LASA156 / LASA356
Contact: Almar Kok
The 15 Words Test (15WT) is developed to investigate episodic memory problems in patients with brain disorders. It is the Dutch version of the Auditory Verbal Learning Test (AVLT; Rey, 1964; Deelman et al. 1980; Saan RJ & Deelman BG. 1986). This test consists of 15 words, which have to be learned during five trials. After every trial the respondent is asked to recall as many words as possible. After a distraction period of 20 minutes, the respondent is asked to name the words they have learned before, again.
Measurement instrument in LASA
The number of trials was limited to three because of scarcity of interview time. The test results are correlated with sex, age and education level. Moreover, a retest effect after several years is found in healthy subjects, caused by knowledge of the procedure. In order to prevent any remembrance of the words, two parallel versions of the 15WT are used in order to reduce a possible practice effect.
Before using the data of the 15WT it is important to look into the data. Some persons may have missing data or extreme bad scores on one of the trials. Therefore it may be preferable to use the maximum score of the three trials, the delayed recall score *MWTDR and as retention score: delayed recall score/highest score of one of the 3 trials (*MRET2PC) as best indices for memory performance in the LASA sample.
Descriptive statistics of the 15 Words Test of waves B-G can be found here: (pdf).
Several scores are computed based on the 15-Word test. The total score for the immediate recall-trials consists of the sum of the number of correctly remembered words in each of the three trials (range 0-45). The maximum score for immediate recall represents the maximum number of correctly remembered words in a single trial (range 0-15). A difference score for immediate recall is computed by subtracting the lowest score from the highest score of the three trials.
Retention scores represent the percentage words that is correctly remembered after the distraction period. Two versions of retention scores are computed. The first retention score represents the percentage of correctly remembered words in the delayed recall-trial, relative to the number of words correctly remembered in the third immediate recall-trial (*MRET1PC). The second retention score represents the percentage of correctly remembered words in the delayed recall-trial, relative to the maximum score in the immediate recall-trials (*MRET2PC).
LASAB156 / LASAC156 / LASAD156 /LASAE156 / LAS2B156 / LASAF156 / LASAG156 / LASAH156 / LAS3B156 / LASAI156 / LASAJ156 (medical interview, 15WT is copyrighted material)
The number of correct words mentioned at each trial is represented in the variables *MWTT1, *MWTT2 and *MWTT3. The total number of words the respondent has learned during the three presentations is the recall score (variable name: *MTOTAL), which ranges from 0-45. The number of words reproduced after 20 minutes is the delayed recall score (variable name: *MWTDR), ranging from 0-15.
LASA*156 contains: the total number of correct words *MWTT1, *MWTT2 and *MWTT3 (from D-wave onwards), particularities during testing, the number of doubles and other words, and the delayed recall score.
LASA*356 contains: *MWTT1, *MWTT2 and *MWTT3 (only in B- and C-wave) and the sumscore of the three trials, the retention scores and the maximum score of the three trials (*MTMA*).
LASAB156 / LASAC156 / LASAD156 /LASAE156 / LAS2B156 / LASAF156 / LASAG156 / LASAH156 / LAS3B156 / LASAI156 / LASAJ156;
LASAB356 / LASAC356 / LASAD356 /LASAE356 / LAS2B356 / LASAF356 / LASAG356 / LASAH356 / LAS3B356 / LASAI356 / LASAJ356 (constructed)
Availability in LASA per wave ¹
¹ More information about the LASA data collection waves is available here.
* 2B=baseline second cohort;
3B=baseline third cohort;
MB=migrants: baseline first cohort;
K=future wave 2021-2022
Me=data collected in medical interview
Previous use in LASA
Episodic memory has been used as a measure of memory decline. Memory decline has been defined as a decrease of at least 1 SD from the mean change score on immediate recall (IR), delayed recall (DR), and retention, based on the AVLT (Dik, Jonker et al. 2000). In this study, it was found that APOE-E4 is associated with memory decline in cognitively impaired elderly. Memory retention was found to be disproportionately low in the oldest age cohort (80–85 years) with less than 11 years of education (Schmand, Smit et al. 1997). Personality traits did not affect the rate of memory decline over time (Klaming, Annese et al. 2017). The association between several biomarkers and decline in episodic memory (among other domains of cognitive functioning) has also been investigated (van den Kommer et al. 2012; 2010; 2009; Dik et al. 2001).
Furthermore, Klaming et al. found that episodic memory is affected by lifestyle factors (Klaming, Veltman et al. 2017). Another study found that higher levels of mastery and self-efficacy were associated with better memory function while high neuroticism was associated with poorer memory (Klaming, Annese et al. 2017). The association between personality and episodic memory was previously investigated as well (van den Heuvel, Smits et al. 1996). Episodic memory was also assessed in relation to physical impairment across different age groups (Stijntjes, Aartsen et al. 2017). The impact of neighborhood socioeconomic status (SES) and urbanity on episodic memory was assessed. It was found that neighborhood SES has no independent effect on cognitive functioning, while neighborhood urbanicity had (Wörn, Ellwardt et al. 2017). Perceived stress was associated with direct and delayed recall (Korten, Comijs et al. 2017). Episodic memory has also been associated with anxiety and depression in one study (Bierman, Comijs et al. 2005), yet another study did not find an association with severity and duration of depressive symptoms (Comijs, van Tilburg et al. 2013). Furthermore, no association between depression and increasing memory impairment or global mental deterioration was found (Comijs, Jonker et al. 2001).
Other studies utilized episodic memory to look at: gender differences in cognitive functioning (Aartsen, Martin et al. 2004), the effects of widowhood on memory performance (Aartsen, Van Tilburg et al. 2005), associations of 25-hydroxyvitamin D and cognitive functioning (van Schoor, Comijs et al. 2015), the prevalence and incidence of memory complaints and memory performance in employed compared to non-employed individuals and the role of employment characteristics (Rijs, Van den Kommer et al. 2015) (Rijs, Comijs et al. 2013), objective health indicators associations (Jelicic, Jonker et al. 1999) and in classification models for identification of at-risk groups for incident memory complaints (van den Kommer, Comijs et al. 2013). A study also used the 15 words test as a measure of immediate memory and found that it showed to be an independent risk factor for falls (van Schoor, Smit et al. 2002).
- Aartsen, M. J., et al. (2004). “Gender Differences in Level and Change in Cognitive Functioning.” Gerontology 50(1): 35-38.
- Aartsen, M. J., et al. (2005). “Does widowhood affect memory performance of older persons?” Psychological Medicine 35(2): 217-226.
- Bierman, E. J. M., et al. (2005). “Effects of Anxiety Versus Depression on Cognition in Later Life.” The American Journal of Geriatric Psychiatry 13(8): 686-693.
- Comijs, H. C., et al. (2001). “The association between depressive symptoms and cognitive decline in community-dwelling elderly persons.” International Journal of Geriatric Psychiatry 16(4): 361-367.
- Comijs, H. C., et al. (2013). “Do severity and duration of depressive symptoms predict cognitive decline in older persons? Results of the Longitudinal Aging Study Amsterdam.” Aging Clinical and Experimental Research 16(3): 226-232.
- Dik, M. G., et al. (2000). “APOE- 4 is associated with memory decline in cognitively impaired elderly.” Neurology 54(7): 1492-1497.
- Dik, M. G., et al. (2001). “Memory complaints and APOE-ε4 accelerate cognitive decline in cognitively normal elderly.” Neurology 57(12): 2217-2222.
- Jelicic, M., et al. (1999). “Do health factors affect memory performance in old age?” International Journal of Geriatric Psychiatry 14(7): 572-576.
- Klaming, R., et al. (2017). “Episodic memory function is affected by lifestyle factors: a 14-year follow-up study in an elderly population.” Aging, Neuropsychology, and Cognition 24(5): 528-542.
- Klaming, R., et al. (2017). “The impact of personality on memory function in older adults—results from the Longitudinal Aging Study Amsterdam.” International Journal of Geriatric Psychiatry 32(7): 798-804.
- Korten, N. C. M., et al. (2017). “Perceived stress and cognitive function in older adults: which aspect of perceived stress is important?” International Journal of Geriatric Psychiatry 32(4): 439-445.
- Rijs, K. J., et al. (2013). “Do employed and not employed 55 to 64-year-olds’ memory complaints relate to memory performance? A longitudinal cohort study.” European Journal of Public Health 23(6): 1013-1020.
- Rijs, K. J., et al. (2015). “Prevalence and Incidence of Memory Complaints in Employed Compared to Non-Employed Aged 55–64 Years and the Role of Employment Characteristics.” PLOS ONE 10(3): e0119192.
- Schmand, B., et al. (1997). “Low education is a genuine risk factor for accelerated memory decline and dementia.” Journal of Clinical Epidemiology 50(9): 1025-1033.
- Stijntjes, M., et al. (2017). “Temporal Relationship Between Cognitive and Physical Performance in Middle-Aged to Oldest Old People.” The Journals of Gerontology: Series A 72(5): 662-668.
- van den Heuvel, N., et al. (1996). “Personality: A moderator of the relation between cognitive functioning and depression in adults aged 55–85?” Journal of Affective Disorders 41(3): 229-240.
- van den Kommer, T. N., et al. (2013). “Classification models for identification of at-risk groups for incident memory complaints.” International Psychogeriatrics 26(2): 257-271.
- van den Kommer, T. N., et al. (2009). “Total cholesterol and oxysterols: Early markers for cognitive decline in elderly?” Neurobiology of Aging 30(4): 534-545.
- van den Kommer, T. N., et al. (2010). “Homocysteine and inflammation: Predictors of cognitive decline in older persons?” Neurobiology of Aging 31(10): 1700-1709.
- van den Kommer, T. N., et al. (2012). “The role of lipoproteins and inflammation in cognitive decline: Do they interact?” Neurobiology of Aging 33(1): 196.e191-196.e112.
- van den Kommer, T. N., et al. (2012). “The role of extracerebral cholesterol homeostasis and ApoE e4 in cognitive decline.” Neurobiology of Aging 33(3): 622.e617-622.e628.
- van Schoor, N. M., et al. (2015). “Cross-sectional and longitudinal associations between serum 25-hydroxyvitamin D and cognitive functioning.” International Psychogeriatrics 28(5): 759-768.
- van Schoor, N. M., et al. (2002). “Different cognitive functions in relation to falls among older persons: Immediate memory as an independent risk factor for falls.” Journal of Clinical Epidemiology 55(9): 855-862.
- Wörn, J., et al. (2017). “Cognitive functioning among Dutch older adults: Do neighborhood socioeconomic status and urbanity matter?” Social Science & Medicine 187: 29-38.
Date of last update: December, 2019