Free Analysis of factors associated with pictures and words that affect naming in young children aged 4-8 (N.B. Secondary data analysis) Dissertation Example

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Analysis of factors associated with pictures and words that affect naming in young children aged 4-8 (N.B. Secondary data analysis)

Category: Communication

Subcategory: Design

Level: PhD

Pages: 31

Words: 8525

Semantic and Phonological Abilities in Children with Word Finding Difficulty: An Analysis of Secondary Data
Abstract
Word finding Difficulty (WFD) is defined as the inability to retrieve appropriate words in response to a stimulus or situation. Individuals with WFD exhibit wrong words with unexpected pauses and circumlocutions. The global prevalence of WFD is estimated to be 5% to 7% and is noted in 25% of the individuals who receive language support services. Only a few studies have explored the underlying causes of WFD. WFD has been attributed to impairment at several levels of cognitive processing that are associated with language production. The present study explored semantic, perceptual, and phonological abilities in WFD and typically-developing (TD) children. The end-points that were explored include picture naming accuracy, abilities in word-picture verification tasks (WPVT), semantic abilities (PJ tasks), and assessment of phonological ability (CNRep task). The study showed that children with TD exhibited significantly higher picture naming accuracy than their WFD counterparts (p>0.05). In TD children, a positive and significant correlation existed between naming accuracy and phonological ability as well as between naming accuracy and WPVT ability (p<0.05). On the contrary, in WFD children, there was a significant and positive correlation between naming accuracy with WPVT abilities only. Such findings suggest that WPVT was the sole determinant of word-finding accuracy in children with WFD. However, a critical appreciation of theories that underpin spoken words production reflected that WFD children could exhibit low linguistic encoding as reflected from their lower phonological abilities that led to a reduction in picture naming accuracy scores compared to their TD counterparts.
Keywords: WFD, TD, underlying causes, semantic, phonological
Section 1: Introduction
Background
WFD is a developmental disorder where an individual is unable to frame appropriate words in response to stimuli (Dockrell, Messer, George, &Ralli, 2003). WFD is a common feature of developmental language disorders. Studies suggest that the global prevalence of WFD is estimated to be 5% to 7%. Almost 25% of individuals who receive language support services are affected with WFD (Dell et al., 2013, Dockrell et al., 2003). It is contended that WFD stems from impaired semantic and phonological abilities in concerned individuals. However, the interaction between semantic and phonological attributes that underpin word-naming remains inconclusive. Messer & Dockrell (2006) further elaborated that children with WFD can identify a referent from a set of exemplars, but are unable or face difficulty in producing a target word. Although in most instances the errors in spoken words are self-corrected, in certain instances individuals with WFD are unable to exhibit self-correction skills (Best et al., 2017). The word-finding difficulty behaviors are manifested as repetition, revision, substitution, the use of fillers, delay, insertions, and incorporation of empty words while naming the target word. It is noted that children with WFD often exhibit circumlocutions of the target word which refers to the partial representation or partial retrieval of the target words. Children with WFD often exhibit significant variations in naming the same target across different occasions or with time (Zens, Gillon, & Moran, 2009).
Word-finding difficulties (WFD) impose significant challenges in both children and adults. Such debilities impact communication and cognitive processing skills in these individuals (Van Hees et al., 2013). However, the impact of WFD is significantly higher across children and adolescents. WFD is classified as a subtype of language impairment disorders where an individual express distinct development needs on language (Best et al., 2017). WFD predisposes an individual to low self-esteem, constrained relationships or difficulty in building new relations, impaired academic skills, and deprivation from wider life chances. Individuals with WFD exhibit a high percentage of naming errors compared to their unaffected counterparts.
Individuals with WFD also exhibit impaired learning ability or deficit in metacognitive processing skills (Thomas & Knowland, 2014). Goldrick (2006) highlighted individuals with WFD exhibit deficits at different levels of cognitive processing. Messer and Dockrell (2013) stated that WFD-affected individuals have difficulties in aligning their semantic and phonological abilities. Retrieval of words to pictorial or verbal stimuli involves activation of the long-term memory (LTM). Hence, different attributes that interact with LTM is speculated to influence word-finding accuracy. First of all, the concept which matches the idea that is to be expressed through words should be appropriately selected from long-term memory storage. Secondly, the appropriate word which matches the concept should be appropriately retrieved. Finally, the retrieved word should be spoken with appropriate phonological accuracy. Hence, WFD could stem from deficits in semantic ability or phonological ability or both (Dell et al., 2013).
Studies reflect that different semantic and phonological processes are involved in retrieving words from one’s mental lexicon (Dell, Faseyitan, Nozari, Schwartz, &Coslett, 2013). Hence, WFDs are evident while producing single words or connected discourse or both. Protopapas (2007) suggested that individuals with WFD should be assessed for retrieving single-word tasks. These tasks often involve word-naming in response to visual and auditory stimuli which induces retrieval of information from the semantic memory of an individual. Tasks commonly used to identify WFD involve the production of specific words or a series of words (without appreciable gaps) in response to visual or auditory stimuli (Smith, 2012). Accuracy and speed of production are explored to understand the severity and extent of WFDs (Smith-Lock et al., 2012). Individuals who exhibit slow reaction time and inaccurate performance in naming are considered to be affected with WFD (Powell, Stainthorp, Stuart, Garwood, & Quinlan 2007).
Broadly, the major models of speech production are divided into serial models and connectionist models. The connectionist model was primarily proposed by Dell (1997) which was grounded on the concept of spreading activation of lexical access. Dell (1997) proposed that speech is produced when a different number of connected nodes can interact with each another. Such interaction may take place in any direction either at the concept level (semantics) or at the level of phonological representation (Fernandez & Cairns, 2011). The serial models of speech production endorsed that speech is produced when the nodes are accessed independently and in a serial manner. For example, Bock and Levelt’s Model contended that speech is produced at the message level (that involves the generation of the main idea that is to be communicated), a functional level which is divided into lexical selection stage and functional assignment stage. After these two levels, speech production involves the position level which involves the determination of the morphological slot. Finally, the phonological encoding level involves the expression of the word in term of its phonological or morphological properties (Levelt, Willem J. M.; Roelofs, A.; & Meyer, AS. (1999).
WFD individuals often exhibit inappropriate semantic abilities while storing words in the brain. As a result, individuals who express semantic-based WFD exhibit frustration for their inability to retrieve appropriate word and they might experience the typical “tip of the tongue” phenomenon. In most circumstances, individuals with semantic-based WFD substitutes semantically similar word without even realizing the meaning of the words (Dell et al., 2013). For example, they might use the term “lion” for “tiger” and “binoculars” for “microscopes.” On the other hand, individuals with phonological-based WFD express difficulty in retrieving the phonological attributes of the target word (Dell et al., 2013). Phonological-based errors include words spoken with similar sounds but different meanings. For example, individuals expressing phonological-based WFD confuse “potato” with “tomato” and “chicken” with “kitchen.” Phonological errors during word-naming are attributed to the weak interaction between semantic and phonological storage systems during retrieval of words (Dell et al., 2013).
The present study explored the potential underlying reasons for WFD. The study was based on the assessment of semantic and phonological processes that are implicated in the various models of spoken word production. This study reflected a comparison between WFD and typically developing (TD) children from the bespoke tasks of semantics and phonological abilities. In this study, TD children served as the reference group. This study was based on the analysis of secondary data, which was originally collected as part of a research project entitled “Lexical retrieval difficulties in children” conducted by Masterson, Best, & Thomas (2011-2014).
Section 2: Literature Review
Background
The objective of the review was to explore the underlying causes of WFD. The underlying causes were explored in the intervention studies that were used to improve word-naming in children with WFD. First of all, the review explored the different theories that underpin spoken word production. Secondly, the review analyzed the studies that explored or managed WFD on the basis of different attributes that are known to influence spoken word production. Finally, the review highlighted the gaps in understanding the development of WFD in comparison to TD children.
Theories Underpinning Spoken Word Production
Different authors have highlighted that speech production involves a general schema. First of all, a message or parts of it that need to be linguistically encoded is identified. Then the speaker selects specific word or words (which are referred to as lexical items) to represent the intended word or message. The process of selecting lexical items is referred to as lexical selection, and it represents semantic information. Retrieval of semantic information is based on an individual’s semantic ability. However, semantic encoding is followed by grammatical encoding to present appropriate syntaxes. Finally, the output (spoken word) is a function of one’s articulation system that involved in speech production. The basic loop of producing speech involves decoding of a speech into its linguistic form. Next, the linguistic form is further decoded into its meaning. Based on the basic loop of speech production various scientists have proposed different models of speech production.
In fact, no model or a set of models can theoretically characterize the production of speech holistically (involving processing of a single phase at any one time) or as components (the processing of the different components of a phrase separately). Nevertheless, all the models of speech production are based on certain considerations that are common between each other. First of all, the primary question behind all models involves the mechanism through which linguistic components of a speech are retrieved during its continuous production. Secondly, all these models mandate that linguistic information is represented by distinct form or units and the order of retrieval of such units. The third domain includes the need to access the semantics and syntaxes before phonological expression.
Evidence supporting and challenging word-naming theories
Studies suggest that naming difficulties in single words could stem from the reduced functioning of the lexical pathway (Dell et al., 1997). Monaghan and Ellis (2002) further contended that word-naming is significantly influenced by the appropriate perception of the meaning of words or pictures. However, the authors did not draw the link between the semantic or phonological attributes in of the words that are retrieved and spoken. (Li, Farkas, & MacWhinney, 2004). Such findings reflected that the retrieval of words to be spoken are dependent on serial processing that involves semantic, phonological, and metacognitive pathways. Hence, vocabulary enhancement programs should help to improve word naming in children with WFD.
In fact, Leonard et al. (2007) highlighted that vocabulary-enhancement programs improve semantic or phonological abilities in an individual with WFD by sharpening of the working memory. The authors’ assumptions were based on recall of words for shorter duration (that indicated verbal working memory) of the participants (n=28).The authors showed that verbal working memory could eplain 62% variations in word-naming accuracy in the participants. Such findings suggest that improved phonological and semantic attributes help to improve verbal working memory. In another study, Lorenz & Ziegler (2009) showed that semantic therapy could improve word-naming in children (n=10) with WFD. However, the findings of the study were confounded by the presence of aphasia in the participants. On the contrary, Messer &Dockrell (2006) concluded that there is inconclusive evidence regarding the role of semantic and phonological abilities and their likely interaction which predisposes the risk of WFD. The authors found no difference in word-naming accuracy with improved semantic and phonological instructions in the participants (p>0.05). However, the compatibility and quality of such interventions in the target participants were not standardized in the studies that were appraised by the authors in their review. Although, the authors suggested that a substantial minority of children with WFD express difficulties in lexical retrieval. Such findings supported the findings of Lorenz & Ziegler (2009). To recall, Lorenz & Ziegler (2009) related lexical retrieval as a function of the verbal working memory.
Since most of the data on the role of interventions in alleviating WFD are based on either small sample sizes or inappropriate study designs, conclusive evidence regarding such variables (semantic and phonological ability) in predisposing the incidence of WFD remained unclear. On the other hand, Messer &Dockrell (2006) further showed that that the semantic and phonological abilities are modulated by one’s knowledge of grammar or perception of words. The study further showed that children with WFD exhibited significantly higher cognitive demands compared to TD counterparts. However, the authors did not report whether increased semantic and phonological support aid word-naming in such individuals over longer periods (p>0.05). German, Schwanke, and Rafid (2012) explored the effectiveness of a differentiated approach to vocabulary instruction across individuals (n=10) with WFD. The respective study participants first received only semantic-based vocabulary intervention. In the second approach, the same study participants received a combination of semantic and phonologic-based vocabulary instruction. Individuals with WFD exhibited higher language gains post-exposure to the combined vocabulary instruction regime (p<0.05). German et al. (2012) concluded that the phonological ability improved retrieval of semantically-based vocabulary instructions.
Ebbels et al. (2012) conducted a study on 15 WFD children. The study focused on the semantic and phonological processing skills in explaining the genesis of WFD. The authors acknowledged that children with WFD exhibit poor semantic knowledge that accounted for their word-finding errors. The study participants received 15-minute semantic therapy session per week that continued for eight weeks. The words were targeted from three semantic categories such as foods, clothes, and animals. All participants were evaluated on the Test of Adolescent Word Finding Difficulty (TAWF) both before and post-intervention. There was a significant increase in TAWF scores in WFD children compared to waiting controls (77 versus 67, p<0.05). The study showed the importance of semantic-based approaches in improving vocabulary instructions in children with WFD. However, the study did not explore the phonological abilities that influenced semantic-based retrieval of spoken words.
Bragard et al. (2012) reflected that semantic- or phonological-based vocabulary interventions could not be generalized. Hence, most intervention programs for WFD focus on improving either semantic- or phonological-based learning. These findings suggest that there might be other variables which might prompt explicit learning (declarative learning) across concerned individuals. For such reasons, Lum et al. (2012) showed that older individuals were more competent in using meta-cognitive skills to build semantic links before retrieving words that are to be spoken. It is also noted that WFD children have difficulties in accessing and interpreting word-forms which have poor semantic attributes (Friedmann, Biran, &Dotan, 2013). On the contrary, differences in strength and elaboration of terms in lexical storage are difficult to assess when individuals also exhibit poor retrieval of single-words (Dell et al., 2013). This is because underrepresented or unrepresented words are difficult to name by children suffering from WFD (Ebbels et al., 2014). The authors reported that semantic-based and phonological-based approaches helped to present the words more effectively to children with WFD. Since WFD can also be present during connected speech (which is featured as disruption or breakdown in language formation fluency), it is contended that conversational disruptions could either stem from poor word knowledge or a deficiency in retrieving the learned words (Ebbels et al., 2014).
Motsch and Mark (2015) showed lexical interventions improve word naming in WFD children (n=157) compared to their experimental controls who received alternative vocabulary support. Best et al. (2015) explored the influences of word-naming ability based on two case studies in children with WFD. The authors explored four core tasks to assess word-naming skills. The four core tasks that measured WFD across the participants include the ability to produce words in response to a picture (the confrontation naming task), the ability to understand the meaning of words in relation to the picture (the word-picture verification task), analysis of semantic knowledge separate from naming ability (picture judgment task), and an assessment of phonological knowledge that was separate from the meaning of the words (non-word repetitions. The two case studies were compared to experimental controls that comprised of typically developing (TD) children.
In the Best et al. (2015) study, TD children exhibited greater accuracy in picture naming tasks than individuals with WFD (with 1.5 standard deviations from TD mean being 30.93 for the picture-naming task). Likewise, the WPVT, PJ scores, and CNRep scores were also higher than their WFD counterparts (p<0.05). These results reflect that deficits in semantic abilities could predispose the episodes of WFD. On the contrary, one individual exhibited superior word naming with phonological intervention. Therefore, both semantic and phonological abilities could interact with each other in influencing spoken words. In fact, Wilson et al. (2015) showed that there is inconclusive evidence regarding the role of semantic or phonological abilities alone in improving word-naming. Such findings once again confirmed the involvement of two parallel pathways in interpreting picture-naming paradigms; one based on semantic attributes while the other based on phonological attributes.
Best et al. (2017) portrayed the results of a vocabulary-enhancement intervention technique in improving word naming across children with WFD (n=20). Such intervention was assumed to improve the meta-cognitive awareness of the respective individuals on word-retrieval. The participants in the intervention group were allocated to receive either a semantic-based or phonological-based vocabulary intervention. The intervention group exhibited greater accuracy in naming the 100-item pictorial stimuli compared to their control counterparts and (p<0.05). However, the authors also expressed their findings in terms as a subset protocol-based on treated and untreated-words. The pictures (n=25) that were “treated” (that were taught to correlate with semantic and phonological symphony) were named significantly more accurately (5.90 items versus 1.48 items, p<0.001).The intervention group also showed higher gains (60% more) for untreated-word items than controls. However, word-naming accuracy did not differ for the pictorial stimuli for untreated and unseen words (p>0.05). Best et al. (2017) also showed that cognitive skills developed in one category of pictures do not necessarily translate into improved retrieval of words that are uncommon to the study participants.
Appraisal of the Literature Review
The literature review reflected that there is a necessity to understand what attributes of semantic-based and phonologically based abilities that are effective in addressing word-difficulty in WFD children. The review also reflected that it would be too generalized to accept either semantic-based or phonologically-based intervention programs in improving word naming in children with WFD. Therefore, the confounding effects of intelligence quotient, receptivity, arousal, auditory processing skills, and visual processing skills in the study participants should be controlled before designing word-naming intervention programs. However, the literature review reflected a few studies which portrayed the underlying causes in terms of cognitive processing skills in individuals with WFD. However, evidence indicates that WFD could be attributed to impairments in several levels of cognitive processing that are associated with word-naming. The evidence was further complemented by the theories and models that underpin word-naming in individuals with or without developmental disorders. There is a need to explore the semantic or phonological deficits in the target population which might lead to WFD.
Section 3: Methodology
Overview
The main objective of the secondary data analysis was to explore the relationship between word naming performance and semantic and phonological abilities in TD children and children with WFD. The data for this study was adopted from a publication entitled “Lexical retrieval difficulties in children” by Masterson, Best, & Thomas. The datasets that were explored in the present study include data on 12 language impaired children with WFD) and data on 52 TD children from the same assessments (primary study). The dataset on 25 TD children was used as age-matched controls for the children with WFD (n=12). The secondary data analysis reviewed the difficulties thought to underlie WFD as reflected in the research literature. The data of the participants with WFD was compared with their TD counterparts to identify the performance expected of TD children in the novel assessments. In the sections that follow, there is an outline of the participants, stimuli, and procedures for data collection employed in the original study.
Participants
The participants in the original funded research were aged 4 to 8 years and recruited from six different schools in London and outer London. The children with word finding difficulty were selected by SLTs (Speech and Language Therapists) and by SENCOs at their schools. For the current study, data for twelve children with WFD were extracted. Their results in the assessments outlined in the next section were analyzed. The data of 25 typically developing (TD) children were also extracted to act as an age-matched comparison group. None of the study participants were diagnosed with autism spectrum disorders, dyspraxia, or attention deficit hyperactivity disorder. Table 1 reflects the descriptive statistics for the chronological age of the participants belonging to the WFD and TD groups. Table 1 shows that the chronological age of the participants was comparable across the two groups (p=0.937).
Table 1
Summary of the chronological age of the participants in the WFD and TD group
type   N Mean Std. Deviation
Age in months WFD 12 (males =7, females=5) 81.67 5.630
  TD 25 (males=16, females=9) 81.52 4.144
Materials
The four core tasks (picture naming, WPVT task, PJ task, and CNRep) were compared between WFD and TD children. Participants in the confrontation task (picture naming task) were asked to speak out the names of the pictures. These pictures comprised 72 line drawings of different objects. Both accuracy and latency (assessed as median reaction time) of the verbal responses were recorded. The errors were categorized into word-picture verification errors, semantic errors, phonological, or mixed errors. The WPVT task assessed the knowledge of the participants on the items that were presented to them in the confrontation naming task. In this task, each of the pictures was presented on two occasions. In one instance, the picture was accompanied by the correct spoken word. In the second instance, the picture was accompanied by a word that was semantically close to the verbal level of the picture but had a different meaning. The participants were asked during each trial to reciprocate whether the spoken word corresponded to the picture.
The 72 pictures used for picture naming and word-picture verification tasks were selected from the study of Funnell, Hughes, & Woodcock (2006). The pictures include black and white line drawings of different objects from four categories and each category included 18 items. Out of the four categories, two represented living things and the other two represented artifacts. The DMDX software was used to program the picture naming task (Forster & Forster, 2003). An external microphone was used to record the responses of the study participants. The accuracy and naming times (in milliseconds) were recorded using the CheckVocal software.
The WPVT was conducted with the 72 items that were used in the confrontation task. The picture naming and WPVT tasks were carried out into two blocks and was separated by a break. The two pictures were presented in separate blocks, however; the order of presentation was counterbalanced in the study participants. In the PJ task, the participants three pictures were presented to the participants. The participants were asked to choose one of the two coordinate pictures that had semantic resemblance with the third picture. For example, a chair and pillow were shown with the third picture of a table. The Children’s Test of Non-word Repetition (CNRep) was used to assess phonological ability. Such estimation reflected their ability to recall without the perception of meaning. The non-word repetition task was considered a sensitive test because both phonological input and outputs must be appropriately processed to produce the verbal response.
Procedure
The pictorial items in the picture naming task were presented in blocks of 24. Each participant was requested to speak out a single word for the picture that was presented. The pictures were presented to the participants in a random manner. However, the participants were shown no more than two pictures in the same category. A fixation cross was introduced in the centre of the screen for 500ms at the beginning of every trial. The picture was presented for 5,000 and10, 000 milliseconds in TD and WFD children respectively. The practice trials were carried out with three items that was not included in the final study. WPVT accuracy was assessed as the acceptance of the actual word and rejection of its close semantic.
In the picture judgment task (PJ), the participants were exposed to two pictures and were asked to express their choice based on a third picture which was semantically close to one of the two pictures. The participants were asked match two pictures that were presented on the top of the screen with those that were presented at the bottom. The participants were asked to click the appropriate choice by pressing the relevant keys on the keyboard. A subset of 20 pictures from the picture-naming task was used for the PJ task. The CNRep task was administered according to manual instructions. The number of items pronounced appropriately was recorded. Single and choice reaction time (which estimated speeded motor responses) was also assessed across both the groups (TD and WFD). The CNRep test consisted of 40 non-words with increasing length and complexity. The reaction time was calculated from the time of presentation of the stimuli and verbal response (word-naming) to such stimuli.
Data Analysis
Descriptive and inferential statistics were used to interpret the findings of the present study. Exploratory data analysis was conducted with the data of 25 TD children to find out whether the variables that were considered are normally distributed. The Kolmogorov-Smirnov and Shapiro-Wilk test showed that all the variables (except PJ task score) that were considered for the study exhibited a normal distribution (p>0.05) (Appendix-1). Since the PJ task scores reflected semantic ability of the participants and judgmental attributes are based on metacognitive attributes the scores were not transformed. The descriptive statistics were undertaken to explore the nature of sampling distribution. Based on the nature of the sampling distribution, inferential statistics were undertaken. Parametric statistics were undertaken when a dataset exhibited a normal distribution. On the contrary, non-parametric statistics were undertaken when the respective data set did not exhibit a normal distribution. The major parametric tests undertaken include t-tests and correlation analysis. All statistical tests for the present study would be interpreted at the 0.05 level of significance.
Section 4: Results
The results are presented as picture-naming accuracy, WPVT accuracy, PJ task accuracy, and CNrep task accuracy for both WFD and TD children. The study aimed to analyze the semantic and phonological abilities that influence WFD. The literature review reflected that there could be other attributes apart from semantic and phonological abilities that could influence WFD. Hence, the results were presented in a manner to compare between such abilities in children with WFD and TD.
Picture-Naming
Picture-naming accuracy scores were based on the responses of the participants on the 72 line drawings. The reaction time for retrieving the words in association with pictures represented the ability to retrieve words from lexical storage based on interpretation of the meaning of pictures. Table 2 gives a summary of the picture-naming task scores and the type of errors expressed by the respective group of participants. The qualitative errors (semantic, phonological, mixed, and perceptual errors) associated with picture-naming were also noted for the participants and presented in Table 2.
Table 2: Summary of accuracy and response times for the WFD and TD children in picture naming tasks
Type   Mean Std. Deviation Sig. (2-tailed) Std. Error Difference 95% Confidence Interval of the Difference
Picture Naming – % correct WFD 41.09 6.139 0.009 2.93 -14.09 -2.17
TD 49.22 11.69 Picture naming – median RT WFD 1400 272.007 0.927 93.27 -203 185.69
TD 1408 251.679 Picture Naming – % of phonological errors WFD 3.35 5.151 0.085 1.5 -0.46 6.13
TD 0.51 1.252 Picture Naming – % of semantic errors WFD 45.61 14.759 0.206 4.71 -3.78 16.2
TD 39.4 10.123 Picture Naming – % of perceptual errors WFD 3 3.848 0.973 1.34 -2.74 2.83
TD 2.95 3.769 Picture Naming – % of mixed errors WFD 6.55 3.325 0.001 1.16 1.82 6.64
 
TD 2.32 3.262      
 
Table 2 reflects that picture naming accuracy was significantly higher in TD children compared to children with WFD (p=0.009). The table 2 further reflected that median reaction time to picture-naming was comparable in children with TD and WFD (p=0.927).
Word-Picture Verification Ability
The WPVT task was carried out for all the 72 items of the picture naming task once it was completed. The WPVT task assessed the children’s knowledge of the pictures. The findings of the WPVT ( in terms of accuracy and latency) for both groups of participants are presented in Table 3.
Table 3: Summary of scores in the WPVT for the WFD and TD groups
type   Mean Std. Deviation Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference
WPVT % correct WFD 65.28 7.180 0.112 -4.556 2.770 -10.23 1.126
TD 69.83 9.191 WPVT
Median RT WFD 2601 351.114 0.103 218.994 127.994 -48.32 486.313
TD 1160 1203.95 Table 3 reflect that the WPVT accuracy percentage and the median reaction times for the WPVT task between WFD and TD children were comparable (p>0.05).
PJ Task
.The PJ task is a measure of the semantic ability of an individual. The scores in the PJ task in the two groups (WFD and TD) is presented in table 4. The median reaction time for the PJ tasks across both groups is also presented which reflects the ease of retrieving words based on its semantic attributes. The PJ task accuracy scores for both groups are shown in Table 4.
Table 4: Summary of PJ task accuracy and response times for the WFD and TD groups
type   Mean Std. Deviation Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference
PJ Task – % correct WFD 90.42 6.895 0.732 0.817 2.353 -4.092 5.725
TD 89.60 6.278 PJ Task – the median of RTs WFD 4081 996.592 0.046 736.597 348.350 13.196 1459.997
TD 3345 982.105 ___________________________________________________________________________
Table 4 reflected that the PJ task accuracy percentage for WFD and TD children were comparable (p>0.05). However, the median reaction times were significantly higher in WFD children compared to their TD counterparts (p<0.05).
Children’s Test of Non-word Repetition Task
The Children’s Test of Non-word Repetition (CNRep) The summary of phonological abilities in WFD and TD children is presented in Table 5.
Table 5: Summary of CNRep task accuracy for WFD and TD groups
Type   Mean Std. Deviation Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference
CNRep -% correct WFD 42.71 15.684 0.006 -16.458 5.367 -27.64 -5.26
TD 59.17 14.116 Table 5 reflected that the CNrep task accuracy for TD children was significantly higher compared to that of WFD children (p<0.05). Such findings reflected that TD children exhibit significantly higher phonological ability compared to WFD children.
Correlation analysis between Picture Naming Tasks with Semantic, Phonological, and WPVT ability
The findings of the independent- t-tests suggested that appreciation of meaning, semantic, and phonological attributes of words could influence their retrieval in children with WFD. The assumptions were confirmed from the assessment of correlation coefficients between picture-naming accuracy with such judgmental (semantic), perceptual, and phonological attributes in the study participants (holistically and separately for both WFD and TD children) (Table 4a, 4b, and 4c). The holistic correlation analysis was undertaken to evaluate which are the contributory factors that underpin WFD. On the other hand, the correlation analysis for WFD and TD children were also undertaken separately because the TD was used as a reference group for evaluating what should be expected at this age on the assessments used in the study. A separate correlation analysis was undertaken for both TD and WFD children to explore the specific qualitative attributes that influenced word finding. The separate correlation analysis between WFD and TD children are depicted in Table 6 and Table 7 respectively.
Table 6: Correlation coefficients of picture-naming tasks with WPVT, PJ, and CNrep task scores for TD children only
    Picture Naming – % correct
WPVT – % correct Pearson Correlation .760**
Sig. (2-tailed) 0.000
N 25
CNRep -% correct Pearson Correlation .659**
Sig. (2-tailed) 0.000
N 24
   
The Correlation analysis was in line with the findings of the underlying causes that influence word –naming either in TD and WFD children as evident in Table 6. Additionally, Table 7 reflected that the median reaction time for PJ task and picture naming task was significantly and negatively correlated to WPVT accuracy % in TD children. Such findings show that TD children are able to name words accurately as they could retrieve them faster from lexical storage.
Table 7: Correlation coefficients of picture-naming tasks with WPVT, PJ, and CNrep task scores for WFD children only
    Picture Naming – % correct
Picture naming – the median of RTs Pearson Correlation -.699*
Sig. (2-tailed) 0.011
N 12
WPVT – % correct Pearson Correlation .720**
Sig. (2-tailed) 0.008
N 12
_________________________________________________________________________
The findings of correlation in table 7 suggested that word-finding accuracy percentage in WFD children is governed by WPVT ability and the reaction time of retrieval of words from lexical storage.
The results on correlation coefficients and independent t-tests reflected that word-picture verification tasks, phonological ability, and predisposition to mixed errors influenced word finding in the study participants. However, the findings of the correlation analysis and the independent t-tests implied that the different abilities (WPVT, semantic, and phonological abilities) could be aligned to each other in influencing word-naming. The assumptions were supported by the correlation between semantic abilities and phonological abilities in influencing WPVT accuracy percentage) in WFD children (Table 8).
Table 8: Correlations between WPVT task performance, semantic abilities, and phonological abilities
__________________________________________________________________________
    WPVT – % correct PJ Task – % correct
PJ Task – % correct Pearson Correlation 0.279 1
Sig. (2-tailed) 0.094 N 37 37
CNRep -% correct Pearson Correlation .436** -0.045
Sig. (2-tailed) 0.008 0.793
N 36 36
     
___________________________________________________________________________
The correlation analysis reflected that CNrep accuracy percentages were significantly correlated to WPVT accuracy percentage (0.008). Such findings indicated the importance of phonological abilities in influencing word naming accuracy in WFD children. This is because earlier correlation reflected that WPVT accuracy was positively and significantly related to word-naming in both WFD and TD children. The study further elucidated individual differences in test scores in the WFD group (1.25SD compared to individuals with TFD)
Table 9: Individual differences (1.25SD from TFD average) in the test scores in WFD children compared to their TD counterparts.
  Pic nam acc WPVT acc PJ task acc CN rep scor (1.25SD below TD average) for TD
1 29 48 18 70 3
2 25 39 15 106 3
3 32 49 20 104 2
4 41 59 19 109 0
5 26 45 15 83 4
6 44 54 19 114 0
7 41 57 18 102 0
8 35 51 18 89 1
9 40 48 18   1
10 28 58 18 70 2
11 51 58 17 94 0
12 31 42 18 83 3
13 34 56 18 83 2
14 33 45 15 120 3
15 51 56 18 109 0
16 20 40 18 85 3
17 23 36 18 62 3
18 44 54 19 114 0
19 41 57 18 102 0
20 26 47 19 85 3
21 43 54 19 104 0
22 31 45 18 99 2
23 41 51 18 94 0
24 41 57 19 107 0
25 35 51 18 89 1
  35.44 50.28 17.92 94.875  
Errors 12 11 2 10 36
  Pic nam acc WPVT acc PJ task acc CN rep scor 1.25SD below average) in WFD
1 29 44 18 75 3
2 34 52 18 72 2
3 33 51 20 78 3
4 30 52 19 83 2
5 20 40 18 2
6 25 44 19 83 3
7 31 47 19 63 3
8 32 47 20 78 3
9 30 47 17 114 2
10 24 41 16 96 3
11 33 42 17 62 3
12 34 57 16 70 3
Mean 29.58333 47 18.08333 79.45455  
Errors 12 8 2 10 32
________________________________________________________
Table 9 reflected that there was variation in the proportion of individuals in TD and WFD group with respect to 1.25 SD differences for the mean test scores in the TFD group. The proportion of participants who exhibited 1.25SD differences in the test scores across both groups is shown in Figure II and Appendix 1.

Fig 2 reflected that 85 % of the WFD children had lower phonological ability than the average TD On the other hand, the individual differences in the Picture accuracy and WPVT test scores of WFD children at 1.25SD of TD average was almost twice than their TD counterparts.
Section 5: Discussion and Conclusion
The present study provided a comprehensive explanation regarding the underlying causes that influence word finding in children with WFD and TD. The study explored the different attributes that determine speech production related to the retrieval of single words in both groups of experimental participants. The study explored whether word-naming accuracy in WFD and TD children is influenced by the same factors. Table 2 revealed that TD children responded faster and accurately than WFD children for the picture-naming task. The anomalies in the naming accuracy were featured by the different type of semantic, phonological, perceptual, and mixed errors. Table 2 further reflected that the percentage of perceptual errors were comparable across WFD and TD children (p=0.973). Likewise, the percentage of semantic errors across both groups of participants were also comparable (p=0. 206). However, the number of mixed errors was significantly lower in TD children compared to WFD children (p=0.001). WFD children exhibited higher percentage of phonological errors than their TD counterparts (p=0.085). Table 3 reflected that the knowledge of word meanings (as evident from the accuracy of WPVT tasks) were comparable in WFD and TD children (p=0.112).
Although the judgmental or semantic abilities (% accuracy of PJ tasks) were comparable across both the experimental group of participants (p=0.732), children with WFD exhibited a higher median reaction time on PJ tasks compared to their TD counterparts (p=0.046) (Table 4). Hence, children with WFD exhibit difficulty in retrieving appropriate words from lexical storage. Table 5 reflected that children with TD exhibited significantly superior phonological abilities than their WFD counterparts (p=0.006). Such findings suggest that individuals with WFD are unable to appreciate the phonological attributes of a word. The reduction in phonological ability in WFD children was further supported by Fig 2. The Figure 2 reflected that around 58% WFD individuals exhibited a CNrep score that was below 1.25 SD of the average score in their group. On the contrary, the proportion of TD children with such score was 40%. On the contrary, the percentage of individuals in the TD group who exhibited accuracy in picture-naming below 1.25SD of the group average was much higher compared to those in the WFD group (48% versus 25%).
The correlation analysis between different abilities reflected that the phonological abilities were significantly correlated with semantic abilities (median reaction time to PJ task) (p=0.024) and WPVT (p=0.008) (Table 8). TD children showed a significant and positive correlation between picture naming accuracy and phonological ability as well as between picture naming accuracy and WPVT ability (p<0.05) (table 6). On the contrary, WFD children showed significant and positive correlation only between picture naming accuracy and WPVT. Such findings suggest that WPVT was the sole determinant of word-finding accuracy in children with WFD. Hence, it can be contended that children with WFD have impaired phonological ability that reduces their WPVT ability. Likewise, the theories of speech production also endorse that lexical retrieval of the words before they are spoken. Although WFD children have comparable semantic ability to TD children, they are unable to retrieve appropriate lexical items accurately and timely. Such assumptions are supported from the qualitative aspects of errors during the picture naming tasks. To recall, both WFD and TD children exhibited comparable semantic, perceptual, and phonological errors. However, the proportion of mixed errors was significantly more in children with WFD (p<0.05). Such findings signified that children with WFD activated wrong schemas while selecting words from lexical storage that was featured as mixed errors.
The results of the present study were supported by Nadeau, Gonzalez-Rothi & Crosson, 2000). These authors highlighted that word retrieval involve two stages. During the first stage, the semantic description of stimuli is converted into lexical representation. For example, a dog is identified from its features such as ‘furry,’ ‘barking,’ and ‘four-legged’. In the second stage, the word “dog” takes a phonological form. The authors highlighted that a failure to retrieve the target lemma for the respective target (stimulus) gives rise to a different lemma (featured as a word that is spoken with inappropriate semantic and phonological attributes) develop. In other words, inappropriate appreciation of phonological attribute leads to both inappropriate semantic and phonological outputs that underpin word finding difficulty. German et al. (2012) also supported the findings of this study. The authors showed that the translation of orthography to phonography automatically activate semantic representations. However, the authors suggested that if the acquisition process becomes too noisy, additional activation of phonological attributes of the words that are intended to be learned to improve word-naming accuracy. On the other hand, German et al. (2012) showed that improving phonological attributes along with semantic attributes during vocabulary enhancement programs improve word-naming in WFD children. In the present study, children with WFD exhibited significantly lower phonological ability than their TD counterparts (Table 5). Such findings reflect that word finding difficulty in children with WFD stems from lower phonological abilities. Hence, vocabulary intervention programs should aim to make the instruction process less noisy and ensure the improvement of phonological abilities in WFD children. Such assumptions are further supported by Levelt et al. 1999.
Levelt et al. (1999) endorsed that phonological and morphological appreciation of words is important in aiding their retrieval. The present study reflected that the underlying cause of WFD could be explained by the serial processing theory on word-naming. Individuals with WFD exhibit word-naming errors due to their inability to link semantic attributes with the phonological attributes for a word to be named. In fact, Best et al. (2017) confirmed that words that were “treated” were named significantly more accurately and timely (low median reaction times). The major strength of this study was that it appraised the findings based on the evidence-based literature. Moreover, the study design helped to compare the attributes that impacted word-naming in children with WFD or TD. However, the study suffered from certain limitations. The first limitation was regarding the small sample size. The second limitation includes the inability of the authors to eliminate the confounding effects of intelligence of the study participants at baseline. Such limitations could have impacted the results of this study.
This study reflected that Speech and Language Therapists should develop learning aids that would help individuals with language deficits (especially individuals with WFD) to appraise the meaning of words. Such improvements can be brought about by enhancing the phonological ability of individuals with WFD or improving the phonological instructions that are used to teach or learn words with specific meaning. This study postulates that improved phonological stimulation could enhance WPVT skills in children with WFD and TD. Once WPVT skills are improved, it might improve word naming accuracy in affected individuals.
References
Best, W,.Fedor, A., Hughes, L., Kapikian, A., Masterson, J., Roncoli, S., FernPollak, L. & Thomas, M. (2015) Intervening to alleviate word-finding difficulties in children: case series data and a computational modelling foundation, Cognitive Neuropsychology, 32(3-4), 133-168
Best, W., Hughes, L., Masterson, J., Thomas, M., Fedor, A., Roncoli, S., Fern-Pollak ,L., Shepherd, D., Howard, D., Shobbrook, K., &Kapikian, A. (2017): Intervention for children with word-finding difficulties: a parallel group randomised control trial, International Journal of Speech-Language Pathology, DOI: 10.1080/17549507.2017.1348541
Best, W. (2005). Investigation of a new intervention for children with word-finding problems. International Journal of Language and Communication Disorders, 40, 279–318
Bragard, A., Schelstraete, M.-A., Snyers, P., & James, D. G. H. (2012). Word-Finding intervention for children with specific language impairment: A multiple single-case study. Language, Speech, and Hearing Services in Schools, 43, 222–234.
Dockrell, J. E., Messer, D., George, R., &Ralli, A. (2003). Beyond naming patterns in children with WFDs—Definitions for nouns and verbs. Journal of Neurolinguistics, 16, 191–211
Dell, G.S., Schwartz, M.F., Martin, N., Saffran, E.M., & Gagnon, D.A. (1997). Lexical access in aphasic and nonaphasic speakers. Psychological Review, 104, 801–838
Dell, G. S., Faseyitan, O., Nozari, N., Schwartz, M. F., &Coslett, H. B. (2013). Voxel-based lesion parameter mapping: Identifying the neural correlates of a computational model of word production. Cognition, 128(3), 380–396
Ebbels, S. H., Nicoll, H., Clark, B., Eachus, B., Gallagher, A. L., Horniman, K., & Turner, G. (2012). Effectiveness of semantic therapy for word-finding difficulties in pupils with persistent language impairments: A randomized control trial. International Journal of Language & Communication Disorders, 47(1), 35–51
Ebbels, S. H. (2014). Introducing the SLI debate. International Journal of Language & Communication, 49, 377–380.
Fernandez, E, & Cairns, H (2011). Fundamentals of Psycholinguistics. Wiley-Blackwell, 138–140
Forster, K. I., & Forster, J. (2003). DMDX: A windows display program with millisecond accuracy. Behavior Research Methods, Instruments, & Computers, 35(1), 116–124
Friedmann, N., Biran, M., &Dotan, D. (2013). Lexical retrieval and its breakdown in aphasia and developmental language impairment. In Boeckx, C., &Grohann, K. K. (Eds.), The Cambridge Handbook of Biolinguistics (pp. 350–374). Cambridge: Cambridge University Press.
German, D., Schwanke, J. H., &Ravid, R. (2012). Word Finding Difficulties: differentiated Vocabulary Instruction in the Speech and Language Room. Communication Disorders Quarterly, 33, 146–156.
Goldrick, M. (2006). Limited interaction in speech production: Chronometric, speech error and neuropsychological evidence. Language and Cognitive Processes, 21, 817–855
Lorenz, A., & Ziegler, W. (2009). Semantics vs. word-form specific techniques in anomia treatment: A multiple single-case study. Journal of Neurolinguistics, 22(6), 515–537
Li, P., Farkas, I., &MacWhinney, B. (2004). Early lexical development in a self-organizing neural network. Neural Networks, 17, 1345–1362
Lum, J. A. G., Conti-Ramsden, G., Page, D., & Ullman, M. T. (2012). Working, declarative and procedural memory in specific language impairment. Cortex, 48, 1138–1154
Leonard, L., Ellis Weismer, S., Miller, C., Francis, D., Tomblin, J., &Kail, R. (2007). Speed of processing, working memory, and language impairment in children. Journal of Speech, Language and Hearing Research, 50, 408–428.
Levelt, Willem J. M.; Roelofs, A.; & Meyer, AS. (1999). “A theory of lexical access in speech production”. Behav Brain Sci. 22(1), 1–38
Marks, I., & Stokes, S. F. (2010). Narrative-based intervention for word-finding difficulties: a case study. International Journal of Language & Communication Disorders, 45, 586–599
Monaghan, J & Ellis, A. (2002). What exactly interacts with spelling-sound consistency in word naming? Journal of Experimental Psychology: Learning, Memory, and Cognition, 28, 183–206
Messer, D., &Dockrell, J. E. (2006). Children’s Naming and Word-Finding Difficulties: Descriptions and ExplanationJournal of Speech, Language, and Hearing Research, 49, 309-324.
Messer, D., &Dockrell, J. E. (2013). Children with word finding difficulties: continuities and profiles of abilities. First Language, 33, 433–448.
Motsch, H. J., & Marks, D. K. (2015). Efficacy of the Lexicon Pirate strategy therapy for improving lexical learning in schoolage children: A randomized controlled trial. Child Language Teaching and Therapy, 31, 237–255.
Powell, D., Stainthorp, R., Stuart, M., Garwood, H., & Quinlan, P. (2007). An experimental comparison between rival theories of rapid automatized naming performance and its relationship to reading. Journal of Experimental Child Psychology, 98(1), 46–68.
Protopapas, A. (2007). CheckVocal: A program to facilitate checking the accuracy and response time of vocal responses from DMDX. Behavior Research Methods, 39(4), 859–862
Smith-Lock, K. M., Leitao, S., Lambert, L., & Nickels, L. (2013). Effective intervention for expressive grammar in children with specific language impairment. International Journal of Language & Communication Disorders, 48 (3), 265–282.
Smith, J. D. (2012). SCEDs: A systematic review of published research and current standards. Psychological Methods, 17(4), 510–550.
Thomas, M. S. C., &Knowland, V. C. P. (2014). Modelling mechanisms of persisting and resolving delay in language development. Journal of Speech, Language, and Hearing Research, 57, 467–483
Van Hees, S., Angwin, A., McMachon, K., & Copland, D. (2013). A comparison of semantic feature analysis and phonological components analysis for the treatment of naming impairments in aphasia. Neuropsychological Rehabilitation, 23(1), 102–132
Wilson, J., Aldersley, A., Dobson, C., Edgar, S., Harding, C., Luckins, J, &Pring, T. (2015). The effectiveness of semantic therapy for the word finding difficulties of children with severe and complex speech, language and communication needs. Child Language Teaching and Therapy, 31, 7–17
Zens, N. K., Gillon, G. T., & Moran, C. (2009). Effects of phonological awareness and semantic intervention on word-learning in children with SLI. International Journal of Speech Language Pathology, 11(6), 509–524.
Appendix-1
Tests of Normality
Kolmogorov-Smirnova Shapiro-Wilk
Statistic df Sig. Statistic df Sig.
Age .150 25 .151 .960 25 .424
Pic nam acc .146 25 .178 .964 25 .497
WPVT acc .153 25 .134 .934 25 .109
PJ task acc .365 25 .000 .761 25 .000
CN rep scor .139 24 .200* .960 24 .446
*. This is a lower bound of the true significance.
a. Lilliefors Significance Correction
Errors by TD children
Pic nam acc WPVT acc PJ task acc CN rep scor
12 11 3 10
Errors by WFD Children
Pic nam acc WPVT acc PJ task acc CN rep scor
3 5 2 7

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