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Background Hebb repetition learning is a form of long-term serial order learning that can occur when sequences of items in an immediate serial recall task are repeated. Repetition improves performance because of the gradual integration of serial order information from short-term memory into a more stable long-term memory trace. Aims The current study assessed whether adolescents with non-specific intellectual disabilities showed Hebb repetition effects, and if their magnitude was equivalent to those of children with typical development, matched for mental age. Methods Two immediate serial recall Hebb repetition learning tasks using verbal and visuospatial materials were presented to 47 adolescents with intellectual disabilities (11–15 years) and 47 individually mental age-matched children with typical development (4–10 years). Results Both groups showed Hebb repetition learning effects of similar magnitude, albeit with some reservations. Evidence for Hebb repetition learning was found for both verbal and visuospatial materials; for our measure of Hebb learning the effects were larger for verbal than visuospatial materials. Conclusions The findings suggested that adolescents with intellectual disabilities may show implicit long-term serial-order learning broadly commensurate with mental age level. The benefits of using repetition in educational contexts for adolescents with intellectual disabilities are considered.
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Research in Developmental Disabilities 125 (2022) 104219
Available online 19 March 2022
0891-4222/© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license
(http://creativecommons.org/licenses/by/4.0/).
Hebb repetition learning in adolescents with
intellectual disabilities
Lucy A. Henry
a
,
*
, Sebastian Poloczek
b
, David J. Messer
a
,
c
, Rachel Dennan
a
,
Elisa Mattiauda
a
, Henrik Danielsson
d
,
e
a
Division of Language and Communication Science, City, University of London, UK
b
Department of Psychology, Goethe University, Frankfurt, Germany
c
Faculty of Wellbeing, Education & Language Studies, Open University, UK
d
Department of Behavioural Sciences and Learning, Link¨
oping University, Link¨
oping, Sweden
e
Linnaeus Centre HEAD, Swedish Institute for Disability Research, Link¨
oping University, Link¨
oping, Sweden
ARTICLE INFO
Keywords:
Hebb repetition learning
Intellectual disability
Adolescents
Mental-age matching
ABSTRACT
Background: Hebb repetition learning is a form of long-term serial order learning that can occur
when sequences of items in an immediate serial recall task are repeated. Repetition improves
performance because of the gradual integration of serial order information from short-term
memory into a more stable long-term memory trace.
Aims: The current study assessed whether adolescents with non-specic intellectual disabilities
showed Hebb repetition effects, and if their magnitude was equivalent to those of children with
typical development, matched for mental age.
Methods: Two immediate serial recall Hebb repetition learning tasks using verbal and visuospatial
materials were presented to 47 adolescents with intellectual disabilities (1115 years) and 47
individually mental age-matched children with typical development (410 years).
Results: Both groups showed Hebb repetition learning effects of similar magnitude, albeit with
some reservations. Evidence for Hebb repetition learning was found for both verbal and visuo-
spatial materials; for our measure of Hebb learning the effects were larger for verbal than vi-
suospatial materials.
Conclusions: The ndings suggested that adolescents with intellectual disabilities may show im-
plicit long-term serial-order learning broadly commensurate with mental age level. The benets
of using repetition in educational contexts for adolescents with intellectual disabilities are
considered.
1. Introduction
Hebb repetition learning (Hebb, 1961) is a form of incidental learning that occurs when sequences of items are repeatedly pre-
sented in the same order. It involves a core learning mechanism that gradually transfers serial order information in short-term memory
(e.g., phonological word forms) into stable long-term memory representations via repeated exposure, or repetition (Attout, Ordonez
Magro, Szmalec, & Majerus, 2020). Procedural memory is believed by some to be the dominant system involved in Hebb repetition
* Correspondence to: Language and Communication Science, City, University of London, London ECV1 0HB, UK.
E-mail address: lucy.henry.1@city.ac.uk (L.A. Henry).
Contents lists available at ScienceDirect
Research in Developmental Disabilities
journal homepage: www.elsevier.com/locate/redevdis
https://doi.org/10.1016/j.ridd.2022.104219
Received 3 August 2021; Received in revised form 20 January 2022; Accepted 8 March 2022
Research in Developmental Disabilities 125 (2022) 104219
2
learning (HRL) - at least in children - and is largely based on implicit processes (Attout et al., 2020). Procedural memory (Hsu & Bishop,
2014) is an important system for commonly repeated, well-known or ‘automatedactivities in different domains of everyday life, such
as acquiring habits, learning implicit rules of grammar, learning new words, or skilled reading (e.g., Bogaerts, Szmalec, Hachmann,
Page, & Duyck, 2015; Page & Norris, 2009).
Whilst there is an established literature on systems that support immediate ‘onlinestorage and information processing, i.e.,
‘working memoryin individuals with non-specic intellectual disabilities (ID) (e.g., Henry, Messer, & Poloczek, 2018), there is no
literature about HRL in these individuals. Consequently, we know little about this core mechanism that could be relevant to learning in
several important domains for adolescents with ID such as grammar, vocabulary and reading (e.g., Attout et al., 2020; Bogaerts,
Szmalec, De Maeyer, Page, & Duyck, 2016; Smalle, Page, Duyck, Edwards, & Szmalec, 2018), potentially acting as a powerful learning
tool for this group.
The current study explored the nature and extent of HRL in adolescents with non-specic ID, comparing them with younger
children with typical development (TD) matched for mental age. ID is a neurodevelopmental condition that begins in childhood, and is
characterised by intellectual and adaptive functioning difculties within conceptual, social, and practical domains. It is a common
condition, with a prevalence of between 1% and 3% worldwide (McKenzie, Milton, Smith, & Ouellette-Kuntz, 2016; Patel, Cabral, Ho,
& Merrick, 2020).
As HRL is a form of incidental long-term serial order learning that occurs when sequences of items in an immediate serial recall task
are repeated (Hebb, 1961), it is distinct from short-term recall for this information (Mosse & Jarrold, 2010). HRL reects the gradual
integration of serial order information within short-term memory into a more stable and unied long-term memory trace (Bogaerts,
Siegelman, Ben-Porat, & Frost, 2018). Thus, sequences maintained for immediate recall contribute to long-term memory traces, and
long-term memory traces, in turn, help improve immediate serial recall when sequences are repeated (Oberauer, Jones, & Lew-
andowsky, 2015). HRL is usually measured using immediate serial recall tasks for letters, digits, syllables, words, spatial locations or
nonsense pictures. The current study focused on immediate serial recall tasks for verbal (words) and visuospatial (nonsense pictures)
materials in which some to-be-remembered sequences were repeated (‘Hebb trials), whereas other sequences were always novel
(‘ller trials). Differences in serial recall between Hebb and ller sequences that emerge over trials provide an assessment of Hebb
learning (Hebb, 1961).
The ‘developmental approachto intellectual disability suggests that cognitive abilities in those with non-specic ID should follow
the same pattern of development as TD peers, albeit at a slower rate and perhaps reaching a lower asymptote (Burack et al., 2021).
Consequently, one would expect similar HRL in groups with ID and TD matched for mental age. Limited support for the developmental
approach comes from the nding that implicit learning tends not to differ between mental age-matched groups with ID and TD (Weiss,
Weisz, & Bromeld, 1986), however, there is no directly-relevant evidence concerning HRL.
Mosse and Jarrold (2010) noted that preserved HRL in those with ID could have important educational implications, suggesting
that knowledge about long-term implicit learning mechanisms for serial order could be applied in the classroom to improve educa-
tional outcomes. In their study of young people with Down syndrome, Mosse and Jarrold (2010) reported no group differences when
they compared HRL in young people with Down syndrome and children with TD matched for verbal (non-verbal in Experiment 1)
ability. This was despite well-documented relative difculties with verbal short-term memory of individuals with Down syndrome (e.
g., Jarrold, Purser, & Brock, 2006). These ndings supported preserved HRL in young people with Down syndrome (i.e., mental age
appropriate HRL, in accordance with the developmental approach), despite their lower verbal short-term memory performance.
To further extend understanding of HRL processes in adolescents with non-specic ID, we assessed HRL for both verbal and vi-
suospatial materials, and compared them with a carefully mental-age matched comparison group of TD children. There are indications
that young TD children show HRL in both verbal and non-verbal domains (e.g., Mosse & Jarrold, 2008; although see West, Vadillo,
Shanks, & Hulme, 2018), as adults do (Couture & Tremblay, 2006; Page, Cumming, Norris, Hitch, & McNeil, 2006), supporting ar-
guments for a common ‘domain-generallearning mechanism (Couture & Tremblay, 2006; Mosse & Jarrold, 2008). Hitch, Flude, and
Burgess (2009) suggested this mechanism could reect the episodic buffer component of working memory, with item information
stored, for example, in the phonological loop or visuospatial sketchpad (Baddeley, 2000). This debate focuses on adults (e.g., Johnson,
Dygacz, & Miles, 2017; Sukegawa, Ueda, & Saito, 2019), so there remains uncertainty around domain-general mechanisms in children
and adolescents. Furthermore, differences in HRL between verbal and visuospatial domains could emerge in individuals with ID, as
they appear to have less well-preserved verbal short-term memory as opposed to visuospatial short-term memory (Henry et al., 2018;
Lifshitz, Kilberg, & Vakil, 2016), and weaker verbal as opposed to visuospatial explicit long-term memory (Lifshitz-Vahav & Vakil,
2014). Consequently, comparisons between these domains can contribute to a better understanding of modality similarities or dif-
ferences related to HRL.
Three research questions were addressed here. First, do adolescents with ID and children with TD matched for mental age both
show HRL? We predicted that participants with ID would show HRL effects. This prediction was tentative, as no directly relevant
previous evidence was available. We also predicted that children with TD (matched for mental age) would show HRL effects. This
prediction was derived from the literature showing such effects are present in TD children from the age of four years (Archibald &
Joanisse, 2013; Attout et al., 2020; Bogaerts et al., 2016; Smalle et al., 2016, 2018; West et al., 2018; Yanaoka, Nakayama, Jarrold, &
Saito, 2019).
Second, are the HRL effects of similar magnitude in the two groups? We predicted that the Hebb effect would be comparable in both
groups, consistent with a preserved learning mechanism in those with ID and supporting the developmental approach. This prediction
was tentative given the lack of previous research.
Third, are the HRL effects of similar magnitude for both verbal and visuospatial materials? Given previous evidence in the literature
for a domain-general process of HRL (Mosse & Jarrold, 2008), we predicted that this form of learning would be similar for visuospatial
L.A. Henry et al.
Research in Developmental Disabilities 125 (2022) 104219
3
materials as well as verbal materials (based on Mosse & Jarrold, 2010).
2. Method
2.1. Participants
The study involved 47 (26 females) adolescents with ID who had a mean mental age of 84.81 months (7:1 years) and a comparison
group of 47 (25 females) children with TD, individually matched for mental age, who had a mean mental age of 85.04 months (7:1
years). There was no signicant difference between the groups on mean mental age, t(92) = − 0.09, p =.93 (see Table 1); nor did the
variances differ using Levenes test, F(1,92) =0.008, p =.95. Teachers conrmed participants had spoken English for at least two years
at the time of testing to ensure they could understand the tasks and participate fully.
Adolescents with non-specic ID (where the biological cause for the ID has not been identied) were recruited. We incorporated the
DSM-5 (American Psychiatric Association, 2013) approach to the denition of ID into participant selection to understand better the
strengths and weaknesses in those with both cognitive and adaptive difculties. DSM-5 emphasizes adaptive functioning as well as
intellectual functioning (Patel et al., 2020) along with less emphasis on exact cut-off scores (Burack et al., 2021). The study was
preregistered on the Open Science Framework (OSF) https://osf.io/gkpwh/ (dated 17.01.19), and a minor change to the inclusion
criteria for the ID group was registered on 08.08.19 under Transparent Changes on the OSF (citation: osf.io/a5724). The change
facilitated recruitment and thereby increased the sample size by relaxing the Vineland adaptive behaviour scores in the ID group from
a standardised score cut-off of 79 to 85. The current study reports data relevant to the rst set of pre-registered research questions; we
also report reliability data relevant to the third pre-registered research question here and in the supplementary materials (data relevant
to the second set of pre-registered research questions will be reported in a separate paper).
The 11- to 15-year-olds with ID were recruited from 27 mainstream secondary schools in England (Greater London, Hertfordshire,
Yorkshire, Cambridgeshire and Nottinghamshire). Teachers identied eligible young people if they had ID and no other diagnoses such
as autism or Down syndrome. Participants were excluded if, after testing, they did not have: 1) a score of between 40 and 79 on the
Stanford-Binet abbreviated intelligence scales (SB-5: Roid, 2003); and 2) a standardized score of between 40 and 85 on the overall
Adaptive Behaviour Composite (ABC) of the Vineland Adaptive Behaviour Scales (Vineland-3: Sparrow, Cicchetti, & Saulner, 2016), or
a standardised score of between 40 and 85 on at least one of the core domains (Communication, Daily Living Skills, Socialisation). Note
that we included participants with SB-5 IQ scores in the borderline (7079), mild (5569) and moderate (4054) ID range provided
they also showed evidence of adaptive difculties. Of the 47 participants, 14 had borderline, 23 had mild and 10 had moderate ID in
terms of their SB-5 scores.
In the group with TD, 4- to 10-year-olds were recruited from seven mainstream primary schools in England (Greater London and
Yorkshire). Participating schools were comparable to the ID group on socio-economic status, as a higher proportion of students than
the national average were from ethnic minority groups, spoke English as an Additional Language and were eligible for pupil premium
funding. Teachers identied eligible children who did not have any special education needs, or diagnosed developmental conditions
such as autism. Children were included if their mental age, based on a composite verbal and non-verbal score derived from the SB-5
matched that of one participant from the ID group; and if they had a standardised score on the SB-5 above 79.
All young people with ID who met inclusion criteria and had full data available from the rst HRL session were included, provided
there was an individual match on mental age within 4 months in the group with TD (note: only one mental age match differed by 4
months, and 32 were exact matches). Some participants (2 with ID; 6 with TD) were missing HRL data from the second session (and one
further TD child was missing visuospatial data from session 2) because data collection was stopped due to Covid-19; there was no
reason to suspect systematic bias so these participants were retained. Some participants were excluded (9 with ID; 11 with TD) who
Table 1
Mean scores, (SD) and [ranges of scores] on key study variables for adolescents with ID and children with TD matched for mental age.
Variables Young people with ID (n =47) Children with TD (n =47) Group differences
Chronological age 13 yrs 4 m (15 m)
[137191 m]
7 yrs 2 m (17 m)
[57123 m]
t(92) =22.41, p <.001
Mental age 7 yrs 1 m (13 m)
[55111 m]
7 yrs 1 m (13 m)
[59111 m]
t(92) = − 0.09, p =.93
SB5 IQ 63.36 (10.39)
[4779]
98.66 (10.76)
[85121]
t(92) = − 16.18, p <.001
Word List Recall: span 3.44 (0.53)
[2.004.50]
3.30 (0.58)
[2.254.25]
t(92) =1.19, p =.24
Visual Sequential Memory: span 3.49 (1.06)
[26]
3.38 (1.01)
[26]
t(92) =0.50, p =.62
Vineland: Communication 73.81 (8.20)
[5486]
Vineland: Daily Living Skills 83.13 (11.20)
[48105]
Vineland: Socialisation 83.30 (10.52)
[60109]
Vineland: ABC 78 (7.88)
[5994]
L.A. Henry et al.
Research in Developmental Disabilities 125 (2022) 104219
4
met the inclusion criteria, because they could not be matched.
Ethical approval was granted by the relevant university committee. Written informed consent from parents/guardians and written
and verbal assent from participants were gained before testing.
2.2. Design
A mixed factorial quasi-experimental study was conducted with three within-subjects factors (Hebb repetition task list type (Hebb,
ller), trial position (eight trials for each list type), and type of material (verbal, visuospatial)), and one between-subjects factor (group
(ID versus TD)). No blinding was employed.
2.3. Materials
Standardized assessments of cognitive ability and adaptive functioning were administered. Measures of verbal and of visuospatial
short-term memory were used to assign participants to an appropriate difculty level of HRL (see Table 1).
2.3.1. Cognitive Assessment
The abbreviated version of the SB-5 (Roid, 2003) was used, consisting of two subtests: verbal knowledge and non-verbal reasoning
skills. Manual-derived mental ages in months were used for matching. The SB-5 is suitable for individuals with ID and has high
reliability (.91.98) (Roid, 2003). Vocabulary, grammar and single-word reading were also assessed, but not reported here.
2.3.2. Adaptive functioning
Parents of participants in the ID group completed the Vineland-3 Domain-Level Parent/Caregiver Form (Sparrow, Cicchetti, &
Saulnier, 2016) via a 20-minute telephone interview (N =43); when this was not possible parents completed the questionnaire by
themselves (N =4). Standardised measures of adaptive functioning in three domains (communication, daily living skills, socialisation),
as well as an overall adaptive behaviour composite (ABC), were derived. The Vineland-3 is a reliable assessment for individuals with ID
(test re-test reliabilities from .73 to .92).
2.3.3. Short-term memory
Word List Recall from the Working Memory Test Battery for Children (WMTB-C: Pickering & Gathercole, 2001) assessed verbal
short-term memory. Participants listened to word lists spoken by the experimenter before repeating the list in the same order. Word
lists increased incrementally, beginning with lists of one word, with six trials for each list length; if four out of six lists were recalled
correctly, the next list length was administered. Testing was discontinued if three out of six or fewer trials were correct in a block. To
obtain ‘sensitivespan scores, the longest list length for which 4 out of 6 trials were correct was identied, and extra credits of 0.25 for
each list at the next higher list length correctly recalled were added to span scores (e.g., a full pass at list length 3 plus two correct trials
at list length 4 gives a sensitive span score of 3.5).
Visual Sequential Memory from the Test of Memory and Learning (TOMAL-2: Reynolds & Voress, 2007) assessed visuospatial
short-term memory. Participants were presented with left to right horizontally displayed sequences of nonsense visual stimuli for ve
seconds. These were then removed and immediately re-presented in a different order. Participants were instructed to point to the
drawings in the order you saw them on the page before. Sequence lengths increased incrementally with two trials per length. Testing
was discontinued if the participant failed to recall any items in the correct order for two consecutive trials. Memory span scores were
derived by taking the childs span score as the longest list length at which perfect recall in serial order was achieved.
2.3.4. HRL tasks
Given concerns about weak HRL effects in children (Archibald & Joanisse, 2013; Bogaerts et al., 2016; West et al., 2018; Yanaoka
et al., 2019) and the reliability of HRL (Bogaerts et al., 2018; West et al., 2018), we aimed to maximize the sensitivity and reliability of
our measures of HRL. No participants with chronological and mental ages younger than four years were included (see Yanaoka et al.,
2019). The lengths of Hebb and ller tasks were chosen according to the participants short-term memory ability to prevent oor and
ceiling effects (Archibald & Joanisse, 2013; Hsu & Bishop, 2014; Siegelman, Bogaerts, & Frost, 2017; Smalle et al., 2016; West et al.,
2018; Yanaoka et al., 2019). We used sensitive scoring of both item presence and serial position (e.g., Smalle et al., 2016).
Non-overlapping item sets were used for Hebb and ller trials to minimise inter-list confusability (Johnson et al., 2017; Mosse &
Jarrold, 2010; Smalle et al., 2016; Yanaoka et al., 2019). Finally, a similar serial order reconstruction recall method for all tasks was
used that produces reliable HRL effects (Johnson et al., 2017).
All participants received two versions of HRL tasks on an iPad: a visuospatial task using non-nameable, unfamiliar ‘nonsense
drawingstimuli; and a verbal task using easily nameable pictures of common objects with one-syllable names (similar to Archibald &
Joanisse, 2013 and Hsu & Bishop, 2014). The verbal task involved simultaneously hearing each items name and seeing its picture,
with a presentation rate of one item every 1.5 s and a 0.5 s interval between items. The dual presentation method was used because, at
recall, participants saw pictures of all items in the relevant item pool and were required to respond by touching the relevant pictures in
serial order, so dual presentation facilitated cross-modal mapping. The visuospatial nonsense picture stimuli were shown without any
sound.
There were 8 Hebb trials (the same to-be-remembered sequence was repeated 8 times), alternating with 8 ller trials (randomly
generated novel sequences on each trial), making a total of 16 trials. The tasks started with a ller trial and alternated thereafter with
L.A. Henry et al.
Research in Developmental Disabilities 125 (2022) 104219
5
Hebb trials. Items were drawn from different item sets for Hebb and ller trials (i.e., stimuli for Hebb and ller trials were non-
overlapping). There were two item-sets each of: 8 nonsense pictures (see Fig. 1a); and 10 one-syllable nouns illustrated as black
and white line drawings (List 1 =dog, car, kite, chair, bell, ring, sun, sh, sock, house; List 2 =book, cat, bus, cup, bed, pear, comb,
ball, duck, shirt) (see Fig. 1b). Choice of item sets was counterbalanced across participants and sessions.
In each HRL task, participants were shown, one at a time, a sequence of items. They then were shown an array of all items from the
relevant item set, 10 items for verbal HRL task and 8 items for the visuospatial HRL task. The array was placed in the lower half of the
screen, with the stimuli in two rows, and these were in a different random order on each trial. At the top of the response screen
horizontal lines also appeared, the number of lines corresponding to the length of the list being recalled (this provided a cue about how
many responses were needed, see Figs. 1a and 1b). To recall the target sequence, participants sequentially touched the images on the
array screen. After each touch, a black circle appeared on the relevant line at the top of the screen to signify the selection. An item could
be selected more than once, although target sequences never contained repetitions.
Both HRL tasks were introduced with practice trials using entirely different item sets. There were four trials in each practice block,
two with short list lengths (two items for non-verbal tasks and three items for verbal tasks) and two with the same list length as the
actual task (which were related to the assigned difculty level).
Participants received a virtual coin for each trial completed in every task (the coin ‘landedinside a money bag with a ‘ping) and a
virtual gold trophy was given at the end of each task .
2.3.5. Hebb task allocation
There were short and long versions of each Hebb task (long versions had list lengths that were one item longer than short versions).
Participants with Word List Recall memory spans of 3.5 or greater received the long verbal Hebb task (list length 6 items; N
ID
=23, N
TD
=21). Participants with Word List Recall memory spans of 3.25 or less received the short verbal Hebb task (list length 5 items, N
ID
=
24, N
TD
=26). Participants with Visual Sequential Memory spans of 3 or greater received the long visuospatial Hebb task (list length 4
items; N
ID
=38, N
TD
=38). Participants with Visual Sequential Memory spans of 2 or less received the short visuospatial Hebb task (list
length 3 items, N
ID
=9, N
TD
=9). This task allocation aimed to ensure there was room for performance improvement, with most
children receiving supraspan list lengths (e.g., Archibald & Joanisse, 2013; Hsu & Bishop, 2014). One potential disadvantage of this
method was that for participants with lower spans, serial reconstruction at recall could have been relatively more demanding because
there were more non-presented items in the response array. However, the benets of standardising the item set sizes and titrating
difculty levels for all participants were regarded as more important.
2.3.6. Nonsense drawing familiarisation
Before administering the visuospatial task, participants were pre-familiarised with the nonsense drawings through playing ‘Snap.
A pack of 64 cards was dealt to the participant and experimenter, consisting of 16 nonsense pictures identical to those in the visuo-
spatial task, each repeated four times. On each card, only one side showed a nonsense picture. The participant and experimenter took
turns to turn over a card from their face-down pile and if the card matched the previous turned over card, the rst player to say ‘snap
won all turned over cards. When all the cards in the pack had been turned over, the player with the largest pile of cards won the game.
This game was designed to give the participants a standardised experience to develop representations of the unfamiliar pictures.
2.3.7. Counterbalancing
Two HRL sessions were administered, up to two weeks apart, to maximise the amount of data collected (without tiring participants)
and assess test-retest and split-half reliability. The sequences that participants received varied as a result of list length (short or long
versions). Each session involved a verbal and visuospatial HRL task, counterbalanced across the two sessions. The items in each set of
sequences were chosen via semi-randomized selection, but otherwise did not differ in format. Two parallel versions of each task were
Fig. 1. a. Response array from the visuospatial Hebb repetition task. Here the participant has not started responding. Fig. 1b. Response array from
the verbal Hebb repetition task. Here, the participant has made three responses as indicated by the black circles.
L.A. Henry et al.
Research in Developmental Disabilities 125 (2022) 104219
6
counterbalanced across participants: for session 2 the ller stimuli set and the Hebb stimuli set were reversed (i.e., the item set for Hebb
sequences in session 1 then became the item set for ller sequences in session 2), and this was counterbalanced across participants. The
specic version that the participant received rst was randomised.
2.3.8. HRL Scoring
Given the known issues with obtaining reliable measures of inter-individual differences in Hebb learning (Bogaerts et al., 2018),
credit for correct item and position information was given, to ensure that partial knowledge of the sequences was taken into account in
the scores. As outlined by Kalm and Norris (2016), HRL involves not just learning item-position associations; there can also be partial
knowledge of subsequences or chunks within the sequence. Item scoring captures this partial learning, even when exact serial order
retention breaks down. Also, our response arrays for serial reconstruction contained more items than just those presented, so some
scoring of item recall was necessary. For each item in a sequence, the participant was scored to take account of correctly recalling the
item and its serial position as follows: 0 =‘no recall; 1 =‘item recall (not in position); and 2 =‘item recall in position. To further
ensure that we did not underestimate the true effects of HRL, we calculated Levenshtein edit-distance metrics, dened as the min-
imum number of edits needed to transform one string into another(Kalm and Norris, 2016, p.112; edit distance was divided by list
length and subtracted from 1 to derive a standardised metric). This gives credit for any similarities between the target sequence and the
recalled sequence, making minimal assumptions about what is being learned. The Levenshtein scoring method and the relevant an-
alyses were exploratory as they were not pre-registered (see the full analyses in supplementary materials, Section 4).
2.4. Procedure
Participants in both groups were assessed one-to-one at their schools during lesson time. Session lengths and the number of sessions
were adapted to the participantsneeds and school schedules. Most participants with ID completed the assessments in 90 min split
across two sessions. During the rst session the SB-5, short-term memory measures, verbal and visuospatial HRL tasks (and a reading
measure if time allowed) were administered. The second session consisted of the second verbal and visuospatial HRL tasks, plus two
language measures (and the reading measure as needed). The majority of children with TD completed the activities in three sessions of
approximately 30 min each (session 1 included SB-5, short-term memory measures, reading task; session 2 included verbal and vi-
suospatial HRL tasks and a language measure; session 3 included the second presentation of the verbal and visuospatial HRL tasks and
another language measure). Certicates were provided to participants after the nal session as a reward and primary school children
also received stickers.
2.5. Analysis method
Recall performance on trials with repeated sequences (Hebb) was compared with recall performance on changing (ller) sequences.
Performance was compared using all trials, for verbal and visuospatial materials in both sessions, in the ID and TD groups. Data were
analysed with generalized linear mixed models (GLMM) to maximise sensitivity. Several studies have taken performance improve-
ments from the rst to the second half of Hebb trials relative to the performance change in ller lists as their measure of Hebb learning
(e.g., Archibald & Joanisse, 2013; Mosse & Jarrold, 2008). The drawback of this ‘halvesapproach, as with any dichotomisation of
continuous variables, is that information about changes within the rst and second halves of trials is lost, resulting in a loss of power to
detect effects (e.g., MacCallum, Zhang, Preacher, & Rucker, 2002). In other studies, separate regression analyses of performance on
Hebb trials and ller trials were performed for each participant. The resulting regression slopes or gradients were entered into ANOVAs
or ANCOVAs (e.g., Bogaerts et al., 2015; Hsu & Bishop, 2014).
However, an alternative approach to deal with the multilevel structure of trials being nested within participants is to analyse the
data with generalized linear mixed models (GLMM) instead of performing separate consecutive analyses. Similar to the regression
approach, changes in recall across trial position are modelled without any information loss about trial position. A key benet of GLMM
is that data from Hebb trials, ller trials, and from all participants are analysed in a joint model. A positive interaction effect between
list type (Hebb vs. ller trials) and trial position (1 through 8) represents the degree of Hebb learning, as it captures recall improvement
over Hebb trials in comparison to ller trials. The mixed GLMM models can include both this xed effect of list type x trial position,
representing the average effect of HRL, and the random effect of list type x trial position, allowing for inter-individual differences in the
degree of HRL. In mixed effect models the residuals of the random effects reect how an individual differs from the group mean (xed
effects). Including a random intercept additionally captures individual differences in recall performance on the rst Hebb and ller
trials. Bogaerts and colleagues (Bogaerts et al., 2016, 2018) introduced mixed logit models to analysing the development of Hebb
learning with recall of items in the correct position as dependent, binary variable (for a similar approach see Yanaoka et al., 2019).
The information from scoring HRL on each of the three to six items constituting a trial was ordinal with three levels (02). We
modelled the scoring of HRL using a cumulative logit model with proportional odds assumed. This means that only one effect per
predictor (material, list type, trial position +list x position interaction) is estimated and the effect on the transition from no recall to
recall is assumed to be the same or proportional in terms of odds as on the transition from recall not in position to recall in position. The
resulting models were complex because various xed effects for group-level experimental effects and random effects for individual
differences had to be estimated. Therefore, only the interaction effect of list and position was included to capture Hebb learning.
Consequently, further two-way interactions or even three-way interactions to test for differences in the degree of Hebb learning be-
tween participant groups or materials were not included in a single model. Increasing the model complexity further would increase the
risk of problems in model estimation. Instead, four separate models were set up to address the specic research questions (compare
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preregistration: https://osf.io/gkpwh/): models for participants with ID and TD, respectively, that pooled data across material and
assumed the same degree of Hebb learning for verbal and visuospatial material; and models for verbal vs. visuospatial material,
respectively, to test differences due to material that included data from both groups, but allowed for individual differences in Hebb
learning by including the relevant random effects. All GLMMs for ordinal dependant variables were performed with MLwiN 3.02
(Charlton, Rasbash, Browne, Healy, & Cameron, 2018) using MCMC estimation, with 100000 iterations and thinning to 5000 estimates
from R with the R2MLwiN package (Zhang, Parker, Charlton, Leckie, & Browne, 2016). On publication, full data and R scripts will be
made available on the Open Science Framework.
2.6. Reliability of the HRL tasks
The test-retest correlations of the Hebb-learning residuals were: r
tt
=0.47 (p<.001) for the model averaging across material (RQ1,
RQ2); r
tt
=0.63 (p<.001) for the verbal material; and r
tt
=0.69 (p<.001) for the visuospatial material (both relating to RQ3),
resulting according to the Spearman-Brown formula in split-half-reliabilities of .64, .77, and .82, respectively.
1
The four correlations
between HRL assessed with verbal and visuospatial materials (in each group) ranged from r=0.45, 95% CI [.26, .60] to r=0.59, 95%
CI [.44, .71]. (See supplementary materials, Section 1, for further details).
3. Results
Concerning the rst research question (do adolescents with ID and children with TD matched for mental age show HRL effects?),
the plots in Fig. 2 suggest that HRL was shown in both groups. On the y-axis, the proportion correct from the combined scores for items
being recalled, but not in position (0.5), and items being recalled in correct position (1.0), are displayed (for further descriptive results
and a discussion of whether there were ceiling and oor effects present, see supplementary materials, Section 2). The gure suggests
that HRL occurred in both groups, as a higher proportion of correct answers were given for Hebb sequences. There also appeared to be a
separation between Hebb and ller sequences as the trials progressed in the verbal task. In line with previous research, involving TD
children, Hebb trials showed maintenance of performance whilst ller trials tended to show declines (e.g., Archibald & Joanisse, 2013;
Mosse & Jarrold, 2008).
To test these observations formally, GLMMs were run. Two separate models were used, one for adolescents with ID and one for
children with TD. Both sets of results include random intercepts parameters for participants to capture inter-individual differences in
how well participants remembered sequences, and random slopes for material and trial position. This allowed investigation of indi-
vidual differences between verbal and visuospatial materials and for differences in how memory performance develops across trials.
Crucially for the rst research question, the random slope for the interaction of list type (Hebb vs. ller) and trial position (1 through 8)
was included to allow for individual differences in how much participants beneted from the repeated presentation of Hebb lists. The
xed effects, and therefore the group level effects, of both models are displayed in Table 2. In ordinal models, instead of one intercept,
multiple intercepts are estimated for each transition between categories. The two intercepts were comparable across groups indicating
that the rst trials of the experimental sessions (position value =0; i.e. the aggregate for the 8 rst trials of Hebb/ ller, verbal/vi-
suospatial, and 1st/2nd sessions) were of comparable difculty for both groups. This implies that both groups could start Hebb
learning with, on average, comparable performance. However, the intercepts do not inform us about whether within-group differ-
ences, for example due to material, existed or not. In fact, the general effect of material was signicant in both samples (ID: β=0.41,
95%CI [0.33, 0.48], p<.001; TD: β=0.42, 95%CI [0.32, 0.51], p<.001): participants were more likely to recall verbal sequences
than visuospatial sequences, even though task difculty was adjusted to the differing memory spans for these materials.
Of key interest for the rst research question was the interaction between list type and trial position to identify an effect of Hebb
learning. This interaction effect was signicant in both groups (ID: β=0.05, p<.001; TD: β=0.09, p<.001) indicating that par-
ticipants in both groups signicantly benetted from the repeated presentation of Hebb sequences compared to ller sequences. The
non-signicant main effect of trial position (ID: β=0.00, p=.71; TD: β= − 0.01, p=.29) suggests that recall performance did not
improve with trial position overall. To examine whether the list x position interaction was driven by performance improvements on
Hebb trials or by decreasing performance on ller trials, exploratory analyses were run on models testing the position effect either only
on Hebb or only ller trials. Recall signicantly improved on Hebb trials for both groups and materials (ID verbal: β=0.04, 95%CI
[0.01, 0.08], p=.02; TD verbal: β=0.09, 95%CI [0.03, 0.15], p=.002; ID visuospatial: β=0.05, 95%CI [0.01, 0.09], p=.02; TD
visuospatial: β=0.06, 95%CI [0.03, 0.10], p<.001) and signicantly deteriorated on ller trials with verbal material (ID:
β= − 0.10, 95%CI [0.13, 0.07], p<.001; TD: β= − 0.16, 95%CI [0.19, 0.13], p<.001) and did not change with visuospatial
material, (ID: β= − 0.00, 95%CI [0.03, 0.03], p<.92; TD: β= − 0.03, 95%CI [0.06, 0.00], p=.06).
To answer the second research question (are HRL effects comparable for both groups?), the 90% credible intervals (CI) for the
interaction between list type and trial position in each group were computed to determine whether they overlapped. As the interaction
effect for Hebb learning was 0.05 with a 90% CI of 0.0330.072 in the ID group and 0.09 with a 90% CI of 0.0710.109 in the TD group,
the CIs were overlapping, however more precisely, the CIs were touching and only barely overlapping. Therefore, although there was
1
Reliability represents how consistently inter-individual differences can be measured. In mixed effect models the residuals of the random effects
reect how an individual differs from the group mean (xed effects). To derive reliability estimates for Hebb learning, we therefore estimated
separate GLMMs for session 1 and session 2, extracted the residuals of the random effects for the list type x position interaction (indicating Hebb
learning) from each model and computed retest-reliabilities (for further details see supplementary materials, Section 1).
L.A. Henry et al.
Research in Developmental Disabilities 125 (2022) 104219
8
no robust evidence that HRL differed between groups, the degree of overlap was only just discernable, so some uncertainty remains
regarding this result.
To answer the third research question (do children in both groups show a similar magnitude of HRL for both verbal and visuospatial
materials?), two further GLMMs were conducted. The data were split by material type, but pooled across participant groups. Apart
from the random intercepts for participants, the random slope for the list type x trial position interaction was included to allow for
individual differences in Hebb learning. Results are displayed in Table 3. The crucial xed effects are the interaction of list type (Hebb
vs. ller) and trial position. The interaction effects were signicant and positive for verbal stimuli (β=0.100, 90%CI [0.081, 0.118],
p<.001) as well as visuospatial stimuli (β=0.034, 90%CI [0.019, 0.050], p<.001) indicating that for both types of materials Hebb
learning was found, hence, childrens recall benetted from the repeated presentation of Hebb lists. As the 90% CIs were not over-
lapping, the HRL effect was more pronounced for verbal than visuospatial materials.
We also ran exploratory analyses using standardised Levenshtein distance scores (which were highly correlated with our combined
item +position scores, r=0.94, p<.001). Of particular interest were xed effects for the list type x trial position interaction rep-
resenting the average Hebb learning effect. Irrespective of the scoring method, the parameter estimates were the same for the rst two
decimal numbers in the analyses run by group: ID: β=0.05, p<.001; TD: β=0.09, p<.001. The results were also similar for the
analyses run by material: verbal β=0.09/0.10, p<.001/<0.001; visuospatial: β=0.03/0.03, p=.003/<0.001 with the models
based on standardised Levenshtein distance or on combined item +position scores, respectively. (See supplementary materials,
Fig. 2. Recall performance across trials for ller lists and repeated Hebb lists. Data are split by experimental groups (ID vs. TD) and material (verbal
vs. visuospatial) and pooled across both experimental sessions (some data are missing for session two; n =2 ID and n =67 TD).
Table 2
GLMMs on recall performance across trial positions for Hebb vs. ller lists to address research question 1 for the ID and TD groups.
ID TD
Fixed Part β 95% CI p β 95% CI p
Intercept 1 (no vs. item recall) 1.08 [0.89, 1.26] <0.001 1.15 [0.96, 1.33] <0.001
Intercept 2 (item vs. position recall) -0.67 [0.93, 0.42] <0.001 -0.67 [0.92, 0.42] <0.001
Material (Verbal = +1 vs. Visuospatial = − 1) 0.41 [0.33, 0.48] <0.001 0.42 [0.32, 0.51] <0.001
List (Hebb = +1 vs. Filler = − 1) 0.16 [0.10, 0.22] <0.001 0.03 [0.03, 0.09] .30
Trial Position (1st =0, 2nd =1 ) -0.00 [0.02, 0.02] .71 -0.01 [0.04, 0.01] .29
List x Position (Hebb effect) 0.05 [0.03, 0.08] <0.001 0.09 [0.07, 0.11] <0.001
Random Part
Random effects for random participant intercepts, for material, position, and for the list x position interaction (individual differences in Hebb
learning), plus all covariances between these effects were included in the model and are displayed in the supplementary materials, Section 3
(Table S4).
Note. Sample sizes for the ID group: N
Participants
=47, N
Trials
=2944, N
Items
=13680; for the TD group: N
Participants
=47, N
Trials
=2800, N
Items
=13024
L.A. Henry et al.
Research in Developmental Disabilities 125 (2022) 104219
9
Section 4, for further details.).
4. Discussion
This rst study of HRL in adolescents with non-specic ID showed, as tentatively predicted, a signicant HRL effect in this group.
Children with TD (individually matched for mental age) also showed signicant HRL, supporting previous literature (Archibald &
Joanisse, 2013; Attout et al., 2020; Bogaerts et al., 2016; Smalle et al., 2016, 2018; West et al., 2018; Yanaoka et al., 2019). The
magnitude of the Hebb effect was similar in the two groups, although there was a degree of uncertainty here as the credible intervals
for the groups were only just touching. As predicted, there were signicant HRL effects for both visuospatial and verbal materials,
although contrary to predictions from previous research (e.g., Mosse & Jarrold, 2010), the magnitude of HRL across these domains for
our measure of Hebb learning was not equal, with larger effects for the verbal task. Although not part of our pre-registration, additional
exploratory analyses using standardised Levenshtein distances as an alternative recall measure conrmed these ndings and revealed a
strong relationship between this measure and our original scoring method.
The ndings broadly support the developmental approach (Burack et al., 2021) that adolescents with non-specic ID show HRL
commensurate with their mental age level, implying that implicit long-term serial-order learning processes could be a relative strength
in this group. Mosse and Jarrold (2010) similarly found that performance on HRL in their participants with Down syndrome was
comparable to a group with TD matched for mental age, even though their group with Down syndrome showed weaker verbal
short-term memory. However, the current ndings were somewhat less supportive of the developmental approach than those of Moss
and Jarrold (2010). This is because the credible intervals for the size of the Hebb repetition effect between the groups were touching
rather than fully overlapping, suggesting that there could be a tendency for the magnitude of HRL to be lower in the ID group. In
addition, verbal short-term memory in the present study did not differ between the groups with ID and TD (despite such ndings often
being reported: Henry et al., 2018; Lifshitz et al., 2016). This could be because the individual mental-age matching was very close, or
because our inclusion criteria for ID, which included both cognitive and adaptive measures, differed from previous research.
Further exploratory analyses on the Hebb sequences showed increases in performance over trials for both types of material (in both
groups). The ller sequences showed declines in performance (for both groups) in the verbal task, although there were no performance
changes over trials for the visuospatial task. For the verbal ller sequences, the deterioration in performance might reect a build-up of
proactive interference or fatigue (Archibald & Joanisse, 2013; Bogaerts et al., 2016; Mosse & Jarrold, 2008). Interference is perhaps
more likely; as trials progress, more confusion could occur on ller sequences because there are increasingly more previous sequences
and individual items from the ller item pool that are ‘partiallyactivated. By contrast, for items in the Hebb sequence, serial order and
item information becomes repeatedly strengthened over trials, with less interference from items that are not in the Hebb sequence,
leading to long-term learning (Hitch et al., 2009). In the visuospatial task, there was no clear evidence for such interference on ller
trials. This could be because interference was not present or did not show in the data due to oor effects. Alternatively, it could be
because the visuospatial items were not well-established in long-term memory, so were less likely to be partially activated and cause
confusion as ller trials progressed. This latter point is interesting, as HRL could feasibly be conceptualized as just the Hebb learning
element, rather than the interaction between learning on Hebb trials versus interference on ller trials. The suggestion of interference
for verbal and not visuospatial ller trials could indicate that the precise conceptualization and operationalization of HRL for different
types of materials may be more important than suspected. It is also important to note that because the current study employed separate
Hebb and ller pools as item sets, interference effects could vary in scale and magnitude if all items were drawn from the same set, an
issue that could be explored in future research.
The current ndings supported the domain generality of HRL reported in both children and young people with Down syndrome (e.
g., Bogaerts et al., 2016; Mosse & Jarrold, 2008, 2010), as HRL effects were signicant for both visuospatial and verbal materials.
Further, the HRL residuals taken from the verbal task correlated with the HRL residuals taken from the visuospatial task: this shared
variance points to at least some domain generality. However, the magnitude of the HRL effect as indexed by the list type x trial position
interaction was greater for verbal than visuospatial materials, whereas other studies have reported equal effects (Mosse & Jarrold,
Table 3
GLMMs conducted on recall performance across trial positions for Hebb vs. ller lists for verbal and visuospatial stimuli to address research question
3.
Verbal Visuospatial
Fixed Part β 95% CI p β 95% CI p
Intercept 1 (no vs. item recall) 1.74 [1.58, 1.9] <0.001 0.49 [0.33, 0.65] <0.001
Intercept 2 (item vs. position recall) -0.27 [0.47, 0.08] .007 -1.04 [1.24, 0.85] <0.001
List (Hebb = +1 vs. Filler = − 1) 0.10 [0.05, 0.16] <0.001 0.09 [0.02, 0.16] .007
Trial Position (1st =0, 2nd =1 ) -0.03 [0.05, 0.01] .01 0.02 [0.01, 0.04] .008
List x Position (Hebb effect) 0.10 [0.08, 0.12] <0.001 0.03 [0.02, 0.05] <0.001
Random Part
Random effects for random participant intercepts, for position (only the model for verbal material), and for the list x position interaction (individual
differences in Hebb learning), plus all covariances between these effects were included in the model and are displayed in the supplementary materials,
Section 3 (Table S5).
Note. Sample sizes for verbal condition: N
Participants
=94, N
Trials
=2880, N
Items
=15792; for visuospatial condition: N
Participants
=94, N
Trials
=2864,
N
Items
=10912
L.A. Henry et al.
Research in Developmental Disabilities 125 (2022) 104219
10
2010), larger visuospatial effects (Bogaerts et al., 2016) or no visuospatial effects (West et al., 2018). It is not clear why ndings differ,
but task differences could be a possibility (e.g., static versus dynamic visuospatial tasks), as well as the problems of exactly matching
the difculty of tasks in different domains. There was some evidence that children with a higher starting performance level showed a
tendency for higher HRL effects, so we cannot rule out the possibility that equating task difculty would remove the differences in HRL
between verbal and visuospatial materials. Thus, employing even more stringent difculty level titration and including both static and
dynamic visuospatial tasks would help to evaluate, in future research, whether HRL is equal for verbal and visuospatial materials.
Larger scale studies would also enable the statistical models to take into account both group and material type in the same analysis, as
more data points are required to ensure such complex models are stable. Overall, therefore, there was evidence to support a domain
general mechanism for HRL, but further research is needed to explore this area, perhaps attempting to identify whether or not there are
different serial order learning mechanisms across domains that share common features (e.g., Logie, Saito, Morita, Varma, & Norris,
2016) or whether commonalities between verbal, visual and spatial short-term memory imply domain-general serial order learning
mechanisms (Hurlstone, Hitch, & Baddeley, 2014).
It has been argued that HRL draws on the same memory processes responsible for representing and learning serial-order infor-
mation in the service of language acquisition(Bogaerts et al., 2015, p.107). Thus, serial-order HRL could boost the long-term
acquisition of phonological sequences, which, in turn, are important for acquiring new vocabulary (Archibald & Joanisse, 2013;
Mosse & Jarrold, 2008; Page & Norris, 2009; Smalle et al., 2018) and reading (Attout et al., 2020; Bogaerts et al., 2016); although
relationships with language measures are not always found (Hsu & Bishop, 2014). Mosse and Jarrold (2010) discussed the educational
implications of HRL, suggesting that indirect associations and learning opportunities afforded by Hebb processes may be more suc-
cessful than direct and explicit instructional approaches using single teaching sessions. Further research could explore educational
applications for HRL within real world learning settings, perhaps involving games and strategies that employ implicit, multiple
presentations approaches or individualised programmes using HRL principles to improve the acquisition of specic vocabulary items
for individual learners.
However, one key difference between HRL paradigms and real world language acquisition is that real world learning may have
greater spacing and interspersed distractions between repetitions. Teachers often use repetition of vocabulary items to enhance word
learning and this repetition could be distributed across one or more lessons. Some evidence suggests HRL is resilient to distraction at
both encoding and retrieval. Oberauer et al. (2015) required both processing and storage within Hebb tasks, effectively making the
immediate serial recall task a ‘complex memory span task. Participants were presented with Hebb and ller sequences in the usual
way, but had to make judgements (about the sizes of pictured objects) after the presentation of each item in the sequence (or make
these judgements at recall - interspersed between the recall of each to-be-remembered item in the sequence). Surprisingly, this degree
of distraction did not minimise HRL effects in adults (Oberauer et al., 2015). Such ndings suggest that the HRL effect could still
promote long-term memory mechanisms despite interruptions, and is robust to immediate distraction.
5. Conclusion
The current study found that adolescents with non-specic ID showed HRL effects that were similar in magnitude to children with
TD matched for mental age, supporting a developmental approach to ID (albeit with some uncertainty given small overlaps in credible
intervals across groups). The ndings suggest that for individuals with ID, repetition of sequences within immediate serial recall tasks
improves long-term serial order learning via the gradual integration of serial order information from short-term memory into a more
stable long-term memory trace. HRL was found for both verbal and visuospatial materials, supporting the suggestion that it is a domain
general process; although contrary to expectations, for our measure of HRL, the effects were larger for verbal than visuospatial ma-
terials. The hypothesised links between HRL and vocabulary acquisition as well as other processes, suggest that using repetition in
educational contexts could support learning in children and adolescents with ID.
What this paper adds
Hebb repetition learning has been linked to important developmental and educationally relevant abilities including vocabulary,
grammar and reading.
Hebb repetition learning has not previously been studied in adolescents with non-specic intellectual disabilities: we provide
information about this process.
Hebb repetition learning occurred in adolescents with intellectual disabilities and its magnitude was broadly similar to that of
younger mental age matched children with typical development.
For both groups, Hebb learning occurred in verbal and visuospatial modalities, thereby supporting the argument that Hebb
repetition learning is a domain general process.
Our ndings about adolescents with intellectual disabilities suggest there could be benets of using this form of learning to support
the acquisition and strengthening of their language and literacy abilities in educational contexts.
CRediT authorship contribution statement
Lucy Henry: Conceptualisation, Methodology, Validation, Resources, Data curation, Writing original draft, Writing review &
editing, Supervision, Project administration, Funding acquisition. David Messer: Conceptualisation, Methodology, Validation,
Writing review & editing, Funding acquisition. Sebastian Poloczek: Conceptualisation, Methodology, Validation, Data curation,
L.A. Henry et al.
Research in Developmental Disabilities 125 (2022) 104219
11
Formal analysis, Visualisation, Writing original draft, Writing review & editing, Funding acquisition. Rachel Dennan: Software,
Validation, Investigation, Data curation, Writing original draft, Writing review & editing, Project administration. Elisa Mattiauda:
Investigation, Data curation, Writing original draft, Writing review & editing, Project administration. Henrik Danielsson: Con-
ceptualisation, Methodology, Validation, Writing review & editing, Funding acquisition.
Declaration of Competing Interest
None.
Data Availability
On publication, the original data and analysis les will be uploaded to the Open Science Framework: https://osf.io/gkpwh/.
Acknowledgements and Funding
This research was supported by The Baily Thomas Charitable Fund, grant reference number 47687692. The funder had no role in
the study design; the collection, analysis and interpretation of data; in the writing of the report; or in the decision to submit the article
for publication. We would like to extend our warm gratitude to the children, young people and families who took part in this study, and
to the participating schools. We would also like to extend our deep appreciation for the support and input from Mencap and their
Research Champions in preparing our study materials and at all stages of this project.
Appendix A. Supporting information
Supplementary data associated with this article can be found in the online version at doi:10.1016/j.ridd.2022.104219.
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