Skip to content

Methodological innovations in data collection in longitudinal studies


The outputs from this project are now available on the CLOSER website.

Use of mixed modes for data collection in longitudinal surveys:

Use of new technologies and novel methods to capture health data in longitudinal studies:

Use of new technologies to measure socio-economic and environmental concepts in longitudinal studies:


Across the world longitudinal studies are facing falling response rates, at the same time cost imperatives are bringing into question the feasibility of large scale regular face-to-face data collection. While, the rapid development of communications technology and associated cultural changes is assumed to mean that study participants will increasingly expect to be able to answer surveys when and how it suits them. All of these factors are driving longitudinal studies to combine different modes of data collection both to increase response and to reduce costs. Mixing modes of data collection either across individuals at one point in time or within individuals over time, presents longitudinal researchers with a range of methodological challenges in both data collection and analysis. Within CLOSER (Cohort & Longitudinal Studies Enhancement Resources), and beyond, studies are investigating different aspects of the implications of mixed mode data collection, and giving data users varying degrees of support and advice about issues that should be of concern.

At the same time, new technologies are increasingly being used in market research and more recently social research to improve the breadth, quality and ease of different kinds of data collection. New technologies that can be used by researchers to collect data include: smartphones, gamification of surveys, gadgets related to the ‘quantified self’ movement and internet of things. Researchers can also link to external technologies to draw in new kinds of data such as linking to social media, storecards and barcoding. Finally, new technologies mean the way samples and data are processed can reduce the complexity of data collection, for example, using hair samples to obtain measures of cortisol or dried blot spots for metabolomics.

Taken together, new technologies mean new kinds of data can be drawn into studies to measure key variables more accurately, or perhaps in a less burdensome way, or to respond to new and emerging research needs. In the future, the most effective way of collecting data will require a more flexible and heterogeneous approach with different topics requiring different modes and frequencies to achieve the most accurate and consistent data. But these exciting opportunities also present significant challenges for both data collection and analytical methods. For example, the passive measurement of health and other behaviours enabled by new digital technologies offers the possibility of capturing data less susceptible to the biases usually associated with measurement but creates new sources of bias in terms of who might participate and how well they engage. In addition, the intensive measures of behaviours these technologies can provide (frequent sampling over extended periods, ambulatory measurement in the wild, sensors closely coupled to individuals) bring the promise of far richer phenotyping of studies, but very different kinds of data to those traditionally collected in surveys. Advances like these mean that new technologies will change the nature of the data that can be measured in longitudinal studies, and our reviews and workshops will demonstrate how this can be achieved and some of the key issues that need to be addressed to do so.

More specifically, this project aims to map out the ways in which longitudinal studies are engaging with new modes and technologies and why. What methodological research has been done to support such innovation, how this is being shared with data users, what guidance is being, or should be developed to support data users?


This project will consist of three separate but linked foci:

  • the use of mixed mode data collection in longitudinal surveys
  • how new technologies can be used for measuring (non health) topics
  • how new technologies can be used for measuring health and health behaviours

In each of the above three areas we plan to:

  • investigate what other longitudinal studies are doing through literature reviews and contacting study Principal Investigators within CLOSER and internationally;
  • hold a workshop to share current research on these methodological challenges, including inviting researchers from non-CLOSER studies and world leading methodological experts to share learning and identify challenges for the future.
  • produce a CLOSER resource document bringing together the literature review, and workshop discussion and agenda for future research.

Project plan

We would be seeking to identify:

  • Which modes/technologies are different longitudinal studies using to collect data?
  • What research (if any) are they doing to test the methods they use and to develop best practice?
  • What research (if any) are they doing to analyse the quality of data collected using these modes/technologies? What are the results of this research?
  • What guidance (if any) are they giving data users on how to analyse the data collected with these modes/technologies? What research (if any) is this guidance based on?
  • What are the key remaining questions about the use of mixed modes/new technologies for their study? (i.e. main uncertainties)?
  • What do they see as research needs to develop best practice for data collection?
  • What are the research needs to develop guidance on analysis methods for users?

Key outputs

There will be three key outputs from this project for each topic: resource documents in relation to each methodological challenge outlining current understanding and what different longitudinal studies are doing; a workshop on each topic held mainly for the CLOSER studies but key researchers from studies drawn in where they have relevant expertise; a research agenda for each topic identifying priority areas for further research.

Team members

Professor Michaela Benzeval

Director, Understanding Society - ISER - University of Essex

Professor Annette Jäckle

Professor of Survey Methodology - ISER - University of Essex

Professor Kate Tilling

Professor of Medical Statistics - University of Bristol

Dr Andy Skinner

Senior Research Associate, School of Experimental Psychology - University of Bristol

Dr Alessandra Gaia

Research Officer - ISER - University of Essex

 dsc5622photocredit anthonycullen%28c%29 ipad