Research on mental health recovery points to an interdependent relationship between experiences of meaning and experiences of recovery; meaning in everyday life promotes recovery, and recovery promotes meaning in everyday life. In this study we address the following question: What do people with mental challenges find meaningful in their everyday life? To explore this question, we offered disposable cameras to people with mental health challenges and asked them to photograph whatever makes their life meaningful. As part of the collaborative procedure of the study, a competence group contributed to different stages of the research process and the visual data were analyzed by the participants themselves in a participant-driven thematic analysis. Through the analysis the participants constructed seven topics addressing the research question: (1) plants and trees, (2) poems and texts, (3) art, (4) music, (5) going for a walk, (6) esthetics, and (7) public movement. An important methodological implication of the study is how photovoice can be a useful way of generating knowledge from the first-person perspective. The participants’ findings may be interpreted as “small things” that are easily overlooked. When the competence group viewed the participants’ photos, they talked about photos they expected to see but found to be missing. Therefore, we offer a discussion related to the photovoice methodology and suggest the importance of considering absent but expected photographs in such a study.


meaningfulness, everyday life, photovoice, thematic analysis, recovery, mental health, supported housing

Author Bio(s)

Siw Tønnessen is a Ph.D. candidate at University of South-Eastern Norway. Please direct correspondence to siw.h.tonnessen@usn.no.

Ottar Ness is a Professor at Norwegian University of Science and Technology. Please direct correspondence to ottar.ness@ntnu.no.

Trude Klevan is an Assistant professor at University of South-Eastern Norway. Please direct correspondence to trude.goril.klevan@usn.no.


The authors would like to thank the residents participating in the data generation and data analysis, and the participants in the competence group.

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