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# Effects of shared text reading for students with intellectual disability: A meta-analytical review of instructional strategies

Rachel Sermier Dessemontet, Megan Geyer, Anne-Laure Linder, Myrto Atzemian, Catherine Martinet, Natalina Meuli, Catherine Audrin,

Anne-Françoise de Chambrier

► To cite this version:

Rachel Sermier Dessemontet, Megan Geyer, Anne-Laure Linder, Myrto Atzemian, Catherine Martinet, et al.. Effects of shared text reading for students with intellectual disability: A meta-analytical review of instructional strategies. Educational Research Review, 2024, 44, 10.1016/j.edurev.2024.100615. hal-04852137

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https://hal.science/hal-04852137v1

Submitted on 20 Dec 2024

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## Review

# Effects of shared text reading for students with intellectual disability: A meta-analytical review of instructional strategies

Rachel Sermier Dessemontet*, Megan Geyer, Anne-Laure Linder, Myrto Atzemian, Catherine Martinet, Natalina Meuli, Catherine Audrin, Anne-Françoise de Chambrier

University of Teacher Education of the State of Vaud, Switzerland

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## ARTICLE INFO

**Keywords:**

Meta-analysis

Intellectual disability

Reading instruction

Shared text reading

Listening comprehension

## ABSTRACT

Although they are an important part of learning to read, listening comprehension skills are often hindered among students with intellectual disability (ID). An increasing number of studies have shown that they can be enhanced through shared text reading interventions. In the current multilevel meta-analysis, we aimed to measure the effect of shared text reading on the listening comprehension skills of students with ID and to identify efficient instructional strategies. The meta-analysis included 19 single-case experimental studies encompassing 67 participants with ID. We found a significant average effect size of shared text reading on the listening comprehension skills of students with ID (log response ratio [LRR] = 1.05, 95% CI [0.87, 1.24]) whether or not they needed alternative or augmentative communication systems to communicate effectively. We found no significant moderator, but instructional strategies backed up by sufficient solid evidence to be considered evidence-based could be identified, with clear implications for practice.

## 1. Introduction

Reading requires the ability to decode texts and understanding their meaning (Castles et al., 2018). Learning to read is especially challenging for students with intellectual disability (ID), who display significant limitations in intellectual functioning and adaptive behavior (American Psychiatric Association, 2013). These last two decades, significant progress has been made in our understanding of instructional practices that allow these students to develop decoding skills and progress toward becoming independent readers (Afacan et al., 2018; Bakken et al., 2021; Sermier Dessemontet et al., 2019). Nevertheless, learning to read short texts independently and sufficiently fluently is a process that can take many years of intensive instruction for most students with moderate or severe ID (Allor et al., 2014). Therefore, in their model of literacy instruction for students with moderate or severe ID, Browder et al. (2008) suggested that there should be two targeted outcomes: increased independence as readers and enhanced quality of life through shared literature. The purpose of this second outcome is to allow students with moderate or severe ID who are not yet able to read texts independently to access age appropriate literature and gather information from texts read aloud to them. Access to age appropriate literature is especially important for their quality of life and social participation because texts are frequently used to convey information in various disciplines of the general education curriculum (e.g., language arts, science, social studies) and in everyday life.

Students with ID who are not yet independent readers may rely on the support of a peer or a teacher who reads a text aloud or on assistive technology. However, reading a text aloud is often not sufficient to guarantee that a student with moderate or severe ID will

<footnote>* Corresponding author. Haute Ecole Pédagogique du Canton de Vaud, Av. De Cour 33, Case postale, 1014, Lausanne, Switzerland. E-mail address: rachel.sermier@hepl.ch (R. Sermier Dessemontet).</footnote>
understand its meaning and gain information from it. Indeed, listening comprehension can be a challenge for students with moderate or severe ID because it requires them to construct meaning thanks to vocabulary, background knowledge, and meta-cognitive strategies (Kim & Pilcher, 2016). Shared text reading, which consists of reading a text aloud to students and engaging them with the text through reader-listener interactions (Browder et al., 2009; Hudson & Test, 2011) has been found to allow for significant progress in typically developing children's (National Early Literacy Panel, 2008) and at-risk children's listening comprehension skills (Towson et al., 2017). It is considered a promising practice to foster access to age appropriate literature among students with ID and help them develop listening comprehension skills regarding texts read aloud to them (Hudson & Test, 2011). However, adaptations are needed to implement shared reading efficiently with students with moderate or severe ID. Indeed, these students often need support to engage with the text and gain meaning from it, for example an adaptation of the texts' content, concrete referents such as objects or pictures of objects to understand the meaning of some concepts or words, repeated readings, prompts, etc. (Browder et al., 2009).

Recently, Gross Toews et al. (2021) extended Hudson and Test's (2011) systematic review to evaluate the evidence base of the effects of shared text reading for students with extensive support needs (i.e., students with intellectual disability, autism, or multiple disabilities). Their review encompassed 31 studies published between 1975 and 2020. They concluded that shared story reading was effective in promoting listening comprehension in students with extensive needs. They observed that more recent studies provided evidence that shared text reading could be used with fictional and nonfictional texts. Moreover, the use of technology, such as e-books, was a strategy with growing support. Although the systematic review by Gross Toews et al. (2021) provides useful information, they could draw no conclusions regarding which instructional characteristics may make shared story reading more efficient. This type of information can only be provided through the calculation of weighted effect sizes and moderator analysis.

Boyle et al. (2019) conducted a meta-analysis to evaluate the effects of shared text reading interventions for children with autism spectrum disorders (ASD) on key early language and literacy skills and engagement. They found 11 single-case experimental studies that met their inclusion criteria published between 2004 and 2017. Their findings suggest that overall, shared reading interventions had a moderate positive impact for students with ASD across all age groups. Studies that evaluated listening comprehension showed a large effect. Because this meta-analysis included only studies including participants with ASD (with and without ID) and because ID impacts comprehension skills, a meta-analysis focusing on students with ID seemed necessary.

The first purpose of this meta-analysis is to offer a more in-depth examination of the instructional strategies that can be used in shared text reading and their effects on the listening comprehension skills of students with ID. Another purpose is to review strategies implemented for students with ID who have complex communication needs (CCN). These students cannot express themselves efficiently with oral language and need alternative and augmentative communication systems to communicate (e.g., communication boards or books, picture exchange communication systems, tablet devices with communication apps). Identifying instructional strategies that can be used to engage students with ID and CCN in literacy instruction could be especially useful given the challenges in teaching them to read. Furthermore, because technology has often been used in recent studies investigating shared text reading, an analysis of the effectiveness of the various ways of exploiting technology is also necessary. More specifically, we investigated the following research questions: (a) What instructional strategies are used in shared text reading interventions with students with ID, and what effects do they have on listening comprehension? (2) What specific adaptations in shared text reading interventions enable students with ID needing alternative and augmentative communication systems to participate in shared text reading instruction? (3) How is technology used in shared text reading interventions for students with ID, and what effects does it have on listening comprehension?

## 2. Method

### 2.1. *Search procedures*

The electronic database searches were conducted using PsycINFO and ERIC. Studies published in English between 2010 and April 2022 in peer reviewed journals were searched. The following descriptors were used: "shared stories," "shared story reading," "story-based lesson," "literacy-based lesson," "read-alouds," "reading aloud," and "storybook reading." All these descriptors were cross-referenced with the following keywords: "intellectual disabilit*," "developmental disabilit*," "mental retardation," "cognitive disabilit*," and "autism." Dissertations were also searched with the same descriptors using ProQuest to minimize the potential publication bias. The reference lists of three systematic reviews on shared story reading for students with disabilities were searched for further records (Boyle et al., 2019; Gross Toews et al., 2021; Snyder et al., 2017). Finally, the reference lists of all documents selected for full-text eligibility screening were searched to identify other possible studies.

### 2.2. *Eligibility criteria*

All records were reviewed for eligibility in two stages: first, at the title and abstract stage and then, if specific criteria were met, at the full-text-eligibility review stage. The following criteria were used to determine eligibility.

* Participants: At least half of the study's participants were described as having an ID or as presenting a syndrome known to be associated with an ID in the large majority of individuals (e.g., Down syndrome). Studies whose participants were described as having ASD with significant limitations in intellectual functioning (IQ < 70) were also included.
*   **Intervention:** The intervention involved shared text reading, defined as reading a text aloud to students and engaging them with the text through reader-listener interactions. We also included studies in which texts were read aloud via assistive technology (e.g., e-books) if it included either an interventionist or technology engaging students with the text (e.g., embedded questions).

*   **Dependent variable:** Listening comprehension was measured in the study.

*   **Design:** The study had either an experimental or quasi-experimental pretest-posttest design with a control group of individuals with ID receiving another type of intervention or business-as-usual instruction, or a single-case experimental design. Experimental single-case studies with AB designs were excluded because they do not provide sufficient experimental control to allow for confirmation of a functional relationship between the manipulation of the independent variable and change in the dependent variable (Horner et al., 2005; Smith, 2012). Moreover, single-case experimental studies had to have at least three measures during each baseline phase and three measures during each intervention phase for all participants (Cook et al., 2014; Smith, 2012).

*   **Data:** Studies had to provide data allowing for calculation of effect size (e.g., in single-case studies, graphed data is displayed for all the measures of the targeted dependent variable for each participant).

### 2.3. Selection of studies for review

The PRISMA flowchart in Fig. 1 illustrates the entire process. After the duplicates were removed, the electronic searches yielded 1,114 records. The examination of references from previous reviews yielded 10 supplementary results. Citation searching in the reports assessed for full-text eligibility yielded 14 results. As a whole, the title and abstracts of the 1,138 records were screened to determine whether the article met the inclusion criteria specified earlier. Of those records, 1,084 were excluded. Interrater reliability between the authors in this screening process was calculated on 30% of the records selected randomly. Interrater agreement for this initial screening was high (98%).

A total of 54 articles were assessed for full-text eligibility independently by two of the authors. Interrater reliability in determining full-text eligibility was 97%. When a disagreement between two authors occurred, the study's inclusion was discussed in group meetings until an agreement was reached. Several articles were excluded because they did not meet the criterion regarding participants' diagnosis (Balsamo, 2019; Fleury & Schwartz, 2017; Gasamis, 2018; Golloher, 2018; Grygas Coogle et al., 2018; Henry & Solari, 2022; Hudson et al., 2017; Jackson & Hanline, 2020; Kang, 2017; Kim et al., 2018; Lo & Shum, 2021; Olszewski et al., 2018; Pamparo, 2012; Phalen, 2020; Piasta et al., 2020; Plattos, 2011; Rivera et al., 2017; Ruppar et al., 2017; Towson et al., 2016; Whalon et al., 2015, 2016, 2019; Williamson et al., 2015; Yorke et al., 2018). Some studies were excluded because shared text reading was not the

<figure><img src="image_5.png" /><figcaption>Fig. 1. PRISMA Flow diagram.</figcaption></figure>
intervention's main component (Douglas et al., 2011; McDuffie et al., 2016, 2018) or because the effects were measured on reading comprehension (texts the students read autonomously) rather than on listening comprehension (Roberts et al., 2019, 2020; Zakas et al., 2013). One study was excluded because it had an AB design (Rivera, 2011). We excluded one study because it provided incomplete visual data (Shurr & Kromer, 2018). A final total of 22 articles were selected for this meta-analysis.

## 2.4. Coding procedure

All 22 studies were coded descriptively. Two authors coded them independently with a coding guide. The interrater reliability between the authors in this coding process was 98%. Discrepancies in coding were discussed and resolved during group meetings. The following elements were coded: (a) research design and type of control/baseline condition, (b) participants (diagnosis, age, IQ, use of AAC), (c) setting (self-contained classroom, inclusive setting, home setting), (d) interventionist (profession, training), (e) instructional format (one to one, small group instruction), (f) duration of the lessons, (g) number of lessons per week, not including maintenance and generalization sessions, and (h) effect intervention. Furthermore, (i) the intervention's instructional characteristics were also coded with the following categories:

* Type of reading comprehension taught: The interventionist taught the students literal and/or inferential comprehension.

* Type of text used: The researchers used narrative and expository (e.g., biographies, science text) texts.

* Adaptations of the text: Adaptations included shortened length, adapted syntax, and simplified wording.

* Enrichment of the text: Images or objects were added to some texts.

* Use of technology: Technology information included type of device and software used, presentation of intervention materials on a computer (i.e., read aloud via assistive technology, presentation of response options on iPad/computer), and incorporation of interactive features to support text comprehension (i.e., embedded corrective feedback, embedded system of least to most prompts, embedded coaches).

* Explicit instruction of text comprehension strategies and type of strategy taught: In an explicit-instruction approach, teachers teach their students specifically and explicitly how to use strategies that help them understand texts (e.g., self-questioning strategy, predicting, summarizing). This approach involves modeling or demonstrating the required skills and providing guided practice with feedback (Rupley et al., 2009).

* Use of systems of prompts vs. no system of prompts: These strategies make use of verbal, visual, or physical prompts that are provided systematically and sequenced to increase or decrease the amount of information/help provided to the student. Their goal is to help students reach the highest level of independent performance (Downing, 2010). The following strategies were coded as systems of prompts: constant time delay (the instructor uses a fixed wait time prior to additional prompting), simultaneous prompting (the instructor guides the student as he makes a demand, leading to errorless learning), least-to-most prompts (the instructor begins with the least supportive/intrusive prompt and provides progressively more supportive/intrusive prompts following wait times and only if the student needs them), and most-to-least prompts (the instructor begins with the most supportive/intrusive prompts and fades them out progressively as the student demonstrates greater efficiency; Downing, 2010).

* Adaptations to allow students who need alternative and augmentative communication systems to participate in shared text reading: Such adaptation included modality of response used.

* Other relevant instructional characteristics were examined (e.g., teaching the meaning of wh-words).

## 2.5. Assessment of the studies' methodological quality

Articles were reviewed to assess the studies' methodological quality using the 22 quality indicators the Council for Exceptional Children (Cook et al., 2014) established for single-case experimental studies. Two authors independently coded each article using these quality indicators. Interrater reliability was high (99% agreement). Discrepancies in coding were discussed and resolved during group meetings.

## 2.6. Effect size estimates

There is no consensus on the effect size that should be calculated in single-case studies and meta-analytical reviews of single-case studies (Jamshidi et al., 2018; Shadish et al., 2015). Yet, Pustejovsky (2018) pointed out that the log response ratio (LRR) is a recommended effect size for single-case studies, notably because this effect size is less sensitive to the experimental design than the nonoverlap of all pairs or the Tau. Two variants of the LRR may be used, depending on the direction of the dependent variable. If the outcome is expected to increase, the LRR increasing will be computed. The LRR is particularly relevant for outcomes that are measured as a ratio. This means that a zero on the scales is equivalent to the absence of outcome. Also, the LRR conceptualizes the effect size in terms of a proportionate change. We believe that this is particularly relevant not only statistically but also practically. Effect sizes were computed on R using the SingleCaseES package (Pustejovsky et al., 2022). The percentage changes were computed on R using the formula Pustejovsky (2018) recommended.

To calculate effect sizes, we first used WebPlot Digitizer to digitize data from the graphs of each study related to the dependent variable targeted in this review. We excluded data collected during a maintenance phase or generalization phases in a few studies to keep as similar as possible measures of the dependent variable among the single-case studies because not all of them involved such supplementary phases for all participants. For the single-case studies by Hudson et al. (2014), Devine (2018), and Mucchetti (2013),
<table><caption>**Table 1**
Shared text reading interventions without technology.</caption><thead><tr><th rowspan="2">Study</th><th rowspan="2">N</th><th colspan="4">Participants</th><th colspan="2">Intervention</th><th colspan="4">Implementation</th><th rowspan="2">Interventionist</th><th rowspan="2">Effect</th></tr><tr><th>Diag.</th><th>Comm.</th><th>IQ</th><th>Age</th><th>Type of text</th><th>Adapted text</th><th>Instructional components</th><th>Format</th><th>N-lessons</th><th>Duration</th><th>Freq.</th></tr></thead><tbody><tr><td>Browder et al. (2011)</td><td>3</td><td>ID</td><td>AAC users</td><td>NR</td><td>6-9</td><td>Narr.</td><td>yes</td><td>LTM Prompting</td><td>1:1</td><td>9-15</td><td>30 min.</td><td>3 x per week</td><td>Teac.</td><td>+</td></tr><tr><td>Cheek et al. (2019)</td><td>3</td><td>ID + ASD</td><td>2 verbal 1 AAC user</td><td>NR</td><td>7-9</td><td>Narr. + Exp.</td><td>no</td><td>Verbal scaffolding</td><td>1:1</td><td>5-15</td><td>15 min.</td><td>NR</td><td>Teac.</td><td>+</td></tr><tr><td>Courtade et al. (2017)</td><td>3</td><td>ID</td><td>verbal</td><td>42-53</td><td>10-12</td><td>Exp.</td><td>yes</td><td>LTM prompting Graphic organizer (Wh-word rules)</td><td>1:1</td><td>12-17</td><td>10-15 min.</td><td>5 x per week</td><td>Res.</td><td>+</td></tr><tr><td>Hudson et al. (2014)</td><td>3</td><td>ID</td><td>2 verbal 1 AAC user</td><td>&lt;55</td><td>NR (≈ 9-11)</td><td>Exp.</td><td>yes</td><td>LTM prompting</td><td>1:1</td><td>12</td><td>NR</td><td>NR</td><td>Peers</td><td>+</td></tr><tr><td>Hudson and Browder (2014)</td><td>3</td><td>ID</td><td>2 verbal 1 AAC user</td><td>51 or NR</td><td>9-11</td><td>Narr.</td><td>yes</td><td>LTM prompting Teaching Wh-words definitions</td><td>1:1</td><td>19-20</td><td>10-15 min.</td><td>3 x per week</td><td>Peers</td><td>Mixed</td></tr><tr><td>Mims et al. (2012)</td><td>4</td><td>ID + ASD</td><td>1 verbal 3 AAC users</td><td>42 or NR</td><td>12-14</td><td>Exp.</td><td>yes</td><td>LTM prompting Teaching Wh-words rules Graphic organizer (text structure + wh-words rules)</td><td>1:1</td><td>15-16</td><td>20 min</td><td>3 x per week</td><td>Res.</td><td>+</td></tr><tr><td>Muchetti (2013)</td><td>4</td><td>ID + ASD</td><td>minimal-ly verbal</td><td>&lt;55</td><td>6-8</td><td>Narr.</td><td>yes</td><td>LTM prompting</td><td>1:1</td><td>4-6</td><td>NR</td><td>NR</td><td>Teac.</td><td>+</td></tr><tr><td>Shurr and Taber-Doughty (2012)</td><td>4</td><td>ID</td><td>2 verbal 1 NR 1 AAC user</td><td>42-54 or NR</td><td>12-15</td><td>Narr. and Exp.</td><td>no</td><td>Pictures plus discussion before and after reading</td><td>NR</td><td>3-12</td><td>NR</td><td>NR</td><td>Res.</td><td>+</td></tr><tr><td>Shurr and Taber-Doughty (2017)</td><td>3</td><td>ID</td><td>verbal</td><td>40 or NR</td><td>18-19</td><td>Exp.</td><td>no</td><td>Pictures plus discussion before and after reading</td><td>1:1</td><td>30</td><td>NR</td><td>NR</td><td>Res. + Peers</td><td>+</td></tr><tr><td>Wood et al. (2015)</td><td>3</td><td>ID</td><td>verbal</td><td>48-51</td><td>10-11</td><td>Exp.</td><td>no</td><td>LTM prompting Self-questioning instruction Graphic organizer (with wh-words)</td><td>1:1</td><td>14-16</td><td>30 min.</td><td>daily</td><td>Teac.</td><td>+</td></tr></tbody></table>

Note. ASD = autism spectrum disorder, AAC = augmentative and alternative communication systems, LTM = least to most, NR = not reported.
<table><caption>**Table 2**
Shared text reading incorporating technology.</caption><thead><tr><th rowspan="2">Study</th><th rowspan="2">N</th><th colspan="4">Participants</th><th colspan="2">Intervention</th><th colspan="2">Use of technology</th><th colspan="4">Implementation</th><th rowspan="2">Interventionist</th><th rowspan="2">Effect</th></tr><tr><th>Diag.</th><th>Comm.</th><th>IQ</th><th>Age</th><th>Type of text</th><th>Adapted text</th><th>Instructional components</th><th>Type</th><th>Role</th><th>For mat</th><th>N- less.</th><th>Durat.</th><th>Freq.</th></tr></thead><tbody><tr><td>Alison et al. (2017)</td><td>3</td><td>ASD</td><td>NR</td><td>51-62</td><td>8-10</td><td>Narr.</td><td>yes</td><td>LTM prompting Teaching Wh-words definitions</td><td>iPad</td><td>Present. material + Interactive Features</td><td>1:1</td><td>9-15</td><td>30 min.</td><td>daily</td><td>Res.</td><td>+</td></tr><tr><td>Browder et al. (2015)</td><td>3</td><td>ASD</td><td>verbal</td><td>58-70</td><td>8-10</td><td>Narr.</td><td>yes</td><td>LTM prompting Teaching story elements + electronic story mapping</td><td>iPad</td><td>Present. material</td><td>1:1</td><td>8-12</td><td>20-30 min.</td><td>daily</td><td>Res.</td><td>+</td></tr><tr><td>Collins et al. (2019)</td><td>3</td><td>ID + ASD</td><td>limited verbal ability</td><td>37-58</td><td>16-21</td><td>Exp.</td><td>yes</td><td>LTM prompting</td><td>iPad/ Computer</td><td>Present. material</td><td>1:1</td><td>7-14</td><td>NR</td><td>NR</td><td>Res.</td><td>+</td></tr><tr><td>Devine (2018)</td><td>4</td><td>ID</td><td>verbal</td><td>NR</td><td>18-27</td><td>Exp.</td><td>yes</td><td>LTM prompting Graphic organizer (Wh-word rules)</td><td>iPad</td><td>Present. material + Interactive Features</td><td>1:1</td><td>9</td><td>15-30 min.</td><td>2-4x per week</td><td>Res.</td><td>+</td></tr><tr><td>Kemp-Inman (2016)</td><td>3</td><td>ID</td><td>verbal</td><td>44-69</td><td>16-18</td><td>Narr.</td><td>yes</td><td>LTM prompting Explicit strategy instruction</td><td>iPad</td><td>Present. material</td><td>1:1</td><td>NR</td><td>NR</td><td>3-4x per week</td><td>Res.</td><td>+</td></tr><tr><td>Knight et al. (2015)</td><td>4</td><td>ID + ASD</td><td>verbal</td><td>53-67</td><td>11-14</td><td>Exp.</td><td>yes</td><td>Explicit strategy instruction Model-Lead-Test approach</td><td>Computer</td><td>Present. material + Interactive Features</td><td>1:1</td><td>9-15</td><td>10-30 min.</td><td>NR</td><td>Res.</td><td>+</td></tr><tr><td>Knight et al. (2018)</td><td>4</td><td>ID</td><td>verbal</td><td>41-55</td><td>18-21</td><td>Exp.</td><td>yes</td><td>Model-Lead-Test approach</td><td>Computer</td><td>Present. material + Interactive Features</td><td>1:1</td><td>8-11</td><td>20-30 min.</td><td>3-4x per week</td><td>Teac.</td><td>+</td></tr><tr><td>Leigh Haughney (2018)</td><td>4</td><td>ID (3: ID + ASD)</td><td>AAC users</td><td>40-50</td><td>17-20</td><td>Exp.</td><td>yes</td><td>LTM prompting Teaching Wh-words definitions</td><td>Computer</td><td>Present. material</td><td>1:1</td><td>5-28</td><td>NR</td><td>4x per week</td><td>Res.</td><td>+</td></tr><tr><td>Nasir-Tucktuck (2017)</td><td>6</td><td>ID (3: ID + ASD)</td><td>verbal</td><td>NR</td><td>NR (K - 2nd gr.)</td><td>Narr.</td><td>yes</td><td>LTM prompting</td><td>Computer</td><td>Present. material</td><td>1:1</td><td>4-14</td><td>8-10 min.</td><td>5x per week</td><td>Res.</td><td>+</td></tr><tr><td>Spooner et al. (2014)</td><td>4</td><td>ASD</td><td>AAC users</td><td>49-61</td><td>8-12</td><td>Narr.</td><td>yes</td><td>LTM prompting</td><td>iPad</td><td>Present. material</td><td>1:1</td><td>9-19</td><td>NR</td><td>NR</td><td>Res.</td><td>+</td></tr><tr><td>Spooner et al. (2015)</td><td>5</td><td>ID (3: ID + ASD)</td><td>AAC users</td><td>47-50or NR</td><td>7-11</td><td>Narr.</td><td>yes</td><td>LTM prompting</td><td>iPad</td><td>Present. material + Interactive Features</td><td>1:1</td><td>4-8</td><td>15 min.</td><td>NR</td><td>Res.</td><td>+</td></tr><tr><td>Wood et al. (2020)</td><td>3</td><td>ID</td><td>verbal</td><td>NR</td><td>8-11</td><td>Exp.</td><td>no</td><td>LTM prompting Self-questioning instruction Graphic organizer (Wh-words)</td><td>iPad/ Comp.</td><td>Present. material</td><td>1:1</td><td>16-17</td><td>NR</td><td>daily</td><td>Teac.</td><td>+</td></tr></tbody></table>

Note. ASD = autism spectrum disorder, ELL = English-Language Learners, AAC = augmentative and alternative communication systems, LTM = least to most, NR = not reported.
we did not take into account points related to intermittent baseline probe sessions occurring during the intervention phase. To ensure homogeneity between studies, regarding Hudson and Browder's (2014) single-case study, we only included data regarding independent correct responses (and not prompted correct responses). For one study with a multiple baseline across participants with embedded alternating treatment design (ABCD) (Knight et al., 2015), we treated Phases B, C, and D as one intervention phase because the intervention in those phases was similar with a progressively growing intensity in the instructional strategies used.

Two authors visually checked all the digitized data independently. For standardization purposes, in the studies providing raw outcome scores, the data was converted to the percentage of correct answers. Next, we calculated the effect sizes for each targeted dependent variable of each study using R.

Effect sizes could not be calculated for three studies, which were therefore not included in the meta-analytical analysis (Shurr & Taber-Doughty, 2017; Spooner et al., 2014, 2015). Indeed, an LRR effect size was technically impossible to calculate for Shurr and Taber-Doughty's (2017) study because two participants had a score of 0 on all measures in all baseline phases (multiple baseline across texts design). In the two studies by Spooner et al. (2014, 2015), graphs displayed cumulative scores of correct responses per session (with only two questions per session), in contrast to all other studies included in this meta-analysis. Moreover, researchers stopped the listening comprehension intervention as soon as the mastery criteria was reached on a different variable (conventions of reading knowledge). The effect size for these studies would have been neither comparable to those of other studies nor representative of the listening comprehension intervention's efficacy.

## 2.7. Meta-analytical analysis

Preliminary analyses were conducted prior to meta-analytical analysis. A Grubbs test conducted with the outlier package (Komsta, 2022) revealed no outlier ($G = 2.28, p = .13$). Influence analyses were also conducted (Viechtbauer & Cheung, 2010). They showed that the effect sizes were normally distributed, except in the study by Browder et al. (2015), which showed high values on all the indices measuring influence. Because this study was not identified as an outlier and had high methodological quality, it was kept in the meta-analysis. A multilevel model meta-analysis was chosen because our meta-analysis included studies displaying several differences that could affect effect sizes (Jamshidi et al., 2022). Based on Pustejovsky and Tipton's (2022) recommendations, we used robust variance estimation when conducting the summary effect size analysis, heterogeneity test, and moderator analyses. They not only allowed us to capture the type of data structure in the best way but also to improve the efficiency of meta-regression estimates (Pustejovsky & Tipton, 2022). Moreover, robust variance estimation allows for an adjustment of the variance and degrees of freedom for meta-analyses comprising a small number of studies (Tipton, 2015; Tipton & Pustejovsky, 2015). Because our data had a hierarchical structure (i.e., lower-level observations nested within higher-level groupings), we computed a hierarchical effects model using the ClubSandwich (Pustejovsky, 2022) and robumeta (Fisher & Tipton, 2015) packages. We used these packages to conduct the summary effect size analysis, heterogeneity test, and moderator analyses. The remaining analyses (influence analyses, publication bias analyses) were conducted using the metafor package (Viechtbauer & Cheung, 2010). Because neither of these analyses can be conducted on multilevel data, we conducted them on the aggregated effect size of each study.

# 3. Results

## 3.1. General description of the studies

Tables 1 and 2 present the detailed content of the studies regarding participants' characteristics, instructional strategies, and interventions' effects. The latter focuses on studies in which the shared story reading intervention included the use of technology.

### 3.1.1. Research design

We found no group study. All 22 studies were single-case experimental studies. The majority of them had a multiple-baseline-across-participants design. One had a multiple-baseline-across-conditions (different texts) design (Shurr & Taber-Doughty, 2017) and another a multiple-baseline-across-participants-with-embedded-alternating-treatment design: ABCD (Knight et al., 2015).

In most studies, instruction during baseline conditions consisted of providing a read aloud and asking comprehension questions but without using the main instructional strategies (e.g., prompting strategies and corrective feedback). In two studies (Hudson & Browder, 2014; Hudson et al., 2014), the baseline condition consisted of providing shared story reading, similarly as planned in the intervention but using prompting strategies and providing corrective feedback only when the student asked for help. In two studies, the baseline condition consisted of business-as-usual shared story reading before training teachers to implement the intervention (Cheek et al., 2019; Mucchetti, 2013).

### 3.1.2. Participants

The review comprises 79 participants with ID (of which 67 included in the meta-analytic analyses). In almost half of the studies (46%), most of the participants had not only an ID but also ASD. In eight studies, some of the participants had associated impairments, such as cerebral palsy, severe physical disability, hearing or visual impairment, and ADHD. A total of 30 students (40% of the participants) were described as minimally verbal and/or using augmentative and alternative communication systems to communicate (of which 21 included in the meta-analyses).

Participants had IQs ranging from 37 to 70. IQ was not reported for a third of the participants, making it difficult to assess the severity of the limitations in intellectual functioning precisely among the participants included in this review. Nevertheless, half of the
participants had an IQ below 55. Adaptive behavior scores were seldom reported. Fourteen studies were conducted with a majority of students who were 6–12 years old. In eight studies, participants were mainly teenagers and/or young adults (13–27 years old). Participants’ oral language comprehension was seldom measured with standardized instruments and described precisely.

### 3.1.3. Dependent variables

In two thirds of the studies, the effect of shared text reading was measured on literal comprehension only. A third of them also assessed inferential comprehension (Cheek et al., 2019; Hudson & Browder, 2014; Hudson et al., 2014; Kemp-Inman, 2016; Knight et al., 2018; Spooner et al., 2014; Wood et al., 2015). In most studies, when asked questions, students were provided multiple choice answers (three to six choices). In these studies, students could answer nonverbally by pointing to images and/or words or sentences read aloud, independently of them being described as verbal or nonverbal. A verbal answer was required in only four studies (Browder et al., 2015; Shurr & Taber-Doughty, 2017; Wood et al., 2015, 2020).

In some studies, the researchers also measured the intervention's effects on other components taught in the intervention, such as the meaning of wh-words (Alison et al., 2017), the meaning of words describing story elements (e.g., characters, location; Browder et al., 2015), and self-questioning (Wood et al., 2020). Some researchers measured reading conventions (e.g., ability to position the book in the right direction, turn the pages, touch the title, touch the author's name) and vocabulary (composite score) in two studies (Spooner et al., 2014, 2015).

### 3.1.4. Implementation of the interventions

In 14 studies, a researcher implemented the intervention. In six of them, a special education teacher implemented it and in two, a peer without disability. In most studies, the intervention was implemented daily or three to four times per week. Several studies did not report the frequency of lessons per week. Depending on the studies, lessons lasted between 10 and 30 min. However, the researchers did not systematically report lesson duration. The intervention phase comprised 3 to 30 lessons, depending on the study (not including maintenance and generalization sessions).

### 3.1.5. Types of texts used

In nine studies, the researchers used narrative texts or books for shared story reading. In 11 studies, the researchers used expository texts, such as science texts (e.g., Hudson et al., 2014; Knight et al., 2015, 2018), biographies (e.g., Mims et al., 2012), social studies texts (e.g., Courtade et al., 2017; Wood et al., 2015), news (e.g., Leigh Haughney, 2018; Shurr & Taber-Doughty, 2017), and an employee handbook (e.g., Devine, 2018; Shurr & Taber-Doughty, 2017). Two studies included both types of texts (Cheek et al., 2019; Shurr & Taber-Doughty, 2017).

In most of the studies, the researchers adapted age appropriate texts to make them more accessible to students with ID. In only five studies did the researchers not adapt the texts' content (Cheek et al., 2019; Shurr & Taber-Doughty, 2012, 2017; Wood et al., 2015, 2020). The most commonly used adaptation was to summarize the original text by keeping only the key elements and rewriting it at a lower reading level. Some researchers also enriched the text with pictures (Devine, 2018; Knight et al., 2015, 2018; Mims et al., 2012; Nasir-Tucktuck, 2017) and introduced a repeated storyline (Courtade et al., 2017). Others added a definition for important vocabulary words (Hudson & Browder, 2014; Hudson et al., 2014). In two studies, researchers also provided verbal scaffolding during the read aloud to improve students' understanding of the text (e.g., making connections with events in previous chapters, making connections with students personal experience or background knowledge; Leigh Haughney, 2018; Kemp-Inman, 2016).

### 3.1.6. The studies' methodological quality

According to the Council for Exceptional Children standards (Cook et al., 2014), studies must meet all 22 quality indicators to be classified as methodologically sound. In a few studies, fidelity of implementation was reported as a whole (average percent) but not for each interventionist separately, as one of the quality indicators specified. Taking into account the high average percentage of implementation fidelity reported in these studies (93%–100%), we believe that intervention was implemented with fidelity (main quality criteria). These studies were therefore classified as methodologically sound. Most of the studies included in this review met all 22 quality indicators and were considered methodologically sound. Of the included studies, two did not meet entirely one of the quality indicators related to internal validity because the participants could have partial access to one of the intervention's instructional strategy (prompts) during the baseline if they asked for help spontaneously (Hudson & Browder, 2014; Hudson et al., 2014). These two studies were kept in the meta-analytical analyses since this threat to internal validity was judged as feeble.

### 3.1.7. Effects of the interventions' effects

Tables 1 and 2 describe the interventions' effects as positive, neutral, mixed, or negative based on the Council for Exceptional Children's recommendations (Cook et al., 2014). A single-case experimental study was considered to have a positive effect when the visual analysis highlighted a functional relationship between the independent and dependent variables, resulting in a meaningful change in the dependent variable for at least three fourths of the participants. In most of the studies, a positive effect was observed. In only one study, the intervention's effect on students' independent responses was mixed (Hudson & Browder, 2014). Interobserver agreement in the visual analysis to determine the nature of the effect for each study was high (100%).

## 3.2. Average effect of shared text reading interventions on listening comprehension

We used robust variance estimation to compute the random-effects average effect size in the 19 studies. A significant and large
<figure><img src="image_6.png" /><figcaption>Fig. 2. Forest plot.</figcaption></figure>
average effect size of shared text reading on the listening comprehension skills of students with ID was found: LRR = 1.05 (SE = .09), 95% CI [0.87, 1.24], t(16) = 11.9, *p* < .01. LRR can be converted to a percentage of increase using the following formula: 100% × [exp (LRR) - 1] (Pustejovsky, 2018). In our case, this means that the intervention led to a change of 185.77% [CI: 138.0, 245.5] in students' ability to answer comprehension questions. This result indicates that shared text reading incorporating varied instructional strategies improves the listening comprehension skills of students with ID. Fig. 2 (forest plot) shows the effect sizes (squares), the 95% CI for each effect size (horizontal bar for each square), the weight of each effect size (size of the square), and the overall average effect size (diamond at the bottom of the figure).

Note that we conducted a moderator analysis to investigate the potential impact of participants having complex communication needs on shared text reading's effect to determine whether this variable had to be controlled for in the further analysis of the effects of instructional strategies. We found no significant difference in the intervention's effect size between participants who could not communicate effectively verbally and those who could ($t(9.8) = -1.01, p = .992$).

A heterogeneity test shows that there is a significant heterogeneity in effect sizes across the studies: $I^2 = 80.09$. Almost 80% of the total variability among effect sizes was caused by true heterogeneity between studies, indicating that investigating moderator variables was important. We also conducted a sensitivity analysis to determine whether the random-effects average effect size, standard error, and variance component estimates changed if a different value for within-study correlation had been used. The estimates for the standard error (0.09) did not change between the lowest ($\rho = 0$) and highest possible correlation ($\rho = 1$). The average effect size and variance component were similar for $\rho = 0$ and $\rho = 1$ (LRR = 1.05 and $\tau^2 = 0.23$), showing that our findings are robust.

### 3.3. Instructional strategies used in shared text reading interventions and their effects

#### 3.3.1. Using a least to most system of prompts to help students answer comprehension questions

In 17 studies, the intervention incorporated a system of least-to-most prompts to help students answer listening comprehension questions in the case of a false response or absence of response. Before each level of prompting, the teacher waited for a fixed number of seconds (constant time delay) before giving assistance (e.g., 5 s). The comprehension question was asked again after each prompt. The hierarchy and type of prompts used to help students answer literal comprehension questions differed among studies, ranging from two to four of these prompts: (a) rereading the page or passage of the text containing the answer, (b) rereading the sentence containing the answer, (c) modeling the correct response by telling and either simultaneously showing the correct answer or showing it in a subsequent prompt, and (d) using physical guidance to help the student select the correct response.

In several studies, one of the first prompts was to remind the student to use a strategy they had been taught: asking for help when they do not know the answer (Hudson & Browder, 2014; Spooner et al., 2015), using a story map as a support (Browder et al., 2015), or explaining/remembering the rule to answer the type of wh-question asked, with the help of a graphic organizer (Courtade et al., 2017; Devine, 2018; Hudson & Browder, 2014; Leigh Haughney, 2018; Mims et al., 2012). In one study including inferential questions, the hierarchy of prompts was slightly different: (a) rereading the text, (b) prompting to use the inferential strategy (e.g., think about their experience), (c) modeling the use of the inferential strategy by talking aloud, and (d) modeling the correct response by telling and/or showing it (Hudson et al., 2014).

<figure><img src="image_7.png" /><figcaption>Fig. 3. Funnel plot.</figcaption></figure>
### 3.3.2. Explicit instruction regarding text comprehension strategies

The researchers explicitly taught the students to use text comprehension strategies in five studies. Wood et al. (2015, 2020) taught students to use a self-questioning strategy with the help of a graphic organizer with wh-words before reading expository texts (social sciences or science texts). Wood et al. (2015) also taught students to determine whether the answer to a question was in the text by raising a small red stop sign if they heard the answer during the read aloud and circling responses to questions on a monitoring sheet including pictures for "in the book," "not in the book," and "I don't know." In contrast, Wood et al. (2020) taught students to determine whether they already knew the answer to a question after the first read aloud or if they needed to find it in the e-text. As a first prompt, they modeled locating topic words from the question in the e-text and replaying three sentences.

Knight et al. (2015) embedded iCoaches in an iBook that prompted students to predict, question, and summarize passages of a text. Browder et al. (2015) taught students to identify narrative texts' main story elements with a problem-solution structure by teaching definitions of story elements (characters, setting, problem, solution, outcome) and teaching students to complete a graphic organizer with these elements after the read aloud and before answering comprehension questions. Finally, Kemp-Inman (2016) taught students to answer higher-order discussion questions (e.g., inferential or applied) with a model-lead-test approach. In the "model" phase, the experimenter demonstrated a think aloud of the process of deducing the correct answer.

### 3.3.3. Instruction regarding wh- words

In several studies, the researchers taught students to answer questions with wh-words by teaching them their definition prior to shared story reading with a graphic organizer or chart with pictures illustrating wh-words. The instructional strategies varied slightly among studies. Alison et al. (2017) taught students to match wh-words with their definitions and examples of words, using a constant time delay. Leigh Haughney (2018) first trained students to sort pictures of people, things, places, and times on a graphic chart with wh-words and then words included in sentences read aloud to them. Hudson and Browder (2014) used examples and counterexamples and trained students to identify wh-words.

Courtade et al. (2017), Devine (2018), and Mims et al. (2012) also taught students rules to answer "why" questions using a graphic organizer (e.g., what: listen for a thing) as the first prompt in a least-to-most prompting strategy if the student was unable to answer a comprehension question correctly. Finally, Wood et al. (2015, 2020) taught students to generate questions about a text with wh-words illustrated in a graphic organizer.

### 3.3.4. Other instructional strategies

Some studies included instruction on reading conventions in the intervention (identifying a text's title, turning a page in the book or iBook, etc.) using a fixed time delay (e.g., Spooner et al., 2014, 2015) and teaching key vocabulary words in texts using examples and counterexamples (e.g., Spooner et al., 2014, 2015). Shurr and Taber-Doughty (2012, 2017) used an intervention called "pictures-plus discussion" with teenagers and young adults. It consisted of showing a set of photos of the text's key elements before reading a text aloud to activate students' background knowledge and allow students to connect their personal perspective to the photos. The interventionist describes each picture's most central components. After the read aloud, the photos are reviewed as they are related to the text in an interactive discussion. Cheek et al. (2019) trained teachers to interact more efficiently with their students during shared story reading using the CAR model and wait time (Comment and wait, Ask questions and wait, Respond and add a little more). More specifically, the researchers encouraged teachers to use five types of questions during shared story reading: completion prompts, recall questions, open-ended questions, wh-questions, and distancing prompts.

### 3.3.5. Results of the moderator analysis

We tested the impact of specific instructional strategies on the effect size of shared text reading, using a system of least to most intrusive prompts to help students answer comprehension questions ($t(5.8) = 0.10, p = .924$), explicit instruction of text comprehension strategies ($t(6.5) = 1.32, p = .232$), and teaching the meaning of wh-words ($t(10.5) = 0.10, p = .921$). No single instructional strategy is a significant moderator of the effect size.

### 3.4. Strategies used with students who cannot communicate effectively verbally

Of the students included in this review, 30 were AAC users or minimally verbal ($n = 21$ in the meta-analytical analyses). In all studies conducted with such students, materials allowing them to answer questions by pointing to or selecting the right answer among multiple choices were provided. Depending on the study, the multiple symbols or pictures were presented on various supports, such as printed cards, communication boards, or an iPad or laptop screen. One student with severe ID and severe motor disability (ataxic quadriplegy) indicated his answers with his gaze (Browder et al., 2011). Two students with severe ID and either a severe motor disability (spastic quadriplegy) or severe vision impairment pointed to or selected objects (Browder et al., 2011). The only exception was the study by Cheek et al. (2019), in which they asked the participant who was an AAC user to point to his answers in the original book's illustrations rather than in a multiple choice answer format. It is interesting to note that in several studies, the researchers also offered this nonverbal response mode (pointing among multiple choices) to verbal students (e.g., Hudson & Browder, 2014; Hudson et al., 2014; Shurr & Taber-Doughty, 2012).

In four studies (Browder et al., 2011; Mucchetti, 2013; Spooner et al., 2014, 2015) the researchers also used strategies to engage students with AAC in interacting physically with the text during shared text reading. Browder et al. (2011) and Mucchetti (2013) prompted students to interact physically with objects or pictures added to the text (e.g., "Feel the hat. That is what I will be reading about," "Find the baseball (picture) in the text") or with the printed words in the text (e.g., "Point to the title") and to fill in story lines
with voice output devices or by pointing to objects, pictures, or symbols.

## 3.5. Use of technology in shared text reading interventions

### 3.5.1. Type of technology used

Several studies (n = 12) included some form of technology in their interventions. In some studies (n = 7), the researchers used technology only to present intervention materials. Some of these interventions used an electronic format to present the text and read it aloud via an audio recording or text to speech (n = 6; Collins et al., 2019; Kemp-Inman, 2016; Leigh Haughney, 2018; Nasir-Tucktuck, 2017; Spooner et al., 2014; Wood et al., 2020) and/or as a material support to allow students to give their answers (n = 7; Browder et al., 2015; Collins et al., 2019; Kemp-Inman, 2016; Leigh Haughney, 2018; Nasir-Tucktuck, 2017; Spooner et al., 2014; Wood et al., 2020).

In contrast, in other studies (n = 5), the researchers delivered instruction through interactive features, giving technology a more central role in instruction. In two studies (Knight et al., 2015, 2018), the researchers used software that integrated hyperlinks to vocabulary definitions and embedded coaches in the e-text that provided explicit prompting to teach vocabulary words. In other studies (Alison et al., 2017; Devine, 2018; Spooner et al., 2015), technology guided probe sessions and provided corrective feedback or incorporated a system of least to most prompts to reorient students after incorrect responses.

### 3.5.2. Results of the moderator analysis

We tested the impact of these three uses of technology on the effect size of shared text reading. The result does not show a significant impact of the use of technology for the read aloud ($t(3.7) = -0.03, p = .975$), as a response mode ($t(3.9) = -0.49, p = .648$), or as a support for interactive instruction ($t(4.2) = 0.19, p = .857$). These results suggest that studies using technology in these three ways in their intervention did not yield larger or smaller effect sizes than studies that did not include technology for these purposes. However, our findings regarding the use of technology for the read aloud or as a response mode must be considered with caution because the degree of freedom is slightly less than 4, suggesting that it may be unreliable (Tipton, 2015).

## 3.6. Publication bias analyses

Publication bias stems from the fact that studies reporting nonsignificant effects tend to have a lower probability of being published. To diminish this bias in our meta-analysis, we decided to include dissertations and unpublished work by contacting the researchers. However, we still wanted to control for publication bias in our results. Therefore, we provide below a funnel plot and a trim and fill analysis. The funnel plot reports the effect sizes of the studies in our meta-analysis as filled circles (x-axis) and relates them with their variance (y-axis). If we found no publication bias, the studies should be distributed symmetrically around the average effect size, which seem to be approximately the case in our data. The trim and fill analysis suggests that for symmetry to be reached, one supplementary study should be added. This study is depicted in the funnel plot as an open circle. The trim and fill analysis reveals that adding this supplementary study would lead to an LRR of 1.02, which is close to our estimated LRR (1.05).

# 4. Discussion

We conducted the meta-analysis to measure the effect of shared text reading on the listening comprehension skills of students with ID and to review the instructional strategies used. We found a significant average effect size on the basis of 19 single-case studies encompassing 67 participants. This is evidence that shared text reading enhances the listening comprehension skills of students with ID. This finding aligns with the findings from the meta-analysis Boyle et al. (2019) conducted on the effect of shared story reading on the literacy skills of students with ASD. In the current meta-analysis, we found shared text reading has a positive effect whether these students could express themselves orally or needed AAC systems. According to the Council for Exceptional Children's criteria (Cook et al., 2014), shared text reading can be considered an evidence-based practice because it is supported by 20 methodologically sound single-case experimental studies, all documenting a positive effect for at least three fourths of the participants. More globally, a positive effect varying in strength from small to large was observed for the majority of the participants of the 20 methodologically sound studies (70/73).

Two axes of intervention can be identified. A first one consists in adapting age-appropriate narrative and expository texts to make them more accessible to students with ID, whatever the severity of their limitations. Indeed, researchers shortened and simplified texts in most of the studies, which suggests that it is an important instructional component for success in shared text reading for students with ID. A second axis encompasses instructional strategies that help students with ID improve their listening comprehension skills by acquiring new knowledge (e.g., the meaning of wh-words) or new strategies that contribute to helping them become more autonomous when asked comprehension questions about a text read aloud to them. These strategies are discussed in the following section.

### 4.1. What instructional strategies can be considered evidence based?

The statistical analyses revealed no significant moderator regarding the instructional strategies even though robust variance estimation was used (Pustejovsky & Tipton, 2022; Tipton, 2015; Tipton & Pustejovsky, 2015). This absence of a significant moderator might be explained by the small number of studies included in this meta-analysis and by the fact that they often included a combination of strategies. For example, the researchers used the least-to-most intrusive prompting strategy to help students answer comprehension
questions in most of the included studies. The limitation in evaluating strategies in intervention packages is that without a sufficient number of component analyses, the impact of each individual strategy in isolation is difficult to identify. However, the absence of a significant moderator should not obscure the fact that many studies included read aloud of an adapted text and questions without any instructional strategies during the baseline conditions and that little or no progress in answering listening comprehension questions was found under those conditions. In contrast, progress was observed in students' ability to answer comprehension questions independently (without prompts) once specific instructional strategies were implemented. Therefore, we can conclude that shared text reading enhanced with specific instructional strategies produces positive effects.

According to the Council for Exceptional Children criteria (Cook et al., 2014), an intervention can be considered evidence based when it is supported by at least five methodologically sound single-case experimental studies with positive effects and at least 20 participants across studies. Therefore, two instructional strategies can be identified as evidence based: (a) least to most intrusive prompts (including rereads and often reminders of the strategy taught) to help students answer comprehension questions (supported by 15 studies) and (b) teaching the meaning of wh-words (supported by seven studies). Teaching comprehension strategies explicitly can be considered potentially evidence based because it is supported by five methodologically sound studies with positive effects but encompassing fewer than 20 participants across studies.

According to the Council for Exceptional Children criteria (Cook et al., 2014), the picture-plus-discussion approach Shurr and Taber-Doughty (2012, 2017) used can also be considered potentially evidence based with teenagers and adults because it is supported by two methodologically sound studies documenting positive effects. However, in another study conducted on this intervention's efficacy with younger participants (7–8-year-old children; Shurr & Kromer, 2018), a study excluded from this review due to missing data for one of the dependent variables, the effect was neutral. This approach may perhaps not provide sufficient scaffolding to support the development of listening comprehension skills in younger students.

The results of this meta-analysis highlight that technology was used in several studies for the read aloud and/or to provide the students response options. In a few studies, technology partly or completely replaced the teacher by proving modeling, prompting, or feedback. These three uses of technology for shared text reading can be considered backed up by sufficiently solid evidence because they are supported by six, seven, and five methodologically sound studies, respectively, with positive effects from at least 20 participants across studies. This result is consistent with the results of recent meta-analyses on technology's efficacy in teaching reading (Kim et al., 2021) and other academic skills (Aspiranti et al., 2020) to children with autism.

Other findings that are useful for practice can be noted. The researchers adapted the texts in most of the studies. Only five studies included original texts without adaptations (Cheek et al., 2019; Shurr & Taber-Doughty, 2012, 2017; Wood et al., 2015, 2020). Their results highlight positive effects if instruction incorporates several strategies to facilitate students' understanding (e.g., showing pictures of words, providing definitions, stimulating students' reflections and interactions before or during the read aloud). The strategies that might render grade-aligned original texts (rather than adapted texts) accessible for students with ID could be further investigated. Moreover, in many studies, students were provided multiple possible answers with a visual support when asked comprehension questions, even those who were verbal. Such a visual support might be an interesting source of help for multiple students in terms of oral expression or memory. Finally, it is also worth pointing out that in one third of the studies, students were trained to respond to inferential questions, not only to literal questions. This training reflects a growing educational ambition for these students, particularly a growing concern for their general knowledge and reasoning, rather than the limitation to functional reading for daily needs that has prevailed for a long time (Rohena-Diaz & Browder, 1996).

## 4.2. Do listening comprehension skills generalize to new texts ?

Seven studies showed that the intervention allowed students to generalize their comprehension skills to untrained texts, since each probe during intervention phase was conducted with an untrained text and measured students' ability to answer independently comprehension questions without prompts (Browder et al., 2015; Collins et al., 2019; Knight et al., 2015, 2018; Leigh Haughney, 2018; Shurr & Taber-Doughty, 2017; Spooner et al., 2015). In five supplementary studies, researchers reported using a large number of texts during intervention, but it was not stated explicitly if probes were conducted each time with an untrained text, even if it can be tentatively presumed to be so (Alison et al., 2017; Kemp-Inman, 2016; Shurr & Taber-Doughty, 2012; Wood et al., 2015, 2020).

In other studies, three to five texts were used during intervention phase and a first probe took place with each text, measuring students' ability to answer independently comprehension questions on an untrained text (Devine, 2018; Hudson et al., 2014; Mims et al., 2012; Muchetti, 2013; Spooner et al., 2014). In these studies texts were trained two to four times during intervention phase. These studies also reveal to some extent the generalization of comprehension skills to new texts or more precisely a progressive diminished need of help (i.e., prompts) when asked comprehension question about a text read aloud to them. The value of this type of effect, even if it mixes effect on untrained and trained texts, should not be underestimated, since providing access and understanding of an age-appropriate text with valuable content is a worthy outcome for students with ID even if texts must be read and trained a few times.

## 4.3. Limitations

Some limitations of the present meta-analysis must be taken into account. First, additional studies are required to draw precise conclusions on which instructional strategies are the most efficient to allow students with ID to generalize new comprehension skills to untrained texts. Second, the small number of studies included in this meta-analysis, their small sample sizes, and the often incomplete information on participants (e.g., IQ, adaptive behavior scores, oral comprehension skills) precluded an examination of the potential
interaction effects of different moderators with more complex statistical analyses. More studies are clearly needed to refine our un-
derstanding of the instructional strategies that can render shared text reading the most effective for students with ID with different
profiles, for example depending on their age, severity of limitations or level of oral language comprehension. Third, despite the
reassuring findings from the publication bias analyses, a publication bias could still have inflated the positive average effect size found.

4.4. Conclusion and further perspectives

In sum, we found shared story reading enriched with several instructional strategies enhances the listening comprehension skills of children with ID, including those with CCN. Researchers could continue to identify instructional strategies that render this practice more effective, especially in teaching more complex comprehension skills, such as inference skills, predicting, summarizing, and self-questioning. Furthermore, more studies with teachers implementing the intervention are necessary because this was done in only a quarter of the studies. Additional studies with teachers as implementers would strengthen the social validity of shared text reading. Also, increasing the evidence regarding interventions that can be taught to teachers during in-service training and that they can easily implement is crucial because the quality of literacy instruction provided to these students is often poor (Ahlgrim-Delzell & Rivera, 2015; Lindström & Lemons, 2021; Ruppar, 2017; Sermier Dessemontet et al., 2022). Assessing training's impact on teachers' practices in addition to interventions' impact on students' progress would be especially helpful to enhance the quality of literacy instruction provided to these students.

Author statement

RSD, AFC and CM conceived the study and obtained funding. RSD supervised and managed the project. RSD, AFC, CM, ALL, MA, NM and MG contributed to all the phases of the meta-analysis (e.g. screening, descriptive coding of the studies, assessment of the study's quality) and to the methodological and conceptual choices involved during the process. RSD and MG managed the data extraction, preparation and verification. CA managed the statistical analyses. RSD wrote the major part of the first draft of the manuscript with contributions from AFC, MG and CA. All authors provided critical feedback and helped shape the final version of the manuscript.

Declaration of competing interest

The Swiss National Science Foundation research grant SNF no 100019_192562 provided funding for this study. All authors declare
that they have no conflicts of interest.

Data availability

Data are available from: https://zenodo.org/records/10566318

Acknowledgment

We thank the anonymous reviewers for their constructive comments that helped us improve the manuscript.

References

References marked with an asterisk indicate studies included in the meta-analysis.

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