Computer Assisted Interview methods are being increasingly used in survey implementation. Questionnaires implemented in this way can utilise in-built features to improve the flow of the questionnaire for the interviewer and respondent versus pen and paper questionnaires. This not only lowers respondent burden, but it also increases the ability to create more varied and wide-ranging questionnaires which is more difficult to manage through PAPI. Furthermore the ability to capture data electronically creates both data quality and efficiency gains given the possibility to implement improved real-time validations and the removal of the need for manual data entry. As such, CAPI and other computer assisted interviewing methods offer a wide range of benefits both for data quality but also in efficiency, flexibility and adaptability of surveys.
The work-related modules are designed to produce core labour statistics aligned with the latest ICLS standards and good survey practice including:
Additional modules covering key background characteristics to generate indicators and disaggregations as needed to support monitoring of Decent Work, SDGs and other national and global goals, are also provided including: basic demographics, education, migration status and disability status, aligned with the latest international standards and survey practice on those topics.
(Latest: Version 3, Jul 2019)
|Approach 1||Approach 2||Approach 3|
|ILO model LFS questionnaire for CAPI - Demographic and background characteristics (v3, 2019)||Word PDF|
|ILO model LFS questionnaire for CAPI - Labour Modules (v3, 2019)||Word PDF|
|National adaptation guide for ILO CAPI model LFS - Demographic and background characteristics (v3, 2019)||Word PDF|
|National adaptation guide for ILO CAPI model LFS - Labour Modules (v3, 2019)||Word PDF|
|Changes introduced in ILO CAPI model LFS (v3, 2019)|