Abstract

BackgroundMindfulness-Based Stress Reduction (MBSR) often improves health outcomes, though literature primarily focuses on middle-class, employed individuals. With an estimated average of six million unemployed over the past year, and the recent uptick in unemployment due to the COVID-19 pandemic, it is important to identify methods to mitigate and reduce the negative health outcomes often associated with under- and unemployment.ObjectivesWe aimed to 1) outline the process of partnering with a community organization to implement a modified MBSR program for under- and unemployed individuals, and 2) present pilot data on preliminary results.MethodsThe modified MBSR program was implemented in two phases within a job training program for under- and unemployed individuals. In Phase I, group one received an eight-week program. Based on feedback, the MBSR program was reduced to six weeks and implemented for groups two and three (Phase II). Feasibility and acceptability were evaluated utilizing a mixed-methods approach. Changes in mindfulness, perceived stress, pain interference, anxiety, depression, and sleep disturbance were assessed pre-post the modified MBSR program.ResultsThirty-three participants completed the program with twenty-nine post-survey responses. The modified MBSR program was feasible and acceptable as evidenced by the enrollment rate (96%), retention rate (72%), and qualitative feedback. Fifty-percent of participants self-reported weekly home practice compliance. Perceived stress and mindfulness demonstrated significant moderate improvements (d = .69, p = .005; d = .46, p = .001). Depression, anxiety, and pain interference results suggested small non-significant effect size improvements (d = .27, p = .19; d = .23, p = .31; d = .25, p = .07). Effects on fatigue and sleep disturbance were negligible.ConclusionThe modified MBSR program was feasible and acceptable to the organization and participants. Small to moderate improvements in mental health and pain interference outcomes were observed. Research using larger sample sizes and randomized designs is warranted.

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