five

Demographic data for each ideal type trajectory.

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NIAID Data Ecosystem2026-05-02 收录
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https://figshare.com/articles/dataset/Demographic_data_for_each_ideal_type_trajectory_/25944732
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Objective Studies on resilience in advanced cancer caregiving typically focus on the interplay between resilience-promoting resources and coping strategies that may be associated with resilience. However, no studies have investigated the emergence of trajectories of resilience and distress in individuals confronted with a cancer diagnosis of a loved one. Methods Ideal-type analysis, a method for constructing typologies from qualitative data, was used to identify trajectories involving resilience or the lack thereof based on fifty-four interviews conducted with seventeen partners of patients recently diagnosed with advanced cancer over a period of three years. Findings Six trajectories could be distinguished, three of which involved resilience (rapidly adapting resilience, gradually adapting resilience, and slowly adapting resilience), while the other three trajectories (continuing distress, delayed distress, and frozen disconnection) reflected a less optimal adjustment. These different trajectories seemed to be rooted in the individual characteristics of partners, the behavior of a support network, and interactions between the two. Conclusion The differentiation between these trajectories in partners of patients diagnosed with cancer not only furthers research on resilience in the face of adversity, but also promises to assist healthcare professionals in optimizing support for this often-neglected group of partners of patients diagnosed with cancer.
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2024-05-31
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