Platform For Recruitment Research Articles

A Motivational Interviewing Chatbot With Generative Reflections for Increasing Readiness to Quit Smoking: Iterative Development Study.

The motivational interviewing (MI) approach has been shown to help move ambivalent smokers toward the decision to quit smoking. There have been several attempts to broaden access to MI through text-based chatbots. These typically use scripted responses to client statements, but such nonspecific responses have been shown to reduce effectiveness. Recent advances in natural language processing provide a new way to create responses that are specific to a client's statements, using a generative language model. This study aimed to design, evolve, and measure the effectiveness of a chatbot system that can guide ambivalent people who smoke toward the decision to quit smoking with MI-style generative reflections. Over time, 4 different MI chatbot versions were evolved, and each version was tested with a separate group of ambivalent smokers. A total of 349 smokers were recruited through a web-based recruitment platform. The first chatbot version only asked questions without reflections on the answers. The second version asked the questions and provided reflections with an initial version of the reflection generator. The third version used an improved reflection generator, and the fourth version added extended interaction on some of the questions. Participants' readiness to quit was measured before the conversation and 1 week later using an 11-point scale that measured 3 attributes related to smoking cessation: readiness, confidence, and importance. The number of quit attempts made in the week before the conversation and the week after was surveyed; in addition, participants rated the perceived empathy of the chatbot. The main body of the conversation consists of 5 scripted questions, responses from participants, and (for 3 of the 4 versions) generated reflections. A pretrained transformer-based neural network was fine-tuned on examples of high-quality reflections to generate MI reflections. The increase in average confidence using the nongenerative version was 1.0 (SD 2.0; P=.001), whereas for the 3 generative versions, the increases ranged from 1.2 to 1.3 (SD 2.0-2.3; P<.001). The extended conversation with improved generative reflections was the only version associated with a significant increase in average importance (0.7, SD 2.0; P<.001) and readiness (0.4, SD 1.7; P=.01). The enhanced reflection and extended conversations exhibited significantly better perceived empathy than the nongenerative conversation (P=.02 and P=.004, respectively). The number of quit attempts did not significantly change between the week before the conversation and the week after across all 4 conversations. The results suggest that generative reflections increase the impact of a conversation on readiness to quit smoking 1 week later, although a significant portion of the impact seen so far can be achieved by only asking questions without the reflections. These results support further evolution of the chatbot conversation and can serve as a basis for comparison against more advanced versions.

Merits and Pitfalls of Social Media as a Platform for Recruitment of Study Participants.

Efficient and effective methods of recruiting participants for studies have characteristically come with many challenges. The unprecedented rise of social media platforms such as Facebook and Instagram has revolutionized the ease of recruiting participants as compared to more traditional methods such as newspaper or radio advertisements. While these new advancements may seem to increase the success of recruitment, they are not without their own faults and limitations. In this paper, we intend to dissect the advantages and disadvantages of social media platforms in recruiting participants. Specifically, we will discuss the advantages of targeted and rapid recruitment, engagement, and cost reduction as well as the disadvantages of representativeness, privacy concerns, limited control, and limited access.

FRI147 A Direct-To-Patient Primary Aldosteronism Screening Program In The United States: Implementing Guidelines Nationwide

Abstract Disclosure: J.M. Brown: Consulting Fee; Self; Bayer, Inc. B. Bacare: None. Y.M. Niebuhr: None. L.C. Tsai: None. E.E. Abel: None. B. Honzel: None. A. Vaidya: Consulting Fee; Self; Corcept Therapeutics, HRA Pharmaceuticals, Mineralys. Context: Primary aldosteronism (PA) is a prevalent but grossly underrecognized contributor to the global burden of hypertension, excess cardiovascular and renal disease, and death. Though Endocrine Society guidelines recommend high risk populations who should be screened for PA, fewer than 2% of these at-risk patients are ever tested. Given the poor rates of routine screening within guideline-eligible populations, we designed and implemented a direct-to-patient virtual-based PA screening intervention. Methods: Participants with one or more guideline indications for PA screening were recruited using social media, online recruitment platforms, and online patient portals to participate in a video visit to review medical history and to arrange a local reference lab draw for plasma renin activity (PRA), aldosterone (via LC-MS/MS), and a basic metabolic panel, without adjustment of medications. Screening results were categorized as “Likely Confirmed PA”, “Possible PA”, or “Unlikely PA” based on established diagnostic frameworks. Test results, their interpretations, and possible next clinical steps (i.e., further testing, referral, empiric treatment) were communicated directly to patients and their primary care providers, with annual reminders and follow-up. Results: To date, 3220 participants from 12 states in the eastern USA had been contacted, with 2504 eligible. At the time of submission, 212 participants had completed laboratory assessment, with the remainder pending. 79 (37.3%) participants had resistant hypertension, 95 (44.8%) had hypertension with hypokalemia, 75 (35.4%) had hypertension with sleep apnea, 11 (5.2%) had hypertension with adrenal mass, and 90 (42.5%) had hypertension with a family history of early hypertension and/or stroke. Indicated PA screening had not previously been performed despite access to specialist care: 55% had an endocrinologist, cardiologist, and/or nephrologist. 27.4% of the participants had screening results consistent with either “likely confirmed PA” (7.1%) or “possible PA” (20.3%). Of those with both resistant hypertension and hypokalemia, 35.0% met criteria for “likely confirmed” or “possible” PA. A “likely confirmed” diagnosis of PA was associated with a median aldosterone-to-renin ratio of 33 ng/dL per ng/mL/h [IQR: 24, 76] and prevalent cardiometabolic comorbidities (33.3% had diabetes, 20.0% coronary artery disease, 13.3% heart failure). Conclusions: This ongoing, prospective, virtual-based, direct-to-patient PA screening program identified confirmed or possible PA in up to 27.4% of guideline-eligible participants. By reaching patients directly, rather than relying on routine clinical screening that is known to be dramatically underutilized, this study highlights the unrecognized prevalence of PA and demonstrates a novel approach to identifying this common, morbid, and treatable condition across the USA. Presentation: Friday, June 16, 2023

Employment Strategies in Applied Universities: A Case Study of Shanxi Technology And Business College in the New Era

&#x0D; &#x0D; &#x0D; &#x0D; The rapid expansion of higher education in China has led to a transformation in the employment landscape for college graduates. In response, the government has established a new employment market mechanism that poses challenges for employment guidance departments. The employment outcomes of college students are closely tied to the development and competitiveness of universities. To address these challenges, applied universities must enhance the comprehensive qualities and employability of their students through long-term planning and coordination. This paper examines the employment work in applied universities in the new era, focusing on the case of Shanxi Technology and Business College. The study highlights the requirements for effective employment strategies, including leadership involvement, coordination, and engagement of all staff members. It also discusses the employment statistics of the 2022 graduates from Shanxi Technology and Business College. The paper outlines the employment strategies employed by the college, such as employment guidance classes, improving the quality of employment education, and establishing on-campus and online recruitment platforms. It emphasizes the coordinated efforts and responsibilities of the college leadership, active participation from various departments, transformation of educational guidance, and the implementation of multiple measures for employment success. The college also emphasizes the accurate collection and statistical verification of graduates' employment data.This study provides insights into the employment work in applied universities, offering valuable strategies and practices for navigating the new era of college graduate employment.&#x0D; &#x0D; &#x0D; &#x0D; &#x0D;

An improved heterogeneous graph convolutional network for job recommendation

Job recommendation is crucial in online recruitment platforms due to the overwhelming number of job postings. Job seekers spend considerable time and effort searching for suitable employment. With millions of job seekers browsing job postings daily, the demand for accurate and effective job recommendations is more pressing than ever. To address this challenge, we propose IHGCN, an improved semi-supervised heterogeneous graph convolutional network model for job recommendation. IHGCN aims to provide job recommendations for early job seekers based on their resumes. Firstly, we introduce a novel labeling classification standard specifically tailored to early job seeker resumes. Secondly, we construct a heterogeneous resume graph where each resume is represented as a node. Job recommendation is treated as a multi-classification problem. Thirdly, our IHGCN model learns a node representation from the graph to perform effective job recommendations. To evaluate our model, we conduct experiments using a real-world resume dataset obtained from LinkedIn. The results demonstrate that IHGCN outperforms the baselines by around 10%. This study highlights the benefits of leveraging meta-paths within the Graph Convolutional Network model to address the sparsity problem caused by the one-hot representation of nodes.

Developing Norms for the Hope-Action Inventory with a Substance Misuse Sample

The Hope-Action Inventory (HAI), a hope-based measure of career competencies, has demonstrated solid predictive validity for educational and vocational outcomes. The purpose of this study was to justify an expansion of the use of the HAI by examining group differences and establishing norms for interpreting HAI results with individuals with a history of substance misuse. Participants (N = 783) were recruited through substance use support centers and the Amazon Mechanical Turk online recruitment platform. Significant group differences were found among differing employment statuses and age groups. Normative data on the HAI with substance use populations are provided by age and employment status.

Substrate recruitment mechanism by gram-negative type III, IV, and VI bacterial injectisomes.

Bacteria use a wide arsenal of macromolecular substrates (DNA and proteins) to interact with or infect prokaryotic and eukaryotic cells. To do so, they utilize substrate-injecting secretion systems or injectisomes. However, prior to secretion, substrates must be recruited to specialized recruitment platforms and then handed over to the secretion apparatus for secretion. In this review, we provide an update on recent advances in substrate recruitment and delivery by gram-negative bacterial recruitment platforms associated with Type III, IV, and VI secretion systems.

Discrimination on the Basis of Personal Data in Employment: The Case Study of Lithuania

Abstract This article examines what kind of personal data disclosure may make it difficult to get employed and what kind of excessive (unlawful) data is collected when selecting candidates in Lithuania. The analysis reveals that there have been a number of justified complaints regarding the selection of employees via recruitment platforms and the provided application forms that specifically requested an excessive amount of information, or situations in which the conditions indicated in job listings were adapted to a specific circle of people, thus eliminating other potential candidates, such as persons of pre-retirement age, young families, persons with children, persons of a particular gender and similar groups of people. The purpose of this article is to identify methods of unlawful collection of personal data, as well as the types of requested personal data, the origin of which may lead to discrimination during the recruitment process in Lithuania. The article analyses the legality of documents requested from candidates, data collected from them by filling out application forms and providing preliminary or additional information during job interviews, or information gathered from former employers or social networks.

Analisis Sistem Informasi Merekrut Karyawan Berbasis WEB pada Perusahaan PT.Erafone Artha Retailindo

Efficient and organized employee recruitment management is very important for the success of a company. In this digital era, web-based technology offers a great opportunity to improve the recruitment process by reducing time, costs and increasing the quality of prospective employees. This study aims to analyze and design an innovative and easy-to-use web-based recruitment system for the company PT ERAFONE ARTHA RETAILINDO to increase efficiency and accuracy in the recruitment process. The research method we use is waterfall and interviews with HR managers and the company's recruitment team to understand the process. current recruitment. We also carry out document analysis, such as historical data on previous recruitment and the recruitment platform used. The results of the system implementation show a significant increase in the response time of the recruitment process and the quality of candidates invited to further selection stages. The HR team also reported reduced workload and increased productivity due to the efficiency of the new recruitment system&#x0D; Keywords: Information systems, recruiting employees, system design, HR, waterfall&#x0D;

Analisis dan Perancangan Sistem Informasi Seleksi Karyawan Baru pada PT.Erafone Artha Retailindo Cabang Pekanbaru

Efficient and organized employee recruitment management is very important for the success of a company. In this digital era, web-based technology offers a great opportunity to improve the recruitment process by reducing time, costs and increasing the quality of prospective employees. This study aims to analyze and design an innovative and easy-to-use web-based recruitment system for the company PT ERAFONE ARTHA RETAILINDO to increase efficiency and accuracy in the recruitment process. The research method we use is waterfall and interviews with HR managers and the company's recruitment team to understand the process. current recruitment. We also carry out document analysis, such as historical data on previous recruitment and the recruitment platform used. The results of the system implementation show a significant increase in the response time of the recruitment process and the quality of candidates invited to further selection stages. The HR team also reported reduced workload and increased productivity due to the efficiency of the new recruitment system&#x0D; Keywords: Information systems, recruiting employees, system design, HR, waterfall

HIRA-mediated loading of histone variant H3.3 controls androgen-induced transcription by regulation of AR/BRD4 complex assembly at enhancers.

Incorporation of histone variant H3.3 comprises active territories of chromatin. Exploring the function of H3.3 in prostate cancer (PC), we found that knockout (KO) of H3.3 chaperone HIRA suppresses PC growth in vitro and in xenograft settings, deregulates androgen-induced gene expression and alters androgen receptor (AR) binding within enhancers of target genes. H3.3 affects transcription in multiple ways, including activation of p300 by phosphorylated H3.3 at Ser-31 (H3.3S31Ph), which results in H3K27 acetylation (H3K27Ac) at enhancers. In turn, H3K27Ac recruits bromodomain protein BRD4 for enhancer-promoter interaction and transcription activation. We observed that HIRA KO reduces H3.3 incorporation, diminishes H3.3S31Ph and H3K27Ac, modifies recruitment of BRD4. These results suggest that H3.3-enriched enhancer chromatin serves as a platform for H3K27Ac-mediated BRD4 recruitment, which interacts with and retains AR at enhancers, resulting in transcription reprogramming. In addition, HIRA KO deregulates glucocorticoid- (GR) driven transcription of genes co-regulated by AR and GR, suggesting a common H3.3/HIRA-dependent mechanism of nuclear receptors function. Expression of HIRA complex proteins is increased in PC compared with normal prostate tissue, especially in high-risk PC groups, and is associated with a negative prognosis. Collectively, our results demonstrate function of HIRA-dependent H3.3 pathway in regulation of nuclear receptors activity.

Internet-Based Recruitment and Retention of Young Adults With Type 1 Diabetes: Cross-Sectional Study.

Multiple research strategies are required to recruit and engage a representative cohort of young adults in diabetes research. In this report, we describe an approach for internet-based recruitment for a repeated-measures descriptive study. The objective of this cross-sectional study was to determine whether internet-based recruitment through multiple social media platforms, a clinical research platform, and cooperation with community partnerships-College Diabetes Network and Beyond Type 1-would serve as an effective way to recruit a representative sample of young adults aged 18-25 years with type 1 diabetes (T1D). We conducted a repeated-measures descriptive study. We captured enrollment rates and participant characteristics acquired from each social media platform through survey data and Facebook analytics. This study was advertised via paid postings across a combination of different social media platforms (eg, Facebook, Instagram, Twitter, and Reddit). We used quarterly application postings, quarterly newsletters, and participation in the ResearchMatch registry to identify potentially eligible participants from February 3, 2021, to June 6, 2022. ResearchMatch proved to be the most cost-effective strategy overall, yielding the highest gender and racial diversity compared to other internet platforms (eg, Facebook, Instagram, Twitter, and Reddit), application postings (eg, Beyond Type 1), and newsletters (eg, College Diabetes Network and a local area college). However, we propose that the combination of these approaches yielded a larger, more diverse sample compared to any individual strategy. Our recruitment cost was US $16.69 per eligible participant, with a 1.27% conversion rate and a 30% eligibility rate. Recruiting young adults with T1D across multiple internet-based platforms was an effective strategy to yield a moderately diverse sample. Leveraging various recruitment strategies is necessary to produce a representative sample of young adults with T1D. As the internet becomes a larger forum for study recruitment, participants from underrepresented backgrounds may continue engaging in research through advertisements on the internet and other internet-based recruitment platforms.

A dual role for the chromatin reader ORCA/LRWD1 in targeting the origin recognition complex to chromatin.

Eukaryotic cells use chromatin marks to regulate the initiation of DNA replication. The origin recognition complex (ORC)-associated protein ORCA plays a critical role in heterochromatin replication in mammalian cells by recruiting the initiator ORC, but the underlying mechanisms remain unclear. Here, we report crystal and cryo-electron microscopy structures of ORCA in complex with ORC's Orc2 subunit and nucleosomes, establishing that ORCA orchestrates ternary complex assembly by simultaneously recognizing a highly conserved peptide sequence in Orc2, nucleosomal DNA, and repressive histone trimethylation marks through an aromatic cage. Unexpectedly, binding of ORCA to nucleosomes prevents chromatin array compaction in a manner that relies on H4K20 trimethylation, a histone modification critical for heterochromatin replication. We further show that ORCA is necessary and sufficient to specifically recruit ORC into chromatin condensates marked by H4K20 trimethylation, providing a paradigm for studying replication initiation in specific chromatin contexts. Collectively, our findings support a model in which ORCA not only serves as a platform for ORC recruitment to nucleosomes bearing specific histone marks but also helps establish a local chromatin environment conducive to subsequent MCM2-7 loading.

Health-Care Seeking Behavior and Treatment of Menstrual Migraine among Danish Women—A Social Media Study

An estimated 4–8% of all women, and 16–25% of women with migraine, have menstrual migraine (MM), which causes considerable disability, but is underdiagnosed and undertreated. We investigated the burden of disease, health-care seeking behavior, and treatment practices among women with MM, using social media. In 12 days, 6246 women answered an online survey, allowing for diagnosis of MM by the International Classification of Headache Disorders third edition (ICHD-3). In total, 47% had MM, 21% had non-menstrual migraine (nMM), and 15% had probable menstrual migraine (pMM). Among women with MM, 61% had missed out on school/work and 69% on family, leisure, or social activities in the last 3 months. Fifty-four percent had consulted a health-care practitioner about their MM, of whom thirty-seven percent had received information about medical treatment of MM. A total of 85% used medicine in connection with MM, either over-the-counter medication only (57%), prescription medication only (24%), or both. Social media offers an efficient and less expensive recruitment platform for population-based studies on MM and is a useful tool to raise public awareness about MM. Moreover, this study confirms the significant impact of MM on women’s everyday lives and the challenges it poses to their regular activities.

(Not) Paying for Diversity: Repugnant Market Concerns Associated with Transactional Approaches to Diversity Recruitment

In a 20-month ethnographic study, I examine how a technology firm, ShopCo (a pseudonym), considered 13 different recruitment platforms to attract racial minority engineering candidates. I find that when choosing whether to adopt recruitment platforms focused on racial minority candidates (targeted recruitment platforms) but not when choosing whether to adopt recruitment platforms on which the modal candidate was White (traditional recruitment platforms), ShopCo managers expressed distaste for what they perceived to be the objectification, exploitation, and race-based targeting of racial minorities. These managers’ repugnant market concerns influenced which types of platforms ShopCo adopted. To recruit racial minorities, ShopCo eschewed recruitment platforms taking a transactional approach that emphasized speed, quantity, efficiency, opportunity, and compensation, in favor of platforms taking a developmental approach that emphasized individuality, ethics, equity, community, and commitment. I show that ShopCo managers had different relational models for recruiting based on the race of the candidate. By exploring the new mechanism of repugnant market concerns, I aim to increase understanding of employees’ resistance to DEI initiatives, which can create barriers to workplace reforms even when organizations are committed to change.

What over 1,000,000 participants tell us about online research protocols.

With the ever-increasing adoption of tools for online research, for the first time we have visibility on macro-level trends in research that were previously unattainable. However, until now this data has been siloed within company databases and unavailable to researchers. Between them, the online study creation and hosting tool Gorilla Experiment Builder and the recruitment platform Prolific hold metadata gleaned from millions of participants and over half a million studies. We analyzed a subset of this data (over 1 million participants and half a million studies) to reveal critical information about the current state of the online research landscape that researchers can use to inform their own study planning and execution. We analyzed this data to discover basic benchmarking statistics about online research that all researchers conducting their work online may be interested to know. In doing so, we identified insights related to: the typical study length, average completion rates within studies, the most frequent sample sizes, the most popular participant filters, and gross participant activity levels. We present this data in the hope that it can be used to inform research choices going forward and provide a snapshot of the current state of online research.

An artificial intelligence (AI)-based approach to clinical trial recruitment: The impact of Viz RECRUIT on enrollment in the EMBOLISE trial.

EMBOLISE (NCT04402632) is an ongoing randomized controlled trial investigating the safety and efficacy of middle meningeal artery embolization for the treatment of subacute or chronic subdural hematoma (SDH). Viz RECRUIT SDH is an artificial intelligence (AI)-based software platform that can automatically detect SDH in noncontrast computed tomography (NCHCT) images and report the volume, maximum thickness, and midline shift. We hypothesized that the mobile recruitment platform would aid enrollment and coordinate communication and image sharing among the entire research team. Patient enrollment in EMBOLISE prior to and after implementation of Viz RECRUIT SDH at a large comprehensive stroke center was compared along with the performance of the software platform. The EMBOLISE trial was activated on May 5, 2021, and Viz RECRUIT SDH was activated on October 6, 2021. The pre-AI cohort consisted of all patients from EMBOLISE to AI activation (153 days), and the post-AI cohort consisted of all patients from AI activation until August 18, 2022 (316 days). All alerts for suspected SDH candidates were manually reviewed to determine the positive predictive value (PPV) of the algorithm. Prior to AI-software implementation, there were 5 patients enrolled (0.99 patients/month) and one screen failure. After the implementation of the software, enrollment increased by 36% to 1.35 patients/month (14 total enrolled), and there were no screen failures. Over the entire post-AI period, a total of 6244 NCHCTs were processed by the system with 207 total SDH detections (3% prevalence). 35% of all alerts for suspected SDH were viewed within 10 min, and 50% were viewed within an hour. The PPV of the algorithm was 81.4 (CI [75.3, 86.7]). The implementation of an AI-based software for the automatic screening of SDH patients increased the enrollment rate in the EMBOLISE trial, and the software performed well in a real-world, clinical trial setting.

Feasibility and Preliminary Efficacy of Digital Interventions for Depressive Symptoms in Working Adults: Multiarm Randomized Controlled Trial.

Depressive symptoms are highly prevalent and have broad-ranging negative implications. Digital interventions are increasingly available in the workplace context, but supporting evidence is limited. This study aimed to evaluate the feasibility, acceptability, and preliminary efficacy of 3 digital interventions for depressive symptoms in a sample of UK-based working adults experiencing mild to moderate symptoms. This was a parallel, multiarm, pilot randomized controlled trial. Participants were allocated to 1 of 3 digital interventions or a waitlist control group and had 3 weeks to complete 6 to 8 short self-guided sessions. The 3 interventions are available on the Unmind mental health app for working adults and draw on behavioral activation, cognitive behavioral therapy, and acceptance and commitment therapy. Web-based assessments were conducted at baseline, postintervention (week 3), and at 1-month follow-up (week 7). Participants were recruited via Prolific, a web-based recruitment platform, and the study was conducted entirely on the web. Feasibility and acceptability were assessed using objective engagement data and self-reported feedback. Efficacy outcomes were assessed using validated self-report measures of mental health and functioning and linear mixed models with intention-to-treat principles. In total, 2003 individuals were screened for participation, of which 20.22% (405/2003) were randomized. A total of 92% (373/405) of the participants were retained in the study, 97.4% (295/303) initiated their allocated intervention, and 66.3% (201/303) completed all sessions. Moreover, 80.6% (229/284) of the participants rated the quality of their allocated intervention as excellent or good, and 79.6% (226/284) of the participants were satisfied or very satisfied with their intervention. All active groups showed improvements in well-being, functioning, and depressive and anxiety symptoms compared with the control group, which were maintained at 4 weeks. Hedges g effect sizes for depressive symptoms ranged from -0.53 (95% CI -0.25 to -0.81) to -0.74 (95% CI -0.45 to -1.03). All interventions were feasible and acceptable, and the preliminary efficacy findings indicated that their use may improve depressive symptoms, well-being, and functioning. The predefined criteria for a definitive trial were met. International Standard Randomised Controlled Trial Number (ISRCTN) ISRCTN13067492; https://www.isrctn.com/ISRCTN13067492.

Web-based psychoacoustics: Hearing screening, infrastructure, and validation

Anonymous web-based experiments are increasingly used in many domains of behavioral research. However, online studies of auditory perception, especially of psychoacoustic phenomena pertaining to low-level sensory processing, are challenging because of limited available control of the acoustics, and the inability to perform audiometry to confirm normal-hearing status of participants. Here, we outline our approach to mitigate these challenges and validate our procedures by comparing web-based measurements to lab-based data on a range of classic psychoacoustic tasks. Individual tasks were created using jsPsych, an open-source JavaScript front-end library. Dynamic sequences of psychoacoustic tasks were implemented using Django, an open-source library for web applications, and combined with consent pages, questionnaires, and debriefing pages. Subjects were recruited via Prolific, a subject recruitment platform for web-based studies. Guided by a meta-analysis of lab-based data, we developed and validated a screening procedure to select participants for (putative) normal-hearing status based on their responses in a suprathreshold task and a survey. Headphone use was standardized by supplementing procedures from prior literature with a binaural hearing task. Individuals meeting all criteria were re-invited to complete a range of classic psychoacoustic tasks. For the re-invited participants, absolute thresholds were in excellent agreement with lab-based data for fundamental frequency discrimination, gap detection, and sensitivity to interaural time delay and level difference. Furthermore, word identification scores, consonant confusion patterns, and co-modulation masking release effect also matched lab-based studies. Our results suggest that web-based psychoacoustics is a viable complement to lab-based research. Source code for our infrastructure is provided.

How is online self-reported weight compared with image-captured weight? A comparative study using data from an online longitudinal study of young adults

BackgroundAccurate anthropometric measurement is important within epidemiological studies and clinical practice. Traditionally, self-reported weight is validated against in-person weight measurement. ObjectivesThis study aimed to 1) determine the comparison of online self-reported weight against images of weight captured on scales in a young adult sample, 2) compare this across body mass index (BMI), gender, country, and age groups, and 3) explore demographics of those who did/did not provide a weight image. MethodsCross-sectional analysis of baseline data from a 12-mo longitudinal study of young adults in Australia and the UK was conducted. Data were collected by online survey via Prolific research recruitment platform. Self-reported weight and sociodemographics (for example, age, gender) were collected for the whole sample (n = 512), and images of weight for a subset (n = 311). Tests included Wilcoxon signed-rank test to evaluate differences between measures, Pearson correlation to explore the strength of the linear relationship, and Bland-Altman plots to evaluate agreement. ResultsSelf-reported weight [median (interquartile range), 92.5 kg (76.7–112.0)] and image-captured weight [93.8 kg (78.8–112.8)] were significantly different (z = −6.76, P < 0.001), but strongly correlated (r = 0.983, P < 0.001). In the Bland-Altman plot [mean difference −0.99 kg (−10.83, 8.84)], most values were within limits of agreement (2 standard deviation). Correlations remained high across BMI, gender, country, and age groups (r > 0.870, P < 0.002). Participants with BMI in ranges 30–34.9 and 35–39.9 kg/m2 were less likely to provide an image. ConclusionsThis study demonstrates the method concordance of image-based collection methods with self-reported weight in online research.