Interventions Designed to Improve Narrative Language in School-Age Children: A Systematic Review With Meta-Analyses

Abstract

Purpose
The purpose of this systematic review with meta-analyses was to examine interventions that aimed to improve narrative language outcomes for preschool and elementary school–age children in the United States. Our goal was to examine peer-reviewed publications to describe the characteristics of these interventions and synthesize their overall effectiveness on narrative comprehension and production via meta-analysis.

Method
We searched electronic databases, examined previously published reviews, and consulted experts in the field to identify published studies that employed robust experimental and quasi-experimental designs. We included randomized controlled trials, studies with nonrandomized comparison groups, and single-case design (SCD) studies. We completed a qualitative synthesis of study factors for all identified studies and calculated meta-analyses for the studies that had sufficient data. All included studies were analyzed for risk of bias.

Results
Our systematic search yielded 40 studies that included one or more narrative language outcomes as part of their assessment battery. Twenty-four of the included studies were group design studies, including randomized controlled trials and quasi-experimental designs, and the other 16 were SCD studies. Effect sizes were analyzed based on narrative production and comprehension outcomes. The meta-analyses of 26 studies indicated overall positive effects of the interventions, with effect sizes of d = 0.51 and 0.54 in the group design studies and d = 1.24 in the SCD studies.

Conclusions
A variety of effective interventions were found that improve narrative production and comprehension outcomes in children with diverse learner characteristics. Some common characteristics across these interventions include manualized curricula, opportunities to produce narrative language, verbal and visual supports, direct instruction of story grammar, and use of authentic children's literature.

Supplemental Material
https://doi.org/10.23641/asha.15079173

Full text

LSHSS
Review Article
Interventions Designed to Improve
Narrative Language in School-Age
Children: A Systematic Review
With Meta-Analyses
Danielle L. Pico,
a
Alison Hessling Prahl,
b
Christa Haring Biel,
c
Amy K. Peterson,
d
Eric J. Biel,
e
Christine Woods,
a
and Valentina A. Contesse
a
Purpose: The purpose of this systematic review with meta-
analyses was to examine interventions that aimed to improve
narrative language outcomes for preschool and elementary
school–age children in the United States. Our goal was to
examine peer-reviewed publications to describe the
characteristics of these interventions and synthesize their
overall effectiveness on narrative co mp re he ns io n an d
production via meta-analysis.
Method: We searched electronic databases, examined
previously published reviews, and consulted experts in the field
to identify published studies that employed robust experimental
and quasi-experimental designs. We included randomized
controlled trials, studies with nonrandomized comparison
groups, and single-case design (SCD) studies. We completed
a qualitative synthesis of study factors for all identified studies
and calculated meta-analyses for the studies that had sufficient
data. All included studies were analyzed for risk of bias.
Results: Our systematic search yielded 40 studies that
included one or more narrative language outcomes as part
of their assessment battery. Twenty-four of the included
studies were group design studies, including randomized
controlled trials and quasi-experimental designs, and the
other 16 were SCD studies. Effect sizes were analyzed based
on narrative production and comprehension outcomes. The
meta-analyses of 26 studies indicated overall positive
effects of the interventions, with effect sizes of d=0.51
and 0.54 in the group design studies and d=1.24intheSCD
studies.
Conclusions: A variety of effective interventions were
found that improve narrative production and comprehension
outcomes in children with diverse learner characteristics.
Some common characteristics across these interventions
include manualized curricula, opportunities to produce
narrative language, verbal and visual supports, direct
instruction of story grammar, and use of authentic children’s
literature.
Supplemental Material: https://doi.org/10.23641/asha.
15079173
How important is a child’s ability to tell a story?
Oral narrative ability is related to later language
and academic outcomes for children of all ages
(e.g., Bishop & Edmundson, 1987; Fazio et al., 1996; Griffin
et al., 2004; O’Neill et al., 2004; Wellman et al., 2011). Re-
telling and recounting narratives are included in the U.S.
Common Core standards for elementary students, further
reflecting the importance of narrative language for academic
outcomes (National Governors Association Center for Best
Practices & Council of Chief State School Officers, 2010).
Experts in speech-language pathology and education have de-
veloped and implemented a variety of interventions that aim
to improve narrative language for students with and without
disabilities (see Spencer & Petersen, 2020). In this review, we
sought to examine the characteristics of these interventions
and their effectiveness.
a
School of Special Education, School Psychology, and Early
Childhood Studies, University of Florida, Gainesville
b
Communication Sciences and Disorders, Baylor University, Waco, TX
c
Department of Special Education and Rehabilitation Counseling,
Utah State University, Logan
d
Department of Communicative Disorders and Deaf Education, Utah
State University, Logan
e
College of Behavioral and Community Sciences, University of
South Florida, Tampa
Correspondence to Danielle L. Pico: leuschendepicod@ufl.edu
Editor-in-Chief: Holly L. Storkel
Editor: Marleen F. Westerveld
Received December 10, 2020
Revision received March 13, 2021
Accepted April 30, 2021
https://doi.org/10.1044/2021_LSHSS-20-00160
Disclosure: The authors have declared that no competing interests existed at the time
of publication.
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Oral Narrative Language
Oral narrative language is typically characterized as
a one-sided monologue in which the narrator orally relates
a series of sequenced events that are causally related (Peterson,
1990). Narrative language is often described in terms of its
macro- and microstructure. Macrostructure is the organiza-
tional structure of the narrative, which is commonly referred
to as “story grammar.”Stein and Glenn (1979) described the
most basic narrative as being composed of three elements:
an initiating event or problem, the protagonist’s attempt or
attempts to resolve that problem, and the consequences of
those actions. More complete narratives include a setting, the
protagonist’s internal response to the problem, a plan, and a
reaction to the consequence (Stein & Glenn, 1982). Although
different cultures may employ diverse narrative structures, most
of the narratives students encounter in U.S. schools are con-
structed with this organizational pattern (Tappe & Hara, 2013).
Narrative microstructure is the productivity and complexity of
narrative language at the sentence level (i.e., grammatical
complexity and accuracy, lexical diversity). Microstructure
elements include the use of conjunctions, adverbs, noun
phrases, and different verb types, in addition to other descrip-
tive features, such as total number of words (TNW) and
number of different words (NDW) used (Petersen et al.,
2010).
Oral narrative discourse can involve retelling a story or
generating a new story, and narrative generations may be based
on personal experiences or fictional events invented by the
narrator (Westerveld & Gillon, 2010). Although narrative retell
may generally be considered an easier task than narrative gen-
eration, the difficulty for each task will depend on the narrator’s
particular characteristics and the demands of the narrative task
(see Spencer & Petersen, 2020). For example, a child may gen-
erate a more complex narrative on a preferred topic than they
would on a less interesting topic, even if they are retelling a
familiar story. A child may also experience varying degrees
of narrative proficiency dependent on the extent to which
verbal or visual cues (e.g., graphic organizer, pictures, or
story grammar icons) are provided (Schneider & Dubé,
2005).
Skills Required to Produce Oral Narrative Language
Producing narratives is a complex, discourse-level skill.
Narrators must integrate their linguistic and cognitive skills
with their pragmatic knowledge to make a narrative mean-
ingful to their audience (Boudreau, 2007). Narratives typically
involve decontextualized language, as the events of the story
are not within the immediate context of the narrator and
audience. To facilitate listener comprehension, the narrator
must consider the audience’s point of view, relate events in
a sequential order, provide sufficient description of events,
and make causal relationships apparent (Petersen, 2011). The
narrator must also employ metacognitive skills to evaluate the
completeness of their story (S. L. Gillam & Gillam, 2016).
Retelling a narrative taps further into cognitive skills as the
narrator must also understand the original narrative well
enough to retell it (see Spencer & Petersen, 2020).
Importance of Narrative Language
Several studies have demonstrated the predictive nature of
early oral narrative language skills on later academic outcomes.
For example, Wellman et al. (2011) found that children’searly
narrative retelling skills (ages 3–6 years) were predictive of
literacy-related skills when the participants were older (ages
8–12 years). Specifically, they documented that children’s
early use of macrostructure in retelling a story was linked to
later decoding of real words, reading comprehension, and
written language, while their use of microstructure was pre-
dictive of decoding psuedowords (i.e., words that are not
real but follow English phonotactic rules, such as sark). These
patterns held for all participants involved in their study:
children with a speech sound disorder, with or without
co-occurring language impairment, and children considered
typically developing. Similarly, Griffin et al. (2004) determined
that typically developing children’s narrative generation
skills at the age of 5 years were related to literacy outcomes
at the age of 8 years. The participants’descriptions of char-
acter states, such as saying a character was mad or thirsty,
and use of modifiers or qualifiers (e.g., “a little bit farther,”
p. 128) were linked to reading comprehension scores, and
their early use of plot structure and elaboration was predictive
of later written narrative skills. Researchers have also demon-
strated that the predictive nature of oral narrative language
skills can extend beyond literacy. Feagans and Appelbaum
(1986) found that for children with learning disabilities
(ages 6–7 years), those with stronger oral narrative language
skills performed better than those with weaker skills on
mathematics achievement assessments in the subsequent
3years.O’Neill et al. (2004) also examined the predictive
nature of oral narrative language on math achievement. The
researchers found that certain characteristics of children’s nar-
rative language (e.g., conjunction use and referring to a charac-
ter’s mental states) in a story generation task at the ages of
3–4 years were predictive of math achievement approximately
3 years later. This relationship was not found for the participants’
performance on a general measure of language ability.
In addition to academic outcomes, oral narrative lan-
guage has social importance, as producing narratives plays
an important role in how we relate to one another. Children
use narratives to relate to their peers (Petersen et al., 2008)
and connect with their parents. Thus, difficulties with nar-
rative language may negatively affect friendships for young
children and decrease the dialogue between children and
parents about school or other events (e.g., Nation et al.,
2004). Because less proficient narrators are not as well ac-
cepted by their peers as compared to good narrators, they
may be reticent to use oral narrative language. With fewer
opportunities to practice and improve their narrative lan-
guage, a social context Matthew effect could come into play
(P. C. McCabe & Marshall, 2006; Stanovich, 1986).
Children at Risk for Narrative
Language Difficulties
Children with diverse disabilities have been found to
produce oral narratives that are quantitatively and/or
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qualitatively different (e.g., shorter, less complex, or
incomplete) than those produced by their peers consid-
ered to be typically developing (Boudreau & Chapman,
2000; Fey et al., 2004; R. B. Gillam & Johnston, 1992).
For example, Greenhalgh and Strong (2001) found that
children with specific language impairment produced narratives
with less literate language features, such as conjunctions
(e.g., before, after) and elaborated noun phrases (e.g., “ahole
in the ground,”p. 116). Diehl et al. (2006) found that children
with high-functioning autism spectrum disorder produced
significantly less coherent narratives in story retell tasks com-
pared to peers considered typically developing.
Students may also have difficulties producing the English
oral narrative language expected in U.S. schools due to lin-
guistic and cultural differences. Students from some cultural
or ethnic backgrounds are accustomed to a narrative struc-
ture and style that is different from that which is expected in
the classroom (Gee, 1989; Gorman et al., 2011; A. McCabe
& Bliss, 2005). English language learners (ELLs) may en-
counter further challenges in producing narratives with
complex microstructure, an indicator of oral narrative pro-
ficiency, as they are in the process of acquiring the English
language (Hipfner-Boucher et al., 2015).
Impact of Oral Narrative Language Intervention
The extant research base on oral narrative language
interventions provides evidence that such interventions
can improve oral narrative language for children with
diverse learner characteristics. In this report, we use diverse
learner characteristics to refer to how children in studies
vary in age, disability, socioeconomic status, language
proficiency, and ethnic/racial backgrounds, among other
characteristics.
For children with disabilities that affect language,
multiple studies have demonstrated the potential of oral
narrative language interventions to improve both production
and comprehension. Oral narrative language interventions
have been found to improve both the macro- and micro-
structural features of oral narratives for children with lan-
guage impairment (e.g., S. L. Gillam, Gillam, & Reece,
2012; Hayward & Schneider, 2000; Hessling & Schuele,
2020). Students with autism spectrum disorder also main-
tained gains on measures of story knowledge and perspective-
taking after relatively few intervention sessions (S. L. Gillam
et al., 2015). Additionally, Soto et al. (2009) found that students
using augmentative and alternative communication devices
demonstrated significant growth in story and linguistic
complexity after participating in narrative-focused instruction.
Oral narrative language interventions implemented
at the classroom level have also demonstrated positive effects
for both preschool and elementary school–age children
(S. L. Gillam et al., 2014; Spencer et al., 2018). Students
who are ELLs also appear to benefit from English narrative
intervention, similarly to proficient English speakers (Spencer,
Petersen, Slocum, & Allen, 2015), and these interventions have
been used to improve communicative competence (Schoenbrodt
et al., 2003).
Characteristics of Interventions Targeting
Narrative Language
One of the many benefits of oral narrative language
interventions is their adaptability. Within the context of
narrative language, interventionists can target macro-
structural features, such as identifying the problem and
solution in a story, or microstructural features, such as the
use of temporal conjunctions (Petersen et al., 2014). Oral
narrative interventions can also vary in the type of narrative
language solicited, for example, a story retell, a personal
story generation, or a fictional story generation (Westerveld
& Gillon, 2010). Oral narrative interventions can differ in
focus, targeting narrative language comprehension, narrative
language production, or a combination of both. In addition,
narrative interventions can vary in the levels of verbal and
visual supports they include.
Prior Syntheses
Petersen (2011) reviewed studies addressing narrative
language interventions for preschool and elementary students
with identified language impairments or learning disabilities,
published between 1980 and 2008. Nine studies met the in-
clusion criteria, with a total of 167 participants. Petersen
reported moderate-to-large effect sizes (d=0.73–1.57) on
measures of macrostructure for the reviewed studies. Although
eight of the nine studies reported microstructure outcomes,
few of the interventions described intentional instruction
around syntax. Petersen’s systematic review also included
measures of study quality. His assessment concluded that
only two of the nine studies met criteria for moderate/high
quality, with all others ranked as low or moderate. Although
most participants demonstrated positive growth after par-
ticipating in an intervention, Petersen concluded that results
should be interpreted with caution due to the small sample
sizes and the lack of high-quality experimental procedures
in the studies.
Favot et al. (2020) synthesized the results of 24 studies,
including 326 participants, to examine the effects of oral
narrative language interventions for children with language
disorders. These 24 studies included 11 single-case design
(SCD) studies, 10 group studies, one study with both SCD
and group design elements, and two case studies. Favot et al.
found moderate effects in the SCD studies and a range of
effects in the group design studies providing adequate data,
with Hedges’sgof 0.58–1.23. Favot et al. also evaluated
the included studies for quality. They concluded that the
results of the SCD studies could be considered with some
confidence but that the group design studies demonstrated
low quality.
This review adds to the existing literature in a number
of ways. In Petersen’s (2011) seminal review, he defined
narrative interventions by two criteria: including (a) oral
language features modeled by a clinician in the context of
an oral narrative and (b) the same type of oral language
practiced by the participant. He also limited his participants
to those with disabilities. Similarly, Favot et al. (2020)
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restricted their review to studies implementing explicit oral
narrative language interventions with children with language
disorders. In this review, we broadened the scope to include
any intervention aiming to improve children’s narrative lan-
guage rather than exclusively focusing on explicit narrative
interventions. We also did not limit the participants to those
with an identified disability.
Research Questions
The purpose of this synthesis is to add to the breadth
and depth of prior syntheses by including all interventions
reporting narrative outcomes and providing meta-analyses
of those outcomes. The specific research questions we sought
to address were the following:
1. What are the characteristics (e.g., interventionists,
settings, dependent variables, dosage) of interventions
across studies with narrative language outcomes for
school-age children in the United States?
2. To what extent are these interventions effective in
improving narrative production and comprehension
for children with a variety of learner characteristics?
Method
Study Selection
We conceptualized our study inclusion criteria using
the participants, intervention, comparison condition, out-
come measures, and settings (PICOS) framework, an exten-
sion of the patient, intervention, comparison, outcomes of
interest (PICO) framework first explained by Richardson
et al. (1995) and described further by the Cochrane Collab-
oration (McKenzie et al., 2020). As such, we considered
study participants, intervention, comparison condition, out-
come measures, and settings (see Supplemental Table S1 for
PICOS inclusion criteria).
Searches
We searched three databases on September 12, 2019,
to locate relevant studies: Academic Search Premier, Psy-
cINFO, and Education Resources Information Center.
These databases were chosen to cast a figuratively wide net
to find relevant articles: Academic Search Premier is con-
sidered a top source for multidisciplinary research, PsycINFO
is a main source for social and behavioral research, and
Education Resources Information Center is a fundamental
database for educational research (American Psychological
Association, 2021; EBSCO Information Services, 2021a,
2021b). We limited the results to only include those articles
published in English and in peer-refereed journals. We did
not attempt to collect unpublished data, and no date limits
were set. The electronic search strategy is shown in Supple-
mental Table S2. We did not preregister this protocol. We
updated the search on May 30, 2020, using the same search
strategy and within the same databases. We imported cita-
tions yielded from both searches into EndNote X9 (Clarivate
Analytics, 2020) for management. In addition, we examined
two previously conducted reviews on narrative language in-
terventions (i.e., S. L. Gillam & Gillam, 2016; Petersen,
2011) and consulted two experts in the field to identify
additional studies.
Identification and Selection of Studies
After deduplication, the first author screened all titles
and abstracts to exclude those studies that did not meet
inclusion criteria. The third author also independently
screened 33% of the original set of articles and had 95%
agreement with the first author. Both authors then com-
pleted an independent full-text review of the remaining
studies. Discrepancies were resolved t hrough discussion
and consensus.
Data Extraction and Coding
The third and fourth authors double-coded the 40
articles that met inclusion criteria. Interrater reliability
across studies was .95. Coding discrepancies were discussed,
articles were reviewed again when necessary, and discrepan-
cies were resolved by consensus. See Supplemental Table S3
for a list of data extracted.
Functional Relations
With SCD studies, researchers examine the resultant
data to determine if a functional relation is evident between
the independent and dependent variables or outcome be-
haviors of interest (Gast & Ledford, 2018). Such a relation-
ship indicates that a change in the dependent variable is
functionally or causally related to the independent variable.
The second author evaluated each SCD to determine if a
functional relation was observed based on What Works
Clearing house standards (What Works Clearinghouse,
2014), specifically if there were at least three demonstra-
tions of effect based on level, trend, variability, immediacy,
overlap, and consistency without a demonstration of a
noneffect. A secondary coder independently made func-
tional relation decisions. They obtained 80% agreement,
and discrepancies were resolved by consensus.
Assessment of Risk of Bias
The term risk of bias refers to the possibility that the
results of a study could contain systematic deviations from
the truth due to study design or outcome analysis and
reporting. The first and sixth authors evaluated the group
design studies using the revised Cochrane risk-of-bias tool
(RoB 2; Sterne et al., 2019). They obtained 92% agreement,
and discrepancies were resolved by consensus. The first
and seventh authors assessed the SCD studies using the
tool developed by Reichow et al. (2018), obtaining 77%
agreement. Due to the relatively low agreement obtained,
they consulted with one of the tool’s developers regard-
ing classifications of risk and resolved discrepancies by
consensus.
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Statistical Analyses
Group Design Effect Sizes
Effect sizes for group design studies utilizing between-
groups methods were calculated using Cohen’sd, which re-
flects the standardized mean difference based on the posttest
difference in means and the pooled posttest standard deviation.
Of the 20 group design studies, 13 provided sufficient data
for calculating effect sizes. For studies with multiple sam-
ples or time points, each sample or time point was treated
as an independent study. Thus, effect sizes were calculated
from a total of 16 independent studies. Two meta-analyses
were completed for (a) narrative production outcomes and
(b) narrative comprehension outcomes. Narrative production
was operationally defined as orally expressing a narrative,
and narrative comprehension was operationally defined as
receptive understanding of a narrative, usually demonstrated
by answering questions about the narrative. In cases where
multiple narrative production or comprehension outcomes
were reported, relevant outcomes were averaged together so
that one narrative production and/or narrative comprehen-
sion effect size was reported for each study.
Effect sizes were weighted by the number of study
participants, such that studies with a larger number of par-
ticipants contributed more heavily to the final effect size
obtained. We interpreted the effect sizes following Cohen’s
(1988) recommendations: small (0.2), medium (0.5), and
large (0.8). Effect sizes are typically considered significant
if the 95% confidence interval (CI) for ddoes not cross 0.
The meta-analysis was conducted using the metafor pack-
age (Viechtbauer, 2010) for the R statistical computing en-
vironment. Heterogeneity was assessed using the Q,I
2
, and
τ
2
statistics. The Qstatistic reflects the amount of heteroge-
neity, I
2
reflects the percentage of variation across studies
that is due to heterogeneity, and τ
2
reflects the amount of
true heterogeneity. I
2
values of 25%, 50%, and 75% are
considered as low, moderate, and high proportions of
heterogeneity, respectively (Higgins et al., 2003).
SCD effect sizes
To calculate effect sizes for the included case studies,
raw data from each study were digitally extracted from
published SCD graphs using Plot Digitizer (2015). The
log response ratio (LRR; Pustejovsky, 2018) was calcu-
lated for the purpose of quantifying the magnitude of
treatment effects for the SCD studies. For multiple-baseline
designs, effect-size estimates were calculated separately for
each baseline–intervention comparison, essentially for each
tier. The LRR is a metric for comparing two mean levels
by quantifying functional relations in terms of the natural
logarithm of the proportionate change between phases in
the level of the outcome (Pustejovsky, 2018). The LRR effect-
size estimate is not appropriate for ordinal data; thus, nine
studies were excluded from the meta-analysis because the
narrative production outcome consisted of a rubric rating.
We synthesized the LRR effect sizes using a multilevel
random effects meta-analysis model, which included study-
level and participant-level random errors. The standard
deviation of the study-level random errors reflects the amount
of heterogeneity across studies, and the standard deviation of
the participant-level random errors reflects the amount of
heterogeneity across participants within a study. We report
the estimated average effect from the LRR model, the
corresponding standard error, and a 95% CI. As measures of
heterogeneity, we also report the estimated study-level and
participant-level standard deviations in which larger stan-
dard deviations indicate greater variability in outcomes.
For analyses, we used the metafor (Viechtbauer, 2010),
clubSandwich (Pustejovsky, 2019), and SingleCaseES
(Pustejovsky & Swan, 2018) packages in the R statistical
computing environment.
Publication Bias Assessment
Publication bias was evaluated to determine whether
findings may be influenced by including only studies with
larger-than-average effects, which are more likely to be
published. Publication bias was assessed by creating funnel
plots and conducting an Egger regression test for funnel
plot asymmetry (Egger et al., 1997).
Results
Study Selection
Of our original compilation of potential articles,
877 unique articles remained after deduplication. Please
see the search results in Supplemental Table S2. We then
screened their titles and abstracts and excluded 813 articles
for not meeting inclusion criteria, leaving 64 articles. A
full-text review of these articles resulted in 40 remaining
articles that met eligibility criteria. We included 13 group
design studies and 13 SCD studies that had adequate
data for meta-analyses. A Preferred Reporting Items for
Systematic Reviews and Meta-Analyses (Moher et al.,
2009) flow diagram of the study selection is shown in
Figure 1.
Study Characteristics
Of the 40 studies identified, 24 employed a group de-
sign and 16 used an SCD. Their publication years ranged
from 1980 through 2020. Across all studies, there were
1,597 participants, with 941 receiving some form of in-
tervention. The corpus of studies included participants with
diverse learner characteristics, including participants with
and without identified disabilities. Study characteristics
are presented in Table 1.
Intervention Characteristics
Study reports varied in the completeness of their de-
scriptions of the interventions implemented; thus, it is im-
possible to provide a comprehensive review of all the
components represented. Nevertheless, there were several
components that were common across many interventions.
Half of the studies reported using a manualized or scripted
intervention. Some of these manualized interventions were
examined in several studies (e.g., Story Champs: Spencer &
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Petersen, 2012; Supporting Knowledge in Language and
Literacy: S. L. Gillam, Gillam, & Laing, 2012). Over
half of the interventions (k= 24, 60%) employed direct
instruction of story grammar components (e.g., character,
problem, solution). Visual supports were also commonly
used, in the form of story grammar icons and/or pictures
to support the retelling of a story. For example, both the
Supporting Knowledge in Language and Literacy and Story
Champs interventions employed story grammar icons so
children could generalize story schema across different
stories. Three studies reported using the Story Grammar
Marker, a manipulative featuring story grammar icons
that children can touch and manipulate. Over half of the
studies reported using verbal supports, in the form of ver-
bal prompts or recasts and expansions (k= 21, 52.5%), and
over half the studies reported using authentic children’s liter-
ature (k= 26, 65%). Some articles also reported use of ac-
tivities requiring peer collaboration and games to keep
children engaged and motivated. Eight of the studies
had Span ish-speaking dual language learners or ELLs as
their participants, and of these, five examined the use of a
dual-language intervention or compared interventions im-
plemented in English with interventions implemented in
Spanish.
Narrative language in interventions. In the majority
(k= 32, 80%) of the studies, the examined intervention
required the participants to produce narrative language as
part of the intervention, either a retell, a personal story
generation, or a fictional story generation (see Supplemen-
tal Table S4). The most common type of narrative produc-
tions elicited in the interventions was story retell (k= 28,
70%). Ten studies (25%) examined interventions that in-
cluded personal story generations, and 10 studies (25%)
examined interventions that included fictional story gener-
ations. Fifteen studies (37.5%) examined interventions
that included two different types of narrative language,
with the most common combination being a story retell
and a personal story generation (k=8).
Eight of the studies (20%) did not require students to
produce narrative language as part of the examined inter-
vention but included narrative elements in other ways. One
study looked at long-term effects of a day care program, so
it was unclear what type of narrative language participants
may have been prompted to produce throughout the course
of the program (Feagans & Farran, 1994). Five of the
examined interventions (i.e., Carnine & Kinder, 1985;
Garner & Bochna, 2004; Green & Klecan-Aker, 2012;
Khan et al., 2014; Stevens et al., 2010) provided explicit
instruction on identifying story grammar components
such as character and problem. Two studies used more
implicit methods: One intervention involved additional
small-group instruction on vocabulary initially exposed
through shared book reading with the whole class (Fien
et al., 2011), and one involved a listening comprehension
and vocabulary interventionthatalsoemployedshared
book reading (Henry & Solari, 2020). These studies met
inclusion criteria because they examined narrative language
as part of their outcome measures.
Narrative Language in Outcomes
In the majority of the studies (k= 35, 87.5%), a story
retell was elicited from participants as part of the narrative
language outcome measures. In 13 of the studies (32.5%),
fictional story generations were elicited, and personal stories
were elicited in 10 (25%) studies. Eleven of the studies
(27.5%) had participants produce both a story retell and a
fictional story, with the fictional story often to be modeled
from the story retell. Six studies (15%) had participants pro-
duce both a story retell and a personal story, and one study
had participants produce a personal story and a fic-
tional story.
We examined the incongruity between the narrative
language solicited as part of the intervention and narrative
language measured as an outcome. Fourteen studies (35%)
measured a type of narrative language as an outcome that
was not explicitly practiced as part of the intervention.
Measures
In addition to narrative language, multiple studies
also measured intervention effects on reading comprehension,
literacy outcomes, expressive or receptive language, or vocab-
ulary. Of those focusing primarily on narrative outcomes,
Figure 1. Preferred Reporting Items for Systematic Reviews and
Meta-Analyses flow diagram of study selection.
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Table 1. Included studies’characteristics.
Study Design Intervention n
Participant
characteristics
(age: years;months)
Approximate
dosage
Interventionist
and setting
Adlof et al.
(2014)
Group T: structured narrative retell intervention
C: code-focused literacy instruction
T: 4
C: 5
African American, low SES
(M= 5;0, range: 4;1–6;10)
480 min across 12 sessions Graduate students; child care
center
Brown et al.
(2014)
SCD T: narrative retell with self-monitoring T: 3 African American at risk for
language disorders (4;4,
4;9, 4;11)
270 min across 16 sessions SLP and gr adu ate students;
private school
Carnine &
Kinder
(1985)
Group T1: schema based
T2: generative based
T1: 13
T2: 14
Students with reading
comprehension difficulties
(Grades 4–6,
a
~9;0–12;0)
475 min across 19 sessions Teachers; elementary school
Feagans
& Farran
(1994)
Group T1: abecedarian early intervention
project (day care program)
C: BAU
T: 45
C: 44
LPS: 64
Low SES (kindergarten,
a
~5;0)
4–5 years (from 3 months
until entered kindergarten)
Interventionists not described;
day care
Fien et al.
(2011)
Group T: small-group reading booster
instruction focused on vocabulary
and comprehension
C: BAU
T: 54
C: 52
Low language and vocabulary
skills (first grade,
a
~6)
320 min across 16 sessions Teachers and paraprofessionals;
elementary school
Freedman &
Brooks
(1980)
Group T1: visual review throughout story
book reading
T2: visual review after storybook
reading
T3: drawing pictures throughout
storybook reading
T4: drawing pictures after storybook
reading
T5: visual review and retell throughout
storybook reading
T6: visual review and retell after
storybook reading
C: no review activities
T1–T6,
and C: 66
Not described (M= 5;0) Not described Not described; preschool
Garner &
Bochna
(2004)
Group T: Reading and Intensive Learning
Strategies (Stevens, 1998)
C: BAU
T: 35
C: 31
Not described (first grade,
a
~6;0)
2,720 min across 160
sessions
Teacher; elementary school
S. L. Gillam,
Gillam, &
Reece
(2012)
Group T1: contextualized literature-based
language intervention
T2: decontextualized language
intervention
C: BAU
T1: 8
T2: 8
C: 8
With LI (M= 7;10, range:
6;0–9;0)
900 min across 18 sessions SLP and graduate students;
elementary school
S. L. Gillam
et al. (2015)
SCD T: SKILL T: 5 With ASD (M= 9;8, range:
8;4–10;0)
Varied across participants,
19–33 sessions
Interventionist; university clinic
S. L. Gillam
et al. (2014)
Group T: SKILL
C: BAU
T: 21
C: 19
Diverse characteristics
b
(M= 7;0, range: 6;6–7;4)
540 min across 18 sessions SLP; elementary school
S. L. Gillam
et al. (2018)
SCD T: SKILL
C: baseline conditions
T: 4
C: 2
With LI (M= 9;5, range:
6;7–10;4)
Varied across participants,
13–24 sessions
SLP; elementary school
Green &
Klecan-Aker
(2012)
Group T: the Expression Connection program
(Klecan-Aker & Brueggeman,
1991)
T: 24 With specific language
learning difficulties
(range: 6;3–9;6)
780 min across 26 sessions Graduate student; campus
laboratory school
(table continues)
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Table 1. (Continued).
Study Design Intervention n
Participant
characteristics
(age: years;months)
Approximate
dosage
Interventionist
and setting
Henry & Solari
(2020)
Group T: adapted from Building Vocabulary
and Early Reading Strategies
(Solari & Ciancio, 2014)
C: BAU
T: 22
C: 21
With ASD (range: 5;0–9;0) 2,730 min across 55–
72 sessions
Special education teachers;
elementary school
Hessling &
Schuele
(2020)
SCD T: Story Champs
c
T: 4 With LI (M= 8;4, range:
8;0–8;11)
Varied by participant, average
of 18 min per session
SLP, graduate students;
elementary school
Justice et al.
(2008)
SCD T: narrative-based language intervention
(NBLI; Swanson et al., 2005) with
Story Grammar Marker
T: 3 With hearing loss and
cochlear implants
(5;4, 7;6, 8;0)
Not described, for 6 weeks Clinician; not described
Khan et al.
(2014)
Group T: story grammar instruction with
student choice
C: story grammar instruction without
student choice
T: 14
C: 12
Considered typically
developing (M= 3;10,
range: 3;1–5;4)
100 min across eight sessions Researcher; preschool
Klecan-Aker
et al. (1997)
Group T: the Expression Connection program
(Klecan-Aker & Brueggeman, 1991)
C: not described
T and
C: 15
With learning disabilities
(M= 7;2, range: 6;2–8;9)
1,080 min across 36 sessions Researcher; school for children
with learning disabilities
Lugo-Neris
et al. (2015)
Group T1: Language and Literacy Together
(LLT) in Spanish
T2: LLT in English
T1 and
T2: 6
Spanish–English bilingual
children at risk for LI,
low SES (M=6;8,
range: 6;2–7;2)
900 min across 24 sessions Graduate student; elementary
school
A. McCabe
et al.
(2009)
Group T: Reading–Writing–Remembering
C: BAU preschool curriculum
T: 57
C: 39
Diverse characteristics
b
(M=4;8)
520 min across 26 sessions University students; preschool
McGregor
(2000)
SCD T: peer-to-peer retell with wordless
storybooks
T: 4 African American English–
speaking children
(M= 3;9, range:
3;4–4;3)
200 min across 10 sessions Clinician; preschool
Miller et al.
(2018)
SCD T: explicit story grammar instruction
with Story Grammar Marker
T: 4 Spanish-speaking ELLs
with LI (M= 9;8,
range: 9;4–10;1)
Varied by participant, three
30-min sessions per week
Bilingual graduate student;
elementary school
Miller et al.
(2017)
SCD T: Mis LIBROS (Literacy Intervention:
Bilingual Reading and Writing
Opportunities)
T: 3 Spanish-speaking ELLs
(8;2, 8;9, 9;3)
Varied by participant, 30-min
sessions, twice a week
for 16 weeks
Bilingual graduate student;
elementary school
Pakulski &
Kaderavek
(2012)
Group T1: read-aloud and discuss story with
reading buddy
T2: read-aloud and discuss story with
reading buddy, using manipulatives
T: 7 (within-
subject
design)
With hearing loss, with
either hearing aids
or cochlear implant
(M= 10;2, range:
9;4–11;1)
80 min across four sessions Teacher; school for children
with hearing loss
Paris & Paris
(2007)
Group T: narrative strategy instruction
C: language and poetry instruction
T: 83
C: 40
Diverse characteristics
b
(M=6;7)
450 min across 10 sessions Researcher; elementary school
Petersen et al.
(2014)
SCD T: individualized, systematic narrative
language intervention
T: 3 With ASD (6;4, 6;6, 8;5) 420 min across 12 sessions Clinician; university speech clinic
(table continues)
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Table 1. (Continued).
Study Design Intervention n
Participant
characteristics
(age: years;months)
Approximate
dosage
Interventionist
and setting
Petersen et al.
(2010)
SCD T: adapted version of the Functional
Language Intervention Program for
Narratives (S. L. Gillam et al., 2008)
T: 3 With neuromuscular
impairment, LI
(6;3, 6;5, 8;1)
600 min across 10 sessions SLP and board-certified behavior
analyst; clinic
Petersen et al.
(2016)
Group T: Story Champs,
c
individual procedures
C: BAU
T: 42
C: 31
Spanish–English bilingual
children, some with LI
(range: 5;11–9;8)
50 min across two sessions Interventionists; elementary school
Schoenbrodt
et al. (2003)
Group T1: narrative intervention with read-aloud
and Story Grammar Marker,inSpanish
T2: narrative intervention with read-aloud
and Story Grammar Marker,inEnglish
T1: 6
T2: 6
Spanish–English bilingual
children (range: 6;0–11;0)
Eight sessions Clinicians; elementary school
Spencer et al.
(2013)
SCD T: Story Champs,
c
individual procedures T: 5 With developmental delay;
four Spanish-speaking
(M=4;9,range:4;8–4;11)
300 min across 24 sessions Interventionists; preschool
Spencer et al.
(2020)
Group T: Puente de Cuentos, dual-language
narrative curriculum, with whole-group
and small-group components
C: BAU
T: 43
C: 38
Spanish-speaking ELLs,
3–5(M= 4;2, range:
3;1–4;10)
Two whole-group sessions
per week, four small-
group sessions per week
throughout the school
year
Teachers and paraprofessionals;
preschool
Spencer,
Petersen,
& Adams
(2015)
Group T: Story Champs
c
small-group procedures,
in addition to whole-group instruction
C: only whole-group instruction
T: 11
C: 10
Identified for Tier 2 language
support based on dynamic
narrative assessments
(M=4;2)
18 sessions across 9 weeks Research assistants; preschool
Spencer
et al.
(2019)
SCD T: dual-language intervention similar
to Story Champs,
c
with embedded
vocabulary instruction
T: 8 Spanish-speaking, low SES
(M= 4;5, range: 3;6–5;0)
480 min across 24 sessions Teachers and research assistants;
preschool
Spencer,
Petersen,
Slocum,
& Allen
(2015)
Group T: Story Champs
c
whole-group
procedures
C: BAU
T: 36
C: 35
Diverse characteristics
b
(M= 4;10)
210 min across 12 sessions School psychologist and special
educator; preschool
Spencer &
Slocum
(2010)
SCD T: modeling and supported retell with
icons and personal story generation
T: 5 With narrative language
delays (M= 4;7, range:
4;3–5;1)
Varied by participant, 12 min
per session, 4 times a
week
School psychologist and SLP;
preschool
(table continues)
Pico et al.: Interventions That Improve Narrative Language 9
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Table 1. (Continued).
Study Design Intervention n
Participant
characteristics
(age: years;months)
Approximate
dosage
Interventionist
and setting
Spencer et al.
(2018)
Group T: Story Champs
c
with whole-group,
small-group, and individual
procedures
C: BAU
T: 53
C: 52
Diverse characteristics
b
(M= 3;10, range:
3;1–5;1)
Whole group: two sessions
a week for 4 weeks and
then one session a week
for 4 months
Small group and individual:
two sessions a week for
4 months
Teachers; preschool
Stevens et al.
(2010)
Group T: Story Structure Instruction
C: storybook reading
T: 200
C: 121
Diverse characteristics
b
(kindergarten to second
grade,
a
~5;0–7;0)
15 min daily throughout the
school year
Teachers; elementary school
Swanson et al.
(2005)
Group T: NBLI T: 10 With LI (M= 7;10, range:
6;11–8;9)
900 min across 18 sessions SLPs; varied: university language
lab, child’s school, or child’s
home
Tyler &
Sandoval
(1994)
SCD T1: direct phonology instruction
T2: indirect narrative intervention:
retelling of narratives with
expansion and recasting
T3: combined phonological treatment
with narrative retelling
T: 6 With language and
phonological disorders
(M= 4;0, range:
3;6–4;8)
900 min across 24 sessions Not described; elementary
school
Valentino et al.
(2015)
SCD T: storybook reading with prompted
retell, with modified chaining
T: 3 With ASD (4;0, 7;0, 8;0) Varied by participant Experimenter; clinic
Weddle et al.
(2016)
SCD T: Story Champs
c
small-group and
individual procedures
T: 7 Culturally and linguistically
diverse, Latino (M= 4;2,
range: 3;7–4;10)
280 min across 16 sessions Research assistants; preschool
Note. T = treatment; SES = socioeconomic status; C = control or comparison; M= mean age; SCD = single-case design; SLP = speech-language pathologist; BAU = business as usual;
LPS = local population sample; LI = language impairment; SKILL = Supporting Knowledge in Language and Literacy (S. L. Gillam, Gillam, & Laing, 2012); ASD = autism spectrum
disorder; ELLs =
English language learners.
a
Age was not reported, so ages were estimated.
b
The term diverse characteristics is used to describe classrooms of children who have diverse racial/ethnic backgrounds, disability
statuses, SES, and/or English language proficiency.
c
Spencer & Petersen, 2012.
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study design (SCD or group design studies) and interven-
tion focus (macrostructure or microstructure) dictated mea-
sures used.
Measures of comprehension. Of the 40 studies meeting
inclusion criteria, 11 included one or more measures of com-
prehension. Four studies assessed story comprehension: two
using the Test of Story Comprehension (Spencer & Petersen,
2011) and two using the Assessment of Story Comprehension
(Spencer & Goldstein, 2019). Two additional studies included
informal or unnamed measures of listening comprehension
and reading comprehension, respectively.
Measures of narrative production. Relatively few
standardized, norm-referenced assessments of narrative
outcomes exist in the field; thus, it was not surprising
that a significant number of studies (k= 12) employed
the use of researcher-made, informal measures or elected
to use selected subtests from formal measures (k=12).Mea-
sures selected reflected both study design and intervention
targets.
Studies measuring changes in narrative macrostructure
(k= 12) such as story grammar, narrative coherence, or
organization most often used standardized instruments, some
of which allow users to capture macrostructure and micro-
structure elements. The Narrative Language Measures
(Petersen & Spencer, 2010) as a comprehensive measure
or one of the subtests (i.e., Test of Narrative Retell, Test of
Story Comprehension, Test of Personal Story Generation)
was used in 11 studies. Three studies reported using the
Monitoring Indicators of Scholarly Language (S. L. Gillam
et al., 2016), which allows for examination of macrostruc-
ture and microstructure elements as a result of an inter-
vention. Two studies used the Test of Narrative Language
(R. B. Gillam & Pearson, 2004), in whole or in part, to
assess participants’growth in narrative production and
comprehension. One study used the Teacher Rating
of Oral Language and Literacy (Dickinson et al., 2001)
to assess oral language, reading, writing, and narrative
quality.
When assessing the microstructure elements that in-
crease syntactic complexity (e.g., conjunctions, verb tenses,
clauses), researchers most often used language sampling.
Participants were asked to retell or generate a story with or
without picture prompts, and researchers used tallies of the
NDW, the TNW, their mean length of utterance (MLU),
and/or the number of T-units (i.e., clauses) as indicators of
growth from pre- to postintervention. Please see Supplemen-
tal Material S1 for results of social validity and fidelity of
implementation.
Functional Relations
Visual analysis of the level, trend, and stability of data
across phases allows for the objective evaluation of treatment
effects (Horner et al., 2012). Based on visual analysis, the
coders identified strong evidence of a functional relation in
11 studies and moderate evidence of a functional relation
in two studies. Eighteen comparisons resulted in no evidence
of a functional relation.
Risk of Bias
Group design studies were evaluated for risk of bias
using the RoB 2 (Sterne et al., 2019), and SCD studies were
evaluated with the tool developed by Reichow et al. (2018).
Two group design studies were excluded from these evalua-
tions as their study design did not match the specifica-
tions of the RoB 2 tool: Green and Klecan-Aker (2012)
and Swanson et al. (2005) used a pretest–posttest design
with no comparison group. The risk of bias for each evalu-
ated study is presented in Supplemental Figures S1 and S2,
and a summary of risk of bias across all studies is presented
in Supplemental Figures S3 and S4. All of the group design
studies evaluated (k= 22) were determined to have some
concerns forriskofbias,andthemajorityoftheSCDs
(k= 15) were assessed as having a high risk of bias: Of the
SCD studies, only the S. L. Gillam et al. (2018) study was
evaluated as having an unclear risk. Similar sources of po-
tential bias appeared repeatedly across many studies. For
example, in the domain of selection of the reported results,
all of the group design studies evaluated were rated some
concerns for not reporting a preregistered protocol. Like-
wise, the SCD studies had common patterns of ratings
across studies, such as unclear risk for sequence generation
(k= 16) and mostly high risk for blinding of participants
and personnel (k= 12). These ratings were due to limited
use of randomization and the close involvement of the re-
searcher in the implementation of the intervention, char-
acteristics that were common across the majority of the
included SCD studies.
Meta-Analysis of Group Design Effect Sizes
Two meta-analyses were completed for the group de-
sign studies examining (a) narrative production outcomes
(see Supplemental Table S5) and (b) narrative compre-
hension outcomes (see Supplemental Table S6). In the
case of significant results, positive effect sizes indicate a
positive effect of narrative interventions and negative effect
sizes indicate a negative effect of narrative interventions.
Two studies included outcomes that combined narrative
production and comprehension, and thus, the effect size for
that outcome was excluded because it did not fit exclusively
into either meta-analysis.
Narrative Production Meta-Analysis
The results from the narrative production meta-analysis
are presented in Figure 2. For the group design studies, the
narrative production sample included 28 effect-size estimates
from 16 unique reports with between one and four narrative
production outcome effect sizes per study. The overall
weighted average effect-size across all 28 narrative pro-
duction effect-size estimates was d= 0.54 (95% CI [0.34, 0.73],
p< .0001). This reflects a positive, medium effect of narrative
interventions on narrative production outcomes. Moderate
heterogeneity was detected across the 16 reports (I
2
= 52.37%,
τ
2
= 0.08). Based on follow-up moderator analyses, narrative
Pico et al.: Interventions That Improve Narrative Language 11
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production outcomes were not moderated by narrative elici-
tation context—retell versus generation (Q=1.93,p=.16).
A funnel plot (see Supplemental Figure S5) was con-
structed to evaluate publication bias. Asymmetric funnel
plots that depict most of the studies with strong, positive
effects (i.e., depicted on the right side of the funnel) may
indicate that findings are vulnerable to publication bias
(Sutton, 2009). The relative symmetry of the funnel plot
in Supplemental Figure S5 suggests that the narrative pro-
duction finding was not significantly vulnerable to publi-
cation bias. Furthermore, there was no evidence of small
study effects or publication bias based on an Egger’sre-
gression test (z= 1.74, p= .08).
Narrative Comprehension Meta-Analysis
The results from the narrative comprehension meta-
analysis are presented in Figure 3. The narrative compre-
hension sample included 20 effect-size estimates from nine
unique reports with between one and eight effect sizes per
study. The overall weighted average effect size across all
20 narrative production effect-size estimates was d= 0.51
(95% CI [0.25, 0.76], p< .0001). This reflects a positive,
medium effect of narrative interventions on narrative com-
prehension outcomes. A moderate level of heterogeneity
was observed across the six studies (I
2
= 56.3%, τ
2
= 0.08).
The relative symmetry of the funnel plot in Supple-
mental Figure S6 suggests that the narrative comprehen-
sion finding was not significantly vulnerable to publication
bias. There was no evidence of small study effects or publi-
cationbiasbasedonanEgger’s regression test (z= 0.41,
p=.68).
Meta-Analysis of SCD Studies
Although we planned to similarly conduct two meta-
analyses (narrative production and narrative comprehension
outcomes) for the SCD studies, too few studies included
narrative comprehension outcomes (k= 1) for a meta-analysis
to be carried out. Thus, the results for the narrative pro-
duction meta-analysis are reported below.
Narrative Production Meta-Analysis
For the SCD studies, the narrative production sam-
ple included 38 effect-size estimates from six unique reports
with between four and nine effect sizes per study. Six com-
parisons were removed due to zero-level variance in the effect-
size estimate, and the data were reanalyzed. The narrative
production outcomes for the remaining studies included
NDW, TNW, MLU, and number of microstructure ele-
ments produced in oral narratives. It is important to note
that these outcomes are all narrative microstructure indi-
ces, whereas indices for both narrative macrostructure and
microstructure were analyzed for the group design narra-
tive production meta-analysis. The average effect across all
SCD comparisons was LRR = 1.28 (SE = 0.50, 95% CI
[0.30, 2.26]). In regard to heterogeneity, high study-level
variation (SD = 1.17) and high participant-level variation
(SD = 0.81) were detected.
Discussion
In this review, we sought to examine all peer-reviewed
studies on interventions that aimed to improve narrative lan-
guage outcomes for preschool and elementary school–age
Figure 2. Forest plot of narrative production group design studies.
12 Language, Speech, and Hearing Services in Schools •1–18
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children in the United States. Our goal was to describe the
characteristics of these interventions and synthesize their
overall effectiveness on narrative comprehension and pro-
duction via meta-analysis. We identified 40 studies, 24 group
design and 16 SCD, published between 1980 and 2020.
Common characteristics of the examined interventions are
described above, and the results of the meta-analyses sug-
gested positive, medium effects for narrative comprehen-
sion outcomes and positive, medium-to-high effects for
narrative production outcomes.
This synthesis adds to the research base in several
ways. First, we did not limit our inclusion criteria to par-
ticipants with disabilities. This, combined with the additional
research conducted since Petersen’s (2011) seminal review,
resulted in a large number of participants—1,597 across 40
studies. By broadening our participant criteria, we increased
the possibility of generalization of the findings to other
populations, including those not identified with a disability
and students who are ELLs.
We also defined our interventions of interest more
broadly and included any intervention that aimed to im-
prove oral narrative language. Despite this wider umbrella,
only eight studies (20%) did not explicitly require the par-
ticipants to produce any form of narrative language as part
of the intervention. The majority (80%) did require the
participants to produce narrative language as part of the
intervention, with story retells being the most commonly
produced. These results are consistent with Petersen’s (2011)
finding that repeated narrative retellings and generations
were the only commonality among the diverse practices
found in the narrative interventions included in his review.
In our review, six studies, however, assessed a type of nar-
rative language different than that employed as part of the
intervention. This may suggest that the researchers as-
sumed generalization across narrative language types could
occur.
Compared to prior syntheses, our corpus of studies
also included more diversity in persons implementing the
interventions, participants, settings, dosage, and outcome
measures. Our review found only four studies were con-
ducted in clinical settings, with the rest housed in school
environments. Additionally, implementers in prior studies
were most often speech-language pathologists, clinicians,
or researchers. This review included nine studies where im-
plementers were teachers and/or teaching assistants. The
number of interventions performed in whole-group settings
(k= 8) is also notable, whereas small-group intervention
sessions had been identified as the primary mode of delivery
in previous reviews. Also of note is the wide range of re-
ported intervention dosages as well, with some studies
reporting significant findings in a relatively small dosage
of narrative language intervention (e.g., McGregor, 2000;
Petersen et al., 2016; Spencer, Petersen, Slocum, & Allen,
2015).
Meta-Analytic Findings
High-quality meta-analyses are among the highest
level of scientific evidence. Systematically assessing the re-
sults of previous research enables us in the fields of speech-
language pathology and education as well as other related
fields to derive conclusions about this body of research. Based
on the group design studies, medium Cohen’sdeffect sizes
were reported for narrative production outcomes (d= 0.54)
and narrative comprehension outcomes (d= 0.51). A much
larger effect size was reported for narrative production
Figure 3. Forest plot of narrative comprehension group design studies.
Pico et al.: Interventions That Improve Narrative Language 13
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outcomes (d= 1.24) based on the SCD studies. Petersen
(2011) reported moderate-to-large effect sizes for narrative
macrostructure, ranging from d=0.67 to d= 1.57, and
noneffects to large effect sizes for narrative microstruc-
ture, ranging from d=−1.08 to d=1.53.Favotetal.
(2020) reported moderate effects from SCD studies and a
range of effect sizes found in group studies, with Hedges’s
gof 0.58–1.23. Hedges’sgeffect sizes are interpreted in a
similar way as compared with Cohen’sd. The smaller av-
erage effect sizes in the current synthesis compared to
Petersen’s review could be attributed to how interven-
tion was operationalized for the included studies. Petersen
reviewed studies “that used oral narratives as a medium
whereby language-related features were modeled by the cli-
nician and practiced by the participant,”whereas we
reviewed any study that included narrative language
outcomes. Larger average effect sizes were reported for
interventions that provided explicit narrative language
modeling and practice than for interventions that did not
explicitly require narrative language production but in-
cluded narrative language as an associated outcome
variable.
In the context of our results, one possible explanation
for the wide range of narrative production outcome effect
sizes is the differing outcome measures included in each
meta-analysis. In general, several different narrative pro-
duction outcomes were reported across all the included
studies(e.g.,storygrammarscore,MLU,NDW,TNW).
This wide range of narrative production outcome mea-
sures (macrostructure and microstructure) was captured
in the meta-analysis of group design studies. However,
the production outcomes measured using a rubric rating
(e.g., Test of Narrative Retell; Spencer & Petersen, 2011),
most commonly measures of macrostructure, are not ap-
propriate for the SCD meta-analysis and thus were excluded.
As a result, the outcomes included in the SCD meta-analysis
reflect mostly microstructure measures of narrative produc-
tion. Interventions that impact narrative language may have
a larger effect on narrative microstructure than macro-
structure. In future research, common measures of narrative
production and comprehension should be included to allow
for more homogeneous outcomes that can more reasonably
be combined and meta-analyzed. We observed moderate
heterogeneity across the analyzed studies, and thus, future
inclusion of similar outcomes may lead to reduced hetero-
geneity across studies as well.
Despite the variability across outcome measures in-
cluded in this synthesis, group design and SCD studies
evaluating interventions that affect narrative language ap-
pear to complement one another and, collectively, cover the
breadth of narrative outcomes. Although narrative compre-
hension was only evaluated in one SCD as a secondary
outcome variable, narrative comprehension outcomes were
evaluated across several group design studies, and signifi-
cant treatment effects were observed. Researchers evaluated
narrative production outcomes in group design and SCD
studies. In group studies, narrative production outcomes
rely on comparing aggregate data across study conditions
(treatment and control). In SCD studies, narrative produc-
tion outcomes rely on baseline logic in which the interven-
tion is introduced in a time-lagged fashion to evaluate the
effect across participants or behaviors. Both approaches
attempt to minimize threats to validity to provide valuable
information regarding treatment effect and generalizabil-
ity. Another strength of the body of research reviewed here
is the lack of publication bias as evidenced by the symme-
try of the funnel plots and Egger regression tests. Thus, the
findings do not appear to be influenced by publication bias.
It is worth noting, however, that all of the group design
studies were evaluated as having some concerns for risk of
bias, and most of the SCD studies were evaluated as hav-
ing a high risk, indicating that the reported effects may be
inaccurate.
SCD Meta-Analytic Findings
The LRR effect-size estimates varied substantially
(range: −1.70 to 4.94) across the SCD studies and did not
always align with whether a functional relation was observed
based on visual analysis. A functional relation was only
observed for one of the SCD studies included in the SCD
meta-analysis (Valentino et al., 2015). Notably, the effect-
size estimates for this study (range: 1.15–4.94) were among
the highest of those included in the meta-analysis. These
data would suggest that failure to establish a functional
relation within an SCD study does not necessarily indi-
cate a weak treatment effect. This conclusion should be
interpreted with caution due to the criteria used to deter-
mine whether a functional relation was established. The
What Works Clearinghouse (2014) criteria for establish-
ing a functional relation are dependent on whether there
(a) are at least three demonstrations of effect based on level,
trend, variability, immediacy, overlap, and consistency and
(b) is not a demonstration of a noneffect. It may be the case
that two demonstrations of an effect and one noneffect were
observed in a study, which would result in the determination
that a functional relation was not observed. In this case,
large effect-size estimates may have been observed for the
two demonstrations of effect.
Limitations
As our inclusion criteria were limited to studies con-
ducted in the United States, the findings of this review are
limited in their generalizability to interventions implemented
in other parts of the world. Interventions implemented in
other countries may be qualitatively different due to cultural
norms related to narrative language and/or academic
expectations. For example, some studies reported using
peer collaboration and games to keep students motivated:
This could be reflective of the educational culture found
in the United States. Likewise, five studies reported find-
ings related to interventions incorporating Spanish, which
is the most common language among ELLs in U.S. public
schools (Hussar et al., 2020). It is also possible that inter-
ventions targeting narrative language outcomes may result
in effect sizes different than those found in our meta-analyses.
14 Language, Speech, and Hearing Services in Schools •1–18
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Different effects could be due to language, cultural, or edu-
cation factors that potentially influence the effect of inter-
ventions on narrative language growth (e.g., Westerveld &
Heilmann, 2012). Future research can examine if similar
patterns are found in intervention studies conducted out-
side the United States.
Conclusions
Findings from this corpus of studies suggest that mea-
surable and lasting improvements in macrostructure and mi-
crostructure elements of narrative production can result from
a variety of interventions even when provided with a relatively
small dosage. Common trends found across interventions in-
cluded manualized and/or scripted curriculum, explicit teach-
ing of story grammar, and verbal and visual prompts. These
interventions can be beneficial for children with diverse
learner characteristics, including students who are ELLs
and students without identified disabilities. Given that
narrative retelling and recounting standards are included
in the Common Core, it is likely that implementing in-
terventions aimed to improve narrative language will be
a continuing practice in U.S. schools. A promising finding
from this review is that practitioners outside the specialized
field of speech-language pathology can effectively implement
narrative interventions (e.g., Spencer et al., 2018). Scripted or
manualized curricula support successful implementation
by teachers and paraprofessionals, potentially expanding
the number of students who may benefit from narrative
instruction.
Acknowledgments
Danielle L. Pico, Christine Woods, and Valentina A. Con-
tesse’s work was supported by the U.S. Department of Education,
Office of Special Education Programs (H325D160019). The other
authors have no funding to report.
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