A questionnaire (PDF 103KB) for the second round of the Social Impact of COVID-19 survey was conducted by the CSO from 13th-19th August. Individuals selected received an email from the CSO and were asked to complete the questionnaire online. The questionnaire asked for information on the following topics:
This survey is the third in a series on the Social Impact of COVID-19. The sample was generated from Labour Force Survey (LFS) respondents that agreed to be contacted for further research and provided an email address and phone number. The Labour Force Survey is a 2-stage sample design stratified using Administrative County and the Pobal HP Deprivation Index.
This Social Impact of COVID-19 survey is third such survey conducted by the CSO. The sample selection methodology resulted in a sample of 2,226 people.
All potential respondents were contacted by email and were asked to complete an online questionnaire. Data collection was closed on Wednesday 19th August 2020, at which point the achieved sample was 1,333 individuals.
Timeliness was a key priority in this survey and therefore the sample and subsequent weighting process is one of convenience to some extent. Some consideration needs to be given to the potential impact of sample design on response rates and achieved sample:
The weighting procedure outlined below was designed to adjust for possible bias in the achieved sample as much as possible.
The following weighting process was devised to counteract some of the potential bias within the sample, and to make the final weighted sample distribution as representative as possible of the population.
In the first stage of the weighting process, each person in the sample was given a weight of 1. We utilised the current LFS non-response adjustment process, in which a stepwise logistic regression was conducted based on census household-level data, to generate response propensities based upon the following characteristics:
The sample is then grouped into strata based on propensity score, for which non-response adjustments were calculated and applied to each respondent.
In stage 2, Q2 2020 LFS population estimates were used to benchmark the dataset across key characteristics for calibration. The non-response adjustments were inflated match overall the population total and then calibrated using CALMAR, to ensure that weighted sample distributions matched the Q2 2020 benchmark distributions for a number of key characteristics such as gender, age, education level, region, urban/rural location, household composition.
As outlined above, non-response adjustment has been used to address some of the imbalances between the original sample design and the achieved sample distribution as much as possible, and the subsequent calibration adjusts to key population totals to try and match current population distributions. However, given the non-random nature of the final sample selected, it is unlikely that we can fully account fully for bias inherent in the final sample. For this reason, caution should be taken when attempting to make inferences to the entire population from these results.
 CALMAR is the statistical software developed by INSEE. Calmar is a SAS macro program that implements the calibration approach and adjusts weights assigned to individuals using auxiliary variables.
The questionnaire focused on the impact of school closures and concerns about returning to school, as well as questions on levels of compliance with government guidelines and wellbeing indicators such as life satisfaction, financial satisfaction and satisfaction with personal relationships.
Some key analysis variables within this publication are:
This analysis variable is broken down by:
This analysis variable is broken down by:
This classification is derived from a single question and refers to educational standards that have been attained and can be compared in some measurable way and it is included in the core LFS on an ongoing basis.
The question is phrased as follows:
What is the highest level of education or training you have ever successfully completed?
For the purposes of this publication these have been classified as follows:
In 2018, the Survey on Income and Living Conditions (SILC) carried out an ad-hoc module on “Material deprivation, well-being and housing difficulties”, which itself provides comparisons with the SILC 2013 “Well-being” module. These surveys provided an interesting reference point for the Social Impact of COVID-19 survey conducted in April 2020. The wellbeing questions in this August survey aim to provide some further insight into feelings of wellbeing in Ireland. While the methodologies across all surveys differ and care should be taken in the interpretation of trends over time, nonetheless the findings from these surveys present an important perspective on the impact of COVID19 in Ireland.
Areas are classified as Urban or Rural based on the following population densities derived from Census of Population 2016:
Regional analysis is presented in this publication are based on the NUTS2 (Nomenclature of Territorial Units) classification used by Eurostat. The regions are categorised as follows:
These regions are comprised as follows:
Northern & Western
Eastern & Midland
The Central Statistics Office wishes to thank the participants for their co-operation in agreeing to take part in the Social Impact of COVID-19 Survey and for facilitating the collection of the relevant data.
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