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Handling missing data through prevention strategies in self-administered questionnaires: a discussion paper
Li-Anne Audet1, Michèle Desmarais1, Émilie Gosselin2
1Ingram School of Nursing, McGill University, Montreal, Quebec, Canada.
Background:
Self-administered questionnaires are efficient and low-cost ways of collecting data with wide cohorts. Nonetheless, their use in studies can result in a high occurrence of missing data, which can affect the statistical power, representativeness and generalisability of the findings. Imputation methods have been considered efficient statistical techniques for managing missing data. However, they have also been associated with limits, such as the risk of under-estimation of the effect, lower statistical power and decrease of correlation among variables. Recent studies have highlighted the importance of using prevention strategies to avoid missing data before the data are analysed.
Aim:
To identify strategies for preventing the occurrence of missing data and to discuss their effects, as well as their methodological and statistical considerations.
Discussion:
The article discusses prevention strategies related to the administration format and follow-up and reminders. Strategies such as the use of electronic tablets, email and telephone reminders are associated with lower rates of missing data in self-administered questionnaires. However, methodological and statistical limits, including the absence of a comparison group and statistical validation of the reported results, limits the capacity to establish robust consensus.
Conclusion:
Prevention strategies represent relevant and feasible avenues for handling missing data in a wide range of clinical, nursing and epidemiological research. More projects based on robust design are needed to ensure accurate and reliable data are collected from patients, families, communities and clinicians.
Implications For Practice:
It is important for clinicians and nurses to understand the phenomenon of missing data and the strategies available to prevent missing data, to collect data representing the patients' and families' perspectives and experiences.
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