| Literature DB >> 29326092 |
Dorthe Boe Danbjørg1,2, Allan Villadsen3, Ester Gill4, Mette Juel Rothmann1,5,6, Jane Clemensen1,7.
Abstract
BACKGROUND: Exercise has proven to reduce pain and increase quality of life among people living with osteoarthritis (OA). However, one major challenge is adherence to exercise once supervision ends.Entities:
Keywords: arthritis; rehabilitation; telemedicine
Year: 2018 PMID: 29326092 PMCID: PMC5785680 DOI: 10.2196/mhealth.7734
Source DB: PubMed Journal: JMIR Mhealth Uhealth ISSN: 2291-5222 Impact factor: 4.773
Characteristics of the participants.
| Participant | Gender | Ethnicity | Employment | Surgery | Daily exercise or activity |
| 1 | Female | Danish | Old age pensioner | No | Exercise on a daily basis |
| 2 | Male | Danish | Old age pensioner | Yes | Daily activity: walking the dog |
| 3 | Female | Danish | Employed | No | Daily activity: biking |
| 4 | Female | Danish | Employed—light duties | No | Daily activity: gardening |
| 5 | Female | Danish | —a | No | — |
| 6 | Male | Danish | Old age pensioner | No | Exercise on a daily basis |
a— indicates missing data.
Figure 1Three processes of data collection.
Figure 2Suggestions for features in the app. The features are: introduction, music, camera, TV, alarm, award, age, personal trainer, and overall assessment.
Figure 4The different features reflecting the participants’ ideas about motivation and reminders.
Process of analysis: examples from the analysis.
| Step 1: superior themes extracted after the first open reading | Step 2: From themes to codes. Identifying meaningful units. The meaningful units are coded based on the superior themes | Step 3: From codes to meaning. The meaningful units are sorted into groups | |
| Quotations | Code | ||
| Competitive | |||
| Prefer being together | |||