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•Results of this study revealed good agreement between self-reported and direct anthropometric measurements.•Classification of body mass index from self-reported and direct measurements showed that 88% of participants were placed in the same body mass index category.•Findings provide support for the use of online self-reported anthropometric data in this sample of young adults. The aim of this study was to validate self-reported anthropometric measurements and body mass index (BMI) classifications in a young adult population. Both self-reported and directly measured weight and height of 100 young adults 18 to 30 y of age were collected. Participants were measured at one of two university clinics by two research dietitians and within 2 wk self-reported their body weight and height via a questionnaire as part of a larger study. BMI was calculated and categorized according to the World Health Organization's cut-points for underweight, healthy weight, and overweight or obesity. The validity of measured against self-reported weight and height was examined using Pearson's correlation, Bland–Altman plots, and Cohen's kappa statistic. Strong correlation was observed between measured and self-reported weight (r = 0.99; P < 0.001), height (r = 0.95; P < 0.001), and BMI (r = 0.94; P < 0.001). Bland–Altman plots indicated that the mean difference between self-reported and direct BMI measurements were small in the total sample (0.1 kg/m2). The majority of values fell within the limits of agreement (2 SD), with random scatter plots and no systemic bias detected. The classification of BMI from self-reported and direct measurements showed that 88% were placed in the equivalent weight category with very good agreement Cohen's kappa (0.76; 95% confidence interval, 0.63–0.89; P < 0.001). Good agreement was detected between self-reported and direct anthropometric measurements. The criticism of self-reported anthropometric measurements is unwarranted. The findings provide support for using self-reported height and weight data for research in Australian young adults when direct measurements are not feasible.

The notion that digital-screen engagement decreases adolescent well-being has become a recurring feature in public, political, and scientific conversation. The current level of psychological evidence, however, is far removed from the certainty voiced by many commentators. There is little clear-cut evidence that screen time decreases adolescent well-being, and most psychological results are based on single-country, exploratory studies that rely on inaccurate but popular self-report measures of digital-screen engagement. In this study, which encompassed three nationally representative large-scale data sets from Ireland, the United States, and the United Kingdom (N = 17,247 after data exclusions) and included time-use-diary measures of digital-screen engagement, we used both exploratory and confirmatory study designs to introduce methodological and analytical improvements to a growing psychological research area. We found little evidence for substantial negative associations between digital-screen engagement—measured throughout the day or particularly before bedtime—and adolescent well-being.

Sustained attention fluctuates between periods of good and poor attentional performance. Two major methodologies exist to study these fluctuations: an objective approach that identifies \"in-the-zone\" states of consistent response times (RTs) and \"out-of-the-zone\" states of erratic RTs and a subjective approach that asks participants whether they are on-task or mind wandering. Although both approaches effectively predict attentional lapses, it remains unclear whether they capture the same or distinct attentional fluctuations. We combined both approaches within a single sustained attention task requiring frequent responses and response inhibition to rare targets to explore their consistency (N = 40). Behaviorally, both objective out-of-the-zone and subjective mind-wandering states were associated with more attentional lapses. However, the percentage of time spent out-of-the-zone did not differ between on-task and mind-wandering periods and both objective and subjective states independently predicted error-proneness, suggesting that the two methods do not capture the same type of attention fluctuations. Whereas attentional preparation before correct inhibitions was greater during out-of-the-zone compared with in-the-zone periods, preparation did not differ by subjective state. In contrast, posterror slowing differed by both objective and subjective states, but in opposite directions: slowing was observed when participants were objectively out-of-the-zone or subjectively on-task. Overall, our results provide evidence that objective and subjective approaches capture distinct attention fluctuations during sustained attention tasks. Integrating both objective and subjective measures is crucial for fully understanding the mechanisms underlying our ability to remain focused.

AbstractObjectiveTo assess whether percutaneous transforaminal endoscopic discectomy (PTED) is non-inferior to conventional open microdiscectomy in reduction of leg pain caused by lumbar disc herniation.DesignMulticentre randomised controlled trial with non-inferiority design.SettingFour hospitals in the Netherlands.Participants613 patients aged 18-70 years with at least six weeks of radiating leg pain caused by lumbar disc herniation. The trial included a predetermined set of 125 patients receiving PTED who were the learning curve cases performed by surgeons who did not do PTED before the trial.InterventionsPTED (n=179) compared with open microdiscectomy (n=309).Main outcome measuresThe primary outcome was self-reported leg pain measured by a 0-100 visual analogue scale at 12 months, assuming a non-inferiority margin of 5.0. Secondary outcomes included complications, reoperations, self-reported functional status as measured with the Oswestry Disability Index, visual analogue scale for back pain, health related quality of life, and self-perceived recovery. Outcomes were measured until one year after surgery and were longitudinally analysed according to the intention-to-treat principle. Patients belonging to the PTED learning curve were omitted from the primary analyses.ResultsAt 12 months, patients who were randomised to PTED had a statistically significantly lower visual analogue scale score for leg pain (median 7.0, interquartile range 1.0-30.0) compared with patients randomised to open microdiscectomy (16.0, 2.0-53.5) (between group difference of 7.1, 95% confidence interval 2.8 to 11.3). Blood loss was less, length of hospital admission was shorter, and timing of postoperative mobilisation was earlier in the PTED group than in the open microdiscectomy group. Secondary patient reported outcomes such as the Oswestry Disability Index, visual analogue scale for back pain, health related quality of life, and self-perceived recovery, were similarly in favour of PTED. Within one year, nine (5%) in the PTED group compared with 14 (6%) in the open microdiscectomy group had repeated surgery. Per protocol analysis and sensitivity analyses including the patients of the learning curve resulted in similar outcomes to the primary analysis.ConclusionsPTED was non-inferior to open microdiscectomy in reduction of leg pain. PTED resulted in more favourable results for self-reported leg pain, back pain, functional status, quality of life, and recovery. These differences, however, were small and may not reach clinical relevance. PTED can be considered as an effective alternative to open microdiscectomy in treating sciatica.Trial registrationNCT02602093ClinicalTrials.gov NCT02602093.

Mobile health (mHealth) apps have the potential to increase smoking cessation, but little research has been conducted with Aboriginal communities in Australia. We conducted a pilot study to assess the feasibility and acceptability and explore the effectiveness of a novel mHealth app to assist Aboriginal people to quit smoking. A pilot randomized controlled trial (RCT) and process evaluation comprising usage analytics data and in-depth interviews was conducted. Current Aboriginal smokers (>16 years old), who were willing to make a quit attempt in the next month, were recruited from Aboriginal Community Controlled Health Services and a government telephone coaching service. The intervention was a multifaceted Android or iOS app comprising a personalized profile and quit plan, text and in-app motivational messages, and a challenge feature allowing users to compete with others. The comparator was usual cessation support services. Outcome data collection and analysis were conducted blinded to treatment allocation. The primary outcome was self-reported continuous smoking abstinence verified by carbon monoxide breath testing at 6 months. Secondary outcomes included point prevalence of abstinence and use of smoking cessation therapies and services. A total of 49 participants were recruited. Competing service delivery priorities, the lack of resources for research, and lack of support for randomization to a control group were the major recruitment barriers. At baseline, 23/49 (47%) of participants had tried to quit in recent weeks. At 6-month follow-up, only 1 participant (intervention arm) was abstinent. The process evaluation highlighted low to moderate app usage (3-10 new users per month and 4-8 returning users per month), an average of 2.9 sessions per user per month and 6.3 min per session. Key themes from interviews with intervention participants (n=15) included the following: (1) the powerful influence of prevailing social norms around acceptability of smoking; (2) high usage of mobile devices for phone, text, and social media but very low use of other smartphone apps; (3) the role of family and social group support in supporting quit attempts; and (4) low awareness and utilization of smoking cessation support services. Despite the broad acceptability of the app, participants also recommended technical improvements to improve functionality, greater customization of text messages, integration with existing social media platforms, and gamification features. Smoking cessation apps need to be integrated with commonly used functions of mobile phones and draw on social networks to support their use. Although they have the potential to increase utilization of cessation support services and treatments, more research is needed to identify optimal implementation models. Robust evaluation is critical to determine their impact; however, an RCT design may not be feasible in this setting. Australian and New Zealand Clinical Trials Registry ACTRN12616001550493; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=371792 (Archived by WebCite at http://www.webcitation.org/76TiV7HA6).

Dental caries and periodontitis account for a vast burden of morbidity and healthcare spending, yet their genetic basis remains largely uncharacterized. Here, we identify self-reported dental disease proxies which have similar underlying genetic contributions to clinical disease measures and then combine these in a genome-wide association study meta-analysis, identifying 47 novel and conditionally-independent risk loci for dental caries. We show that the heritability of dental caries is enriched for conserved genomic regions and partially overlapping with a range of complex traits including smoking, education, personality traits and metabolic measures. Using cardio-metabolic traits as an example in Mendelian randomization analysis, we estimate causal relationships and provide evidence suggesting that the processes contributing to dental caries may have undesirable downstream effects on health. Dental caries and periodontitis are among the most common medical conditions. Here, the authors report a GWAS for measures of oral health that reveals 47 risk loci for caries, find genetic correlation with 31 other complex traits and use Mendelian randomization analyses to explore potential causal relationships.

Introduction Sleep is critical for memory, but research indicates that eyewitness identification may be an exception. We conducted three experiments to assess the effect of self-reported sleep duration and quality, and current sleepiness on eyewitness recall for a mock crime and suspect identification. Experiments 1 and 2 looked at pre-encoding sleep on lineups and showups, respectively. Experiment 3 investigated lineups across two days to assess retrieval effects. Methods Participants viewed a mock crime video then answered sleep questions as well as central and peripheral recall questions over the crime. Participants were then randomly assigned to view a fair 6-person target-present (TP) or target-absent (TA) lineup for experiments 1 and 3, or a TP or TA showup for experiment 2. In experiment 3, the recall questions and lineups occurred on day 2, but the sleep questions were asked both days. Decision confidence was provided after the identification procedure. Results Sleep quality predicted central recall for experiment 1 [F(1, 3834)=12.96, p<.001] whereas sleep quantity predicted central recall for experiment 2, F(1, 2712)=36.22, p< .001. Choosing rate for pre-encoding sleep was higher for low quality [X2(1)=29.10, p<.001] and low duration [X2(1)=20.15, p<.001], but false IDs were lower for high duration [X2(1)=29.76, p<.001] and high quality, X2(1)=35.47, p<.001. High quality self-reported sleep increased discriminability for lineups, G=2.14, p=.016. False IDs for showups were lower for high duration [X2(1)=5.27, p=.024] and all three sleep questions predicted discriminability for showups: more sleep (G=2.85, p=.002), better sleep (G=2.60, p=.005), and less sleepiness, G=2.44, p=.007. Showups had greater accuracy (p=.038) and a stronger confidence-accuracy relationship (p<.001) for the average of the “good sleep” conditions than the average of the three “bad sleep” conditions, p=.022. In experiment 3, involving post-encoding self-reported sleep, there were still effects on recall but minimal effects on eyewitness identification (and no effects on discriminability). Conclusion Self-reported sleep for the night prior to the crime could be an important individual difference variable for eyewitness memory, affecting encoding more than post-encoding processes. Support (if any) This project was supported by Grant 2018-R2-CX-0027 awarded by the National Institute of Justice, Office of Justice Programs, and U.S. Department of Justice.

Introduction Despite being used and widely recommended since the 1970s, few studies have examined whether adherence to sleep hygiene practices affect objectively measured sleep in non-clinical populations. While individual components of sleep hygiene such as limiting caffeine and alcohol consumption are clearly related to sleep by plausible physiological and psychosocial mechanisms, the real-world evidence of overall sleep hygiene practices on sleep is surprisingly inconsistent. Here, we examined the association between self-reported sleep hygiene practices and objectively measured sleep in a general population. Methods Responses to a survey on sleep hygiene were used and matched with objective sleep data, resulting in data from 720 users (mean age: 52.5 ± 15.9, 63.4% female). Objective sleep data across 92,808 nights were included in the analysis from the PSG-validated SleepScore Mobile Application, which uses a non-contact sonar-based method to capture sleep-related metrics and self-reported lifestyle. Self-reported sleep hygiene practices were assessed with 13-items on a 5-point scale ranging from “Never” to “Always”. Descriptive statistics and linear regressions were used for the analysis, controlling for age and gender. Results Overall, the top three most frequented poor sleep hygiene practices were going to bed at different times (29.7%), overthinking/worrying in bed (24.0%), and waking at different times (22.7%). Linear regressions revealed a significant negative association between composite sleep hygiene scores and objective sleep measures, whereby poorer sleep hygiene was associated with significant reductions in total sleep time (ß=-0.89, SE=0.33, p< 0.01), REM duration (ß=-0.24, SE=0.10, p< 0.05), and SleepScore (ß=-0.15, SE=0.05, p< 0.01), an objective sleep quality metric. No significant associations were observed between individual sleep hygiene factors and objectively measured sleep. Conclusion While we could not identify a relationship between individual hygiene factors and sleep, poorer aggregated sleep hygiene scores were associated with poorer objectively measured sleep. Thus, sleep health may not be defined by one single behavior, but rather by the sum of its parts. Future work should examine the efficacy of personalized sleep hygiene factors in sub-clinical populations, where targeted sleep hygiene education may be preferred given it is more intuitive and less burdensome than other behavioral interventions. Support (if any) SleepScore Labs

Introduction Accurate measurement of sleep is a challenge for researchers and practitioners. Objective measures (i.e., polysomnography, actigraphy) are expensive and time-consuming. Thus, the practical approach is self-report – with the cost of reduced validity. The purpose of this actigraphy ­experiment was to compare the validity of differently ­formatted self-reported sleep duration measures. It was hypothesized that question formats which encourage duration reporting to the nearest 15 minutes would lead to improved validity. Methods Adults (n=56, 73.2% female, 80.4% white, mean age = 21.3 years, SD = 4.18) were recruited through university email, a psychology participant pool, and word of mouth. Sleep was recorded via actigraphy for 7 days. Participants were randomly assigned to respond via computer to one of three versions of the Pittsburgh Sleep Quality Index (Buysse et al., 1989). Specifically, they reported hours of sleep per night in one of the following formats: 1) Open-ended response with standard instructions 2) Open-ended with modified instructions to “round to the nearest 15-minutes”, or 3) Standard instructions with drop-down menus to select hours and minutes (15-minute increments). Results Self-reported and actigraphy sleep duration were strongly correlated, r = .63, p < .001. Average self-reported duration (7.05 hours) was significantly longer than actigraphy average (M = 6.65 hours), t(55) = 3.27, p < .01, d = 0.44. There were no significant differences across the three self-reported sleep duration formats, F(2, 53) = 0.02, p = .98, η2 = .00. As expected, the open-ended standard format had the weakest correlation with actigraphy (r = .47), whereas the open-ended with modified instructions (r = .74) and drop-down menu (r = .68) versions were better predictors of actigraphy duration. The effect sizes for the improvement (q = .44, .32) were medium in magnitude (Cohen, 1969). Conclusion The results suggest that researchers and practitioners should consider the format of self-report sleep duration questions. We found formats that encourage participants the reporting of more precise estimates to more strongly predict actigraphy. Additional data is needed to replicate these findings, and for a better understanding of the factors that influence the magnitude of agreement between objective and subjectively reported sleep duration. Support (if any)