| Literature DB >> 34042592 |
Andrea H Rossman1, Hadley W Reid2, Michelle M Pieters3, Cecelia Mizelle3, Megan von Isenburg4, Nimmi Ramanujam1,3, Megan J Huchko3,5, Lavanya Vasudevan3,6.
Abstract
BACKGROUND: Nearly 90% of deaths due to cervical cancer occur in low- and middle-income countries (LMICs). In recent years, many digital health strategies have been implemented in LMICs to ameliorate patient-, provider-, and health system-level challenges in cervical cancer control. However, there are limited efforts to systematically review the effectiveness and current landscape of digital health strategies for cervical cancer control in LMICs.Entities:
Keywords: cell phones; cervical cancer; colposcopy; developing countries; digital health; low- and middle-income countries; mobile phones; telemedicine or mobile apps; uterine cervical neoplasms
Year: 2021 PMID: 34042592 PMCID: PMC8193495 DOI: 10.2196/23350
Source DB: PubMed Journal: J Med Internet Res ISSN: 1438-8871 Impact factor: 5.428
Figure 1PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flowchart of systematic search results. LMIC: low- and middle-income country; mHealth: mobile health.
Risk of bias assessment for included studies using the Effective Public Health Practice Project’s quality assessment tool for quantitative studiesa.
| Study | Selection bias | Study design | Confounders | Blinding | Data collection method | Withdrawals and dropouts | Global rating |
| Asgary et al (2016) [ | 1 | 3 | 3 | 2 | 1 | 1 | 3 |
| Bhatt et al (2018) [ | 3 | 3 | 3 | 3 | 3 | 3 | 3 |
| Caster et al (2015) [ | 1 | 2 | 3 | 2 | 2 | 1 | 2 |
| Catarino et al (2015) [ | 2 | 3 | 3 | 2 | 1 | N/Ab,c | 3 |
| Devi et al (2018) [ | 3 | 3 | 3 | 3 | 2 | 3 | 3 |
| Erwin et al (2019) [ | 1 | 1 | 2 | 2 | 2 | 1 | 1 |
| Gallay et al (2017) [ | 2 | 3 | 1 | 2 | 3 | 1 | 3 |
| Huchko et al (2019) [ | 1 | 3 | 2 | 3 | 2 | 2 | 3 |
| Khademolhosseini et al (2017) [ | 2 | 1 | 1 | 3 | 1 | 1 | 2 |
| Lima et al (2017) [ | 2 | 1 | 1 | 1 | 3 | 3 | 3 |
| Linde et al (2020) [ | 1 | 1 | 1 | 2 | 3 | 1 | 2 |
| Littman-Quinn et al (2013) [ | 2 | 3 | 3 | 3 | 3 | 3 | 3 |
| Ndlovu et al (2014) [ | 2 | 3 | 3 | 3 | 1 | 3 | 3 |
| Parham et al (2010) [ | 2 | 3 | 3 | 3 | 3 | 3 | 3 |
| Peterson et al (2016) [ | 1 | 3 | 1 | 3 | 3 | N/A | 3 |
| Quercia et al (2018) [ | 2 | 3 | N/A | 3 | 1 | 1 | 3 |
| Quinley et al (2011) [ | 1 | 3 | 3 | 2 | 1 | N/A | 3 |
| Rashid et al (2013) [ | 1 | 1 | 3 | 2 | 3 | N/A | 3 |
| Ricard-Gauthier et al (2015) [ | 2 | 3 | 3 | 2 | 1 | 2 | 3 |
| Romli et al (2020) [ | 1 | 1 | 1 | 2 | 1 | 1 | 1 |
| Sharma et al (2018) [ | 2 | 3 | N/A | 3 | 2 | 2 | 3 |
| Swanson et al (2018) [ | 1 | 2 | 1 | 3 | 3 | 3 | 3 |
| Taghavi et al (2018) [ | 1 | 3 | N/A | 2 | 1 | 1 | 2 |
| Tran et al (2018) [ | 2 | 3 | 3 | 2 | 3 | 3 | 3 |
| Urner et al (2017) [ | 2 | 3 | 1 | 2 | 2 | 3 | 3 |
| Yeates et al (2016) [ | 2 | 3 | 3 | 3 | 3 | 3 | 3 |
| Yeates et al (2020) [ | 2 | 3 | 3 | 2 | 3 | 2 | 3 |
aScores of 1, 2, and 3 indicate low, moderate, and high risks of bias, respectively. The risk of bias was assessed cumulatively for studies with multiple sources, for example, Asgary et al [30,31].
bN/A: not applicable.
cCriteria were not applicable based on a skip pattern in the Effective Public Health Practice Project tool.
Outcomes of randomized controlled trial studies included in the review of primary objectives.
| Study and participants | Outcome | Result | Summary of risk of biasa | ||||
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281 controls 272 SMS messaging 298 SMS messaging+e-voucher | Cervical cancer screening attendance within 60 days of randomization (combined for women from rural and urban settings) |
Women in the SMS messaging group had 3.0 higher adjusted odds of attendance as compared with women in the control group Women in the SMS messaging+e-voucher group had 4.7 higher adjusted odds of attendance as compared with women in the control group Women in the SMS messaging+e-voucher group had 1.5 times higher adjusted odds of attendance compared with women in the SMS messaging group | The overall risk of bias was assessed to be low | |||
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47 control 48 intervention | Mean difference in pre- and posttraining knowledge among women in the intervention group as compared with those in the control group measured immediately and 3 months after SMS messaging–based training |
Women in the intervention group had a mean increase in the knowledge of 8.18 points from baseline as compared with a mean increase of 0.27 points from baseline in the control group immediately posttraining Women in the intervention group had a mean increase in the knowledge of 8.35 points from baseline as compared with a mean increase of 0.17 points in the control group at 3 months of posttraining | The overall risk of bias was assessed to be moderate | |||
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47 control 48 intervention | Uptake of Pap test within 3 months of training in the intervention group compared with control group |
At 3 months of posttraining, only 4 (5.8%) participants of the control group as compared with 23 (47.9%) participants of the intervention group had received a Pap test | The overall risk of bias was assessed to be moderate | |||
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347 standard of care (control) 358 standard of care+text message | The attendance rate of follow-up cervical cancer screening among HPVb-positive women |
Compared with standard of care, a written appointment card, the addition of one-way text messages had no effect on follow-up cervical cancer screening among HPV-positive women | The overall risk of bias was assessed to be moderate | |||
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250 letters 250 registered letters 250 SMS messaging 250 phone calls | The uptake of Pap test in response to recall through phone call as compared with recall by letter |
Compared with women receiving recall by letter, those receiving recall by phone call had 2.38 times higher odds of receiving a Pap smear | The overall risk of bias was assessed to be high | |||
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250 letters 250 registered letters 250 SMS messaging 250 phone calls | The uptake of Pap test in response to recall through SMS messaging as compared with recall by letter |
Compared with women receiving recall by letter, those receiving recall by SMS messaging had no significant change in the odds of receiving a Pap smear | The overall risk of bias was assessed to be high | |||
aAssessed using the Effective Public Health Practice Project risk of bias assessment tool for quantitative studies.
bHPV: human papillomavirus.
Landscape of digital health strategies for cervical cancer prevention and control.
| Individual-, provider- and health system–level challenges in cervical cancer control | Stages in cervical cancer prevention and control | ||||||||||
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| Primary prevention | Secondary prevention | Treatment and palliative care | ||||||||
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| HPVa vaccination | Screening (study) | Treatment of precancerous lesions (study) | Treatment | Palliative care | ||||||
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| Low knowledge of HPV or cervical cancer | Not within the scope of this review | 5 [ | 1 [ | 0 | 0 | |||||
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| Low knowledge of cervical cancer screening or treatment services | Not within the scope of this review | 6 [ | 1 [ | 0 | 0 | |||||
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| Low access to health facilities or cervical cancer services | Not within the scope of this review | 1 [ | 0 | 0 | 0 | |||||
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| Low availability of appropriate and accurate screening or treatment methods | Not within the scope of this review | 15 [ | 0 | 0 | N/A | |||||
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| Low access to experts | Not within the scope of this review | 15 [ | 0 | 0 | 0 | |||||
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| Financial barriers | Not within the scope of this review | 1 [ | 0 | 0 | 0 | |||||
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| A low uptake of follow-up services | Not within the scope of this review | 7 [ | 0 | 0 | N/A | |||||
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| A lack of training opportunities for health workers | Not within the scope of this review | 10 [ | 0 | 0 | 0 | |||||
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| Poor data availability | Not within the scope of this review | 19 [ | 2 [ | 0 | 0 | |||||
aHPV: human papillomavirus.
bRepresents the number of included studies mapped to each category. For example, we found 3 studies that aimed to increase the demand for screening by increasing women’s knowledge of human papillomavirus or cervical cancer.
cSome studies were associated with multiple records, for example, Asgary et al [30,31].
Description of implementation challenges for digital health strategies for cervical cancer control.
| Implementation challenge | Included studies | Description and examples |
| High training requirements | [ |
Pretraining lasting several weeks, providing supplemental training for augmenting skills, refresher training to minimize loss of skills, and the availability of experts to provide ongoing feedback for using digital cervicography
Catarino et al [
Asgary et al [
Ndlovu et al [
Caster et al [ |
| Technology-specific challenges | [ |
Procurement of appropriate technology Challenges with the availability of technology options in the study area in preparation for and during the study [ Considerations related to finding mobile phone cameras with high image quality and zoom capabilities [ The use of high-pixel smartphone cameras were associated with better reported quality of images [ Parham et al [ Software and hardware issues: software “bugs,” crashing of apps, device malfunctions, and an insufficient battery life [ Gallay et al [ Data security issues Littman-Quinn et al [ Software updates Bhatt et al [ Littman-Quinn et al [ |
| Infrastructure challenges | [ |
Issues with network coverage and electrical outages as limitations to widespread implementation
Bhatt et al [
Yeates et al [ |
| Challenges with technology reach | [ |
Rashid et al [ Rashid et al [ |
| Inequitable access to technology | [ |
Exclusion of women without mobile phones from digital health intervention components in some studies |