Abstract

The Prospective and Retrospective Memory Questionnaire (PRMQ) has been reported to have acceptable reliability and a tripartite structure, including a general memory factor and specific Prospective and Retrospective Memory factors. The Taiwanese version of the PRMQ was examined in an adult sample (n = 269, age range: 19–95). The 11-item Taiwanese PRMQ demonstrated acceptable internal consistency (Cronbach's α = 0.82–0.90) as well as a tripartite structure with one general Episodic Memory factor and one specific Prospective Memory factor. There was no gender effect, but older adults reported better prospective memory performance, and individuals with a higher level of education rated less retrospective memory failure. Preliminary Taiwanese normative data are also presented.

Introduction

Prospective memory is the memory of an action to be performed in the future (Einstein, Holland, McDaniel, & Guynn, 1992). Successful prospective memory performance requires an individual to detect the target cue (the intention cue, e.g., the whistle of a tea pot), recall the intended action (intention initiation and intention retrieval), and then complete the course of action (intention execution, e.g., turning off the stove; Carey, Woods, Rippeth, Heaton, & Grant, 2006). It differs from retrospective memory with regard to the absence of salient cues (prompt of recall or recognition in a research paradigm) of intention retrieval (McDaniel & Einstein, 2000). In addition to the content of the memory to be remembered present in both types, prospective memory comprises an additional prospective component responsible for remembering to remember (Dobbs & Rule, 1987; Einstein et al., 1992). Prospective memory thus relies more on the self-initiated internal control (Maylor, 1995) and the subcortical-frontal-related attention-executive processes (Burgess, Scott, & Frith, 2003; Okuda et al., 2007).

According to the type of intention cues, prospective memory tasks can be categorized into event-based and time-based tasks. In event-based prospective memory tasks, the intention retrieval is induced by external events (e.g., an auditory cue), whereas time-based prospective memory tasks, which lack external cues, rely more on self-activated intention control (Henry, MacLeod, Phillips, & Crawford, 2004). Hence, it is believed that time-based prospective memory tasks are affected more by decreased self-initiation, attention switching, and inhibition abilities, as well as the early involvement of the frontal system in the aging process (Troyer & Murphy, 2007).

Although, in the part, little research was conducted on prospective memory, it has recently been receiving growing attention because of its ubiquity, greater life impact (Smith, Sala, Logie, & Maylor, 2000), relationship with autonomy (Woods et al., 2008), and the value of early detection (Troyer & Murphy, 2007).

Measurement of Prospective Memory

Prospective memory can be measured by several methods. In a naturalistic approach, participants are instructed to execute some previously assigned tasks (formed intentions, e.g., returning a book or reminding the examiner of an appointment) under certain conditions (Groot, Wilson, Evans, & Watson, 2002; Raskin, 2004). In experimental paradigms, they are asked to press particular keys (intended actions) in response to target cues, such as in the standard Einstein and McDaniel (1990) paradigm. Another way to evaluate prospective memory function is to use self-reported inventories (Chau, Lee, Fleming, Roche, & Shum, 2007; Smith et al., 2000).

Although the paper-and-pencil questionnaire may not offer strong, objectively justifiable test results or the manipulation of relevant parameters, it does provide a reference for real-life performance and outperforms performance-based tests in terms of economy of time and supervision. The self-reported inventory thus serves as a good tool for convenient and rapid screening to determine real-life prospective memory performance.

The Prospective and Retrospective Memory Questionnaire

Smith and colleagues (2000) developed the 16-item Prospective and Retrospective Memory Questionnaire (PRMQ), which comprises the Prospective Memory subscale and the Retrospective Memory subscale, each consisting of eight items. In addition, test items can be conceptually divided into self-cued and event-cued items, of which the former are similar to time-based prospective memory, and the latter can be taken as event-based prospective memory. The total scale and the two subscales have been shown to have acceptable internal consistency reliability, varying from 0.77 to 0.89 depending on the research sample (Crawford, Smith, Maylor, Della Sala, & Logie, 2003; Piauilino et al., 2010; Ronnlund, Mantyla, & Nilsson, 2008). Factor analytic studies have confirmed a tripartite latent structure with a general memory factor and two orthogonal specific factors of prospective and retrospective memory in British (Crawford et al., 2003), Swedish (Ronnlund et al., 2008), and Brazilian (Piauilino et al., 2010) populations.

When compared with other prospective memory questionnaires, such as the Comprehensive Assessment of Prospective Memory (Waugh, 1999, as reported in Chau et al., 2007), the PRMQ both allow for quick understanding of a subject's daily prospective memory performance and provide a method of direct comparison between prospective and retrospective memory. The PRMQ has been adopted by research groups for measuring the two types of memory complaints in normal aging (Zeintl, Kliegel, Rast, & Zimprich, 2006), Alzheimer's disease (Smith et al., 2000), HIV (Woods et al., 2007), and stroke (Kim, Craik, Luo, & Ween, 2009) patients.

Demographic Variables

PRMQ ratings are widely believed to be influenced by some demographic variables. Crawford and colleagues (2003) reported a gender effect on the PRMQ, wherein women tended to report slightly fewer retrospective memory failures than men; however, no difference was found in the Prospective memory subscale or the total scale. They suggested that this was caused by the large sample size, which makes it prone to statistical significance. In contrast, Piauilino and colleagues (2010) reported an opposite gender effect, wherein women complained of more general memory problems than men, and posited that the cause might have been hormonal changes, a heavier memory load caused by additional domestic responsibilities, and difference in memory styles between genders.

As for the influence from aging, Crawford and colleagues (2003) and Piauilino and colleagues (2010) found no age effect in the ratings of the PRMQ. In contrast, Ronnlund and colleagues (2008) reported a trend of fewer prospective memory complaints in older adults. Sample characteristics might partly account for the contradiction as in the latter study younger subjects (those under 35) were not recruited. Findings from other memory questionnaires (Maylor, 1993; Reese & Cherry, 2006) and research based on other study approaches have also yielded controversial results. Some researchers (Knight, Nicholls, & Titov, 2008; Kvavilashvili, Kornbrot, Mash, Cockburn, & Milne, 2009; Rendell & Craik, 2000) have found an age-related decrement in prospective memory. This might relate to its heavy reliance on the frontal-related attention and self-initiation ability, which deteriorated greatly with aging (Cockburn, 1995). Some have argued against the presence of age effects (Einstein & McDaniel, 1990). McDaniel and Einstein (2000) posited that the more robust automatic process involved in the intention retrieval process may explain the absence of an age effect. Some studies (Henry et al., 2004; Rendell & Craik, 2000) have even demonstrated a better performance on prospective memory in elder subjects. The use of memory aids and the reduced complexity of one's life schedule might contribute to this inverse age effect (Rendell & Craik, 2000). Overall, the age-related prospective memory paradox might result from the differences in task procedures (Einstein, Smith, McDaniel, & Shaw, 1997), properties of the intention cue, and demand on self-initiated processing (Cherry et al., 2001; Einstein, McDaniel, Richardson, Guynn, & Cunfer, 1995).

Goal of the Present Study

We intended to develop the Taiwanese version of the PRMQ. The aim of the present study was three-fold. The first aim was to examine the psychometric properties of the questionnaire. Internal consistency reliability was to be estimated and competing latent structures were to be evaluated by factor analytic methods. The second was to evaluate the influence of demographic characteristics on the PRMQ rating. The third was to provide preliminary Taiwanese normative data of the PRMQ.

Methods

Participants

The study sample consisted of 269 healthy adults (Table 1). Older adults (n = 221, aged ≥36 years old) were enrolled in conjunction with community health checkups in a suburban community; younger adults (n = 48, aged ≤35 years old) were recruited from a university through online advertisement. Those with self-reported central nervous system disease (e.g., stroke and history of traumatic brain history) were excluded. All provided written informed consent. The mean age of the sample was 61.56 years (SD = 19.12) ranging from 19 to 95 years old. The mean duration of formal education was 11.08 years (SD = 5.11) ranging from illiterate to doctorate; those with more than 16 years of education were still counted as having completed 16 years.

Table 1.

Summary of descriptive data of the study sample

 n Mean SD Range 
Sex 269 1.58 0.49  
Age 268 61.56 19.12 19–95 
Education 256 11.08 5.11 0–18 
 n Mean SD Range 
Sex 269 1.58 0.49  
Age 268 61.56 19.12 19–95 
Education 256 11.08 5.11 0–18 

Materials and Procedure

Each subject signed a written informed consent sheet and completed a brief survey on demographic information and related medical issues. Following a brief introduction of the questionnaire, they completed the Taiwanese PRMQ. The study was explained as a survey of the memory problems that frequently occurred in daily life. The participants were asked to rate the frequency of their memory failure on each item on a 5-point Likert scale: graphic (Very often), graphic (Quite often), graphic (Sometimes), graphic (Rarely), and graphic (Never). The ratings were then assigned as 5 (graphic) to 1 (graphic). The total score ranged from 16 to 80. The questionnaire was further categorized into two dimensions, with eight self-cued items (items 1, 3, 5, 7, 10, 12, 14, 16) including the Prospective Memory subscale and the other eight event-cued items (items 2, 4, 6, 8, 9, 11, 13, 15) including the Retrospective Memory subscales.

The Taiwanese PRMQ was translated from the original PRMQ into Mandarin and written in traditional Chinese characters. The translation was authorized by Dr Robert Logie. Backward translation was then performed, and the back-translated version was judged as identical by two native English speakers.

Analyses

SPSS 15.0 and LISREL 8.0 were used for exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), respectively. EFA was first conducted to check the factor structure. Factor loadings were estimated with the principal axis method, and the factor structure was rotated by the promax method. Factor numbers were chosen according to the rule of eigen value >1. Items with factor loading disagreement between theoretical and factor analysis assignments were removed. CFAs were then adopted to test the more constrained models. Four models were tested following previous studies (Crawford et al., 2003; Piauilino et al., 2010; Ronnlund et al., 2008). Model 1, a single-factor model, assumed the covariance among items could be explained by one general memory factor. Model 2, a two-factor model, posited prospective memory and retrospective memory factors which were correlated. Model 3 predicted a tripartite structure wherein all items indicated a general episodic memory factor, whereas the eight prospective memory items and the eight retrospective memory items were indicators of additional factors that explained the specific variance of prospective and retrospective memory, respectively. The two additional specific factors were constrained to be orthogonal to each other and to the general factor. The error terms were assumed to be uncorrelated in all cases. Model 4 was identical to Model 3, except that the specific retrospective memory factor was removed, assuming all items tapping a general episodic memory factor and the prospective memory items tapping an additional specific prospective memory factor. All parameters were estimated with the maximum likelihood method. In addition to the χ2 test, fit indices were also selected on the basis of previous studies to provide comparison. The selected indices were root mean square of approximation (RMSEA; Hu & Bentler, 1999), comparative fit index (CFI; Bentler & Moijart, 1989), and standardized root mean-squared residual (SRMR; Hu & Bentler, 1999). We used the Pearson correlation and independent t-test to examine the correlation between demographic variables and the PRMQ rating. A paired t-test was used to compare the two subscales. Cohen's d, one kind of effect size, was also calculated to evaluate the effect of demographic variables.

Normative data were generated according to the procedure described in Crawford and colleagues (2003). The T score was chosen because it is easy to comprehend. The True score was calculated by forumla, where rxx is estimated by Cronbach's α, and the 95% confidence interval of the standardized true scores was estimated by forumla, where SEMxt stands for standard error of measurement.

Results

The results will be presented following the order of our main objectives. First, we will show the reliability data, followed by the evaluation of the latent structure and correlation analyses between demographic variables and PRMQ scores, and then we will provide the normative data.

Reliability

For the original 16-item PRMQ Total score, the Prospective Memory and the Retrospective Memory subscale scores demonstrated acceptable internal consistency (Cronbach's α = 0.93, 0.88, and 0.87, respectively). The revised 11-item PRMQ (will be described in the Factor Structure section) had a similar level of internal consistency reliability (0.90, 0.86, and 0.82, respectively).

Factor Structure

To evaluate the factor structure, the characteristics of the data were examined. According to Bentler and Chou (1987), the ratio of the sample size to the number of free parameters should be greater than five when the normality assumption is satisfied. In the present data, the skewness and kurtosis of each item score were all between 1 and −1, indicating the fulfillment of the normality assumption. The number of our valid samples (269) was greater than five times of the number of free parameters (16). This fulfilled the criteria of the least subject number suggested by Bentler and Chou.

The original CFA with 16-item questionnaire showed a preference to Model 3 (tripartite model); however, less than half of the items had significant factor loadings. Considering cross-cultural differences and that some item meaning might not be as precise after being translated into Chinese due to its different system of tense, a preliminary EFA was conducted to check the raw pattern and it revealed five items (items 4, 7, 8, 9, 14) were not loaded on the theoretically presumed subscales. These items were thus removed.

The remaining 11-item version of the PRMQ was subjected to CFA. Results of the fit indices of competing models are shown in Table 2. Although the significant χ2 values for the four models might imply a mismatch between the observed and predicted covariance, it was not expected that the values would attain non-significance, given the sufficiently large sample size. We thus adopted the results of other fit indices.

Table 2.

Summary of fit indices for the competing confirmatory factor analytic models

Model χ2 df RMSEA SRMR CFI PNFI AIC 
1. One-factor model 149.5405 44 0.0974 0.051 0.967 0.763 3,224.730 
2. Two-factor model 120.2231 43 0.0821 0.044 0.976 0.753 166.615 
3. Tripartite model 74.546 33 0.0666 0.035 0.987 0.586 138.175 
4. Tripartite model (with Retrospective Memory factor omitted) 106.6527 38 0.0837 0.041 0.978 0.668 165.261 
Model χ2 df RMSEA SRMR CFI PNFI AIC 
1. One-factor model 149.5405 44 0.0974 0.051 0.967 0.763 3,224.730 
2. Two-factor model 120.2231 43 0.0821 0.044 0.976 0.753 166.615 
3. Tripartite model 74.546 33 0.0666 0.035 0.987 0.586 138.175 
4. Tripartite model (with Retrospective Memory factor omitted) 106.6527 38 0.0837 0.041 0.978 0.668 165.261 

Notes: RMSEA = root mean square of approximation; SRMR = standardized root mean-squared residual; CFI = comparative fit index; PNFI = parsimony normed fit index; AIC = akaike's information criterion.

In Model 1 (the unitary model), the RMSEA (0.10) fell far from Browne and Cudeck's (1989) criterion (<0.08). The SRMR (0.05) and the CFI (0.96) otherwise met Hu and Bentler's (1999) criteria (<0.08 and >0.95, respectively). Model 2 roughly met the criterion of the RMSEA (observed: 0.08, criterion: <0.08) and had satisfactory values of the SRMR (0.03) and the CFI (0.98). Model 3 (the tripartite model) performed the best in terms of fit indices (RMSEA = 0.07, SRMR = 0.03, CFI = 0.99, AIC = 138.175); however, five of six of the loadings on the Prospective Memory subscale were not significant. For Model 4 (the tripartite model with retrospective memory factor removed), the RMSEA (0.08), which might have been overestimated because of the relatively small sample size, was close to the criterion (<0.08). The SRMR (0.04) and the CFI (0.98) were satisfactory. All the factor loadings were significant. Taken together, although Model 3 performed the best on all model fit indices, not all items had significant factor loadings. Thus, Model 4 that had satisfactory model fit with all items yielding significant factor loading appeared to be the best choice. It is also consistent to the hypothesis that it requires an additional cognitive component (probably relating to executive function and/or supervisory attentional process) during the prospective memory process.

Correlation with Demographic Data

The mean scores of men and women did not significantly differ on the Total scale (t = −0.59, p = .56, d = 0.07), the Prospective Memory subscale (t = −1.29, p = .20, d = 0.16), or Retrospective Memory subscale (t = 0.32, p = .74, d = 0.04). Although there was no significant relationship between age and the Total scale (r = −.03, p = .59) and the Retrospective Memory subscale (r = .09, p = .16), a small but significant correlation was shown on the Prospective Memory subscale (r = −.13, p = .03). We further analyzed the influence of education on ratings. Significant correlation was found on the Retrospective Memory (r = −.26, p < .0001) and Total scales (r = −.18, p < .01), but not on the Prospective Memory scale (r = −.09, p = .15).

Normative Data

Means and standard deviations for the PRMQ scores are presented in Table 3. There was a significant difference between the two types of memory complaints in that subjects reported more prospective than retrospective memory failures (t = 21.38, p < .001, d = 1.00). The mean ratings of items on the Prospective (2.49) and the Retrospective (2.10) Memory subscales were lower than those of the British (2.52 and 2.34, respectively, according to Crawford et al., 2003) and higher than those of the Swedish (2.24 and 1.70, respectively, according to Ronnlund et al., 2008) normative data. The variances (SD= 4.88 and 4.11, respectively) were similar to those of the British (4.91 and 4.98, respectively) and the Swedish (4.74 and 4.18, respectively) norms.

Table 3.

Summary statistics for the Taiwanese PRMQ

Scale Mean SD Range SEMxt 
Total Scale 25.43 8.36 11–55 2.35 
Prospective Memory subscale 14.92 4.88 6–30 1.55 
Retrospective Memory subscale 10.51 4.11 5–25 1.44 
Scale Mean SD Range SEMxt 
Total Scale 25.43 8.36 11–55 2.35 
Prospective Memory subscale 14.92 4.88 6–30 1.55 
Retrospective Memory subscale 10.51 4.11 5–25 1.44 

Tables 4–6 provide the T scores corresponding to the raw scores of the Total scale and the Prospective Memory and Retrospective Memory subscales. Based on the findings of correlation analyses, the normative data were stratified by age for the Prospective Memory subscale but simplified for the Total scale and the Retrospective Memory subscale for practical reasons. T scores were reflected so that the higher scores indicated fewer memory complaints. True scores and the 95% confidence interval are also presented.

Table 4.

Conversion of raw scores on the Prospective Memory subscale to T scores and 95% confidence interval on true scores

Aged 19–49 years old
 
Aged 50–95 years old
 
Raw score T score True score 95% confidence limits
 
Raw score T score True score 95% confidence limits
 
   Lower Upper    Lower Upper 
30 82 28 25 31 30 81 28 25 31 
29 79 27 24 30 29 79 27 24 30 
28 77 26 23 29 28 77 26 23 29 
27 74 25 22 28 27 75 25 22 28 
26 72 24 22 27 26 73 24 21 28 
25 70 24 21 26 25 71 24 21 27 
24 67 23 20 26 24 69 23 20 26 
23 65 22 19 25 23 67 22 19 25 
22 62 21 18 24 22 65 21 19 24 
21 60 20 17 23 21 63 20 18 23 
20 58 19 17 22 20 61 19 17 22 
19 55 19 16 21 19 59 18 16 21 
18 53 18 15 21 18 57 18 14 21 
17 51 17 14 20 17 55 17 14 20 
16 48 16 13 19 16 53 16 13 19 
15 46 15 12 18 15 51 15 12 18 
14 43 14 12 17 14 49 14 11 17 
13 41 14 11 16 13 47 13 10 16 
12 39 13 10 16 12 46 12 15 
11 36 12 15 11 43 11 15 
10 34 11 14 10 41 11 14 
31 10 13 39 10 13 
29 12 37 12 
27 11 35 11 
24 11 33 10 
Aged 19–49 years old
 
Aged 50–95 years old
 
Raw score T score True score 95% confidence limits
 
Raw score T score True score 95% confidence limits
 
   Lower Upper    Lower Upper 
30 82 28 25 31 30 81 28 25 31 
29 79 27 24 30 29 79 27 24 30 
28 77 26 23 29 28 77 26 23 29 
27 74 25 22 28 27 75 25 22 28 
26 72 24 22 27 26 73 24 21 28 
25 70 24 21 26 25 71 24 21 27 
24 67 23 20 26 24 69 23 20 26 
23 65 22 19 25 23 67 22 19 25 
22 62 21 18 24 22 65 21 19 24 
21 60 20 17 23 21 63 20 18 23 
20 58 19 17 22 20 61 19 17 22 
19 55 19 16 21 19 59 18 16 21 
18 53 18 15 21 18 57 18 14 21 
17 51 17 14 20 17 55 17 14 20 
16 48 16 13 19 16 53 16 13 19 
15 46 15 12 18 15 51 15 12 18 
14 43 14 12 17 14 49 14 11 17 
13 41 14 11 16 13 47 13 10 16 
12 39 13 10 16 12 46 12 15 
11 36 12 15 11 43 11 15 
10 34 11 14 10 41 11 14 
31 10 13 39 10 13 
29 12 37 12 
27 11 35 11 
24 11 33 10 
Table 5.

Conversion of raw scores on the Prospective Memory subscale to T scores and 95% confidence interval on true scores

Raw score T score True score 95% confidence limits
 
   Lower Upper 
30 32 10 
29 34 11 
28 36 12 
27 38 10 13 
26 40 11 14 
25 42 12 15 
24 44 12 15 
23 46 13 10 16 
22 48 14 11 17 
21 50 15 12 18 
20 52 16 13 19 
19 54 17 14 20 
18 56 18 15 21 
17 58 18 15 21 
16 60 19 16 22 
15 62 20 17 23 
14 65 21 18 24 
13 67 22 19 25 
12 69 23 20 26 
11 71 24 21 27 
10 73 24 21 28 
75 25 22 28 
77 26 23 29 
79 27 24 30 
81 28 25 31 
Raw score T score True score 95% confidence limits
 
   Lower Upper 
30 32 10 
29 34 11 
28 36 12 
27 38 10 13 
26 40 11 14 
25 42 12 15 
24 44 12 15 
23 46 13 10 16 
22 48 14 11 17 
21 50 15 12 18 
20 52 16 13 19 
19 54 17 14 20 
18 56 18 15 21 
17 58 18 15 21 
16 60 19 16 22 
15 62 20 17 23 
14 65 21 18 24 
13 67 22 19 25 
12 69 23 20 26 
11 71 24 21 27 
10 73 24 21 28 
75 25 22 28 
77 26 23 29 
79 27 24 30 
81 28 25 31 
Table 6.

Conversion of raw scores on the Retrospective Memory subscale to T scores and 95% confidence interval on true scores

Raw score T score True score 95% confidence limits
 
   Lower Upper 
25 37 
24 39 10 
23 41 10 
22 44 11 
21 46 12 
10 49 10 13 
19 51 11 14 
18 54 12 15 
17 56 13 10 15 
16 58 13 11 16 
15 61 14 11 17 
14 63 15 12 18 
13 66 16 13 19 
12 68 17 14 19 
11 71 17 15 20 
10 73 18 15 21 
76 19 16 22 
78 20 17 23 
80 21 18 24 
83 22 19 24 
85 22 20 25 
Raw score T score True score 95% confidence limits
 
   Lower Upper 
25 37 
24 39 10 
23 41 10 
22 44 11 
21 46 12 
10 49 10 13 
19 51 11 14 
18 54 12 15 
17 56 13 10 15 
16 58 13 11 16 
15 61 14 11 17 
14 63 15 12 18 
13 66 16 13 19 
12 68 17 14 19 
11 71 17 15 20 
10 73 18 15 21 
76 19 16 22 
78 20 17 23 
80 21 18 24 
83 22 19 24 
85 22 20 25 

Discussion

The aim of the present study was to evaluate the psychometric properties of the Taiwanese version of the PRMQ, to examine its correlation to demographic variables, and to provide preliminary Taiwanese normative data.

Reliability and Latent Structure

The Taiwanese PRMQ has acceptable internal consistency on the Total scale and on the Prospective and the Retrospective subscales. Factor analyses revealed that the best fit model has a tripartite structure with a general Episodic Memory factor plus a specific Prospective Memory factor on the Prospective Memory subscale. This partially corroborates previous finding in British (Crawford et al., 2003), Swedish (Ronnlund et al., 2008), and Brazilian (Piauilino et al., 2010) samples and is even more compatible with the theoretical framework that there is an additional prospective memory component in prospective memory in addition to the retrospective memory component shared with retrospective memory.

Despite being approved through backward translation, the original 16-item Taiwanese PRMQ still failed to fit the hypothetical factors on some items. It might be that the different language system could not convey exactly identical meanings to readers and influenced the assessment. The PRMQ taps two different types of memory, types that differ mainly in the time of intention execution, with one in the past and the other in the future. The lack of verb tenses in Chinese might lead individuals to different interpretations of the test items and thus confound the results. For example, after a close inspection of the wording, we found that most items with good fit to the prospective memory factor contained the term “in a few minutes,” which explicitly emphasized the time of action. Nonetheless, after the removal of some test items, the construct validity and adequacy in measuring prospective and retrospective memory were confirmed for the 11-item Taiwanese PRMQ.

Influence of Demographic Variables

We found no gender effect on either memory type in our sample. This is different from Piauilino and colleagues' (2010) finding that women tended to have more general memory complaints, but it is partially in line with Crawford and co-workers' (2003) interpretation of their results. They found that women reported fewer retrospective memory problems, but they explained this gender effect by the large sample size and did not consider it to be a real difference. The characteristics of our sample were similar to those of Crawford and colleagues' (2003) in the broader age range (17–94 years in their sample and 19–95 years in ours), and our sample had a greater number of women than the sample of Piauilino and colleagues (2010) (age ranging from 35 to 90 years with similar numbers of each gender). The inconsistent findings might be attributed to the difference in the samples.

With regard to the age effect, men and women reported similar amounts of retrospective memory problems, which is consistent with previous results (Crawford et al., 2003; Piauilino et al., 2010; Ronnlund et al., 2008). Nonetheless, older adults tended to rate themselves as having better prospective memory performance. This is consistent with Ronnlund and colleagues' (2008) finding that older adults rated their prospective memory performance as slightly better on the PRMQ, and also in accordance with previous results in naturalistic research (Henry et al., 2004; Rendell & Craik, 2000). One reason could be that older people adopt more memory aids (Henry et al., 2004), thereby facilitating their memory performance; alternatively, the elderly, who have lower levels of activity and more structured life schedules, may have a decreased likelihood of memory failure. This finding might also result from a decrease in internal monitoring of behaviors in the elderly (Pansky, Goldsmith, Koriat, & Pearlman-Avnion, 2009); that is, it is less likely for individuals to be aware of prospective memory failure if their own behaviors are not well monitored by metacognition. Hence, they may tend to rate themselves as performing better on prospective memory. Yet, another possible explanation is the cohort effect; younger adults might adopt more stringent criteria in judging their performance level when compared with their older counterparts.

Compared with results generated by different study approaches, the lack of an age-related decrement is probably due to the simple tasks described in our test items and the relatively automatic processes involved in them. Einstein and colleagues (1992) stated that the age effect on prospective memory only occurred in complex memory tasks in which retrospective memory accounted for most of the age-related decrement. Henry and colleagues (2004) also concluded that a larger age effect was found in tasks with higher controlled strategic demand than in the more automatic ones. Nevertheless, the controversial results in the literature indicate that the age effect is not a robust phenomenon in prospective memory function.

The influence of education was not specified in previous norm studies of the PRMQ. Piauilino and colleagues (2010) reported that there was no effect of education on the PRMQ rating. However, the present results show that individuals with higher levels of education reported less retrospective memory complaints. Even though there was an age/cohort-related difference in regard to educational attainment, this could not be explained by aging, since the direction of the impact was somewhat opposite. Education level seems to be either a protective factor or a consequence of better retrospective memory abilities. On the other hand, prospective memory was not remarkably influenced by education. Again, the relatively automatic processes underlying the prospective memory tasks assessed by the PRMQ might account for this result. McDaniel and Einstein (2000) noted one kind of prospective memory, in which intention retrieval just “pops-out” in the mind. It is reasonable to infer that this relatively automatic and resource-free retrieval would show less or little benefit from or to education.

Normative Data

We have provided normative data for use in the Taiwanese population. Our Taiwanese sample generally reported more prospective and retrospective memory problems than Swedish and Brazilian samples, but less than British samples. As for the comparison between the retrospective and prospective memory complaints, our results were consistent with previous findings (Crawford et al., 2003; Piauilino et al., 2010; Smith et al., 2000), where more prospective than retrospective memory problems were reported. Smith and colleagues (2000) explained this discrepancy by the greater life impact of prospective memory failure, which makes it more noticeable and thus more likely to be reported. The conversion tables (Table 4–6) offer easy and quick access to the T score of each scale. In consideration of the presence of the age effect, the normative data of the Prospective Memory subscale were further stratified into two age groups in order to increase the sensitivity in the older population.

Clinical Usage

The PRMQ is a fast and convenient tool for understanding the performance level of prospective and retrospective memory, as well as general memory abilities. It can serve as a screening tool for further evaluation or for sample selection for use in research. However, in view of the discrepancy of results derived from experimental and naturalistic approaches (Fleming et al., 2009; Kliegel, 2006; Zeintl et al., 2006), we do not suggest that the PRMQ be used as the sole measurement. Rather, it should be used in combination with other formal test tools to offer additional function information about the subject's real-life situation.

As discussed before, the PRMQ probably mainly assesses prospective memory, which predominately involves automatic processes, whereas other aspects, such as strategic and memory-based ones (McDaniel & Einstein, 2000), were included to a lesser extent. Supplementary interviews or other test tools are thus required. However, this does not mean that the PRMQ is poorly designed. For some clinical uses, such as cognitive rehabilitation, the PRMQ reflects the most prevalent and real-life problems that a patient encounters and can be used to prioritize problems to be dealt with.

The growing research on prospective memory provides a somewhat different view from the traditional perspective in terms of the underlying neural substrates. Related frontal-subcortical circuits other than mesial temporal structures also play an important role, in both retrieval of retrospective memory and the accomplishment of prospective memory tasks. Likewise, not only executive functions but also memory, especially prospective memory, should be major concern to the clinician when treating patients with frontal and/or temporal lesions.

Limitation

The present study has several limitations. First, despite the fulfillment of the suggested sample size (as described in the Method section), the sample recruited was still much smaller than those in previous norm studies (Crawford et al., 2003; Ronnlund et al., 2008). The sampling method, non-probabilistic sampling, did not consider the stratification based on geographical areas. In addition, factor analysis and the normative data provided were generated by the same sample and the results might be unstable. This should be taken into account when applying the present data. A normative study on a large scale is needed in the future. Second, in spite of the attempt to exclude subjects with central nervous system disease, the screening was based only on self-reported data. We are thus not confident that all participants were free of central nervous system disease, such as dementia, due to the lack of formal neuropsychological examinations and chart reviews. However, this study can be considered a preliminary survey of self-perceived memory problems in the general population in Taiwan. Third, knowing oneself to have a poor memory requires metacognition and self-monitoring, as well as at least modest memory ability to know and remember that one has forgotten to do something. However, we did not adopt direct tests of metacognition and memory abilities. Consequently, it might be possible that people with poor metacognition or memory ability evaluated themselves as having better memory performance, whereas those with better memory ability rated themselves as worse, since they may have been better at detecting and knowing their own memory failure. This potential confounding factor requires future investigation.

In conclusion, the Taiwanese version of the PRMQ has acceptable internal consistency and a tripartite structure with one general episodic memory factor and an additional specific prospective memory factor. As for the influence of demographic variables, older adults perceived themselves to have better prospective memory, and higher education was related to better self-reported retrospective memory performance. The questionnaire is suitable for study sample selection, clinical screening, or use as a supplementary assessment tool for evaluating and comparing prospective and retrospective memory in formal testing.

Conflict of Interest

None declared.

Acknowledgement

We wish to thank Keng-Lin Lee for his help in statistical consultation.

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