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Record W2922398957 · doi:10.2196/10921

A Mobile-Based Mindfulness and Social Support Program for Adolescents and Young Adults With Sarcoma: Development and Pilot Testing

2019· article· en· W2922398957 on OpenAlexvenueno aff
Elizabeth Donovan, Sarah R. Martin, Laura C. Seidman, Lonnie K. Zeltzer, Tara M. Cousineau, Laura A. Payne, Meredith Trant, Marjorie Weiman, Marla Knoll, Noah Federman

Bibliographic record

VenueJMIR mhealth and uhealth · 2019
Typearticle
Languageen
FieldMedicine
TopicChildhood Cancer Survivors' Quality of Life
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Cancer InstituteNational Heart, Lung, and Blood Institute
KeywordsPsychosocialMedicineCancerIntervention (counseling)MindfulnessYoung adultGerontologySocial supportClinical psychologyPsychologyPsychiatryPsychotherapist

Abstract

fetched live from OpenAlex

BACKGROUND: Approximately 70,000 adolescents and young adults (AYA) are diagnosed with cancer each year in the United States. Sarcomas carry a particularly high symptom burden and are some of the most common cancers among AYA. Recent work has documented significant levels of unmet needs among AYA with cancer, particularly the need for psychosocial support. Mobile technology may be a cost-effective and efficient way to deliver a psychosocial intervention to AYA with cancer and cancer survivors. OBJECTIVE: The two aims of this study were to (1) develop a pilot version of a mobile-based mindfulness and social support program and (2) evaluate program usage and acceptability. An exploratory aim was to examine change in psychosocial outcomes. METHODS: Thirty-seven AYA with sarcoma or sarcoma survivors, parents, and health care providers participated in the study. Semistructured interviews were conducted with 10 AYA, parents of five of the adolescents, and six health care providers. Themes from the interviews helped to inform the development of a mobile-based mindfulness pilot program and a companion Facebook-based social support group. Twenty AYA consented to participate in a single-arm pre-post evaluation of the program; 17 downloaded the app and joined the Facebook group. Seven of these participants had participated in the semistructured interviews. Six additional health care providers consented to participate in the evaluation stage. RESULTS: On average, participants completed 16.9 of the 28 unique sessions and used the mindfulness app for a mean 10.2 (SD 8.2) days during the 28-day evaluation period. The majority of participants (16/17) engaged in the social group and posted at least one reply to the moderator's prompts. The mean number of responses per person to the moderator of the social group was 15.2 of 31 (49%, range 0%-97%). Both AYA and health care providers responded positively to the Mindfulness for Resilience in Illness program and offered useful recommendations for improvements. Exploratory psychosocial analyses indicated there were no significant differences from pretest to posttest on measures of perceived social support, mindfulness, body image, or psychological functioning. CONCLUSIONS: This study offers preliminary support for the feasibility and acceptability of a mobile-based mindfulness and Facebook-based social support program for AYA with sarcoma. The feedback from AYA and health care providers will assist in creating a fully developed intervention. TRIAL REGISTRATION: ClinicalTrials.gov NCT03130751; https://clinicaltrials.gov/ct2/show/NCT03130751.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.051
GPT teacher head0.363
Teacher spread0.312 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations41
Published2019
Admission routes1
Has abstractyes

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