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Poor coherence in older people's speech is explained by impaired semantic and executive processes

  1. Paul Hoffman  Is a corresponding author
  2. Ekaterina Loginova
  3. Asatta Russell
  1. University of Edinburgh, United Kingdom
Research Article
Cite this article as: eLife 2018;7:e38907 doi: 10.7554/eLife.38907
7 figures, 3 tables and 2 additional files

Figures

Process for computing coherence in speech samples.
https://doi.org/10.7554/eLife.38907.003
Effects of age and task on speech rate and coherence *p<0.05; ***p<0.001.
https://doi.org/10.7554/eLife.38907.005
Effects of semantic and executive abilities on coherence *p<0.05; **p<0.01; ***p<0.001.
https://doi.org/10.7554/eLife.38907.006

(A) Principal components analysis identifying four latent speech factors. (B) Effects of semantic and executive abilities on factor scores. *p<0.05; **p<0.01; ***p<0.001.

https://doi.org/10.7554/eLife.38907.007
Example trials from semantic tasks.

The correct response is highlighted in each case.

https://doi.org/10.7554/eLife.38907.008
Appendix 5—figure 1
Results of tests of semantic processing.

Cong = congruent; Incon = incongruent; Lex Dec = lexical decision.

https://doi.org/10.7554/eLife.38907.018
Appendix 5—figure 2
Reaction times on the manual secondary task.
https://doi.org/10.7554/eLife.38907.019

Tables

Table 1
Results of mixed effects models predicting global and local coherence.
https://doi.org/10.7554/eLife.38907.004
Model 1Model 2Model 3
BSePBSePBSeP
Global Coherence
(Intercept)44.61.45<0.00144.61.43<0.00144.61.42<0.001
Age−2.300.54<0.001−1.970.50<0.001−0.680.73.35
Task−0.310.24.20−0.310.24.20−0.300.24.21
Age*Task−0.530.25.056−0.530.25.052−0.530.25.052
Response length−0.970.38.014−0.900.36.016−0.860.35.019
Trails ratio−1.610.45<0.001−1.710.42<0.001
Semantic knowledge−1.630.73.028
Semantic selection1.160.42.007
Weak association0.290.52.58
Local Coherence
(Intercept)26.81.36<0.00126.81.35<0.00126.81.34<0.001
Age−2.510.58<0.001−2.270.57<0.001−1.420.80.081
Task−0.160.34.63−0.160.33.63−0.160.34.64
Age*Task−0.550.32.10−0.550.32.10−0.550.32.10
Response length0.010.39.980.090.38.820.120.38.74
Trails ratio−1.160.45.012−1.230.43.006
Semantic knowledge−1.140.76.14
Semantic selection0.940.43.034
Weak association0.330.54.54
Appendix 1—table 1
Demographic information and mean test scores for young and older participants.
https://doi.org/10.7554/eLife.38907.012
Young adultsOlder adults
N3030
Age19.3 (2.2)76.0 (8.3)
Sex M:F8:2215:15
Years of education13.8 (0.9)14.3 (3.0)
MMSE /3028.8 (1.0)29.2 (1.1)
Category fluency (items per category)25.4 (5.4)**21.1 (5.2)
Letter fluency (items per category)12.9 (5.0)16.4 (7.1)*
Trails A errors0.1 (0.3)0.1 (0.3)
Trails B errors0.5 (1.0)0.9 (1.4)
Trails A time (s)26.9 (9.1)**35.9 (11.7)
Trails B time (s)46.2 (12.8)***76.3 (34.9)
Trails ratio score (B time / A time)1.84 (0.69)2.12 (0.70)
  1. Standard deviations are shown in parentheses. Asterisks indicate the significance of t-tests comparing young and older adults. *p<0.05; **p<0.01; ***p<0.001.

Appendix 3—table 1
Examples of high and low coherence responses.
https://doi.org/10.7554/eLife.38907.015
ExamplePromptResponse
 Low GC (22), low LC (11). Older participant.Which is your favourite season and why?My favourite season is spring because it increases the amount of light that you receive from the sun. It’s not easy to know why the sun should get bigger but the more you think about it, the more you realise that it’s all because in earlier times, people worked out that the earth was a small ball and was affected by the sun, during its travels. In fact, if you’re listening to the test match you won’t hear anything from Australia unless you get up in the middle of the night and go through to the morning. And that seems to me to, for small boys anyway, is one of the main reasons why it’s quite effective to do that.
 Low GC (26), high LC (37). Young participant.Describe a typical visit to a restaurant.I’d get changed. Once I’d got changed, I would get the bus or I would drive in with the family to a restaurant. We’d use the car. We’d drive through into town to get to the restaurant. We’d find a parking space and we’d have a longer walk into town. Once we get into town we’d go through, we’d go up past the bridges looking for a nice place, a place with a view. We’d walk through St. Andrews Square and look for somewhere with a balcony. We’d travel through maybe George Street to somewhere fancy to dine.
 Moderate GC (44), low LC (16). Young participant.What do people generally do when getting ready for work in the morning?They usually, you know, get out of bed and stuff and then make their breakfast, and then make their lunch if they're going to be in for lunch as well. And get ready, put their clothes on, and then lock everything up again and leave, however they usually get there. So they might be on the bus or something. Like some people like to have a shower in the morning before work as well. I like to take the recycling out on the way to work, which is good. So they do lots of different things depending on what their work is and depending whether it's in the morning or they’re leaving at night time for work.
 High GC (59), high LC (58). Older participantWhich is your favourite season and why?My favourite season is spring which, where I live, is quite a dramatic season because there is a tremendous difference from winter, which is cold and everything is, all the flowers and plants appear to be dead, trees have no leaves. So once spring comes, the buds start coming on the trees, plants start bursting through the ground. The earliest ones are probably the snowdrops, followed by crocuses and daffodils and other spring bulbs. And then it moves on, as the spring develops, into the beautiful blossom of cherry and plum and I have a beautiful wild plum tree in my neighbour’s back garden, which I enjoy very much every spring. It’s my perfect spring tree. The weather generally begins to warm up a bit; we lose any likelihood of getting snow or ice, although it may still be wet and cold.

Additional files

Supplementary file 1

Results of mixed effects models predicting characteristics of speech.

https://doi.org/10.7554/eLife.38907.009
Transparent reporting form
https://doi.org/10.7554/eLife.38907.010

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