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Record W4400594183 · doi:10.3389/fresc.2024.1359371

First Step to empowering change: enhancing self-efficacy, energy management, and physical activity in patients with sleep apnea

2024· article· en· W4400594183 on OpenAlexaboutno aff
Gitte Johannesen, Anders Ravnholt Schüsler Damlund, Sofie Grundtvig Vinter, Helle Skadborg Spuur, Mathias Sarkez-Knudsen, Thora Grothe Thomsen

Bibliographic record

VenueFrontiers in Rehabilitation Sciences · 2024
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsnot available
FundersInterregSjællands Universitetshospital
KeywordsPhysical therapyPsychological interventionRehabilitationActivity trackerQuality of life (healthcare)Obstructive sleep apneaTest (biology)Sleep apneaPsychologyIntervention (counseling)MedicineQualitative propertyPhysical medicine and rehabilitationPhysical activityNursingComputer science

Abstract

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Introduction: Fatigue often leads to a sedentary lifestyle, negatively impacting health, mortality, and quality of life. Engaging in physical activity can be challenging for individuals experiencing fatigue, particularly those with sleep apnea. This study's objective was to assess the "First Step" concepts' usability in constructing and implementing different interventions through qualitative data. The intervention targets patients with sleep apnea, focusing on individualized energy distribution and meaningful engagement in physical activity. Methods: Two programs were developed based on the First Step concept, a rehabilitation program and a patient education program. Initially, 13 patients were recruited, split between the groups, with two dropping out. Primarily evaluated through qualitative data, patients in both groups attended group interviews. For one of the programs supplementary quantitative data were collected through the 6-min walk test (6MWT), Sit-to-Stand test, and Canadian Occupational Performance Measure (COPM). Patients in the rehabilitation program also monitored daily step counts using activity trackers. Results: Patients found the energy management education enlightening, enabling them to make conscious changes in their daily lives. They reported the program's positive reception, with social interaction playing a crucial role in its success. Of the six patients who completed the rehabilitation program, significant improvements in 6MWT scores were observed, indicating enhanced walking endurance. While no changes were seen in the Sit-to-Stand test, COPM results showed notable improvements in performance and satisfaction with chosen activities. Discussion: The incorporation of the First Step concept empowered patients with sleep apnea to manage fatigue, conserve energy, engage in meaningful activities, and improve their wellbeing. Merging occupational therapy and physiotherapy interventions effectively addressed daily challenges while promoting physical activity. Adaptations to the program, guided by patient feedback, suggest a preference for longer, more personalized sessions. This approach offers a promising pathway to improving quality of life for individuals with chronic conditions. Conclusion: Our study highlights the usability of the First Step concept, integrating occupational therapy and physiotherapy, to address challenges in individuals with sleep apnea. The tailored, multidisciplinary intervention prioritizes meaningful activities, focuses on energy distribution and physical exercise, yielding improved satisfaction and performance. Further research is warranted to enhance this salutogenic approach for chronic conditions.

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)0.004
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 score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.036
GPT teacher head0.411
Teacher spread0.374 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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