Newly developed Learning and Verbal Memory Test (TAMV-I): Normative data for Spanish-speaking pediatric population

2.1Participants

The sample consisted of 4,373 healthy children who were recruited from Chile, Cuba, Ecuador, Guatemala, Honduras, Mexico, Paraguay, Peru, Puerto Rico, and Spain. Participants were selected according to the following criteria: a) were between 6 and 17 years of age, b) were born and currently lived in the country where the study was conducted, c) have Spanish as their mother tongue, d) an IQ≥80 on the Test of Non-verbal Intelligence (TONI-2, Brown, Sherbenou, & Johnsen, 2009), and e) scored <19 on the Children’s Depression Inventory (CDI, Kovacs, 1992).

Children with history of neurologic or psychiatric disorders as reported by the participant’s parent(s) were excluded due to its effects on cognitive performance. Participants in the study were from public or private schools, and they signed an informed consent to participate. Socio-demographic and participant characteristics for each of the countries’ samples have been reported elsewhere (Rivera & Arango-Lasprilla, 2017). Ethics Committee approval was obtained for the study in each country.

2.2Instrument administration

The TAMV-I consists of a list of 12 words belonging to three semantic categories: clothing, furniture, and body parts. The test is administered in 4 trials. In each trial, first the examiner tells the examinee he/she will have to repeat the 12 words that will be read aloud. Immediately after reading the 12 words, the examinee is asked to list all the words he/she can remember. Even if the examinee can’t say all 12 words, all 4 trials of listing and remembering must be completed. Therefore, there is an immediate recall total learning score with a maximum of 48 points (12 per trial). After 30 minutes, the examinee is asked to remember and list the same 12 words. Thus, the total memory delayed recall score has a maximum of 12 points. After the delayed recall trial, the recognition trials begin. In each of 12 recognition trials, the examinee must identify the initial words from the list of 12 when presented with 3 other words in groups of 4 – 1 semantically related to the initial word, 1 non-semantically related, and 1 phonologically related. Thus, the total recognition score has a maximum of 12 points. The TAMV-I administration guidelines can be found in Rivera et al. (2017a).

2.3Statistical analyses

Detailed statistical analyses used to generate the normative data for the TAMV-I scores are described in Rivera & Arango-Lasprilla (2017). In summary, the scores were standardized using multiple linear regression analyses by means of a four-step procedure. 1) First, the free recall, memory delay and recognition scores were computed separately by means of the final multiple regression models. The full regression models included as predictors: age, age², sex, and mean level of parental education (MLPE). Age was centered (= calendar age – mean age in the sample by country) before computing the quadratic age term to avoid multicollinearity (Aiken & West, 1991). Sex was coded as male = 1 and female = 0. The MLPE variable was coded as 1 if the participant’s parent(s) had > 12 years of education or 0 if participant’s parent(s) had≤12 years of education. If predicted variables were not statistically significant in the multivariate model with an alpha of 0.05, the non-significant variables were removed and the model was run again. A final regression model was conducted yˆi = B0 + B1 · (Age-x¯Age by country)i + B2 · (Age-x¯Age by country)i2 + B3 · Sexi + B4 · MLPEi . 2) Residual scores were calculated based on the final model ( ei = yi-yˆi ). 3) Residuals were standardized using the residual Standard Deviation (SD_e) value provided by the regression model: z_i  =  e_i/SD_e. 4) Standardized residuals were converted to percentile values using the standard normal cumulative distribution function. This four-step process was applied to free recall, memory delay and recognition scores separately for each country.

For all multiple linear regression models, the following assumptions were evaluated: a) multicollinearity by the values of the Variance Inflation Factor (VIF), which must not exceed 10, and the collinearity tolerance values, which must not exceed the value of 1 (Kutner, Nachtsheim, Neter, & Li, 2005), and b) the existence of influential values by calculating the Cook’s distance. The maximum Cook’s distance value was related to a F (p, n - p) distribution. Influential values are considered when percentile value is equal or higher than 50 (Cook, 1977; Kutner et al., 2005). All analyzes were performed using SPSS version 23 (IBM Corp., Armonk, NY).

3.1TAMV-I free recall

The final multivariate linear regression models for the ten country-specific TAMV-I free recall scores were significant (see Table 1). In all countries, the TAMV-I free recall scores increased linearly as a function of age. The TAMV-I free recall scores were affected by a quadratic age effect for all countries except for Cuba and Puerto Rico. Children from Chile, Honduras, Mexico, Puerto Rico, and Spain whose parents had a MLPE >12 years obtained higher TAMV-I free recall scores than children whose parents had a MLPE≤12 years. The child’s sex affected TAMV-I free recall scores for Cuba, Ecuador, Guatemala, Mexico, Paraguay, Peru, and Spain, so that girls achieved higher scores than boys. The amount of variance these predictors explained in the TAMV-I free recall scores ranged from 11.8% (in Guatemala) to 38.0% (in Cuba).

3.2TAMV-I memory delay

The final multivariate linear regression models for the ten country-specific TAMV-I memory delay scores were significant (see Table 2). In all countries, the TAMV-I memory delay scores increased linearly as a function of age. The TAMV-I memory delay scores were affected by a quadratic age effect for all countries except for Cuba and Puerto Rico. Children from Puerto Rico and Spain whose parents had a MLPE >12 years obtained higher TAMV-I memory delay scores than children whose parents had a MLPE≤12 years. The child’s sex affected TAMV-I memory delay scores for all countries except for Chile, Paraguay, and Puerto Rico, so that girls achieved higher scores than boys. The amount of variance these predictors explained in the TAMV-I memory delay scores ranged from 13.5% (in Guatemala) to 27.5% (in Cuba).

3.3TAMV-I recognition

The final multivariate linear regression models for the ten country-specific TAMV-I recognition scores were significant (see Table 3). In all countries, the TAMV-I recognition scores increased linearly as a function of age. The TAMV-I recognition scores were affected by a quadratic age effect for Chile, Cuba, Ecuador, Mexico, Paraguay, Peru, and Spain. MLPE affect TAMV-I recognition scores for Puerto Rico. The child’s sex affected TAMV-I recognition scores for Ecuador, Mexico, Peru, and Spain, so that girls achieved higher scores than boys. The amount of variance these predictors explained in the TAMV-I recognition score ranged from 4.3% (in Paraguay) to 16.5% (in Chile).

The assumptions of multiple linear regression analysis were met for all final models. There was not multicollinearity (the VIF values were below 10; VIF≤1.066; collinearity tolerance values did not exceed the value of 1) or influential cases (the maximum Cook’s distance value was 0.187 in a F _(2,298)  distribution which correspond to percentile 17).

3.4Normative procedure

Norms (e.g., a percentile score) for the different TAMV-I scores by country were established using the four-step procedure described in the statistical analysis section. An example will be provided to facilitate an improved understanding of the procedure used to obtain the percentile associated with a score on this test. Let’s assume we need to find the percentile score for a 17-year-old Cuban boy who scored a 39 on the TAMV-I free recall and whose parent(s) have a MLPE of 14. The steps to obtain the percentile for this score are: 1) Find Cuba in Table 1, which provides the final regression models by country for the TAMV-I free recall scores. Use the B weights to create an equation that will allow you to obtain the predicted TAMV-I free recall score for this child using the coding provided in the statistical analysis section. The corresponding B weights are multiplied by the centered age (= calendar age – mean age in the Cuban sample which is equal to 11.5 years), and sex which was coded as male = 1 and female = 0. MLPE was not a significant predictor, and therefore is not included in this model. See Rivera & Arango-Lasprilla (2017) to figure out the mean age of each country’s sample. Then the result is added to the constant generated by the model in order to calculate the predicted value.

In the case of the Cuban boy, the predicted TAMV-I free recall score would be calculated using the following equation: yˆi = 33.200 + [1.340 · (Agei-11.5)] + (-1.324 · Sexi) . The boy’s age is 17. Sex was coded as male = 1 and female = 0, so in this case as the child is a male, the sex value is 1. Thus, the predicted value equation is: yˆi = 33.200 + [1.340 · (17-11.5)] + (-1.324 · 1) = 33.200 + 7.37 + (-1.324) = 39.246 . 2) In order to calculate the residual value (indicated with an e_i in the equation), we subtract the actual free recall score (he scored 39) from the predicted value we just calculated ( ei = yi-yˆi ). In this case, it would be e_i  =  39 - 39.246  =   -0.246. 3) Next, consult the SD_e column in Table 1 to obtain the country-specific SD_e (residual) value. For Cuba it is 5.986. Using this value, we can transform the residual value to a standardized z score using the equation z_i  =  e_i/SD_e. In this case, we have -0.246/5.986  =   -0.041. This is the standardized z score for a 17-year-old Cuban boy who scored a 39 on the TAMV-I free recall who has parent(s) with a MLPE of 14. 4) The last step is to use the tables available in most statistical reference books (e.g., Strauss et al., 2006). In this example, the z score (probability) of -0.041 corresponds to the 48 percentile. It is important to remember to use the appropriate tables that correspond to each test (free recall, memory delay and recognition) when performing these calculations.

3.5User-friendly normative data

The four-step normative procedures explained above offers the clinician the ability to determine an exact percentile for a child who has a specific score on the TAMV-I. However, this method can be prone to human error due to the number of required computations by hand. To enhance user-friendliness, the authors have completed these steps for a range of raw scores based on age, sex, and MLPE and created tables for clinicians to more easily obtain a percentile range/estimate associated with a given raw score on this test. These tables are available by country and type of test in the Appendix. In order to obtain an approximate percentile for the above example (converting a raw score of 39 on the TAMV-I free recall test for a Cuban boy who is 17 years old and whose parent(s) have a MLPE of 14) using the simplified normative tables provided in the Appendix, the following steps must be followed. (1) First, identify the appropriate table ensuring the appropriate country and test (free recall, memory delay and recognition). In this case, the table for TAMV-I free recall score for boys from Cuba can be found in Table A2. (2) Find the appropriate age of the child, in this case, 17 years old. (3) Next, look in the 17 years’ age column to find the approximate location of the raw score obtained on the test. Within the 17 years’ column, the score of 39 obtained by this Cuban boy corresponds to an approximate percentile of 50.

The percentile obtained using this user-friendly table sometimes could be slightly different than the hand-calculated, more accurate method (48 vs. 50) because the user-friendly table is based on a limited number of percentile values. Individual percentiles cannot be presented in these tables due to space limitations. If the exact score is not listed in the column, you must estimate the percentile value from the list of raw scores available.

4.1Implications

A recently study found that 65% of neuropsychologists in Spain and 86% in Latin America included assessment of learning and memory processes as part of their usual daily practice (Arango-Lasprilla et al., 2016; Olabarrieta-Landa et al., 2016). However, few of these tests have been validated and have norms to evaluate memory and learning in children and adolescent populations. Therefore, the results of the present study have great clinical implications for the practice of neuropsychology in Spanish-speaking countries. The TAMV-I is a free access neuropsychological test created exclusively for Spanish-speaking children and adolescents, giving special attention to the words that would compose the lists for the learning task. In order to do that, norms for the categories in Spanish-speaking children were selected (Rivera et al., 2017a). In addition, the selection of words not only addressed the frequency of words in each category, but also the most common words among the different Spanish-speaking countries were selected, allowing their use in different countries were Spanish is spoken (Rivera et al., 2017a). On the other hand, the TAMV-I allows the evaluation of main processes involved in memory (learning, short- and long-term memory, and recognition), which allows professional to determine not only if the patient presents memory problems but also in which process presents the problems.

4.2Limitations and future directions

The present study presents some limitations. First, only children whose mother tongue was Spanish were recruited. In addition, the TAMV-I was specially created for use in Spanish-speaking children (Rivera et al., 2017a). Therefore, caution should be taken into account when using the TAMV-I, as well as the use of its norms in children whose mother tongue is not Spanish. This is especially important because many countries in Latin America and Spain are multilingual, with Spanish being one of the most widely spoken languages (Chamoreau, 2014; Garrido Medina, 2007).

Secondly, it is not advisable to use these normative data in pediatric population of those Spanish-speaking countries in which the study was not conducted, such as Argentina, Bolivia, Panama or Venezuela, among others. Future studies should generate normative data for the TAMV-I in these countries.

Although the norms of the present study could be used by neuropsychologists in other countries to evaluate Spanish-speaking immigrant children from the countries where the sample was collected for this study, it should be used with caution since other variables such as level of acculturation, bilingualism, number of years living in the country, and so on, could influence performance. In addition, the quality of education of both the child and the parent(s) is another aspect that may influence the cognitive performance of children.

Although the size of the sample was adequate in each of the countries where the study was conducted, it is very important to note that only the sample in Chile, Mexico, Paraguay, Puerto Rico, and Spain were obtained from several regions of the country, while in the remaining countries the sample was collected from only one geographic area. Future studies should expand the sample in other geographical areas of these countries with the objective to have a greater representativeness.

Finally, it is important to keep in mind that the present study was performed with a normal healthy population. Therefore, future studies should be performed with clinical populations to establish the sensitivity and specificity of the TAMV-I.