Natural History of Stuttering to 4 Years of Age: A Prospective Community-Based Study

These findings from a community-ascertained cohort refute long-held views suggesting that developmental stuttering is associated with a range of poorer outcomes. If anything, the reverse was true, with stuttering predicting subsequently better language,nonverbal skills, and psychosocial health-related quality of life at 4 years of age.Future research with this cohort will support a more complete longitudinal understanding of when and in whom recovery occurs. Current best practice recommends waiting for 12 monthsbefore commencing treatment, unlessthe child is distressed, there is parental concern, or the child becomes reluctant to communicate. It may be that for many children treatment could be deferred even longer. Treatment is efficacious15 but is both intensive (median of 15.4o ne-hour clinical sessions followedby 10 one-hour clinical maintenance sessions) and expensive; this "watchful waiting" recommendation would therefore help target allocation of scarce resources to the small number of children who do not resolve and experience adverse outcomes, secure in the knowledge that delaying treatment by a year or more has been shown not to compromise treatment efficac

Predicting death in young offenders: a retrospective cohort study

Objective: To examine predictors of death in young offenders who have received a custodial sentence using data routinely collected by juvenile justice services. Design: A retrospective cohort of 2849 (2625 male) 11–20-year-olds receiving their first custodial sentence between 1 January 1988 and 31 December 1999 was identified. Main outcome measures: Deaths, date and primary cause of death ascertained from study commencement to 1 March 2003 by data-matching with the National Death Index; measures comprising year of and age at admission, sex, offence profile, any drug offence, multiple admissions and ethnic and Indigenous status, obtained from departmental records. Results: Theoverallmortalityratewas7.2deathsper1000person-yearsofobservation. Younger admission age (hazard ratio [HR], 1.4; 95% CI, 1.0–1.9), repeat admissions (HR, 1.8; 95% CI, 1.1–2.9) and drug offences (HR, 1.5; 95% CI, 1.0–2.1) predicted early death. The role of ethnicity/Aboriginality could only be assessed in cohort entrants from 1996 to 1999. The Asian subcohort showed higher risk of death from drug-related causes (HR, 2.5; 95% CI, 1.1–5.5), more drug offences (relative risk ratio [RRR], 13; 95% CI, 8.5–20.0) and older admission age (oldest group v youngest: RRR, 9.3; 95% CI, 1.3–68.0) than non- Indigenous Australians. Although higher mortality was not identified in Indigenous Australians, this group was more likely to be admitted younger (oldest v youngest: RRR, 0.31; 95% CI, 0.15–0.63) and experience repeat admissions (RRR, 1.6; 95% CI, 1.0–2.4). Conclusions: Young offenders have a much higher death rate than other young Victorians. Early detention, multiple detentions and drug-related offences are indicators of high mortality risk. For these offenders, targeted healthcare while in custody and further mental healthcare and social support after release appear essential if we are to reduce the mortality rate in this group

Mutable-distal predictors: measures, age of measurement, and derivation.

<p>^aAustralian Bureau of Statistics. (2001). <i>Socio-Economic Indexes for Areas</i>. Canberra: Australian Bureau of Statistics.</p><p>^bMHVS Raven, J., Raven, J. C. and Court. J. H. (1998). Manual for Raven’s Progressive Matrices and Vocabulary Scales. Section 5: The Mill Hill Vocabulary Scale. San Antonio, TX: Harcourt Assessment;</p><p>^cWRAT—Wilkinson, G. S., and Robertson, G. J. (2006) <i>The Wide Range Achievement Test-4th edition</i> Lutz, FL: Psychological Assessment Resources</p><p>Mutable-distal predictors: measures, age of measurement, and derivation.</p

Random sample of ‘empirical growth’ plots—Individual OLS trajectories for 1 child in 10 (N = 83).

<p>Random sample of ‘empirical growth’ plots—Individual OLS trajectories for 1 child in 10 (N = 83).</p

Least-mutable predictors: measures, age of measurement, derivation and criteria and evidence for categorisation.

<p>Key to Criteria: 1) cannot be modified through intervention as the factor is biologically driven; 2) comorbid diagnoses such as ADHD, ASD or Learning Disability whose symptoms can be ameliorated to a degree but which cannot be removed entirely; and 4) it would be unethical or impracticable to target in an intervention.</p><p>*presented only where criteria for assignment to ‘least mutable’ category is number 3) evidence of limited responsiveness to intervention</p><p>^a KBIT-2—Kaufman, A. S., and N. L. Kaufman. (2004). <i>Kaufman Brief Intelligence Test</i>. <i>2nd ed</i>. Bloomington, MN: Pearson;</p><p>^bATS—Prior, M., Sanson, A., & Oberklaid, F. (1989). The Australian temperament project. In G. Kohnstamm, J. Bates, &M. Rothbart (Eds.), <i>Temperament in childhood</i> (pp. 537–554). Chichester: Wiley</p><p>Least-mutable predictors: measures, age of measurement, derivation and criteria and evidence for categorisation.</p

Mutable-proximal predictors: measures, age of measurement, derivation and evidence for potential to be modified through intervention.

<p>^aSDQ—Goodman, R. (1997). The Strengths and Difficulties Questionnaire: a research note. <i>Journal of Child Psychology and Psychiatry</i>, <i>38</i>, 581–586;</p><p>^bGFTA—Goldman R, Fristoe M. (2000) <i>Goldman-Fristoe Test of Articulation 2</i>. <i>2nd edn</i>. Circle Pines, MN: American Guidance Service</p><p>Mutable-proximal predictors: measures, age of measurement, derivation and evidence for potential to be modified through intervention.</p

Multivariate growth trajectory models 1, 2 and 3: variance components for Mean CELF scaled standard score at 4 years (intercept) Growth rate per year 4–7 years (slope) and Pseudo R².

<p>Multivariate growth trajectory models 1, 2 and 3: variance components for Mean CELF scaled standard score at 4 years (intercept) Growth rate per year 4–7 years (slope) and Pseudo R².</p

Scatterplot of the relationship between Language Z score at 4 years (intercept) and rate of change in Language Z scores per year from 4–7 years (slope).

<p>Scatterplot of the relationship between Language Z score at 4 years (intercept) and rate of change in Language Z scores per year from 4–7 years (slope).</p