Edited by: McNeel Gordon Jantzen, Western Washington University, USA
Reviewed by: Virginia Penhune, Concordia University, Canada; Franziska Degé, Justus-Liebig-University, Germany
*Correspondence: Reyna L. Gordon
This article was submitted to Auditory Cognitive Neuroscience, a section of the journal Frontiers in Psychology
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Children's engagement in music practice is associated with enhancements in literacy-related language skills, as demonstrated by multiple reports of correlation across these two domains. Training studies have tested whether engaging in music training directly transfers benefit to children's literacy skill development. Results of such studies, however, are mixed. Interpretation of these mixed results is made more complex by the fact that a wide range of literacy-related outcome measures are used across these studies. Here, we address these challenges via a meta-analytic approach. A comprehensive literature review of peer-reviewed music training studies was built around key criteria needed to test the direct transfer hypothesis, including: (a) inclusion of music training vs. control groups; (b) inclusion of pre- vs. post-comparison measures, and (c) indication that reading instruction was held constant across groups. Thirteen studies were identified (
Acquiring fluency in reading requires children to transform symbolic information provided by print into mental representations based on their prior language experience. This literacy acquisition relies heavily on the process of phonological awareness. In particular, children's ability to focus their attention on sub-syllabic phonological units within words is a critical factor for mastering the early challenge of alphabetic decoding. Phonological awareness has also been linked to neural mechanisms that help explain individual differences in early literacy (Schlaggar and McCandliss,
Understanding the potential connection between music training and literacy skills is informed by two areas of research literature. The first is a well-established body of research showing that some language-related skills, such as phonological awareness, are a fundamental pre-cursor of reading skills (see meta-analysis by Melby-Lervag et al.,
A rapidly accumulating body of evidence has shown associations between language and music skills in children. For instance, 7-to-9-year-old musicians outperformed their non-musician peers at detecting small prosodic (pitch) incongruities in sentences (Magne et al.,
Reading is one language skill that has received recent attention in the neuroscience community regarding potential shared neural resources with music. Anvari et al. (
The relation between rhythm and reading-related skills continues to be significant in later stages of language development. Tierney and Kraus (
If enhanced language skills and musical skills are correlated, then would individuals with language disorders also have deficits in musical processing? Research on reading disabilities and language impairment suggests that this is often the case (e.g., Goswami,
Correlational evidence does not, of course, exclude potential effects of self-selection or environmental and genetic differences that could alternatively account for enhanced language skills in musicians (Schellenberg,
A meta-analytic approach is useful in assessing the efficacy of music training for language outcomes and identifying the attributes of music training paradigms that are relevant to specific reading outcomes. The present meta-analysis is thus aimed at synthesizing previous research on music training and reading-related outcomes. The following research questions were examined:
Does music training improve reading-related outcomes when other reading instruction is controlled for? Are certain aspects of learning how to read (i.e., reading fluency and phonological awareness) particularly susceptible to transfer from music training?
Does the age of participants account for variability in the efficacy of the training?
Does the quantity of music training impact the efficacy of the training, and how many hours of training are needed to affect changes in reading-related outcomes?
Does the design of the control group condition moderate outcomes?
The goal of this meta-analysis is to evaluate the effectiveness of musical interventions on reading-related measures. To find all articles that met our criteria, we conducted a literature search using the PubMed, Web of Knowledge, and ProQuest article databases. ProQuest functioned as a meta-database, allowing us to search 12 databases simultaneously: ERIC, International Index to Music Periodicals Full Text, Linguistics and Language Behavior Abstracts, MLA International Bibliography, ProQuest Education Journals, ProQuest Psychology Journals, ProQuest Research Library, ProQuest Science Journals, ProQuest Social Science Journals, PsychARTICLES, PsycINFO, and RILM Abstracts of Music Literature. The search terms used in each of the three searches are listed in Supplementary Table
In our literature review, we defined inclusion and exclusion criteria based on meta-analysis guidelines for distinguishing features of studies (e.g., characteristics of the participants, key variables, research methods, and publication type; Lipsey and Wilson,
Out of 178 studies that were reviewed at the abstract level (with full-text examination if necessary to determine inclusion based on above criteria), 17 articles met these criteria. The types of interventions used and contrasting control groups were found to vary substantially across the studies, with some showing confounds of uneven amounts of reading instruction across the groups or failed to provide more musical training to one of the groups. We thus added the following constraint to study design for inclusion:
The intervention group had to receive more music instruction than the control group.
Studies need to provide an indication of equivalent amounts of reading instruction across the intervention and control groups.
After applying this final design constraint, an additional 5 studies were excluded (Register,
(Bolduc and Lefebvre, |
French | 4.9 ( |
Phonological awareness measure (PAM; Armand and Montésinos-Gelet, |
||
(Cogo-Moreira et al., |
Portuguese (Brazil) | 9.2 ( |
Accuracy of Word reading (custom) | Test of phonological awareness (Capovilla and Capovilla, |
|
(Degé and Schwarzer, |
German | 5.8 ( |
Phonological awareness—total from Bielefelder screening (Jansen et al., |
||
(Gromko, |
English (US) | 5.5 ( |
DIBELS letter-naming fluency (Good and Kaminski, |
DIBELS phoneme-segmentation fluency | |
(Herrera et al., |
Spanish | 4.5 ( |
Rhyme oddity task (custom) | Initial phoneme oddity task (custom) | |
(Herrera et al., |
Tamazight | 4.7 ( |
Rhyme oddity task (custom) | Initial phoneme oddity task (custom) | |
(Moreno et al., |
Portuguese (Portugal) | 8.3 ( |
Reading inconsistent words (from Portuguese European reading battery, Succena and Castro, |
||
(Moreno et al., |
English (Canada) | 5.3 ( |
Rhyming (from WJ-III, Woodcock et al., |
||
(Moritz et al., |
English (US) | 5.6 ( |
Rhyming Discrimination from Phonological awareness test (PAT; Robertson and Salter, |
Isolation of initial phonemes from PAT | |
(Myant et al., |
English (UK) | 4.3 ( |
Rhyme test from Phonological Assessment Battery (PhAB; Frederickson et al., |
Alliteration test from PhAB | |
(Register, |
English (US) | 5.5 ( |
Letter-naming fluency from DIBELS (Good and Kaminski, |
Initial sounds fluency from DIBELS | |
(Thomson et al., |
English (UK) | 9.3 ( |
TOWRE (Torgesen et al., |
Rhyme test from PhAB | Spoonerisms from PhAB |
(Yazejian and Peisner-Feinberg, |
English (US) | 4.4 ( |
Rhyming from Early Phonological Awareness Profile (EPAP; Dickinson and Chaney, |
Phoneme deletion from EPAP |
A custom data entry system was created for the study using the Research Electronic Data Capture (REDCap) tools (Harris et al.,
The outcomes measures used within these 13 studies are somewhat variable; each can be classified into one of the two broad categories of Reading Fluency and Phonological Awareness. For studies that reported more than one measure in an outcome category, we selected the measure that most directly tapped into the category. For Reading Fluency, measures that emphasized fluent use of known words and letters were chosen over those that used non-words. Within Phonological awareness, two subcategories were identified: Rhyming and Other Phonological measures. For Rhyming, measures that involved discrimination of rhymes were chosen over those that involved producing rhymes. For Other Phonological, measures that involved identification, discrimination, or manipulation of phonemes were chosen over those that dealt with non-word reading fluency or syllabic segmentation. All measures included are reported in Table
These 13 studies were then carefully coded for the following study design features, which are reported in Tables
Bolduc and Lefebvre, |
6.67 | ✓ | ✓ | ✓ | ✓ | |||||
Cogo-Moreira et al., |
50 | ✓ | ✓ | ✓ | ✓ | |||||
Degé and Schwarzer, |
16.67 | ✓ | ✓ | ✓ | ✓ | ✓ | ||||
Gromko, |
6.5 | ✓ | ✓ | ✓ | ✓ | ✓ | ||||
(Herrera et al., |
16 | ✓ | ✓ | ✓ | ✓ | ✓ | ||||
(Herrera et al., |
16 | ✓ | ✓ | ✓ | ✓ | ✓ | ||||
Moreno et al., |
60 | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | |
Moreno et al., |
40 | ✓ | ✓ | ✓ | ||||||
Moritz et al., |
90 | ✓ | ✓ | ✓ | ||||||
Myant et al., |
17.5 | ✓ | ✓ | ✓ | ✓ | |||||
Register, |
8.5 | ✓ | ✓ | ✓ | ✓ | |||||
Thomson et al., |
3 | ✓ | ✓ | ✓ | ✓ | |||||
Yazejian and Peisner-Feinberg, |
26 | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
Bolduc and Lefebvre, |
Typical | Yes | SES not reported | Random assignment by class | Phonological control |
Cogo-Moreira et al., |
Atypical | Yes | SES not reported | Random assignment by school | No-treatment control |
Degé and Schwarzer, |
Typical | Yes | Yes | Student random | Non-auditory control (sports) |
Gromko, |
Typical | IQ not reported | No | Non-random assignment by school | No-treatment control |
Herrera et al., |
Typical | Yes | SES not reported | Student random | Phonological control |
Herrera et al., |
Typical | Yes | SES not reported | Student random | Phonological control |
Moreno et al., |
Typical | Yes | Yes | Student random | Non-auditory control (art) |
Moreno et al., |
Typical | Yes | Yes | Student random | Non-auditory control (art) |
Moritz et al., |
Typical | Yes | No | Non-random assignment by school | Less intensive music control |
Myant et al., |
Typical | IQ not reported | Yes | Non-random assignment by school | No-treatment control |
Register, |
Typical | IQ not reported | Yes | Non-random assignment by class | No-treatment control |
Thomson et al., |
Atypical | Yes | SES not reported | Student random | No-treatment control |
Yazejian and Peisner-Feinberg, |
Typical | IQ not reported | Yes | Random assignment by class | No-treatment control |
For each outcome and measure, a single effect size was computed in the following manner, where ES = effect size:
Meta-analysis was performed using the open-source statistical software package R (R Core Team,
Publication information, language, age of participants, and outcomes measured are reported in Table
Several aspects of control factors in the study design are reported in Table
Means, standard deviations, pre- and post-training, N's per group, and the computed effect sizes are reported in Table
Cogo-Moreira et al., |
Accuracy of word reading | 114 | 9.45 (11.33) | 16.14 (15.59) | 121 | 11.22 (14.37) | 16.5 (15.33) | 0.11 |
Gromko, |
DIBELS letter-naming task | 43 | 33.42 (15.48) | 42.63 (15.22) | 60 | 36.27 (18.87) | 44.1 (15.63) | 0.08 |
Moreno et al., |
Inconsistent word reading | 16 | 41.73 (16.38) | 71.35 (13.25) | 16 | 45.83 (17.48) | 56.77 (17.53) | 1.07 |
Register, |
DIBELS letter naming fluency | 22 | 12.18 (10.58) | 20.23 (14.27) | 21 | 17.48 (16.74) | 25.38 (17.65) | 0.01 |
Herrera et al., |
Word reading | 9 | 49.67 (12.44) | 52.44 (11.26) | 12 | 48 (15.97) | 48.25 (17.27) | 0.17 |
Bolduc and Lefebvre, |
Phonological Awareness Measure (PAM) | 28 | 10.5 (2.58) | 14.8 (3.65) | 26 | 12 (3.12) | 15.4 (3.54) | 0.31 |
Cogo-Moreira et al., |
Phonological awareness | 114 | 25.79 (4.96) | 27.66 (4.64) | 121 | 23.98 (5.13) | 25.18 (5.25) | 0.13 |
Degé and Schwarzer, |
Phonological Awareness—Total | 13 | 35.77 (2.35) | 38.23 (1.17) | 14 | 35.86 (3.18) | 36.07 (2.99) | 0.78 |
Gromko, |
DIBELS phoneme-segmentation fluency | 43 | 18.61 (16.26) | 44.72 (16.94) | 60 | 25.83 (14.73) | 41.55 (14.5) | 0.67 |
(Herrera et al., |
Initial sound | 15 | 42.69 (22.5) | 60.14 (12.5) | 14 | 45.8 (17.76) | 60.5 (12.63) | 0.13 |
(Herrera et al., |
Initial sound | 17 | 42.44 (10.2) | 51.99 (8.67) | 10 | 39.72 (12.18) | 55.14 (7.9) | –0.52 |
Moritz et al., |
PAT isolation initial | 15 | 7.5 (2.15) | 9.93 (0.27) | 15 | 6.57 (2.3) | 9.15 (1.21) | –0.07 |
Myant et al., |
Alliteration | 28 | 1.82 (2.58) | 3.35 (3.35) | 31 | 0.26 (0.58) | 1.11 (1.6) | 0.37 |
Register, |
DIBELS initial sounds fluency | 22 | 6 (6.62) | 14.27 (8.47) | 21 | 9.52 (6.41) | 15.71 (8.04) | 0.31 |
Thomson et al., |
PhAB spoonerisms | 9 | 14.11 (6.54) | 17.44 (7.38) | 12 | 14.17 (7.21) | 14.83 (6.93) | 0.37 |
Yazejian and Peisner-Feinberg, |
Phoneme deletion | 111 | 10.35 (4.19) | 12.32 (2.88) | 70 | 8.99 (4.68) | 12.03 (3.27) | –0.24 |
(Herrera et al., |
Rhyme oddity | 15 | 42.08 (11.97) | 56.64 (6.82) | 14 | 40.56 (14.49) | 52.49 (10.94) | 0.19 |
(Herrera et al., |
Rhyme oddity | 17 | 46.68 (8.8) | 64.65 (9.12) | 10 | 42.92 (11.4) | 57.36 (10.27) | 0.35 |
Moreno et al., |
Rhyming | 30 | 9.2 (2.9) | 11 (3.7) | 30 | 8.6 (3.9) | 10 (4.3) | 0.11 |
Moritz et al., |
PAT rhyming discrimination | 15 | 7.53 (2.1) | 9.86 (0.36) | 15 | 8.64 (1.39) | 8.77 (1.54) | 1.20 |
Myant et al., |
Rhyme | 28 | 3.86 (2.92) | 6.77 (3) | 31 | 3 (2.67) | 6.04 (2.93) | –0.05 |
Thomson et al., |
PhAB rhyme | 9 | 16.78 (2.28) | 18.78 (2.28) | 12 | 14.08 (5.45) | 15.08 (5.87) | 0.22 |
Yazejian and Peisner-Feinberg, |
Rhyme recognition | 111 | 3.52 (2.89) | 6.05 (3.74) | 70 | 2.76 (2.58) | 5.21 (3.85) | 0.02 |
Due to the non-independence of the studies that reported both types of phonological awareness outcomes (Rhyming and Other Phonological) in the same sample, mixed effects analysis was employed to test overall Phonological Awareness. This analysis on All Phonological Awareness (
Random-effects analysis on the subset of rhyming outcomes (
Random effects analyses on Other Phonological outcomes (
Random effects analysis on the five studies that included Reading Fluency outcomes showed a weighted average effect size of 0.16 (95% CI [−0.03, 0.35],
The Rank Correlation Test for Funnel Plot Asymmetry indicated no publication bias for either Reading Fluency (Kendall's tau = 0.60,
The current meta-analysis was carried out to assess the impact of music intervention on reading-related skills in children, and adds to the literature by specifically highlighting effects of music training transferring to reading-related skills when non-musical reading training is held constant. Results of the meta-analysis on the broad category of Phonological Awareness outcomes suggest modest gains (a small effect size of
When broken down into subcategories (Rhyming and Other Phonological outcomes), moderator analysis revealed that the effectiveness of music intervention on Rhyming outcomes was dependent on the number of training hours. Total music intervention training hours ranged between 3 and 90 h in the studies included here, and the model estimated that at least 40 h are needed to improve Rhyming skills. To put this number in perspective, other work (e.g., Hambrick et al.,
The separate meta-analysis on eleven datasets with Other Phonological Outcomes was inconclusive: the effect size was small (
The effect size for the separate meta-analysis assessing the impact of music training on reading fluency outcomes was also small (
Moreover, previous meta-analyses with different parameters than the present study have found both a non-significant effect of music on reading skills (Butzlaff,
It is interesting to note that a previous meta-analysis on literacy development found medium-to-strong effects of phonological awareness training on reading skills (yet longer term studies produced only small effects), and that phonological awareness was a necessary, but not sufficient condition for reading (Bus and van IJzendoorn,
Overall, the findings of the current meta-analyses are somewhat inconclusive with regards to the hypothesized impact of music education on reading-related skills. The literature search revealed a large amount of variability in outcomes studied, content and intensity of music training, native language of participants, type of subject populations (typically developing vs. reading disordered) and age of participants. In addition, some of the study designs in the set of studies included in this meta-analysis are laden with potential biases that make it difficult to draw broader conclusions from the findings (see Table
• IQ and socio-economic status | • What are the effects of different components of interventions (rhythm, pitch; instruments vs. singing; phonological activities in musical context, etc.) on training efficacy? |
• Control intervention content | • What degree of music-driven gains in phonological awareness are needed to impact reading fluency? |
• Type and duration of music training | • What are the mechanisms underlying improvement: such as attention, motivation, (e.g., OPERA hypothesis; Patel, |
• Guidelines for typical and atypical development | • How are changes in brain function and structure associated with music-training-driven improvements? |
• Random assignment to experimental groups | • How do individual differences predict response to training? Is there a subset of children that stands to benefit the most from music training? |
Moreover, the small effects of music on reading-related outcomes observed in this meta-analysis stand in contrast to the robust results seen in the correlational literature reporting (broadly defined) linguistic advantages in musician children (Magne et al.,
The literature review encompassed by the present study revealed two somewhat opposing trends: on the one hand, an approach that favors
In contrast, the auditory neurodevelopment framework posits that music training strengthens basic auditory and speech processing, which in turn influence phonological perception and reading skills. These gains have been described as domain-general improvements in auditory brain mechanisms underlying temporal and frequency resolution, auditory processing, and phonological awareness (Tierney and Kraus,
Another important aspect of the neurodevelopmental framework, thus far not definitively investigated in the literature, is that individual differences in innate (or pre-existing) musical traits may differentially affect music-training-driven plasticity and transfer to language skills. The extant literature does suggest that the relationship between language and music skills varies with different levels of music aptitude (Banai and Ahissar,
The mixed results obtained in the current meta-analysis could instead signify possible limitations of music training for literacy skills in children. Such an interpretation could be regarded in accordance with previous accounts of modularity of some aspects of language and music (Peretz,
To develop a full picture of the extent of transfer from music experiences to language skills and the possible applicability of the neuro-developmental framework, more work is also needed on the underlying mechanisms of music-related improvements in language when they are reported (either in individual studies or future meta-analyses). These effects could potentially be due to all-around, general acoustic perception/auditory processing skills (affecting perception of pitch, timing, and spectral characteristics); or, the benefits may be only specific to certain aspects of phonology such as fine-tuned detection of voice-onset-time (Zuk et al.,
The present meta-analysis contributes to the literature by examining the influence of music training on reading-related skills while also constraining the amount of reading instruction received across groups and modeling potentially important moderators (age, hours of training and type of control intervention). The findings yielded modest gains in phonological awareness (mainly in rhyming skills) for music vs. control interventions, but the small subset of studies examining reading fluency skills found no significant aggregate improvements in music vs. control groups. The literature review synthesized results from previous work suggesting potential benefits of music training on non-musical academic skills (e.g., Patel,
To draw definitive conclusions on a causal link from music to literacy and possible mediating mechanisms, there is abundant room for further progress in using longitudinal studies to address both the study design factors and the potential moderators of music-training-driven plasticity in reading-related skills. Brain imaging methods may reveal mechanisms underlying this plasticity, and can potentially be exploited to establish innovative approaches for predicting individual differences in response to music training. Recent work linking rhythmic processing to speech sound sensitivity and literacy skills suggests candidate mechanisms for improving reading skills via music education, and warrant further investigation in the context of using music training to remediate reading disabilities in school-age children. Future longitudinal studies incorporating both behavioral reading-related outcomes and measures of neural plasticity in typically developing and struggling readers are also needed in order to assess the viability of the neuro-developmental framework for music interventions.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
This project was funded in part through NIH award R01DC007694 to BM. The RedCAP system, made possible through UL1 TR000445 from NCATS/NIH to the Vanderbilt Institute for Clinical and Translational Research, was used for coding and secure data storage. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The authors would like to gratefully acknowledge Sandra Wilson and Gloria Han for insightful comments on the approach, McKenzie Miller for assistance with coding and data entry, Alison Williams for formatting assistance, and Rita Pfeiffer and two reviewers for feedback and helpful comments on the manuscript. We would also like to thank Noreen Yazejian, Cathy Moritz, Georgios Papadelis, Sylvain Moreno, San Luis Castro, Mireille Besson, Franziska Degé, Hugo Cogo-Moreira, Dena Register, and Wendy Armstrong for providing data and/or additional information about their studies.
The Supplementary Material for this article can be found online at:
*