| Literature DB >> 32442143 |
Helen Slater1, Jennifer N Stinson2,3,4, Joanne E Jordan5, Jason Chua6, Ben Low7, Chitra Lalloo3,4, Quynh Pham4,8, Joseph A Cafazzo4,8,9, Andrew M Briggs1.
Abstract
BACKGROUND: Digital technologies connect young people with health services and resources that support their self-care. The lack of accessible, reliable digital resources tailored to young people with persistent musculoskeletal pain is a significant gap in the health services in Australia. Recognizing the intense resourcing required to develop and implement effective electronic health (eHealth) interventions, the adaptation of extant, proven digital technologies may improve access to pain care with cost and time efficiencies.Entities:
Keywords: adolescent; eHealth; mHealth; mobile phone; musculoskeletal pain; self-management; smartphone
Mesh:
Year: 2020 PMID: 32442143 PMCID: PMC7305555 DOI: 10.2196/18315
Source DB: PubMed Journal: J Med Internet Res ISSN: 1438-8871 Impact factor: 5.428
Figure 1A 3-phased approach to the user testing was adopted, with all participants undertaking user testing of website prototypes (phase 1), pain app user testing (phase 2), and semistructured interviews on their experiences of using these digital technologies (phase 3).
Figure 2Screenshots of the 2 prototype websites: to the left, the round, soft version is shown, and to the right, the geometric version.
Four test tasks were mapped, as per ticks, to reflect specific electronic health evaluation criteria.
| Design and quality criteria | Test tasks | |||
|
| Daniel’s story | Self-checka | Making sense of pain | Further support |
| Navigation | ✓ | N/Ab | N/A | ✓ |
| Usability | N/A | ✓ | N/A | ✓ |
| User engagement | ✓ | ✓ | ✓ | ✓ |
| Content | ✓ | ✓ | ✓ | ✓ |
| Acceptability | ✓ | ✓ | ✓ | ✓ |
aSelf-check refers to validated self-report questionnaires.
bN/A: not applicable.
Demographic and clinical pain characteristics of consenting participants (N=20).
| Demographic/clinical pain characteristics | Consenting and participating (n=15) | Consenting and not participating (n=5) | ||
|
| ||||
| Mean (SD) | 20.5 (3.3) | 22.6 (3.1) | ||
| Range | 15-25 | 18-25 | ||
| Gender (female), n (%) | 12 (80) | 4 (80) | ||
| Urban/rural, n (%) | 13 (86) | 1 (20) | ||
| English as a first language, n (%) | 14 (93) | 5 (100) | ||
|
| ||||
| University | 4 (26) | 1 (20) | ||
| TAFEa | 1 (6) | 2 (40) | ||
| Year 12 (tertiary entrance)b | 6 (40) | 1 (20) | ||
| Year 12 (other) | 2 (13) | 1 (20) | ||
| Less than 3 year secondary | 2 (13) | 0 (0) | ||
|
| ||||
| School | 4 (26) | 0 (0) | ||
| University or TAFE | 8 (53) | 1 (20) | ||
| Unemployed | 0 (0) | 2 (40) | ||
| Employed (volunteer or paid work) | 3 (20) | 2 (40) | ||
|
| ||||
| Diagnosis from health professional (yes), n (%) | 10 (66) | 4 (80) | ||
|
| ||||
| Mean (SD) | 6 (6) | 8 (8) | ||
| Range | 0.3-22 | 2.5-18 | ||
|
| ||||
| Mean (SD) | 47 (14) | 62 (6) | ||
| Range | 27-74 | 52-66 | ||
|
| ||||
| Neck pain | 6 (40) | 3 (60) | ||
| Mid back | 7 (46) | 3 (60) | ||
| Low back | 8 (53) | 4 (80) | ||
| Hips | 5 (33) | 2 (40) | ||
| Knees | 3 (20) | 2 (40) | ||
| Ankles | 4 (26) | 0 (0) | ||
| Shoulders | 4 (26) | 1 (20) | ||
| Elbows | 1 (6) | 1 (20) | ||
| Wrists/hands | 11 (73) | 1 (20) | ||
| All over pain (muscles and joints) | 6 (40) | 2 (40) | ||
| Other paine | 10 (66) | 3 (60) | ||
aTAFE: Technical and Further Education Institutions.
bPathway for university entrance.
cÖMPSQ-SF: Örebro Musculoskeletal Pain Screening Questionnaire-Short Form, possible score 1 to 100.
dTotal count may be greater than the number of participants as more than one area of pain could be nominated.
eAreas of pain nominated in free text included abdominal pain (n=3), coccygeal pain (n=1), migraine (n=3), gastrointestinal issues (n=2), dysmenorrhea (n=1), and nerve pain (n=1).
Individual participant engagement data for the use of the iCanCope with Pain app over 7 days.
| Participant ID | Full check-ins, n | History views, n | Goals set, n | Library articles accessed, n |
| 1 | 4 | 21 | 2 | 4 |
| 2 | 8 | 18 | 4 | 8 |
| 3 | 6 | 3 | 0 | 1 |
| 4 | 13 | 38 | 11 | 6 |
| 5 | 7 | 3 | 4 | 2 |
| 6 | 3 | 4 | 0 | 11 |
| 7 | 17 | 7 | 2 | 11 |
| 8 | 7 | 0 | 2 | 7 |
| 9 | 2 | 0 | 1 | 8 |
| 10 | 6 | 14 | 2 | 0 |
| 11 | 7 | 13 | 5 | 1 |
| 12 | 4 | 0 | 5 | 1 |
| 13 | 8 | 1 | 1 | 1 |
| 14 | 5 | 0 | 1 | 0 |
| 15 | 12 | 36 | 2 | 2 |
Figure 3Individual-level data are shown for participants 1 to 15 (vertical axis). Relative user engagement (horizontal axis, proportional frequencies, and ranges for each domain) is presented across 4 key domains: (1) total (full) check-ins (blue), range 2-17; (2) history views (bright orange), range 0-38; (3) goals set (gray), 0-11; and (4) library articles accessed (light orange), range 0-11. Note that it is the variable relative engagement of each individual with the features of the app.
Figure 4Graphic summary of metathemes and themes derived from qualitative interviews. Metathemes were as follows: user-centered digital design (orange), website design promoting engagement and acceptability (blue), app functionality to support self-care (green), and leveraging uptake of digital tools (yellow).