The impact of the Global Programme to Eliminate Lymphatic Filariasis (GPELF) (initiated in 2000 in Ghana and ran for 12 years) in mitigating soil-transmitted helminth (STH) infections in LF-endemic areas is unknown. During a 1-year hiatus which ensued between 2011 and 2012, a longitudinal study was conducted to determine GPELF effect on hookworm infections in selected communities involved in the programme since its inception, while measuring the effectiveness of biannual ALB treatments on schoolchildren living in such communities. A total of 399 school children aged 3 to 18 years were randomly selected from four communities in the Kpandai district of northern Ghana. Each presented a single stool sample at baseline, 21 days post-treatment, at the 3rd and 6th months, 21 days post-second intervention (i.e. following sample collection and treatment with ALB in the 6th month), and in the ninth month of the study period. Haemoglobin (hb) levels were also measured at all time points using finger prick blood samples and a URIT digital test kit. Each participant submitting a sample, was treated with a single-dose ALB (400mg) at baseline and in the sixth month. Stool samples were processed by preparing duplicate Kato-Katz slides per sample, and examined by microscopy. The Body Mass Index-for-age z-scores (BAZ) of participants were assessed following the determination of BMIs at each time point by measuring their height and weight with a stadiometer and weighing scale. Overall hookworm prevalences were 25.68% (95% CI = 20.51–31.75) at baseline, 11.18% (95% CI = 7.87–15.41) 21 days post-treatment, 11.78% (95% CI = 8.38–16.11) and 6.95% (95% CI = 4.41–10.43) in the 3rd and 6th months, 0.91% (95% CI = 0.19–2.65) 21 days post-second intervention, and 8.46% (95% CI = 5.62–12.23) in the ninth month. Observed overall faecal egg count reduction rates (ERRs) were 94.21% (95% CI = 81.50%– 100.00%) 21 days after baseline treatment, 97.70% (95% CI = 85.08–100.00) and 96.95% (95% CI = 84.18%– 100.00%) in the 3rd and 6th months, 99.98% (95% CI = 86.42%– 100.00%) 21 days post-second intervention, and 17.18% (95% CI = 14.07%– 20.67%) in the 9th month. Respective cure rates (CRs) were 62.35% (95% CI = 46.71–81.56%), 85.88% (95% CI = 67.32–100.00%), 87.06% (95% CI = 68.36%– 100.00%), 98.82% (95% CI = 78.83%– 100.00%), and 36.36% (95% CI = 9.91%– 93.11%). Additionally, increases in the percent frequency of ‘normal hb’ (p < 0.01) were observed across the study time points, whilst ‘normal BAZ’ cases remained high (from 94.87% to 98.87%) throughout the study period. These findings primarily indicate satisfactory effectiveness of ALB which may be maintainable in mass drug administration programmes by the modification of treatment strategies from annual to bi-annual regimes. This could minimize the likelihood of emerging poorly-responding hookworm phenotypes in Ghana. Additionally, a positive impact of bi-annual treatment on participant anaemia status is herein indicated with particular regard to the school children in our cohort.

BackgroundThe risk factors for tuberculosis (TB) disease development in children remained understudied, particularly in low-income countries like Ethiopia. The objective of this study was to identify determinants of TB disease development in general and in relation to BCG vaccination in children in central Ethiopia.MethodsWe employed a 1:1 age-matched case-control design to compare the characteristics of children who developed TB (cases) with those who did not (controls). Data were collected in healthcare facilities in Addis Ababa city, Adama, and Bishoftu towns between September 25, 2021, and June 24, 2022. Two hundred and fifty-six cases were drawn at random from a list of childhood TB patients entered into SPSS software, and 256 controls were selected sequentially at triage from the same healthcare facilities where the cases were treated. A bivariate conditional logistic regression analysis was performed first to select candidate variables with p-values less than or equal to 0.20 for the multivariable model. Finally, variables with a p-value less than 0.05 for a matched adjusted odds ratio (mORadj) were reported as independent determinants of TB disease development.ResultsThe mean age of the cases was nine years, while that of the controls was 10 years. Males comprised 126 cases (49.2%) and 119 controls (46.5%), with the remainder being females. Ninety-nine (38.7%) of the cases were not BCG-vaccinated, compared to 58 (22.7%) of the controls. Household TB contact was experienced by 43 (16.8%) of the cases and 10 (3.9%) of the controls. Twenty-two (8.6%) of the cases and six (2.3%) of the controls were exposed to a cigarette smoker in their household. Twenty-two (8.6%) of the cases and three (1.2%) of the controls were positive for HIV. Children who were not vaccinated with BCG at birth or within two weeks of birth had more than twice the odds (mORadj = 2.11, 95% CI = 1.28–3.48) of developing TB compared to those who were. Children who ever lived with a TB-sick family member (mORadj = 4.28, 95% CI = 1.95–9.39), smoking family members (mORadj = 3.15, 95% CI = 1.07–9.27), and HIV-infected children (mORadj = 8.71, 95% CI = 1.96–38.66) also had higher odds of developing TB disease than their counterparts.ConclusionsBeing BCG-unvaccinated, having household TB contact, having a smoker in the household, and being HIV-infected were found to be independent determinants of TB disease development among children.

The General Household Survey (GHS) is a continuous national survey of people living in private households conducted on an annual basis, by the Social Survey Division of the Office for National Statistics (ONS). The main aim of the survey is to collect data on a range of core topics, covering household, family and individual information. This information is used by government departments and other organisations for planning, policy and monitoring purposes, and to present a picture of house holds, family and people in Great Britain. From 2008, the General Household Survey became a module of the Integrated Household Survey (IHS). In recognition, the survey was renamed the General Lifestyle Survey (GLF/GLS). The GHS started in 1971 and has been carried out continuously since then, except for breaks in 1997-1998 when the survey was reviewed, and 1999-2000 when the survey was redeveloped. Following the 1997 review, the survey was relaunched from April 2000 with a different design. The relevant development work and the changes made are fully described in the Living in Britain report for the 2000-2001 survey. Following its review, the GHS was changed to comprise two elements: the continuous survey and extra modules, or 'trailers'. The continuous survey remained unchanged from 2000 to 2004, apart from essential adjustments to take account of, for example, changes in benefits and pensions. The GHS retained its modular structure and this allowed a number of different trailers to be included for each of those years, to a plan agreed by sponsoring government departments. Further changes to the GHS methodology from 2005: From April 1994 to 2005, the GHS was conducted on a financial year basis, with fieldwork spread evenly from April of one year to March the following year. However, in 2005 the survey period reverted to a calendar year and the whole of the annual sample was surveyed in the nine months from April to December 2005. Future surveys will run from January to December each year, hence the title date change to single year from 2005 onwards. Since the 2005 GHS (held under SN 5640) does not cover the January-March quarter, this affects annual estimates for topics which are subject to seasonal variation. To rectify this, where the questions were the same in 2005 as in 2004-2005, the final quarter of the latter survey was added (weighted in the correct proportion) to the nine months of the 2005 survey. Furthermore, in 2005, the European Union (EU) made a legal obligation (EU-SILC) for member states to collect additional statistics on income and living conditions. In addition to this the EU-SILC data cover poverty and social exclusion. These statistics are used to help plan and monitor European social policy by comparing poverty indicators and changes over time across the EU. The EU-SILC requirement has been integrated into the GHS, leading to large-scale changes in the 2005 survey questionnaire. The trailers on 'Views of your Local Area' and 'Dental Health' have been removed. Other changes have been made to many of the standard questionnaire sections, details of which may be found in the GHS 2005 documentation. Further changes to the GLF/GHS methodology from 2008 As noted above, the General Household Survey (GHS) was renamed the General Lifestyle Survey (GLF/GLS) in 2008. The sample design of the GLF/GLS is the same as the GHS before, and the questionnaire remains largely the same. The main change is that the GLF now includes the IHS core questions, which are common to all of the separate modules that together comprise the IHS. Some of these core questions are simpl y questions that were previously asked in the same or a similar format on all of the IHS component surveys (including the GLF/GLS). The core questions cover employment, smoking prevalence, general health, ethnicity, citizenship and national identity. These questions are asked by proxy if an interview is not possible with the selected respondent (that is a member of the household can answer on behalf of other respondents in the household). This is a departure from the GHS which did not ask smoking prevalence and general health questions by proxy, whereas the GLF/GLS does from 2008. For details on other changes to the GLF/GLS questionnaire, please see the GLF/GLS 2008: Special Licence Access documentation held with SN 6414. Currently, the UK Data Archive holds only the SL (and not the EUL) version of the GLF/GLS for 2008. Changes to the drinking section There have been a number of revisions to the methodology that is used to produce the alcohol consumption estimates. In 2006, the average number of units assigned to the different drink types and the assumption around the average size of a wine glass was updated, resulting in significantly increased consumption estimates. In addition to the revised method, a new question about wine glass size was included in the survey in 2008. Respondents were asked whether they have consumed small (125 ml), standard (175 ml) or large (250 ml) glasses of wine. The data from this question are used when calculating the number of units of alcohol consumed by the respondent. It is assumed that a small glass contains 1.5 units, a standard glass contains 2 units and a large glass contains 3 units. (In 2006 and 2007 it was assumed that all respondents drank from a standard 175 ml glass containing 2 units.) The datasets contain the original set of variables based on the original methodology, as well as those based on the revised and (for 2008 onwards) updated methodologies. Further details on these changes are provided in the Guidelines documents held in SN 5804 - GHS 2006; and SN 6414 - GLF/GLS 2008: Special Licence Access. Special Licence GHS/GLF/GLS Special Licence (SL) versions of the GHS/GLF/GLS are available from 1998-1999 onwards. The SL versions include all variables held in the standard 'End User Licence' (EUL) version, plus extra variables covering cigarette codes and descriptions, and some birthdate information for respondents and household members. Prospective SL users will need to complete an extra application form and demonstrate to the data owners exactly why they need access to t he extra variables, in order to get permission to use the SL version. Therefore, most users should order the EUL version of the data. In order to help users choose the correct dataset, 'Special Licence Access' has been added to the dataset titles for the SL versions of the data. A list of all GHS/GLF/GLS studies available from the UK Data Archive may be found on the GHS/GLF/GLS major studies web page. See below for details of SL datasets for the corresponding GHS/GLF/GLS year (1998-1999 onwards only). UK Data Archive data holdings and formats The UK Data Archive GHS/GLF/GLS holdings begin with the 1971 study for EUL data, and from 1998-1999 for SL versions (see above). Users should note that data for the 1971 study are currently only available as ASCII files without accompanying SPSS set-up files. SPSS files for the 1972 study were created by John Simister, and redeposited at the Archive in 2000. Currently, the UK Data Archive holds only the SL versions of the GHS/GLF/GLS for 2007 and 2008. Reformatted Data 1973 to 1982 - Surrey SPSS Files SPSS files have been created by the University of Surrey for all study years from 1973 to 1982 inclusive. These early files were restructured and the case changed from the household to the individual with all of the household information duplicated for each individual. The Surrey SPSS files contain all the original variabl es as well as some extra derived variables (a few variables were omitted from the data files for 1973-76). In 1973 only, the section on leisure was not included in the Surrey SPSS files. This has subsequently been made available, however, and is now held in a separate study, General Household Survey, 1973: Leisure Questions (held under SN 3982). Records for the original GHS 1973-1982 ASCII files have been removed from the UK Data Archive catalogue, but the data are still preserved and available upon request. Users should note that GHS/GLF/GLS data are also available in formats other than SPSS.

Abstract

The main objective of the HEIS survey is to obtain detailed data on household expenditure and income, linked to various demographic and socio-economic variables, to enable computation of poverty indices and determine the characteristics of the poor and prepare poverty maps. Therefore, to achieve these goals, the sample had to be representative on the sub-district level. The raw survey data provided by the Statistical Office was cleaned and harmonized by the Economic Research Forum, in the context of a major research project to develop and expand knowledge on equity and inequality in the Arab region. The main focus of the project is to measure the magnitude and direction of change in inequality and to understand the complex contributing social, political and economic forces influencing its levels. However, the measurement and analysis of the magnitude and direction of change in this inequality cannot be consistently carried out without harmonized and comparable micro-level data on income and expenditures. Therefore, one important component of this research project is securing and harmonizing household surveys from as many countries in the region as possible, adhering to international statistics on household living standards distribution. Once the dataset has been compiled, the Economic Research Forum makes it available, subject to confidentiality agreements, to all researchers and institutions concerned with data collection and issues of inequality.

Data collected through the survey helped in achieving the following objectives: 1. Provide data weights that reflect the relative importance of consumer expenditure items used in the preparation of the consumer price index 2. Study the consumer expenditure pattern prevailing in the society and the impact of demographic and socio-economic variables on those patterns 3. Calculate the average annual income of the household and the individual, and assess the relationship between income and different economic and social factors, such as profession and educational level of the head of the household and other indicators 4. Study the distribution of individuals and households by income and expenditure categories and analyze the factors associated with it 5. Provide the necessary data for the national accounts related to overall consumption and income of the household sector 6. Provide the necessary income data to serve in calculating poverty indices and identifying the poor characteristics as well as drawing poverty maps 7. Provide the data necessary for the formulation, follow-up and evaluation of economic and social development programs, including those addressed to eradicate poverty

Geographic coverage

National

Analysis unit

• Households
• Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

The Household Expenditure and Income survey sample for 2010, was designed to serve the basic objectives of the survey through providing a relatively large sample in each sub-district to enable drawing a poverty map in Jordan. The General Census of Population and Housing in 2004 provided a detailed framework for housing and households for different administrative levels in the country. Jordan is administratively divided into 12 governorates, each governorate is composed of a number of districts, each district (Liwa) includes one or more sub-district (Qada). In each sub-district, there are a number of communities (cities and villages). Each community was divided into a number of blocks. Where in each block, the number of houses ranged between 60 and 100 houses. Nomads, persons living in collective dwellings such as hotels, hospitals and prison were excluded from the survey framework.

A two stage stratified cluster sampling technique was used. In the first stage, a cluster sample proportional to the size was uniformly selected, where the number of households in each cluster was considered the weight of the cluster. At the second stage, a sample of 8 households was selected from each cluster, in addition to another 4 households selected as a backup for the basic sample, using a systematic sampling technique. Those 4 households were sampled to be used during the first visit to the block in case the visit to the original household selected is not possible for any reason. For the purposes of this survey, each sub-district was considered a separate stratum to ensure the possibility of producing results on the sub-district level. In this respect, the survey framework adopted that provided by the General Census of Population and Housing Census in dividing the sample strata. To estimate the sample size, the coefficient of variation and the design effect of the expenditure variable provided in the Household Expenditure and Income Survey for the year 2008 was calculated for each sub-district. These results were used to estimate the sample size on the sub-district level so that the coefficient of variation for the expenditure variable in each sub-district is less than 10%, at a minimum, of the number of clusters in the same sub-district (6 clusters). This is to ensure adequate presentation of clusters in different administrative areas to enable drawing an indicative poverty map.

It should be noted that in addition to the standard non response rate assumed, higher rates were expected in areas where poor households are concentrated in major cities. Therefore, those were taken into consideration during the sampling design phase, and a higher number of households were selected from those areas, aiming at well covering all regions where poverty spreads.

Mode of data collection

Face-to-face [f2f]

Research instrument

• General form
• Expenditure on food commodities form
• Expenditure on non-food commodities form

Cleaning operations

Raw Data: - Organizing forms/questionnaires: A compatible archive system was used to classify the forms according to different rounds throughout the year. A registry was prepared to indicate different stages of the process of data checking, coding and entry till forms were back to the archive system. - Data office checking: This phase was achieved concurrently with the data collection phase in the field where questionnaires completed in the field were immediately sent to data office checking phase. - Data coding: A team was trained to work on the data coding phase, which in this survey is only limited to education specialization, profession and economic activity. In this respect, international classifications were used, while for the rest of the questions, coding was predefined during the design phase. - Data entry/validation: A team consisting of system analysts, programmers and data entry personnel were working on the data at this stage. System analysts and programmers started by identifying the survey framework and questionnaire fields to help build computerized data entry forms. A set of validation rules were added to the entry form to ensure accuracy of data entered. A team was then trained to complete the data entry process. Forms prepared for data entry were provided by the archive department to ensure forms are correctly extracted and put back in the archive system. A data validation process was run on the data to ensure the data entered is free of errors. - Results tabulation and dissemination: After the completion of all data processing operations, ORACLE was used to tabulate the survey final results. Those results were further checked using similar outputs from SPSS to ensure that tabulations produced were correct. A check was also run on each table to guarantee consistency of figures presented, together with required editing for tables' titles and report formatting.

Harmonized Data: - The Statistical Package for Social Science (SPSS) was used to clean and harmonize the datasets. - The harmonization process started with cleaning all raw data files received from the Statistical Office. - Cleaned data files were then merged to produce one data file on the individual level containing all variables subject to harmonization. - A country-specific program was generated for each dataset to generate/compute/recode/rename/format/label harmonized variables. - A post-harmonization cleaning process was run on the data. - Harmonized data was saved on the household as well as the individual level, in SPSS and converted to STATA format.

Abstract (en): This survey is the first broad-based, systematic examination of the nature of civil litigation in state general jurisdiction trial courts. Data collection was carried out by the National Center for State Courts with assistance from the National Association of Criminal Justice Planners and the United States Bureau of the Census. The data collection produced two datasets. Part 1, Tort, Contract, and Real Property Rights Data, is a merged sample of approximately 30,000 tort, contract, and real property rights cases disposed during the 12-month period ending June 30, 1992. Part 2, Civil Jury Cases Data, is a sample of about 6,500 jury trial cases disposed over the same time period. Data collected include information about litigants, case type, disposition type, processing time, case outcome, and award amounts for civil jury cases. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Performed consistency checks.; Standardized missing values.; Checked for undocumented or out-of-range codes.. Forty-five jurisdictions chosen to represent the 75 most populous counties in the nation. The sample for this study was designed and selected by the United States Bureau of the Census. It was a two-stage stratified sample with 45 of the 75 most populous counties selected at the first stage. The top 75 counties account for about 37 percent of the United States population and about half of all civil filings. The 75 counties were divided into four strata based on aggregate civil disposition data for 1990 obtained through telephone interviews with court staffs in the general jurisdiction trial courts. The sample consisted of tort, contract, and real property rights cases disposed between July 1, 1991, and June 30, 1992. 2011-11-02 All parts are being moved to restricted access and will be available only using the restricted access procedures.2006-03-30 File CB6587.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads.2006-03-30 File CB6587.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads.2006-03-30 File CB6587.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads.2006-03-30 File CB6587.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads.2006-03-30 File CB6587.ALL.PDF was removed from any previous datasets and flagged as a study-level file, so that it will accompany all downloads.2005-11-04 On 2005-03-14 new files were added to one or more datasets. These files included additional setup files as well as one or more of the following: SAS program, SAS transport, SPSS portable, and Stata system files. The metadata record was revised 2005-11-04 to reflect these additions.2004-06-01 The data have been updated by the principal investigator to include replicate weights and a few other variables. The codebook and SAS and SPSS data definition statements have been revised to reflect these changes.2001-03-26 The data have been updated by the principal investigator to include replicate weights. The codebook and SAS and SPSS data definition statements have been revised to reflect these changes.2001-03-26 The data had been updated by the principal investigator to include replicate weights. The codebook and SAS and SPSS data definition statements had been revised to reflect these changes.1997-07-29 The codebook had been revised to correct errors documenting both data files. Column location (and width) of variable WGHT "TOTAL WEIGHT" was incorrectly shown as 10.4 for Part 1, Tort, Contract, and Real Property Data. It was accurately shown in the data definition statements as 9.4. Variables listed after WGHT were inaccurately reported one column off in the codebook. Similarly, column location (and width) of variable WGHT "TOTAL WEIGHT" was incorrectly shown as 10.2 for Part 2, Civil Jury Data. It was accurately shown in the data definition statements as 9.2. Variables listed after WGHT were inaccurately reported one column off in the codebook. Fundi...

The study titled "Effect of Corporate Social Responsibility (CSR) on customer loyalty with the mediating role of customer satisfaction: the case of commercial banks in Ethiopia" aims to investigate the relationship between CSR initiatives, customer satisfaction, and customer loyalty within the context of commercial banks in Ethiopia. The research is predominantly explanatory in nature, seeking to understand how CSR practices impact customer loyalty through the mediating role of customer satisfaction.Data for this study was collected using a structured questionnaire as the data collection instrument. The respondents involved in the study were customers of commercial banks in Ethiopia, with a total sample size of 790 individuals. Purposive sampling techniques were employed to select respondents who have direct experience with the services provided by commercial banks.The analysis of the data was conducted using the AMOS structural equation model in conjunction with SPSS software to test and evaluate the hypotheses formulated in the study. The data description includes detailed information on the demographic characteristics of the respondents, allowing for a comprehensive understanding of the sample profile.Furthermore, the data collected encompasses various dimensions related to CSR initiatives, including economic, legal, ethical, philanthropic, environmental aspects. Additionally, customer satisfaction and customer loyalty related data are included to assess the impact of CSR on customer loyalty through the mediating role of customer satisfaction. This comprehensive dataset provides valuable insights into the relationships between CSR practices, customer satisfaction, and customer loyalty in the context of commercial banks in Ethiopia.

This dataset consists of the responses to a quantitative survey among the managers of Cultural and Creative Industries (CCIs) to collect data on their Strategic Management mind-set and practices, with special focus on performance evaluation. The questionnaire was composed using the core elements of a similar Danish study (Tscherning and Boxenbaum 2011) targeted at creative enterprises and a self-assessment tool introduced in the United States (BTW Consultants 2010).

A Likert-scale was used, thus the respondents had (in most of the cases) five options to choose from (from full agreement to total disagreement). As the questionnaire was anonymous, there was no reason to believe that managers would intentionally hide their challenges or aspirations, or make their daily evaluation practices look better or worse than they are in reality.

The study was designed as a systematic sampling survey, which allowed making inferences about the whole population of CCIs in Estonia on the basis of a carefully selected subset. Since different umbrella organisations have an important role in providing information to CCIs, they were asked to spread the request to fill out the questionnaire. Also, the contact databases of Estonian Customs and Tax Board were used for sending requests to fill in the questionnaire. In total, the request with the link to the online questionnaire was delivered to approximately 2,000 contacts, whereas the response rate was approximately 23%. The online survey environment in Google Forms was accessible to participants for roughly two-and-a-half months (from mid-January until the end of March 2016).

This raw dataset (based on 503 responses) is in SPSS format, as the data was analysed using SPSS.

Factors associated with NNM in selected public hospitals of Jimma zone, southwest Ethiopia, 2020 (n = 255).

Data from: Doctoral dissertation; Preprint article entitled: Managers' and physicians’ perception of palm vein technology adoption in the healthcare industry. Formats of the files associated with dataset: CSV; SAV. SPSS setup files can be used to generate native SPSS file formats such as SPSS system files and SPSS portable files. SPSS setup files generally include the following SPSS sections: DATA LIST: Assigns the name, type, decimal specification (if any), and specifies the beginning and ending column locations for each variable in the data file. Users must replace the "physical-filename" with host computer-specific input file specifications. For example, users on Windows platforms should replace "physical-filename" with "C:\06512-0001-Data.txt" for the data file named "06512-0001-Data.txt" located on the root directory "C:". VARIABLE LABELS: Assigns descriptive labels to all variables. Variable labels and variable names may be identical for some variables. VALUE LABELS: Assigns descriptive labels to codes in the data file. Not all variables necessarily have assigned value labels. MISSING VALUES: Declares user-defined missing values. Not all variables in the data file necessarily have user-defined missing values. These values can be treated specially in data transformations, statistical calculations, and case selection. MISSING VALUE RECODE: Sets user-defined numeric missing values to missing as interpreted by the SPSS system. Only variables with user-defined missing values are included in the statements. ABSTRACT: The purpose of the article is to examine the factors that influence the adoption of palm vein technology by considering the healthcare managers’ and physicians’ perception, using the Unified Theory of Acceptance and Use of Technology theoretical foundation. A quantitative approach was used for this study through which an exploratory research design was utilized. A cross-sectional questionnaire was distributed to responders who were managers and physicians in the healthcare industry and who had previous experience with palm vein technology. The perceived factors tested for correlation with adoption were perceived usefulness, complexity, security, peer influence, and relative advantage. A Pearson product-moment correlation coefficient was used to test the correlation between the perceived factors and palm vein technology. The results showed that perceived usefulness, security, and peer influence are important factors for adoption. Study limitations included purposive sampling from a single industry (healthcare) and limited literature was available with regard to managers’ and physicians’ perception of palm vein technology adoption in the healthcare industry. Researchers could focus on an examination of the impact of mediating variables on palm vein technology adoption in future studies. The study offers managers insight into the important factors that need to be considered in adopting palm vein technology. With biometric technology becoming pervasive, the study seeks to provide managers with the insight in managing the adoption of palm vein technology. KEYWORDS: biometrics, human identification, image recognition, palm vein authentication, technology adoption, user acceptance, palm vein technology

The dataset is a part of the survey conducted in Ho Chi Minh City and Dong Nai the Southeast region of Vietnam in 2020 to collect information for research on fertility. The main research purpose is to identify the socioeconomic determinants of low fertility in the Southeast. In total 808 individuals in the main reproductive age were interviewed, including 382 cases from Dong Nai and 426 cases from Ho Chi Minh City, or 273 unmarried persons and 535 married women. Information about family size desires and socio-demographic characteristics of 535 married men were asked when interviewing their spouses. As such, the survey collected information on the family size desires of 1343 individuals. The dataset has been converted to SPSS format (version 26.0). For data analysis, the dataset need to be weighted (WEI variable) as individuals were not selected with equal probability.

Abstract

The basic goal of this survey is to provide the necessary database for formulating national policies at various levels. It represents the contribution of the household sector to the Gross National Product (GNP). Household Surveys help as well in determining the incidence of poverty, and providing weighted data which reflects the relative importance of the consumption items to be employed in determining the benchmark for rates and prices of items and services. Generally, the Household Expenditure and Consumption Survey is a fundamental cornerstone in the process of studying the nutritional status in the Palestinian territory.

The raw survey data provided by the Statistical Office was cleaned and harmonized by the Economic Research Forum, in the context of a major research project to develop and expand knowledge on equity and inequality in the Arab region. The main focus of the project is to measure the magnitude and direction of change in inequality and to understand the complex contributing social, political and economic forces influencing its levels. However, the measurement and analysis of the magnitude and direction of change in this inequality cannot be consistently carried out without harmonized and comparable micro-level data on income and expenditures. Therefore, one important component of this research project is securing and harmonizing household surveys from as many countries in the region as possible, adhering to international statistics on household living standards distribution. Once the dataset has been compiled, the Economic Research Forum makes it available, subject to confidentiality agreements, to all researchers and institutions concerned with data collection and issues of inequality. Data is a public good, in the interest of the region, and it is consistent with the Economic Research Forum's mandate to make micro data available, aiding regional research on this important topic.

Geographic coverage

The survey data covers urban, rural and camp areas in West Bank and Gaza Strip.

Analysis unit

1- Household/families. 2- Individuals.

Universe

The survey covered all the Palestinian households who are a usual residence in the Palestinian Territory.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample and Frame:

The sampling frame consists of all enumeration areas which enumerated in 1997 and the numeration area consists of buildings and housing units and has in average about 150 households in it. We use the enumeration areas as primary sampling units PSUs in the first stage of the sampling selection. The enumeration areas of the master sample were updated in 2003.

Sample Design:

The sample is stratified cluster systematic random sample with two stages: First stage: selection a systematic random sample of 120 enumeration areas. Second stage: selection a systematic random sample of 12-18 households from each enumeration area selected in the first stage.

Sample strata:

The population is divided by: 1-Region (North West Bank, Middle West Bank, South West Bank, Gaza Strip) 2-Type of Locality (urban, rural, refugee camps)

Target cluster size:

The target cluster size or "sample-take" is the average number of households to be selected per PSU. In this survey, the sample take is around 12 households.

Sample Size:

The calculated sample size is 1,714 households, the completed households were 1,231 (812 in the west bank and 419 in the Gaza strip).

Mode of data collection

Face-to-face [f2f]

Research instrument

The PECS questionnaire consists of two main sections:

First section: Certain articles / provisions of the form filled at the beginning of the month, and the remainder filled out at the end of the month. The questionnaire includes the following provisions:

Cover sheet: It contains detailed and particulars of the family, date of visit, particular of the field/office work team, number/sex of the family members.

Statement of the family members: Contains social, economic and demographic particulars of the selected family.

Statement of the long-lasting commodities and income generation activities: Includes a number of basic and indispensable items (i.e., Livestock, or agricultural lands).

Housing Characteristics: Includes information and data pertaining to the housing conditions, including type of shelter, number of rooms, ownership, rent, water, electricity supply, connection to the sewer system, source of cooking and heating fuel, and remoteness/proximity of the house to education and health facilities.

Monthly and Annual Income: Data pertaining to the income of the family is collected from different sources at the end of the registration / recording period.

Assistance and poverty: includes questions about household conditions and assistances that got through the the past month.

Second section: The second section of the questionnaire includes a list of 55 consumption and expenditure groups itemized and serially numbered according to its importance to the family. Each of these groups contains important commodities. The number of commodities items in each for all groups stood at 667 commodities and services items. Groups 1-21 include food, drink, and cigarettes. Group 22 includes homemade commodities. Groups 23-45 include all items except for food, drink and cigarettes. Groups 50-55 include all of the long-lasting commodities. Data on each of these groups was collected over different intervals of time so as to reflect expenditure over a period of one full year, except the cars group the data of which was collected for three previous years. These data was abotained from the recording book which is covered a period of month for each household.

Cleaning operations

Raw Data

Data editing took place through a number of stages, including: 1. Office editing and coding 2. Data entry 3. Structure checking and completeness 4. Structural checking of SPSS data files

Harmonized Data

• The Statistical Package for Social Science (SPSS) is used to clean and harmonize the datasets.
• The harmonization process starts with cleaning all raw data files received from the Statistical Office.
• Cleaned data files are then all merged to produce one data file on the individual level containing all variables subject to harmonization.
• A country-specific program is generated for each dataset to generate/compute/recode/rename/format/label harmonized variables.
• A post-harmonization cleaning process is run on the data.
• Harmonized data is saved on the household as well as the individual level, in SPSS and converted to STATA format.

Response rate

The survey sample consists of about 1,714 households interviewed over a twelve months period between (January 2007-January 2008).1,231 households completed the interview, of which 812 were from the West Bank and 419 households in Gaza Strip; the response rate was 71.8% in the Palestinian Territory.

Sampling error estimates

The calculations of standard errors for the main survey estimates enable the user to identify the accuracy of estimates and the survey reliability. Total errors of the survey can be divided into two kinds: statistical errors, and non-statistical errors. Non-statistical errors are related to the procedures of statistical work at different stages, such as the failure to explain questions in the questionnaire, unwillingness or inability to provide correct responses, bad statistical coverage, etc. These errors depend on the nature of the work, training, supervision, and conducting of all the various related activities. The work team spared no effort at the different stages to minimize non-statistical errors; however, it is difficult to estimate numerically such errors due to absence of technical computation methods based on theoretical principles to tackle them. On the other hand, statistical errors can be measured. Frequently they are measured by the standard error, which is the positive square root of the variance. The variance of this survey has been computed by using the "programming package" CENVAR

Data appraisal

The impact of errors on the data quality was reduced to the minimal due to the high efficiency and outstanding selection, training, and performance of the fieldworkers. Procedures adopted during the fieldwork of the survey were considered a necessity to ensure the collection of accurate data, notably: 1) Develop schedules to conduct field visits to households during survey fieldwork. The objectives of the visits and the data that is collected on each visit were predetermined. 2) Fieldwork editing rules were applied during the data collection to ensure corrections were implemented before the end of fieldwork activities 3) Fieldworker were instructed to provide details in case of extreme expenditure or consumption of the household. 4) Postpone the questions on income to the last visit at the end of the month 5) Validation rules were embedded in the data processing systems along with procedures to verify data entry and data editing.

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