The mixed mode (MM), i.e. the use of different collection techniques in the same survey, is a relatively new approach that ISTAT, as well as other NSIs, is adopting especially for social surveys. Its use is spreading both to contrast declining response rates and to reduce the total cost of surveys. Using different data collection techniques, in fact, helps in contacting different types of respondents in the most suitable way for each of them, allowing a gain in population coverage and response rate. However, it introduces a bias, named mode effect, that must be faced at different levels: in the design phase by defining the best collection instruments to contain the measurement error; in the estimation phase by assessing and treating the bias effects due to the use of MM, in order to ensure the accuracy of the estimates. The surveys based on MM must be designed, in fact, considering the accuracy of the produced estimates, that must be consistent and comparable with the analogue ones obtained in the previous survey editions, for ensuring that changes in the time series are exclusively due to real changes of the observed phenomenon. The focus of this work is the experience in the evaluation and treatment of MM effect in the experimental situation of ISTAT survey “Aspects of daily life - 2017”, a sequential web/PAPI survey for which an independent control single mode (SM) sample PAPI was planned to make an assessment of the introduction of the mixed mode. The aim of the analyses presented in this work is to evaluate first the impact on the survey estimates of the introduction of MM design, with respect to the previous single mode design, and subsequently to analyse in depth the reasons that determine significant differences in the estimates obtained with the two samples. The study is developed on several levels of analysis: the first level makes the comparison between SM and MM samples; the second level assesses the mode effect (selection and measurement) in the MM sample.