Citation for published version (APA): Ni Mhurchu, C., te Morenga, L., Tupai-firestone, R., Grey, J., Jiang, Y., Jull, A., Whittaker, R., Dobson, R., Dalhousie, S., Funaki, T., Hughes, E., Henry, A., Lyndon-tonga, L., Pekepo, C., Penetito-hemara, D., Tunks, M., Verbiest, M. E. A., Humphrey, G., Schumacher, J., & Goodwin, D. (2019). A co-designed mHealth programme to support healthy lifestyles in Māori and Pasifika peoples in New Zealand (OL@-OR@): A cluster-randomised controlled trial. The Lancet Digital Health, 1(6), e298-e307. https://doi.org/10.1016/S2589-7500(19)30130-X

© 2019 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license Background: The OL@-OR@ mobile health programme was co-designed with Māori and Pasifika communities in New Zealand, to support healthy lifestyle behaviours. We aimed to determine whether use of the programme improved adherence to health-related guidelines among Māori and Pasifika communities in New Zealand compared with a control group on a waiting list for the programme. Methods: The OL@-OR@ trial was a 12-week, two-arm, cluster-randomised controlled trial. A cluster was defined as any distinct location or setting in New Zealand where people with shared interests or contexts congregated, such as churches, sports clubs, and community groups. Members of a cluster were eligible to participate if they were aged 18 years or older, had regular access to a mobile device or computer, and had regular internet access. Clusters of Māori and of Pasifika (separately) were randomly assigned (1:1) to either the intervention or control condition. The intervention group received the OL@-OR@ mHealth programme (smartphone app and website). The control group received a control version of the app that only collected baseline and outcome data. The primary outcome was self-reported adherence to health-related guidelines, which were measured with a composite health behaviour score (of physical activity, smoking, alcohol intake, and fruit and vegetable intake) at 12 weeks. The secondary outcomes were self-reported adherence to health-related behaviour guidelines at 4 weeks; self-reported bodyweight at 12 weeks; and holistic health and wellbeing status at 12 weeks, in all enrolled individuals in eligible clusters; and user engagement with the app, in individuals allocated to the intervention. Adverse events were not collected. This study is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12617001484336. Findings: Between Jan 24 and Aug 14, 2018, we enrolled 337 Māori participants from 19 clusters and 389 Pasifika participants from 18 clusters (n=726 participants) in the intervention group and 320 Māori participants from 15 clusters and 405 Pasifika participants from 17 clusters (n=725 participants) in the control group. Of these participants, 227 (67%) Māori participants and 347 (89%) Pasifika participants (n=574 participants) in the intervention group and 281 (88%) Māori participants and 369 (91%) Pasifika participants (n=650 participants) in the control group completed the 12-week follow-up and were included in the final analysis. Relative to baseline, adherence to health-related behaviour guidelines increased at 12 weeks in both groups (315 [43%] of 726 participants at baseline to 329 [57%] of 574 participants in the intervention group; 331 [46%] of 725 participants to 369 [57%] of 650 participants in the control group); however, there was no significant difference between intervention and control groups in adherence at 12 weeks (odds ratio [OR] 1·13; 95% CI 0·84–1·52; p=0·42). Furthermore, the proportion of participants adhering to guidelines on physical activity (351 [61%] of 574 intervention group participants vs 407 [63%] of 650 control group participants; OR 1·03, 95% CI 0·73–1·45; p=0·88), smoking (434 [76%] participants vs 501 [77%] participants; 1·12, 0·67–1·87; p=0·66), alcohol consumption (518 [90%] participants vs 596 [92%] participants; 0·73, 0·37–1·44; p=0·36), and fruit and vegetable intake (194 [34%] participants vs 196 [30%] participants; 1·08, 0·79–1·49; p=0·64) did not differ between groups. We found no significant differences between the intervention and control groups in any secondary outcome. 147 (26%) intervention group participants engaged with the OL@-OR@ programme (ie, set at least one behaviour change goal online). Interpretation: The OL@-OR@ mobile health programme did not improve adherence to health-related behaviour guidelines amongst Māori and Pasifika individuals. Funding: Healthier Lives He Oranga Hauora National Science Challenge.

The obesity rate in New Zealand is one of the highest worldwide (31%), with highest rates among Māori (47%) and Pasifika (67%). Codesign was used to develop a culturally tailored, behavior change mHealth intervention for Māori and Pasifika in New Zealand. The purpose of this article is to provide an overview of the codesign methods and processes and describe how these were used to inform and build a theory-driven approach to the selection of behavioral determinants and change techniques. The codesign approach in this study was based on a partnership between Māori and Pasifika partners and an academic research team. This involved working with communities on opportunity identification, elucidation of needs and desires, knowledge generation, envisaging the mHealth tool, and prototype testing. Models of Māori and Pasifika holistic well-being and health promotion were the basis for identifying key content modules and were applied to relevant determinants of behavior change and theoretically based behavior change techniques from the Theoretical Domains Framework and Behavior Change Taxonomy, respectively. Three key content modules were identified: physical activity, family/whānau [extended family], and healthy eating. Other important themes included mental well-being/stress, connecting, motivation/support, and health literacy. Relevant behavioral determinants were selected, and 17 change techniques were mapped to these determinants. Community partners established that a smartphone app was the optimal vehicle for the intervention. Both Māori and Pasifika versions of the app were developed to ensure features and functionalities were culturally tailored and appealing to users. Codesign enabled and empowered users to tailor the intervention to their cultural needs. By using codesign and applying both ethnic-specific and Western theoretical frameworks of health and behavior change, the mHealth intervention is both evidence based and culturally tailored.

© 2018, © The Author(s) 2018. Obesity rates in Aotearoa/New Zealand continue to rise, and there is an urgent need for effective interventions. However, interventions designed for the general population tend to be less effective for Māori communities and may contribute to increased health inequities. We describe the integration of co-design and kaupapa Māori research approaches to design a mobile-phone delivered (mHealth) healthy lifestyle app that supports the health aspirations of Māori communities. The co-design approach empowered our communities to take an active role in the research. They described a holistic vision of health centred on family well-being and maintaining connections to people and place. Our resultant prototype app, OL@-OR@, includes content that would not have been readily envisaged by academic researchers used to adapting international research on behaviour change techniques to develop health interventions. We argue that this research approach should be considered best practice for developing health interventions targeting Māori communities in future.

Most mobile health (mHealth) programmes are designed with minimal input from target end users and are not truly personalised or adaptive to their specific and evolving needs. This review describes the methods and processes used in the co-design of mHealth interventions. Nine relevant studies of varying design were identified following searches of six academic databases. All employed co-design or participatory methods for the development of a health intervention delivered via a mobile device, with three focusing on health behaviour change (one on nutrition) and six on management of a health condition. Overall, six key phases of design and 17 different methods were used. Sufficiency of reporting was poor, and no study undertook a robust assessment of efficacy; these factors should be a focus for future studies. An opportunity exists to use co-design methods to develop acceptable and feasible mHealth interventions, especially to support improved nutrition and for minority and indigenous groups.

Cultural fit is a concept that can be applied to the effectiveness of one’s evaluation practice as well as the interventions that seek to help people. We argue that there is substantial vagueness about being culturally competent, or culturally responsive, or both, and that the concepts these terms are attempting to embody can be viewed better as a continuum of skills, knowledge, attitudes, and positioning. We propose replacing these terms with the concept of cultural fit; that is, the contextual stance or positioning of a practitioner or evaluator as an insider, of the same culture(s) as the service user or evaluand, and having a congruency with the service user or evaluand’s core cultural values. We argue that the cultural fit between organisa tional staff and service user creates grounds for greater effectiveness, and therefore the concept of cultural fit is potentially an important effectiveness criterion for interventions and evaluators. Cultural fit also has relevance both for commissioners of evaluation (in reflect ing on how they might reasonably assess the cultural fit of an evalu ation team, or evaluator, or both), and for evaluators themselves, as a way of measuring their own cultural fit and how this impacts on their effectiveness as an evaluator.