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The language-screening instrument SNEL

The Dutch well child language screening protocol for 2-year-old children was valid for detecting current and later language problems

AIM: Little is known about predictive validity of and professionals' adherence to language screening protocols. This study assessed the concurrent and predictive validity of the Dutch well child language screening protocol for two-year-old children and the effects of protocol deviations by professionals.METHODS: A prospective cohort study of 124 children recruited and tested between October 2013 and December 2015. Children were recruited from four well child clinics in urban and rural areas. To validate the screening, we assessed children's language ability with standardized language tests following the two-year screening and one year later. We assessed the concurrent and predictive validity of the screening and of protocol deviations.RESULTS: At two years, the sensitivity and specificity of the language-screening were 0.79 and 0.86, and at three years 0.82 and 0.74, respectively. Protocol deviations by professionals were rare (7%) and did not significantly affect the validity of the screening.CONCLUSION: The language-screening protocol was valid for detecting current and later language problems. Deviations from the protocol by professionals were rare and did not affect the concurrent nor predictive validity of the protocol. The two-year language screening supports professionals working in preventive child health care and deserves wider implementation in well child care.

Validation of the Early Language Scale

The aim of this study was to assess the criterion validity of a new screening instrument, the Early Language Scale (ELS), for the identification of young children at risk for developmental language disorder (DLD), and to determine optimal age-adjusted cut-off scores. We recruited a community-based sample of 265 children aged 1 to 6 years of age. Parents of these children responded on the ELS, a 26-item "yes-no" questionnaire. The children were assessed with extended language tests (language comprehension, word production, sentence production, communication). A composite score out of these tests (two tests below - 1 SD or one below - 1.5 SD) was used as reference standard. We assessed the validity of the ELS, measured by sensitivity, specificity, predictive values, and AUC. The optimal sensitivity/specificity age-dependent cut-off ELS score was at 15th percentile. Sensitivity and specificity were 0.62 and 0.93, respectively. Positive predictive value was moderate (0.53), negative predictive value was high (0.95), the positive likelihood ratio was 9.16, and negative likelihood ratio was 0.41. The area under the ROC curve was 0.88. The items covered the increasing language development for the ages from 1 to 6.Conclusion: The ELS is a valid instrument to identify children with DLD covering an age range of 1 to 6 years in community-based settings.What is Known:• Early identification and treatment of developmental language disorders can reduce negative effects on children's emotional functioning, academic success, and social relationships.• Short, validated language screening instruments that cover the full age range of early childhood language development lack.What is New:• The 26-item Early Language Scale (ELS) is a valid instrument to identify children at risk for developmental language disorder in well-child care and early educational settings among Dutch children aged 1-6 years.

Children with language delay referred to Dutch speech and hearing centres: caseload characteristics

Background: Early detection and remediation of language disorders are important in helping children to establish appropriate communicative and social behaviour and acquire additional information about the world through the use of language. In the Netherlands, children with (a suspicion of) language disorders are referred to speech and hearing centres for multidisciplinary assessment. Reliable data are needed on the nature of language disorders, as well as the age and source of referral, and the effects of cultural and socioeconomic profiles of the population served in order to plan speech and language therapy service provision. Aims: To provide a detailed description of caseload characteristics of children referred with a possible language disorder by generating more understanding of factors that might influence early identification. Methods & Procedures: A database of 11,450 children was analysed consisting of data on children, aged 2–7 years (70% boys, 30% girls), visiting Dutch speech and hearing centres. The factors analysed were age of referral, ratio of boys to girls, mono‐ and bilingualism, nature of the language delay, and language profile of the children. Outcomes & Results:Results revealed an age bias in the referral of children with language disorders. On average, boys were referred 5 months earlier than girls, and monolingual children were referred 3 months earlier than bilingual children. In addition, bilingual children seemed to have more complex problems at referral than monolingual children. They more often had both a disorder in both receptive and expressive language, and a language disorder with additional (developmental) problems. Conclusions & Implications: This study revealed a bias in age of referral of young children with language disorders. The results implicate the need for objective language screening instruments and the need to increase the awareness of staff in primary child healthcare of red flags in language development of girls and multilingual children aiming at earlier identification of language disorders in these children.

Language Sample Analysis in Clinical Practice: Speech-Language Pathologists’ Barriers, Facilitators, and Needs

Purpose: Most speech-language pathologists (SLPs) working with children with developmental language disorder (DLD) do not perform language sample analysis (LSA) on a regular basis, although they do regard LSA as highly informative for goal setting and evaluating grammatical therapy. The primary aim of this study was to identify facilitators, barriers, and needs related to performing LSA by Dutch SLPs working with children with DLD. The secondary aim was to investigate whether a training would change the actual performance of LSA. Method: A focus group with 11 SLPs working in Dutch speech-language pathology practices was conducted. Barriers, facilitators, and needs were identified using thematic analysis and categorized using the theoretical domain framework. To address the barriers, a training was developed using software program CLAN. Changes in barriers and use of LSA were evaluated with a survey sent to participants before, directly after, and 3 months posttraining. Results: The barriers reported in the focus group were SLPs’ lack of knowledge and skills, time investment, negative beliefs about their capabilities, differences in beliefs about their professional role, and no reimbursement from health insurance companies. Posttraining survey results revealed that LSA was not performed more often in daily practice. Using CLAN was not the solution according to participating SLPs. Time investment remained a huge barrier. Conclusions: A training in performing LSA did not resolve the time investment barrier experienced by SLPs. User-friendly software, developed in codesign with SLPs might provide a solution. For the short-term, shorter samples, preferably from narrative tasks, should be considered.

Malnutrition screening tools are not sensitive enough to identify older hospital patients with malnutrition

This study evaluates the concurrent validity of five malnutrition screening tools to identify older hospitalized patients against the Global Leadership Initiative on Malnutrition (GLIM) diagnostic criteria as limited evidence is available. The screening tools Short Nutritional Assessment Questionnaire (SNAQ), Malnutrition Universal Screening Tool (MUST), Malnutrition Screening Tool (MST), Mini Nutritional Assessment—Short Form (MNA-SF), and the Patient-Generated Subjective Global Assessment—Short Form (PG-SGA-SF) with cut-offs for both malnutrition (conservative) and moderate malnutrition or risk of malnutrition (liberal) were used. The concurrent validity was determined by the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and the level of agreement by Cohen’s kappa. In total, 356 patients were included in the analyses (median age 70 y (IQR 63–77); 54% male). The prevalence of malnutrition according to the GLIM criteria without prior screening was 42%. The conservative cut-offs showed a low-to-moderate sensitivity (32–68%) and moderate-to-high specificity (61–98%). The PPV and NPV ranged from 59 to 94% and 67–86%, respectively. The Cohen’s kappa showed poor agreement (k = 0.21–0.59). The liberal cut-offs displayed a moderate-to-high sensitivity (66–89%) and a low-to-high specificity (46–95%). The agreement was fair to good (k = 0.33–0.75). The currently used screening tools vary in their capacity to identify hospitalized older patients with malnutrition. The screening process in the GLIM framework requires further consideration.