Using Smartphones in Multi-Modal Qualitative Research

Presenter(s): Dimitar Karadzhov

The ubiquity of smartphones has enhanced the capacity for collecting rich, multi-modal data in real time and engaging with participants in innovative ways. Smartphone-assisted qualitative research has several advantages, including the ability to capture the immediacy of experiences, gather diverse data formats (e.g., text, audio, video), and overcome geographical limitations. However, this approach also presents unique challenges such as ensuring participant privacy, bridging the digital divide, and managing large volumes of data.

As smartphone capabilities have grown exponentially in recent years, it is natural to feel overwhelmed and uncertain as to how to design an original, feasible and inclusive smartphone app-based study. This short tutorial covers a range of practical, methodological and ethical issues in designing smartphone-assisted qualitative research, with a special focus on multi-modal data collection and hard-to-reach populations.

Multi-Modal Qualitative Research

Multi-modal research involves the collection and integration of different data formats, such as text, images, audio, and video, to gain a more comprehensive understanding of a phenomenon. These could be gathered simultaneously or sequentially. 

The use of multi-modal data in qualitative research has several theoretical and practical advantages. Firstly, it allows researchers to capture the richness and complexity of human experiences, as different data formats can reveal different facets of a phenomenon. For instance, while traditional interviews may yield in-depth accounts, visual data such as photographs or videos — collected via smartphones — can capture the context, changes and emotions associated with those accounts. Secondly, triangulating different data formats can help researchers corroborate findings and ensure a more holistic understanding of the phenomenon under study. Such pragmatic and creative combinations of data collection and analysis techniques have been called multi-modal, multi-method and pluralistic qualitative research.

For example, to explore how asylum-seekers create a sense of community and belonging, one may combine a conversation analysis of group chats, a thematic analysis of images depicting community settings and activities, and geospatial data tracking participants’ mobility patterns.

However, managing and analysing multi-modal data can be challenging, as researchers need to integrate diverse data formats into a coherent analysis. Awareness of the relative strengths and limitations of different data modalities helps tailor study designs accordingly. Trade-offs between affordances and limitations of data modalities are unavoidable. For example, while participant-generated videos provide rich, evocative contextual data, they also increase anonymity and privacy risks, and analytic complexity.

The choice of approach will depend on the research question, the type of data collected, the study population, and the researcher's epistemological stance and experience level, and funding available. For instance:

Are the research questions appropriate for a multi-modal enquiry?;

Do you have a sufficient understanding of participants’ needs, preferences and circumstances?;

Have ethical protocols been adapted to each data modality?;

How will each type of data be stored, coded and integrated into a coherent analysis? Do you possess the necessary analytic skills to achieve this? Will software (e.g. NVivo) be employed to facilitate multi-modal analysis?

Engaging Hard-to-Reach Groups

As research tools, smartphones can often be perceived as more user-friendly, engaging and acceptable by participants. Indeed, mobile methods have been described by participants as ‘fun’, ‘engaging’, ‘interesting’, ‘helpful’, ‘cool’ and ‘enriching’. In contrast, traditional data collection methods such as one-to-one interviews and surveys can be viewed as impersonal, uncomfortable, artificial and unappealing.

Smartphone-assisted qualitative research can be particularly valuable for engaging with hard-to-reach populations, who may face distinct barriers to participation in traditional research such as stigma, lack of time, or limited access to research settings, in addition to differences in literacy levels and economic stability. Examples of marginalised or disenfranchised populations are street-involved youth, destitute individuals, ethnoracial minorities and people with disabilities. Portable and accessible, smartphones can lower some of these barriers and authentically involve, represent and even empower participants.

When designing smartphone-assisted research with hard-to-reach groups, it is crucial to adopt an inclusive and user-centred approach. This involves considering the needs, preferences, and habits of the target population so that the research design is flexible, accessible and meaningful to them. For instance, researchers should consider the participants' level of digital literacy, their access and attitude to technology, their comfort level with different devices and data formats, and the volatility and security of their living environments, among other situational factors. The table details some key design considerations and adaptations.

Table 1.   Research design considerations specific to hard-to-reach and marginalised populations.

Practical Strategies for Rigorous, Ethical and Fundable Research

While researchers need to be adaptable and responsive to participants and their contexts, they also need to ensure that the research design remains methodologically sound and ethically rigorous. Smartphone-assisted designs can present novelty, complexity and ambiguity, which can complicate obtaining ethics clearances and securing research funding.

Researchers should proactively address common ‘pain points’, risks and other core considerations — including:

• Feasibility and efficiency: cost, user-friendliness, piloting, connectivity, functionalities of mobile app or platform;
• Data privacy and management: storage, encryption, GDPR compliance, anonymisation;
• Data collection: protocols and training guides, setting expectations, flexibility, incentive structure, contingency plans;
• Permissions and participant control: data modification and deletion; copyright and ownership;
• Data analysis and representation: participant involvement, authentic representation, impactful dissemination.

> Download worksheet.

> Download supporting document (affordances, limitations, and design examples).

Supporting materials

About the author

Dr Dimitar Karadzhov is a Lecturer in the School of Health & Wellbeing, College of Medical, Veterinary & Life Sciences. He teaches in the Global Mental Health MSc Programme (both on-campus and online distance learning), and has contributed to those programmes since 2016.

Dr Karadzhov's primary research interests include mental health recovery and health inequalities; global mental health; public health; homelessness; child welfare and human rights; qualitative and smartphone-assisted research methodologies; and learning technologies.

Primary author profile page

• Published on: 12 May 2025
• Event hosted by: University of Glasgow
• Keywords: Multi-modal qualitative research | Participatory research | Mobile methods | Visual methods | Digital social research | Mixed methods | Digital Social Research | Mixed Methods | Visual Methods | Online Data Collection | Multimodal Analysis |
• To cite this resource:

  Dimitar Karadzhov. (2025). Using Smartphones in Multi-Modal Qualitative Research. National Centre for Research Methods online learning resource. Available at https://www.ncrm.ac.uk/resources/online/all/?id=20856 [accessed: 15 May 2025]