Normative data for the Rey Auditory Verbal Learning Test in the older French-Quebec population

<p><b>Objective</b>: The aim of this study was to establish normative data for the Rey Auditory Verbal Learning Test, a test assessing verbal episodic memory, in the older French-Quebec population. <b>Method</b>: A total of 432 French-speaking participants aged between 55 and 93 years old, from the Province of Quebec (Canada), were included in the study. Using multiple regression analyses, normative data were developed for five variable of interest, namely scores on trial 1, sum of trials 1 to 5, interference list B, immediate recall of list A, and delayed recall of list A. <b>Results</b>: Results showed that age, education, and sex were associated with performance on all variables. Equations to calculate the expected score for a participant based on sex, age, and education level as well as the <i>Z</i> score were developed. <b>Conclusion</b>: This study provides clinicians with normative data that take into account the participants’ sociodemographic characteristics, thus giving a more accurate interpretation of the results.</p

SW characteristics showing significant interactions between age group and sleep conditions.

<p>SW density (panel A) and SW positive phase duration (panel B) are shown for young subjects (black dots) and middle-aged subjects (open squares). Stars indicate differences between baseline sleep and daytime recovery sleep in young and middle-aged subjects (Contrast analysis: *: p<0.0001; **: p<0.00001).</p

SW amplitude showing significant interaction between age group, sleep condition and NREMP.

<p>SW amplitude (panel A) and SW slope (panel B) are shown for young subjects (black dots) and middle-aged subjects (open squares), for baseline and recovery sleep during the first NREMP. Stars indicate differences between baseline and recovery sleep (Contrast analysis: *: p<0.05; **: p<0.001; ***: p<0.00001). A) After sleep deprivation, young subjects showed higher SW amplitude enhancement compared to middle-aged subjects during the first NREMP only (interaction age group * sleep condition: F(1,61) = 6.55; p = 0.05). B) After sleep deprivation, young subjects tended to show higher slope enhancement compared to middle-aged subjects during the first NREMP only (interaction age group * sleep condition: F(1,61) = 3,71; p = 0.06).</p

Polysomnographic variables for young and middle-age in both sleep condition.

<p>Untransformed mean (standard deviation); Y: Young, MA: Middle-aged, B: Baseline nocturnal sleep, R: Daytime recovery sleep.</p

SW durations showing significant interactions between age group and sleep pressure.

<p>SW density (panel A), negative phase (panel B) and positive phase (panel C) on F3 derivation are shown for young subjects (black dots), middle-aged subjects (open squares) for the first and last NREMP averaged on the two sleep condition. Star indicates difference between young and middle-aged subjects for SW density and between the first and the last NREMP for SW durations (*: p<0.001; **: p<0.0001). A) Contrast analysis showed higher SW density in young than in middle-aged subjects during the first NREMP only (F(1,61) = 12.15; p<0.001). B) Contrast analysis showed significant SW negative phase duration increase between the first and last NREMP in young subjects (F(1,61) = 15.12; p<0.001) and no significant modification in middle-aged subjects. C) Contrast analysis showed higher SW positive phase duration increase between the first and last NREMP in young subjects (F(1,61) = 120.04; p<0.0001) compared to middle-aged subjects (F(1,61) = 37.48; p<0.001).</p

SW characteristics showing significant interactions between sleep condition and derivations.

<p>SW density (panel A), negative phase (panel B), and positive phase duration (panel C) are shown for baseline sleep (black triangles) and daytime recovery sleep (open circles). Stars indicate differences between baseline sleep and daytime recovery sleep for each derivation (Contrast analysis*: p<0.0001; **: p<0.00001; ***: p<0.000001).</p

SW characteristics showing significant interactions between age group, sleep condition and derivations.

<p>SW amplitude (panel A) and SW slope (panel B) are shown for Fp1 (upper panel) and F3 derivations (lower panel) and for young subjects (black dots) and middle-aged subjects (open squares). Stars indicate differences between baseline sleep and daytime recovery sleep in young and middle-aged subjects (contrast analysis: *: p<0.0001; **: p<0.00001). A) Post-hoc analyses showed significant interactions between age group and sleep condition only in Fp1 (F(1,61) = 10.93, p<0.01) and F3 (F(1,61) = 7.11, p<0.01) derivations. B) Post-hoc analyses showed significant interactions between age group and sleep condition were found only on Fp1 (F(1,61) = 16.31, p<0.001) and F3 (F(1,61) = 8.19, p<0.01) derivations.</p

Trail Making Tests A and B: regression-based normative data for Quebec French-speaking mid and older aged adults

<p><b>Objective:</b> The Trail Making Test (TMT) is mainly used to assess visual scanning/processing speed (part A) and executive functions (part B). The test has proven sensitive at detecting cognitive impairment during aging. However, previous studies have shown differences between normative data from different countries and cultures, even when corrected for age and education. Such inconsistencies between normative data may lead to serious diagnostic errors, thus, the development of local norms is warranted. The purpose of this study was to provide regression-based normative data for TMT-A and -B, tailored for a large sample of French-speaking adults from Quebec (Canada).</p> <p><b>Method:</b> The normative sample consisted of 792 participants aged 50–91 years. Based on multiple linear regression, equations to calculate <i>Z</i>-scores were provided for TMT-A and -B, and for a contrast score which compared performance between TMT-A and -B. Percentiles, stratified by age, are presented for the number of recorded errors.</p> <p><b>Results:</b> Age was a significant predictor for TMT-A performance, while age and education were independently associated with performance on TMT-B. Gender did not have any effect on performance, in either condition. Education was the only significant predictor of the contrast score between TMT-B and TMT-A. Examiners should remain vigilant when two or more errors are recorded on the TMT-B since this was uncommon in the normative sample.</p> <p><b>Conclusions:</b> Our TMT normative data improve the accurate detection of visual scanning/processing speed and executive function deficits in Quebec (Canada) French-speaking adults.</p