Validating the Cooper Quality of Imagery: A Measure of Vividness of Sporting Mental Imagery. Casey Laura Cooper

Transcription

1 Validating the Cooper Quality of Imagery: A Measure of Vividness of Sporting Mental Imagery by Casey Laura Cooper, M.A. A Dissertation Presented to the FACULTY OF THE GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIROFNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (COUNSELING PSYCHOLOGY) August 2004 Copyright 2004 Casey Laura Cooper

2 ACKNOWLEDGMENTS I would first like to thank Dr. Rodney Goodyear. Your support of me personally and professionally to enter the Ph.D. program and complete my subspecialty in Sport Psychology is something I will be eternally grateful for. So few scholars receive such unconditional encouragement. You and Karen are dear friends. I would also like to recognize Dr. John Callaghan, whose guidance and expertise in the field of Sport Psychology uniquely enhanced this instrument and my research of mental imagery. Seminars in your office were a great gift! Dr. Clark, you are a very special professor to our program. Your willingness to spend so much time on my pursuits was truly appreciated. Thank you for keeping me on my toes; this dissertation project is the better for it. I must also recognize the dedication of my family. My husband, you encouraged and challenged me, listened to me, and offered your love and support throughout this process. I love you. Mom, you committed your time in so many ways to seeing me through, proofreading, babysitting, vocal recordings. Only a mother would give so willingly. My Father, this is truly for you. If it weren t for you and Tommie and your dreams for me, who knows where I d be. My Brother and everyone else who donated their time to this dissertation, I love you all. A very special thank you to Coach Ron Allice whose amazing support of my career made this project possible. Also, Bryan walker whose amazing effort, dedication, and computer expertise made the CQI a reality! And to everyone else who supported this project, Coach Mark Blethen, Gynne, Teri Thank You. ii

3 TABLE OF CONTENTS Acknowledgements ii List of Tables List of Figures Abstract Chapter I (Introduction) 1 Defining Vividness of Mental Imagery Vision and Mental Imagery The Hardware of Vision The Software of Vision Memory and Mental Imagery Encoding Retrieving Summary Current Imagery Questionnaires Theoretical Support Criticisms of Current Measures Construct Validity Response Sets Imagery Scripts Methodological Problems in Sports Imagery Literature Summary Proposed Instrument Improvements Summary Chapter II (Method) Design of Validation Study The Cooper Quality of Imagery, Screen by Screen Vignettes Development Expert Review Peer Review Program Software Development Video Progressions Audio Clips iii

4 Server and Data Storage Psychophysical Scaling of the Video Progressions Method Participants Focus Group Discussion Outcome of Focus Group Procedure Recruitment Participants Chapter III (Results) Validation of Clarity and Color Scales VVIQ CQI Correlational Analysis Demographics The CQI and VVIQ Chapter IV (Discussion) VVIQ CQI Validation Other Findings Limitations Implications Future Directions Conclusion References Appendices A B C D E Transcribed Vignette Imagery Scripts Questionnaire Used For The Peer Review Of Imagery Vignettes Recruitment Letter General Instructions for Participants Consent Form iv

5 F G Instrument Instruction Screens Direct-Estimation Questionnaires v

6 LIST OF TABLES Table 1. Table 2. Table 3A. Table 3B. Table 3C. Table 3D. Table 4A. Table 4B. Table 5. Table 6A. Table 6B. A summary of mental imagery assessment tools commonly used with athletes. # Data from the peer review of imagery vignettes. Clarity 1 direct-estimation results and geometric mean. Clarity 2 direct-estimation results and geometric mean. Color 1 direct-estimation results and geometric mean. Color 2 direct-estimation results and geometric mean. Correlations between odd and even slides for the clarity scale. Correlations between odd and even slides for the color scale. Clarity and color scale ratings, adjusted psychological and physical values. Correlations between adjusted psychological and physical values for the clarity scale. Correlations between adjusted psychological and physical values for the color scale. vi

7 LIST OF FIGURES Figure 1. Numeric estimation data for Clarity slides. # vii

8 ABSTRACT VALIDATING THE COOPER QUALITY OF IMAGERY: A MEASURE OF VIVIDNESS OF SPORTING MENTAL IMAGERY While mental imagery is often a primary intervention used by psychologists and coaches to enhance athletic performance and training, research examining its effectiveness is hindered by the instruments currently available to measure this ability. There are several limitations commonly sited in mental imagery literature regarding the methodological flaws of assessment instruments such as the VVIQ and the VMIQ, the most commonly used tests in the sport psychology community. This study sought out to validate a new assessment tool for measuring the vividness of mental imagery of athletes. Major improvements include implementation of computer technology, magnitudinal scaling, and detailed imagery scripts. Development of the Cooper Quality of Imagery (CQI) included expert and peer review of imagery scripts, software development, direct-estimation to validate magnitudinal scaling of video, and a focus group review of the final instrument. * participants were recruited from collegiate Track & Field programs in Southern California. Demographics. viii

9 CHAPTER 1 INTRODUCTION Achieving and sustaining top athletic performance is rare. The financial, social, and personal rewards of becoming one of the world s best athletes are huge. Uncovering the formula to attaining athletic success is the goal of almost every athlete. At the very least, the essential factors to become a superior athlete are proper physique, commitment, talent, and specialized training. There are state-ofthe-art training facilities now available to many young and promising players who often are identified at an early age. Therefore, the differences in skill and abilities are becoming more and more minimal. Many athletes are turning to psychology to provide the necessary edge needed to become champions. Within the last two decades sport psychology has developed into a legitimate area of practice and inquiry. In 1986, the American Psychological Association (APA) created Division 47, Exercise and Sport Psychology. Increased interest has led to Division 47 s current petition sponsored by Division 47 to the Commission for the Recognition of Specialties in Professional Psychology (CRSPPP), requesting that sport psychology be designated an official proficiency. Sport psychology is the study of the effect of psychological factors on behavior in sport or the psychological effect that participation in sport or physical activity had on the performer (Silva & Weinberg, 1984, p. 6). Mental imagery is often a primary intervention used by psychologists and coaches to enhance athletic 1

10 performance. In fact, Murphy, Jowdy, and Durtschi (1989) reported that 90 percent of athletes, 94 percent of coaches, and 100 percent of sport psychologists in the United States identified mental imagery techniques as a standard fixture in their training regimens. One therefore would expect, given the usage of such a technique, that there would be a substantial amount of literature dedicated to the theory, implementation, and effect of imagery on athletic performance. Unfortunately, the existing research on mental imagery and its effect on sport performance is tainted by two serious methodological flaws; either the instruments used to detect difference in imagery ability are negligible or the assumption is made that all participants are equal in their mental imagery ability. To date, research to determine the impact of imagery on sporting performance has been seriously hampered by the very limited variance that the Vividness of Visual Imagery Questionnaire (VVIQ), Vividness of Movement Imagery Questionnaire (VMIQ), and other imagery instruments have been able to detect. This limited variance leaves research doomed from the beginning because the identified difference in imagery ability is so negligible that it cannot serve as a meaningful predictor of performance (Kihlstrom, Glisky, Peterson, Harvey, & Rose, 1991). The alternative approach to this dilemma is to assume equal imagery ability of the participants. However, that assumption is also problematic and produces results based on an improbable tenet. Equally concerning is the high level of criticism of the current measures used. In the Fall/Winter issue of 1995, the Journal of Mental Imagery commented on the vividness of mental imagery debate. The VVIQ was reviewed and many 2

11 researchers commented on the status of its continued usefulness. Katz (1995) went so far as to suggest, Rather than trying to save the test, we should go back to the drawing board and take the lessons learned from our use with the VVIQ to construct a better instrument of imagery vividness (p.144), and surmised that its continued use, despite years of critical review, is due to the VVIQ s quick administration and ease of scoring. Surprisingly, no new instruments have surfaced to answer this call. In order to improve the body of literature on this commonly used intervention, our assessment of mental imagery must be modernized so that research on the impact of mental imagery in sport training and performance has the possibility to reach consistent and methodologically sound conclusions. The purpose of this validation study is to develop a psychometrically sound, magnitudinally scaled instrument that utilizes technology to advance the assessment of mental imagery in the sport setting. To more fully appreciate the need for and development of the proposed instrument, a review of the how we produce mental images and a description of the development of previous measures of imagery is presented. Methodological concerns with currently available mental imagery instruments will be offered. Also, a thorough discussion of the proposed instrument s importance, purpose, and rational will follow. Defining Vividness of Mental Imagery Mental imagery refers to an individual s ability to represent in the mind experiences that are not physically there (Matlin, 1989). Sports imagery, a specific type of mental imagery, is the rehearsal of physical actions without deliberate 3

12 muscular activity (Gilmore, 1973). Denis (1985) expanded this explanation to, any psychological activity, which evokes the physical characteristics of an absent object (p. 4). This absent object may be either temporarily or permanently undetectable. A more simplified definition of sports imagery is suggested by Singer (1980) who contends that mental imagery and imagery rehearsal are essentially the same concept, task rehearsal in which there are no observable movements (p. 426). Suinn (1996) incorporates relaxation training prior to visualization exercises. Athletes utilize imagery to learn new tasks, enhance a skill that has already been physically practiced or taught, rehearse a performance, strategize for competition, narrow focus, maintain attention, minimize anxiety, and evaluate technique and performance (Onestak, 1991; Suinn, 1996). Regardless of its use, the vividness of a mental image is multidimensional and includes many sensory experiences such as sounds, muscles, and other visceral feelings in addition to what is seen in the mind s eye (Ahsen, 1995). This definition of vividness is contradictory to the unidimensional, stable ability approach that is used by the VVIQ and VMIQ, two of the more commonly used mental imagery assessment tools. Debate over the past 2 decades has encouraged a fresh look at the vividness construct to inspire a revised assessment of mental imagery. The Fall/Winter 1995 issue of the Journal of Mental Imagery was dedicated to this debate and focused on redefining vividness of mental imagery and the continued use of the VVIQ. The featured article by McKelvie, The VVIQ as a Psychometric Test of Individual Differences in Visual Imagery Vividness: A Critical Quantitative Review 4

13 and Plea for Direction (1995) is considered the most thorough review of the VVIQ to date and spurred considerable comment for the issue. McKelvie (1995) noted that Marks, the creator of the VVIQ, defined vividness of mental imagery as an ability, which implies its stability as a trait. This definition is no longer accepted as valid within current literature. McKelvie (1995) argues in his review that perception is not a fixed stimulus-driven automatic process, but a joint function of sensory input and interpretation by higher-order factors such as stored knowledge (p.36). Kaufmann, as cited in McKelvie (1995), calls for an assessment of vividness that extends beyond a simple representation and incorporates imagery as a sensuous experience. Ahsen (1995) also agrees that other senses commingle with the visual cue (p.114). Redefining vividness of mental imagery as multidimensional and multisensory allows assessment to change from measuring ability of memory recall to an experience that incorporates both memory and imagination. Kunzendorf (1995) encourages this shift of viewing a mental image as an internal construction that is different from an actual experience. By acknowledging this interplay of external history and internal perception, mental imagery becomes a different construction that is no longer related to accuracy, but instead focuses on intensity of sensory experience during the mental imagery exercise. In developing this assessment tool, the following definition will be used for mental imagery in the context of sport: The ability to symbolically rehearse a physical activity or experience in the mind that which is not physically there and is 5

14 absent of overt muscular movements (Moran, 1991; Onestak, 1991). The mental image will be assessed in terms of its vividness. Vividness of mental imagery is defined by this researcher as: Generating from memory and/or imagination an internal experience that is rich in visual color and clarity, audition, and physical sensation in response to verbal instruction (Ahsen, 1995; Campos, 1995; Kunzendorf, 1995; McKelvie, 1995). Vision and Mental Imagery To represent in the mind experiences that are not physically there suggests that mental imagery is based on our perceptions of past experiences that have occurred in the physical world. To assess the vividness of such experiences in the non-physical world of imagery, it is critical to review the mechanics, or hardware, of vision to understand how we observationally take in events. The perceiving, or software, of vision allows us to make sense of and utilize these optical messages. The Hardware of Vision The idea of visual hardware (Williams, Davids, & Williams, 1999) refers to the physical structures involved in the act of detecting data in the visual field. The eyes are the primary organs of this hardware system. Their function is to detect the light reflected by objects in order to communicate with the visual centers of the cortex to determine what was seen and makes sense of what needs to be done in response (Lester, 2000). Located in the front center of the eye, the cornea s role is to reduce the speed of light and bend the light towards the retina to focus the image (Lester, 6

15 2000). The lens directly behind the cornea fine-tunes the focus. The curved surfaces of the cornea and lens make this focus possible. As light continues to pass through the eye, it will reach the retina. The retina is the most critical tool of the eyes in translating impulses to nerve signals as light passes through five different layers of cells (Williams, Davids, & Williams, 1999). Composed of light sensitive cells, the retina creates an inverted image of the outside world. Within the retina, the rod receptors detect light and motion while the cone receptors are responsible for identifying color. Maximal resolution occurs in the small region of the fovea where there is a very high quantity of receptors (Lester, 2000). Therefore, objects will be seen most clearly when they are within a line of sight that lies within the fovea s range. The Software of Vision The mechanics of sight seem quite logical. The same technology is used in cameras, binoculars, etc. However, our brain s ability to make sense of this data beyond variations in light and darkness is what creates meaning. The information highway between the retina and the primary visual cortex (V1) appears to hold the key to unlocking this complex system of software (Williams, Davids, & Williams, 1999). Neural signals detected by the retina are transmitted to the lateral geniculate nuclei (LGN) located in the thalamus to the V1 where a copy of the image is created. The image constructed in the V1 is not assigned meaning, but it is the center where identification occurs (Lester, 2000). 7

16 Of particular importance to the vision of athletes, the suggestion of two visual streams of processing information has stimulated new theory and investigation on the perception of visual images. Milner and Goodale (1995) suggest that beginning in the retina, information is divided between a dorsal and ventral stream. These pathways are not believed to function entirely independently. However, beyond the V1, the ventral stream continues to the posterior parietal cortex, the center for object recognition, whereas the dorsal stream is sent to the infero temporal cortex where action is determined. In short, the ventral stream determines what the object is, and the dorsal stream decides what to do with the object (Williams, Daivds, & Williams, 1999). A review of several types of visual abilities including static visual acuity (clarity), dynamic visual acuity (motion between person and scene), and peripheral vision (field of view) concluded that an increase in ability did not correspond with increased athletic performance (Williams, Davids, & Williams, 1999). The authors suggest that superior hardware should not be the focus of training. Instead, the software of sight is what is transformed during practice, becoming more efficient with time and translating into better sporting performance. Memory and Mental Imagery The creation of a mental image is based on what we have seen and experienced in the external world. The mechanics of vision and the act of perception allow us to interpret these images. The next step to understanding the elements that create quality imagery is to explore our ability to store and retrieve relevant images. 8

17 When a mental image is stimulated, we pull from our mind images, feelings, sounds, and smells that correspond with the suggestion. The images recalled are connected to sensory awareness depending on the time they were perceived, utilized, and stored in long-term memory. For example, when a song triggers a memory from a High School dance, the images that begin to flood one s mind are coupled with that specific melody. Therefore, the context of the image helps to create the meaningfulness of the experience as a whole. All of this comes together when a vivid mental image is formed. Encoding Once an image has been detected and perceived, it is compared with past images in the hippocampus (Lester, 2000). If the current image is deemed important or remarkable, it is stored for later use. The storage of images begins with comparison, or pattern recognition. Pattern recognition takes many variables into account in order to make an accurate assessment of an image s meaning (Bruning, Schraw, & Ronning, 1999). This recognition includes the qualities of the image, our body of knowledge pertaining to the image, and the contextual factors present during its detection. Templates represent objects that have been previously stored in memory. If a new image matches the properties of a known template, then it is recognized. However, if there is too much discrepancy between the template and the image, the brain will utilize stored prototypes. A prototype is the essence or set of basic elements of an object (Bruning, Schraw, & Ronning, 1999). The next level in 9

18 memory structures is a schema, which relates perceived information to a preexisting structure, guiding additional information gathering. Schemata provide a framework to organize data. As all of the contextual cues are processed, we are better able to detect other relevant information from the environment based on our expectations (Bruning, Schraw, & Ronning, 1999). As exposure to stimuli increase, our processing speed also increases because the demand on our brain s resources is reduced. Therefore, the more often athletes are exposed to the elements of their sport, the more quickly they will be able to recognize the situation at hand. Their schemata are more advanced due to practice; efficiency becomes a priority as the processes are automated (Bruning, Schraw, & Ronning, 1999). Contextual cues are more integrated into their framework due to the number of times they have been detected, recognized, and stored. The more familiar a person is with a task, the fewer nuances will be needed to be identified for the first time, resulting in fewer attentional demands on the performer. Retrieving The ability to develop a mental image is contingent upon one s memories and their recollection. Working memory enables the current processing of information, or the current contents of consciousness (Bruning, Schraw, & Ronning, 1999). There are three parts to working memory. The executive control system governs what enters our consciousness and organizes the information. The articulatory loop allows for the rehearsal of auditory information. Most important to mental imagery, the visual-spatial sketchpad makes possible the manipulation of objects and other 10

19 visual data. During an imagery exercise, stored images are pulled from long-term memory into the visual-spatial sketchpad for further manipulation and processing (Bruning, Schraw, & Ronning, 1999). Interaction with current information also occurs as the imagery script or prompt influences the remembrance. The dual coding theory (Paivio, 1985) explains that when information is stored in both the verbal and nonverbal systems, memory will be improved. Since concrete words are immediately matched with an internal image, the result is greater memory recall. This is the difference in imaging the word cat versus something more intangible, progress. Much research (Williams, Davids, &Williams, 1999) suggests that subjects recall ability of pictures is superior to words. This visual recall ability has been evidenced in both short-term and long-term memory trials. Delays in recall occurred only when responses were requested in verbal form. Paivio (1985) contends that since imagery rehearsal is based on the memories of past performances, the result is only as accurate as the performer s skill level. More specific to the quality of the images created, Paivio (1985) suggests, language provides the retrieval cues for memories expressed as images (p. 27). Thus, the instructions for the imagery requested must be precise enough to trigger recall, and the performer must have a significant memory base from which to retrieve the image. Summary Mental imagery relies on the strength and automaticity of a memory framework and the capacity of the working memory systems. The quality of the 11

20 mental image is contingent upon this complex series of steps. The detection of light in the visual field is translated into neural signals that are sent to the primary visual cortex for perception. From there, comparisons with stored memories in the hippocampus result in the development and refinement of schemata, creating a meaningful context of the stimuli originally identified. Stored memories can be further enhanced and manipulated within working memory. The vividness of a mental image cannot be assessed without recognizing the role of our vision, perception, storage, and retrieval of the images we are hoping to stimulate in the minds of athletes. Current Imagery Questionnaires Instruments measuring imagery ability originated with Galton s breakfast table questionnaire in Later, Betts 1909 Questionnaire upon Mental Imagery (QMI) paved the way for current self-report measures. Originally 150 questions, the Betts QMI evaluated individual differences on seven sensory modalities: visual, auditory, tactile, kinesthetic, gustatory, olfactory, and organic (White, Sheehan & Ashton, 1977). Sheehan (1967) shortened the Betts QMI to 35 items, and it is the more commonly used form. The QMI utilizes a 7-point Likert scale that ranges from Perfectly clear and as vivid as the actual experience to No image present at all, only knowing that you are thinking of the object. The QMI is a measure of imagery vividness and has a high internal consistency value of.95 (Juhasz, 1972) and a seven-month test-retest reliability of.78 (Sheehan, 1967). 12

21 The QMI contributed greatly to the development of Marks (1973) Vividness of Visual Imagery Questionnaire (VVIQ) and (Isaac, Marks & Russell, 1986) Vividness of Movement Imagery Questionnaire (VMIQ), two of the most widely used inventories for sports related imagery. The VVIQ consists of sixteen items that are an extension of the QMI s visual subscale. Marks (1973) also based his 5-point Likert scale on the QMI, utilizing the same end points. The choices of the 5-point scale are: 1) Perfectly clear and as vivid as the actual experience, 2) Clear and reasonably vivid, 3) Moderately clear and vivid, 4) Vague and dim, and 5) No image present at all, only knowing that you are thinking of the object. Subjects taking the VVIQ are asked to image the item requested (a friend or relative, rising sun, familiar shop, country scene) with their eyes open and then with their eyes shut. The prompts to stimulate the image are very short and no more descriptive than the examples cited. It is not clear why participants are required to visualize under both conditions. No theoretical explanation has been provided, and testing of the instrument has not yielded scores that are significantly different (White, Sheehan, & Ashton, 1977). There are 16 items rated from 1-5. The overall score is the mean of the 16 ratings. The reliability reported for the VVIQ has ranged from.67 to.87 (McKelvie, 1990). Isaac, Marks, and Russell (1986) believed that a movement-related imagery assessment tool was needed. The VMIQ was created to fill that need to assess vividness of movement imagery. The same 5-point scale from the VVIQ is used in the VMIQ for 24 items. Similarly to the VVIQ, the VMIQ asks participants to imagine the cues under two different conditions, as though you are watching 13

22 someone else and doing it yourself. However, in the VMIQ you are instructed to keep your eyes closed during the visualizations. The movement prompts are categorized into six groups: 1) Basic body movements, 2) Basic movements with more precision, 3) Movement with control but some unplanned risk, 4) Movement controlling an object, 5) Movements which cause imbalance and recover, and 6) Movements demanding control in aerial situations (Isaac, Marks, & Russell, 1986). Given its roots, the VMIQ exhibits high convergent validity with the VVIQ (.81). Its test-retest reliability is also consistent with its predecessor at.76 (Isaac, Marks, & Russell, 1986). Unfortunately, like the VVIQ, the prompts meant to stimulate the movement imagery are insufficient, oftentimes consisting of a single word (standing, walking, running, etc.). The rationale to support imaging under different conditions is also lacking, and it is unclear why this line of thinking was continued in the VMIQ. Self-report questionnaires have employed two main approaches to assess imagery ability. One approach was to measure the vividness, or the sensory richness (Richardson, 1988) of an image. This is evident in the Questionnaire upon Mental Imagery, Betts QMI, VVIQ, and the VMIQ. The other approach has been to focus on a person s control over his or her imagery experience: his or her ability to change and direct imagery (Kosslyn, 1990). This ability is most often assessed using Gordon s (1949) Test of Visual Imagery Control (TVIC). The TVIC consists of 12 items and was originally a dichotomous scale. It was later revised by Richardson (1969) to include unsure among the choices. Now, the TVIC employs a 5-point 14

23 scale with the same end points of yes and no. During the assessment, participants are asked to image an automobile and manipulate its position and movements (stopped, turned over, climbing a hill). The reported test-retest reliability is.84 (McKelvie & Gingras, 1974). The TVIC has been criticized for its brevity and its high correlation to the QMI,.47 (Moran, 1991) and VVIQ,.45 (Kihlstrom et al., 1991). This criticism is very troubling because the TVIC is a test of imagery controllability, whereas the QMI and VVIQ are vividness assessments. These findings of convergent validity have supported arguments that controllability and vividness instruments are essentially measuring the same factor and are not distinguishably different dimensions (Ernest, 1977; Kihlstrom et al., 1991; Moran, 1991; White, Sheehan, & Ashton, 1977). The Imagery Use Questionnaire (IUQ) was first introduced by Hall, Rodgers, and Barr (1990) and has gone through several revisions. Even though it does not tap into ability, the IUQ is noteworthy due to its imagery use assessment properties and to its use in conjunction with the QMI, VVIQ, VMIQ, and TVIC. Also, the authors utilized Paivio s (1985) framework motivation/cognitive and specific/general to guide their assessment of imagery use by athletes. The IUQ is also the only instrument designed specifically for use with an athletic population to assess any aspect of imagery. The IUQ can also be adjusted to fit a particular sport and varies in its number of questions. The questionnaire employs a 7-point Likert scale ranging from never to always and very difficult to very easy. Questions target 15

24 areas of when, where, and how an athlete utilizes imagery. The IUQ can be a helpful guide to acquiring pertinent demographic and sport specific information. Table 1. A summary of mental imagery assessment tools commonly used with athletes. Scale Author/Year Purpose Scale Items Reliability Questionnaire on Mental Imagery SQMI Vividness 7 Point Gordon Test of Imagery Control GTIC Vividness of Visual Imagery Questionnaire VVIQ Vividness of Movement Imagery Questionnaire VMIQ Imagery Use Questionnaire IUQ Betts 1909 Sheehan 1967 Gordon 1949 Richardson 1969 Marks 1973 Isaac, Mark, & Russell 1986 Hall, Rodgers, & Barr 1990 Controllability Yes/No 5 Point Internal Consistency.95 Test-Retest Split Half.76 Test-Retest.84 Correlation to QMI.47*** Vividness 5 Point 16 Test-Retest Range Between Vividness 5 Point 24 Test-Retest.76 Convergent Validity with VVIQ.81 Use by Athletes 7 Point 37 16

25 Theoretical Support Imagery instruments have been criticized for their lack of theoretical support. Two competing theories discussed in mental practice literature are the symbolic learning theory and the psycho neuromuscular theory. The symbolic learning theory suggests that imagery improves performance by providing a blueprint of sorts for athletes to pattern their movements into symbolic components, thereby improving the cognitive component of motor activity (Savoyant, 1988). The psychoneuromuscular theory contends that imagery of motor tasks results in a minute innervation in the muscles that will later be activated during the deliberate performance of the same task (Hale, 1982). Feltz and Landers (1983) performed a meta-analysis of 60 studies. They found an overall effect size of.48 for mental practice, which was superior to no practice. The authors also found a larger effect size (1.44) for tasks designated to be cognitive than for basic motor (.43) or strength (.20). They concluded that mental practice enhances performance by enabling the athlete to better focus attention. This conclusion has been interpreted to support the symbolic learning theory. However, Savoyant (1988) has suggested that these competing theories should be linked rather than separated. Savoyant (1988) suggests that performance of a task has both a cognitive and motor component, such as planning to throw a baseball (i.e. which grip to use, where to throw, route of the throw, etc.) and the execution of the throw (i.e. holding the baseball, rotation of the arm, extension and 17

26 release, etc.). To label sporting tasks as solely cognitive or motor becomes nearly impossible and is not productive. Paivio s (1985) analytic framework for imagery effects is consistent with this idea of integration. He suggests that imagery intended to improve human performance has both a motivational and cognitive role that operates on a general or specific level. Motivational imagery is connected with emotive arousal at the general level and goal-related activities at the specific level. Cognitive imagery that is general corresponds to strategizing for success, and specific cognitive imagery relates to skill acquisition and mastery. Cognitive specific imagery focuses on skill development and execution for sport participation. Proper form and execution are listed as important elements during the imagery exercise. Cognitive general imagery focuses on strategy development and execution. An athlete would use this form of imagery to prepare for a competition to help ensure a winning outcome. Motivational specific imagery is related to a positive performance outcome. The critical element to this imagery is visualizing the winning moment. Motivational general arousal imagery centers on emotive arousal, relaxation, and control. Athletes image the emotions of competition and see themselves controlling their physical and emotional responses. Motivational general mastery images are about focus, confidence, and positive self-talk. These images are centered on maintaining attention often in the face of distractions that may or may not be a part of their sport s competition (Munroe, Giacobbi, Hall, & Weinberg, 2000). 18

27 There is research to support the framework suggested by Paivio. Salmon and Hall (1994) and Munroe, Giacobbi, Hall, and Weinberg (2000) found factorial support for Paivio s framework through use of the IUQ and qualitative interviews with different athletic groups. When asked about their imagery, athletes responses consistently supported the breakdown of cognitive and motivational on a general and specific level. Criticisms of Current Measures Unfortunately, all of the imagery instruments previously reviewed have been criticized for their lack of construct validity, susceptibility to response sets and social desirability, a lack of divergent validity, an absence of current norms for interpretation, inadequate scripts to prompt vivid images, and a need for the standardization of scales There have been several reviews of imagery questionnaires (Hall, 1985; Hiscock, 1978; Kihlstrom et al., 1991; McKelvie, 1995; Moran, 1991; Murphy, 1990; White, Sheehan, & Ashton, 1977). The problems identified by these authors are considerable. Construct Validity Self-report imagery instruments face many challenges. The most significant difficulty is the professional community s concern regarding their construct validity, their ability to accurately measure what these questionnaires claim to measure. Like many psychological constructs, mental imagery is an internal, individual experience that is not directly observable by researchers (Reisberg & Heuer, 1988). Bringing out a person s subjective and private event into the external realm for a shared 19

28 examination has always proven challenging. In the case of mental imagery assessment, Hiscock (1978) concluded that, It is not clear what imagery questionnaires really measure or what criteria are appropriate for validating them (p. 223). Since there is nothing tangible to compare one s ideas or findings, research has looked to other means to try and prove validity of these elusive constructs. Analysis of reliability and various forms of validity allow researchers to demonstrate that they are accurately measuring their construct (Reisberg & Heuer, 1988). Reliability refers to the stability of scores over time, whereas validity is the degree to which the construct accurately measures what it is designed to measure. The imagery measures reviewed have demonstrated sufficient reliability (see Table 1). However, reliability does not guarantee validity (Moran, 1991). Predictive validity, using results to predict a range of observable effects, is one form of validity that has been used to validate quality of imagery tests. Attempts to predict performance on spatial ability, mental rotation, image scanning, and memory tasks using imagery ability scores have been made, but without consistent results (Hiscock, 1978; Reisberg & Heuer, 1988). Hall (1985) argued that such correlations incorrectly assume that mental imagery is a central ingredient to solving spatial tasks. Another way to demonstrate construct validity is to compare a new instrument to already accepted tests of the same (convergent validity) or dissimilar (divergent validity) constructs. This strategy has been employed to validate the 20

29 GTIC. Since the QMI and GTIC measure different constructs, imagery vividness and controllability, it was expected that there would be a negative correlation. This result would show that they are indeed measuring different constructs. However, this has not been the case. Positive correlations as high as.47 and a shared variance of 22% have been reported between the QMI and GTIC (McKelvie & Gingras, 1974). The GTIC also correlates significantly with the VVIQ at.45 (Kihlstrom et al., 1991). This similarity suggests that the concepts of vividness (QMI and VVIQ) and controllability (GTIC) are based on the same general factor and are not tapping into different constructs (White, Sheehan, & Ashton, 1977). The more commonly used vividness instruments in sports, the VVIQ and the VMIQ, have demonstrated a convergent validity of.81, (Isaac, Marks, & Russell, 1986), which is expected given their equivalent designs and methodology. The VVIQ also correlates positively with the QMI, most likely because it is based on a subscale of the QMI, with four of the sixteen questions being identical (Kihlstrom et al., 1991). A major concern with the VVIQ and VMIQ s ability to accurately measure vividness of imagery is their implication of a uniformity of vividness (Reisberg & Heuer, 1988). These tests do not have the ability to assess vividness on multiple dimensions, such as clarity and color. The image is assessed as a whole without any consideration of variation in experience or differing abilities within the same image. This may explain the minimal range that the VVIQ and VMIQ are able to detect because of this all-or-nothing mentality. Although the tests use a 5-point scale, Kihlstrom et al. (1991) found that only 3% of their sample (730 college 21

30 students) reported having vague or dim images or no imagery at all. Those ratings (Vague or dim, No imagery at all) account for two of the five categories. McKelvie (1995) identified an overall mean score of with an overall standard deviation of.692 in his review of 38 research studies utilizing the VVIQ. The researchers concluded that, few subjects lack the ability to produce the images requested by these questionnaires (Kihlstrom et al., 1991, p. 139) and that the VVIQ should be considered an easy test. It appears that the VVIQ and the VMIQ do measure vividness, but not in a very meaningful way due to the small range in scores. Adding to the problem of ascertaining meaning from the scores provided by the VVIQ and other imagery assessment tools is a lack of standardization (Moran, 1991). In fact, Ostrow (1990) reported that only 20% of the tests published in a directory of sport psychology instruments had undergone a validation study! This lack of attention to proper scientific method can also be seen in the absence of contemporary norms to provide a meaningful interpretation of imagery scores (Kihlstrom et al., 1991). Response Sets There are two types of response sets by which imagery questionnaires have been influenced: social desirability and acquiescence. Like all self-report measures, the potential for participants to rank themselves higher than is accurate is an expected limitation. However, in the sporting community it may be even more critical to consider the expectations, setting, or persons who will be reviewing 22

31 scores when determining if a subject has varied their performance (White, Sheehan, & Ashton, 1977). For some athletes, there is a considerable amount at stake when exposing themselves to a battery of tests that may be interpreted for coaches, managers, or agents. Imagery testing is not an uncommon practice when recruiting players for collegiate or professional level sport organizations. Given the simple nature of the imagery questionnaires that are often used, it would not be difficult for participants to rank themselves as having a vivid imagination (Moran, 1991), which is known throughout the sport community as a desirable asset. Acquiescence, the propensity to apply the same ranking to each item on a scale without regard for its substance (Moran, 1991), is another concern when utilizing current imagery questionnaires. It is common practice to employ reverse scoring in an attempt to control for such contamination. Unfortunately, this procedure has not been utilized in the QMI, VVIQ, or VMIQ. The VVIQ s susceptibility to response sets has been noted for decades. Hiscock (1978) noted his concern with the VVIQ s rating of images using a numerical scale on which one pole always represents good imagery (p. 224). In addition to being an easy test that may be particularly vulnerable to the desire to score as high as possible, the QMI, VVIQ, and the VMIQ are plagued by an inconsistency of subject s ratings (Moran, 1991). This inconsistency is because there is no way of knowing whether or not Ss are applying the same standard in making their ratings (Anderson, 1981, p.157). I find it very difficult to distinguish perfectly clear and vivid from clear and reasonably vivid from moderately 23

32 clear from vague and dim. Examples to aid subjects in differentiating between the ratings on these scales are not provided. It would be difficult to assign these values to tangible images, let alone an internal imagery experience that is being remembered or recalled as the subject is making his or her assessment. It is possible that this confusion is contributing to a participant s acquiescence. This confusion would also explain why there is such a limited range detected even when the VVIQ or VMIQ is administered to large groups. Researchers are unable to distinguish adequate variability because the scale to express the total range is convoluted and unclear at best. Imagery Scripts The imagery script, instructions written for the participant in order to stimulate the imagery intended, in all questionnaires to date are appallingly brief (Murphy, 1990, p. 161). At times, one word is used to stimulate an image. This simplicity is a crucial error because our understanding of memory and retrieval which create images suggest that these instructions must contain sufficient detail to ensure that all subjects are imaging the task in the same manner (Paivio, 1985, p.20). To assume that all participants will be able to stimulate an image based on such minimal promptings is amazing because these measures are supposed to be able to detect a wide range of ability. Lack of details leaves low-level imagers to fill in an abundance of gaps if they are to stimulate a quality image. Also, how is the measure expected to detect any significant level of variation when the task is so simple? Without adding any complexity to the script, it is more likely that subjects 24

33 will feel they are high-level imagers. For example, the script running might stimulate a shadow figure with legs and arms in action as if they are running, but without movement, color, interaction with the ground, and sound for a low-level imager. But when asked how vivid their imagery was, the imagers may feel very successful about their shadow figure and rate themselves somewhere towards the middle of the scale. The same script could also stimulate a much more complex image that includes the elements of setting, movement, sound, and texture for a highlevel imager. When asked to rate their level of vividness they may be likely to lower their rating because they saw room for improvement in their imagery. Script instructions that are too brief create a very real and troubling problem. Paivio (1985) states, The goal is to find ways of augmenting the richness and accuracy of the memory base for imagery and maximizing the efficiency with which the relevant information can be retrieved (p. 26). When we add detail and multiple senses to running, a more complex script emerges. What if instead of asking a participant to image running, we provided the following script? Imagine a person running. See their body moving in rhythm, their arms and legs driving them forward. See the expression on their face. Are they pushing themselves to their limit or staying in their comfort zone? Hear them breathing. Are they gasping for air or perhaps their breath is in rhythm with their body. Now when the participants are asked to rate their vividness of the image, they have more information upon which to base their assessment. They will be able to better understand the qualities of a vivid image. A high-level imager may already be filling in the dimensions requested above, but it is very possible that a 25

34 low-level imager may have no idea how complex mental imagery can become until he or she is given a more in-depth script. In addition to providing the foundation for a quality mental image, scripts provide the retrieval cues for stored experiences that will be incorporated into imagery (Paivio, 1985). What happens when the athlete plays pool and does not run on a regular or casual basis? How does the script running spark a vivid image for him or her? By providing additional cues regarding the act of running, the pool player will be better able to piece together a series of memories that match the request of the script and result in a more vivid image. A quality of imagery assessment tool must provide an equal footing for all participants. Brief scripts create an imbalanced playing field before the imagery has occurred. Inadequate scripts are also aligned with a prior mentality of measuring vividness through memory recall ability. This outlook is not continued in the new instrument and required a rethinking of how imagery scripts are determined by the construct of imagery vividness. By redefining vividness of mental imagery as multisensory and a combination of memory and imagination, it became imperative to encourage participants to allow their minds to wander. More elaborate and detailed stories were necessary to encourage this type of experience. 26

35 Summary Overall, the problems with current imagery questionnaires are that their prompts are too simple and their ratings are quite confusing. In an attempt to demonstrate validity, predictive studies have been plagued with inconsistency. It is highly probable that the measures inability to detect enough variance has made it statistically impossible for meaningful predictions to be made with statistically significant success (Kihlstrom, et al., 1991). Controllability measures have also lost credibility due to their inappropriate correlations with vividness instruments. Although they demonstrate high reliability and convergent validity, the VVIQ and VMIQ have been deemed easy tests. They are easy in both their assumption about the imagery experience as a whole without dimensions and in their lack of statistical variance. Another major limitation is the likelihood for response sets because athletes may have considerable incentives to perform well on imagery assessments, or are unaware of what truly high-quality imagery looks like. Without employing reverse scoring, a more straightforward means of rating the imagery experience, or without writing scripts that are realistic and complex, such contamination will continue. Methodological Problems in Sports Imagery Literature Most research on the impact of imagery on performance has utilized a before and after approach to compare performances of athletes who have trained 27

36 with mental rehearsal, physical practice, mental rehearsal and physical practice, and no practice (Murphy, 1990). These studies have primarily examined differences between novice and elite athletes, gross motor and finite motor tasks, and internal and external imagery perspectives. The findings have been inconsistent. This inconsistency is quite possibly related to the limited variance or imagery scores obtained by the instruments utilized because scores can no longer act as meaningful predictors of performance (Kihlstrom, et al., 1991). Some authors contend that mental imagery practice is superior when compared to no practice (Feltz & Landers, 1983). Others have found a significant difference in performance of varying tasks when mental and physical practice is compared to physical practice alone (Onestak, 1991). Unfortunately, the overwhelming majority of researchers have assumed that the ability of their subjects to perform the required imagery tasks was equal. This concern has been expressed repeatedly. Sport psychology researchers have also been comparatively neglectful of individual differences in imagery ability and styles in their assessment efforts (Murphy, 1990, p. 163). Hall (1985) discusses a typical example that describes this particular problem in sports imagery research. When subjects are requested to image a motor skill in an experiment, generally there has been little concern with how subjects might differ in their ability to comply with this request. Yet there are individual differences in imagery and these differences may influence the results (p. 18). These assumptions regarding imagery ability have created a major methodological flaw that permeates the body of sport psychology research. What happens if the 28