Testing memory word list

Are you nearing 75 or 80? And driving?

 I did not do well in the Drs word list memory test!! (from a reader.)

Cognitive skills are critical to driving because your brain is required to process so many different pieces of information at once – what you can see and hear, emotions you are experiencing while driving, the feel you have for road surfaces, they way your car is performing, other traffic on the road ….. your working memory is in full swing.

At key ages in New Zealand, you will be completing a range of face-to-face tests at your medical centre.

Here’s how to get ready for that test.

You can practice for one of them – remembering a list of words:

This is an exercise you can practice with groups of random words at home, too. Give yourself 30 seconds to study a list of 10 or 12 words. turn over the page and see how many you can recall – write down or say out loud. Start with 6 and work up to a longer list. You will see how much you improve with practice!

p.s. On the video, you will see us referred to as the Brain and Memory Foundation – that was our full name until we were able to shorten it to Memory Foundation (and Brainfit® for Life). It is still us!


Memory-Tune-premium-memory-trainingThe Memory Tune course, written by Dr Allison Lamont and Gillian Eadie, takes you through, step-by-step, many other kinds of brain skills that will sharpen your cognition and memory skills. Thousands of people have now used this tried and tested course. It comes to you over seven weeks and is accompanied by a print version, also.

$169.00 for the full course and book.

“Thank you both so much for this course which has given me the confidence and the tools to deal with my memory problems. I now enjoy puzzles, crosswords and memory tests.. I used to avoid them like the plague. Meeting people and remembering their names is now a pleasant experience rather than a nightmare! You have shone a light at the end of what was fast becoming a very dark tunnel. Thank you.” Maria G.


Will you share your experiences with this cognition test? Your story will be helpful for others ….

For example, in a word list learning task, patients with left frontal damage had increased false positive errors in memory recognition.

From: Encyclopedia of Neuroscience, 2009

Recovered Memories

Heidi Sivers, … Jennifer J. Freyd, in Encyclopedia of the Human Brain, 2002

IV.B.3 Interference Theories of Memory

Countless examples of word-list learning experiments have demonstrated that if two related pieces of information are learned, practice of one piece of information can interfere with the ability to remember the other piece of information. This can take the form of prospective interference, in which past information interferes with the ability to retrieve new information. One example of this phenomenon is having difficulty remembering a friend’s married name because her maiden name keeps popping to mind. Alternatively, retrospective interference can occur, in which the learning of new information interferes with the ability to recall old information; the new married name gets in the way of recalling the friend’s maiden name. In either case, recall of one set of information “interferes” with the ability to recall the other. When considering traumatic experiences, imagine the child who’s favorite uncle sexually abused him on one occasion and takes him to a ball game on another. The child may rehearse the uncle–ball game association repeatedly while never rehearsing the uncle–abuse experience due to pressure not to disclose, threats or denial from the uncle, or numerous other reasons. According to standard interference theories of memory, the strengthening of the uncle–ball game association would actually decrease the ability to recall the uncle–abuse situation.

Read full chapter

URL: 

https://www.sciencedirect.com/science/article/pii/B0122272102002995

Diazepam

In Meyler’s Side Effects of Drugs (Sixteenth Edition), 2016

Psychiatric

The effects of diazepam on word list recall, prospective memory, sustained attention and subjective ratings of arousal have been studied in 48 healthy participants, aged 19–35 years, who took oral diazepam mean dose 0.19 mg/kg or placebo in a double-blind study [21]. Retrospective memory and prospective memory were assessed by free recall of unrelated word lists and by instructing participants to ask for a hidden belonging at the end of the session. Sustained attention was measured by multiple trials of a digit cancellation task and subjective arousal was assessed by self-ratings of drowsiness. Diazepam impaired performance on all measures. Diazepam reduced prospective memory performance associated with reduced subjective arousal, but unrelated to sustained attention. This is the first report of the effects of benzodiazepines on prospective remembering and further supports the view that the arousal/attentional system is composed of partially independent subsystems that have differential relationships to memory.

Read full chapter

URL: 

https://www.sciencedirect.com/science/article/pii/B9780444537171006077

Assessment

C. Munro Cullum, in Comprehensive Clinical Psychology, 1998

4.11.4.8.4 Verbal memory tests

(i) California Verbal Learning Test (CVLT)

This is a 16-item word list-learning task that contains items from four semantic categories (Delis, Kramer, Kaplan, & Ober, 1987). The list is presented five times to subjects, in the same order, which allows for not only an assessment of learning, but of primacy-recency recall effects. The CVLT was developed with principles of cognitive neuroscience and clinical memory disorders in mind, and provides a quantitative assessment of a wide variety of qualitative features of memory performance. It has been shown to be reliable (Paolo, Troster, & Ryan, 1997) and clinically useful in a variety of clinical populations, particularly in the differential diagnostic assessment of memory disorders (Cullum, Filley, & Kozora, 1995; Peavy et al., 1994).

After the fifth presentation of the word list, an interference list is presented to permit an examination of the effects of interference on recall. Next, free recall of the initial word list is examined, followed by cued recall that involves the presentation of semantic categories for the words (e.g., “Tell me all the items that were fruits”). Long delay free recall is examined following a 20-minute delay. This is immediately followed by another series of cued recall trials, and finally, a recognition trial wherein a longer list of items containing target items as well as distractors is presented, and subjects must simply indicate “yes” or “no” whether or not these items appeared in the originally presented list. As noted, the CVLT provides for a quantified assessment of a variety of qualitative aspects of verbal learning and memory, and scoring software is available to provide normative reference scores for a host of verbal learning and memory indices. An alternate form of the CVLT has been developed that has shown good correlations with the original version (Delis et al., 1991), and a revised CVLT is in preparation in 1998. A nine-item dementia version of the CVLT has also been derived for use in more impaired populations (Libon, Mattson, et al., 1996).

(ii) Hopkins Verbal Learning Test (HVLT)

This test was developed to provide an abbreviated assessment of word list-learning and memory (Brandt, 1991). It is particularly well suited for more impaired patients who might not be able to complete measures such as the CVLT. A list of 12 items from three semantic categories is presented across three trials, followed by recognition testing. A modification of the original HVLT provides for an assessment of delayed recall prior to recognition in order to assess forgetting over time. A unique aspect of the HVLT is that it includes six alternate forms, thereby reducing practice effects and making it a good choice in serial assessment situations.

(iii) Logical Memory (WMS, WMS-R, WMS-III)

This is the classic story learning and memory test that is one of the most widely used clinical indices of memory function. It is a measure of the ability to learn and retain new structured verbal information. The original WMS included two stories that were read to patients, followed by an assessment of immediate recall. The WMS-R updated the stories, norms, and scoring procedures, and importantly, added a delayed recall trial. Each of the WMS-R stories contains 25 bits of information, and a standard 30-minute delayed recall procedure provides for a ready assessment of forgetting rates. The WMS-III version includes an initial story that is administered in standard fashion (i.e., one trial, followed by immediate and then delayed recall), and a second story that is repeated in order to assess the effects of learning on storage and retrieval of material.

Patients’ responses should be written down verbatim in order to glean additional qualitative information, and to allow for cross-checking of scoring. Scoring for Logical Memory is done largely based upon identical or almost-identical recall of the story material, although several scoring procedures allow partial credits to be assigned for close approximations, and the WMS-III version also incorporates scores for thematic units or gist. Logical Memory has been shown to be highly useful in the assessment of a wide array of memory disorders and senstive to left hippocampal damage in particular (Sass et al., 1992).

Read full chapter

URL: 

https://www.sciencedirect.com/science/article/pii/B0080427073002273

Memory disorders and impaired language and communication

Randi Martin, L. Robert Slevc, in Cognition and Acquired Language Disorders, 2012

Phonological versus semantic short-term memory deficits

Aphasic patients are almost universally impaired on simple span tasks involving word list recall (Martin & Ayala, 2004). While neurally healthy adults may have a STM span of about 7 digits and 5 words, aphasic patients typically have spans of 1 to 3 items. A large body of research has examined the causes of these STM deficits and their consequences for aphasic patients’ language comprehension and production. In some theoretical positions, the passive storage involved in word span tasks is assumed to be a buffer that maintains phonological representations (e.g., Baddeley, 1986). In other approaches that take a more language-based approach to STM, both phonological and semantic information are thought to support word list retention. R. Martin and colleagues (e.g., Martin, Shelton & Yaffee, 1994) and N. Martin and colleagues (e.g., Martin & Saffran, 1997) have provided patient data supporting the latter view. For instance, Martin et al. (1994) and Martin and He (2004) have shown that some patients show a deficit specifically in maintaining phonological information and others show a deficit specifically in maintaining semantic information. Those with a phonological STM deficit fail to show the standard effects of phonological variables on span performance (e.g., failing to show an effect of phonological similarity of the words in the list) but do show effects related to semantic variables (e.g., performing better with word lists than lists made up of nonwords such as “pem, dat, tur”). Patients with a semantic STM deficit show the reverse pattern, showing effects of phonological variables, but failing to show effects of semantic variables (for instance, performing at the same level on word and nonword lists). Two tasks that have been shown to discriminate the patients with semantic and phonological STM deficits are the category and rhyme probe tasks (Figure 9-3). In both tasks, patients hear a list of words followed by a probe word. In the category probe task, subjects must judge if the probe word is in the same category as any of the list words. In the rhyme probe task, subjects judge whether the probe word rhymes with any of the list words. Patients with a phonological STM deficit perform better on the category than the rhyme probe task, whereas the patients with a semantic STM deficit perform better on the rhyme that the category probe task. (See also Barde, Schwartz, Chrysikou, & Thompson-Schill, 2010; Hoffman, Jefferies, Ehsan, et al., 2009; Wong & Law, 2008, for recent replications of these findings.) N. Martin and colleagues have presented other data showing different effects of semantic and phonological variables on recall of words which are correlated with patients’ semantic and phonological processing abilities. For instance, a composite measure of semantic processing is correlated with imageability effects on span, whereas a composite measure of phonological processing is correlated with frequency effects on span.

Based on these dissociations, Martin, Lesch, and Bartha (1999) presented a model of verbal STM that includes separate capacities for retaining semantic and phonological information (Figure 9-4). On the left hand side of Figure 9-4 are the types of knowledge representations that one has about words. On the right are buffers used to maintain these different types of representations. In addition to separate buffers for semantic and phonological information, as shown in Figure 9-4, separate capacities are assumed for maintaining input and output phonological representations. Input representations are those derived from the perception of speech. Output representations are those used in speech production. Martin et al. (1999) and others (e.g., Allport, 1984; Shallice & Butterworth, 1977) have presented evidence showing that patients can have poor retention of spoken words on the input side but show normal patterns of speech production (implying preserved output phonological retention), whereas other patients can show normal retention of phonological representations during speech perception but have difficulty in maintaining phonological information used in production.

Read full chapter

URL: 

https://www.sciencedirect.com/science/article/pii/B9780323072014000180

Dementia and Language☆

S. Kemper, L.J.P. Altmann, in Reference Module in Neuroscience and Biobehavioral Psychology, 2017

Implications and Conclusions

There has been considerable interest in using linguistic measures to predict risk, aid in diagnosis, and track the progression of dementia, particularly Alzheimer dementia. Performance on tests of verbal memory, such as immediate and delayed word list recall, as well as tests of verbal fluency, appear to be particularly sensitive indicators of risk for dementia and its onset and seem to covary with other known risk factors, such as apolipoprotein E genotype. However, deficits in verbal fluency are not specific to Alzheimer disease, as discussed above.

The relationship between linguistic ability and Alzheimer disease has been the focus of a number of studies. Declining language ability in late life may be a marker of risk for Alzheimer disease, indicating the onset and progression of this disease. For example, clues to the onset of dementia can be found in the writings of well-known authors including Iris Murdoch and Agatha Christie by examining lexical diversity and syntactic complexity. Thus, changes in language ability in late life may signal incipient dementia. Along similar lines, the Nun Study, a longitudinal, epidemiological study of aging found that low linguistic ability in young adulthood, determined from an analysis of language samples written by the nuns at age 18–32 years, was associated with increased risk for poor performance on cognitive and memory tests in late adulthood, increased neuropathology characteristic of Alzheimer disease, and increased all-cause mortality among participants. A similar analysis of oral speech samples collected from individuals at risk for the development of Alzheimer disease also found that linguistic ability in late life predicts cognitive decline. These findings suggest that linguistic ability may offer a general measure of cognitive and neurological development. Low linguistic ability may reflect suboptimal neurocognitive development, which in turn may increase or reflect susceptibility to Alzheimer and other dementing diseases.

Read full chapter

URL: 

https://www.sciencedirect.com/science/article/pii/B9780128093245018848

Dementia and Language

S. Kemper, L.J.P. Altmann, in Encyclopedia of Neuroscience, 2009

Implications and Conclusions

There has been considerable interest in using linguistic measures to predict risk, aid in diagnosis, and track the progression of dementia, particularly Alzheimer’s dementia. Performance on tests of verbal memory, such as immediate and delayed word list recall, as well as tests of verbal fluency, appear to be particularly sensitive indicators of risk for dementia and its onset and seem to covary with other known risk factors, such as apolipoprotein E genotype. However, deficits in verbal fluency are not specific to Alzheimer’s disease, as discussed above. The relationship between linguistic ability and the risk for Alzheimer’s disease and longevity has been the focus of the Nun Study, an ongoing longitudinal, epidemiological study of aging. Low linguistic ability in young adulthood, determined from an analysis of language samples written by the nuns at age 18 to 32 years, was associated with increased risk for poor performance on cognitive and memory tests in late adulthood, increased neuropathology characteristic of Alzheimer’s disease, and increased all-cause mortality among participants. These findings suggest that linguistic ability may offer a general measure of cognitive and neurological development. Low linguistic ability in young adulthood may reflect suboptimal neurocognitive development, which in turn may increase or reflect susceptibility to Alzheimer’s and other dementing diseases.

Read full chapter

URL: 

https://www.sciencedirect.com/science/article/pii/B9780080450469018738

Using WAIS-IV with WMS-IV

James A. Holdnack, Lisa W. Drozdick, in WAIS-IV Clinical Use and Interpretation, 2010

Verbal Paired Associates Delayed Word Recall

This delayed free-recall task requires an examinee to recall as many of the words from the list of word pairs as he or she can remember. This task does not require the words to be correctly associated, just recalled. Performance on this task is not considered a measure of associative memory; rather, it is a word list recall task. Also, the juxtaposition of the recognition trial prior to the administration of the free recall condition provides the examinee with another exposure to the correct information, as well as competing incorrect information. Performance on this task is not a true delayed recall condition due to the re-exposure of the stimuli just prior to recall. This is best interpreted as a measure of immediate word recall for previously learned material. Low scores suggest that the examinee did not encode many of the words required to perform the association task and did not benefit from re-exposure to the word pairs. The examinee may have a more basic word list learning problem that may have limited the amount of verbal associations encoded. Also, the task is a free-recall measure compared to the Verbal Paired Associates I and II tasks, which are cued recall. Problems with retrieving information from memory may also contribute to low scores on this measure.

Read full chapter

URL: 

https://www.sciencedirect.com/science/article/pii/B9780123750358100096

DISORDERS OF MEMORY

Peter J. Nestor, in Neurology and Clinical Neuroscience, 2007

Frontotemporal Dementia

There are three clinical presentations of frontotemporal dementia: a neuropsychiatric syndrome, nonfluent progressive aphasia, and semantic dementia.37 Of these, semantic dementia is of most interest with respect to impainment of declarative memory.38 As the name suggests, these patients have progressive semantic memory impairment (factual knowledge, word meanings, and object knowledge), which gives rise to comprehension deficits and fluent aphasia. Unlike post-HSVE cases, significant category-specific deficits in semantic knowledge are rarely encountered, possibly because HSVE is more likely to result in a patchy distribution of cortical damage. In fascinating contrast to amnesic syndromes, patients with semantic dementia have relative preservation of episodic memory, as evinced by their often remarkably rich ability to recount anecdotes from the recent past. An important caveat for the neuropsychological assessment of episodic memory in semantic dementia is that the semantic knowledge deficit confounds performance on verbal memory tasks. Word-list learning or story recall is aided under normal circumstances by the ability to make semantic associations; if semantic knowledge is degraded, then word-list learning is analogous to normal subjects’ learning a list of unfamiliar foreign-language words. Nevertheless, because degeneration is usually maximal in the left temporal lobe, a degree of verbal episodic memory impairment is difficult to rule out. However, on nonverbal tests that minimize semantic associative knowledge (e.g., the Rey-Osterrieth Complex Figure Copy Test [Fig. 4-9]), delayed recall scores are often within the normal range.

The remote memory profile also provides an interesting contrast to that seen in classic amnesic syndromes. Recent episodic memory (dating back weeks to months) is relatively preserved in comparison with memory from more remote time periods,39 a finding that is also true of semantic facts that can be dated to a specific time period (such as knowledge of famous people and events).40 These findings suggest that remote autobiographical memories may actually be supported by similar mechanisms to those involved in semantic memory.

The distribution of degenerative change in semantic dementia is typically asymmetrical and involves the anterior temporal lobes (especially the poles and inferior surfaces) (Fig. 4-10). The preservation of episodic memory was initially thought result from sparing of the hippocampi; however, volumetric MRI has shown that hippocampal atrophy in semantic dementia is at least as severe as that seen in Alzheimer’s disease, which suggests that the amnesia in the latter may be more a consequence of damage to other areas. A final contentious issue in semantic dementia is whether the asymmetrical atrophy of the temporal lobes can give rise to material-specific semantic memory deficits. Some authors have suggested that patients with greater right-sided atrophy have more problems with nonverbal semantics41 (such as prosopagnosia for famous faces). The alternative view is that semantic knowledge is bilaterally distributed but naming is lateralized to the left. Consequently, verbal semantics are more impaired with greater degrees of left temporal atrophy, because this weights word-processing ability.

Read full chapter

URL: 

https://www.sciencedirect.com/science/article/pii/B9780323033541500080

Lyme Encephalopathy

Richard F. Kaplan, in Encyclopedia of the Human Brain, 2002

IV Population Studies

In the laboratory studies of the LE described previously patients were selected on the basis of neurologic complaints. Although these types of studies have been helpful in understanding the nature and severity of neurologic deficits in Lyme disease, they tell us little about the prevalence of these symptoms. Nancy Shadick and colleagues studied the prevalence of persistent neurologic symptoms in a sample of unselected patients with a history of Lyme disease in Ipswich, Massachusetts, a community endemic for Lyme disease. These investigators initially studied 38 people who met CDC criteria for previous Lyme disease and 43 people who did not. There was a slight but statistically significantly difference between groups on the CVLT, with the Lyme disease group performing more poorly. Twelve of the 38 Lyme patients scored two or more standard deviations below mean on the word list test, compared to only 5 of the 43 controls. Patients with residual symptoms, neurologic and musculoskeletal, had longer duration of disease prior to treatment. These findings suggested that a small percentage of patients with previous Lyme disease may have permanent learning and memory deficits, albeit subtle. In a larger subsequent study on Nantucket, another community highly endemic for Lyme disease, these investigators compared 186 people with prior Lyme disease to 167 healthy controls using similar measures including the CVLT. Patients were studied an average of 6 years after infection. Although the patient group reported a higher incidence of nonspecific symptoms, including fatigue, difficulty sleeping, memory impairment, and poor concentration, there were no significant differences between groups on any of the objective tests of memory and concentration. At least two other population studies produced similar findings—namely, that the prevalence of objective measures of LE in previously infected patients who were treated for Lyme disese is very low. Thus, although patients previously infected with Lyme disease may report more neurologic symptoms than never infected controls, there is little evidence of any objective deficits. The relationship between reports of perceived memory dysfunction and performance on memory tests is discussed later.

Read full chapter

URL: 

https://www.sciencedirect.com/science/article/pii/B0122272102001928

The Temporal Lobe

Christian G. Bien, in Handbook of Clinical Neurology, 2022

Memory deficits

Memory deficits are often prominent and a leading complaint. The international consensus paper referred to “working memory deficits” or “short-term memory loss” and did not give an operationalization. The intended meaning was that remote memories usually appear unimpaired, whereas patients perform poorly during one-time tests in the presence of an investigator (“short-term memory”). This terminology has been criticized. It has been pointed out that this “clinical” concept of “short-term memory” has in fact been disentangled into working memory and declarative-episodic memory. Typical tests for “working memory” assess the memory span: How many items—for example, digits—can a proband correctly repeat back immediately after presentation? Episodic memory, by contrast, is typically examined by word list learning tests with delayed recall like the California Verbal Learning Test (CVLT) or the Verbal Learning and Memory Test (VLMT). These word lists are longer than the capacity of the working memory (e.g., 15 items). Nonverbal episodic memory tests are also available. One group of researchers emphasized the dissociation of preserved “working memory” and impaired “long-term anterograde memory” in six patients with LE associated with different abs (Nascimento Alves et al., 2017). Another study performed more sophisticated tests on seven patients with high-concentration “VGKC abs” (probably LGI1 in today’s nomenclature) > 1 year after the disease nadir. All had developed left-sided or bilateral hippocampal atrophy. The authors reported on impaired recent episodic memories but less striking impairment of remote episodic memories. They documented preserved personal semantic memory. There were recall but not recognition memory problems (Lad et al., 2019). One careful long-term study of a patient with relapsing LE due to LGI1 abs illustrates the distinction between an always normal digit and visual span but subnormal performance on a verbal list learning test—more often in the recall than in the learning aspects (Zangrandi et al., 2019). Recently, the boundary between declarative-episodic performance as hippocampal function and working memory as a frontal task has become more permeable: researchers have noted in LE patients a mediotemporal linkage of different types of information, potentially situated in different regions of the brain, regardless of memory duration (Pertzov et al., 2013). For clinical purposes, however, it is recommended to rely on established tests and concepts: in LE, strong deficits are typically observed on delayed recall during list learning tests (episodic memory), whereas the digit span is usually unimpaired (working memory).

Read full chapter

URL: 

https://www.sciencedirect.com/science/article/pii/B9780128234938000249

Memory Tests Using Words

The average person’s short-term memory can hold about 7 pieces of information. This test will help determine your limit. By using mnemonics and other memory exercises you can improve your memory. You can keep taking the test to see how well you are improving.

Numbers Test
Letters Test
Words Test

Word Test

When you click the start button, you will be presented with a bunch of words. After the time has elapsed you will be quizzed to see how many of these words you remember.

Time limit: 90 seconds

!

Save Your Results

If you create an account and sign in you can save and track your results over time.

Studies investigating memory for word lists are amongst the most popular to do for research methods assignments. This is for good reason, since such studies are usually straightforward both conceptually and methodologically. However, problems arise due to people’s choice of words. These problems are important to address in their own right, but also teach us something about doing research in general.

When people do studies of memory for word lists, it’s common for them to make up lists of words off the top of their head. This is a Bad Thing. As an example, consider the study I described in the last post, comparing memory for long words with memory for short words. The logic of this study is that people are given either a list of long words and/or a list of short words to remember. Recall for the respective kinds of list is measured, and then compared using an appropriate analysis, e.g. a t-test. If a significant difference is found, then we conclude that the length of words affects how well we can remember them, and particularly conclude that the phonological loop has a time limited capacity.

The logic above is sound, but only as long as we can discount any alternative explanations. However, if there can be an alternative explanation for why memory for the two lists differs, then we can’t confidently conclude that word length has an effect. Take the following two lists as an example:
cat xylophone
hat phenomenon
mat evolution
bat conundrum
Clearly, one list consists of short words, and one list consists of longer words. However, that’s not the only difference between the two lists. The lists also differ in that:
* all the words in list one are familiar, the words in the second list less so. Familiarity affects memory
* the words in the first list rhyme with each other, words in the second list don’t. Rhyming affects memory.
* words in the first list all refer to concrete objects, words in the second list are more abstract. Concreteness affects memory.
If we find a difference between people’s memory for list one and their memory for list two, we’d want to conclude that it’s because of the word length. Actually, there are at least four possible reasons for such a difference, because there are at least four kinds of difference between the lists: word length; rhyming; familiarity; and concreteness.

(Actually, we probably wouldn’t find a difference, because even the four long words fit into the 2 second phonological loop. Almost everyone would score 4 for each list. We need more words in each list to detect a difference, which illustrates the importance of measures being fine grained enough to measure what we want.)

So, the study described above is clearly flawed because there are alternative explanations for the results – the study is potentially confounded. That’s the general issue I talked about above.

The specific issue is as follows. If you’re doing a study of memory for words, you need to think carefully about the words you use. If you’re doing a between (unrelated) design where the same list of words can be used, e.g. recall with and without interference, then you can relax a little – there’s only one list of words, so no need to worry about differences between those lists. If you’re doing a between design where there are separate lists though, e.g. long and short, you need to worry.

If you’re doing a within (related) design, then you almost always need to choose word lists carefully, because participants will be remembering more than one list of words. If you’re doing a within design where you’re testing memory with and without interference, then you can’t use the same list of words because of practice effects. You need two (or more) lists of words, but you also need to make sure that the lists are equally difficult to remember, so that the only explanation for any difference you find is that for one list there was interference.

In general, when you’re doing a study of memory for word lists where you’re using more than one list of words, then you need to design two matched word lists that you can show are equivalent on any possible confounding variables. Of course, the words will differ on the one criterion you’re interested in as an independent variable, if any. So, if you’re looking at the effects of interference in a within design, you need to ensure that the words in each list are of equal length; equal familiarity; equal concreteness; etc. If you’re doing a within design looking at the effect of word length, then you need to ensure that the words in each list are of equal familiarity; equal concreteness; etc.; but different in terms of word length.

(A quick note: the word length effect arises because of the time based capacity of the phonological loop. Length in this context refers to articulatory length – how long it takes to say a word – not the number of letters in the word. The number of syllables is a rough guide to articulatory length, and certainly a better one than the number of letters.)

So, how do you get these magical matched word lists? Luckily, some kind souls have developed a publicly available database of words marked up with various psycholinguistic characteristics, including articulatory length, familiarity, concreteness, etc. The database allows you to select words according to whichever of these characteristics you want to focus on. Use the database to generate words according to whatever criteria you choose, then randomly choose the number of words you need for each list. You can then write about this in your materials section, to show how much care you’ve taken to eliminate confounding variables. You can access the database at the following address:
http://websites.psychology.uwa.edu.au/school/MRCDatabase/mrc2.html

Use the “Dict Utility Interface” link to access the old, web searchable version of the interface.

I’d recommend using sections 2 & 3 of the interface to select required values of NSYL, the number of syllables; FAM, the familiarity, where 100=not familiar, 700=very familiar; CONC, for concreteness, 100=not concrete, 700=very concrete; and PDWTYPE, part of speech, choosing INClude N, for nouns. Adjust these, then click the GO button to generate a list of words. If anyone wants help, give me a shout or leave a comment.

  • Loading metrics

Open Access

Peer-reviewed

Research Article

  • Daichi Sone,

  • Kazushi Maruo,

  • Hiroyuki Shimada,

  • Keisuke Suzuki,

  • Hiroshi Watanabe,

  • Hiroshi Matsuda ,

  • Hidehiro Mizusawa

Analysis of risk factors for mild cognitive impairment based on word list memory test results and questionnaire responses in healthy Japanese individuals registered in an online database

  • Masayo Ogawa, 
  • Daichi Sone, 
  • Kazushi Maruo, 
  • Hiroyuki Shimada, 
  • Keisuke Suzuki, 
  • Hiroshi Watanabe, 
  • Hiroshi Matsuda, 
  • Hidehiro Mizusawa

PLOS

x

  • Published: May 17, 2018
  • https://doi.org/10.1371/journal.pone.0197466

Figures

Abstract

Although the development of effective therapeutic drugs and radical treatment options for dementia and Alzheimer’s disease (AD) remains urgent, progress in recent clinical trials of AD drugs has been less than adequate. In order to advance the progress of clinical trials, it is necessary to establish more efficient methods of recruitment. In Japan, there are registration systems stratified by mild cognitive impairment and preclinical and clinical stages of early and advanced stage dementia, but there is no registration system for healthy individuals yet. Therefore, in the present study, we developed a large-scale, internet-based health registry to investigate factors associated with cognitive function among registered participants. A total of 1038 participants completed the initial questionnaire and word list memory test. Among these participants, 353 individuals completed a second questionnaire and memory test. Stepwise multiple regression analysis was performed using IBM SPSS version 23.0 for Windows at a statistical significance level of p<0.05. We found that mood, motivation, and a decreased ability to perform activities of daily living were significantly associated with cognitive function. The results of the present study suggest that maintaining social involvement is important to prevent decreases in physical activity, daily function, mood, and motivation.

Citation: Ogawa M, Sone D, Maruo K, Shimada H, Suzuki K, Watanabe H, et al. (2018) Analysis of risk factors for mild cognitive impairment based on word list memory test results and questionnaire responses in healthy Japanese individuals registered in an online database. PLoS ONE 13(5):
e0197466.

https://doi.org/10.1371/journal.pone.0197466

Editor: David Fardo, University of Kentucky, UNITED STATES

Received: January 30, 2018; Accepted: May 2, 2018; Published: May 17, 2018

Copyright: © 2018 Ogawa et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Due to the Japanese regulation, the Act on the Protection of Personal Information, only researchers approved by the Ethics Committee can have access to the data. For more information, please contact the Ethics Committee of National Center of Neurology and Psychiatry (rinri-jimu@ncnp.go.jp).

Funding: This work was carried out under the Brain Mapping by Integrated Neurotechnologies for Disease Studies (Brain/MINDS) project (grant number 17dk0207028h0002 to Hidehiro Mizusawa), funded by the Japan Agency for Medical Research and Development (AMED). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The number of people with dementia in Japan is estimated to reach 7 million by the year 2025 [1]. Despite the urgent need to develop therapeutic strategies for dementia and Alzheimer’s disease (AD), progress in recent clinical trials of AD drugs has been less than adequate [2]. Matsuda et al. reported that over the past 10 years, clinical trials for AD modifying therapies have been largely unsuccessful, partly due to difficulties in recruiting early stage patients for enrollment [3]. Until therapeutic drugs are developed, it is essential to examine risk factors for dementia and intervene in lifestyle habits that may put one at a risk of AD. A recent review reported that modifiable risk factors for AD are mostly related to either cardiovascular risk factors (diabetes, hypertension, and obesity) or lifestyle habits (e.g., smoking, physical activity, diet, and mental and social activity) [2]. Thus, until more effective therapeutic drugs and radical treatment options are developed for AD, the most promising strategies require the assessment and modification of risk factors for dementia. Although the development of radical therapeutic strategies remains critical, the importance of creating a registry system for individuals with normal cognitive function at a risk of AD cannot be understated. To ensure that clinical trials targeting mild cognitive impairment (MCI) and the preclinical/early stages of AD are conducted efficiently, it is necessary to establish more appropriate methods for large-scale clinical trial recruitment [4]. In clinical research aimed at preventing dementia, a large-scale registration system is necessary to make it scale to validate its efficacy. The American Global Alzheimer’s Platform [5] and European Prevention of Alzheimer’s Dementia [6] were designed to develop new treatments for secondary prevention. These are actively thriving internet-based registries. In Japan, however, there is not yet a large-scale registration system. It is necessary to recruit enough participants to validate its efficacy. Therefore, it is necessary to establish a system aiming at facilitating patient registration in clinical trials and, at the same time, use this registration system as a platform for preventive clinical research.

Thus, in the present study, we aimed to create a large-scale, internet-based registry system for healthy people, known as the Integrated Registry of Orange Plan (IROOP®), to identify not only factors associated with cognitive function, but also those which affect changes in cognitive function over a 6-month period.

Participants and methods

Participants

Registration in the IROOP® system began on July 5, 2016. The present study included 1038 individuals whose registration information, responses to all items of the initial questionnaire, and word list memory test results (MCI Screen) were entered on or before August 15, 2017 (mean age: 59.0±10.4 years; 400 men and 638 women; Table 1), as well as 353 individuals who had completed the follow-up questionnaire and a second MCI Screen 6 months after completing the initial questionnaire (mean age: 60.2± 10.0 years; 139 men and 214 women; Table 2).

This internet-based registry system targeted healthy Japanese people whose cognitive function has not remarkably deteriorated and were aged 40 years or older, living in Japan, and native Japanese speakers. This study excluded those who had already been diagnosed with AD, MCI, dementia, frontotemporal dementia, Lewy body type dementia, psychiatric disorders (major depression, bipolar disorder, anxiety disorder, obsessive compulsive disorder, posttraumatic stress disorder, panic disorder, schizophrenia, and eating disorders), and those taking symptom-controlling drugs, such as Aircept. We recruited participants using advertising media, such as the television and newspaper. In addition, we explained our registry and recruited participants at a lecture open to the public and research societies.

Internet-based questionnaire items

Using the questionnaire administered to patients in the Brain Health Registry (http://www.brainhealthregistry.org/) of the United States as a reference, although there are differences in the number depending on participants, we generated approximately 220 items for the online questionnaire. After logging into the IROOP® system (https://www.iroop.jp/), participants entered their consent and registration information, following which personal pages were created (“My Pages”). Participants accessed the initial questionnaire on their respective My Pages. The follow-up questionnaire was displayed on the My Page 6 months after the initial questionnaire had been completed. Questionnaire items were categorized as follows:

  • Items required for registration: e-mail address, birthday, gender, years of education, race, prefecture of residence, and the presence or absence of any housemates.
  • Items on the initial questionnaire: weight, height, lifestyle (demographics, mood, quality of life, sleep patterns, and diet), and medical history (present illness, medication, past history, family history, past history of head and neck injuries or concussion, and daily cognitive function).
  • Items on the follow-up questionnaire (administered every 6 months; note that registration in this system is in progress and this study uses the initial questionnaire and the first six month follow up data of the first time and the first regular time in this study): health status, mood, quality of life, sleep patterns, diet, medication history, history of present illness, past history of head and neck injuries and concussion, and daily cognitive function.

Questionnaire responses

The questionnaires included items that required yes/no responses, as well as those for which multiple response options were provided. For example, participants chose either “1: yes” or “2: no” when presented with the question, “Do you feel that your life is empty?” For questions with multiple response options, participants rated their responses using a scale similar to the following: “1: very difficult,” “2: a little difficult,” or “3: not difficult at all.” The questionnaire also included open-ended items for which participants could provide unique responses.

Word list memory test

Whenever participants completed either the initial or periodic questionnaire, a toll-free telephone number was posted on their My Page. Calling the number enabled participants to take the Japanese version of the word list memory test (MCI Screen) [7] for free. The MCI Screen is a simplified scale for the assessment of cognitive function that has been approved by the United States Food and Drug Administration. The examination takes approximately 15 minutes to complete and the questions differ for each session. A scoring algorithm is then used to calculate a memory performance index (MPI) score based on the patient’s test results, age, educational background, and race [8]. The MPI quantifies the pattern of correctly recalled words from the Consortium to Establish a Registry for Alzheimer’s Disease wordlist on a scale from 0 to 100, which distinguishes normal from MCI with an accuracy rate of 96–97% [8].

Statistical analysis

Statistical analyses were performed using IBM SPSS version 23.0 for Windows (SPSS Inc., Tokyo, Japan). Differences in age groups were analyzed using an ANOVA and χ2 tests were used to analyze differences in categorical variables. Stepwise multiple regression analyses were used to identify questionnaire items associated with the MPI score, using the initial MPI score as the dependent variable and each questionnaire item as the independent variable. In the present study, nonessential questionnaire items and open-ended questions were excluded from analysis. Moreover, items that were irrelevant to all participants in the initial questionnaire (previous history of non-parkinsonian motor disorders, Huntington’s disease, amyotrophic lateral sclerosis, motor neuron diseases other than amyotrophic lateral sclerosis, and multiple sclerosis) were excluded from analyses.

Next, we performed stepwise multiple regression analysis to identify which questionnaire items were associated with longitudinal changes in cognitive function, using the difference between the initial and follow-up MPI scores as the dependent variable and each questionnaire item as the independent variable. These analyses were performed using data from the 353 participants who completed the follow-up questionnaire and the second MCI Screen 6 months after completing the initial questionnaire. Similarly, items that were irrelevant to all participants (history of Parkinson’s disease, non-parkinsonian motor disorders, Huntington’s disease, amyotrophic lateral sclerosis, motor neuron diseases other than amyotrophic lateral sclerosis, multiple sclerosis, medication history, obsessive compulsive disorder, hoarding disorder, and mental disorder) were excluded from analyses. The level of statistical significance was set at p<0.05.

Ethical considerations

The present study was approved by the ethics committee of the National Center of Neurology and Psychiatry. All included participants provided informed consent by marking the appropriate box on the IROOP® home page, on which the full details of the study were posted. This study was registered in the University Hospital Medical Information Network Clinical Trials Registry (UMIN000022795).

Results

Participant characteristics

Table 1 presents the characteristics of the 1038 participants who had completed the initial questionnaire and the MCI Screen. Among participants in their 40s to 60s, the proportion of women was greater than that of men, whereas the reverse was true among participants in their 70s and 80s We observed no significant differences in the years of education among the age groups, likely due to the use of an internet-based registry system. MPI scores decreased along with increases in age.

Table 2 presents the characteristics of the 353 participants who completed the follow-up questionnaire and second MCI Screen. Again, the proportion of women was greater than that of men among participants in their 40s to 60s, whereas the reverse was true among participants in their 70s and 80s. MPI scores also decreased along with increases in age. There was no significant difference in MPI score and gender among age groups; however, there was a significant difference in the years of education.

Multiple regression analysis of each questionnaire item and MPI scores

Table 3 shows the results of the stepwise multiple regression analysis of the initial MPI scores, including the coefficients linking each independent variable to the dependent variable.

MPI scores were significantly associated with the following questionnaire items: age, gender, years of education, the extent of changes in the ability to adjust one’s schedule in advance for anticipated events over a 10-year period; the extent of difficulty in bathing and dressing alone, and a past history of cancer or diabetes mellitus. The coefficient of determination for the generated model (R2) was 0.608 (p<0.05). Although MPI scores decreased along with increases in age, these scores were significantly higher among women than men.

We then examined the answers for each questionnaire item by MPI score. For the question, “how difficult is it for you to bathe and dress by yourself, according to your health status?,” participants chose the most appropriate response from among the following three options: “1: very difficult,” “2: a little difficult,” or “3: not difficult at all.” The MPI scores of participants who responded with “3: not difficult at all” were approximately 3.8 points higher than those who responded with “1: very difficult.” For the question, “during the past month, how much of a problem has it been for you to have enough enthusiasm to get things done?,” participants chose the most appropriate response from among the following four options: “1: no problem at all,” “2: only a little problem,” “3: some problem,” and “4: considerable problem.” The MPI scores of participants who responded with “3: considerable problem” were approximately 2.5 points lower than those who responded with “1: no problem at all.” For the question, “do you currently have cancer or have you ever had cancer?,” participants chose either “1: yes” or “2: no.” The MPI scores of participants who responded with “2: no” were approximately 2.3 points higher than those of participants who responded with “1: yes.” For each additional year of education, MPI scores increased by approximately 2.9 points.

Among the items shown in Table 3, the following factors were most strongly associated with MPI score: age, gender, difficulty in bathing and dressing alone according to health status, difficulty in maintaining enthusiasm for accomplishing tasks, and ability to create a schedule before an expected event.

Multiple regression analysis was then used to evaluate data from the 353 participants who completed the baseline and follow-up questionnaires as well as the MCI Screen (Table 4).

These analyses revealed that the following questionnaire items were associated with changes in MPI scores during the 6 months between the initial and follow-up examinations: initial MPI score, age, feelings of emptiness, an increase or decrease in daily activities or interests over the past 6 months, among others. The coefficients representing the contribution of each independent variable to the dependent variable are shown in Table 4. The following questionnaire items, listed in descending order of t value, were associated with changes between the initial and second MPI scores: initial MPI score, age, an increase or decrease in daily activities or interests over the past 6 months, and a past history of traumatic brain injury.

When asked to evaluate changes in the ability to organize things (e.g., mail, papers, etc.) over the past 10 years, participants selected their responses from among the following five options: “1: better than before or unchanged,” “2: questionable/sometimes worse,” “2.5: unknown,” “3: gradually worsening,” and “4: increasingly worsening.” The MPI scores of participants who selected “1: better than before or unchanged” were approximately 2.4 points higher than the scores of those who selected “4: increasingly worsening.” Furthermore, the MPI scores of participants who reported no history of hearing loss were approximately 2.4 points higher than those who reported such a history. The MPI scores of participants who reported feeling that their situation was “hopeless” were approximately 2.8 points lower than those who did not report such feelings.

Discussion

In the present study, we aimed to identify factors associated with cognitive function (MPI score) as well as those affecting changes in cognitive function over a 6-month period among healthy Japanese adults registered in the IROOP® database. Stepwise multiple regression analysis revealed that 19 factors from the initial questionnaire and 20 factors from the follow-up questionnaire were significantly associated with MPI score. Factors significantly associated with initial MPI score included difficulty bathing/dressing alone, level of happiness most of the time, history of cancer, the extent of change in the ability to make adjustments to one’s schedule in advance, and history of diabetes mellitus (Table 3). Multiple regression analysis of data from 353 participants revealed that the following items were significantly associated with changes between the initial and follow-up MPI scores: Compared to 6 months ago, are you pursuing fewer or more activities and interests? Do you feel that your life is empty? and feelings of hopelessness regarding one’s general situation.

In the present study, participants were asked to evaluate their extent of difficulty in bathing and dressing alone. This item, which was significantly associated with initial MPI score, reflects basic activities of daily living that involve physical movements. Fratiglioni et al. [9] highlighted the destructive nature of confining oneself to the home in old age, as it leads to decreased physical activity and human interaction that contributes to the rapid deterioration of mental and physical function. Sabia et al. [10] reported that a lower risk of dementia in physically active people may be attributed to reverse causation; that is, due to a decline in physical activity levels in the preclinical phase of dementia.

Such impairments; MCI then lead to further reductions in activity, allowing the cycle to continue. Thus, regular physical exercise and maintaining the ability to perform basic activities of daily living should be promoted, as these may aid older adults in preventing the development and progression of substantial MCI.

Moreover, our analysis of initial responses revealed that the MPI scores of participants who reported feeling happy most of the time were approximately 2.5 points higher than those of participants who responded otherwise. In addition, the MPI scores of participants who reported no difficulty in maintaining enthusiasm for accomplishing tasks were approximately 2.5 points higher than those who reported considerable difficulty in maintaining enthusiasm. A constant state of low mood or enthusiasm causes depressive symptoms, which have been identified as risk factors for social isolation and reduced activity [11]. In contrast, social involvement, intellectual activities, and social networks have been recognized as protective factors against the development of dementia [12]. The magnitude of the association of social participation is comparable to other well-established predictors of cognitive functioning, providing evidence that social participation plays an important role in cognitive functioning and successful aging [13]. To prevent decreases in physical activity and human interaction due to a rapid progression of physical and cognitive impairment, clinicians and researchers should stress the importance of social integration and maintaining the ability to perform activities of daily living.

Given these findings, the availability of social opportunities and activities outside the home for middle-aged and older adults seems to be critical for maintaining physical and cognitive function. In Japan, a social project called the Dementia (Orange) Café has been implemented in various communities, medical institutions, and other venues. This is one of the main policies presented in the Comprehensive Strategy to Accelerate Dementia Measures (New Orange Plan) issued by the Ministry of Health, Labour, and Welfare. At these cafés, anyone, including those diagnosed with dementia and their families, as well as others interested in the prevention of dementia, can connect with local communities and specialists in their region. The results of the present study highlight the need for public agencies and organizations to support this and similar projects.

Previous prospective cohort studies have revealed that lifestyle-related diseases and lifestyle factors are closely associated with the incidence of AD [9]. Consistent with the 1988 Hisayama Study that demonstrated that the incidence of AD was significantly higher among patients with diabetes mellitus [14], our findings suggest that diabetes mellitus is associated with cognitive impairment. Likewise, the Hisayama Study reported smoking as a risk factor, which is consistent with our findings [15]. Although the present study yielded some results that were comparable to those of previous studies, our findings also indicated that MPI scores were higher in participants who reported poor sleep quality and poor participation in events at the public hall. As these results are opposed to those of previous studies, they must be interpreted with caution. Future studies should investigate the relevance of these factors in AD among a larger group of participants over a longer period of time.

The level of education did not significantly differ among age groups for participants who completed the follow-up questionnaire. Such findings suggest that highly educated older adults are likely to be interested in studies that rely on this type of registry system.

As less than half of the number of people who completed the initial questionnaire also completed the follow-up assessment, there is a possibility that the low response rate generated response bias. People who are confident in their memory may have completed the follow-up assessment. It is necessary to keep in mind the possibility that someone who lacks confidence in their memory did not complete the follow-up assessment. This represents a potential limitation of our study, in that our findings may not be generalizable to older adults with lower levels of education.

Among the 353 participants who completed MPI assessments at the 6-month follow-up, some individuals exhibited improvements in cognitive function between the first and second assessments. This finding indicates that those who were interested in this registry system and participated in this study may also have been interested in the prevention of dementia and managing modifiable risk factors for dementia in their daily lives. In addition, although the questions in the MCI Screen differed for each session, we speculate that participants may have become more familiar with taking the test over the telephone by the second session. Indeed, previous neuropsychological studies have reported that responses to repeated stimulation follow a natural course, eventually reaching a plateau [16]. Thus, the effect of increasing familiarity to the assessment may subside with more follow-up sessions.

The items of traumatic brain injury have been extracted this time, and it is necessary to carefully follow people who have this clinical history. In addition, there are items related to pain as the first extracted as common in both the first and second times, and it also shows the importance of first removing organic pain mechanically. Secondly, there were items related to mood and motivation; it will be necessary to identify old age depression, as this could lead to early interventions for depression.

At the 2017 International Conference of Alzheimer’s Disease International in London, the following risk factors for dementia were among those identified as modifiable factors: depression, obesity, diabetes mellitus, decreased social interaction, and lack of exercise [17]. Because numerous studies have also reported relatively consistent results regarding risk and preventive factors for dementia [2], a consensus has begun to emerge. Indeed, the present study identified certain activities of daily living and diabetes mellitus as risk factors for dementia. Because the currently available drug therapies prevent the progression of dementia only to a limited extent, efforts should be made to prevent or delay the onset of dementia via the modification of significant risk factors. We aim to continue our investigation of modifiable factors in future studies.

Acknowledgments

We greatly appreciate Mrs. Yuko Furuya, Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, and Mr. Jun Sasaki, Nittetsu Hitachi Systems, for their stimulating and inspiring discussions and for supporting this system.

References

  1. 1.
    Government of Japan: Annual Report on the Aging Society.2017

    • 2.
      Crous-Bou M, Minguillōn C, Gramunt N, Molinuevo J. Alzheimer’s disease prevention: from risk factors to early intervention. Alzheimers Res Ther. 2017;9(1): 71. pmid:28899416

      • View Article
      • PubMed/NCBI
      • Google Scholar
    • 3.
      Matsuda H, Mizusawa H, Maikusa N, Imabayashi E, Ogawa M, Toba K, et al. Online registry for the prevention of dementia in Japan. Alzheimer Dement. 2016;12(7): P1178.

      • View Article
      • Google Scholar
    • 4.
      Krysinska K, Sachdev PS, Breitner J, Kivipelto M, Kukull W, Brodaty H. Dementia registries around the globe and their applications: A systematic review. Alzheimers Dement. 2017;13(9): 1031–1047. pmid:28576507

      • View Article
      • PubMed/NCBI
      • Google Scholar
    • 5.
      Commings J, Aisen P, Barton R, Bork J, Doody R. Re-Engineering Alzheimer Clinical Trials: Global Alzheimer’s Platform Network.J Prev Alzheimers Dis. 2016;3(2):114–120. pmid:28459045

      • View Article
      • PubMed/NCBI
      • Google Scholar
    • 6.
      Ritchie C, Molinuevo J, Truyen L, Satlin A, Geyten S. Development of interventions for the secondary prevention of Alzheimer’s dementia: the European Prevention of Alzheimer’s Dementia(EPAD) project: Lancet Psychiatry 2016;3:179–86 pmid:26683239

      • View Article
      • PubMed/NCBI
      • Google Scholar
    • 7.
      Cho A, Sugimura M, Nakano S, Yamada T. The Japanese MCI screen for early detection of Alzheimer’s disease and related disorders. Am J Alzheimers Dis Other Demen. 2008;23(2): 162–166. pmid:18223126

      • View Article
      • PubMed/NCBI
      • Google Scholar
    • 8.
      Shankle WR, Mangrola T, Chan T, Hara J. Development and validation of the Memory Performance Index: reducing measurement error in recall tests. Alzheimers Dement. 2009;5(4): 295–306. pmid:19560100

      • View Article
      • PubMed/NCBI
      • Google Scholar
    • 9.
      Fratiglioni L, Paillard-Borg S, Winblad B. An active and socially integrated lifestyle in late life might protect against dementia. Lancet Neurol. 2004;3(6):343–353. pmid:15157849

      • View Article
      • PubMed/NCBI
      • Google Scholar
    • 10.
      Sabia S, Dugravot A, Dartigues JF, Abell J, Elbaz A, Kivimäki M, et al. Physical activity, cognitive decline, and risk of dementia: 28 year follow-up of WhitehallⅡcohort study. BMJ 2017;357: j2709 pmid:28642251

      • View Article
      • PubMed/NCBI
      • Google Scholar
    • 11.
      Rosqvist E, Heikkinen E, Lyyra TM, Hirvensalo M, Kallinen M, Leinonen R, et al. Factors affecting the increased risk of physical inactivity among older people with depressive symptoms. Scand J Med Sci Sports 2009: 19:398–405 pmid:18503493

      • View Article
      • PubMed/NCBI
      • Google Scholar
    • 12.
      Fratiglioni L, Wang HX, Ericsson K, Maytan M, Winblad B. Influence of social network on occurrence of dementia, a community based longitudinal study. Lancet. 2000;355(9212): 1315–1319. pmid:10776744

      • View Article
      • PubMed/NCBI
      • Google Scholar
    • 13.
      Bourassa KJ, Memel M, Woolverton C, Sbarra DA. Social participation predicts cognitive functioning in aging adults over time: comparisons with physical health, depression, and physical activity. Aging & Mental Health.2017;21(2):133–146

      • View Article
      • Google Scholar
    • 14.
      Yoshitake T, Kiyohara Y, Kato I, Ohmura T, Iwamoto H, Nakayama K, et al. Incidence and risk factors of vascular dementia and Alzheimer’s disease in a defined elderly Japanese population: The Hisayama Study. Neurology. 1995;45(6): 1161–1168. pmid:7783883

      • View Article
      • PubMed/NCBI
      • Google Scholar
    • 15.
      Ohara T, Ninomiya T, Hata J, Ozawa M, Yoshida D, et al. Midlife and Late-Life Smoking and Riskof Dementia in the Community: The Hisayama Study. Geriatr Soc.2015;63:(11):2332–9

      • View Article
      • Google Scholar
    • 16.
      Luria AR. The Basics of Neuropsychology, 2nd ed. Shinkosha Printing Co. Tokyo Japan; 1999.

      • 17.
        Livingston G, Sommerlad A, Ortega V, Costafreda SG, Huntley J, Ames D, et al. Dementia prevention, intervention, and care. Lancet. 2017;390 (10113): 2673–2734. pmid:28735855

        • View Article
        • PubMed/NCBI
        • Google Scholar

      Like this post? Please share to your friends:
    • Testing for microsoft excel
    • Test по английскому языку 7 класс fill in the correct word
    • Test your word knowledge
    • Test your word formation
    • Test your english word