Abstract This paper contributes to the existing literature by reviewing the research methodology and the literature review with the focus on potential applications for the novelty technology of the single platform E-payment. These included, but were not restricted to the subjects, population, sample size requirement, data collection method and measurement of variables, pilot study and statistical techniques for data analysis. The reviews will shed some light and potential applications for future researchers, students and others to conceptualize, operationalize and analyze the underlying research methodology to assist in the development of their research methodology.

analyze the current population survey (cps) annual social and economic supplement (asec) with r the annual march cps-asec has been supplying the statistics for the census bureau's report on income, poverty, and health insurance coverage since 1948. wow. the us census bureau and the bureau of labor statistics ( bls) tag-team on this one. until the american community survey (acs) hit the scene in the early aughts (2000s), the current population survey had the largest sample size of all the annual general demographic data sets outside of the decennial census - about two hundred thousand respondents. this provides enough sample to conduct state- and a few large metro area-level analyses. your sample size will vanish if you start investigating subgroups b y state - consider pooling multiple years. county-level is a no-no. despite the american community survey's larger size, the cps-asec contains many more variables related to employment, sources of income, and insurance - and can be trended back to harry truman's presidency. aside from questions specifically asked about an annual experience (like income), many of the questions in this march data set should be t reated as point-in-time statistics. cps-asec generalizes to the united states non-institutional, non-active duty military population. the national bureau of economic research (nber) provides sas, spss, and stata importation scripts to create a rectangular file (rectangular data means only person-level records; household- and family-level information gets attached to each person). to import these files into r, the parse.SAScii function uses nber's sas code to determine how to import the fixed-width file, then RSQLite to put everything into a schnazzy database. you can try reading through the nber march 2012 sas importation code yourself, but it's a bit of a proc freak show. this new github repository contains three scripts: 2005-2012 asec - download all microdata.R down load the fixed-width file containing household, family, and person records import by separating this file into three tables, then merge 'em together at the person-level download the fixed-width file containing the person-level replicate weights merge the rectangular person-level file with the replicate weights, then store it in a sql database create a new variable - one - in the data table 2012 asec - analysis examples.R connect to the sql database created by the 'download all microdata' progr am create the complex sample survey object, using the replicate weights perform a boatload of analysis examples replicate census estimates - 2011.R connect to the sql database created by the 'download all microdata' program create the complex sample survey object, using the replicate weights match the sas output shown in the png file below 2011 asec replicate weight sas output.png statistic and standard error generated from the replicate-weighted example sas script contained in this census-provided person replicate weights usage instructions document. click here to view these three scripts for more detail about the current population survey - annual social and economic supplement (cps-asec), visit: the census bureau's current population survey page the bureau of labor statistics' current population survey page the current population survey's wikipedia article notes: interviews are conducted in march about experiences during the previous year. the file labeled 2012 includes information (income, work experience, health insurance) pertaining to 2011. when you use the current populat ion survey to talk about america, subract a year from the data file name. as of the 2010 file (the interview focusing on america during 2009), the cps-asec contains exciting new medical out-of-pocket spending variables most useful for supplemental (medical spending-adjusted) poverty research. confidential to sas, spss, stata, sudaan users: why are you still rubbing two sticks together after we've invented the butane lighter? time to transition to r. :D

This is a mixed-methods data collection. This study used Respondent Driven Sampling (RDS) methodology, which is a sampling method designed to generate unbiased estimates of population characteristics for populations where a sampling frame is not available. It is a form of snowball or link-tracing sampling, where respondents are given coupons to recruit other members of the target population, and where respondents are rewarded for both participating and for recruiting others. In addition to variables of interest, data are collected on the number of members of the target population each participant knows. Estimation methods are then applied to account for the non-random sample selection in an attempt to generate unbiased estimates for the target population.

In 2010, the researchers conducted an RDS study in a rural Ugandan population where total population data were available. The aim of this study was to evaluate whether RDS could generate representative data on a rural Ugandan population by comparing estimates from an RDS survey with total-population data. The data used to define the target population (male household heads) were available from an ongoing general population cohort of 25 villages in rural Masaka, Uganda covering an area of approximately 38km. Annually, households in the study villages are mapped and after obtaining consent, a total-population household census and an individual questionnaire are administered and blood taken for HIV-1 testing. A random sample of eligible men in the target population who were not recruited during the RDS study were also interviewed, using the same RDS questionnaire. Finally, 49 qualitative interviews (of which summaries have been deposited) were conducted with a range of people (men and women) including RDS participants and non-participants, and RDS interviewers. These data can be used to evaluate the RDS sampling method, and to test new RDS estimators.

Further information may be found in the documentation and in the journal articles listed in the Publications section.

Special Licence access and geographic data
This data collection is subject to Special Licence access conditions (see Access section for details). Data are analysable at individual village level, and GPS point data are available for the villages and interview sites. Finer detail geographic variables may be available for certain research questions. If these are required, users should request this when making their Special Licence application.

Definition of the selected demographic and socioeconomic variables.

Objectives(i) To identify peer reviewed publications reporting the mental and/or physical health outcomes of Deaf adults who are sign language users and to synthesise evidence; (ii) If data available, to analyse how the health of the adult Deaf population compares to that of the general population; (iii) to evaluate the quality of evidence in the identified publications; (iv) to identify limitations of the current evidence base and suggest directions for future research.DesignSystematic review.Data sourcesMedline, Embase, PsychINFO, and Web of Science.Eligibility criteria for selecting studiesThe inclusion criteria were Deaf adult populations who used a signed language, all study types, including methods-focused papers which also contain results in relation to health outcomes of Deaf signing populations. Full-text articles, published in peer-review journals were searched up to 13th June 2023, published in English or a signed language such as ASL (American Sign Language).Data extractionSupported by the Rayyan systematic review software, two authors independently reviewed identified publications at each screening stage (primary and secondary). A third reviewer was consulted to settle any disagreements. Comprehensive data extraction included research design, study sample, methodology, findings, and a quality assessment.ResultsOf the 35 included studies, the majority (25 out of 35) concerned mental health outcomes. The findings from this review highlighted the inequalities in health and mental health outcomes for Deaf signing populations in comparison with the general population, gaps in the range of conditions studied in relation to Deaf people, and the poor quality of available data.ConclusionsPopulation sample definition and consistency of standards of reporting of health outcomes for Deaf people who use sign language should be improved. Further research on health outcomes not previously reported is needed to gain better understanding of Deaf people’s state of health.

Labour Force Sample Survey 1991-92 panel file, 2.q.1991-3.q.1992

As of the 1st quarter of 1972, SSB has conducted official quarterly labour force surveys (AKU). These surveys aim to give the labour force authorities (and other people interested) knowledge of the occupational structure of the population and how it develops over time. The surveys are meant to give a foundation and statistical material for occupational prognoses and labour research. The samples in AKU are from 1992 representative at county level. In the period 1972-1991 they were representative on county pair level.

Originally, AKU respondents were interviewed in two consecutive quarters of a year, followed by a pause of two quarters, and then another two quarters of interviews. The sample was approximately 10-11.000 respondents in each quarter up until 1988. Originally, AKU was intended to be an analytical supplement to the monthly occupational statistics that was based on the social security membership index file. However, the social security-based statistics disappeared when the sickness benefit was included in the National Insurance as of 1st of January 1971, and AKU has after gradually developed into the most significant source of knowledge of the state of the labour market and its development.

In 1975, Statistics Norway changed the sampling frame of survey research, see article 37: “Om bruk av stikkprøver ved kontoret for intervjuundersøkelser”, SSB (About the Use of Random Samples at the Office for Survey Research, Statistics Norway) by Steinar Tamsfoss, and SØS 33: “Prinsipper og metoder for Statistisk sentralbyrås utvalgsundersøkelse (Principles and Methods for Statistics Norway's sample research) by Ib Thomsen. Simultaneously, the method for estimation of inflation to national numbers was changed, so that reasonable numbers for regions do exist from 1975 and onwards. The change in 1975 led to a different way of interviewing in groups. This caused amongst other things a break with the AKU panel systematics.

In the AKU survey of 1976, a slightly changed questionnaire was introduced. Also, there was a return to the original 6-quarter rotation scheme. The new questionnaire implied a better identification of family workers and persons that are temporarily without paid work. Thus, 30-35 000 more people were defined as employed. The group of "job-seekers without income" were also extended to include persons that were on an involuntary leave of absence. The questions concerning underemployment and “over employment” in the original questionnaire were abandoned.

From the 1st quarter of 1987, the estimation method (inflation to national numbers) was slightly changed. There was also a minor adjustment in the definition of employment. In order to ensure that the numbers were to be comparable to earlier surveys, new versions of the 1980-1986 AKU-files were drawn up. Consequently two versions of the 1980-1987 files - respectively with the old and new methods of estimation - exist. The “old” means that the data are comparable to the original numbers published in the period of 1972 - 1987, whilst the “new” implies that the data are comparable to numbers published after 1987.

Between the 1st and 2nd quarter of 1988, the AKU file description was changed. The variable “Labour-market status” was given a different coding. In addition, adjustments in the data collections were made - from interviewing a specific week every quarter to carry out continuous weekly interviews. SSB also started up an escalation scheme to increase the sample size. This affected the weights, and from the 2nd quarter of 1988, these were recalculated monthly. To balance out the quarterly or yearly files to total national numbers, the monthly weights therefore had to be divided in three or twelve to give the correct total number.

In 1996, AKU was significantly revised: The questionnaire, the file description and the standard for coding of industry and occupation. The data collection also changed to CATI - Computer Assisted Telephone Interviewing. A new classification of industry was put into use (NOS C 182, based on the EU standard NACE, Rev.1). This standard was updated in 2002 and 2007. Also, the new occupational classification (STYRK) based on ISCO 88 was used from 1996 and onwards. The variable indicating socio-economic status was omitted, as a similar variable was not developed in the new occupational classification.

As from January 2006 some major changes were introduced to AKU in order to enhance its comparability to similar surveys in other countries. The changes consist of minor definitional adjustments of unemployment, some adjustments and enlargement of the questionnaire and a change in age definition (age at reference point instead of at the end of the year). Simultaneously the lower age limit to be included in AKU was lowered from 16 to...

Characteristics of the datasets used to estimate minimum sample size.

Zipped file containing: (A) A file containing more detailed information on the parameters estimated by SaSii, including the equations used for the calculations, and with examples of accepted input formats. (B) SaSii script. (C) Configuration file with parameters used to describe the dataset and analysis settings. (ZIP)

IntroductionGenetic variants may influence Toll-like receptor (TLR) signaling in the immune response to human papillomavirus (HPV) infection and lead to cervical cancer. In this study, we investigated the pattern of TLR expression in the transcriptome of HPV-positive and HPV-negative cervical cancer samples and looked for variants potentially related to TLR gene alterations in exomes from different populations.Materials and methodsA cervical tissue sample from 28 women, which was obtained from the Gene Expression Omnibus database, was used to examine TLR gene expression. Subsequently, the transcripts related to the TLRs that showed significant gene expression were queried in the Genome Aggregation Database to search for variants in more than 5,728 exomes from different ethnicities.ResultsCancer and HPV were found to be associated (p<0.0001). TLR1(p = 0.001), TLR3(p = 0.004), TLR4(221060_s_at)(p = 0.001), TLR7(p = 0.001;p = 0.047), TLR8(p = 0.002) and TLR10(p = 0.008) were negatively regulated, while TLR4(1552798_at)(p<0.0001) and TLR6(p = 0.019) were positively regulated in HPV-positive patients (p<0.05). The clinical significance of the variants was statistically significant for TLR1, TLR3, TLR6 and TLR8 in association with ethnicity. Genetic variants in different TLRs have been found in various ethnic populations. Variants of the TLR gene were of the following types: TLR1(5_prime_UTR), TLR4(start_lost), TLR8(synonymous;missense) and TLR10(3_prime_UTR). The “missense” variant was found to have a risk of its clinical significance being pathogenic in South Asian populations (OR = 56,820[95%CI:40,206,80,299]).ConclusionThe results of this study suggest that the variants found in the transcriptomes of different populations may lead to impairment of the functional aspect of TLRs that show significant gene expression in cervical cancer samples caused by HPV.

Questionnaires are among the most basic and widespread tools to assess the mental health of a population in epidemiological and public health studies. Their most obvious advantage (firsthand self-report) is also the source of their main problems: the raw data requires interpretation, and are a snapshot of the specific sample’s status at a given time. Efforts to deal with both issues created a bi-dimensional space defined by two orthogonal axes, in which most of the quantitative mental health research can be located. Methods aimed to assure that mental health diagnoses are solidly grounded on existing raw data are part of the individual validity axis. Tools allowing the generalization of the results across the entire population compose the collective validity axis. This paper raises a different question. Since one goal of mental health assessments is to obtain results that can be generalized to some extent, an important question is how robust is a questionnaire result when applied to a different population or to the same population at a different time. In this case, there is deep uncertainty, without any a priori probabilistic information. The main claim of this paper is that this task requires the development of a new robustness to deep uncertainty axis, defining a three-dimensional research space. We demonstrate the analysis of deep uncertainty using the concept of robustness in info-gap decision theory. Based on data from questionnaires collected before and during the Covid-19 pandemic, we first locate a mental health assessment in the space defined by the individual validity axis and the collective validity axis. Then we develop a model of info-gap robustness to uncertainty in mental health assessment, showing how the robustness to deep uncertainty axis interacts with the other two axes, highlighting the contributions and the limitations of this approach. The ability to measure robustness to deep uncertainty in the mental health realm is important particularly in troubled and changing times. In this paper, we provide the basic methodological building blocks of the suggested approach using the outbreak of Covid-19 as a recent example.

Table of target populations vs analytical sample demographics.

Chart of the complexities illustrated in each example case study available in serosim.

COVID-19 mortality rates increase rapidly with age, are higher among men than women, and vary across racial/ethnic groups, but this is also true for other natural causes of death. Prior research on COVID-19 mortality rates and racial/ethnic disparities in those rates has not considered to what extent disparities reflect COVID-19-specific factors, versus preexisting health differences. This study examines both questions. We study the COVID-19-related increase in mortality risk and racial/ethnic disparities in COVID-19 mortality, and how both vary with age, gender, and time period. We use a novel measure validated in prior work, the COVID Excess Mortality Percentage (CEMP), defined as the COVID-19 mortality rate (Covid-MR), divided by the non-COVID natural mortality rate during the same time period (non-Covid NMR), converted to a percentage. The CEMP denominator uses Non-COVID NMR to adjust COVID-19 mortality risk for underlying population health. The CEMP measure generates insights which differ from those using two common measures–the COVID-MR and the all-cause excess mortality rate. By studying both CEMP and COVID-MRMR, we can separate the effects of background health from Covid-specific factors affecting COVID-19 mortality. We study how CEMP and COVID-MR vary by age, gender, race/ethnicity, and time period, using data on all adult decedents from natural causes in Indiana and Wisconsin over April 2020-June 2022 and Illinois over April 2020-December 2021. CEMP levels for racial and ethnic minority groups can be very high relative to White levels, especially for Hispanics in 2020 and the first-half of 2021. For example, during 2020, CEMP for Hispanics aged 18–59 was 68.9% versus 7.2% for non-Hispanic Whites; a ratio of 9.57:1. CEMP disparities are substantial but less extreme for other demographic groups. Disparities were generally lower after age 60 and declined over our sample period. Differences in socio-economic status and education explain only a small part of these disparities.

Definitions of qualitative themes and subthemes for student-parents.

Definition and descriptive statistics of the main variables.

Evidence to date indicates that compassion and empathy are health-enhancing qualities. Research points to interventions and practices involving compassion and empathy being beneficial, as well as being salient outcomes of contemplative practices such as mindfulness. Advancing the science of compassion and empathy requires that we select measures best suited to evaluating effectiveness of training and answering research questions. The objective of this scoping review was to 1) determine what instruments are currently available for measuring empathy and compassion, 2) assess how and to what extent they have been validated, and 3) provide an online tool to assist researchers and program evaluators in selecting appropriate measures for their settings and populations. A scoping review and broad evidence map were employed to systematically search and present an overview of the large and diverse body of literature pertaining to measuring compassion and empathy. A search string yielded 19,446 articles, and screening resulted in 559 measure development or validation articles reporting on 503 measures focusing on or containing subscales designed to measure empathy and/or compassion. For each measure, we identified the type of measure, construct being measured, in what context or population it was validated, response set, sample items, and how many different types of psychometrics had been assessed for that measure. We provide tables summarizing these data, as well as an open-source online interactive data visualization allowing viewers to search for measures of empathy and compassion, review their basic qualities, and access original citations containing more detail. Finally, we provide a rubric to help readers determine which measure(s) might best fit their context.

Definitions of qualitative themes and subthemes for non-parent students.

BackgroundPopulation-based studies provide the understanding of health-need required for effective public health policy and service-planning. Mental disorders are an important but, until recently, neglected agenda in global health. This paper reviews the coverage and limitations in global epidemiological data for mental disorders and suggests strategies to strengthen the data.MethodsSystematic reviews were conducted for population-based epidemiological studies in mental disorders to inform new estimates for the global burden of disease study. Estimates of population coverage were calculated, adjusted for study parameters (age, gender and sampling frames) to quantify regional coverage.ResultsOf the 77,000 data sources identified, fewer than 1% could be used for deriving national estimates of prevalence, incidence, remission, and mortality in mental disorders. The two major limitations were (1) highly variable regional coverage, and (2) important methodological issues that prevented synthesis across studies, including the use of varying case definitions, the selection of samples not allowing generalization, lack of standardized indicators, and incomplete reporting. North America and Australasia had the most complete prevalence data for mental disorders while coverage was highly variable across Europe, Latin America, and Asia Pacific, and poor in other regions of Asia and Africa. Nationally-representative data for incidence, remission, and mortality were sparse across most of the world.DiscussionRecent calls to action for global mental health were predicated on the high prevalence and disability of mental disorders. However, the global picture of disorders is inadequate for planning. Global data coverage is not commensurate with other important health problems, and for most of the world's population, mental disorders are invisible and remain a low priority.

This paper presents the first translation and adaptation of the Multidimensional Mentalizing Questionnaire (MMQ) into Spanish for a native Spanish-speaking sample in Chile. The study examines the psychometric properties and internal consistency of the translated MMQ. The instrument undergoes modifications based on a confirmatory factor analysis of the original structure, resulting in the elimination of items with cross-loadings and improvement in model fit. The modified scale is then analyzed, demonstrating strong psychometric properties. Convergent evidence is assessed by correlating MMQ subscales with the Interpersonal Reactivity Index (IRI) and Empathy Quotient (EQ), while divergent evidence is assessed by correlating aggressive traits using the Buss-Perry Aggression Questionnaire (BPAQ). The study also explores gender differences and age. Results reveal positive correlations between good mentalizing and empathy, particularly cognitive empathy, supporting the significance of positive mentalization in empathy. Negative mentalization is associated with difficulties in perspective-taking and social skills, as well as aggressive traits. Gender differences in mentalizing capacities are observed, and negative aspects of mentalization decrease with age. The availability of the Spanish translation of the MMQ, the first self-reporting scale measuring mentalization adapted to Chilean population, contributes to research aiming to understand its relationship with other psychological phenomena in different cultural context and facilitating clinical interventions with different population groups. We therefore encourage further investigation into cultural, gender and age differences in mentalization.

The population of pensioners remains on the rise in Ghana coupled with an intrinsic need for sexual activity and satisfaction. However, data on factors associated with sexual satisfaction among pensioners are limited in Ghana. The aim of this study was to examine the predictors of sexual satisfaction among Social Security and National Insurance Trust pensioners in the Greater Accra Region of Ghana. We employed a cross-sectional survey design in this study. Participants were recruited using cluster and stratified sampling techniques. Our analytical sample was 410 participants. Ordinal logistic regressions were employed to determine predictors of sexual satisfaction among the participants. The significance of the test was set at a p-value ≤ 0.05. The results showed that participants who were household head (AOR: 1.874, 95% CI: 1.037–3.388), who did not incur any expenditure on their household in a month (AOR: 6.290, 95% CI: 1.758–22.511) and those who undertake daily exercises were significantly (AOR: 1.981, 95% CI: 1.276–3.075) more likely to fall in one of the higher categories of sexual satisfaction compared to their counterparts. Also, the study revealed that those with secondary education (AOR:.503, 95% CI:.253-.0.999), who were in the public sector (AOR:.449, 95% CI:.237 −.850), who were very dissatisfied with health service access/use (AOR:.032, 95% CI:.002−.421) and not able to determine whether they were satisfied or dissatisfied with their health status (AOR:.518, 95% CI:.329−.816) were significantly less likely to fall in one of the higher categories of sexual satisfaction. Findings of this study suggest that household headship, education level, employment sector, expenditure on household, satisfaction with health services/use, daily exercises intake and satisfaction with health status were associated with sexual satisfaction among the participants. In relation to our findings, the implications for policy, practice and future research have been discussed for the attention of policy makers and researchers.