Evidence map›Paper›PMID 39312390›Full record

ArticleJournal of medical Internet research2024

Factors Associated With the Use of Digital Technology Among Youth in Zimbabwe: Findings From a Cross-Sectional Population-Based Survey.

Kevin Martin, Rachel Wei Chun Peh, Mandikudza Tembo, Constancia Vimbayi Mavodza, Aoife M Doyle, Chido Dziva Chikwari, Ethel Dauya, Tsitsi Bandason, Steven Azizi, Victoria Simms and 1 more

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Kevin MartinDepartment of Clinical Research, London School of Hygiene & Tropical Medicine, London, United Kingdom.ORCID 0000-0001-6561-1353
Rachel Wei Chun PehDepartment of Clinical Research, London School of Hygiene & Tropical Medicine, London, United Kingdom.ORCID 0009-0008-2252-1743
Mandikudza TemboThe Health Research Unit Zimbabwe, Biomedical Research and Training Institute, Harare, Zimbabwe.ORCID 0000-0002-4520-3317
Constancia Vimbayi MavodzaThe Health Research Unit Zimbabwe, Biomedical Research and Training Institute, Harare, Zimbabwe.ORCID 0000-0003-1651-5888
Aoife M DoyleThe Health Research Unit Zimbabwe, Biomedical Research and Training Institute, Harare, Zimbabwe.ORCID 0000-0002-3305-7738
Chido Dziva ChikwariThe Health Research Unit Zimbabwe, Biomedical Research and Training Institute, Harare, Zimbabwe.ORCID 0000-0003-1617-3603
Ethel DauyaThe Health Research Unit Zimbabwe, Biomedical Research and Training Institute, Harare, Zimbabwe.ORCID 0000-0003-3241-2512
Tsitsi BandasonThe Health Research Unit Zimbabwe, Biomedical Research and Training Institute, Harare, Zimbabwe.ORCID 0000-0003-0066-8345
Steven AziziThe Health Research Unit Zimbabwe, Biomedical Research and Training Institute, Harare, Zimbabwe.ORCID 0000-0002-6892-0984
Victoria SimmsThe Health Research Unit Zimbabwe, Biomedical Research and Training Institute, Harare, Zimbabwe.ORCID 0000-0002-4897-458X
Rashida A FerrandDepartment of Clinical Research, London School of Hygiene & Tropical Medicine, London, United Kingdom.ORCID 0000-0002-7660-9176

Funding

Wellcome Trust
6 · The paper itself

Abstract

backgroundGlobally, the increasing use of digital technologies such as mobile phones and the internet has allowed for the development of innovative mobile health interventions, particularly for reaching and engaging with youth. However, there is a risk that using such technologies may exclude those who lack access to them.

objectiveIn this study, we investigated the sociodemographic factors associated with mobile phone ownership, internet use, and social media use among youth in Zimbabwe.

methodsA population-based prevalence survey was conducted in 24 urban and periurban communities across 3 provinces of Zimbabwe (Harare, Mashonaland East, and Bulawayo). Youths aged 18 to 24 years resident in randomly selected households in the study communities completed an interviewer-administered questionnaire. The primary outcomes were mobile phone ownership and current internet and social media use. A household wealth indicator was developed using principal components analysis, based on household asset ownership. Multivariable logistic regression was used to investigate the factors associated with each primary outcome. Age, sex, and province were considered a priori confounders. Household wealth, marital status, education level, employment status, time lived at current address, and HIV status were included in the final multivariable model if there was an age-, sex-, and province-adjusted association with a primary outcome on univariable analysis at a significance level of P<.10.

resultsOf the 17,636 participants assessed for the primary outcome, 16,370 (92.82%) had access to a mobile phone, and 15,454 (87.63%) owned a mobile phone. Among participants with access to a mobile phone, 58.61% (9594/16,370) and 57.79% (9460/16,370), respectively, used internet and social media at least weekly. Older age (adjusted odds ratio [aOR] 1.76, 95% CI 1.55-2.00), increasing wealth (ranging from aOR 1.85, 95% CI 1.58-2.16, for wealth quintile 2 to aOR 3.80, 95% CI 3.00-4.80, for wealth quintile 5, with quintile 1 as reference), and higher education level (secondary: aOR 1.96, 95% CI 1.60-2.39; tertiary: aOR 8.36, 95% CI 5.29-13.20) were associated with mobile phone ownership. Older age, male sex, increasing wealth, having never been married, higher education level, being in education or formal employment, and having lived at the same address for ≥2 years were associated with higher levels of internet and social media use.

conclusionsWhile mobile phone ownership was near-universal, over one-third of youths in urban and periurban settings did not have access to the internet and social media. Access to the internet and social media use were strongly associated with household wealth and education level. Mobile health interventions must ensure that they do not amplify existing inequalities in access to health care. Such interventions must be accompanied by alternative strategies to engage and enroll individuals without internet or social media access to prevent the exclusion of young people by sex and socioeconomic status.

Indexed as

Digital TechnologyAdolescentAdultCell PhoneCross-Sectional StudiesFemaleHumansInternetMaleSocial MediaSociodemographic FactorsSurveys and QuestionnairesYoung AdultZimbabwedigital technologyhousehold wealthyouthZimbabwe

Identifiers

PMID39312390
PMCPMC11459104

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.