The <i>StoryListening</i> Project: Feasibility and Acceptability of a Remotely Delivered Intervention to Alleviate Grief during the COVID-19 Pandemic

Reblin, Maija; Wong, April S. Y.; Arnoldy, Francesca; Pratt, Susanna; Dewoolkar, Advik Mandar; Gramling, Robert; Rizzo, Donna M.

doi:10.1089/jpm.2022.0261

Cited by 4 publications

(3 citation statements)

References 32 publications

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“…Description of the participant samples and their experience of the intervention are available elsewhere. 13 …”

Section: Methodsmentioning

confidence: 99%

“…The purpose of this report is to describe the protocol for a brief doula storytelling intervention that we found to be feasible and acceptable 13 for reducing the existential loneliness of grief among families, friends, and clinicians who experienced the death of a person during the time of COVID-19.…”

Section: Introductionmentioning

confidence: 99%

“…As recently reported, participants found the intervention to be highly acceptable and impactful. 13 Given the rapid growth, 20 acceptability, 21 , 22 and attention to quality 23 of telehealth services, offering the StoryListening intervention over televideo may increase access for some isolated persons with transportation, in home caregiving or other barriers to a face-to-face encounter. At the same time, we suggest that a hybrid approach—telehealth and in-person options—may best serve our public health by honoring personal preferences 20 and minimizing disparities in access to televideo healing services.…”

Section: Introductionmentioning

confidence: 99%

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Protocol for a Scalable StoryListening Intervention for Grief-Related Loneliness During COVID-19

Arnoldy

Garrido

Wong

et al. 2023

Palliative Medicine Reports

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Background: Social distancing during the COVID-19 pandemic limited how family, friends, and clinicians physically interacted with people who were dying and decreased communal opportunities for processing grief. These barriers can cause or exacerbate suffering due to loneliness while grieving. Purpose: In this article, we describe the protocol for a brief storytelling intervention designed to reduce loneliness among families, friends, and clinicians grieving the death of a person during the time of COVID-19. Methods: We trained four StoryListening doulas (SLDs) to hold a welcoming space and listen to stories with curiosity and openness. The intervention included a video StoryListening session and two brief questionnaires, filled out before and two weeks after the encounter, assessing loneliness and quality of life. During sessions, SLDs invited participants to share their story of loss in their own words and in as much detail as preferred. When participants felt a sense of story completion, SLDs shared validating statements and expressed gratitude to the participant for sharing. The video and audio for each participant's StoryListening encounter were recorded and the participant was offered an audio copy of their session.

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“…Description of the participant samples and their experience of the intervention are available elsewhere. 13 …”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Protocol for a Scalable StoryListening Intervention for Grief-Related Loneliness During COVID-19

Arnoldy

Garrido

Wong

et al. 2023

Palliative Medicine Reports

Self Cite

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Somtimes: self organizing maps for time series clustering and its application to serious illness conversations

Javed,

Rizzo,

Lee

et al. 2023

Data Min Knowl Disc

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There is demand for scalable algorithms capable of clustering and analyzing large time series data. The Kohonen self-organizing map (SOM) is an unsupervised artificial neural network for clustering, visualizing, and reducing the dimensionality of complex data. Like all clustering methods, it requires a measure of similarity between input data (in this work time series). Dynamic time warping (DTW) is one such measure, and a top performer that accommodates distortions when aligning time series. Despite its popularity in clustering, DTW is limited in practice because the runtime complexity is quadratic with the length of the time series. To address this, we present a new a self-organizing map for clustering TIME Series, called SOMTimeS, which uses DTW as the distance measure. The method has similar accuracy compared with other DTW-based clustering algorithms, yet scales better and runs faster. The computational performance stems from the pruning of unnecessary DTW computations during the SOM’s training phase. For comparison, we implement a similar pruning strategy for K-means, and call the latter K-TimeS. SOMTimeS and K-TimeS pruned 43% and 50% of the total DTW computations, respectively. Pruning effectiveness, accuracy, execution time and scalability are evaluated using 112 benchmark time series datasets from the UC Riverside classification archive, and show that for similar accuracy, a 1.8$$\times$$ × speed-up on average for SOMTimeS and K-TimeS, respectively with that rates vary between 1$$\times$$ × and 18$$\times$$ × depending on the dataset. We also apply SOMTimeS to a healthcare study of patient-clinician serious illness conversations to demonstrate the algorithm’s utility with complex, temporally sequenced natural language.

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Connecting Families to Bereavement Resources: A Hospital-Based, Bereavement Follow-Up Pilot During First-Wave COVID-19

Cullen,

Bailes,

Shropshire

et al. 2024

Journal of Palliative Medicine

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The StoryListening Project: Feasibility and Acceptability of a Remotely Delivered Intervention to Alleviate Grief during the COVID-19 Pandemic

Cited by 4 publications

References 32 publications

Protocol for a Scalable StoryListening Intervention for Grief-Related Loneliness During COVID-19

Protocol for a Scalable StoryListening Intervention for Grief-Related Loneliness During COVID-19

Somtimes: self organizing maps for time series clustering and its application to serious illness conversations

Connecting Families to Bereavement Resources: A Hospital-Based, Bereavement Follow-Up Pilot During First-Wave COVID-19

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