| Literature DB >> 30616579 |
Jennifer Moodley1,2,3, Deborah Constant4, Matthys H Botha5, Frederick H van der Merwe5, Amanda Edwards6, Mariette Momberg4.
Abstract
BACKGROUND: Cancer screening programs hold much potential for reducing the cervical cancer disease burden in developing countries. The aim of this study was to determine the feasibility of mobile health (mHealth) phone technology to improve management and follow-up of clients with cervical cancer precursor lesions.Entities:
Keywords: Cervical cancer; Colposcopy; Loss to follow-up; Pap smear; Prevention; Screening; eHealth; mHealth
Mesh:
Year: 2019 PMID: 30616579 PMCID: PMC6322222 DOI: 10.1186/s12905-018-0702-1
Source DB: PubMed Journal: BMC Womens Health ISSN: 1472-6874 Impact factor: 2.809
Profile of participants who currently owned a mobile phone
| Characteristic | < 30 years ( | ≥ 30 years ( | Total ( | |
|---|---|---|---|---|
| Median age in years (IQR) | 25 (23–28) | 37 (32–42 | 29 (25–36) | |
| Main home language | ||||
| Afrikaans | 13 (7%) | 21 (11.9%) | 34 (9.3%) | 0.272 |
| English | 1 (0.5%) | 3 (1.7%) | 4 (1.1%) | |
| isiXhosa | 165 (88.2%) | 145 (81.9%) | 310 (85.2%) | |
| Other | 8 (4.3%) | 8 (4.5%) | 16 (4.4%) | |
| Languages spoken (after main home language) | ||||
| Afrikaans | 29 (15.5%) | 45 (25.4%) | 74 (20.3%) | 0.019 |
| English | 158 (84.5%) | 132 (74.6%) | 315 (86.5%) | 0.012 |
| isiXhosa | 174 (93.1%) | 150 (84.8%) | 324 (89.0%) | 0.011 |
| Other | 25 (13.4%) | 27 (15.3%) | 52 (14.3%) | 0.607 |
| Highest level of education | 0.007b | |||
| Primary or less | 16 (8.6%) | 35 (19.8%) | 51 (14.0%) | |
| Secondary | 167 (89.3%) | 137 (77.4%) | 304 (83.5%) | |
| Post-secondary | 4 (2.1%) | 5 (2.8%) | 9 (2.5%) | |
| Formal housing | 83 (44.4%) | 81 (45.8%) | 164 (45.1%) | 0.792 |
| Median number of people living in home (IQR) | 4 (3–6) | 4 (3–5) | 4 (3–6) | 0.029c |
| Employed | 52 (27.8%) | 81 (45.8%) | 133 (36.5%) | < 0.001 |
(IQR Interquartile range)
aP-value for Chi-squared test unless otherwise stated
bFishers exact test
cKruskal-Wallis test
Mobile phone ownership and patterns of use
| Characteristic | < age 30 ( | ≥ age 30 ( | Total sample ( | |
|---|---|---|---|---|
| Mobile phone type | ||||
| Basic | 60 (32.1%) | 68 (38.4%) | 128 (35.2%) | 0.001 |
| Smart/Feature | 127 (67.9%) | 98 (55.4%) | 225 (61.81%) | |
| Unknown | 0 (0%) | 11 (6.21%) | 11 (3.0%) | |
| Cash purchase of phone (as opposed to contract) | 177 (94.7%) | 169 (95.5%) | 346 (95.1%) | 0.716 |
| Median time owned mobile phone (IQR) | 12 months (5–24) | 8 months (6–36) | 12 months (5–30) | < 0.001 |
| Ever lost or had mobile phone stolen | 115 (61.5%) | 95 (53.7%) | 210 (57.7%) | 0.031 |
| Someone else has access to phone | 99 (52.9%) | 84 (47.5%) | 183 (50.3%) | 0.296 |
| Owns SIM card | 183 (97.9%) | 174 (98.3%) | 357 (98.1%) | 0.758 |
| Ever uses someone else’s SIM card | 12 (6.4%) | 8 (4.5%) | 20 (5.5%) | 0.427 |
| Ways phone is used | ||||
| Receive SMS | 187 (100%) | 170 (96.1%) | 357 (98.1%) | 0.006b |
| Send SMS | 186 (99.5%) | 165 (93.2%) | 351 (96.4%) | 0.001b |
| Make calls | 187 (100%) | 177 (100%) | 364 (100%) | – |
| Receive calls | 187 (100%) | 175 (98.9%) | 362 (99.5%) | 0.236b |
| Send money | 13 (7%) | 14 (7.9%) | 27 (7.4%) | 0.727 |
| Receive money | 15 (8%) | 16 (9%) | 31 (8.5%) | 0.728 |
| 103 (55.1%) | 67 (37.9%) | 170 (46.7%) | 0.001 | |
| Mxit | 35 (18.7%) | 21 (11.9%) | 56 (15.4%) | 0.070 |
| Browse internet | 84 (44.9%) | 51 (28.8%) | 135 (37.1%) | 0.001 |
| Send/receive emails | 36 (19.3%) | 21 (11.9%) | 57 (15.7%) | 0.053 |
aP-value for Chi-squared test unless otherwise stated
bFishers exact test
Factors associated with interest in receiving Pap smear results via SMS
| Variable | Adjusted OR (95% CI)a | |
|---|---|---|
| Uses text | 4.34 (0.54–34.94) | 0.168 |
| Completed high school | 2.15 (1.16–3.98) | 0.015 |
| Previous pap smear | 1.78 (1.04–3.07) | 0.037 |
| Phone not private | 0.31 (0.18–0.51) | < 0.001 |
| HIV positive | 0.65 (0.34–1.25) | 0.196 |
aAdjusted by all the variables reported in the table
Factors associated with receiving appointment reminders via SMS
| Variable | Adjusted OR (95% CI)a | |
|---|---|---|
| Uses text | 14.19 (1.72–117.13) | 0.014 |
| HIV positive | 0.33 (0.15–0.75) | 0.008 |
| Afrikaans speaking | 3.01 (1.23–7.37) | 0.016 |
| Phone not private | 0.83 (0.49–1.41) | 0.495 |
| Complete high school | 1.26 (0.70–2.27) | 0.435 |
| Previous Pap smear | 0.80 (0.44–1.45) | 0.455 |
aAdjusted by all variables reported in the table