Understanding the "black box" of a health-promotion program : keys to enable health among older persons aging in the context of migration

Although the need to make health services more accessible to persons who have migrated has been identified, knowledge about health-promotion programs (HPPs) from the perspective of older persons born abroad is lacking. This study explores the design experiences and content implemented in an adapted version of a group-based HPP developed in a researcher-community partnership. Fourteen persons aged 70-83 years or older who had migrated to Sweden from Finland or the Balkan Peninsula were included. A grounded theory approach guided the data collection and analysis. The findings showed how participants and personnel jointly helped raise awareness. The participants experienced three key processes that could open doors to awareness: enabling community, providing opportunities to understand and be understood, and confirming human values and abilities. Depending on how the HPP content and design are being shaped by the group, the key processes could both inhibit or encourage opening doors to awareness. Therefore, this study provides key insights into how to enable health by deepening the understanding of how the exchange of health-promoting messages is experienced to be facilitated or hindered. This study adds to the scientific knowledge base of how the design and content of HPP may support and recognize the capabilities of persons aging in the context of migration.

Spatial modeling of data with excessive zeros applied to reindeer pellet-group counts

We analyze a real data set pertaining to reindeer fecal pellet-group counts obtained from a survey conducted in a forest area in northern Sweden. In the data set, over 70% of counts are zeros, and there is high spatial correlation. We use conditionally autoregressive random effects for modeling of spatial correlation in a Poisson generalized linear mixed model (GLMM), quasi-Poisson hierarchical generalized linear model (HGLM), zero-inflated Poisson (ZIP), and hurdle models. The quasi-Poisson HGLM allows for both under- and overdispersion with excessive zeros, while the ZIP and hurdle models allow only for overdispersion. In analyzing the real data set, we see that the quasi-Poisson HGLMs can perform better than the other commonly used models, for example, ordinary Poisson HGLMs, spatial ZIP, and spatial hurdle models, and that the underdispersed Poisson HGLMs with spatial correlation fit the reindeer data best. We develop R codes for fitting these models using a unified algorithm for the HGLMs. Spatial count response with an extremely high proportion of zeros, and underdispersion can be successfully modeled using the quasi-Poisson HGLM with spatial random effects.