The Italian Face-Name Association Test (ItFNAT): A preliminary validation of three parallel versions

The Italian Face-Name Association Test (ItFNAT): A preliminary validation of three parallel versions | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Italian Face-Name Association Test (ItFNAT): A preliminary validation of three parallel versions Valerio Manippa, Alessandro Oronzo Caffò, Davide Rivolta This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5912323/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background and Objectives: Associating names with faces is crucial for social interactions and reflects cognitive health. To address the need for reliable tools to assess associative memory, we developed and validated the Italian Face-Name Associative Test (ItFNAT), a tool allows clinicians to monitor cognitive functioning and detect early signs of decline related to aging and neurodegenerative conditions. Materials and Methods: 101 Italian participants (51 females) aged 18-80 years completed the three parallel versions of the ItFNAT, which assessed immediate recall (IR), delayed free recall (DFR), and delayed recall with cues (TDR). ItFNAT was administered alongside other neuropsychological tests to explore its relationship with memory and attention. Results: Cronbach’s alpha revealed high reliability across all three versions of the ItFNAT. MANOVA showed no significant differences between the subscores of the three versions. ANCOVA indicated that schooling significantly influenced DFR scores and had a marginal effect on IR scores, while age and sex did not significantly impact scores. Accordingly, specific cut-offs based on schooling were established. The 3 x 12 correlation matrix demonstrated significant correlations between ItFNAT scores and memory and attention test scores. Discussions: This study introduces the ItFNAT, a test designed to assess cross-modal associative memory. It includes three parallel versions with good internal consistency, and minimal score differences. The subscores—IR, DFR, and TDR—capture various aspects of cognitive functioning, with educational attainment influencing DFR scores. Preliminary cut-offs were established based on schooling, enhancing the test's clinical applicability. Future research should refine its utility for monitoring cognitive changes and neurodegenerative conditions. neuropsychology cognitive assessment neurodegenerative disease Face-Name Associative Memory Exams Figures Figure 1 Introduction The ability to associate a name with a specific face is a critical aspect of social cognition, and it is essential for recognizing and interacting with others in daily life. Difficulties in learning new names or associating the correct name with a familiar face represent a rather common cognitive complaint among older adults (James et al., 2008 ; Weaver Cargin et al., 2008 ). This process requires the integration of complex ecological episodic memory, involving both visual and verbal processing, making it a strong indicator of overall cognitive function. Albeit various tests have been developed to assess cross-modal associative memory for specific experiments (e.g., Sperling et al., 2003 ; Troyer et al., 2011 ), the first standardized version of a face-name memory test was introduced by Rentz et al. ( 2011 ). In this version, participants are required to remember 16 unfamiliar face-name pairs and 16 face-occupation pairs. The test consists of an initial study phase, followed by an immediate free recall trial and a delayed cued recall trial. Today, such tests are commonly referred to as Face-Name Associative Memory Exams (FNAME). Although alternative versions have been developed and standardized since Rentz’s original test, they all adhere to a similar structure typically comprises three phases: face-name encoding (study), an immediate free recall trial, and a delayed recall trial (free and/or cued). Despite differences in administration procedures, numerous studies have demonstrated the efficacy of the FNAME in helping the diagnosis of neurodegenerative diseases such as Alzheimer's Disease (AD) (Rubiño & Andrés, 2018 ; Werheid & Clare, 2007 ), underscoring its importance for early detection. Recently, an alternative version of the FNAME called Face-Name Association Test (FNAT) has been used to evaluate the impact of a session of transcranial alternating current stimulation (tACS) on cognitive functioning in AD and Mild Cognitive Impairment (MCI) due to AD (Benussi et al., 2021 , 2022 ). Their study demonstrated the test's reliability in detecting cognitive improvements resulting from tACS. Unlike the original FNAME developed by Rentz (2011), Benussi et al. ( 2021 ) employed a computer-administered version featuring 20 face-name associations (excluding face-occupation associations) studying, followed by a retrieval phase with faces either presented without cues or, in case of missed/wrong response, with cues. Other versions of the FNAME/FNAT have been used in Italian samples to test various experimental conditions (Bagattini et al., 2019 ; Cotelli et al., 2014 ), but none of these versions were standardized. Given the lack of validated versions in Italy, the use of instruments investigating face-name associative memory is currently limited to experimental settings, despite its potential to provide valuable insights into degenerative processes related to associative memory (Rubiño & Andrés, 2018 ). Furthermore, it remains unclear how this tool assesses cross-modal associative memory or general cognitive functioning; this gap has significant implications for both clinical practice and research. To address this, we have developed and validated three parallel versions of the Italian FNAT (ItFNAT). Each version was administered as part of a neuropsychological battery to evaluate whether ItFNAT scores correlate with commonly used tests that assess memory and attentional processes. Our goal is to standardize ItFNAT procedure and establish preliminary normative data, ensuring its reliability and validity within the Italian context. Additionally, by providing three parallel versions of the ItFNAT, we aim to offer clinicians an easy-to-use tool that can track both normal and pathological aging while minimizing potential learning effects. Materials and Methods Participants One-hundred-one Italian participants (51 F) were included in this study (Age range: 18–80 years, M age : 32.12 years, SD age : 15.34 years; Schooling range: 5–21 years, M schooling : 14.59, SD schooling : 3.30 years) via snowball sampling. In the initial recruitment phase, participants were recruited and randomly assigned to the three versions of the ItFNAT. Subsequently, a targeted selection was applied to ensure a balanced distribution of age, education, and gender across the three parallel versions (see Table 1 ). All participants provided informed consent before completing the procedure. Exclusion criteria were knowing the administered tests, history of neurological diseases, cerebral stroke, epilepsy or epileptic seizures, head injury with loss of consciousness, severe medical conditions or psychiatric disorders, and alcohol or drug abuse. All participants had normal or corrected-to-normal vision. The study was approved by the Ethical Committee of the Institution and was performed following the Helsinki Declaration and its later amendments. Table 1 Descriptive statistics and p-values for age, schooling, and sex distribution across the three versions of the ItFNAT (v1, v2, and v3). The p-values are from one-way ANOVAs for age and schooling, and a chi-square test for sex distribution, indicating no significant differences. ItFNAT v1 (N = 34) ItFNAT v2 (N = 33) ItFNAT v3 (N = 34) M ± SD M ± SD M ± SD p-value Age 32.79 ± 17.52 32.33 ± 15.40 32.33 ± 13.23 .913 Schooling 14.06 ± 3.73 14.18 ± 2.72 15.53 ± 3.29 .128 Sex (N) F = 20, M = 16 F = 16, M = 17 F = 15, M = 19 .461 ItFNAT In each parallel version of the Italian Face-Name Association Test (ItFNAT), we associated 16 black-and-white faces with 16 names. Half of the pairs were male, and the other half were female. Faces were extracted from the neutral faces of the Karolinska Directed Emotional Faces database (Goeleven et al., 2008 ), while names (both correct and distractor used for the cued delay recall) were chosen among the most common name spread within Italian population during 2022 (Istat, 2023). ItFNAT was administered using Microsoft Office PowerPoint, and the responses were collected by post-graduate psychologists using ad-hoc scoring grids. All the materials are free available at: https://doi.org/10.6084/m9.figshare.28113620 . The administration of the test was divided in three phases (trials): During the encoding phase, participants were asked to view and memorize 16 faces, each presented one at a time for 2 seconds. Following this, each face, presented in a different order than the previous presentation, was paired with a name. Participants were asked to read the name aloud to memorize and associate it with the shown face. Participants then moved on to the next face-name pair at their own pace. During the immediate recall phase, participants were shown all faces, one at the time, and asked to recall the name paired with it during the encoding phase (immediate recall). After participant's response, the correct name was shown again, and they were asked to try to memorize it if they had initially missed or failed to recall it. After 15 minutes, during which participants completed other tests that did not require the memorization of verbal information, the delayed recall phase began. In this phase, a face was presented on the left side of the screen, and participants were asked to recall the associated name (delayed free recall). If they miss or fail to recall the name, three choices were shown on the right of the faces (delayed cued recall/recognition): the correct name, a name previously associated with another face (interference), or a name that had not been presented before (intrusion). These administration protocols, including encoding, immediate recall, and delayed free and cued recalls (i.e., recognition), emulate those used in the most widely shared and common long-term memory tests. A score of 1 was assigned for each correct answer, while missed or incorrect responses received a score of 0. Main scores were: Correct Immediate Recall (IR): the number of name-face pairs correctly recalled during the immediate recall trial; Correct Delayed Free Recall (DFR): the number of name-face pairs correctly recalled during the delayed free recall trial; Total Delayed Recall (TDR): the sum of name-face pairs correctly recalled during the delayed recall trial (free and cued). Procedure Participants were administered a neuropsychological battery consisting of the ItFNAT and the Italian version of the following tests: Digit Span (Forward and Backward; Monaco et al., 2013 ): This test assesses short-term and working memory. In the Forward task, participants repeat a sequence of numbers in the same order they were presented. In the Backward task, participants repeat the numbers in the reverse order. The number of digits in each sequence (span length) increases by one digit every two trials. In our study we used the numbers of sequence correctly repeated by the participant, with separate scores for Forward (DS-F) and Backward (DS-B) tasks. Rey Auditory-Verbal Learning Test (RAVLT; Caltagirone et al., 1995 ): This test evaluates episodic memory and learning by having participants listen to a list of words, recall them immediately (immediate recall), and after a delay (delayed recall), assessing both retention and retrieval abilities. The score is the number of words correctly recalled in immediate and delayed recall trials, with additional scores for recognition. Trail Making Test (TMT; Giovagnoli et al., 1996 ): This test measures visual attention and task-switching. It consists of two parts: TMT-A, where participants connect numbered circles in order, and TMT-B, where they alternate between numbers and letters. The score we used in our analyses is the time taken to complete TMT-A and TMT-B, separately. Rey-Osterrieth Complex Figure Test (ROCF; Caffarra et al., 2002 ): This test assesses visuospatial abilities and memory. Participants are asked to copy a complex geometric figure and then reproduce it from memory after a delay. The score is based on the accuracy and completeness of the copied (copy) and recalled (recall) figures, typically using a standardized scoring system. Everyday Memory Questionnaire (EMQ; Calabria et al., 2011 ): This self-report questionnaire evaluates the frequency of memory failures in daily life, providing insights into the practical implications of memory performance. The score is the sum of responses to the questionnaire items, with higher scores indicating more frequent self-reported memory lapses. Stroop Color and Word Test (SCWT; (Scarpina & Tagini, 2017 )): This test, which features various subtests and comes in different versions, assesses attention, cognitive control, and executive function. Specifically, participants are asked to name the color of the ink in which color words are written. This latter can either match or mismatch the color word (e.g., the word “Blue” written in green ink, representing an incongruent condition) requiring the inhibition of the automatic reading response. For our analysis, we used the time taken and the number of errors in the incongruent condition as measures of cognitive control. The order of the tests varied among participants. However, the sequence was designed so that there was about 15-minute interval between the immediate recall and the delayed recall of the RAVLT and the ItFNAT. During this interval, participants completed tests that did not require memorizing materials (i.e., TMT, ROCF copy, EMQ or SCWT). Data Analysis First, a preliminary independent samples t -test was run to examine differences in schooling years and age between sexes, along with a simple correlation analysis between age and schooling years to assess their relationship. Cronbach’s alpha was calculated separately for each version, as well as for the overall test, which incorporated all three versions and their respective subtests. Then, a Multivariate Analysis of Variance (MANOVA) to examine whether ItFNAT scores (IR, DFR, TDR) varied significantly across test versions (v1, v2, v3). Following this, three Analyses of Covariance (ANCOVA) were conducted to assess the influence of participants' sex (as a fixed factor), as well as age and schooling (as continuous covariates), on each of the ItFNAT scores. Based on the ANCOVA results, we refined our preliminary validation procedure by determining the 15th percentile (as a lower normative limit) and the 5th percentile (as a pathological threshold) for each ItFNAT measure, establishing clinically relevant cut-offs. Then, a 3 x 12 Person’s correlation analysis was conducted to examine whether each of the three ItFNAT scores (IR, DFR, TDR) correlated with scores from other cognitive and memory tests (EMQ, DS-F, DS-B, SCWT error, SCWT time, TMT-A, TMT-B, RAVLT immediate recall, delayed recall, recognition, ROCF copy, and recall). This correlation matrix was intended to explore the relationship between ItFNAT scores and performance on these additional cognitive assessments. Instead of using traditional significance thresholds, we applied Bayesian correlation analyses to assess the strength of the relationships (significant threshold set at BF 10 > 10), providing a more nuanced understanding of the correlations observed (Wetzels & Wagenmakers, 2012 ). Results The preliminary analysis revealed no statistically significant differences in age ( p = .272) and schooling ( p = .919) between males and females. However, a significant negative correlation was found between age and schooling (r = − .632, p < .001). The validation analyses revealed an overall Cronbach's alpha for all three versions was .882, with individual values of .935 for v1, .852 for v2, and .868 for v3 (see Table 2 ). The MANOVA, conducted with the three ItFNAT scores as dependent variables and the three ItFNAT versions as fixed factors, showed no significant effect of the version on any of the ItFNAT scores (Wilks' Lambda = .963, F (6, 98) = .618, p = .715). Mean and Standard Deviation for each ItFNAT version and subscore are reported in Table 3 . Table 2 Cronbach's alpha for Immediate Recall (IR), Delayed Free Recall (DFR), and Total Delayed Recall (TDR) scores across the three versions (v1, v2, and v3) of the ItFNAT. In the last colon and in the last row (in light gray) are reported the Cronbach's alpha of the subscore and of the version, while in the dark grey cell are reported the general alpha of the ItFNAT. Cronbach's alpha Version 1 Version 2 Version 3 Overall Subscore Immediate Recall .826 .641 .568 .670 Delayed free Recall .913 .769 .789 .772 Total delayed recall .705 .567 .716 .707 Overall Version .935 .852 .868 .935 (ItFNAT) Table 3 Mean, Standard Deviation (SD) for Immediate Recall (IR), Delayed Free Recall (DFR), and Total Delayed Recall (TDR) scores (number of correctly recalled face-name associations out of a maximum of 16) across the three versions (v1, v2, and v3) of the ItFNAT. Immediate Recall Delayed Free Recall Total Delayed Recall M = 6.02, SD = 3.32 M = 7.26, SD = 4.26 M = 13.48, SD = 2.39 v1 v2 v3 v1 v2 v3 v1 v2 v3 Mean 6.03 6.51 5.59 7.62 7.67 7.15 13.32 13.85 13.38 SD 4.05 3.11 2.65 4.73 3.80 3.70 2.53 2.08 2.74 The three ANCOVA analyses on ItFNAT scores indicated that participant's schooling significantly influenced DFR score (F 1, 97 = 6.285, p = .014) and IR score (F 1, 97 = 3.691, p = .058). Participants’ age and sex did not show significant effects on any ItFNAT score. Based on these findings, the total sample was divided into two groups according to median years of schooling (≤ 14 or > 14 years). Schooling-dependent cut-offs for each ItFNAT measure were then established by calculating the 15th percentile (as an inferior limit) and the 5th percentile (as a pathological score) within each education group (see Table 4 ). Table 4 Descriptive statistics and schooling-dependent cut-off scores (15th and 5th percentiles) for ItFNAT measures (IR, DFR, TDR) stratified by schooling level (< 15 years and ≥ 15 years). Mean and standard deviation (SD) values are presented for each measure (number of correctly recalled face-name associations out of a maximum of 16), alongside the rounded 15th percentile (lower normative limit) and 5th percentile (pathological threshold) cut-offs within each group. Immediate Recall 15th %= 3, 5th %= 2 Delayed Free Recall 15th %= 3, 5th %= 1 Total Delayed Recall 15th %= 11, 5th %= 9 Schooling < 15y Schooling ≥ 15y Schooling < 15y Schooling ≥ 15y Schooling < 15y Schooling ≥ 15y Mean 5.53 6.61 6.20 8.52 12.91 14.17 SD 2.94 3.66 4.02 4.23 2.61 1.90 15th % 3 3 2 4 10 12 5th % 2 2 1 2 7 10 The 3 x 12 Person’s correlation matrix (see Fig. 1 ) demonstrates that ItFNAT scores significantly correlate both with memory and attention test scores. Specifically, the ItFNAT IR score showed a positive correlation with the RAVLT Immediate Recall ( r = .422, BF 10 = 1722) and Delayed Recall ( r = .385, BF 10 = 294). The ItFNAT DFR score showed significant positive correlations with the DS-B score (r = 0.310, BF 10 = 16.98), the ROCFT Recall ( r = .390, BF 10 = 370) and with all the RAVLT scores—Immediate Recall ( r = .434, BF 10 = 3202), Delayed Recall ( r = .512, BF 10 = 326879), and Recognition ( r = .376, BF 10 = 205). Finally, the ItFNAT TDR score positively correlated with all RAVLT scores—Immediate Recall ( r = .399, BF 10 = 554), Delayed Recall ( r = .368, BF 10 = 147), and Recognition ( r = .420, BF 10 = 1511)—and with ROCFT Recall ( r = .327, BF 10 = 30). Conversely it showed negative correlations with the time taken to complete the SCWT ( r = .322, BF 10 = 26), the TMT-A ( r = − .400, BF 10 = 603) and the TMT-B ( r = − .377, BF 10 = 212). Discussion This study presents the first standardized face-name associative test for the Italian sample (ItFNAT), which was designed to assess cross-modal associative memory. The test is freely available ( https://doi.org/10.6084/m9.figshare.28113620 ) and consists of three parallel versions. All versions demonstrated high reliability, with good internal consistency and no significant score differences, underscoring the test's robustness and suitability as a standardized tool within the Italian context. The subscores of the test, namely Immediate Recall (IR), Delayed Free Recall (DFR), and Total Delayed Recall (TDR), offer distinct insights into cognitive functioning. While IR reflects memory performance, DFR and, in particular, TDR, capture broader aspects of general cognitive functioning. This finding is supported by correlation analyses. The validation process enabled the derivation of preliminary cut-off scores for each subscore according to individual schooling, as this appears to be the predominant sociodemographic factor influencing scores. The validation analyses of the ItFNAT demonstrated good overall internal consistency, with Version 1 exhibiting the highest internal consistency. Versions 2 and 3 also showed slightly lower but good levels of internal consistency. The MANOVA analysis revealed no significant effect of version on any of the ItFNAT scores, indicating that all three versions are highly comparable in terms of difficulty. Overall, these data suggest that the three versions of the ItFNAT are reliable and substantially interchangeable. Concerning the subscores, several studies suggested that minimal forgetting can occur after 30 minutes from encoding (McBride & Dosher, 1997 ). This phenomenon was not observed in the present study, indeed the mean DFR score (about 7 out of 16) was slightly higher than the IR score (about 6 out of 16). This phenomenon can be attributed to the shorter interval (15 minutes) between the immediate and delayed recall trials. Additionally, during the immediate recall trial, the correct face-name association was re-presented to participants regardless of their IR accuracy response, thereby reinforcing the name-face association. The use of cues (i.e., three alternative names) when participants were unable to freely recall a name during the delayed recall trials significantly enhanced performance, increasing the number of correctly recalled associations from approximately 7 (mean DFR score) to about 13 (mean TDR score) out of 16. This finding is consistent with the efficacy of associative prompts, which leverage recognition processes, in enhancing free memory recall among the general population (Tulving & Tulving, 1985 ). The significant improvement with cues also highlights their potential in distinguishing retrieval versus encoding deficits, aiding differential diagnosis of AD and other conditions. In AD, limited cue benefits suggest encoding issues (Flicker et al., 1991 ), whereas larger improvements in conditions like frontotemporal dementia (Pasquier et al., 2001 ) or neurodevelopmental disorders (e.g., Attention-Deficit/Hyperactivity Disorder (Sjöwall et al., 2013 )) and indicate retrieval deficits. Cue-based strategies could further enhance cognitive rehabilitation in early AD (Clare & Woods, 2004 ) and help monitor progression in neurodegenerative disorders. The three ANCOVA analyses indicated that the participants' educational attainment had a significant influence on the DFR score and a marginal effect on the IR score. Participants with higher levels of education reported higher scores. No significant effects were observed for age or sex on any of the ItFNAT scores. These findings align with the existing literature, which suggests that individuals with higher educational attainment may possess enhanced associative memory capabilities or employ more effective encoding strategies. This is also consistent with findings of previous research linking higher education level to improved performance on cognitive tasks (Le Carret et al., 2003 ) and its neuroprotective role (Brayne et al., 2010 ). In general, an IR score ≤ 2, a DFR score ≤ 1, and a TDS ≤ 9 are indicative of a pathological outcome, with the severity of this outcome depending on the number of schooling years (lower on higher than 15 years). However, given the global increase in educational attainment (Stern, 2002 ), a negative correlation between schooling years and age was observed in the present study's sample. To ensure more precise assessments, future studies should stratify the sample; this will allow for more precise evaluation of individuals with varying educational backgrounds, thereby reducing any potential influence of educational disparities on cognitive evaluations. Results of the 3 x 12 Person’s correlation matrix (Fig. 1 ) reveal significant correlations between ItFNAT scores and various memory and attention test performances, underscoring its utility as a comprehensive tool for assessing face-name associative memory. Specifically, the ItFNAT IR score demonstrated positive correlations with RAVLT Immediate Recall and Delayed Recall, indicating that this measure effectively reflects episodic memory encoding processes. The ItFNAT DFR score exhibited an even broader pattern of positive correlations, encompassing all RAVLT scores, the DS-B, and the ROCFT Recall score. This finding underlines the role of DFR as a robust indicator of cross-modal memory and working memory and its integration with other established cognitive assessments. Notably, the TDR subscore demonstrated negative correlations with the time required to complete the SCWT, TMT-A, and TMT-B, highlighting its capacity to not only assess memory processes but also elements of attentional performance speed. This finding suggests the potential of TDR to extend beyond specific memory measures to reflect aspects of general cognitive functioning. Conversely, any ItFNAT subscore exhibited correlations with ROCF Copy, DS-F, EMQ scores, or SCWT errors. Results indicate that ItFNAT provides a progression from more selective assessments of memory encoding (e.g., IR) to measures such as DFR and TDR, which integrate broader cognitive functions (working memory and attentive/processing speed, respectively). This is consistent with the literature on cognitive aging, which underscores the critical role of processing speed in facilitating efficient encoding and retrieval of information (Nettelbeck & Wilson, 2012 ), particularly in older adults (Salthouse, 1996 ). The strength of these correlations supports the effectiveness of the ItFNAT in evaluating associative memory while also demonstrating its relationship with overall cognitive functioning (Papp et al., 2014 ). The Bayesian factor analyses provide substantial evidence (BF10 > 10) for the observed relationships, thereby bolstering confidence in the validity of these findings. Limitations, Future Research and Conclusions Notwithstanding the encouraging results, this preliminary validation study is not without limitations. For instance, the IR score of Version 3 and the TDR score of Version 2 exhibited very low internal consistency. This may be partially attributed to the dichotomous scoring method (correct vs. incorrect) employed, the low number of items (16) and the relatively small sample size of approximately 33 individuals per version. A larger sample size could help refine these measures. Additionally, the assessment of test-retest reliability is crucial to evaluate the consistency of the tool over time. Furthermore, while the sample size was adequate for preliminary validation, it did not fully capture the variability in memory performance across a broader range of demographics, particularly among older adults and individuals with lower educational attainment. Future research could enhance the clinical applicability of the ItFNAT by expanding normative data to include a wider range of ages and educational backgrounds, thereby refining cut-off scores for different groups or providing correction grids. Finally, while the present study focused exclusively on correct responses, it is possible that participants may choose not to respond (i.e., "missed") or provide incorrect answers. These latter incorrect answers can be intrusive (associating to a face a name never encountered during the former phases) or interfering (associating a face with a name that was incorrect but presented during the former phases). The analysis of these error types could yield valuable insights, which could assist in distinguishing between different diagnostic categories in the context of neurodegenerative or neurodevelopmental conditions. Future studies could explore whether specific response patterns are linked to distinct conditions, offering a deeper understanding of underlying cognitive processes and their relationship to different clinical profiles. In conclusion, this study provides a standardized version of a FNAT validated on an Italian population. The ItFNAT is a rapid instrument designed to evaluate cognitive functioning with a particular emphasis on cross-modal associative memory. A significant strength of the ItFNAT is its availability in three parallel versions, all of which are freely accessible online. These versions have been developed to minimize potential learning effects when employed repeatedly for the purpose of monitoring cognitive changes over time. This feature is particularly advantageous in clinical trials, where repeated assessments are a common practice. As neurodegenerative diseases, including Alzheimer's disease, continue to rise on a global scale, standardized tools such as the ItFNAT will play a pivotal role in the early detection of cognitive changes (Blackwell et al., 2004 ; Rentz et al., 2011 ), guiding both clinical diagnosis and research into therapeutic interventions. References Bagattini C, Mutanen TP, Fracassi C, Manenti R, Cotelli M, Ilmoniemi RJ, Miniussi C, Bortoletto M (2019) Predicting Alzheimer’s disease severity by means of TMS–EEG coregistration. Neurobiol Aging 80:38–45. https://doi.org/10.1016/j.neurobiolaging.2019.04.008 Benussi A, Cantoni V, Cotelli MS, Cotelli M, Brattini C, Datta A, Thomas C, Santarnecchi E, Pascual-Leone A, Borroni B (2021) Exposure to gamma tACS in Alzheimer’s disease: A randomized, double-blind, sham-controlled, crossover, pilot study. Brain Stimul 14(3):531–540 Benussi A, Cantoni V, Grassi M, Brechet L, Michel CM, Datta A, Thomas C, Gazzina S, Cotelli MS, Bianchi M, Premi E, Gadola Y, Cotelli M, Pengo M, Perrone F, Scolaro M, Archetti S, Solje E, Padovani A, Borroni B (2022) Increasing Brain Gamma Activity Improves Episodic Memory and Restores Cholinergic Dysfunction in Alzheimer’s Disease. Ann Neurol 92(2):322–334. https://doi.org/10.1002/ana.26411 Blackwell AD, Sahakian BJ, Vesey R, Semple JM, Robbins TW, Hodges JR (2004) Detecting dementia: Novel neuropsychological markers of preclinical Alzheimer’s disease. Dement Geriatr Cogn Disord 17(1–2):42–48. https://doi.org/10.1159/000074081 Brayne C, Ince PG, Keage HA, McKeith IG, Matthews FE, Polvikoski T, Sulkava R (2010) Education, the brain and dementia: Neuroprotection or compensation? EClipSE Collaborative Members. Brain 133(8):2210–2216 Caffarra P, Vezzadini G, Dieci F, Zonato F, Venneri A (2002) Rey-Osterrieth complex figure: Normative values in an Italian population sample. Neurol Sci 22:443–447 Calabria M, Manenti R, Rosini S, Zanetti O, Miniussi C, Cotelli M (2011) Objective and subjective memory impairment in elderly adults: A revised version of the Everyday Memory Questionnaire. Aging Clin Exp Res 23(1):67–73. https://doi.org/10.1007/BF03324954 Caltagirone C, Gainotti G, Carlesimo GA, Parnetti L (1995) Batteria per la valutazione del deterioramento mentale: I. Descrizione di uno strumento di diagnosi neuropsicologica. [The Mental Deterioration Battery: I. Description of a neuropsychological diagnostic instrument]. Archivio di Psicologia Neurologia e Psichiatria 56(4):461–470 Clare L, Woods RT (2004) Cognitive training and cognitive rehabilitation for people with early-stage Alzheimer’s disease: A review. Neuropsychological Rehabilitation 14(4):385–401. https://doi.org/10.1080/09602010443000074 Cotelli M, Manenti R, Brambilla M, Petesi M, Rosini S, Ferrari C, Zanetti O, Miniussi C (2014) Anodal tDCS during face-name associations memory training in Alzheimer’s patients. Frontiers in Aging Neuroscience , 6 . https://doi.org/10.3389/fnagi.2014.00038 Flicker C, Ferris SH, Reisberg B (1991) Mild cognitive impairment in the elderly: Predictors of dementia. Neurology 41(7):1006–1009. https://doi.org/10.1212/wnl.41.7.1006 Giovagnoli AR, Pesce D, Mascheroni M, Simoncelli S, Laiacona M, M., Capitani E (1996) Trail making test: Normative values from 287 normal adult controls. Italian J Neurol Sci 17(4):305–309. https://doi.org/10.1007/BF01997792 Goeleven E, De Raedt R, Leyman L, Verschuere B (2008) The Karolinska Directed Emotional Faces: A validation study. Cognition Emot 22(6):1094–1118. https://doi.org/10.1080/02699930701626582 James LE, Fogler KA, Tauber SK (2008) Recognition memory measures yield disproportionate effects of aging on learning face-name associations. Psychol Aging 23(3):657–664. https://doi.org/10.1037/a0013008 Le Carret N, Lafont S, Letenneur L, Dartigues J-F, Mayo W, Fabrigoule C (2003) The Effect of Education on Cognitive Performances and Its Implication for the Constitution of the Cognitive Reserve. Dev Neuropsychol 23(3):317–337. https://doi.org/10.1207/S15326942DN2303_1 McBride DM, Dosher BA (1997) A comparison of forgetting in an implicit and explicit memory task. J Exp Psychol Gen 126(4):371 Monaco M, Costa A, Caltagirone C, Carlesimo GA (2013) Forward and backward span for verbal and visuo-spatial data: Standardization and normative data from an Italian adult population. Neurol Sci 34:749–754 Nettelbeck T, Wilson C (2012) Speed of information processing and cognition. In Ellis’ handbook of mental deficiency, psychological theory and research (pp. 245–274). Routledge. https://www.taylorfrancis.com/chapters/edit/10.4324/9780203052846-13/speed-information-processing-cognition-ted-nettelbeck-carlene-wilson Papp KV, Amariglio RE, Dekhtyar M, Roy K, Wigman S, Bamfo R, Sherman J, Sperling RA, Rentz DM (2014) Development of a Psychometrically Equivalent Short Form of the Face–Name Associative Memory Exam for use Along the Early Alzheimer’s Disease Trajectory. Clin Neuropsychol 28(5):771–785. https://doi.org/10.1080/13854046.2014.911351 Pasquier F, Grymonprez L, Lebert F, Van der Linden M (2001) Memory Impairment Differs in Frontotemporal Dementia and Alzhemier’s Disease. Neurocase 7(2):161–171. https://doi.org/10.1093/neucas/7.2.161 Rentz DM, Amariglio RE, Becker JA, Frey M, Olson LE, Frishe K, Carmasin J, Maye JE, Johnson KA, Sperling RA (2011) Face-name associative memory performance is related to amyloid burden in normal elderly. Neuropsychologia 49(9):2776–2783. https://doi.org/10.1016/j.neuropsychologia.2011.06.006 Rubiño J, Andrés P (2018) The Face-Name Associative Memory Test as a Tool for Early Diagnosis of Alzheimer’s Disease. Frontiers in Psychology , 9 . https://doi.org/10.3389/fpsyg.2018.01464 Salthouse TA (1996) The processing-speed theory of adult age differences in cognition. Psychol Rev 103(3):403 Scarpina F, Tagini S (2017) The Stroop Color and Word Test. Frontiers in Psychology , 8 . https://www.frontiersin.org/articles/ 10.3389/fpsyg.2017.00557 Sjöwall D, Roth L, Lindqvist S, Thorell LB (2013) Multiple deficits in ADHD: Executive dysfunction, delay aversion, reaction time variability, and emotional deficits. J Child Psychol Psychiatry Allied Discip 54(6):619–627. https://doi.org/10.1111/jcpp.12006 Sperling RA, Bates JF, Chua EF, Cocchiarella AJ, Rentz DM, Rosen BR, Schacter DL, Albert MS (2003) fMRI studies of associative encoding in young and elderly controls and mild Alzheimer’s disease. J Neurol Neurosurg Psychiatry 74(1):44–50. https://doi.org/10.1136/jnnp.74.1.44 . Scopus Stern Y (2002) What is cognitive reserve? Theory and research application of the reserve concept. J Int Neuropsychol Soc 8(3):448–460 Troyer AK, D’Souza NA, Vandermorris S, Murphy KJ (2011) Age-related differences in associative memory depend on the types of associations that are formed. Neuropsychol Dev Cogn B Aging Neuropsychol Cogn 18(3):340–352. https://doi.org/10.1080/13825585.2011.553273 Tulving E, Tulving E (1985) Elements of Episodic Memory. Oxford University Press Weaver Cargin J, Collie A, Masters C, Maruff P (2008) The nature of cognitive complaints in healthy older adults with and without objective memory decline. J Clin Exp Neuropsychol 30(2):245–257. https://doi.org/10.1080/13803390701377829 Werheid K, Clare L (2007) Are Faces Special in Alzheimer’s Disease? Cognitive Conceptualisation, Neural Correlates, and Diagnostic Relevance of Impaired Memory for Faces and Names. Cortex 43(7):898–906. https://doi.org/10.1016/S0010-9452(08)70689-0 Wetzels R, Wagenmakers E-J (2012) A default Bayesian hypothesis test for correlations and partial correlations. Psychon Bull Rev 19(6):1057–1064. https://doi.org/10.3758/s13423-012-0295-x Additional Declarations The authors declare no competing interests. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5912323","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":407668401,"identity":"60494a8c-825c-4c56-af16-3c6d197f288b","order_by":0,"name":"Valerio Manippa","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBUlEQVRIiWNgGAWjYFAC5gYGBgMI8wAQyzEwMLYBaQk8WhhRtRjDtODRA9KCBBKBXDYGfNYYHD/Y+LiiwIZBt/3swcOFO+zSN9xubnvwg8GiDqeWM4nNhmcM0hjMzuQlHJ55Jjl3w52D7YY9eBwm2ZDYJtlgcJjB7ECOwWHeNubcDTcS2yR48Gnpf9j+E6zl/BuQlvp0A6AWyT94tPBLJLYxgrXcANtyOAGkRRqfLfwSD5uBDkvjMbsBtGXmmeOGM28kthvLGEhINuDQwsaffPBjwx8bObPzOcafC3dUy/PdSH/28E1FHT8uW2CAB0QwI+LIgJAGKGBGi9ZRMApGwSgYBWAAAOTyWJg8XXwDAAAAAElFTkSuQmCC","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Valerio","middleName":"","lastName":"Manippa","suffix":""},{"id":407668402,"identity":"83e07157-b4a2-4179-b705-03c476603ae5","order_by":1,"name":"Alessandro Oronzo Caffò","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Alessandro","middleName":"Oronzo","lastName":"Caffò","suffix":""},{"id":407668403,"identity":"6419404a-fcf8-44f7-9d8b-42ede995aa23","order_by":2,"name":"Davide Rivolta","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Davide","middleName":"","lastName":"Rivolta","suffix":""}],"badges":[],"createdAt":"2025-01-27 12:42:34","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-5912323/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5912323/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":75085715,"identity":"e5e12c54-6a79-4f35-84c9-76e5375c2b4f","added_by":"auto","created_at":"2025-01-30 10:02:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":394739,"visible":true,"origin":"","legend":"\u003cp\u003eThe 3 x 12 Person’s correlation matrix with the \u003cem\u003er \u003c/em\u003evalue reported for each pairwise. Single asterisk (*) indicate a BF10\u0026gt;10, while double asterisk (**) indicates BF10\u0026gt;100.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5912323/v1/5eb91d26c55bbdccbc1d97fb.png"},{"id":75086562,"identity":"fe6e283c-d7e7-41e0-96f5-730045839039","added_by":"auto","created_at":"2025-01-30 10:11:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":993509,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5912323/v1/443cad5e-fa16-4aa4-abe0-454a87792530.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eThe Italian Face-Name Association Test (ItFNAT): A preliminary validation of three parallel versions\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe ability to associate a name with a specific face is a critical aspect of social cognition, and it is essential for recognizing and interacting with others in daily life. Difficulties in learning new names or associating the correct name with a familiar face represent a rather common cognitive complaint among older adults (James et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Weaver Cargin et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). This process requires the integration of complex ecological episodic memory, involving both visual and verbal processing, making it a strong indicator of overall cognitive function. Albeit various tests have been developed to assess cross-modal associative memory for specific experiments (e.g., Sperling et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Troyer et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), the first standardized version of a face-name memory test was introduced by Rentz et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). In this version, participants are required to remember 16 unfamiliar face-name pairs and 16 face-occupation pairs. The test consists of an initial study phase, followed by an immediate free recall trial and a delayed cued recall trial. Today, such tests are commonly referred to as Face-Name Associative Memory Exams (FNAME). Although alternative versions have been developed and standardized since Rentz\u0026rsquo;s original test, they all adhere to a similar structure typically comprises three phases: face-name encoding (study), an immediate free recall trial, and a delayed recall trial (free and/or cued).\u003c/p\u003e \u003cp\u003eDespite differences in administration procedures, numerous studies have demonstrated the efficacy of the FNAME in helping the diagnosis of neurodegenerative diseases such as Alzheimer's Disease (AD) (Rubi\u0026ntilde;o \u0026amp; Andr\u0026eacute;s, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Werheid \u0026amp; Clare, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), underscoring its importance for early detection. Recently, an alternative version of the FNAME called Face-Name Association Test (FNAT) has been used to evaluate the impact of a session of transcranial alternating current stimulation (tACS) on cognitive functioning in AD and Mild Cognitive Impairment (MCI) due to AD (Benussi et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Their study demonstrated the test's reliability in detecting cognitive improvements resulting from tACS. Unlike the original FNAME developed by Rentz (2011), Benussi et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) employed a computer-administered version featuring 20 face-name associations (excluding face-occupation associations) studying, followed by a retrieval phase with faces either presented without cues or, in case of missed/wrong response, with cues. Other versions of the FNAME/FNAT have been used in Italian samples to test various experimental conditions (Bagattini et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Cotelli et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), but none of these versions were standardized.\u003c/p\u003e \u003cp\u003eGiven the lack of validated versions in Italy, the use of instruments investigating face-name associative memory is currently limited to experimental settings, despite its potential to provide valuable insights into degenerative processes related to associative memory (Rubi\u0026ntilde;o \u0026amp; Andr\u0026eacute;s, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Furthermore, it remains unclear how this tool assesses cross-modal associative memory or general cognitive functioning; this gap has significant implications for both clinical practice and research. To address this, we have developed and validated three parallel versions of the Italian FNAT (ItFNAT). Each version was administered as part of a neuropsychological battery to evaluate whether ItFNAT scores correlate with commonly used tests that assess memory and attentional processes. Our goal is to standardize ItFNAT procedure and establish preliminary normative data, ensuring its reliability and validity within the Italian context. Additionally, by providing three parallel versions of the ItFNAT, we aim to offer clinicians an easy-to-use tool that can track both normal and pathological aging while minimizing potential learning effects.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eOne-hundred-one Italian participants (51 F) were included in this study (Age range: 18\u0026ndash;80 years, \u003cem\u003eM\u003c/em\u003e\u003csub\u003eage\u003c/sub\u003e: 32.12 years, \u003cem\u003eSD\u003c/em\u003e\u003csub\u003eage\u003c/sub\u003e: 15.34 years; Schooling range: 5\u0026ndash;21 years, \u003cem\u003eM\u003c/em\u003e\u003csub\u003eschooling\u003c/sub\u003e: 14.59, \u003cem\u003eSD\u003c/em\u003e\u003csub\u003eschooling\u003c/sub\u003e: 3.30 years) via snowball sampling. In the initial recruitment phase, participants were recruited and randomly assigned to the three versions of the ItFNAT. Subsequently, a targeted selection was applied to ensure a balanced distribution of age, education, and gender across the three parallel versions (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). All participants provided informed consent before completing the procedure. Exclusion criteria were knowing the administered tests, history of neurological diseases, cerebral stroke, epilepsy or epileptic seizures, head injury with loss of consciousness, severe medical conditions or psychiatric disorders, and alcohol or drug abuse. All participants had normal or corrected-to-normal vision. The study was approved by the Ethical Committee of the Institution and was performed following the Helsinki Declaration and its later amendments.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics and p-values for age, schooling, and sex distribution across the three versions of the ItFNAT (v1, v2, and v3). The p-values are from one-way ANOVAs for age and schooling, and a chi-square test for sex distribution, indicating no significant differences.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eItFNAT v1 (N\u0026thinsp;=\u0026thinsp;34)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eItFNAT v2 (N\u0026thinsp;=\u0026thinsp;33)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eItFNAT v3 (N\u0026thinsp;=\u0026thinsp;34)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eM\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eM\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eM\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.79\u0026thinsp;\u0026plusmn;\u0026thinsp;17.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.33\u0026thinsp;\u0026plusmn;\u0026thinsp;15.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.33\u0026thinsp;\u0026plusmn;\u0026thinsp;13.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.913\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSchooling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.06\u0026thinsp;\u0026plusmn;\u0026thinsp;3.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.18\u0026thinsp;\u0026plusmn;\u0026thinsp;2.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.53\u0026thinsp;\u0026plusmn;\u0026thinsp;3.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.128\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (N)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF\u0026thinsp;=\u0026thinsp;20, M\u0026thinsp;=\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF\u0026thinsp;=\u0026thinsp;16, M\u0026thinsp;=\u0026thinsp;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eF\u0026thinsp;=\u0026thinsp;15, M\u0026thinsp;=\u0026thinsp;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.461\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eItFNAT\u003c/h3\u003e\n\u003cp\u003eIn each parallel version of the Italian Face-Name Association Test (ItFNAT), we associated 16 black-and-white faces with 16 names. Half of the pairs were male, and the other half were female. Faces were extracted from the neutral faces of the Karolinska Directed Emotional Faces database (Goeleven et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), while names (both correct and distractor used for the cued delay recall) were chosen among the most common name spread within Italian population during 2022 (Istat, 2023). ItFNAT was administered using Microsoft Office PowerPoint, and the responses were collected by post-graduate psychologists using ad-hoc scoring grids. All the materials are free available at: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.6084/m9.figshare.28113620\u003c/span\u003e\u003cspan address=\"10.6084/m9.figshare.28113620\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe administration of the test was divided in three phases (trials):\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eDuring the \u003cem\u003eencoding\u003c/em\u003e phase, participants were asked to view and memorize 16 faces, each presented one at a time for 2 seconds. Following this, each face, presented in a different order than the previous presentation, was paired with a name. Participants were asked to read the name aloud to memorize and associate it with the shown face. Participants then moved on to the next face-name pair at their own pace.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eDuring the \u003cem\u003eimmediate recall\u003c/em\u003e phase, participants were shown all faces, one at the time, and asked to recall the name paired with it during the encoding phase (immediate recall). After participant's response, the correct name was shown again, and they were asked to try to memorize it if they had initially missed or failed to recall it.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAfter 15 minutes, during which participants completed other tests that did not require the memorization of verbal information, the \u003cem\u003edelayed recall\u003c/em\u003e phase began. In this phase, a face was presented on the left side of the screen, and participants were asked to recall the associated name (delayed free recall). If they miss or fail to recall the name, three choices were shown on the right of the faces (delayed cued recall/recognition): the correct name, a name previously associated with another face (interference), or a name that had not been presented before (intrusion).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThese administration protocols, including encoding, immediate recall, and delayed free and cued recalls (i.e., recognition), emulate those used in the most widely shared and common long-term memory tests. A score of 1 was assigned for each correct answer, while missed or incorrect responses received a score of 0. Main scores were:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eCorrect Immediate Recall (IR): the number of name-face pairs correctly recalled during the immediate recall trial;\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eCorrect Delayed Free Recall (DFR): the number of name-face pairs correctly recalled during the delayed free recall trial;\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eTotal Delayed Recall (TDR): the sum of name-face pairs correctly recalled during the delayed recall trial (free and cued).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e\n\u003ch3\u003eProcedure\u003c/h3\u003e\n\u003cp\u003eParticipants were administered a neuropsychological battery consisting of the ItFNAT and the Italian version of the following tests:\u003c/p\u003e \u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eDigit Span (Forward and Backward; Monaco et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2013\u003c/span\u003e): This test assesses short-term and working memory. In the Forward task, participants repeat a sequence of numbers in the same order they were presented. In the Backward task, participants repeat the numbers in the reverse order. The number of digits in each sequence (span length) increases by one digit every two trials. In our study we used the numbers of sequence correctly repeated by the participant, with separate scores for Forward (DS-F) and Backward (DS-B) tasks.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eRey Auditory-Verbal Learning Test (RAVLT; Caltagirone et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1995\u003c/span\u003e): This test evaluates episodic memory and learning by having participants listen to a list of words, recall them immediately (immediate recall), and after a delay (delayed recall), assessing both retention and retrieval abilities. The score is the number of words correctly recalled in immediate and delayed recall trials, with additional scores for recognition.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eTrail Making Test (TMT; Giovagnoli et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1996\u003c/span\u003e): This test measures visual attention and task-switching. It consists of two parts: TMT-A, where participants connect numbered circles in order, and TMT-B, where they alternate between numbers and letters. The score we used in our analyses is the time taken to complete TMT-A and TMT-B, separately.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eRey-Osterrieth Complex Figure Test (ROCF; Caffarra et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2002\u003c/span\u003e): This test assesses visuospatial abilities and memory. Participants are asked to copy a complex geometric figure and then reproduce it from memory after a delay. The score is based on the accuracy and completeness of the copied (copy) and recalled (recall) figures, typically using a standardized scoring system.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eEveryday Memory Questionnaire (EMQ; Calabria et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2011\u003c/span\u003e): This self-report questionnaire evaluates the frequency of memory failures in daily life, providing insights into the practical implications of memory performance. The score is the sum of responses to the questionnaire items, with higher scores indicating more frequent self-reported memory lapses.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eStroop Color and Word Test (SCWT; (Scarpina \u0026amp; Tagini, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)): This test, which features various subtests and comes in different versions, assesses attention, cognitive control, and executive function. Specifically, participants are asked to name the color of the ink in which color words are written. This latter can either match or mismatch the color word (e.g., the word \u0026ldquo;Blue\u0026rdquo; written in green ink, representing an incongruent condition) requiring the inhibition of the automatic reading response. For our analysis, we used the time taken and the number of errors in the incongruent condition as measures of cognitive control.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e \u003cp\u003eThe order of the tests varied among participants. However, the sequence was designed so that there was about 15-minute interval between the immediate recall and the delayed recall of the RAVLT and the ItFNAT. During this interval, participants completed tests that did not require memorizing materials (i.e., TMT, ROCF copy, EMQ or SCWT).\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eFirst, a preliminary independent samples \u003cem\u003et\u003c/em\u003e-test was run to examine differences in schooling years and age between sexes, along with a simple correlation analysis between age and schooling years to assess their relationship. Cronbach\u0026rsquo;s alpha was calculated separately for each version, as well as for the overall test, which incorporated all three versions and their respective subtests. Then, a Multivariate Analysis of Variance (MANOVA) to examine whether ItFNAT scores (IR, DFR, TDR) varied significantly across test versions (v1, v2, v3). Following this, three Analyses of Covariance (ANCOVA) were conducted to assess the influence of participants' sex (as a fixed factor), as well as age and schooling (as continuous covariates), on each of the ItFNAT scores. Based on the ANCOVA results, we refined our preliminary validation procedure by determining the 15th percentile (as a lower normative limit) and the 5th percentile (as a pathological threshold) for each ItFNAT measure, establishing clinically relevant cut-offs. Then, a 3 x 12 Person\u0026rsquo;s correlation analysis was conducted to examine whether each of the three ItFNAT scores (IR, DFR, TDR) correlated with scores from other cognitive and memory tests (EMQ, DS-F, DS-B, SCWT error, SCWT time, TMT-A, TMT-B, RAVLT immediate recall, delayed recall, recognition, ROCF copy, and recall). This correlation matrix was intended to explore the relationship between ItFNAT scores and performance on these additional cognitive assessments. Instead of using traditional significance thresholds, we applied Bayesian correlation analyses to assess the strength of the relationships (significant threshold set at BF\u003csub\u003e10\u003c/sub\u003e\u0026thinsp;\u0026gt;\u0026thinsp;10), providing a more nuanced understanding of the correlations observed (Wetzels \u0026amp; Wagenmakers, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThe \u003cem\u003epreliminary analysis\u003c/em\u003e revealed no statistically significant differences in age (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.272) and schooling (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.919) between males and females. However, a significant negative correlation was found between age and schooling (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.632, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001).\u003c/p\u003e \u003cp\u003eThe \u003cem\u003evalidation analyses\u003c/em\u003e revealed an overall Cronbach's alpha for all three versions was .882, with individual values of .935 for v1, .852 for v2, and .868 for v3 (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The MANOVA, conducted with the three ItFNAT scores as dependent variables and the three ItFNAT versions as fixed factors, showed no significant effect of the version on any of the ItFNAT scores (Wilks' Lambda\u0026thinsp;=\u0026thinsp;.963, F\u003csub\u003e(6, 98)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;.618, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.715). Mean and Standard Deviation for each ItFNAT version and subscore are reported in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCronbach's alpha for Immediate Recall (IR), Delayed Free Recall (DFR), and Total Delayed Recall (TDR) scores across the three versions (v1, v2, and v3) of the ItFNAT. In the last colon and in the last row (in light gray) are reported the Cronbach's alpha of the subscore and of the version, while in the dark grey cell are reported the general alpha of the ItFNAT.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eCronbach's alpha\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eVersion 1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eVersion 2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eVersion 3\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eOverall Subscore\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eImmediate Recall\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.826\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.641\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.568\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e.670\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eDelayed free Recall\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.913\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.769\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.789\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e.772\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eTotal delayed recall\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.716\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e.707\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eOverall Version\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e.935\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e.852\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e.868\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e.935 (ItFNAT)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean, Standard Deviation (SD) for Immediate Recall (IR), Delayed Free Recall (DFR), and Total Delayed Recall (TDR) scores (number of correctly recalled face-name associations out of a maximum of 16) across the three versions (v1, v2, and v3) of the ItFNAT.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eImmediate Recall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eDelayed Free Recall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eTotal Delayed Recall\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6.02, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.32\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;7.26, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.26\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;13.48, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.39\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ev1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ev2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ev3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003ev1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003ev2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003ev3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003ev1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003ev2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003ev3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMean\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e13.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e13.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e13.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe three ANCOVA analyses on ItFNAT scores indicated that participant's schooling significantly influenced DFR score (F\u003csub\u003e1, 97\u003c/sub\u003e = 6.285, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.014) and IR score (F\u003csub\u003e1, 97\u003c/sub\u003e = 3.691, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.058). Participants\u0026rsquo; age and sex did not show significant effects on any ItFNAT score. Based on these findings, the total sample was divided into two groups according to median years of schooling (\u0026le;\u0026thinsp;14 or \u0026gt;\u0026thinsp;14 years). Schooling-dependent \u003cem\u003ecut-offs\u003c/em\u003e for each ItFNAT measure were then established by calculating the 15th percentile (as an inferior limit) and the 5th percentile (as a pathological score) within each education group (see Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics and schooling-dependent cut-off scores (15th and 5th percentiles) for ItFNAT measures (IR, DFR, TDR) stratified by schooling level (\u0026lt;\u0026thinsp;15 years and \u0026ge;\u0026thinsp;15 years). Mean and standard deviation (SD) values are presented for each measure (number of correctly recalled face-name associations out of a maximum of 16), alongside the rounded 15th percentile (lower normative limit) and 5th percentile (pathological threshold) cut-offs within each group.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eImmediate Recall\u003c/p\u003e \u003cp\u003e\u003cem\u003e15th\u003c/em\u003e %= 3, 5th %= 2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eDelayed Free Recall\u003c/p\u003e \u003cp\u003e15th %= 3, 5th %= 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eTotal Delayed Recall\u003c/p\u003e \u003cp\u003e15th %= 11, 5th %= 9\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSchooling\u0026thinsp;\u0026lt;\u0026thinsp;15y\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSchooling\u0026thinsp;\u0026ge;\u0026thinsp;15y\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSchooling\u0026thinsp;\u0026lt;\u0026thinsp;15y\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSchooling\u0026thinsp;\u0026ge;\u0026thinsp;15y\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSchooling\u0026thinsp;\u0026lt;\u0026thinsp;15y\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSchooling\u0026thinsp;\u0026ge;\u0026thinsp;15y\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMean\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14.17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e15th %\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e5th %\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe 3 x 12 Person\u0026rsquo;s correlation matrix (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) demonstrates that ItFNAT scores significantly correlate both with memory and attention test scores. Specifically, the ItFNAT IR score showed a positive correlation with the RAVLT Immediate Recall (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.422, BF\u003csub\u003e10\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;1722) and Delayed Recall (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.385, BF\u003csub\u003e10\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;294). The ItFNAT DFR score showed significant positive correlations with the DS-B score (r\u0026thinsp;=\u0026thinsp;0.310, BF\u003csub\u003e10\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;16.98), the ROCFT Recall (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.390, BF\u003csub\u003e10\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;370) and with all the RAVLT scores\u0026mdash;Immediate Recall (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.434, BF\u003csub\u003e10\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;3202), Delayed Recall (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.512, BF\u003csub\u003e10\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;326879), and Recognition (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.376, BF\u003csub\u003e10\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;205). Finally, the ItFNAT TDR score positively correlated with all RAVLT scores\u0026mdash;Immediate Recall (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.399, BF\u003csub\u003e10\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;554), Delayed Recall (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.368, BF\u003csub\u003e10\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;147), and Recognition (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.420, BF\u003csub\u003e10\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;1511)\u0026mdash;and with ROCFT Recall (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.327, BF\u003csub\u003e10\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;30). Conversely it showed negative correlations with the time taken to complete the SCWT (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.322, BF\u003csub\u003e10\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;26), the TMT-A (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.400, BF\u003csub\u003e10\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;603) and the TMT-B (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.377, BF\u003csub\u003e10\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;212).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study presents the first standardized face-name associative test for the Italian sample (ItFNAT), which was designed to assess cross-modal associative memory. The test is freely available (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.6084/m9.figshare.28113620\u003c/span\u003e\u003cspan address=\"10.6084/m9.figshare.28113620\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and consists of three parallel versions. All versions demonstrated high reliability, with good internal consistency and no significant score differences, underscoring the test's robustness and suitability as a standardized tool within the Italian context. The subscores of the test, namely Immediate Recall (IR), Delayed Free Recall (DFR), and Total Delayed Recall (TDR), offer distinct insights into cognitive functioning. While IR reflects memory performance, DFR and, in particular, TDR, capture broader aspects of general cognitive functioning. This finding is supported by correlation analyses. The validation process enabled the derivation of preliminary \u003cem\u003ecut-off\u003c/em\u003e scores for each subscore according to individual schooling, as this appears to be the predominant sociodemographic factor influencing scores. The validation analyses of the ItFNAT demonstrated good overall internal consistency, with Version 1 exhibiting the highest internal consistency. Versions 2 and 3 also showed slightly lower but good levels of internal consistency. The MANOVA analysis revealed no significant effect of version on any of the ItFNAT scores, indicating that all three versions are highly comparable in terms of difficulty. Overall, these data suggest that the three versions of the ItFNAT are reliable and substantially interchangeable.\u003c/p\u003e \u003cp\u003eConcerning the subscores, several studies suggested that minimal forgetting can occur after 30 minutes from encoding (McBride \u0026amp; Dosher, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). This phenomenon was not observed in the present study, indeed the mean DFR score (about 7 out of 16) was slightly higher than the IR score (about 6 out of 16). This phenomenon can be attributed to the shorter interval (15 minutes) between the immediate and delayed recall trials. Additionally, during the immediate recall trial, the correct face-name association was re-presented to participants regardless of their IR accuracy response, thereby reinforcing the name-face association. The use of cues (i.e., three alternative names) when participants were unable to freely recall a name during the delayed recall trials significantly enhanced performance, increasing the number of correctly recalled associations from approximately 7 (mean DFR score) to about 13 (mean TDR score) out of 16. This finding is consistent with the efficacy of associative prompts, which leverage recognition processes, in enhancing free memory recall among the general population (Tulving \u0026amp; Tulving, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1985\u003c/span\u003e). The significant improvement with cues also highlights their potential in distinguishing retrieval versus encoding deficits, aiding differential diagnosis of AD and other conditions. In AD, limited cue benefits suggest encoding issues (Flicker et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1991\u003c/span\u003e), whereas larger improvements in conditions like frontotemporal dementia (Pasquier et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) or neurodevelopmental disorders (e.g., Attention-Deficit/Hyperactivity Disorder (Sjöwall et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2013\u003c/span\u003e)) and indicate retrieval deficits. Cue-based strategies could further enhance cognitive rehabilitation in early AD (Clare \u0026amp; Woods, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) and help monitor progression in neurodegenerative disorders.\u003c/p\u003e \u003cp\u003eThe three ANCOVA analyses indicated that the participants' educational attainment had a significant influence on the DFR score and a marginal effect on the IR score. Participants with higher levels of education reported higher scores. No significant effects were observed for age or sex on any of the ItFNAT scores. These findings align with the existing literature, which suggests that individuals with higher educational attainment may possess enhanced associative memory capabilities or employ more effective encoding strategies. This is also consistent with findings of previous research linking higher education level to improved performance on cognitive tasks (Le Carret et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) and its neuroprotective role (Brayne et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). In general, an IR score ≤ 2, a DFR score ≤ 1, and a TDS ≤ 9 are indicative of a pathological outcome, with the severity of this outcome depending on the number of schooling years (lower on higher than 15 years). However, given the global increase in educational attainment (Stern, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), a negative correlation between schooling years and age was observed in the present study's sample. To ensure more precise assessments, future studies should stratify the sample; this will allow for more precise evaluation of individuals with varying educational backgrounds, thereby reducing any potential influence of educational disparities on cognitive evaluations.\u003c/p\u003e \u003cp\u003eResults of the 3 x 12 Person’s correlation matrix (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) reveal significant correlations between ItFNAT scores and various memory and attention test performances, underscoring its utility as a comprehensive tool for assessing face-name associative memory. Specifically, the ItFNAT IR score demonstrated positive correlations with RAVLT Immediate Recall and Delayed Recall, indicating that this measure effectively reflects episodic memory encoding processes. The ItFNAT DFR score exhibited an even broader pattern of positive correlations, encompassing all RAVLT scores, the DS-B, and the ROCFT Recall score. This finding underlines the role of DFR as a robust indicator of cross-modal memory and working memory and its integration with other established cognitive assessments. Notably, the TDR subscore demonstrated negative correlations with the time required to complete the SCWT, TMT-A, and TMT-B, highlighting its capacity to not only assess memory processes but also elements of attentional performance speed. This finding suggests the potential of TDR to extend beyond specific memory measures to reflect aspects of general cognitive functioning. Conversely, any ItFNAT subscore exhibited correlations with ROCF Copy, DS-F, EMQ scores, or SCWT errors. Results indicate that ItFNAT provides a progression from more selective assessments of memory encoding (e.g., IR) to measures such as DFR and TDR, which integrate broader cognitive functions (working memory and attentive/processing speed, respectively). This is consistent with the literature on cognitive aging, which underscores the critical role of processing speed in facilitating efficient encoding and retrieval of information (Nettelbeck \u0026amp; Wilson, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), particularly in older adults (Salthouse, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). The strength of these correlations supports the effectiveness of the ItFNAT in evaluating associative memory while also demonstrating its relationship with overall cognitive functioning (Papp et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The Bayesian factor analyses provide substantial evidence (BF10 \u0026gt; 10) for the observed relationships, thereby bolstering confidence in the validity of these findings.\u003c/p\u003e\n\n "},{"header":"Limitations, Future Research and Conclusions","content":"\u003cp\u003eNotwithstanding the encouraging results, this preliminary validation study is not without limitations. For instance, the IR score of Version 3 and the TDR score of Version 2 exhibited very low internal consistency. This may be partially attributed to the dichotomous scoring method (correct vs. incorrect) employed, the low number of items (16) and the relatively small sample size of approximately 33 individuals per version. A larger sample size could help refine these measures. Additionally, the assessment of test-retest reliability is crucial to evaluate the consistency of the tool over time. Furthermore, while the sample size was adequate for preliminary validation, it did not fully capture the variability in memory performance across a broader range of demographics, particularly among older adults and individuals with lower educational attainment. Future research could enhance the clinical applicability of the ItFNAT by expanding normative data to include a wider range of ages and educational backgrounds, thereby refining cut-off scores for different groups or providing correction grids.\u003c/p\u003e\u003cp\u003eFinally, while the present study focused exclusively on correct responses, it is possible that participants may choose not to respond (i.e., \"missed\") or provide incorrect answers. These latter incorrect answers can be intrusive (associating to a face a name never encountered during the former phases) or interfering (associating a face with a name that was incorrect but presented during the former phases). The analysis of these error types could yield valuable insights, which could assist in distinguishing between different diagnostic categories in the context of neurodegenerative or neurodevelopmental conditions. Future studies could explore whether specific response patterns are linked to distinct conditions, offering a deeper understanding of underlying cognitive processes and their relationship to different clinical profiles.\u003c/p\u003e\u003cp\u003eIn conclusion, this study provides a standardized version of a FNAT validated on an Italian population. The ItFNAT is a rapid instrument designed to evaluate cognitive functioning with a particular emphasis on cross-modal associative memory. A significant strength of the ItFNAT is its availability in three parallel versions, all of which are freely accessible online. These versions have been developed to minimize potential learning effects when employed repeatedly for the purpose of monitoring cognitive changes over time. This feature is particularly advantageous in clinical trials, where repeated assessments are a common practice. As neurodegenerative diseases, including Alzheimer's disease, continue to rise on a global scale, standardized tools such as the ItFNAT will play a pivotal role in the early detection of cognitive changes (Blackwell et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Rentz et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), guiding both clinical diagnosis and research into therapeutic interventions.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBagattini C, Mutanen TP, Fracassi C, Manenti R, Cotelli M, Ilmoniemi RJ, Miniussi C, Bortoletto M (2019) Predicting Alzheimer\u0026rsquo;s disease severity by means of TMS\u0026ndash;EEG coregistration. Neurobiol Aging 80:38\u0026ndash;45. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.neurobiolaging.2019.04.008\u003c/span\u003e\u003cspan address=\"10.1016/j.neurobiolaging.2019.04.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBenussi A, Cantoni V, Cotelli MS, Cotelli M, Brattini C, Datta A, Thomas C, Santarnecchi E, Pascual-Leone A, Borroni B (2021) Exposure to gamma tACS in Alzheimer\u0026rsquo;s disease: A randomized, double-blind, sham-controlled, crossover, pilot study. Brain Stimul 14(3):531\u0026ndash;540\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBenussi A, Cantoni V, Grassi M, Brechet L, Michel CM, Datta A, Thomas C, Gazzina S, Cotelli MS, Bianchi M, Premi E, Gadola Y, Cotelli M, Pengo M, Perrone F, Scolaro M, Archetti S, Solje E, Padovani A, Borroni B (2022) Increasing Brain Gamma Activity Improves Episodic Memory and Restores Cholinergic Dysfunction in Alzheimer\u0026rsquo;s Disease. Ann Neurol 92(2):322\u0026ndash;334. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/ana.26411\u003c/span\u003e\u003cspan address=\"10.1002/ana.26411\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBlackwell AD, Sahakian BJ, Vesey R, Semple JM, Robbins TW, Hodges JR (2004) Detecting dementia: Novel neuropsychological markers of preclinical Alzheimer\u0026rsquo;s disease. Dement Geriatr Cogn Disord 17(1\u0026ndash;2):42\u0026ndash;48. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1159/000074081\u003c/span\u003e\u003cspan address=\"10.1159/000074081\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrayne C, Ince PG, Keage HA, McKeith IG, Matthews FE, Polvikoski T, Sulkava R (2010) Education, the brain and dementia: Neuroprotection or compensation? EClipSE Collaborative Members. Brain 133(8):2210\u0026ndash;2216\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCaffarra P, Vezzadini G, Dieci F, Zonato F, Venneri A (2002) Rey-Osterrieth complex figure: Normative values in an Italian population sample. Neurol Sci 22:443\u0026ndash;447\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCalabria M, Manenti R, Rosini S, Zanetti O, Miniussi C, Cotelli M (2011) Objective and subjective memory impairment in elderly adults: A revised version of the Everyday Memory Questionnaire. Aging Clin Exp Res 23(1):67\u0026ndash;73. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/BF03324954\u003c/span\u003e\u003cspan address=\"10.1007/BF03324954\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCaltagirone C, Gainotti G, Carlesimo GA, Parnetti L (1995) Batteria per la valutazione del deterioramento mentale: I. Descrizione di uno strumento di diagnosi neuropsicologica. [The Mental Deterioration Battery: I. Description of a neuropsychological diagnostic instrument]. Archivio di Psicologia Neurologia e Psichiatria 56(4):461\u0026ndash;470\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eClare L, Woods RT (2004) Cognitive training and cognitive rehabilitation for people with early-stage Alzheimer\u0026rsquo;s disease: A review. Neuropsychological Rehabilitation 14(4):385\u0026ndash;401. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/09602010443000074\u003c/span\u003e\u003cspan address=\"10.1080/09602010443000074\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCotelli M, Manenti R, Brambilla M, Petesi M, Rosini S, Ferrari C, Zanetti O, Miniussi C (2014) Anodal tDCS during face-name associations memory training in Alzheimer\u0026rsquo;s patients. \u003cem\u003eFrontiers in Aging Neuroscience\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fnagi.2014.00038\u003c/span\u003e\u003cspan address=\"10.3389/fnagi.2014.00038\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFlicker C, Ferris SH, Reisberg B (1991) Mild cognitive impairment in the elderly: Predictors of dementia. Neurology 41(7):1006\u0026ndash;1009. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1212/wnl.41.7.1006\u003c/span\u003e\u003cspan address=\"10.1212/wnl.41.7.1006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGiovagnoli AR, Pesce D, Mascheroni M, Simoncelli S, Laiacona M, M., Capitani E (1996) Trail making test: Normative values from 287 normal adult controls. Italian J Neurol Sci 17(4):305\u0026ndash;309. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/BF01997792\u003c/span\u003e\u003cspan address=\"10.1007/BF01997792\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoeleven E, De Raedt R, Leyman L, Verschuere B (2008) The Karolinska Directed Emotional Faces: A validation study. Cognition Emot 22(6):1094\u0026ndash;1118. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/02699930701626582\u003c/span\u003e\u003cspan address=\"10.1080/02699930701626582\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJames LE, Fogler KA, Tauber SK (2008) Recognition memory measures yield disproportionate effects of aging on learning face-name associations. Psychol Aging 23(3):657\u0026ndash;664. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/a0013008\u003c/span\u003e\u003cspan address=\"10.1037/a0013008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLe Carret N, Lafont S, Letenneur L, Dartigues J-F, Mayo W, Fabrigoule C (2003) The Effect of Education on Cognitive Performances and Its Implication for the Constitution of the Cognitive Reserve. Dev Neuropsychol 23(3):317\u0026ndash;337. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1207/S15326942DN2303_1\u003c/span\u003e\u003cspan address=\"10.1207/S15326942DN2303_1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcBride DM, Dosher BA (1997) A comparison of forgetting in an implicit and explicit memory task. J Exp Psychol Gen 126(4):371\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMonaco M, Costa A, Caltagirone C, Carlesimo GA (2013) Forward and backward span for verbal and visuo-spatial data: Standardization and normative data from an Italian adult population. Neurol Sci 34:749\u0026ndash;754\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNettelbeck T, Wilson C (2012) Speed of information processing and cognition. In \u003cem\u003eEllis\u0026rsquo; handbook of mental deficiency, psychological theory and research\u003c/em\u003e (pp. 245\u0026ndash;274). Routledge. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.taylorfrancis.com/chapters/edit/10.4324/9780203052846-13/speed-information-processing-cognition-ted-nettelbeck-carlene-wilson\u003c/span\u003e\u003cspan address=\"https://www.taylorfrancis.com/chapters/edit/10.4324/9780203052846-13/speed-information-processing-cognition-ted-nettelbeck-carlene-wilson\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePapp KV, Amariglio RE, Dekhtyar M, Roy K, Wigman S, Bamfo R, Sherman J, Sperling RA, Rentz DM (2014) Development of a Psychometrically Equivalent Short Form of the Face\u0026ndash;Name Associative Memory Exam for use Along the Early Alzheimer\u0026rsquo;s Disease Trajectory. Clin Neuropsychol 28(5):771\u0026ndash;785. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/13854046.2014.911351\u003c/span\u003e\u003cspan address=\"10.1080/13854046.2014.911351\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePasquier F, Grymonprez L, Lebert F, Van der Linden M (2001) Memory Impairment Differs in Frontotemporal Dementia and Alzhemier\u0026rsquo;s Disease. Neurocase 7(2):161\u0026ndash;171. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/neucas/7.2.161\u003c/span\u003e\u003cspan address=\"10.1093/neucas/7.2.161\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRentz DM, Amariglio RE, Becker JA, Frey M, Olson LE, Frishe K, Carmasin J, Maye JE, Johnson KA, Sperling RA (2011) Face-name associative memory performance is related to amyloid burden in normal elderly. Neuropsychologia 49(9):2776\u0026ndash;2783. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.neuropsychologia.2011.06.006\u003c/span\u003e\u003cspan address=\"10.1016/j.neuropsychologia.2011.06.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRubi\u0026ntilde;o J, Andr\u0026eacute;s P (2018) The Face-Name Associative Memory Test as a Tool for Early Diagnosis of Alzheimer\u0026rsquo;s Disease. \u003cem\u003eFrontiers in Psychology\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fpsyg.2018.01464\u003c/span\u003e\u003cspan address=\"10.3389/fpsyg.2018.01464\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSalthouse TA (1996) The processing-speed theory of adult age differences in cognition. Psychol Rev 103(3):403\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eScarpina F, Tagini S (2017) The Stroop Color and Word Test. \u003cem\u003eFrontiers in Psychology\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.frontiersin.org/articles/\u003c/span\u003e\u003cspan address=\"https://www.frontiersin.org/articles/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpsyg.2017.00557\u003c/span\u003e\u003cspan address=\"10.3389/fpsyg.2017.00557\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSj\u0026ouml;wall D, Roth L, Lindqvist S, Thorell LB (2013) Multiple deficits in ADHD: Executive dysfunction, delay aversion, reaction time variability, and emotional deficits. J Child Psychol Psychiatry Allied Discip 54(6):619\u0026ndash;627. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/jcpp.12006\u003c/span\u003e\u003cspan address=\"10.1111/jcpp.12006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSperling RA, Bates JF, Chua EF, Cocchiarella AJ, Rentz DM, Rosen BR, Schacter DL, Albert MS (2003) fMRI studies of associative encoding in young and elderly controls and mild Alzheimer\u0026rsquo;s disease. J Neurol Neurosurg Psychiatry 74(1):44\u0026ndash;50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/jnnp.74.1.44\u003c/span\u003e\u003cspan address=\"10.1136/jnnp.74.1.44\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Scopus\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStern Y (2002) What is cognitive reserve? Theory and research application of the reserve concept. J Int Neuropsychol Soc 8(3):448\u0026ndash;460\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTroyer AK, D\u0026rsquo;Souza NA, Vandermorris S, Murphy KJ (2011) Age-related differences in associative memory depend on the types of associations that are formed. Neuropsychol Dev Cogn B Aging Neuropsychol Cogn 18(3):340\u0026ndash;352. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/13825585.2011.553273\u003c/span\u003e\u003cspan address=\"10.1080/13825585.2011.553273\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTulving E, Tulving E (1985) Elements of Episodic Memory. Oxford University Press\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeaver Cargin J, Collie A, Masters C, Maruff P (2008) The nature of cognitive complaints in healthy older adults with and without objective memory decline. J Clin Exp Neuropsychol 30(2):245\u0026ndash;257. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/13803390701377829\u003c/span\u003e\u003cspan address=\"10.1080/13803390701377829\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWerheid K, Clare L (2007) Are Faces Special in Alzheimer\u0026rsquo;s Disease? Cognitive Conceptualisation, Neural Correlates, and Diagnostic Relevance of Impaired Memory for Faces and Names. Cortex 43(7):898\u0026ndash;906. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0010-9452(08)70689-0\u003c/span\u003e\u003cspan address=\"10.1016/S0010-9452(08)70689-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWetzels R, Wagenmakers E-J (2012) A default Bayesian hypothesis test for correlations and partial correlations. Psychon Bull Rev 19(6):1057\u0026ndash;1064. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3758/s13423-012-0295-x\u003c/span\u003e\u003cspan address=\"10.3758/s13423-012-0295-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"neuropsychology, cognitive assessment, neurodegenerative disease, Face-Name Associative Memory Exams","lastPublishedDoi":"10.21203/rs.3.rs-5912323/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5912323/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground and Objectives: \u003c/strong\u003eAssociating names with faces is crucial for social interactions and reflects cognitive health. To address the need for reliable tools to assess associative memory, we developed and validated the Italian Face-Name Associative Test (ItFNAT), a tool allows clinicians to monitor cognitive functioning and detect early signs of decline related to aging and neurodegenerative conditions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMaterials and Methods: \u003c/strong\u003e101 Italian participants (51 females) aged 18-80 years completed the three parallel versions of the ItFNAT, which assessed immediate recall (IR), delayed free recall (DFR), and delayed recall with cues (TDR). ItFNAT was administered alongside other neuropsychological tests to explore its relationship with memory and attention.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eCronbach’s alpha revealed high reliability across all three versions of the ItFNAT. MANOVA showed no significant differences between the subscores of the three versions. ANCOVA indicated that schooling significantly influenced DFR scores and had a marginal effect on IR scores, while age and sex did not significantly impact scores. Accordingly, specific cut-offs based on schooling were established. The 3 x 12 correlation matrix demonstrated significant correlations between ItFNAT scores and memory and attention test scores.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDiscussions: \u003c/strong\u003eThis study introduces the ItFNAT, a test designed to assess cross-modal associative memory. It includes three parallel versions with good internal consistency, and minimal score differences. The subscores—IR, DFR, and TDR—capture various aspects of cognitive functioning, with educational attainment influencing DFR scores. Preliminary cut-offs were established based on schooling, enhancing the test's clinical applicability. Future research should refine its utility for monitoring cognitive changes and neurodegenerative conditions.\u003c/p\u003e","manuscriptTitle":"The Italian Face-Name Association Test (ItFNAT): A preliminary validation of three parallel versions","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-30 10:02:53","doi":"10.21203/rs.3.rs-5912323/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"13644606-5a2a-4859-b490-9081519a9021","owner":[],"postedDate":"January 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-01-30T10:02:53+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-30 10:02:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5912323","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5912323","identity":"rs-5912323","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}