Richard Parsons

The Case for Using the Repeatability Coefficient When Calculating Test-Retest Reliability

The use of standardised tools is an essential component of evidence-based practice. Reliance on standardised tools places demands on clinicians to understand their properties, strengths, and weaknesses, in order to interpret results and make clinical decisions. This paper makes a case for clinicians to consider measurement error (ME) indices Coefficient of Repeatability (CR) or the Smallest Real Difference (SRD) over relative reliability coefficients like the Pearson’s (r) and the Intraclass Correlation Coefficient (ICC), while selecting tools to measure change and inferring change as true. The authors present statistical methods that are part of the current approach to evaluate test–retest reliability of assessment tools and outcome measurements. Selected examples from a previous test–retest study are used to elucidate the added advantages of knowledge of the ME of an assessment tool in clinical decision making. The CR is computed in the same units as the assessment tool and sets the boundary of the minimal detectable true change that can be measured by the tool.

The Cost of Autism Spectrum Disorders

Objective A diagnosis of an autism spectrum disorders is usually associated with substantial lifetime costs to an individual, their family and the community. However, there remains an elusive factor in any cost-benefit analysis of ASD diagnosis, namely the cost of not obtaining a diagnosis. Given the infeasibility of estimating the costs of a population that, by its nature, is inaccessible, the current study compares expenses between families whose children received a formal ASD diagnosis immediately upon suspecting developmental atypicality and seeking advice, with families that experienced a delay between first suspicion and formal diagnosis. Design A register based questionnaire study covering all families with a child with ASD in Western Australia. Participants Families with one or more children diagnosed with an ASD, totalling 521 children diagnosed with an ASD; 317 records were able to be included in the final analysis. Results The median family cost of ASD was estimated to be AUD

Proton Pump Inhibitor–Associated Hypomagnesemia: What Do FDA Data Tell Us?

34,900 per annum with almost 90% of the sum (

Self-management programs conducted within a practice setting: Who participates, who benefits and what can be learned?

29,200) due to loss of income from employment. For each additional symptom reported, approximately

Internet-Based Photoaging Within Australian Pharmacies to Promote Smoking Cessation: Randomized Controlled Trial

1,400 cost for the family per annum was added. While there was little direct influence on costs associated with a delay in the diagnosis, the delay was associated with a modest increase in the number of ASD symptoms, indirectly impacting the cost of ASD. Conclusions A delay in diagnosis was associated with an indirect increased financial burden to families. Early and appropriate access to early intervention is known to improve a childs long-term outcomes and reduce lifetime costs to the individual, family and society. Consequently, a per symptom dollar value may assist in allocation of individualised funding amounts for interventions rather than a nominal amount allocated to all children below a certain age, regardless of symptom presentation, as is the case in Western Australia.

The impact of personal background and school contextual factors on academic competence and mental health functioning across the primary-secondary school transition

BACKGROUND: Proton pump inhibitors (PPIs) are a class of medications indicated for the treatment of gastric acid–related diseases. Hypomagnesemia is a rare but serious adverse effect of PPIs. OBJECTIVE: To address the association between the use of different PPIs and hypomagnesemia by examining the frequency of occurrence of hypomagnesemia among the reported adverse drug reactions from the Food and Drug Administration (FDA) Adverse Event Reporting System database. METHODS: We conducted a cross-sectional study of PPI-associated adverse effect cases reported to the FDA between November 1, 1997, and April 1, 2012. Logistic regression was used to examine the association of sex, age, and different PPIs with hypomagnesemia. χ2 Analysis was conducted to investigate the association of PPI-associated hypomagnesemia with hypocalcemia and hypokalemia. RESULTS: Among 66,102 subjects identified as experiencing 1 or more adverse effects while taking a PPI, 1.0% (n = 693) were reported to have hypomagnesemia. The mean (SD) age of PPI users presenting with hypomagnesemia was 64.4 (12.9) years. Results from logistic regression indicated that, compared with esomeprazole, all other PPIs had a higher rate of hypomagnesemia, with pantoprazole having the highest rate (OR 4.3; 95% CI 3.3–5.7; p < 0.001). The risk of female subjects having hypomagnesemia (OR 0.83; 95% CI 0.71–0.97; p = 0.016) was significantly lower than that of males. Elderly subjects (age >65 years) were at increased risk of PPI-associated hypomagnesemia (OR 1.5; 95% CI 1.2–1.7; p < 0.001). χ2 Analysis showed strong association between hypomagnesemia and both hypocalcemia (p < 0.001) and hypokalemia (p < 0.001). CONCLUSIONS: All PPIs were associated with hypomagnesemia, with esomeprazole having the lowest risk and pantoprazole having the highest risk. The risk of PPI-associated hypomagnesemia was higher in males and the elderly population. Hypocalcemia and hypokalemia commonly coexisted with PPI-associated hypomagnesemia.

Differences in the use of vision and proprioception for postural control in autism spectrum disorder.

OBJECTIVE To investigate the impact of generic and diabetes-specific self-management programs offered in a real world context. METHODS A quasi-experimental design with 12-week follow-up compared Living with a Chronic Condition and Living with Diabetes. Self-report data collected included: Self-management Knowledge and Skills; Health Related Quality of Life (HRQOL); Depression; Social Isolation; Loneliness; Self-efficacy; and Health Behaviours. RESULTS Participants (N=458) in the two programs differed on almost all baseline measures. Both demonstrated statistically significant improvements in Self-management Knowledge and Skills, as well as reductions in depression. In addition to younger age, low HRQOL, high self-efficacy and Positive and Active Engagement in Life, were the clinical factors most likely to lead to improvements in HRQOL and self-efficacy. Changes in different characteristics predicted different outcomes. CONCLUSION Both generic and disease-specific programs led to improved outcomes, despite the two programs attracting significantly different participants. Referral patterns also differed but GP referral rates were low for both. PRACTICE IMPLICATIONS Positive participant outcomes can be achieved in real life clinical settings. While younger people with a positive attitude may appear to gain more, it is important to encourage people from low socio-economic status to enter these programs so that social inequalities in health are not worsened.

Clinical setting influences off-label and unlicensed prescribing in a paediatric teaching hospital

Background Tobacco smoking leads to death or disability and a drain on national resources. The literature suggests that cigarette smoking continues to be a major modifiable risk factor for a variety of diseases and that smokers aged 18-30 years are relatively resistant to antismoking messages due to their widely held belief that they will not be lifelong smokers. Objective To conduct a randomized controlled trial (RCT) of a computer-generated photoaging intervention to promote smoking cessation among young adult smokers within a community pharmacy setting. Methods A trial was designed with 80% power based on the effect size observed in a published pilot study; 160 subjects were recruited (80 allocated to the control group and 80 to the intervention group) from 8 metropolitan community pharmacies located around Perth city center in Western Australia. All participants received standardized smoking cessation advice. The intervention group participants were also digitally photoaged by using the Internet-based APRIL Face Aging software so they could preview images of themselves as a lifelong smoker and as a nonsmoker. Due to the nature of the intervention, the participants and researcher could not be blinded to the study. The main outcome measure was quit attempts at 6-month follow-up, both self-reported and biochemically validated through testing for carbon monoxide (CO), and nicotine dependence assessed via the Fagerström scale. Results At 6-month follow-up, 5 of 80 control group participants (6.3%) suggested they had quit smoking, but only 1 of 80 control group participants (1.3%) consented to, and was confirmed by, CO validation. In the intervention group, 22 of 80 participants (27.5%) reported quitting, with 11 of 80 participants (13.8%) confirmed by CO testing. This difference in biochemically confirmed quit attempts was statistically significant (χ2 1=9.0, P=.003). A repeated measures analysis suggested the average intervention group smoking dependence score had also significantly dropped compared to control participants (P<.001). These differences remained statistically significant after adjustment for small differences in gender distribution and nicotine dependence between the groups. The mean cost of implementing the intervention was estimated at AU

Impact of experience when using the Rapid Upper Limb Assessment to assess postural risk in children using information and communication technologies

5.79 per participant. The incremental cost-effectiveness ratio was AU

The Effect of the Global Positioning System on the Driving Performance of People with Mild Alzheimer's Disease

46 per additional quitter. The mean cost that participants indicated they were willing to pay for the digital aging service was AU