Normative data for tests of visuo-spatial,visuo-constructional skills,and visual memory for Spanish-speaking adults in the United States

Abstract

BACKGROUND:

The Rey-Osterrieth Complex Figure Test (ROCFT) and the Clock Drawing Test (CDT) are commonly used in clinical practice. The ROCFT measures constructional praxis, visual perception, and visuospatial learning and memory, and the CDT assesses for visuospatial, constructional, and executive difficulties. Several neurological disorders are associated with visuospatial and visuo-constructional impairments, yet reliable normative data accounting for sociodemographic and acculturative variables are scarce for Hispanics living in the U.S.

OBJECTIVE:

To generate normative data for the ROCFT and CDT in a Spanish-speaking adult population living in the U.S.

METHODS:

The sample consisted of 245 cognitively healthy adults recruited from several states in the U.S. Each participant was administered the ROCFT and CDT as part of a larger cognitive battery. The ROCFT and CDT were normed using a Bayesian approach. Age, age², education, sex, acculturation, and language proficiency were included as predictors in the analyses.

RESULTS:

ROCFT performance was associated with education and age, particularly as they interacted with Spanish language proficiency and time spent in the U.S. Education was significantly associated with recall abilities and a lower memory recall on the ROCFT. Age was found to vary depending on a person’s bilingual abilities. Sex did not emerge as a predictor of performance, and it did not interact significantly with other variables.

CONCLUSION:

This is the first study to include acculturation and language proficiency variables in the creation of norms for the assessment of visuo-constructional abilities. This study will have a large impact on the practice of neuropsychology in the U.S.

Keywords

Rey figure visuospatial constructional clock drawing test

1 Introduction

Visuo-constructional skills refer to the ability to perceive and analyze simple or complex visual stimuli and replicate by copying, drawing, and/or assembling (Mervis et al., 1999; Scott & Schoenberg, 2011). Visual memory is the encoding, storage, and retrieval of visual information and these rely heavily on visuospatial functioning. They play a central role in daily life, as they are involved in drawing, dressing, driving/navigation, and other similar tasks. They require adequate visual perception, hand-eye coordination, executive functions (planning and organization), and praxis, and as a result, many cortical and subcortical areas are involved (Scott & Schoenberg, 2011).

Several neurological disorders are associated with visuospatial and visuo-constructional deficits, including visuospatial memory impairments such as traumatic brain injury (Aguerrevere et al., 2014), stroke (Jokinen et al., 2015), Alzheimer’s disease, frontotemporal dementia, Lewy body dementia (Hernández et al., 2022), Parkinson’s disease (Lehrner et al., 2015), and multiple sclerosis (Marasescu et al., 2016). As a result, it is not surprising that visuospatial and visuo-constructional skills are among the common cognitive domains assessed by neuropsychologists worldwide (i.e., Arango-Lasprilla et al., 2017; Egeland et al., 2016; Onida et al., 2019; Olabarrieta-Landa et al., 2016; Monette et al., 2023), including clinicians based in the U.S. (Arango-Lasprilla et al., 2022).

According to a recent survey regarding neuropsychologists who offer their services in Spanish in the U.S., the Rey-Osterrieth Complex Figure Test (ROCFT) was the most frequently used neuropsychological measure to assess visuospatial and visuo-constructional abilities (30%) followed by the clock drawing test (CDT) at 6% (Gasquoine et al., 2021). Rey created the ROCFT in 1941; three years later, Osterrieth developed the current subcategorization of the figure with 18 elements and its scoring procedure (Strauss et al., 2006). While there are various administration procedures, we utilized the most common approach, which is comprised of first having the examinee copy the complex figure. After the copy is completed and the stimulus removed immediate (3 minutes) and delayed (30 minutes) incidental recall trials are administered.

The CDT is a simple and quick to administer test that may be easily incorporated into neuropsychological batteries (Turcotte et al., 2018), and it is a useful screening tool for detecting and discriminating between different types of dementia (Cahn-Weiner et al., 2003). The CDT is divided into two parts: 1) the free drawing condition, where the participant is asked to draw a clock that indicates a particular time, and 2) the less cognitively demanding copy version condition, in which the person is asked to copy a clock. Multiple versions of the CDT exist that vary in administration and scoring guidelines, but according to Siciliano et al. (2016), Rouleau et al. (1992) scoring systems vary in their focus. For example, Sunderland’s (1989) system focuses on scoring more on clock hand placement (with less attention to the presence or absence of numbers), whereas the Wolf-Klein et al. (1989) system present a pre-drawn clock without considering a time setting (Siciliano et al., 2016). The Rouleau et al. (1992) scoring system considers three major components: clock representation, the presence of numbers, and the position of the hands.

Some sociodemographic factors are associated with ROCFT and CDT performance. For instance, younger and higher educated individuals perform better in the ROCFT copy and delayed trials (of the ROCTF) and the free drawing condition (of the CDT) compared to older and less educated individuals (Ponton et al., 1996; Rivera et al., 2015; Palomo et al., 2013; Machulda et al., 2007; Tsatali et al., 2022, Vicente et al., 2021; Tremblay et al., 2015; Turcotte et al., 2018; LaRue et al., 1999; Royall et al., 2003; Menon et al., 2012; O’Bryant et al., 2017). However, the impact of sex is as small or no differences have been reported in some research on the ROFCT (Rivera et al., 2015; Ponton et al., 1996; Palomo et al., 2012; Tsatali et al., 2022) and CDT (Turcotte et al., 2018; O’Bryant et al., 2017), whereas others have found that men outperformed women on the ROCFT (Vicente et al., 2021; Caffarra et al., 2002) and CDT (LaRue et al., 1999).

On non-verbal neuropsychological tests, such as the ROCFT and CDT, cultural biases are associated specifically with language. Nevertheless, cultural variables have been reported to influence performance. For example, Boone et al. (2007) found significant differences in constructional ability (ROCFT copy) between White (non-Hispanic), African-American, Hispanic, and Asian outpatients from the departments of neurology and psychiatry, with Whites and Asians outperforming African Americans. Moreover, they found that outpatients who spoke English as their second language performed significantly better on the ROCFT copy than those who spoke English as a first language. Regarding the CDT, Royall et al. (2003) found that Hispanics with higher acculturation levels performed better on command and copy versions than those who were less acculturated; however, administration language was not significantly associated with CDT performance. On the other hand, LaRue et al. (1999) found significant differences related to language administration among Hispanics living in the U.S., such that those who were administered the test in English scored higher than those who were administered the test in Spanish.

Hispanic neuropsychologists in the U.S. (70%). pointed out that the main problem when utilizing cognitive assessments with patients of Hispanic descent is lack of culturally and linguistically representative normative data. A higher percentage (75%) of neuropsychologists reported using U.S.-based norms when assessing monolingual Spanish-speaking patients, while 73.9% reported using norms developed in Spain and Latin American countries (Arango-Lasprilla et al., 2022). In Spain, Peña-Casanova’s research group developed norms for several cognitive tests for older (Peña-Casanova, Blesa et al., 2009) and younger adults (Peña-Casanova et al., 2012) which included norms for the ROCFT (Peña-Casanova, Gramunt-Fombuena et al., 2009; Palomo et al., 2013). More recently, Calderón-Rubio et al. (2021) developed normative data for the ROCFT for cognitively active older adults in Spain. In 2015, a research group led by Arango-Lasprilla et al. generated norms for various neuropsychological tests designed specifically for adult Spanish speakers from Latin America, including norms for the ROCFT (Rivera et al., 2015). However, existing norms are not suitable for use with Spanish speakers in the U.S. as they do not account for language variations (including level of bilingualism), time living in the U.S., and acculturation, among other variables that may influence test performance.

Some normative data do exist for the ROCFT and CDT for this population, but it is highly circumscribed. For example, for the CDT, norms for adults are available, but only for those over 40 years. LaRue et al. (1999) generated norms for older adults (>65 age) from New Mexico, and Menon et al. (2011) and O’Bryant et al. (2017) created norms for a multi-ethnic bilingual sample (ages 40 or older) including English-Spanish Hispanic bilinguals from the Texas-Mexico border. Regarding the ROCFT, Ponton et al. (1996) developed norms for Hispanics between 16- and 75-years old living in California.

Despite efforts in recent years to publish norms for Spanish speakers, professionals still report difficulty finding appropriately fitting normative data for their Spanish-speaking patients (Arango-Lasprilla et al., 2022). Therefore, the purpose of this study was to generate normative data for the ROCFT and CDT for Spanish speakers in the U.S.

2 Materials and method

2.1 Participants

The initial sample consisted of 253 healthy individuals who were recruited from the U.S. (California, Connecticut, Florida, Oregon, Indiana, New Jersey, Virginia, and Wisconsin). To participate in the study, individuals met the following eligibility criteria: a) be between 18–80 years of age, b) have been living in the U.S. for at least 1 year (12 continuous months), c) self-identify Spanish as their “dominant language,” d) have at least 1 year of formal education, e) be able to read and write in Spanish, f) obtain a score of ≥23 on the Mini-Mental State Examination (MMSE) (Folstein et al., 1975; Villaseñor-Cabrera et al., 2010), g) obtain a score of ≤10 on the Patient Health Questionnaire– 9 (PHQ-9) (Kroenke et al., 2001), and h) obtain a score of ≤4 on the Generalized Anxiety Disorder-7 (GAD-7) (Spitzer et al., 2006).

Individuals were ineligible if any of the following exclusion criteria were present: a) history of a neurodevelopmental disorder, b) history of a learning disorder, c) past or present neurological condition, d) past or present chronic medical condition that might affect cognition (i.e., metabolic syndrome, chronic heart failure, sleep apnea, complications associated with SARS-CoV-2), e) past or present use of psychotropic medications that might affect cognition, f) past or present history of substance abuse or dependence, or g) past or present history of a psychiatric disorder.

Eight participants were excluded from data analysis due to incomplete sociodemographic information, resulting in a final sample of 245 participants. The majority of the sample was women (60.8%, n = 149), the mean age was 41.1 (SD = 14.9), and the mean years of formal education was 15.1 (SD = 4.2). Sociodemographic characteristics have been reported in Rivera et al. (2024).

Each of the institutions obtained their own institutional review board protocol approved to cover the ethical conduct of the study at their own site. All the participants signed an informant consent and were paid 25 U.S. dollars as compensation for their participation on the study.

2.2 Instruments

The ROCFT Figure A was administered. The examinee was prompted to copy the figure, and then recall the figure after 3 (immediate) and 30 (delayed) minutes. The Spanish-language ROCFT manual (Rey, 2009) scoring procedure was followed. The ROCFT comprises 18 elements, with a maximum score of 36 for each of the three tasks (copy, immediate recall, and delayed recall). Two points were awarded if the reproduction was complete and properly placed. One point was awarded if the reproduction is distorted, incomplete but properly placed, or complete but poorly placed; 0.5 points were given if the element was distorted or incomplete and poorly placed. A score of 0 was assigned if the element was absent or unrecognizable (Osterrieth, 1944). Using the copy and recall scores (3 and 30 minutes), memory decay score was estimated using the formula: [(recall score - copy score)/copy score].

Participants were also administered the clock drawing test (CDT). The examinee was asked to draw a clock with hands placed at “10 past 11.” This time setting helps identify executive function deficits (Strauss et al., 2006). In this study, data were generated for the free-drawing and copy scores using the Cacho et al. scoring criteria (1998), with a maximum score of 10.

2.3 Statistical analyses

The detailed statistical analyses used to generate the normative data for these tests are described in Rivera et al. (2024). In summary, copy, immediate recall, and delayed recall of the ROCFT and free drawing and copy clock test scores were scaled using [(maximum test score - participant score)/ maximum test score]. As a result, a score was obtained in terms of proportions. This scaling was performed to find a probabilistic Beta and exponential distribution, which is a continuous probability distribution defined on the interval [0, 1], and is commonly used to model random variables representing proportions or probabilities. Beta distribution was assumed [Y_i ∼ B (μ_i, φ_i)] for immediate recall and delayed recall scores, while for copy was exponential distribution was used. For the decay memory score, a normal distribution was assumed Y_i ∼ N (μ_i, σ²). To determine which variables should be included as predictors, a Bayesian approach was adopted, wherein the available prior information was combined with the information from the data. This combination is summarized in a posterior probability distribution for each unknown quantity in the model. In the variable selection procedure, the unknown quantity is the true model and, for each of the 2^p combinations, where p refers to the number of covariates, a candidate is obtained that may be potentially related to the output (Li & Clyde, 2018).

The full regression models included as predictors: age, age², education (log transformed), sex, the Bidimensional Acculturation Scale for Hispanics (BAS), the Bilingual Dominance Scale (BDS), and all two-way interactions between these variables. Age was centered (age in years – ${\bar{X}}_{Age}$ in the sample) before computing quadratic age to avoid multicollinearity (Kutner et al., 2005). Once the variables were selected, the model estimations were obtained using Exponential, Beta and Normal regression models, respectively. The models can be expressed as follows: $logit (μ_{i}) = β_{0} + β_{1} X_{i}^{(1)} + \dots + β_{p} X_{i}^{(p)}$ for Beta regression, and $μ_{i} = β_{0} + β_{1} X_{i}^{(1)} + \dots + β_{p} X_{i}^{(p)}$ for linear regression. Prior distributions for each of the unknown parameters (β₀, β₁, … β_p) followed a normal distribution centered at 0 and with large variance (i.e., σ² = 1 ×10⁴ and τ = 1 ×10^-3). Vague or non-informative prior distributions were assigned to the models. The Bayesian inference procedure was performed using Markov Chain Monte Carlo methods through the software JAGS (Just Another Gibbs Sampler) and its R interface rjags (Plummer, 2022). For the convergence of three chains for each parameter, a burning period was used. A total of 3000 samples of each posterior distribution was left.

3 Results

3.1 Variable selection

Twenty-nine possible candidate covariates were examined. Table 1 shows the posterior inclusion probability (PIP) values of all covariates in each neuropsychological score. From the PIPs, an elbow plot (x-axis=each covariate, y-axis=PIP values) was made and the substantial change in PIPs was studied to select variables for the regression model for each neuropsychological score (see Table 1). CDT scores showed PIP lower than 0.045, therefore, no covariates were included in the regression model.

Table 1
Posterior inclusion probabilities (PIP) for variable selection by each test score

Covariable Copy Recall 3M Delayed 30M Decay 3M Decay 30M CDT free CDT copy

Intercept 1.000 1.000 1.000 1.000 1.000 1.000 1.000

Age 0.037 0.116 0.061 0.128 0.076 0.002 0.002

Age² 0.022 0.035 0.023 0.024 0.015 0.003 0.003

log(education) 0.407 0.864 0.812 0.731 0.482 0.046 0.046

Sex (Woman) 0.102 0.037 0.032 0.029 0.018 0.002 0.002

Time in U.S. 0.367 0.058 0.143 0.038 0.098 0.003 0.003

BAS-Hispanic 0.067 0.079 0.057 0.04 0.027 0.002 0.002

BDS 0.089 0.056 0.071 0.039 0.026 0.002 0.002

Age*Age² 0.028 0.043 0.021 0.028 0.017 0.002 0.002

Age**log(education) 0.036 0.098 0.054 0.104 0.059 0.002 0.002

AgeSex (Woman) 0.021 0.069 0.055 0.114 0.077 0.002 0.002

AgeTime in U.S. 0.075 0.09 0.03 0.043 0.022 0.002 0.002

AgeBAS-Hispanic 0.036 0.126 0.075 0.155 0.107 0.002 0.002

Age*BDS 0.373 0.624 0.722 0.345 0.418 0.002 0.002

Age²**log(education) 0.022 0.039 0.023 0.028 0.016 0.002 0.002

Age²Sex (Woman) 0.024 0.129 0.02 0.104 0.014 0.003 0.003

Age²Time in U.S. 0.022 0.222 0.05 0.13 0.024 0.003 0.003

Age²BAS-Hispanic 0.022 0.035 0.023 0.024 0.015 0.003 0.003

Age²BDS 0.025 0.093 0.03 0.061 0.016 0.002 0.002

log(education)Sex (Woman) 0.129 0.041 0.038 0.028 0.019 0.002 0.002

log(education)Time in U.S. 0.366 0.052 0.116 0.035 0.073 0.002 0.002

log(education)BAS-Hispanic 0.171 0.112 0.087 0.065 0.042 0.007 0.007

log(education)BDS 0.163 0.059 0.087 0.038 0.034 0.003 0.003

Sex (Woman)Time in U.S. 0.032 0.221 0.155 0.156 0.085 0.002 0.002

Sex (Woman)BAS-Hispanic 0.043 0.031 0.026 0.027 0.017 0.002 0.002

Sex (Woman)BDS 0.069 0.024 0.021 0.022 0.015 0.003 0.003

Time in U.S.BAS-Hispanic 0.035 0.037 0.08 0.032 0.1 0.004 0.004

Time in U.S.BDS 0.04 0.036 0.034 0.055 0.037 0.002 0.002

BAS-Hispanic*BDS 0.091 0.033 0.031 0.03 0.018 0.002 0.002

Covariable	Copy	Recall 3M	Delayed 30M	Decay 3M	Decay 30M	CDT free	CDT copy
Intercept	1.000	1.000	1.000	1.000	1.000	1.000	1.000
Age	0.037	0.116	0.061	0.128	0.076	0.002	0.002
Age²	0.022	0.035	0.023	0.024	0.015	0.003	0.003
log(education)	0.407	0.864	0.812	0.731	0.482	0.046	0.046
Sex (Woman)	0.102	0.037	0.032	0.029	0.018	0.002	0.002
Time in U.S.	0.367	0.058	0.143	0.038	0.098	0.003	0.003
BAS-Hispanic	0.067	0.079	0.057	0.04	0.027	0.002	0.002
BDS	0.089	0.056	0.071	0.039	0.026	0.002	0.002
Age*Age²	0.028	0.043	0.021	0.028	0.017	0.002	0.002
Age*log(education)	0.036	0.098	0.054	0.104	0.059	0.002	0.002
Age*Sex (Woman)	0.021	0.069	0.055	0.114	0.077	0.002	0.002
Age*Time in U.S.	0.075	0.09	0.03	0.043	0.022	0.002	0.002
Age*BAS-Hispanic	0.036	0.126	0.075	0.155	0.107	0.002	0.002
Age*BDS	0.373	0.624	0.722	0.345	0.418	0.002	0.002
Age²*log(education)	0.022	0.039	0.023	0.028	0.016	0.002	0.002
Age²*Sex (Woman)	0.024	0.129	0.02	0.104	0.014	0.003	0.003
Age²*Time in U.S.	0.022	0.222	0.05	0.13	0.024	0.003	0.003
Age²*BAS-Hispanic	0.022	0.035	0.023	0.024	0.015	0.003	0.003
Age²*BDS	0.025	0.093	0.03	0.061	0.016	0.002	0.002
log(education)*Sex (Woman)	0.129	0.041	0.038	0.028	0.019	0.002	0.002
log(education)*Time in U.S.	0.366	0.052	0.116	0.035	0.073	0.002	0.002
log(education)*BAS-Hispanic	0.171	0.112	0.087	0.065	0.042	0.007	0.007
log(education)*BDS	0.163	0.059	0.087	0.038	0.034	0.003	0.003
Sex (Woman)*Time in U.S.	0.032	0.221	0.155	0.156	0.085	0.002	0.002
Sex (Woman)*BAS-Hispanic	0.043	0.031	0.026	0.027	0.017	0.002	0.002
Sex (Woman)*BDS	0.069	0.024	0.021	0.022	0.015	0.003	0.003
Time in U.S.*BAS-Hispanic	0.035	0.037	0.08	0.032	0.1	0.004	0.004
Time in U.S.*BDS	0.04	0.036	0.034	0.055	0.037	0.002	0.002
BAS-Hispanic*BDS	0.091	0.033	0.031	0.03	0.018	0.002	0.002

Note* BAS = Bidimensional Acculturation Scale for Hispanics; BDS = Bilingual Dominance Scale; M = Minutes; CDT = Clock drawing Test.

Table 2 presents the mean, median, mode, and credibility interval (95%) of the posterior distributions for the parameters in each model. The models were implemented using the transformed scores (1- proportions of correct scores) as mentioned in the methods section. The final model for copy showed an age by BDS interaction, such that people over 60 years of age who had higher Spanish proficiency or were balanced bilinguals produced a higher proportion of incorrect scores. However, those with higher English proficiency did not show any change. Also, a logarithmic function of education by time in the U.S. interaction arose such that people with less education and more time living in the U.S. produced a higher proportion of incorrect scores compared to those with less time living in the U.S. However, after 16 years of education, those living more time in the U.S. produced a lower proportion of incorrect scores; in other words, a higher copy score (seeFig. 1A).

Table 2

Mean, median, mode, and credibility interval (95%) for the posterior distributions of the parameters in each model

Test score	Parameters	Mean	Median	Mode	HDI Low	HDI High
Copy	Intercept	0.3254	0.3333	0.229	–0.6402	1.3423
	Age	6.0×10^–4	5.0×10^–4	3.0×10^–4	–0.0106	0.0109
	log(education)	–0.0924	–0.094	–0.0977	–0.471	0.2642
	z-Time in U.S.	0.1827	0.1893	0.2067	–0.9407	1.2626
	z-BDS	–0.0068	–0.0067	–0.0106	–0.1665	0.1543
	Age*z-BDS	0.0010	0.001	8.00×10^–4	–0.0083	0.0115
	log(education)* z-Time in U.S.	–0.0663	–0.0659	–0.0619	–0.4926	0.334
Recall (3 minutes)	Intercept	1.2449	1.2385	1.2460	0.5047	2.0788
	Age	0.0034	0.0034	0.0039	–0.0058	0.0129
	log(education)	–0.5653	–0.5629	–0.5615	–0.8704	–0.3051
	BDS	–1.0×10^–4	–1.0×10^–4	–6.0×10^–4	–8.7×10^–3	9.2×10^–3
	Age*BDS	6.0×10^–4	6.0×10^–4	6.0×10^–4	2.33×10^–5	1.1×10^–3
	φ	7.1552	7.1579	7.2186	5.8760	8.2964
Delayed (30 minutes)	Intercept	1.1855	1.1765	1.1624	0.4762	1.9340
	Age	0.0045	0.0045	0.0047	–0.0053	0.0126
	log(education)	–0.5102	–0.5075	–0.5019	–0.7742	–0.2464
	BDS	–3.3×10^–3	–3.2×10^–3	–2.6×10^–3	–1.2×10^–2	4.7×10^–3
	Age*BDS	6.0×10^–4	6.0×10^–4	6.0×10^–4	1.0×10^–4	1.2×10^–3
	φ	8.0429	8.0158	7.9221	6.6643	9.3419
Memory Decay for 3 minutes	Intercept	–0.6649	–0.6673	–0.6653	–0.8465	–0.4701
	Age	–0.0007	–0.0007	–0.0006	–0.0031	0.0015
	log(education)	0.1082	0.1089	0.1077	0.0373	0.1717
	BDS	–6.0×10^–4	–6.0×10^–4	–7.0×10^–4	–2.7×10^–3	1.5×10^–3
	Age*BDS	–1.0×10^–4	–1.0×10^–4	–1.0×10^–4	–3.0×10^–4	1.6×10^–5
	σ	0.1752	0.1749	0.1746	0.1596	0.1909
Memory Decay for 30 minutes	Intercept	–0.6503	–0.6500	–0.6378	–0.8236	–0.4882
	Age	–9.0×10^–4	–9.0×10^–4	–7.0×10^–4	–3.2×10^–3	1.1×10^–3
	log(education)	0.0937	0.0936	0.0945	0.0367	0.1578
	BDS	3.0×10^–4	3.0×10^–4	2.0×10^–4	–1.7×10^–3	2.4×10^–3
	Age*BDS	–1.0×10^–4	–1.0×10^–4	–1.0×10^–4	–3.0×10^–4	8.9×10^–6
	σ	0.1632	0.1629	0.1616	0.1489	0.1775
CDT Free	λ	92.4317	92.4097	92.5843	79.8897	103.2905
CDT copy	λ	14.9882	14.972	14.8672	13.2561	16.9643

Note* BDS = Bilingual Dominance Scale; HDI = Highest Density Intervals; CDT = Clock Drawing Test; z = rescaling variables in z-distribution.

Fig. 1

Predicted mean score as a function of demographic variable included in the models. Note: BDS = Bilingual Dominance Scale; 3M = 3 minutes.

Regarding recall scores, logarithmic function of education was associated with these scores, such that people with more years of education had a lower proportion of incorrect scores. Also, age by BDS interactions were found for recall at 3 and 30 minutes, such that older age resulted in a higher proportion of incorrect scores, but this proportion differed according to language proficiency. As such, people with higher Spanish proficiency or who spent equal time in both languages generated a higher proportion of incorrect scores compared to those with higher proficiency in English (see Fig. 1B).

Finally, for decay scores, logarithmic function of education was associated, such that people with more years of education had a lower memory decay proportion (see Fig. 1C). Also, age by BDS interactions were found for memory decay at 3 and 30 minutes, whereas older individuals had a higher proportion of memory decay. However, this proportion differed according to language proficiency in that people with higher Spanish proficiency or spent equal time in both languages presented more memory decay compared to those with higher proficiency in English(see Fig. 1D).

For Clock Drawing Test no covariates were found to explain the behavior of the test scores.

3.2 Normative procedure

An expanded explanation of the procedure can be found in Rivera et al. (2024). Briefly, norms (e.g., a percentile score) for the ROCFT were established using a four-step procedure: 1) The expected test score $({\hat{μ}}_{i})$ was computed based on the parameters estimates from the established regression model $({\hat{β}}_{p})$ . Bear in mind that demographic variables were multiplied by 3000 samples of parameters. 2) The probability based on the Exponential, Beta or Normal distribution was estimated for each of the 3000 sample parameters through cumulative distribution function. For CDT test-score λ values were used (see last two rows of Table 2), 3) A mean probability was calculated 4) This probability was multiplied by 100 to interpret it as a percentile.

3.3 User-friendly normative data

To facilitate the understanding of the procedure to obtain the percentile associated with a given score on this test, an example will explain further. Suppose you need to find the probability for a woman, who is 40 years old and has 5 years of education. She obtained a BDS score of 10, a score of 20 on the ROCFT 3-minute memory recall, and 30 ROCFT copy. Let us assume we need to find the percentile for delayed memory recall score [(20–30)/30 = -0.333].

Since the method explained above is complex and can be prone to human error due to the number of required computations, we have created an online calculator. This will facilitate probability calculation as clinicians should only input patient information requested into the calculator (e.g., raw score for the specific test, age, education). This tool is available at https://neuropsychologylearning.com/datos-normativos-archivos-descargables/. Using the calculator and introducing the information requested, this woman would obtain a mean probability score of.815, which is in the 81.5th percentile.

4 Discussion

The purpose of the current study was to generate normative data for the Rey ROCFT and CDT for Spanish speakers in the U.S., taking into account how performance on these neuropsychological tests is impacted both by sociodemographic and acculturative variables. Results showed that performance on the different components of the ROCFT were associated with education and age, particularly as they interacted with Spanish language proficiency and time spent in the U.S. Though there is evidence that cultural variables such as higher acculturation and administration of the test in English results in higher CDT scores (Royall et al., 2003; LaRue et al., 1999), performance on the CDT was not significantly associated with any demographic or cultural variables in the current study.

Education was significantly and positively associated with recall abilities and a lower memory recall on the ROCFT. This is in line with previous research that also found a positive main effect of education on performance on the different components of the ROCFT for individuals across a number of different populations and countries (Rivera et al., 2015; Tremblay et al., 2015; Ponton et al., 1996; Palomo et al., 2013; Vicente et al., 2021). On the copy condition of the ROCFT, the current study also demonstrated a differential effect of education on performance as a function of time spent living in the U.S., such that those with lower education and more time spent living in the U.S. produced more errors and demonstrated lower performance compared to those with less time spent in the U.S. However, the inverse was seen in these results at the 16-year education point, with individuals who had spent more time in the U.S. making fewer errors. Given these differential results, it is critical to incorporate the cultural variable of time spent in the U.S. to qualify the effect of education on the ROCFT.

While prior research has demonstrated lower ROCFT scores and a higher proportion of errors as age increases (Rivera et al., 2015; Tremblay et al., 2015; Ponton et al., 1996; Palomo et al., 2013; Vicente et al., 2021), the current study found that the effect of age varies depending on a person’s linguistic abilities. On the copy subtest, individuals with higher English proficiency showed no significant difference in performance as a function of age. However, for individuals over age 50 with higher Spanish proficiency or those that spent equal time in both languages (balanced bilingualism) there was a stronger effect of age on the number of errors made on the ROCFT. These findings add context to prior research that found that performance on the ROCFT copy is better when an individual’s second language is English as compared to their native language (Boone et al., 2007). On the recall conditions when looking at memory loss after 3 and 30 minutes, a similar moderating effect of bilingualism was found, such that there was a stronger effect of age on recall abilities and level of memory decay for individuals with a higher Spanish proficiency or balanced bilingualism. Thus, the current study generated age-adjusted norms in the context of an individual’s degree of bilingualism.

In the current study, sex did not emerge as a significant predictor of performance and was not moderated by the effects of any other variables. Prior research examining the effect of sex is mixed. Several studies have found that there is no main effect of sex on ROCFT (Tremblay et al., 2015, Palomo et al., 2013) or CDT (O’Bryant et al., 2017; Turcotte et al., 2018) performance. In contrast, others have found a small effect of men outperforming women on the CDT (LaRue et al., 1999) and on different components of the ROCFT, including the recall subtest for Honduran individuals (Rivera et al., 2015) and the delayed copy subtest for Italian individuals (Caffarra et al., 2002). The effect of education on ROCFT copy scores has also been shown to vary as a function of sex (Vicente et al., 2021). The lack of a sex effect in the current study suggests that sex does not need to be controlled for in the calculation of Spanish-speaking individuals predicted ROCFT scores.

4.1 Clinical implications

The results of this study provide normative ROCFT data for Spanish-speaking individuals in the U.S., a population for which there previously were none. It builds upon previous work developing norms for Latin American Spanish-speaking adults and extends it by examining the interactions of demographic and cultural variables (Rivera et al., 2015). Clinically, these results highlight the need to take an intersectional approach in the development of Spanish norms in the U.S. for neuropsychological assessments of visuo-constructional abilities, including not only traditional sociodemographic variables but also aspects of culture that have not typically been considered. Traditional demographic variables such as education and age provide important frameworks that can be further contextualized through the incorporation of cultural measures, such as Spanish language dominance and time spent in the U.S. The interactions between these variables can better inform providers about an individual’s visuo-constructional and visual memory abilities, resulting in more accurate assessment and treatment. As such, neuropsychologists and rehabilitation clinicians are able to build a more nuanced clinical picture of an individual’s cultural background when collecting background information to ensure an accurate assessment of neuropsychological abilities.

4.2 Limitations and future directions

There are several important limitations and future directions to consider with the current study. First, the sample may not accurately represent all Spanish speakers in the U.S., particularly if they live in a state or region that was not included in the data collection. Future research should aim to collect data from a more nationally representative sample. Additionally, individuals were excluded from the current study if they had a history of a neurodevelopmental or learning disorder, a history of substance abuse, or a past or present neurological, psychiatric, or medical condition that may affect cognition. These conditions are likely to influence an individual’s performance on the ROCFT and CDT, and future studies should be conducted in populations with these conditions, as well as illiterate populations. Third, while prior research has found the effects of cultural variables on CDT performance, the current study did not. Further, norms could not be calculated for the CDT because of extreme skewness in its distribution. Future research should further examine the role of these variables on CDT performance and determine if separate Spanish language norms are necessary or if the CDT is a valid measure for Spanish speakers in the U.S.

5 Conclusion

The current study created standardized norms for neuropsychological assessment with the ROCFT and CDT for Spanish-speaking adults in the U.S. Historically, sociodemographic variables, such as education and age, have been a chief component in accurately calculating an individual’s neuropsychological performance. By incorporating critical cultural variables necessary in cross-cultural examinations, such as degree of Spanish and English proficiency and time spent in the U.S., rehabilitation clinicians can take an intersectional approach to neuropsychological assessment and utilize the interactions of these variables to better contextualize performance and subsequently make more accurate diagnoses and treatment recommendations.

Footnotes

Acknowledgments

We extend our sincere gratitude to the institutions and participants whose contributions made this research possible. We furthermore sincerely thank Frances Chiliquinga, M.A., Zara Belo, and Erika Mendez, Yanci Almonte Vargas, B.S. for their assistance in participant recruitment and community engagement. Their contributions were vital to the study’s success.

Declaration of interest

The authors have no conflicts of interest to declare.

Funding

This research was supported in part by grants awarded to Carmen I. Carrión, Psy.D. from the National Institutes of Health P30 AG066508 and CTSA Grant Number UL1 TR001863 from the National Center for Advancing Translational Science (NCATS), a component of the National Institutes of Health (NIH). The contents of this paper are solely the responsibility of the authors and do not necessarily represent the official view of NIH. This research was funded, in part by a grant awarded to Miriam J Rodríguez to the National Institutes of Health/National Institute on Aging grant number L60 AG069322.

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