Attention/Deficit Hyperactivity Disorder in Adolescent and Young Adult Males With Fragile X Syndrome.

This study characterized the rates of attention-deficit/hyperactivity disorder (ADHD) in adolescent and young adult males with fragile X syndrome (FXS) using a multi-method approach integrating a DSM-based parent interview (Children's Interview for Psychiatric Syndromes; P-ChIPS, Fristad et al., 1998) and a parent rating scale (Child Behavior Checklist; CBCL, Achenbach, 2001). Thirty-one males with FXS, aged 16-24 years, participated. Forty-two percent met DSM-5 criteria for ADHD and 35% exceeded the CBCL cut-offs. Agreement between the two classification methods was fair (κ = 0.38). Autism symptom severity and nonverbal cognitive ability did not predict ADHD diagnoses/symptoms. Results show high rates of ADHD in males with FXS during late adolescence and young adulthood, which are not accounted for by impaired nonverbal cognitive skills or autism symptom severity. DSM-based ADHD-specific scales are recommended over broadband symptom scales to improve accurate identification.

Lessons Learned in Providing Claims-Based Data to Participants in Health Care Innovation Models.

The Centers for Medicare & Medicaid Services (CMS) has been providing data to organizations participating in a range of innovation models to help them implement interventions and to provide feedback on performance. The authors studied 18 CMS models to gain a better understanding of factors contributing to model participants' use or nonuse of CMS-provided data. Factors that contribute to greater use include providing data that participants view as actionable, some type of accountability for performance, robust learning support, participants having resources to work with the data, and soliciting ongoing feedback about the data and related learning needs. Factors that discourage data uptake include time lag, lack of aggregated multi-payer data, exclusion of data for sensitive diagnoses, and small sample sizes. Claims-based data from payers can be an important source of information to innovation model participants. Lessons from this study can increase the usefulness of such data.

A comparison of scoring models for computerised mental health screening for federal prison inmates.

BACKGROUND: There are high rates of mental disorder in correctional environments, so effective mental health screening is needed. Implementation of the computerised mental health screen of the Correctional Service of Canada has led to improved identification of offenders with mental health needs but with high rates of false positives. AIMS: The goal of this study is to evaluate the use of an iterative classification tree (ICT) approach to mental health screening compared with a simple binary approach using cut-off scores on screening tools. METHODS: A total of 504 consecutive admissions to federal prison completed the screen and were also interviewed by a mental health professional. Relationships between screening results and more extended assessment and clinical team discussion were tested. RESULTS: The ICT was more parsimonious in identifying probable 'cases' than standard binary screening. ICT was also highly accurate at detecting mental health needs (AUC=0.87, 95% CI 0.84-0.90). The model identified 118 (23.4%) offenders as likely to need further assessment or treatment, 87% of whom were confirmed cases at clinical interview. Of the 244 (48.4%) offenders who were screened out, only 9% were clinically assessed as requiring further assessment or treatment. Standard binary screening was characterised by more false positives and a comparable false negative rate. CONCLUSIONS: The use of ICTs to interpret screening data on the mental health of prisoners needs further evaluation in independent samples in Canada and elsewhere. This first evaluation of the application of such an approach offers the prospect of more effective and efficient use of the scarce resource of mental health services in prisons. Although not required, the use of computers can increase the ease of implementing an ICT model.

Measuring adherence with the Doser CT in children with asthma.

Non-adherence with prescribed asthma treatment causes compromised treatment effectiveness, including greater morbidity, mortality, and health care utilization costs. As a result, there is an increasing interest in measuring patient adherence behaviors. Electronic monitoring devices offer a promising method for assessing patient adherence behavior patterns. The reliability of the Doser Clinical Trials (CT) (Meditrack Products, Hudson, MA), an inexpensive, pressure-actuated device that monitors metered-dose inhaler (MDI) usage, was evaluated in a field study of outpatient pediatric asthmatics. Canister weight and various Doser CT measures of patient medication use were compared to determine the reliability and usefulness of the device. Doser CTs were dispensed to 16 research subjects for use on corticosteroid MDIs over a period of several months. One Doser CT per month was dispensed to each subject. Doser CTs were collected at 30-60 day intervals, with a total of 61 months of Doser CT data obtained across the subjects. MDI canister weights were monitored for a subset of 6 subjects. Usable Doser CT data were summarized and average adherence estimates were computed. Adherence estimates differed from one another and the adherence estimate, as measured by canister weight, was significantly higher than each Doser CT estimate. However, overall, the Doser CT showed adequate reliability as evidenced by high correlations among the Doser CT estimates of adherence and the existing gold standard of canister weight. The Doser CT is likely to be useful for monitoring MDI use in clinical care and research, potentially providing greater accuracy than the standard of canister weight.

Relations among asthma knowledge, treatment adherence, and outcome.

BACKGROUND: Asthma knowledge is frequently assumed to be a prerequisite for optimal asthma treatment. However, the validity of existing asthma knowledge questionnaires has not been rigorously examined, and no contemporary measure of asthma knowledge has received widespread acceptance. OBJECTIVE: To construct and examine the psychometric properties of an asthma knowledge instrument, and its association with demographic and psychosocial variables, asthma medication adherence, and treatment outcome. METHODS: A 25-item Asthma Knowledge Questionnaire was developed with input from national pediatric asthma experts. Parents of 155 children with asthma completed the Asthma Knowledge Questionnaire as well as demographic, family functioning, and home environment measures. Asthma outcomes and adherence with inhaled medication was measured across 12 months. RESULTS: Despite the many steps taken to develop a strong measure of asthma knowledge, reliability was relatively poor. There was also no association between asthma knowledge and treatment adherence or outcomes. Furthermore, asthma knowledge was not a unidimensional construct and was not a simple function of education. CONCLUSIONS: Findings from this study, in combination with previous studies of asthma knowledge questionnaires, suggest that the construction of a simple self-report asthma knowledge instrument for use as a primary outcome measure demonstrating mastery of asthma self-management skills may not be achievable.