were fully debriefed and then dismissed. 36
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Table 1 Mean scores across the three groups on all study measures. Measure
Conditional
Hierarchy
Mixed
PASAT C Quit Time PASAT C Total Scores
310.39 (81.85) 56 (16.49)
540 (66.2) 109 (14.87)
581.35 (37.15) 121.87 (17.54)
Dysphoria Pre Post
60.43 (13.64) 237.39 (29.88)
59.52 (14.29) 102.61 (16.85)
59.57 (14.3) 134.78 (15.34)
PANAS Negative Affect Pre Post
11.83 (1.23) 26.87 (1.98)
12.35 (1.07) 13.48 (1.08)
11.91 (.85) 15.26 (1.51)
PANAS Positive Affect Pre Post Self Efficacy Willingness to participate again Discomfort Positivity Perceived task performance Perceived task difficulty
26.91 (1.88) 16.3 (2.08) 397.69 70.96 (8.19) 75.78 33.69 (10.19) 35.04 (8.36) 30.35 (8.84)
27.09 (1.7) 33.65 (1.92 538.46 25.09 (8.21) 30.65 (5.45) 65.79 (11.31) 62.17 (9.39) 70.04 (11.14)
26.96 (1.72) 28.26 (1.65) 546.92 39.69 (10.89) 41.87 (10.95) 54.22 (11.39) 68.39 (9.93) 59.22 (11.08)
Anagram Pre Post
2.61 (.72) 2.43 (.59)
2.43 (.59) 3.39 (.72)
2.26 (.54) 4.22 (.67)
3. Results The descriptive statistics for each group across all tasks are presented in Table 1. A series of 2 × 3 mixed analyses of variance were conducted in order to determine the group, time and group time interaction across the study variables. A series of one-way ANOVAs were conducted to assess group differences at both pre-instruction and post-instruction, respectively. To determine if any differences between pre and post instruction scores on individual measures were significant, t tests were used. To reduce the risk of familywise error, the alpha was adjusted by the Bonferroni correction to .0055 (.05/9). Each is presented in turn below. 3.1. PANAS 3.1.1. Positive affect A 2 (PA: pre- and post-PASAT-C) x3 (instruction: conditional, hierarchical, and mixed) mixed ANOVA was conducted to assess the effect of the different instructions on positive affect. A significant effect of time, F(1, 66) = 9.98, p = .002, η² = .13, and group, F(2, 66) = 235.1, p < .001, η² = .88, was observed. A significant interaction between time and condition was observed, F(2, 66) = 330.41, p < .001, η² = .91, indicating that the different instructions had differing effects on levels of positive affect. As a significant interaction was observed a series of one-way ANOVAS were conducted to assess where the differences lie. A one-way between-subjects ANOVA revealed there was no significant difference in positive affect between the three groups preinstruction (See Table 2). A subsequent one-way between-subjects ANOVA revealed a significant difference between the three groups post-intstruction (See Table 2). Bonferroni corrected post-hoc analysis revealed that all groups significantly differed from each other (all p < .001). Within-group analysis through within-subject t-tests revealed that the hierarchy group observed a significant increase in positive affect postinstruction, t(22) = −17.208, p < .001, d= -3.6, and the conditional group observed a significant decrease in positive affect, t (22) = 20.06, p < . 001, d = 5.35. A significant difference was not observed pre- and post-intervention in positive affect for the mixed group, t(22) = −2.63, p =.015, d= -.77. 3.1.2. Negative affect A 2 (NA: pre- and post-PASAT-C) x2 (instruction: conditional, hierarchical, and mixed) mixed ANOVA was conducted to assess the effect of the different instructions on negative affect. A significant effect of time, F(1, 66) = 1103.29, p < .001, η² = .94, and group, F (2, 66) = 235.6, p < .001, η² = .88, was observed. A significant interaction between time and condition was observed, F(2, 66) = 485.32, p < .001, η² = .94, indicating that the different instructions had differing effects on levels of negative affect. As a significant interaction was observed a series of one-way ANOVAS were conducted to assess where the differences lie. A one-way between-subjects ANOVA revealed there was no significant difference in negative affect between the three groups preinstruction (See Table 2). A subsequent one-way between-subjects ANOVA revealed a significant difference between the groups postinstruction (See Table 2). Bonferroni corrected post-hoc analysis revealed that the hierarchy and mixed group differed from the conditional group (p < . 001), the mixed group did not significantly differ from the hierarchy group (p =. 036). Within-group analysis through within-subject t-tests revealed that both the hierarchy and conditional group observed a significant increase in negative affect post-instruction, with 37
Dysphoria Pre Post PANAS Negative Affect Pre Post PANAS Positive Affect Pre Post Anagram Pre Post
Measure
38
330.41 493.1
.1 505.92
1.79 41.59
2,66 2,66
2,66 2,66
.029 242.16
F
2,66 2,66
2,66 2,66
df
.17 < .001
.95 < .001
.21 < .001
.971 < .001
p
.05 .56
.003 .94
.05 .92
.001 .87
η²
22
22
22
22
df
1.07
20.06
.295
< .001
< .001
< .001
−26.91
−39.62
p
Conditional t
.27
5.35
−9.12
−7.62
Cohen’s d
22
22
22
22
df
−5.23
−17.21
−3.57
−9.55
Hierarchy t
< .001
< .001
.002
< .001
p
−1.48
−3.6
−1.05
−2.76
Cohen’s d
22
22
22
22
df
−19.77
−2.63
−10.52
−19.44
Mixed t
< .001
.015
< .001
< .001
p
−3.18
.77
−2.73
−5.07
Cohen’s d
Table 2 Between-Subjects ANOVAS to assess group differences at both pre and post-instruction and within-subject t-tests for all three conditions to assess pre and post differences within groups. Contains test statistic, degrees of freedom, p-value, and effect size for all tests.
V. Eswara Murthy et al.
Learning and Motivation 65 (2019) 33–42
Learning and Motivation 65 (2019) 33–42
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negative affect not significantly changing for the mixed group (See Table 2). 3.2. Dysphoria A 2 (Dysphoria: pre- and post-PASAT-C) x2 (instruction: conditional, hierarchical, and mixed) mixed ANOVA was conducted to assess the effect of the different instructions on total scores of dysphoria. A significant effect of time, F(1, 66) = 1109.48, p < .001, η² = .92, and group, F(2, 66) = 157.09, p < .001, η² = .83, was observed. A significant interaction between time and condition was observed, F(2, 66) = 186.62, p < .001, η² = .85, indicating that the different instructions had differing effects on levels of dysphoria. As a significant interaction was observed a series of one-way ANOVAS were conducted to assess where the differences lie. A one-way between-subjects ANOVA revealed there was no significant difference in dysphoria between all three groups (See Table 2) A subsequent one-way between-subjects ANOVA revealed a significant difference between the groups. Bonferroni corrected post-hoc analysis revealed that all groups significantly differed from each other (all p < .001). Within-group analysis through within-subject t-tests revealed that a significant increase in dysphoria was observed for all three groups postinstruction (See Table 2). 3.3. Anagram A 2 (Anagram: pre- and post-instruction) x2 (instruction: conditional, hierarchical, and mixed) mixed ANOVA was conducted to assess the effect of the different instructions on proficiency at solving anagrams. A significant effect of time, F(1, 66) = 107.8, p < .001, η² = .62, and group, F(2, 66) = 10.59, p < .001, η² = .24, was observed. A significant interaction between time and condition was observed, F(2, 66) = 48.97, p < .001, η² = .6, indicating that the different instructions had differing effects on proficiency at the anagram task. As a significant interaction was observed a series of one-way ANOVAS were conducted to assess where the differences lie. A one-way between-subjects ANOVA revealed there was no significant difference in anagram scores pre-instruction. A subsequent one-way between-subjects ANOVA revealed a significant difference between the three groups. Bonferroni corrected post-hoc analysis revealed that only the conditional and mixed groups differed, with the mixed group scoring higher post-instruction than the conditional group (p < . 001), the mixed group did not significantly differ from the hierarchy group (p =. 12) and the conditional group did not significantly differ from the hierarchical group (p =.04). Within-group analysis through within-subject t-tests revealed that both the hierarchy and mixed group observed a significant increase in scores postinstruction, with no significant difference observed in the conditional group (See Table 2). 3.4. Distress tolerance- PASAT-C quit time A one-way between-subjects ANOVA (IV: Instruction: conditional, hierarchy, and mixed. DV: PASAT-C quit times) revealed a significant difference in quit times between groups, F(2, 66) = 117.95, p < .001, η² = .78, between the conditional (M = 310.39, SD = 81.85), hierarchical (M = 540, SD = 66.2), and mixed (M = 581.35, SD = 37.15). Bonferroni corrected post-hoc analysis revealed that the conditional group differed from both the hierarchy and mixed groups (p < .001) indicating that the conditional group had significantly lower quit times than both the hierarchy and mixed groups. The hierarchy and mixed groups did not significantly differ in quit times (p =.1). 3.5. PASAT-C total scores A one-way between-subjects ANOVA (IV: Instruction: conditional, hierarchy, and mixed. DV: PASAT-C total scores) revealed a significant difference in total scores between groups, F(2, 66) = 105.04, p < .001, η² = .76, between the conditional (M = 56, SD = 16.49), hierarchical (M = 109, SD =14.87), and mixed (M = 121.87, SD = 17.54). Bonferroni corrected post-hoc analysis revealed that the conditional group differed from both the hierarchy and mixed groups (p < .001) indicating that the conditional group had significantly lower total scores than both the hierarchy and mixed groups. The hierarchy and mixed groups did not significantly differ in total scores (p = .029). 3.6. Self-Efficacy A one-way between-subjects ANOVA (IV: Instruction: conditional, hierarchy, and mixed. DV: self-esteem) revealed a significant difference in self-esteem between groups, F(2, 66) = 116.16, p < .001, η² = .59, between the conditional (M = 406.52, SD = 32.42), hierarchical (M = 566.09, SD = 47.55), and mixed (M = 559.56, SD = 39.14). Bonferroni corrected post-hoc analysis revealed that the conditional group differed from both the hierarchy and mixed groups (p < .001) indicating that the conditional group had significantly lower self-esteem scores than both the hierarchy and mixed groups. The hierarchy and mixed groups did not significantly differ in total scores (p = 1.00). 3.7. Willingness A one-way between-subjects ANOVA (IV: Instruction: conditional, hierarchy, and mixed. DV: willingness to do task again) 39
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revealed a significant difference in willingness to engage in the task again between groups, F(2, 66) = 149.82, p < .001, η² = .82, between the conditional (M = 70.96, SD = 8.19), hierarchical (M = 25.09, SD = 8.21), and mixed (M = 39.69, SD = 10.89). Bonferroni corrected post-hoc analysis revealed that all groups significantly differed from each other (all p < .001), with the hierarchy group revealing increased willingness to engage in the task again over the conditional and mixed groups and the mixed group showing an increase in willingness over the conditional group. 3.8. Comfort A one-way between-subjects ANOVA (IV: Instruction: conditional, hierarchy, and mixed. DV: comfort) revealed a significant difference in comfort in participating in the task between groups, F(2, 66) = 158.5, p < .001, η² = .79, between the conditional (M = 75.78, SD = 9.52), hierarchical (M = 30.65, SD = 5.45), and mixed (M = 41.87, SD =10.95). Bonferroni corrected post-hoc analysis revealed that all groups significantly differed from each other (all p < .001), with the hierarchy group revealing significantly increased comfort in doing the task over the conditional and mixed groups and the mixed group showing an increase in comfort over the conditional group. 3.9. Positivity A one-way between-subjects ANOVA (IV: Instruction: conditional, hierarchy, and mixed. DV: positivity) revealed a significant difference in positivity between groups, F(2, 66) = 50.34, p < .001, η² = .61, between the conditional (M = 33.69, SD = 10.19), hierarchical (M = 65.79, SD = 11.31), and mixed (M = 54.22, SD = 11.39). Bonferroni corrected post-hoc analysis revealed that all groups significantly differed from each other, with the hierarchy group revealing significantly increased positivity associated with the experience of the task over the conditional (p < .001) and mixed groups (p = .002). and the mixed group showing an increase in comfort over the conditional group (p < .01). 3.10. Self-perception of task performance A one-way between-subjects ANOVA (IV: Instruction: conditional, hierarchy, and mixed. DV: Self-perception of task performance) revealed a significant difference in self-perception of task performace between groups, F(2, 66) = 84.46, p < .001, η² = .72, between the conditional (M = 35.04, SD = 8.36), hierarchical (M = 62.17, SD =9.39), and mixed (M = 68.39, SD = 9.93). Bonferroni corrected post-hoc analysis revealed that the conditional group differed from both the hierarchy and mixed groups (p < .001) indicating that the conditional group had significantly lower ratings of how they felt they performed on the task than both the hierarchy and mixed groups. The hierarchy and mixed groups did not significantly differ in perception of task performance (p =.076). 3.11. Difficulty A one-way between-subjects ANOVA (IV: Instruction: conditional, hierarchy, and mixed. DV: Difficulty) revealed a significant difference in perception of task difficulty between groups, F(2, 66) = 89.37, p < .001, η² = .73, between the conditional (M = 30.35, SD = 8.84), hierarchical (M = 70.04, SD = 11.14), and mixed (M = 59.22, SD = 11.08). Bonferroni corrected post-hoc analysis revealed that all groups significantly differed from each other, with the hierarchy group revealing a significantly lower perception of task difficulty associated with the experience of the task over the conditional (p < .001) and mixed groups (p = .002). and the mixed group showing a lower in perception of task difficulty over the conditional group (p < .01). 4. Discussion The current study aimed to investigate how motivation based on hierarchical versus conditional versus mixed (hierarchical and conditional) framing impacted performance and psychological experiences in a distress tolerance task. The findings indicated that the hierarchical and mixed groups outperformed the conditional group on measures of task performance and of number psychological experiences, such as self-efficacy, comfortableness and willingness. This effect was transferred to performance on a different type of task (anagram). To our knowledge, this is the first RFT study to test the impact of different types of framing on motivation. The results we observed confirm the benefit of hierarchical and mixed hierarchical/conditional framing as suggested in a number of publications on applied contextual behavioral science (e.g. Dahl et al., 2009; Villatte, Villatte, & Hayes, 2015). The current study also extends a developing approach in RFT initiated by Luciano et al. (2011), consisting of comparing the effect of types of framing through natural language (i.e., using instructions in the language of the participants). We believe the method used in our study demonstrates a higher level of precision than in previous studies due to the fact that the targeted relations were specifically compared rather than comparing a larger textual instruction which included multiple relational frames, as in Luciano et al. (2011) and Foody, Barnes-Holmes, BarnesHolmes, and Luciano (2013) for example. That is, the different experimental conditions varied based only on one type of framing between the hierarchical and the conditional framing groups. In Luciano et al. (2011) and Foody et al. (2013) several types of framing were changed across conditions, making it difficult to draw unequivocal conclusions. More recent investigations have looked at the effects of deictic and hierarchical instructions on broadening participants sense of self and the impact of these relations on 40
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psychological flexibility (Gil-Luciano, Ruiz, Valdivia-Salas, & Suárez-Falcón, 2017) and cognitive performance (López-López and Luciano (2017). All of these studies used relatively long instructions that lack tight control over the different relations being emphasized across conditions. A recent study by Sierra, Ruiz, Flórez, Riaño-Hernández, and Luciano (2016) investigated the effects of brief instructions that only manipulated specific relational cues in a similar way to the current study. The relational cues were manipulated in order to change a metaphor that was instructing participants on how to cope in a pain tolerance analogue task (i.e., cold-pressor task). Participants received metaphors that included physical properties similar to the individual’s pain (e.g., ‘very cold’) in the metaphor content and specified appetitive augmental functions (e.g., to get ‘this thing you dream about’). The findings from Sierra et al. (2016) showed that both including physical properties and augmental functions had significant effects on the pain tolerance during the cold-pressor task. The current findings can also be considered in terms of Vrooms Expectancy Theory of motivation. According to Expectancy Theory individuals will choose how to behave depending on the outcomes they expect as a result of their behavior (Van Eerde & Thierry, 1996). Put simply, people decide what to do based on what they expect the outcome to be. In a work setting, a person may work overtime because they expect that it will result in a promotion. However, from this perspective the process by which we decide our behaviors is also influenced by how likely we perceive the rewards to be. Extending on the example, the person may be more likely to work harder if their boss told them that working overtime would lead to a promotion rather than if they perceived the outcome as less likely. Expectancy theory is based on three elements, expectancy, instrumentality (i.e., the belief that you will receive a reward if you meet performance expectations) and valence (i.e., the value you place on the reward.) Therefore, from the expectancy theory point of view people will be most motivated if they believe that they will receive a desired reward if they hit an achievable target. The current study involved providing the participants with rules where the mixed condition involved the highest level of expectancy, instrumentality and valence and also resulted in the best performance in terms of task performance and persistence. Motivation is often considered in terms of whether it is extrinsic, that is, originating from an outside demand, obligation, or reward that requires the achievement of a particular goal or intrinsic where the individual strives towards a goal for personal satisfaction or accomplishment. From an RFT point of view we look at whether the motivation is intrinsic. or extrinsic to the action. In this sense, hierarchical framing provides intrinsic reinforcement by simply engaging in the action because it is “part of” a process or a value. Participants in the hierarchical condition of the current study were seem to have benefited from this kind of intrinsic motivation, which is particularly helpful in the context of a task that is difficult to accomplish and fairly distressing. When examining the current results it can be seen that the condition that emphasized conditional relations alone was less effective than the condition that emphasized hierarchical relations. However, the condition with conditional associated with hierarchical relations was the most effective. This suggests that tracking outcome is effective as long as it is in the context of process focused motivation. This can be understood form an RFT perspective. That is, awareness of outcome (tracking requires awareness of consequences) and clarity of values (so that satisfaction is not expected only from these outcomes) are both important. This can also be understood in terms of the literature on intrinsic and extrinsic motivation. Specifically, the results from this perspective would indicate that extrinsic motivation can be effective if it is associated with intrinsic motivation. Interestingly, in the mixed condition, participants were instructed that what was most important was the process. In this sense it was not just mixed, a hierarchical relation between outcome and process was established. That is, participants were instructed that outcome is important but process is even more important. If the two instructions were pitched at the same level of importance it is likely that different results may have emerged. Some limitations to the current study should be noted. First, the use of the PASAT-C may limit the generalization of our findings to distress tolerance tasks. Indeed, the very purpose of distress tolerance tasks is to stay engaged in the task. Therefore, it is possible that motivation based on hierarchical framing (engaging in the task as part of a process rather than focusing on the outcome) is effective for these kinds of tasks, but not for others. The fact that performance increased on the anagram task in the hierarchical and mixed condition, but not in the conditional condition is perhaps an indication that hierarchical framing can have a better impact than conditional framing alone on other types of task than distress tolerance. However, at this stage, we can only conclude that the difference observed among the groups on the anagram task was caused by prior exposure to the PASAT-C task with different types of motivation. Future studies should replicate our experiment using the same instructions with another type of dependent measure, such as problem solving or reaction time tasks. Another limitation is related to the use of natural language to activate the different relations. While we created instructions as precisely as possible using words aimed to reflect hierarchical vs conditional framing vs mixed framing, it is possible that the participants interpreted these words in different ways. That is, some participants in the hierarchical condition may have derived motivation based on conditional framing and vice versa. Future studies should replicate our experiment using a manipulation check in this regard (e.g. by asking participants how they understood the instructions). Given our use of natural language (rather than cues established through training in controlled conditions) it is also necessary to replicate the current study with different instructions aimed to activate hierarchical vs conditional motivation, including in different languages than English. This will ensure that the effects we observed were not due to the particular words used in our instructions, but to the types of framing these instructions were meant to activate. Despite these limitations, the results we observed highlight the potential differing effects framing tasks conditionally, hierarchically or both hierarchically and conditionally can have on motivation and task performance. We believe our study constitutes an important contribution to the RFT analysis of middle level terms such as values and committed action in acceptance and commitment therapy (ACT, Hayes, Strosahl, & Wilson, 2011). While there have been debates about the relationship between middle level terms and RFT principles (Barnes-Holmes, Barnes-Holmes, Luciano, & McEnteggart, 2017; Hayes, Barnes-Holmes, & Wilson, 2012), the method used in our study shows that these two levels of analysis are not incompatible and can in fact inform each other in a 41
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reticulated fashion (Villatte et al., 2018). Indeed, we conducted the current study as a result of clinical observations and conceptual analyses. In turn, the results we observed can help refine the way practitioners use language to build meaningful motivation in applied settings. We believe a similar approach can be applied to other areas of applied psychology, such as interventions on self, compassion, or mindfulness. Acknowledgment The first author is funded by the Irish Research Council. References Barnes-Holmes, D., Barnes-Holmes, Y., Luciano, C., & McEnteggart, C. (2017). From the IRAP and REC model to a multi-dimensional multi-level framework for analyzing the dynamics of arbitrarily applicable relational responding. Journal of Contextual Behavioral Science, 6(4), 434–445. Brehm, J. W., & Self, E. A. (1989). The intensity of motivation. In M. R. Rozensweig, & L. W. Porter (Vol. Eds.), Annual, review of psychology: Vol. 40, (pp. 109–131). Brown, R. A., Lejuez, C. W., Kahler, C. W., & Strong, D. (2002). Distress tolerance and duration of past smoking cessation attempts. Journal of Abnormal Psychology, 111, 180–185. Catania, A. C. (1992). B. F. Skinner, organism. American Psychologist, 47(11), 1521–1530. Crawford, J. R., & Henry, J. D. (2004). The positive and negative affect schedule (PANAS): Construct validity, measurement properties and normative data in a large non-clinical sample. British Journal of Clinical Psychology, 43(3), 245–265. Dahl, J. C., Plumb, J. C., Stewart, I., & Lundgren, T. (2009). The art and science of valuing in psychotherapy: Helping clients discover, explore, and commit to valued action using acceptance and commitment therapy. Oakland, CA: New Harbinger Publications, Inc. Daughters, S. B., Lejuez, C. W., Strong, D. R., Brown, R. A., Breen, R. B., & Lesieur, H. R. (2005). The relationship among negative affect, distress tolerance, and length of gambling abstinence attempt. Journal of Gambling Studies, 21(4), 363–378. Daughters, S. B., Lejuez, C. W., Kahler, C., Strong, D., & Brown, R. (2005). Psychological distress tolerance and duration of most recent abstinence attempt among residential treatment seeking substance abusers. Psychology and Addictive Behavior, 19, 208–211. Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. New York, NY: Plenum. Fishbach, A., & Choi, J. (2012). Self-regulatory failure and intimate partner violence perpetration. Journal of Personality and Social Psychology, 97, 483–499. Foody, M., Barnes-Holmes, Y., Barnes-Holmes, D., & Luciano, C. (2013). An empirical investigation of hierarchical versus distinction relations in a self-based ACT exercise. International Journal of Psychology & Psychological Therapy, 13(3), 373–388. Gil-Luciano, B., Ruiz, F. J., Valdivia-Salas, S., & Suárez-Falcón, J. C. (2017). Effect of framing behavior through deictic/hierarchical relations and specifying augmental functions in promoting psychological flexibility. The Psychological Record, 67, 1–9. Gratz, K. L., Rosenthal, M. Z., Tull, M. T., Lejuez, C. W., & Gunderson, J. G. (2006). An experimental investigation of emotion dysregulation in borderline personality disorder. Journal of Abnormal Psychology, 115(4), 850–855. Hayes, S. C., Barnes-Holmes, D., & Roche, B. (Eds.). (2001). Relational frame theory: A post-Skinnerian account of human language and cognition. New York: Plenum Press. Hayes, S. C., Barnes-Holmes, D., & Wilson, K. G. (2012). Contextual Behavioral Science: Creating a science more adequate to the challenge of the human condition. Journal of Contextual Behavioral Science, 1, 1–16. Hayes, S. C., Strosahl, K. D., & Wilson, K. G. (2012). Acceptance and commitment therapy: The process and practice of mindful change (2nd ed.). New York: Guildford. Iwata, B. A., Smith, R. G., & Michael, J. (2000). Current research on the influence of establishing operations on behavior in applied settings. Journal of Applied Behavior Analysis, 33(4), 411–418. Ju, W. C., & Hayes, S. C. (2008). Verbal establishing stimuli: Testing the motivative effect of stimuli in a derived relation with consequences. The Psychological Record, 58(3), 339–363. Keller, F. S., & Schoenfeld, W. N. (1950). Principles of psychology: A systematic text in the science of behavior. New York: Appleton-Century, Crofts. Lejuez, C. W., Kahler, C. W., & Brown, R. A. (2003). A modified computer version of the Paced Auditory Serial Addition Task (PASAT) as a laboratory-based stressor. The Behavior Therapist, 26, 290–293. Locke, E. A., & Latham, G. P. (1990). A theory of goal setting and task performance. Upper Saddle River, NJ: Prentice Hall. López-López, J. C., & Luciano, C. (2017). An experimental analysis of defusion interactions based on deictic and hierarchical framings and their impact on cognitive performance. The Psychological Record, 1–13. Luciano, C., Ruiz, F. J., Vizcaíno-Torres, R., Sánchez, V., Gutiérrez-Martínez, O., & López-López, J. C. (2011). A relational frame analysis of defusion interactions in acceptance and commitment therapy. A preliminary and quasi-experimental study with at-risk adolescents. International Journal of Psychology and Psychological Therapy, 11, 165–182. Michael, J. (2000). Implications and refinements of the establishing operation concept. Journal of Applied Behavior Analysis, 33, 401–410. Plumb, J. C., Stewart, I., Dahl, J., & Lundgren, T. (2009). In search of meaning: Values in modern clinical behavior analysis. The Behavior Analyst, 32, 85–103. Sansone, C., & Harackiewicz, J. M. (1996). “I don’t feel like it”: The function of interest in self- regulation. In L. L. Martin, & A. Tesser (Eds.). Striving and feeling: Interactions among goals, affect, and self-regulation (pp. 203–228). Hillsdale, NJ: England Lawrence Erlbaum Associates, Inc. Scholz, U., Gutiérrez-Doña, B., Sud, S., & Schwarzer, R. (2002). Is general self-efficacy a universal construct? Psychometric findings from 25 countries. European Journal of Psychological Assessment, 18, 242–251. Schwarzer, R., & Jerusalem, M. (1995). Generalized self-efficacy scale. In J. Weinman, S. Wright, & M. Johnston (Eds.). Measures in health psychology: A user’s portfolio. Causal and control beliefs (pp. 35–37). Windsor, UK: NFER-NELSON. Shah, J. Y., & Kruglanski, A. W. (2000). Aspects of goal networks: Implications for self- regulation. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.). Handbook of selfregulation (pp. 85–110). San Diego, CA: Academic Press. Sierra, M. A., Ruiz, F. J., Flórez, C. L., Riaño-Hernández, D., & Luciano, C. (2016). The role of common physical properties and augmental functions in metaphor effect. International Journal of Psychology and Psychological Therapy, 16, 265–279. Van Eerde, W., & Thierry, H. (1996). Vroom’s expectancy models and work-related criteria: A meta-analysis. Journal of Applied Psychology, 81, 575–586. Villatte, M., Villatte, J. L., & Hayes, S. C. (2015). Mastering the clinical conversation: Language as intervention. New York: Guilford Press. Villatte, M., Villatte, J. L., & Hayes, S. C. (2018). A reticulated and progressive strategy for developing clinical applications of RFT. The Psychological Record, 68(March (1)), 113–117. https://link.springer.com/article/10.1007/s40732-017-0251-2. Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54, 1063–1070.
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Contents lists available at ScienceDirect
Learning and Motivation journal homepage: www.elsevier.com/locate/l&m
Investigating the effect of conditional vs hierarchical framing on motivation Varsha Eswara Murthya, Matthieu Villatteb, Louise McHugha, a b
T
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University College Dublin, School of Psychology, Newman Building, Belfield, Ireland Bastyr University, Seattle, USA
A R T IC LE I N F O
ABS TRA CT
Keywords: Motivation Relational frame theory Hierarchical relating Conditional relating Persistence
Manipulating motivational factors is an effective method for increasing desired behavior and reducing problematic behavior, as well as for increasing satisfaction from desired but challenging actions. From the Relational Frame Theory (RFT) perspective, hierarchical networks of symbolic positive reinforcers are advantageous motivators as they provide intrinsic, overarching, and inexhaustible reinforcement to our actions, even when they cause some degree of distress. The current study aimed to investigate how motivation based on hierarchical versus conditional versus a mixed (hierarchical and conditional) framing impacts performance and psychological experiences in a distress tolerance task. Participants completed an anagram task, followed by the presentation of scripts relating to three separate framing conditions. Participants then proceeded to take part in an adapted PASAT-C to measure task persistence, followed by completion of selfreport measures evaluating mood, self-efficacy, and experiences of task participation. A final anagram task was completed to evaluate the effect of framing condition on task performance and transfer of framing conditions across different tasks. Hierarchical and mixed groups outperformed the conditional group on measures of task performance and persistence. This effect was transferred to performance on the anagram task. Significantly increased self-efficacy, comfortableness, and willingness were observed for both the hierarchical and mixed conditions over the conditional group with the hierarchical group outperforming the mixed group. This study highlights the potential differing effects that framing tasks conditionally, hierarchically or both hierarchically and conditionally can have on motivation and task performance.
1. Introduction Manipulating motivational factors is an effective method for increasing desired behavior and reducing problematic behavior (Iwata, Smith, & Michael, 2000), as well as for increasing satisfaction from desired but challenging actions (Plumb, Stewart, Dahl, & Lundgren, 2009). Relational Frame Theory (RFT; Hayes, Barnes-Holmes, & Roche, 2001) is a contextual behavioural approach to language and cognition which proposes that motivation can be altered through the use of language. According to RFT, language is a behavior consisting of building relations among stimuli not solely based on their physical or formal properties but based on socially established cues (technically referred to as relational framing or framing events relationally). Consider the relationship between the word ‘SWEATER’ and an actual sweater. We treat these two things as being similar in many contexts, despite the fact that they have
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Corresponding author. E-mail addresses: [email protected] (V. Eswara Murthy), [email protected] (M. Villatte), [email protected] (L. McHugh). https://doi.org/10.1016/j.lmot.2018.11.002 Received 9 December 2017; Received in revised form 26 November 2018; Accepted 27 November 2018 0023-9690/ © 2018 Elsevier Inc. All rights reserved.
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physically very little in common (they are put into an abstract relation of sameness with each other). As a result, if a person asks you to give her the sweater, you will likely hand her the actual sweater. Being able to relate stimuli abstractly (i.e. to build symbolic relationships between things) is what allows us to contact experiences that are not physically present in our environment, such as distant or abstract consequences of current actions (e.g. knowing that studying hard will help get a degree several months later, or smiling at a stranger as an expression of compassion). We can relate things in many different ways, other than relations of sameness. For example, we can relate things as opposite (‘Thin is opposite to fat’) different (‘medium is different from rare’) comparatively (‘Maura is smarter than Kate’) conditionally (‘If I get angry then I break something’) temporally (‘Halloween is before Christmas’), in terms of perspective (‘From where I am, I can see the mountains, and from where you are, you can see the sea’) and hierarchically (‘dog is a type of animal’; ‘valued goals and actions are part of valued living’). From a learning theory perspective studying motivation involves looking at what makes consequences more or less effective as reinforcers or as punishers (Catania, 1992). Traditionally motivational effects have been distinguished from reinforcement effects and referred to as Establishing Operations (EO; Keller & Schoenfeld, 1950). An EO is a condition of deprivation or aversion that temporarily alters the value of a particular reinforcer. Michael (2000) worked on more clearly defining motivational variables by developing and extending Skinner’s account of motivation with the term motivating operation (MO). According to Michael MOs explain variations in the effects in the consequences of behavior. For example, sleep deprivation can be considered a motivating operation. If an individual is tired, sleep is strongly reinforcing, but if an individual is well rested, sleep is less reinforcing. In the RFT literature augmenting involves relational networks that alter the degree to which events function as consequences. One form of augmenting is referred to as motivative augmenting and is defined as ‘behavior due to relational networks that temporarily alter the degree to which previously established consequences function as reinforcers or punishers’, (Hayes et al., 2001, P109). An example of a motivative augmental is, “Wouldn’t a hot cup of hot chocolate taste good right now?” An important distinction is to be made between events that are verbal establishing stimuli (establish something as a reinforcer) and verbal discriminative stimuli (have a discriminative function). Buying hot tea after the earlier statement likely functions as a verbal establishing stimulus, not a verbal discriminative stimulus, given that hot tea is available whether or not the rule is present. Motivative augmentals operate by presenting the sensory or perceptual functions of a consequence. In the earlier example the words “hot” and “tea” come to have sensory functions via a transformation of stimulus function (i.e., the listener can imagine tasting hot tea) (see Ju & Hayes, 2008 for an experimental demonstration). It has been suggested that employing different types of framing will have a differential impact on motivation (Villatte, Villatte, & Hayes, 2018). However, to date there is no empirical evidence to support this postulate. More specifically, conditional and hierarchical framing are two patterns of relational framing that can be used to build or identify symbolic functions of actions. Conditional framing could be likened to outcome based motivation (Brehm & Self, 1989; Locke & Latham, 1990). In this case, motivation to participate and complete a task can be based on achieving a ‘good score’, for example. Hierarchical framing can be likened to process based motivation (Dahl, Plumb, Stewart, & Lundgren, 2009; Deci & Ryan, 1985; Fishbach & Choi, 2012; Sansone & Harackiewicz, 1996; Shah & Kruglanski, 2000). In this case for example, motivation to participate in a task could come from a motivation to learn, such that participation in the task is viewed as serving the overarching value and purpose of learning. From the RFT perspective, hierarchical networks of this kind can provide intrinsic, overarching, and inexhaustible reinforcement by linking actions (at the bottom of the hiearchical network) to an overarching goal (e.g. sharing knowledge with others) and qualities of action (e.g. with precision) (at the top of the hiearchical network). Actions are thus guided by these symbolically contructed consequences across time and situtions, and become reinforcing independent of additional consequences. While conditional relations focusing on specific goals only allow contact with satisfaction if the goal is met (e.g. “I need to study to get my degree and make a lot of money and then I will be happy”), hierarchical relations make the process of engaging in the action reinforcing in and of itself (e.g. “Studying is part of learning, which is something I value regardless of the outcome of studying”). In a clinical context, developing motivation through hierarchical framing can be linked to work on values in therapies such as Acceptance and Commitment Therapy (ACT, Hayes, Strosahl, & Wilson, 2012). In these approaches, clients are trained to connect their actions to sources of meaningful reinforcement that are not dependent on outcomes of action. For example, before starting an exposure session (e.g. working on fear of public speaking), a therapist might ask a client to express the higher purpose of doing this exercise not in terms of a specific outcome (e.g. getting better at public speaking) but in terms of values (e.g. openness). By doing so, the client can connect to the value as soon as she is exposing herself to the fear situation rather than waiting for the outcome to happen. Even outside clinical issues, finding motivation during difficult or undesirable tasks is obviously particularly challenging. However, living a meaningful life involves times when sticking with difficult tasks is critical. All areas of life (e.g. parenting, relationships, work) involve times when motivation to engage in valued actions is low, but disengaging at these times can have negative consequences (e.g, failed marriage, job loss). The Paced Auditory Serial Addition Task (PASAT-C; Lejuez, Kahler, & Brown, 2003) is a behavioral measure of persistence, in which the participant performs serial addition of numbers under tight time constraints. PASATC scores have been related to borderline personality disorder diagnosis (Gratz, Rosenthal, Tull, Lejuez, & Gunderson, 2006) and to the length of time smokers (Brown, Lejuez, Kahler, & Strong, 2002), illicit drug abusers (Daughters, Lejuez, Strong et al., 2005), or gamblers (Daughters, Lejuez, Kahler, Strong & Brown, 2005) had remained abstinent during prior quit attempts. The current study aims to investigate how hierarchical vs. conditional vs. a mixed condition (hierarchical and conditional) framing of task participation impacts motivation on the PASAT-C. The study specifically investigates the impact of the framing conditions on task performance, transfer of framing condition functions to performance on an alternate task, task persistence, mood reactivity to tasks, self-efficacy, willingness to participate in the task again, comfortableness doing task, self-perceptions of task 34
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performance. 2. Method 2.1. Participants The sample totalled 69 participants, with 23 participants being assigned to the three different framing instruction groups. An apriori power analysis revealed that a sample size of 50 would be required to yield a moderate effect sizes. Data was collected for a set recruitment period of two months. At the end of this period it was determined that data collection would end as long as the 50 participants or more had been recruited. Thus a sample of size of 69 with 23 being assigned to each group was what was collected at the end of this period. Participants aged 18 to 48 (M = 23.25; SD = 5.44) was recruited using opportunity sampling from University College Dublin, including a student sample. The sample included 32 males and 37 females, each framing instruction group was closely balanced for gender. Informed consent was obtained prior to data collection and research was granted ethical approval from University College Dublin’s Human Research Ethics Committee. No compensation was given to participants. Participants were otherwise blind to the true nature of the study. Exclusion criteria included having a specific developmental disorder, such as dyslexia (due to the verbal-based nature of the learning task) and dyscalculia (due to the arithmetic-based nature of the PASAT-C). In order to reduce demand characteristics, the study was advertised as an experiment testing various cognitive abilities and, thus, participants were naïve to the true nature of the study as well as being blind as to which instruction they received. 2.2. Study design The study design, involved a mixed between-within design with group as the between-subject factor (Hierarchy, Conditional, and Mixed) and time (Pre- and Post-PASAT-C) as the within-subject factor to assess differences on scores on the mood reactivity scale, PANAS, and anagram task performance post completion of the PASAT-C. A between-group analysis using 8 separate ANOVAs with group as the independent variable, dependent variables include: total number of correct answers on the PASAT-C time to quit task on third trial of the PASAT-C, scores on the self-efficacy scale, scores on each of the items on the 5 item scale (comfortableness doing task, willingness to engage in the task again, positivity/negativity of experience in participating in the task, perceptions of task performance, and task difficulty). Each separate ANOVA was calculated in order to assess whether there is a significant difference between the framing conditions. 2.3. Measures 2.3.1. Mood 2.3.1.1. Positive and negative affect scale (PANAS). The PANAS (Watson, Clark, & Tellegen, 1988) is a 20-item self-report measure measuring positive and negative affect, with each item rated on a 5-point Likert scale. It consists of two scales for positive and negative affect, with the Cronbach’s alpha in the current study of participants’ ratings of 0.91 and .75, respectively, for each of the scales. Construct validity has been found to be good, and confirmatory factor analysis has yielded two factors corresponding to the PA and NA scales (Crawford & Henry, 2004). The scale was implemented as a between-groups current mood measure T1 to T4. 2.3.1.2. Mood reactivity scale. To determine whether the PASAT-C induced distress, dysphoria was measured, both prior to and after the PASAT-C, using a four-item self-report scale. Irritability, frustration, anxiety, and difficulty concentrating were each rated on a visual analogue scale ranging from 0 to 100 (0 = none; 100 = extreme). Anxiety, frustration, difficulty concentrating, and irritability are believed to be indicators of psychological distress and have been shown to be highly inter-correlated (Brown et al., 2002), these variables were summed to create the dysphoria measure. 2.3.1.3. Task performance. An anagram task served as a pre- and post-measure of task performance following induction of a framing condition and completion of the PASAT-C and also served to measure the ability of transfer of framing conditions across differing tasks. This involved 5 anagrams being individually presented via PowerPoint for a period of 1-minute each, with participants being instructed to solve the anagram and write down their answers on a blank answer sheet, this is in line with previous research conducted by Shah and Kruglanski (2000). 2.3.2. Self-Efficacy General Self-Efficacy Scale (GSES). The GSES (Scholz, Gutiérrez-Doña, Sud, & Schwarzer, 2002; Schwarzer & Jerusalem, 1995) is a measure of general self-efficacy. It consists of 10 items. Respondents rate each item on a 1 (not true at all) to 4 (exactly true) scale. Sample items include “I am confident that I could deal efficiently with unexpected events,” and “I can usually handle whatever comes my way.” Researchers have provided evidence supporting the reliability and validity of the GSES (Scholz et al., 2002). In the present sample, the GSES had a Cronbach's alpha of 0.73. 2.3.3. Distress tolerance measure 2.3.3.1. The paced auditory serial addition task (PASAT-C; Lejuez et al., 2003). This is a behavioural measure of task persistence and distress tolerance, in which the participant performs serial addition of numbers presented one at a time on a computer monitor. 35
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Participants were asked to add the most recent number presented to the previous one and to use the computer mouse to click on the correct answer from the numbers shown on the bottom of the screen. After clicking on the sum, the participants were asked to ignore the sum and to continue adding the number that is shown by the computer to the next number presented. A point is awarded for every correct answer, and an aversive “explosion” sound effect is played in response to every incorrect answer. The task includes three rounds of increasing difficulty (i.e., the latencies between numbers presented decreased and the length of the round increased). Unlike rounds 1–2, participants were given the option to “quit” the task at any time during level 3 (the most difficult round). The time (in seconds) it took for the participant to quit the task in round 3 is the behavioural index of task persistence or distress tolerance as a continuous measure. The maximum score possible is 600 (seconds), as the third round ends after 10 min. Participants will not be told of this time limit in advance. The PASAT-C was also used as a dichotomous measure (completed the entire 600 s versus quit early). PASAT-C scores have been related to borderline personality disorder diagnosis (Gratz et al., 2006) and to the length of time smokers (Brown et al., 2002), illicit drug abusers (Daughters, Lejuez, Strong et al., 2005; Daughters, Lejuez, Kahler et al., 2005), or gamblers (Daughters, Lejuez, Strong et al., 2005; Daughters, Lejuez, Kahler et al., 2005) had remained abstinent during prior quit attempts. 2.3.4. Framing instructions Framing instructions were presented before commencing the PASAT-C. Short prompts were also presented in-between trials of the PASAT-C. 2.3.4.1. Hierarchy. In the hierarchical framing group, specific hierarchical language was utilised such as “engage” and “taking part in the process”. Participants were presented with the following main instruction prior to commencing the PASAT-C: “My participation in the study will be worth it if I engage in the task because my taking part in the process is what matters most to the research.” Participants were presented with the following prompts in between PASAT-C trials; Pre-trial 1, after the instructions for the PASAT-C were presented: “Focus on engaging in the task.” Pre-trial 2, following completion of trial 1: “Focusing on what you are doing is the most important part of doing the task.” Pre-trial 3, following completion of trial 2: “Remember just engaging in the process of the task is the most important part of your participation.” 2.3.4.2. Conditional. In the conditional framing group, specific conditional language was utilised such as “getting a good score” and “focus on the outcome”. Participants were presented with the following main instruction prior to commencing the PASAT-C: “My participation will be worth it if I finish the task and make a good score, because the outcome is what matters most to the research.” Participants were presented with the following prompts in between PASAT-C trials; Pre-trial 1, after the instructions for the PASAT-C were presented: “Focus on getting a good score.” Pre-trial 2, following completion of trial 1:“Focusing on the end result of the task is what matters.” Pre-trial 3, following completion of trial 2: “Remember getting a good score is the aim of your participation.” 2.3.4.3. Mixed. In the mixed group, both hierarchical and conditional instructions were used. Participants were presented with the following main instruction prior to commencing the PASAT-C: “My participation in the study will be worth it if I engage in the task because taking part in the process is what matters, but finishing the task and getting a good score will be helpful for the research.” Participants were presented with the following prompts in between PASAT-C trials; Pre-trial 1, after the instructions for the PASAT-C were presented: “Focus on engaging in the task and getting a good score” Pre-trial 2, following completion of trial 1: “Focusing on what you are doing is part of the task but focusing on the end result of the task also matters.” Pre-trial 3, following completion of trial 2: “Remember just engaging in the task is the most important part of the task but getting a good score is also an important aim of your participation” 2.3.5. Procedure Participants were allocated to the three groups using random sampling procedure. Participants first completed the mood reactivity scale, PANAS and anagram task. Following completion of the questionnaires participants were immediately presented with their framing instructions, either hierarchical, conditional or mixed. Participants were then instructed to commence the PASAT-C task, with prompts corresponding to their framing instruction group appearing on the computer screen in-between trials. The moodreactivity scale, PANAS, anagram task, general self-efficacy, task-specific self-efficacy, comfortableness, willingness, positivity, perceptions of task difficulty and task performance, were measured post-completion of the PASAT-C. Participants were fully debriefed and then dismissed. 36
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Table 1 Mean scores across the three groups on all study measures. Measure
Conditional
Hierarchy
Mixed
PASAT C Quit Time PASAT C Total Scores
310.39 (81.85) 56 (16.49)
540 (66.2) 109 (14.87)
581.35 (37.15) 121.87 (17.54)
Dysphoria Pre Post
60.43 (13.64) 237.39 (29.88)
59.52 (14.29) 102.61 (16.85)
59.57 (14.3) 134.78 (15.34)
PANAS Negative Affect Pre Post
11.83 (1.23) 26.87 (1.98)
12.35 (1.07) 13.48 (1.08)
11.91 (.85) 15.26 (1.51)
PANAS Positive Affect Pre Post Self Efficacy Willingness to participate again Discomfort Positivity Perceived task performance Perceived task difficulty
26.91 (1.88) 16.3 (2.08) 397.69 70.96 (8.19) 75.78 33.69 (10.19) 35.04 (8.36) 30.35 (8.84)
27.09 (1.7) 33.65 (1.92 538.46 25.09 (8.21) 30.65 (5.45) 65.79 (11.31) 62.17 (9.39) 70.04 (11.14)
26.96 (1.72) 28.26 (1.65) 546.92 39.69 (10.89) 41.87 (10.95) 54.22 (11.39) 68.39 (9.93) 59.22 (11.08)
Anagram Pre Post
2.61 (.72) 2.43 (.59)
2.43 (.59) 3.39 (.72)
2.26 (.54) 4.22 (.67)
3. Results The descriptive statistics for each group across all tasks are presented in Table 1. A series of 2 × 3 mixed analyses of variance were conducted in order to determine the group, time and group time interaction across the study variables. A series of one-way ANOVAs were conducted to assess group differences at both pre-instruction and post-instruction, respectively. To determine if any differences between pre and post instruction scores on individual measures were significant, t tests were used. To reduce the risk of familywise error, the alpha was adjusted by the Bonferroni correction to .0055 (.05/9). Each is presented in turn below. 3.1. PANAS 3.1.1. Positive affect A 2 (PA: pre- and post-PASAT-C) x3 (instruction: conditional, hierarchical, and mixed) mixed ANOVA was conducted to assess the effect of the different instructions on positive affect. A significant effect of time, F(1, 66) = 9.98, p = .002, η² = .13, and group, F(2, 66) = 235.1, p < .001, η² = .88, was observed. A significant interaction between time and condition was observed, F(2, 66) = 330.41, p < .001, η² = .91, indicating that the different instructions had differing effects on levels of positive affect. As a significant interaction was observed a series of one-way ANOVAS were conducted to assess where the differences lie. A one-way between-subjects ANOVA revealed there was no significant difference in positive affect between the three groups preinstruction (See Table 2). A subsequent one-way between-subjects ANOVA revealed a significant difference between the three groups post-intstruction (See Table 2). Bonferroni corrected post-hoc analysis revealed that all groups significantly differed from each other (all p < .001). Within-group analysis through within-subject t-tests revealed that the hierarchy group observed a significant increase in positive affect postinstruction, t(22) = −17.208, p < .001, d= -3.6, and the conditional group observed a significant decrease in positive affect, t (22) = 20.06, p < . 001, d = 5.35. A significant difference was not observed pre- and post-intervention in positive affect for the mixed group, t(22) = −2.63, p =.015, d= -.77. 3.1.2. Negative affect A 2 (NA: pre- and post-PASAT-C) x2 (instruction: conditional, hierarchical, and mixed) mixed ANOVA was conducted to assess the effect of the different instructions on negative affect. A significant effect of time, F(1, 66) = 1103.29, p < .001, η² = .94, and group, F (2, 66) = 235.6, p < .001, η² = .88, was observed. A significant interaction between time and condition was observed, F(2, 66) = 485.32, p < .001, η² = .94, indicating that the different instructions had differing effects on levels of negative affect. As a significant interaction was observed a series of one-way ANOVAS were conducted to assess where the differences lie. A one-way between-subjects ANOVA revealed there was no significant difference in negative affect between the three groups preinstruction (See Table 2). A subsequent one-way between-subjects ANOVA revealed a significant difference between the groups postinstruction (See Table 2). Bonferroni corrected post-hoc analysis revealed that the hierarchy and mixed group differed from the conditional group (p < . 001), the mixed group did not significantly differ from the hierarchy group (p =. 036). Within-group analysis through within-subject t-tests revealed that both the hierarchy and conditional group observed a significant increase in negative affect post-instruction, with 37
Dysphoria Pre Post PANAS Negative Affect Pre Post PANAS Positive Affect Pre Post Anagram Pre Post
Measure
38
330.41 493.1
.1 505.92
1.79 41.59
2,66 2,66
2,66 2,66
.029 242.16
F
2,66 2,66
2,66 2,66
df
.17 < .001
.95 < .001
.21 < .001
.971 < .001
p
.05 .56
.003 .94
.05 .92
.001 .87
η²
22
22
22
22
df
1.07
20.06
.295
< .001
< .001
< .001
−26.91
−39.62
p
Conditional t
.27
5.35
−9.12
−7.62
Cohen’s d
22
22
22
22
df
−5.23
−17.21
−3.57
−9.55
Hierarchy t
< .001
< .001
.002
< .001
p
−1.48
−3.6
−1.05
−2.76
Cohen’s d
22
22
22
22
df
−19.77
−2.63
−10.52
−19.44
Mixed t
< .001
.015
< .001
< .001
p
−3.18
.77
−2.73
−5.07
Cohen’s d
Table 2 Between-Subjects ANOVAS to assess group differences at both pre and post-instruction and within-subject t-tests for all three conditions to assess pre and post differences within groups. Contains test statistic, degrees of freedom, p-value, and effect size for all tests.
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negative affect not significantly changing for the mixed group (See Table 2). 3.2. Dysphoria A 2 (Dysphoria: pre- and post-PASAT-C) x2 (instruction: conditional, hierarchical, and mixed) mixed ANOVA was conducted to assess the effect of the different instructions on total scores of dysphoria. A significant effect of time, F(1, 66) = 1109.48, p < .001, η² = .92, and group, F(2, 66) = 157.09, p < .001, η² = .83, was observed. A significant interaction between time and condition was observed, F(2, 66) = 186.62, p < .001, η² = .85, indicating that the different instructions had differing effects on levels of dysphoria. As a significant interaction was observed a series of one-way ANOVAS were conducted to assess where the differences lie. A one-way between-subjects ANOVA revealed there was no significant difference in dysphoria between all three groups (See Table 2) A subsequent one-way between-subjects ANOVA revealed a significant difference between the groups. Bonferroni corrected post-hoc analysis revealed that all groups significantly differed from each other (all p < .001). Within-group analysis through within-subject t-tests revealed that a significant increase in dysphoria was observed for all three groups postinstruction (See Table 2). 3.3. Anagram A 2 (Anagram: pre- and post-instruction) x2 (instruction: conditional, hierarchical, and mixed) mixed ANOVA was conducted to assess the effect of the different instructions on proficiency at solving anagrams. A significant effect of time, F(1, 66) = 107.8, p < .001, η² = .62, and group, F(2, 66) = 10.59, p < .001, η² = .24, was observed. A significant interaction between time and condition was observed, F(2, 66) = 48.97, p < .001, η² = .6, indicating that the different instructions had differing effects on proficiency at the anagram task. As a significant interaction was observed a series of one-way ANOVAS were conducted to assess where the differences lie. A one-way between-subjects ANOVA revealed there was no significant difference in anagram scores pre-instruction. A subsequent one-way between-subjects ANOVA revealed a significant difference between the three groups. Bonferroni corrected post-hoc analysis revealed that only the conditional and mixed groups differed, with the mixed group scoring higher post-instruction than the conditional group (p < . 001), the mixed group did not significantly differ from the hierarchy group (p =. 12) and the conditional group did not significantly differ from the hierarchical group (p =.04). Within-group analysis through within-subject t-tests revealed that both the hierarchy and mixed group observed a significant increase in scores postinstruction, with no significant difference observed in the conditional group (See Table 2). 3.4. Distress tolerance- PASAT-C quit time A one-way between-subjects ANOVA (IV: Instruction: conditional, hierarchy, and mixed. DV: PASAT-C quit times) revealed a significant difference in quit times between groups, F(2, 66) = 117.95, p < .001, η² = .78, between the conditional (M = 310.39, SD = 81.85), hierarchical (M = 540, SD = 66.2), and mixed (M = 581.35, SD = 37.15). Bonferroni corrected post-hoc analysis revealed that the conditional group differed from both the hierarchy and mixed groups (p < .001) indicating that the conditional group had significantly lower quit times than both the hierarchy and mixed groups. The hierarchy and mixed groups did not significantly differ in quit times (p =.1). 3.5. PASAT-C total scores A one-way between-subjects ANOVA (IV: Instruction: conditional, hierarchy, and mixed. DV: PASAT-C total scores) revealed a significant difference in total scores between groups, F(2, 66) = 105.04, p < .001, η² = .76, between the conditional (M = 56, SD = 16.49), hierarchical (M = 109, SD =14.87), and mixed (M = 121.87, SD = 17.54). Bonferroni corrected post-hoc analysis revealed that the conditional group differed from both the hierarchy and mixed groups (p < .001) indicating that the conditional group had significantly lower total scores than both the hierarchy and mixed groups. The hierarchy and mixed groups did not significantly differ in total scores (p = .029). 3.6. Self-Efficacy A one-way between-subjects ANOVA (IV: Instruction: conditional, hierarchy, and mixed. DV: self-esteem) revealed a significant difference in self-esteem between groups, F(2, 66) = 116.16, p < .001, η² = .59, between the conditional (M = 406.52, SD = 32.42), hierarchical (M = 566.09, SD = 47.55), and mixed (M = 559.56, SD = 39.14). Bonferroni corrected post-hoc analysis revealed that the conditional group differed from both the hierarchy and mixed groups (p < .001) indicating that the conditional group had significantly lower self-esteem scores than both the hierarchy and mixed groups. The hierarchy and mixed groups did not significantly differ in total scores (p = 1.00). 3.7. Willingness A one-way between-subjects ANOVA (IV: Instruction: conditional, hierarchy, and mixed. DV: willingness to do task again) 39
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revealed a significant difference in willingness to engage in the task again between groups, F(2, 66) = 149.82, p < .001, η² = .82, between the conditional (M = 70.96, SD = 8.19), hierarchical (M = 25.09, SD = 8.21), and mixed (M = 39.69, SD = 10.89). Bonferroni corrected post-hoc analysis revealed that all groups significantly differed from each other (all p < .001), with the hierarchy group revealing increased willingness to engage in the task again over the conditional and mixed groups and the mixed group showing an increase in willingness over the conditional group. 3.8. Comfort A one-way between-subjects ANOVA (IV: Instruction: conditional, hierarchy, and mixed. DV: comfort) revealed a significant difference in comfort in participating in the task between groups, F(2, 66) = 158.5, p < .001, η² = .79, between the conditional (M = 75.78, SD = 9.52), hierarchical (M = 30.65, SD = 5.45), and mixed (M = 41.87, SD =10.95). Bonferroni corrected post-hoc analysis revealed that all groups significantly differed from each other (all p < .001), with the hierarchy group revealing significantly increased comfort in doing the task over the conditional and mixed groups and the mixed group showing an increase in comfort over the conditional group. 3.9. Positivity A one-way between-subjects ANOVA (IV: Instruction: conditional, hierarchy, and mixed. DV: positivity) revealed a significant difference in positivity between groups, F(2, 66) = 50.34, p < .001, η² = .61, between the conditional (M = 33.69, SD = 10.19), hierarchical (M = 65.79, SD = 11.31), and mixed (M = 54.22, SD = 11.39). Bonferroni corrected post-hoc analysis revealed that all groups significantly differed from each other, with the hierarchy group revealing significantly increased positivity associated with the experience of the task over the conditional (p < .001) and mixed groups (p = .002). and the mixed group showing an increase in comfort over the conditional group (p < .01). 3.10. Self-perception of task performance A one-way between-subjects ANOVA (IV: Instruction: conditional, hierarchy, and mixed. DV: Self-perception of task performance) revealed a significant difference in self-perception of task performace between groups, F(2, 66) = 84.46, p < .001, η² = .72, between the conditional (M = 35.04, SD = 8.36), hierarchical (M = 62.17, SD =9.39), and mixed (M = 68.39, SD = 9.93). Bonferroni corrected post-hoc analysis revealed that the conditional group differed from both the hierarchy and mixed groups (p < .001) indicating that the conditional group had significantly lower ratings of how they felt they performed on the task than both the hierarchy and mixed groups. The hierarchy and mixed groups did not significantly differ in perception of task performance (p =.076). 3.11. Difficulty A one-way between-subjects ANOVA (IV: Instruction: conditional, hierarchy, and mixed. DV: Difficulty) revealed a significant difference in perception of task difficulty between groups, F(2, 66) = 89.37, p < .001, η² = .73, between the conditional (M = 30.35, SD = 8.84), hierarchical (M = 70.04, SD = 11.14), and mixed (M = 59.22, SD = 11.08). Bonferroni corrected post-hoc analysis revealed that all groups significantly differed from each other, with the hierarchy group revealing a significantly lower perception of task difficulty associated with the experience of the task over the conditional (p < .001) and mixed groups (p = .002). and the mixed group showing a lower in perception of task difficulty over the conditional group (p < .01). 4. Discussion The current study aimed to investigate how motivation based on hierarchical versus conditional versus mixed (hierarchical and conditional) framing impacted performance and psychological experiences in a distress tolerance task. The findings indicated that the hierarchical and mixed groups outperformed the conditional group on measures of task performance and of number psychological experiences, such as self-efficacy, comfortableness and willingness. This effect was transferred to performance on a different type of task (anagram). To our knowledge, this is the first RFT study to test the impact of different types of framing on motivation. The results we observed confirm the benefit of hierarchical and mixed hierarchical/conditional framing as suggested in a number of publications on applied contextual behavioral science (e.g. Dahl et al., 2009; Villatte, Villatte, & Hayes, 2015). The current study also extends a developing approach in RFT initiated by Luciano et al. (2011), consisting of comparing the effect of types of framing through natural language (i.e., using instructions in the language of the participants). We believe the method used in our study demonstrates a higher level of precision than in previous studies due to the fact that the targeted relations were specifically compared rather than comparing a larger textual instruction which included multiple relational frames, as in Luciano et al. (2011) and Foody, Barnes-Holmes, BarnesHolmes, and Luciano (2013) for example. That is, the different experimental conditions varied based only on one type of framing between the hierarchical and the conditional framing groups. In Luciano et al. (2011) and Foody et al. (2013) several types of framing were changed across conditions, making it difficult to draw unequivocal conclusions. More recent investigations have looked at the effects of deictic and hierarchical instructions on broadening participants sense of self and the impact of these relations on 40
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psychological flexibility (Gil-Luciano, Ruiz, Valdivia-Salas, & Suárez-Falcón, 2017) and cognitive performance (López-López and Luciano (2017). All of these studies used relatively long instructions that lack tight control over the different relations being emphasized across conditions. A recent study by Sierra, Ruiz, Flórez, Riaño-Hernández, and Luciano (2016) investigated the effects of brief instructions that only manipulated specific relational cues in a similar way to the current study. The relational cues were manipulated in order to change a metaphor that was instructing participants on how to cope in a pain tolerance analogue task (i.e., cold-pressor task). Participants received metaphors that included physical properties similar to the individual’s pain (e.g., ‘very cold’) in the metaphor content and specified appetitive augmental functions (e.g., to get ‘this thing you dream about’). The findings from Sierra et al. (2016) showed that both including physical properties and augmental functions had significant effects on the pain tolerance during the cold-pressor task. The current findings can also be considered in terms of Vrooms Expectancy Theory of motivation. According to Expectancy Theory individuals will choose how to behave depending on the outcomes they expect as a result of their behavior (Van Eerde & Thierry, 1996). Put simply, people decide what to do based on what they expect the outcome to be. In a work setting, a person may work overtime because they expect that it will result in a promotion. However, from this perspective the process by which we decide our behaviors is also influenced by how likely we perceive the rewards to be. Extending on the example, the person may be more likely to work harder if their boss told them that working overtime would lead to a promotion rather than if they perceived the outcome as less likely. Expectancy theory is based on three elements, expectancy, instrumentality (i.e., the belief that you will receive a reward if you meet performance expectations) and valence (i.e., the value you place on the reward.) Therefore, from the expectancy theory point of view people will be most motivated if they believe that they will receive a desired reward if they hit an achievable target. The current study involved providing the participants with rules where the mixed condition involved the highest level of expectancy, instrumentality and valence and also resulted in the best performance in terms of task performance and persistence. Motivation is often considered in terms of whether it is extrinsic, that is, originating from an outside demand, obligation, or reward that requires the achievement of a particular goal or intrinsic where the individual strives towards a goal for personal satisfaction or accomplishment. From an RFT point of view we look at whether the motivation is intrinsic. or extrinsic to the action. In this sense, hierarchical framing provides intrinsic reinforcement by simply engaging in the action because it is “part of” a process or a value. Participants in the hierarchical condition of the current study were seem to have benefited from this kind of intrinsic motivation, which is particularly helpful in the context of a task that is difficult to accomplish and fairly distressing. When examining the current results it can be seen that the condition that emphasized conditional relations alone was less effective than the condition that emphasized hierarchical relations. However, the condition with conditional associated with hierarchical relations was the most effective. This suggests that tracking outcome is effective as long as it is in the context of process focused motivation. This can be understood form an RFT perspective. That is, awareness of outcome (tracking requires awareness of consequences) and clarity of values (so that satisfaction is not expected only from these outcomes) are both important. This can also be understood in terms of the literature on intrinsic and extrinsic motivation. Specifically, the results from this perspective would indicate that extrinsic motivation can be effective if it is associated with intrinsic motivation. Interestingly, in the mixed condition, participants were instructed that what was most important was the process. In this sense it was not just mixed, a hierarchical relation between outcome and process was established. That is, participants were instructed that outcome is important but process is even more important. If the two instructions were pitched at the same level of importance it is likely that different results may have emerged. Some limitations to the current study should be noted. First, the use of the PASAT-C may limit the generalization of our findings to distress tolerance tasks. Indeed, the very purpose of distress tolerance tasks is to stay engaged in the task. Therefore, it is possible that motivation based on hierarchical framing (engaging in the task as part of a process rather than focusing on the outcome) is effective for these kinds of tasks, but not for others. The fact that performance increased on the anagram task in the hierarchical and mixed condition, but not in the conditional condition is perhaps an indication that hierarchical framing can have a better impact than conditional framing alone on other types of task than distress tolerance. However, at this stage, we can only conclude that the difference observed among the groups on the anagram task was caused by prior exposure to the PASAT-C task with different types of motivation. Future studies should replicate our experiment using the same instructions with another type of dependent measure, such as problem solving or reaction time tasks. Another limitation is related to the use of natural language to activate the different relations. While we created instructions as precisely as possible using words aimed to reflect hierarchical vs conditional framing vs mixed framing, it is possible that the participants interpreted these words in different ways. That is, some participants in the hierarchical condition may have derived motivation based on conditional framing and vice versa. Future studies should replicate our experiment using a manipulation check in this regard (e.g. by asking participants how they understood the instructions). Given our use of natural language (rather than cues established through training in controlled conditions) it is also necessary to replicate the current study with different instructions aimed to activate hierarchical vs conditional motivation, including in different languages than English. This will ensure that the effects we observed were not due to the particular words used in our instructions, but to the types of framing these instructions were meant to activate. Despite these limitations, the results we observed highlight the potential differing effects framing tasks conditionally, hierarchically or both hierarchically and conditionally can have on motivation and task performance. We believe our study constitutes an important contribution to the RFT analysis of middle level terms such as values and committed action in acceptance and commitment therapy (ACT, Hayes, Strosahl, & Wilson, 2011). While there have been debates about the relationship between middle level terms and RFT principles (Barnes-Holmes, Barnes-Holmes, Luciano, & McEnteggart, 2017; Hayes, Barnes-Holmes, & Wilson, 2012), the method used in our study shows that these two levels of analysis are not incompatible and can in fact inform each other in a 41
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reticulated fashion (Villatte et al., 2018). Indeed, we conducted the current study as a result of clinical observations and conceptual analyses. In turn, the results we observed can help refine the way practitioners use language to build meaningful motivation in applied settings. We believe a similar approach can be applied to other areas of applied psychology, such as interventions on self, compassion, or mindfulness. Acknowledgment The first author is funded by the Irish Research Council. References Barnes-Holmes, D., Barnes-Holmes, Y., Luciano, C., & McEnteggart, C. (2017). From the IRAP and REC model to a multi-dimensional multi-level framework for analyzing the dynamics of arbitrarily applicable relational responding. Journal of Contextual Behavioral Science, 6(4), 434–445. Brehm, J. W., & Self, E. A. (1989). The intensity of motivation. In M. R. Rozensweig, & L. W. Porter (Vol. Eds.), Annual, review of psychology: Vol. 40, (pp. 109–131). Brown, R. A., Lejuez, C. W., Kahler, C. W., & Strong, D. (2002). Distress tolerance and duration of past smoking cessation attempts. Journal of Abnormal Psychology, 111, 180–185. Catania, A. C. (1992). B. F. Skinner, organism. American Psychologist, 47(11), 1521–1530. Crawford, J. R., & Henry, J. D. (2004). The positive and negative affect schedule (PANAS): Construct validity, measurement properties and normative data in a large non-clinical sample. British Journal of Clinical Psychology, 43(3), 245–265. Dahl, J. C., Plumb, J. C., Stewart, I., & Lundgren, T. (2009). The art and science of valuing in psychotherapy: Helping clients discover, explore, and commit to valued action using acceptance and commitment therapy. Oakland, CA: New Harbinger Publications, Inc. Daughters, S. B., Lejuez, C. W., Strong, D. R., Brown, R. A., Breen, R. B., & Lesieur, H. R. (2005). The relationship among negative affect, distress tolerance, and length of gambling abstinence attempt. Journal of Gambling Studies, 21(4), 363–378. Daughters, S. B., Lejuez, C. W., Kahler, C., Strong, D., & Brown, R. (2005). Psychological distress tolerance and duration of most recent abstinence attempt among residential treatment seeking substance abusers. Psychology and Addictive Behavior, 19, 208–211. Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. New York, NY: Plenum. Fishbach, A., & Choi, J. (2012). Self-regulatory failure and intimate partner violence perpetration. Journal of Personality and Social Psychology, 97, 483–499. Foody, M., Barnes-Holmes, Y., Barnes-Holmes, D., & Luciano, C. (2013). An empirical investigation of hierarchical versus distinction relations in a self-based ACT exercise. International Journal of Psychology & Psychological Therapy, 13(3), 373–388. Gil-Luciano, B., Ruiz, F. J., Valdivia-Salas, S., & Suárez-Falcón, J. C. (2017). Effect of framing behavior through deictic/hierarchical relations and specifying augmental functions in promoting psychological flexibility. The Psychological Record, 67, 1–9. Gratz, K. L., Rosenthal, M. Z., Tull, M. T., Lejuez, C. W., & Gunderson, J. G. (2006). An experimental investigation of emotion dysregulation in borderline personality disorder. Journal of Abnormal Psychology, 115(4), 850–855. Hayes, S. C., Barnes-Holmes, D., & Roche, B. (Eds.). (2001). Relational frame theory: A post-Skinnerian account of human language and cognition. New York: Plenum Press. Hayes, S. C., Barnes-Holmes, D., & Wilson, K. G. (2012). Contextual Behavioral Science: Creating a science more adequate to the challenge of the human condition. Journal of Contextual Behavioral Science, 1, 1–16. Hayes, S. C., Strosahl, K. D., & Wilson, K. G. (2012). Acceptance and commitment therapy: The process and practice of mindful change (2nd ed.). New York: Guildford. Iwata, B. A., Smith, R. G., & Michael, J. (2000). Current research on the influence of establishing operations on behavior in applied settings. Journal of Applied Behavior Analysis, 33(4), 411–418. Ju, W. C., & Hayes, S. C. (2008). Verbal establishing stimuli: Testing the motivative effect of stimuli in a derived relation with consequences. The Psychological Record, 58(3), 339–363. Keller, F. S., & Schoenfeld, W. N. (1950). Principles of psychology: A systematic text in the science of behavior. New York: Appleton-Century, Crofts. Lejuez, C. W., Kahler, C. W., & Brown, R. A. (2003). A modified computer version of the Paced Auditory Serial Addition Task (PASAT) as a laboratory-based stressor. The Behavior Therapist, 26, 290–293. Locke, E. A., & Latham, G. P. (1990). A theory of goal setting and task performance. Upper Saddle River, NJ: Prentice Hall. López-López, J. C., & Luciano, C. (2017). An experimental analysis of defusion interactions based on deictic and hierarchical framings and their impact on cognitive performance. The Psychological Record, 1–13. Luciano, C., Ruiz, F. J., Vizcaíno-Torres, R., Sánchez, V., Gutiérrez-Martínez, O., & López-López, J. C. (2011). A relational frame analysis of defusion interactions in acceptance and commitment therapy. A preliminary and quasi-experimental study with at-risk adolescents. International Journal of Psychology and Psychological Therapy, 11, 165–182. Michael, J. (2000). Implications and refinements of the establishing operation concept. Journal of Applied Behavior Analysis, 33, 401–410. Plumb, J. C., Stewart, I., Dahl, J., & Lundgren, T. (2009). In search of meaning: Values in modern clinical behavior analysis. The Behavior Analyst, 32, 85–103. Sansone, C., & Harackiewicz, J. M. (1996). “I don’t feel like it”: The function of interest in self- regulation. In L. L. Martin, & A. Tesser (Eds.). Striving and feeling: Interactions among goals, affect, and self-regulation (pp. 203–228). Hillsdale, NJ: England Lawrence Erlbaum Associates, Inc. Scholz, U., Gutiérrez-Doña, B., Sud, S., & Schwarzer, R. (2002). Is general self-efficacy a universal construct? Psychometric findings from 25 countries. European Journal of Psychological Assessment, 18, 242–251. Schwarzer, R., & Jerusalem, M. (1995). Generalized self-efficacy scale. In J. Weinman, S. Wright, & M. Johnston (Eds.). Measures in health psychology: A user’s portfolio. Causal and control beliefs (pp. 35–37). Windsor, UK: NFER-NELSON. Shah, J. Y., & Kruglanski, A. W. (2000). Aspects of goal networks: Implications for self- regulation. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.). Handbook of selfregulation (pp. 85–110). San Diego, CA: Academic Press. Sierra, M. A., Ruiz, F. J., Flórez, C. L., Riaño-Hernández, D., & Luciano, C. (2016). The role of common physical properties and augmental functions in metaphor effect. International Journal of Psychology and Psychological Therapy, 16, 265–279. Van Eerde, W., & Thierry, H. (1996). Vroom’s expectancy models and work-related criteria: A meta-analysis. Journal of Applied Psychology, 81, 575–586. Villatte, M., Villatte, J. L., & Hayes, S. C. (2015). Mastering the clinical conversation: Language as intervention. New York: Guilford Press. Villatte, M., Villatte, J. L., & Hayes, S. C. (2018). A reticulated and progressive strategy for developing clinical applications of RFT. The Psychological Record, 68(March (1)), 113–117. https://link.springer.com/article/10.1007/s40732-017-0251-2. Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54, 1063–1070.
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