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BACKGROUND: Accurate measurement of dietary intake throughout childhood is important to monitor children's growth and development and for their long-term health. However, measuring dietary intake in children is challenging because of misreporting, difficulties in establishing portion size, and heavy reliance on proxy reporters. OBJECTIVES: This study aimed to determine the accuracy of self-reported food intake by primary school children aged 7-9 y. METHODS: A total of 105 children (51% boys), aged 8.0 ± 0.8 y, were recruited from three primary schools in Selangor, Malaysia. Individual meal intakes during a school break time were determined using a food photography method as the reference method. The children were then interviewed the following day to assess their recall of their meal intakes the previous day. ANOVA and Kruskal-Wallis tests were used to determine mean differences in the accuracy of reporting food items and amount by age and weight status, respectively. RESULTS: On average, the children achieved 85.8% match rate, 14.2% omission rate, and 3.2% intrusion rate for accuracy in reporting food items. The children also achieved 85.9% correspondence rate and 6.8% inflation ratio for accuracy in reporting food amounts. Children living with obesity had notably higher intrusion rates compared with normal weight children (10.6% vs. 1.9%) (P < 0.05). Children aged >9 y had notably higher correspondence rates, compared with children aged 7 y (93.3% vs. 78.8%) (P < 0.05). CONCLUSIONS: The low omission and intrusion rates and the high correspondence rate indicate that primary school children aged 7-9 y are capable of self-reporting food intake accurately for a lunch meal without proxy assistance. However, to confirm children's abilities to report their daily food intakes, further studies should be conducted to assess the accuracy of children in reporting their food intakes for more than one meal in a day.

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AIMS: National joint registries under-report revisions for periprosthetic joint infection (PJI). We aimed to validate PJI reporting to the Australian Orthopaedic Association National Joint Arthroplasty Registry (AOANJRR) and the factors associated with its accuracy. We then applied these data to refine estimates of the total national burden of PJI. METHODS: A total of 561 Australian cases of confirmed PJI were captured by a large, prospective observational study, and matched to data available for the same patients through the AOANJRR. RESULTS: In all, 501 (89.3%) cases of PJI recruited to the prospective observational study were successfully matched with the AOANJRR database. Of these, 376 (75.0%) were captured by the registry, while 125 (25.0%) did not have a revision or reoperation for PJI recorded. In a multivariate logistic regression analysis, early (within 30 days of implantation) PJIs were less likely to be reported (adjusted odds ratio (OR) 0.56; 95% confidence interval (CI) 0.34 to 0.93; p = 0.020), while two-stage revision procedures were more likely to be reported as a PJI to the registry (OR 5.3 (95% CI 2.37 to 14.0); p ≤ 0.001) than debridement and implant retention or other surgical procedures. Based on this data, the true estimate of the incidence of PJI in Australia is up to 3,900 cases per year. CONCLUSION: In Australia, infection was not recorded as the indication for revision or reoperation in one-quarter of those with confirmed PJI. This is better than in other registries, but suggests that registry-captured estimates of the total national burden of PJI are underestimated by at least one-third. Inconsistent PJI reporting is multifactorial but could be improved by developing a nested PJI registry embedded within the national arthroplasty registry. Cite this article: Bone Jt Open 2022;3(5):367-373.

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OBJECTIVE: To examine factors associated with accurate reporting of private and public health insurance coverage. DATA SOURCES: Minnesota health plan enrollment records provided the sample for the Comparing Health Insurance Measurement Error (CHIME) study, a survey conducted in 2015 that randomly assigned enrollees to treatments that included health insurance questions from the American Community Survey (ACS) or the redesigned Current Population Survey Annual Social and Economic Supplement (CPS). STUDY DESIGN: Reverse record check study that compared CHIME study survey responses to enrollment records of coverage type (direct purchase on and off the Marketplace, Medicaid, or MinnesotaCare), service use, subsidy receipt, and duration of coverage from a major insurer. DATA COLLECTION METHODS: Using matched enrollment and CHIME survey data and logistic regression, we examined correlates of accurate insurance type reporting, including characteristics of the insurance coverage, the covered individual, respondent, and family. PRINCIPAL FINDINGS: Reporting accuracy across treatment and coverage type is high (77%-84%). As with past research, accurate reporting of public insurance is higher for people with characteristics consistent with eligibility for public insurance for both survey treatments. For the ACS treatment, reports of direct purchase insurance are more accurate for enrollees who receive a premium subsidy. CONCLUSIONS: Given the complexity of health insurance measurement and frequently changing policy environment, differences in reporting accuracy across treatments or coverage types are not surprising. Several results have important implications for data editing and modeling routines. First, adding premium and subsidy questions in federal surveys should prove useful given the finding that subsidy receipt is associated with reporting accuracy. Second, across both survey treatments, people whose opportunity structures (race, ethnicity, and income) match public program eligibility are accurate reporters of this coverage. This evidence supports using these commonly collected demographic variables in simulation, imputation, and editing routines.

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BACKGROUND: Age-associated increases in medical complexity, frailty, and cognitive impairment may compromise reliable reporting of medical history. OBJECTIVE: To evaluate the influence of increasing age and cognitive impairment on concordance between reported history of stroke and cerebral infarction, and reported history of diabetes and elevated hemoglobinA1c in community-dwelling older adults. METHODS: The association between participant-specific factors and accurate reporting of stroke or diabetes was evaluated using multivariable logistic regression in 1,401 participants enrolled in longitudinal studies of memory and aging, including 425 participants with dementia (30.3%). Stroke and diabetes were selected as index variables as gold standard measures of both were obtained in all participants: magnetic resonance neuroimaging for cerebral infarcts and hemoglobinA1c (≥6.5%) for diabetes. RESULTS: Concordance between reported history of stroke and imaging-confirmed cerebral infarction was low (sensitivity: 17.4%, 8/46; specificity: 97.9%, 799/816). Small infarcts were strongly associated with inaccurate reporting (OR = 265.8; 95% CI: 86.2, 819.4), suggesting that occult/silent infarcts contributed to discordant reporting. Reporting accuracy was higher concerning diabetes (sensitivity: 83.5%, 147/176; specificity: 96.2%, 1100/1143). A history of hypertension (OR = 2.3; 95% CI: 1.3, 4.2), higher hemoglobinA1c (OR = 1.9; 95% CI: 1.5, 2.4), and hemoglobinA1c compatible with impaired glucose tolerance (OR = 3.1; 95% CI 1.8, 5.3) associated with increased odds of discordant reporting. Cognitive impairment and increased age were not independently associated with reliable reporting. CONCLUSION: Factors beyond advancing age and cognitive impairment appear to drive discordance in reported medical history in older participants. Objective testing for cerebral infarcts or diabetes should be performed when relevant to diagnostic or therapeutic decisions in clinical and research settings.

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OBJECTIVE: To measure the accuracy of survey-reported data on features and type of health insurance coverage. DATA SOURCE: Enrollment records from a private insurer were used as sample for primary survey data collection in spring of 2015 using the Current Population Survey health insurance module. STUDY DESIGN: A reverse record check study where households with individuals enrolled in a range of public and private health insurance plans (including the marketplace) were administered a telephone survey that included questions about general source of coverage (eg, employer), program name (eg, Medicaid), portal, premium, and subsidies. DATA COLLECTION/EXTRACTION METHODS: Survey data were matched back to enrollment records, which indicated coverage status at the time of the survey. Concordance between the records and survey data was assessed. PRINCIPAL FINDINGS: Correct reporting of general source of coverage ranged from 77.8 percent to 98.3 percent across coverage type, premium ranged from 91.6 percent to 96.4 percent, and subsidy ranged from 83.0 percent to 91.0 percent. Using a conceptual algorithm to categorize coverage type resulted in sensitivity of 98.3 percent for employer-sponsored enrollees, and 70.6 percent-77.6 percent for the other coverage types, while specificity ranged from 93.9 percent to 99.4 percent across coverage types. CONCLUSIONS: Survey reports of features of coverage suggest they are viable items to include in an algorithm to categorize coverage type. Findings have implications beyond the CPS, particularly for marketplace enrollees.

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We examined reporting accuracy by meal component (beverage, bread, breakfast meat, combination entrée, condiment, dessert, entrée, fruit, vegetable) with validation-study data on 455 fourth-grade children (mean age = 9.92 ± 0.41 years) observed eating school meals and randomized to one of eight dietary recall conditions (two retention intervals [short, long] crossed with four prompts [forward, meal-name, open, reverse]). Accuracy category (match [observed and reported], omission [observed but unreported], intrusion [unobserved but reported]) was a polytomous nominal item response variable. We fit a multilevel cumulative logit model with item variables meal component and serving period (breakfast, lunch) and child variables retention interval, prompt and sex. Significant accuracy category predictors were meal component (p < 0.0003), retention interval (p < 0.0003), meal-component × serving-period (p < 0.0003) and meal-component × retention-interval (p = 0.001). The relationship of meal component and accuracy category was much stronger for lunch than breakfast. For lunch, beverages were matches more often, omissions much less often and intrusions more often than expected under independence; fruits and desserts were omissions more often. For the meal-component × retention-interval interaction, for the short retention interval, beverages were intrusions much more often but combination entrées and condiments were intrusions less often; for the long retention interval, beverages were matches more often and omissions less often but fruits were matches less often. Accuracy for each meal component appeared better with the short than long retention interval. For lunch and for the short retention interval, children's reporting was most accurate for entrée and combination entrée meal components, whereas it was least accurate for vegetable and fruit meal components. Results have implications for conclusions of studies and interventions assessed with dietary recalls obtained from children.

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BACKGROUND/AIM: The hyperdense middle cerebral artery sign (HMCAS) is a useful clinical sign in the management of acute stroke and may alter time-critical decisions within an emergency setting. Though gold standards have been published, these are rarely used in clinical practice and scans tend to be reported subjectively. It is therefore possible that the level of experience of the doctor reporting the scan may impact on the accuracy of the reporting and hence patient management. This study was designed to evaluate the accuracy in detecting HMCAS across doctors with varying levels of experience. METHODS: Forty doctors were recruited into four categories of experience. Each subject received a brief computer-based tutorial on how to identify an HMCAS and was then asked to report on the presence or absence of an HMCAS in 19 pre-prepared CT scans using a standardised viewing template. RESULTS: The mean (±SE) percentage correct scores increased with experience from 76.8 ± 3.69 among interns and residents to 90.1 ± 2.23 (neurologists and radiologists; p < 0.01). Sensitivity and specificity as well as positive and negative predictive values all increased with experience. In addition, more experienced clinicians were better able to distinguish scans which met the radiological criteria for HMCAS from those which only just failed to do so. CONCLUSIONS: Experienced neurologists and radiologists consistently and accurately reported the presence or absence of HMCAS, whereas less experienced clinicians tended to over-report the presence of HMCAS. This may have implications for the acute management of thromboembolic stroke.

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BACKGROUND: The OPUS (Optimal well-being, development and health for Danish children through a healthy New Nordic Diet) project carried out a school meal study to assess the impact of a New Nordic Diet (NND). The random controlled trial involved 834 children aged 8-11 in nine local authority schools in Denmark. Dietary assessment was carried out using a program known as WebDASC (Web-based Dietary Assessment Software for Children) to collect data from the children. OBJECTIVE: To compare the energy intake (EI) of schoolchildren aged 8-11 estimated using the WebDASC system against the total energy expenditure (TEE) as derived from accelerometers worn by the children during the same period. A second objective was to evaluate the WebDASC's usability. DESIGN: Eighty-one schoolchildren took part in what was the pilot study for the OPUS project, and they recorded their total diet using WebDASC and wore an accelerometer for two periods of seven consecutive days: at baseline, when they ate their usual packed lunches and at intervention when they were served the NND. EI was estimated using WebDASC, and TEE was calculated from accelerometer-derived activity energy expenditure, basal metabolic rate, and diet-induced thermogenesis. WebDASC's usability was assessed using a questionnaire. Parents could help their children record their diet and answer the questionnaire. RESULTS: Evaluated against TEE as derived from the accelerometers worn at the same time, the WebDASC performed just as well as other traditional methods of collecting dietary data and proved both effective and acceptable with children aged 8-11, even with perhaps less familiar foods of the NND. CONCLUSIONS: WebDASC is a useful method that provided a reasonably accurate measure of EI at group level when compared to TEE derived from accelerometer-determined physical activity in children. WebDASC will benefit future research in this area.

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Few studies have examined adolescent reporting accuracy for secondhand smoke exposure (SHSe), and never for youth with cancer. SHSe reporting from adolescents being treated for cancer (Mage=14.92 years, SD=1.67) was examined against parent/guardian reports and urine cotinine among 42 adolescent-parent dyads. Number of days in hospital-based lodgings prior to assessment emerged as the strongest predictor of urine cotinine (ß=-0.46, p=0.003) and adolescent SHSe reporting significantly predicted urine cotinine (ß=0.37, p=0.011) beyond relevant demographic and contextual variables (overall R2=0.40, F(6, 35)=3.90, p=0.004). Findings support adolescents as accurate reporters of discrete SHSe occurrences.