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The vividness of visual imagery questionnaire as predictor of facial recognition memory performance.

As part of the effort to include individual differences in the study of cognitive processes, various measures of imagery skill have been developed. The fall into two categories, identified by whether the assessment reflects a person's 'subjective' self-report or 'objective' overt performance (Sheehan, Ashton & White, 1983). Although the merits of these two approaches have been vigorously debated (Katz, 1983; Kaufmann 1981, 1983; Marks, 1977, 1983a; A. Richardson, 1977; J. T. E. Richardson, 1980, 1988) and although there is evidence that the two kinds of measure are independent (A. Richardson, 1977; Ernest, 1977), self-report imagery tests can be best validated by showing that they predict objective and theoretically-relevant criterion task performance.

In particular, measures of visual imagery might be related to visual memory. Although rivalled in popularity by Sheehan's (1967) revised version of the Questionnaire Upon Mental Imagery, which taps imagery in a number of modalities Marks' (1973) more specific Vividness of Visual Imagery Questionnaire (VVIQ) ha been employed in over 100 empirical studies (Marks, 1989a). According to Marks' (1973) instructions, subjects twice rate (once with eyes open, once with eyes closed) the vividness of their imagery on a five-point scale (with lower number indicating higher vividness) for 16 items arranged in blocks of four. Marks (1989b) states that these items involve a variety of processes including retrieval of visual images from memory and that, when the VVIQ is used as a predictor of memory performance, it is most appropriate with short delays, wher the role of imagination is minimized. Indeed, Marks (1973) himself presented three short-term memory experiments demonstrating that good imagers (or visualizers) correctly recalled more picture details than poor imagers.

Although Marks (1985) paints a uniformly positive picture of the relationship between VVIQ scores and visual memory performance, results are not entirely consistent. With recall tasks and short delays, it has been found that good visualizers were more accurate than poor visualizers (Cairns & Coll, 1977; Hishitani, 1985b; Housner, 1984; Housner & Hoffman, 1978; Marks, 1973; McKelvie & Demers, 1979; O'Brien & Wolford, 1982; Rossi & Fingeret, 1977). However, othe studies have shown similar performance levels for the two groups (Berger & Gaunitz, 1977; Chara & Hamm, 1989; Chara & Verplanck, 1986; Childers, Houston & Heckler, 1985; Cohen & Saslona, 1990; Crawford & Allen, 1983; Dickel & Slak, 1983; Dywan, 1988; Gur & Hilgard, 1975; Hall, Talukder & Esposito, 1989; Hishitani, 1985 a, b; MacLeod, 1986; Marks, 1972; Phillips, 1978; Reisberg, Culver, Heuer & Fischman, 1986), and it has even been reported that good visualizers were less accurate (Cohen & Saslona, 1990; Reisberg & Leak, 1987). Moreover, delayed visual recall has been found to be higher for good than poor visualizers (Hishitani, 1985b; McKelvie & Demers, 1979).

For short-term recognition memory, Marks (1977, 1983b) summarizes three unpublished experiments that demonstrated a positive relationship between imagery vividness and recognition accuracy for pictures of scenes but not words However, other studies have had mixed outcomes, with a positive relationship fo narrative prose (Chaguiboff & Denis, 1981; Denis, 1982, 1987), social information from an interview (Swann & Miller, 1982), and a zero-order relationship for words (Denis, 1982; Devane, 1988; MacLeod, 1986), pictures of droodles (MacLeod, 1986), and pictures of abstract art (Marks, 1983b; Mou, Anderson, Vaughan & Rouse, 1989). Moreover, as with recall, a negative relationship between vividness and accuracy has occurred (Heuer, Fischman & Reisberg, 1986; Reisberg et al., 1986).

This set of varied results does not necessarily invalidate the VVIQ, since construct validity is multifaceted (McKelvie, 1990a) and imagery vividness is not expected to predict visual memory in all circumstances (Marks, 1989b). For example, some of the results showing no difference occurred under instructions to form images, which may minimize natural processing differences (Marks, 1972) In addition, the conflicting recall results may reflect differences among different kinds of task (recall of picture detail, paired-associated recall, free recall). With its images of varied scenes, the VVIQ may be more appropriat for predicting memory for complex meaningful material.

Another factor that may encourage a positive VVIQ/memory performance relationship is the use of a holistic strategy, in which subjects simultaneousl process configural properties of the stimulus. Such opportunities are likely to be available with complex meaningful pictures, on which Marks (1973, 1977, 1983b) reported better recall and recognition memory performance by good than b poor imagers. In fact, Gur & Hilgard (1975) showed that good imagers were not only faster than poor imagers at pointing to a difference between two successively-presented pictures, but also were more likely to report seeing the difference 'pop out'. Poor imagers, on the other hand, preferred to recall individual picture details one at a time, then search for them. Using a similar task, Berger & Gaunitz (1979) found that both good and poor imagers reported both strategies, but also that good imagers were faster than poor imagers if th holistic (or imagery) strategy was used. In addition, Wallace (1988, 1991) has argued that superior visual search and proofreading performance by good over poor imagers can be attributed to holistic processing. Finally, although not mentioning the term holistic processing, Hishitani (1991) asked subjects either to form an integrated visual image or to verbally rehearse noun triplets, after which he administered a recognition probe for one of the nouns. In the imagery, but not in the verbal condition, correct responses were faster for triplets classified as vivid compared with those others classified as dim. This suggests that vividness encourages holistic processing.

If vivid imagers are more likely to use and to profit from holistic processing than poor imagers, their memory accuracy should be worse than that of poor imagers when they cannot engage in this strategy. However, when both configurational and detail processing can occur, group performance should not differ. These hypotheses can be examined with facial photographs, which possess both component (detail) and configural (holistic) properties (Sergent, 1984), a least when shown upright. Indeed, recognition memory for upright faces is similar for encoding strategies that emphasize either configural (search for a distinctive trait) or detail (search for a distinctive feature) processing (Winograd, 1981), and for good and poor imagers (McKelvie & Demers, 1979; Phillips, 1978).

In contrast, it has been suggested that configurational information is difficul to extract from inverted faces (Sergent, 1984; Valentine, 1988). Although inversion impairs recognition memory accuracy for various kinds of pictorial material, faces suffer most (Yin, 1969). Furthermore, the effect is particularl strong for faces with which subjects are very familiar. Inversion is more disruptive for pictures of dog faces for dog experts than for non-experts (Diamond & Carey, 1986), for own- than other-race faces (Rhodes, Brake, Taylor Tan, 1989; Valentine & Bruce, 1986), and for faces lit from a more (above) than a less common angle (below) (Johnston, Hill & Carman, 1992). In addition, a greater loss of accuracy with inversion has been reported for faces that were initially processed more 'deeply' (liking vs. gender classification, McKelvie, 1985) or in terms of a trait (intelligence) compared to a feature (presence or absence of spectacles, McKelvie, 1991). These disproportionate effects of inversion have been attributed by the authors to a loss of configural or semantic information about the face. Thus, it can be hypothesized that, if good visualizers are more likely than poor visualizers to engage in holistic processing, then their recognition memory performance for inverted faces will deteriorate more than that of poor visualizers. This outcome would also be consistent with the hypothesis that the VVIQ predicts memory for complex meaningful (i.e. upright photographs) but not meaningless (i.e. inverted photographs) material.

On the other hand, it has also been argued (Kaufmann, 1981; J. T. E. Richardson 1988) that the self-report scale of the VVIQ (and other measures of subjective vividness) is inherently flawed, since there is no objective standard of vividness by which different respondents can impute the same meaning to the fiv scale points. This implies that subjects may answer honestly but that their scores are not comparable, or that they may respond on some basis other than perceived vividness. Although Marks (1977) found no significant relationship between VVIQ scores and the response criterion beta, indicating that good visualizers do not simply adopt a more lenient criterion than poor visualizers, it has been suggested (Cohen & Saslona, 1990) that VVIQ ratings may reflect general self-confidence, or perhaps even overconfidence, particularly if the subject has just completed a criterion task. This possibility is supported by the finding that a negative relationship between vividness and memory performance was accompanied by a positive relationship between vividness and confidence (Reisberg et al., 1986; Reisberg & Leak (1987).

The purpose of the present experiment was to evaluate the competing holistic an rating scale proposals by comparing accuracy, confidence and response speed for immediate recognition memory of upright and inverted faces. The rating scale hypothesis predicts that there will be no relationship between the VVIQ on the one hand and either accuracy or response speed on the other, but that good visualizers will be generally more confident than poor visualizers. However, th holistic processing hypothesis predicts that upright recognition accuracy will be more disrupted by inversion for good than for poor visualizers and, since holistic processing seems to be faster than detail processing (Berger & Gaunitz 1979; Gur & Hilgard, 1975), that good visualizers should respond more quickly than poor visualizers on upright but not on inverted faces. For confidence, the holistic hypothesis predicts no VVIQ effect. The derivation of this prediction also involves the optimality hypothesis (Deffenbacher, 1989), which refers to the finding that confidence correlates more positively with accuracy under easier than under more difficult testing conditions (Bothwell, Deffenbacher & Brigham, 1987; Cutler & Penrod, 1989; Read, Vokey & Hammersley, 1990), particularly for upright and inverted faces (McKelvie, 1990b). If confidence follows accuracy for upright faces and if good and poor visualizers do not differ on accuracy, then they will also not differ on confidence. However, if confidence and accuracy are less strongly related for inverted faces, then weaker performance by good than by poor visualizers may not appear on confidence.

Method

Subjects

The subjects were 94 individuals (33 men, 61 women) who volunteered to participate in face memory research. Most were working adults and the remainder were undergraduate students. They were allocated to two conditions (upright, inverted), with matching for gender: upright 18 men, 36 women; inverted 15 men, 25 women. For the primary analysis, where the VVIQ served as the independent variable, groups of 12 good and 12 poor visualizers were formed on the basis of VVIQ scores. For the inverted condition, the 12 lowest scorers (five men, seven women) and the 12 highest scorers (four men, eight women) were designated as good and poor visualizers, respectively. This 30 per cent split is close to the optimal 27 per cent which, although derived for scores that are normally distributed (Feldt, 1961), also applies to those, like the VVIQ (McKelvie, 1986 1992), that are skewed (Fowler, 1992).

Similarly, the 17 lowest (four men, 13 women) and 17 highest (six men, 11 women scorers were designated as good and poor visualizers for the upright condition. In order to equalize sample sizes in the four VVIQ x transformation cells, 12 o these were selected at random to form the final groups of upright good and poor visualizers (four men, eight women in each).

Materials

The stimuli consisted of 54 black and white head-and-shoulders photographs (slides) of young men, half of which were presented for inspection. The other 2 were matched to the originals on head direction, hairstyle and general expression, and were paired with their counterparts in a two-alternative forced-choice recognition memory test.

Procedure

Subjects were tested individually. First they were shown each of the 27 presentation photographs in the upright orientation for 10 seconds, with the instruction to inspect each one carefully for a later memory test. Following three minutes of general conversation and recognition memory instructions, they were shown each of the 27 test pairs in the same order as before, and asked to choose which member (left or right) they had just seen and to rate their confidence that they were correct on a four-point scale (1 = certain, 2 = reasonably confident, 3 = somewhat confident, 4 = guessing). Subjects called ou their answers (e.g. left certain) to the experimenter who wrote them down and recorded response latency to the nearest second using a stop-watch. This was timed from the moment that the experimenter pressed the control to present the slide pairs until the subjects responded. Subjects were informed that response time was being noted, but that they should not interpret this as a signal to answer as quickly as possible. Rather, they were told simply to answer when the were ready. Those in the upright condition viewed the pairs upright as before, whereas those in the inverted condition, who were not told of the manipulation until just before the recognition test, viewed the pairs rotated through 180 degrees. Finally, the VVIQ was administered. Since there does not appear to be any systematic effect of eyes open and closed instructions on VVIQ ratings (Dowling, 1973, cited in White, Sheehan & Ashton, 1977; Narchal & Broota, 1988; A. Richardson, 1979), the questionnaire was given only once, with eyes not mentioned (see also McKelvie & Demers, 1979).

Results

For all statistical analyses, alpha was set at .05. As a stimulus check on the independent variable in each face condition, VVIQ scores for the good and poor visualizers exposed to upright and inverted faces were examined with a 2 x 2 (VVIQ x transformation) analysis of variance. This showed that both main effects, but not their interaction, were significant: VVIQ (F(1, 44) = 72.65), transformation (F(1,44) = 4.17) and interaction (F(1, 44) = 0.32). From Table 1 it can be seen that VVIQ scores were lower for good than for poor visualizers (as expected from the choice of extreme groups), but were also lower in the upright than the inverted condition, i.e. subjects reported less vivid visual imagery following the inverted than the upright recognition memory test. Although this result shows that the two groups of good and the two groups of poor visualizers were not equivalent in terms of VVIQ scores, a fact that will be addressed below, good and poor visualizers were themselves widely separated. Therefore, the planned analyses of accuracy (errors), response speed (latency) and confidence were made. It is also notable that the standard deviation of .86 for poor imagers in the upright condition was higher than any of the others. This occurred because of one subject who rated every item as 5. Since Marks (1983b, p. 108) urges caution with such extreme scores, as they may represent a inadvertent reversal of the polarity of the rating scale, the following analyse were conducted with this subject both retained and replaced by the next-highest scorer (who had a mean VVIQ score across the 16 items of 3.56). Since the patterns of significance throughout the study were not altered, the original data are reported.

Table 1 shows that there were significantly more errors in the inverted than upright condition (F(1, 44) = 29.36), but that the other two effects were not significant: VVIQ (F(1, 44) = .25) and interaction (F(1, 44) = .17). In addition, for latency, only the effect of transformation (F(1, 44) = 19.10) was significant. Responses were considerably slower for inverted than for upright faces. The VVIQ effect approached significance here (F(1, 44) = 3.51, p |is les than~ .10), but the interaction did not (F(1, 44) = .00). Finally, subjects wer less confident in the inverted than upright condition (F(1, 44) = 28.68), but good visualizers were also more confident than poor visualizers (F(1, 44) = 8.38). The interaction was not significant (F(1, 44) = 1.29). For the complete sample of 54 upright and 40 inverted subjects, respectively, the product-moment correlations between the VVIQ and the three dependent variables showed the same pattern of significance as the analyses of variance: .117, -.057 (errors); .143 .153 (latency); and .380, .376 (confidence). Only the last two values were significant, indicating a positive relationship between reported vividness and confidence.

One potential problem with the findings for accuracy, latency and confidence is that it may be difficult to make meaningful upright-inverted comparisons for good visualizers or for poor visualizers, since neither set of VVIQ scores was equivalent. However, since the main effect of transformation clearly replicated many previous findings, and since it never interacted with the VVIQ, the matter is probably not of immediate concern. Nevertheless, I conducted another analysi which attempted to match the VVIQ scores of good and poor visualizers selected from the original upper and lower thirds of the upright and inverted VVIQ distributions. The number in each of the four VVIQ x transformation conditions was reduced to eight, but the matching was successful. A stimulus check on the matching of VVIQ scores showed that only the effect of VVIQ was significant (F(1, 28) = 78.66), with Fs(1, 28) = .00 and .03, for the transformation and interaction, respectively. Mean VVIQ scores in the four conditions were 1.60 (good, upright), 1.56 (good, inverted), 3.16 (poor, upright) and 3.18 (poor, inverted). When the other analyses were repeated with these groups of good and poor visualizers, the pattern of results for errors and confidence was identica to the original ones. For latency, the marginally significant effect of VVIQ disappeared.

Since VVIQ scores predicted confidence but not accuracy in both conditions, a final analysis was conducted to examine the possibility that responding on the VVIQ might reflect overconfidence (Cohen & Saslona, 1990) or general self-monitoring. That is, subjects whose confidence did not match their accurac may have responded more extremely on the VVIQ, with those who were overconfiden scoring low (high vividness) and those who were underconfident scoring high (lo vividness). To accomplish this, VVIQ scores were treated as the dependent variable and were analysed from subjects who fell in the top and bottom 40 per cent of the original distributions (Ns = 54 and 40 for upright and inverted, respectively) of scores for errors and confidence. For each condition, four groups were formed: high scores on both errors and confidence (inaccurate unsure), high scores on errors and low scores on confidence (inaccurate sure or overconfident), low scores on errors and high scores on confidence (accurate unsure or underconfident), and low scores on both (accurate sure). As Table 2 indicates, numbers in the four conditions were similar for the inverted but not the upright conditions. This was a consequence of the expected stronger relatio between accuracy and confidence in the latter case (the optimality hypothesis).
Table 1. Mean scores and standard deviations (SD) for VVIQ scores, and face
recognition errors, latency and confidence in each condition

                      Transformation
                   Upright      Inverted
VVIQ status       M     SD     M      SD

VVIQ scores
Good            1.50   0.23   1.72   0.29
Poor            2.68   0.86   3.07   0.41

Errors
Good            2.92   2.97   8.25   3.74
Poor            3.75   2.67   8.33   3.20

Latency
Good            4.12   1.27   7.27   2.67
Poor            5.50   1.42   8.55   3.67

Confidence
Good            1.58   0.54   2.19   0.34
Poor            1.84   0.58   2.78   0.53

Notes. N = 12 in each condition. Maximum scores were 5 = no image (VVIQ), 27
(errors), and 4 = guessing (confidence). Latency in mean number of seconds per
trial.
Table 2. Mean VVIQ scores and standard deviations for subjects classified as
accurate or inaccurate and sure or unsure (40 per cent splits)

                       Sure                Unsure
                N     M       SD      N     M       SD

Upright
Accurate       10    1.81    0.65     5    1.88    0.32
Inaccurate      6    1.75    0.40    14    2.50    0.88

Inverted
Accurate        9    2.53    0.67     9    2.53    0.51
Inaccurate      7    1.91    0.57     7    2.85    0.37

Note. Maximum score = 5 (no image).


A three-way independent-groups analysis of variance (condition x errors x confidence) gave significant effects of condition (F(1,59) = 8.47), confidence (F(1, 59) = 7.36) and the errors x confidence interaction (F(1, 59) = 6.35). Table 2 shows that VVIQ scores were lower in the upright than inverted conditions and for sure than unsure subjects, but that the latter effect was confined to inaccurate subjects.

Discussion

The major findings of this experiment are clear. As expected from previous research (e.g. Valentine, 1988; Yin, 1969), inversion seriously disrupted recognition memory accuracy, and was associated with longer response time and reduced confidence. Not only was the inverted task more difficult, it was also perceived as more difficult. However, contrary to the holistic processing hypothesis, the effect of inversion did not differ significantly for good and poor visualizers for either accuracy or latency. Rather, and consistent with th subjective rating scale hypothesis and with previous investigations that have included confidence measures (Reisberg et al., 1986; Reisberg & Leak, 1987), VVIQ scores were related to confidence in both the upright and inverted conditions, with good visualizers reporting greater confidence in their performance than poor visualizers. These results are also consistent with a low but significant positive correlation (Childers et al., 1985; Parrott, 1986; A. Richardson, 1979) between reported visual vividness on the VVIQ and reported social desirability on the Personal Reaction Inventory. Taken together, they suggest that VVIQ ratings may reflect an instrument factor.

However, the final analysis did not support the proposal that responses on the VVIQ would be related to overconfidence (Cohen & Saslona, 1990) or to self-monitoring. In the first case, VVIQ scores should have been lower for inaccurate sure subjects than for each of the other three groups; this applied in the inverted but not in the upright condition. In the second case, VVIQ scores should have been lower for inaccurate unsure and higher for accurate sur subjects; this did not occur in either condition. However, the results did suggest that the tendency for more confident subjects to give lower (i.e. more vivid) imagery ratings than less confident ones was confined to those who were inaccurate. This may indicate that some people take greater care to answer honestly the VVIQ than others. It is not clear which subject characteristic is involved, but Shapiro & Penrod (1986) identify 'degree of attention' as one of the most important determinants of face memory performance, and they also note that accuracy was positively related to verbal ability. This implies that a general processing skill may underlie the present link between VVIQ scores and confidence.

In addition, since ratings were generally lower following upright than inverted recognition, the VVIQ seems to bc easily contaminated by the effect of context. In this case, it appears that subjects were cued to rate their visual imagery a less vivid when they had just experienced a more difficult task. Notably, it ha also been reported that VVIQ ratings were lower following hypnosis than waking instructions (Crawford & Allen, 1983). Although Marks (1989b) notes that some influence of context on the VVIQ is to be expected, such results should alert researchers to the cueing effects of a criterion task on the VVIQ. Introduction of a delay between the two tasks might help to avoid them.

The present findings confirm previous reports (McKelvie & Demers, 1979; Phillips, 1978; see also Shapiro & Penrod, 1986) of no relationship between the VVIQ and recognition memory for faces, and offer no support for the holistic processing hypothesis. Since they also suggest that VVIQ ratings are affected b an instrument factor, they then cast doubt on the VVIQ as a measure of visual imagery vividness. At the same time, it has already been observed that there ar other positive results in the memory literature. In particular, it is notable that both Marks (1973) and Rossi & Fingeret (1977) found that good visualizers performed better on picture and paired-associate recall, respectively, under conditions that included controls for verbal processing. In addition, the present experiment suggested that some subjects responded to the VVIQ on the basis of confidence rather than on an honest assessment of vividness. If these individuals have poorer general processing skills, future research with the VVI might include an independent measure of such skill, and only consider the VVIQ scores of subjects who meet some minimal criterion on the measure. In this manner, a possible contaminating effect on VVIQ scores could be removed, thereb allowing their true relationship with other variables to emerge.

Acknowledgement

This work received support from the Bishop's University Research Committee.

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Author:McKelvie, Stuart J.
Publication:British Journal of Psychology
Date:Feb 1, 1994
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