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Record W3103778105 · doi:10.2196/20314

Mobile Phone Use and Acceptability for the Delivery of Mental Health Information Among Perinatal Adolescents in Nigeria: Survey Study

2020· article· en· W3103778105 on OpenAlexvenueno aff
Lola Kola, Dolapo Abiona, Adeyinka Olufolake Adefolarin, Dror Ben‐Zeev

Bibliographic record

VenueJMIR Mental Health · 2020
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
FundersFogarty International CenterNational Institutes of Health
KeywordsmHealthMedicinePsychological interventionMental healthMobile phonePublic healthHealth careFamily medicineEnvironmental healthPsychiatryNursing

Abstract

fetched live from OpenAlex

BACKGROUND: There are several barriers that may hamper adolescent mothers' utilization of available health interventions for perinatal depression. Innovative treatment approaches are needed to increase adolescent mothers' access to mental health care for improved maternal and child health outcomes. Mobile phones have the potential to serve as important conduits to mental health care in Africa. However, mobile phone use patterns and needs among young mothers in Nigeria are not well documented. OBJECTIVE: This study sought to determine the prevalence of mobile phone use among perinatal adolescents and report patterns of use, as well as to assess the openness of young mothers to mobile health (mHealth) mental health interventions. METHODS: We surveyed 260 adolescent mothers (ages 16-19 years) in their perinatal or postnatal periods of pregnancies in 33 primary health care clinics in Ibadan, Oyo State, Nigeria in 2020. Respondents were included if they were pregnant with a gestation age of greater than or equal to 4 weeks, or had babies (which they had birthed) that were younger than 12 months. RESULTS: The total study sample consisted of 260 adolescent mothers with a mean age of 18.4 (SD 0.88) years. The majority of the respondents (233/260, 89.6%) owned mobile phones (eg, keypad, keypad and internet, smartphones); 22 (8.5%) of the 260 mothers had access to phones that belonged to relatives who lived in the same household, while 5 (1.9%) had access only to public paid phones. Only 23% (54/233) of phone owners (which is 20.5% of the total study population) had smartphones. On average, respondents reported first using mobile phones at 15.5 (SD 2.06) years old. The majority of respondents (222/260, 85.4%) reported using their phones for an average of 45 minutes daily for calls to family members. Facebook was the social media platform that was most often used among respondents who had phones with internet access (122/146 minutes per day, 83.4%). The majority of the sample responded as being "interested" and "very interested" in the use of mobile phones for preventive interventions (250/260, 96.2%) and treatment (243/260, 93.5%) information on mental illness such as depression and "hearing voices." Half of the respondents (126/233, 50.4%) preferred to receive such information in the form of text messages. CONCLUSIONS: Findings from this study suggest that the vast majority of perinatal adolescents in Nigeria own and use mobile phones and that they are interested in leveraging these devices for prevention, treatment, and informational campaigns focused on mental health. The use of smartphones in this population is relatively low, and health intervention through text messages were favored by the women.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.051
GPT teacher head0.416
Teacher spread0.364 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations34
Published2020
Admission routes1
Has abstractyes

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