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Global child health
Digital tools to improve parenting behaviour in low-income settings: a mixed-methods feasibility study
  1. Lena Jäggi1,2,
  2. Leonel Aguilar3,
  3. Milagros Alvarado Llatance4,
  4. Andreana Castellanos5,
  5. Guenther Fink1,2,
  6. Kristen Hinckley1,2,
  7. Maria-Luisa Huaylinos Bustamante4,
  8. Dana Charles McCoy6,
  9. Hector Verastegui4,
  10. Daniel Mäusezahl1,2,
  11. Stella Maria Hartinger Pena2,4
  1. 1 University of Basel, Basel, Switzerland
  2. 2 Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
  3. 3 Department of Computer Science, ETH Zurich, Zurich, Switzerland
  4. 4 School of Public Health and Administration, Universidad Peruana Cayetano Heredia, Lima, Peru
  5. 5 Afinidata, Guatemala City, Guatemala
  6. 6 Harvard Graduate School of Education, Cambridge, Massachusetts, USA
  1. Correspondence to Dr Lena Jäggi, University of Basel, Basel 4001, Switzerland; lena.jaeggi{at}unibas.ch

Abstract

Introduction Digital parenting interventions could be potentially cost-effective means for providing early child development services in low-income settings. This 5-month mixed-methods pilot study evaluated the feasibility of using Afinidata, a comprehensive Facebook Messenger-based digital parenting intervention in a remote rural setting in Latin America and explored necessary adaptations to local context.

Methods The study was conducted in three provinces in the Cajamarca region, Peru, from February to July 2021. 180 mothers with children aged between 2 and 24 months and regular access to a smartphone were enrolled. Mothers were interviewed three times in-person. Selected mothers also participated in focus groups or in-depth qualitative interviews.

Results Despite the rural and remote study site, 88% of local families with children between 0 and 24 months had access to internet and smartphones. Two months after baseline, 84% of mothers reported using the platform at least once, and of those, 87% rated it as useful to very useful. After 5 months, 42% of mothers were still active on the platform, with little variation between urban and rural settings. Modifications to the intervention focused on assisting mothers in navigating the platform independently and included adding a laminated booklet with general information on child development, sample activities and detailed instructions on how to self-enrol in case of lost phones.

Conclusions We found high access to smartphones and the intervention was well received and used in very remote areas of Peru, suggesting that digital parenting interventions could be a promising path forward for supporting low-income families in remote parts of Latin America.

  • child development
  • global health
  • infant development

Data availability statement

Data are available on reasonable request.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi.org/10.1136/archdischild-2022-324964

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    WHAT IS ALREADY KNOWN ON THIS TOPIC

    • Digital parenting interventions are potentially cost-effective means for providing early child development services in low-income settings but have not been well-studied to date.

    WHAT THIS STUDY ADDS

    • This mixed-methods pilot study in a very remote setting in Latin America showed that 88% of local families with children between 0 and 24 months had access to smartphones with internet and 42% were still engaging with a digital parenting intervention after 5 months.

    HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

    • High access to smartphones suggest that digital parenting interventions could be a promising path forward for supporting low-income families in remote parts of Latin America, but mothers might benefit from additional instructions to navigate all features of digital interventions on their own.

    Introduction

    According to latest estimates, over 250 million young children are at risk of missing their developmental potential due to early life adversity.1 Early life interventions are increasingly recognised as key for ensuring children’s optimal development and long-term well-being.2 3

    One of the most promising interventions for low-income settings are home visiting programmes, where trained facilitators regularly visit parents following a structured curriculum to improve knowledge and care practices related to early child development (ECD).4 5 Such programmes have been successfully implemented across the world6–9 and in Peru.10 The national Peruvian home visiting programme (Programa Nacional Cuna Más (PNCM)11) is one of the world’s largest, serving families with children aged under 36 months from areas of poverty. While a recent evaluation has shown PNCM to positively impact ECD and be cost-effective at scale,12 the programme can currently only support the most vulnerable.

    The rapid rise in cell-phone coverage and internet access globally means digital parenting interventions may be one means for addressing gaps in ECD services in Peru and many other low-income and middle-income country (LMIC) settings.13 14 Afinidata is one example of a comprehensive digital parenting support platform leveraging this opportunity using a Facebook (FB) Messenger chatbot.15 The intervention is described in detail below and in online supplemental annex 1.

    Despite their potential, there is limited evidence on how feasible digital parenting interventions are in practice, especially in remote rural settings in LMIC. The current study describes the results of a 5-month mixed-methods study testing reach, reception and use of the Afinidata parenting platform while exploring necessary adaptations to local context. We also summarise lessons learnt for the implementation of Afinidata in a full-scale randomised controlled trial (RCT; https://clinicaltrials.gov/ct2/show/NCT05202106).

    Methods

    Setting

    The results reported in this study follow the framework for feasibility studies16 and Strengthening the Reporting of Observational Studies in Epidemiology standards.17 Community leaders and local authorities were aware of the study. No incentives were given for participation. The study was conducted in the provinces of San Marcos, Cajabamba and Cajamarca in northern Andean Peru, located between 1900 and 3900 m above sea level. The region is predominantly rural and representative of many rural and peri-urban settings in Andean South America, with a large share of poor and remote households engaged in farming. Communities were classified in accordance with the Peruvian National Institute of Statistics and Informatics as urban (communities with >2000 inhabitants with contiguous, grouped homes forming streets) or rural (scattered or grouped houses of up to 2000 inhabitants per community18). The study area is partially covered by PNCM.

    Participants

    Using administrative data on recent births, we identified all eligible families and visited them at home. We recruited 180 adult mothers with children aged between 2 and 24 months who either owned or had regular access to a smartphone.

    The intervention

    The Afinidata platform (www.afinidata.com) uses FB Messenger to interact with pregnant mothers and parents of children aged 0–6 years from low-income settings through automated chatbots. Afinidata was designed for LMIC families and includes minimal text and data-intensive features.

    Similar to home visitors, a ‘virtual tutor’ asks about the child’s well-being through messages and push-notifications and makes two to three suggestions for development-promoting activities that parents can do with their children. Parents can reach out to the chatbot anytime, seeking advice or sharing their child’s achievements. The system tracks parents’ reactions to the recommended activities, children’s age and development over time and uses this feedback to provide parents with customised activity recommendations.

    During the study, mothers received a weekly push-message with age-appropriate informative content and a reminder to use Afinidata. Mothers could also respond to questions about their children’s development, which were summarised into a simple graphical report. We screened all 641 activities and messages for the relevant age group (2–24 months) for local language, cultural appropriateness and availability of playing materials (see also online supplemental annex 1 for more details).

    Procedures

    We conducted 5 months of extensive field-testing with local mothers from February to July 2021, squarely during the COVID-19 pandemic in Peru.

    First, we measured internet and phone connectivity in 142 communities in all three provinces for all four national cell-phone providers. Measurements were taken in the central plaza, or in central schools, health centres or main roads. Using SIM cards for each provider in the same ZTE-BLADE-A3-2020 smartphone, we started a conversation with Afinidata in FB Messenger and opened the platform-generated link for an activity. Of the 136 communities with successful activity-download through at least one provider, we selected 49 communities for this study. We also noted presence of administration building, health centre and school for each community.

    Mothers were shown how to use Afinidata and completed a baseline interview in their home. After 2 months, mothers gave detailed qualitative and quantitative feedback on Afinidata content during a second visit. Simultaneously, we called 27 mothers who were not using Afinidata to inquire about technical difficulties and reasons for non-use and conducted seven focus group discussions (FGD) and two in-depth interviews with a mix of urban and rural mothers with varying levels of engagement in Afinidata. After 5 months, we conducted a final visit asking about additional family characteristics, mothers’ digital literacy and their platform use and satisfaction.

    Measures

    Main outcome measures

    Use of the app over time was measured automatically by Afinidata. We defined mothers as active users if they interacted with Afinidata at least weekly, either asking for an activity, choosing a Frequently Asked Question or updating their child’s development. Some other interactions, such as responding to push-messages, requesting tips on development or asking the virtual tutor direct questions, were not tracked in the system.

    Demographic, socioeconomic and literacy measures

    Sociodemographic data collected at baseline included household characteristics, reception of conditional cash transfers for poor families called ‘Juntos’,19 mother’s and child’s age (in years and months, respectively), mother’s education and economic activity. For reading comprehension, mothers answered three content questions after reading a sample activity. Results are presented as percentage who answered all questions correctly.

    Internet connectivity, phone use and digital literacy

    At baseline, mothers reported internet signal availability in the house, their phone ownership, type of contract, monthly cost and social media usage. At endline, mothers also reported on their satisfaction and future use of Afinidata and completed the Survey of Adult Skills digital literacy scale (Programme for the International Assessment of Adult Competencies; Cronbach’s alpha=0.79).20

    Data analysis

    Statistical analyses were conducted using STATA V.16 and Python’s statsmodels and scipy libraries. Participant characteristics are presented as means, SD and relative percentages. We compared participants from urban and rural communities with mothers who were active versus inactive at endline using χ2 test and two-sided Mann-Whitney U test (non-corrected for continuity). Additionally, we analysed participants’ engagement over time by mapping the weekly percentage of active mothers by phone ownership and setting (urban/rural).

    In the FGD and qualitative interviews, we asked in-depth questions on Afinidata satisfaction and specific in-platform features. Following simulation study by Namey et al,21 we estimated needing three to five FGD to reach 80%–90% saturation. FGD and interviews were tape-recorded and summarised in detailed notes. Notes were translated and analysed for common themes using a reflexive thematic approach.22 Finally, themes were compared with the data collected in the phone calls to mothers who were not using Afinidata and from the feedback on Afinidata content from the second visit.

    Results

    Reach of the digital intervention

    The five included urban communities had full internet connectivity for all providers and all resources present. Among the 44 rural communities, 10 (22%) had connectivity with only 1–2 phone providers. Figure 1 shows a participant flow chart. After up to 3 attempts at contact, 133 mothers were interviewed at a final visit. Table 1 shows a general description of the sample, as well as phone and social media use by urban and rural setting. Of all eligible families, 12% (35) were excluded because there was no smartphone available for the mother to use. Among included families, 16% (28) of mothers used a smartphone belonging to their husband or another family member.

    View this table:
    Table 1

    Demographic characteristics of sample

    Figure 1
    Figure 1

    Flow chart of study enrolment. *For endline, 31 mothers who were absent for visit 2 were contacted again.

    Reception and use of the intervention

    Two months after baseline, 84% of mothers reported ever using the platform and of those, 87% rated it as useful to very useful (mean=4.37/5, SD=1.00). These results are similar to automatically collected rates by Afinidata after 1 month (see figure 2A). Figure 2A also presents weekly engagement for mothers who had their own smartphone and those who used a family member’s phone. Results show generally higher engagement by mothers with their own phones. Figure 2B presents the same analysis by urban versus rural setting, and shows no meaningful differences between groups. Overall, 42% (73) of mothers were still active after 5 months. These mothers did not differ by age of the child (under or over 12 months), level of education or social media usage at baseline.

    Figure 2
    Figure 2

    Showing (A) Afinidata platform use over time by phone ownership and (B) Afinidata platform use over time by urban and rural setting.

    During the second visit, mothers gave feedback on specific activities they had received. Most mothers reported spending between 20 and 30 min on the activities per session. Only 11% of mothers recalled an activity they did not like. Recommendations for improvement included simpler wording and materials. Interviews with 16% of mothers who self-reported not using the platform revealed that barriers were mainly lack of time, followed by lost phone or lost access to a borrowed phone. Similarly, follow-up calls to 27 mothers without activity in the platform for over a month showed that mothers often did not re-instal the platform if they switched phones.

    In five FGD and two in-depth interviews mothers expanded on the topics above. Data analysis of the FGD and in-depth interviews showed that we had reached saturation on themes. Examples of original quotes and translations are included in online supplemental appendix 2. Overall, Afinidata was received very positively, and several mothers recounted spending more time engaging with their children, feeling closer to their children or involving their husbands in the activities.

    Mothers who experienced problems with materials reported substituting or moving on to the next activity without negative impact on their perception of the intervention. Most mothers cited time constraints as the main barrier for participation. For those mothers with school-aged children, this was mainly due to additional demands on managing virtual classes during the COVID-19 pandemic. Additionally, sometimes mothers lost access to their phone because their older children needed it for school. Technical difficulties, lack of credit or loss of phone were not perceived as relevant barriers for use.

    Adaptation of the intervention

    We changed various components of Afinidata or the RCT protocol following the detailed feedback (see table 2 for a summary). The most important lessons learnt were to include additional steps to facilitate self-enrolment or re-enrolment by the mother. For this, we designed a laminated booklet containing general information on ECD, sample activities and detailed self-enrolment instructions. To increase comfort and agency in using the platform, interviewers assist mothers in experiencing the platform features during the baseline visit of the RCT, and we added real-time communication between the field team and Afinidata to provide technical support during enrolment.

    View this table:
    Table 2

    Summary of modifications to the intervention based on participant feedback

    Discussion

    Digital parenting interventions are potentially cost-effective yet untested means for expanding access to ECD programmes in LMICs. In this study, we extensively tested the reach, reception and use of Afinidata, a FB Messenger-based ‘virtual tutor’ for parents, and explored necessary adaptations to local context in a remote rural setting in Latin America.

    Our results show that there was high access to internet and smartphones throughout the rural and remote region. Only six of the most remote villages out of 142 communities were excluded from the study area for lack of connectivity. Among eligible families, 88% had a smartphone and 94% of participating households had internet signal inside their homes. Moreover, 84% of mothers owned their own device, and almost all were already using Facebook (94%) and WhatsApp (96%). This shows a tremendous potential to reach most of the primary caregivers of young children through interventions that use those channels in a typical LMIC setting.

    Overall, participant feedback showed that the Afinidata platform was received very positively. Similarly, a recent study in the Peruvian Amazon region showed high acceptance of a mobile health-assisted curriculum by caregivers and facilitators and increased knowledge on child health among caregivers in the digitally enhanced home visit intervention.23 Most mothers visited at endline reported that they would continue to use Afinidata in the future. However, this contrasts with actual usage data from the platform.

    While there was high initial engagement with Afinidata, there was a rapid decline in use over 2 months, and after 5 months only 73 (42%) mothers were still engaging weekly. Digital parenting interventions commonly have to contend with high attrition rates.24 25 In programmes that resemble Afinidata (ie, freely available online-only universal prevention programmes for parents), completion rates as low as 15%26 to 7%27 have been reported. Since we only measured part of the possible interactions with the system, our results likely underestimate engagement with the platform. This means, in comparison with similar interventions, measured engagement at 5 months was high, but more data over longer time periods are needed.

    Keeping users engaged is a crucial and challenging step for all self-guided digital interventions. Using push-messages and other content are important means to maintain interest in the intervention. The following RCT will measure such interactions, expand our knowledge on engagement beyond 5 months and investigate additional barriers and encouragement for engagement.

    As expected, mothers who were using a family member’s phone showed lower rates of engagement, with only 25% still engaging weekly with the platform after 5 months. Importantly, we found no meaningful differences in engagement between urban or rural participants. Furthermore, there were no differences in use by mothers’ level of education, social media use or age of the child, indicating that the intervention is similarly relevant and accessible for mothers across different contexts. Lack of credit, technical difficulties and loss of phone were not perceived as barriers for engagement by the mothers, although field observations showed that mothers often did not re-instal the platform after they switched phones.

    Because we found few concerns regarding the content of Afinidata, we focused on modifications that would assist mothers in navigating the platform in our RCT (eg, teaching how to self-enrol, ask for technical support or leave the platform). Two key lessons learnt were: (1) while the use of the platform quickly becomes intuitive, mothers in remote areas with poor connection greatly benefit from personal assistance with the initial installation and exploration of features; (2) it is beneficial to accompany the digital intervention with a physical booklet giving instructions for later self-enrolment for families who might not have a smartphone present during the visit or who change phones later. While this investment in initial enrolment and ongoing technical support requires additional staffing, the overall costs associated with these changes are still well below those of an in-person intervention.

    Limitations

    This study had several limitations. Most importantly, we did not assess impact on maternal or child outcomes or cost-effectiveness of the intervention—this will be done in the ongoing RCT. Our results could be biased by losing the least satisfied users for follow-up. Excluding families without access to a smartphone means that this was not a truly representative sample.

    Conclusion

    Our results show that access to smartphones is high in remote areas of Peru. Participant feedback showed that digital ECD interventions are well-received by mothers initially. While app-use declined over time, engagement was higher than in similar self-guided digital interventions. Furthermore, engagement after 5 months was similar for mothers across urban and rural settings with diverse individual characteristics. Digital parenting interventions could thus be a promising path forward for supporting families in remote parts of Latin America and other LMICs.

    Data availability statement

    Data are available on reasonable request.

    Ethics statements

    Patient consent for publication

    Ethics approval

    This study was approved by the Universidad Peruana Cayetano Heredia (SIDISI: 202522-Ref 030-03-21) and the Ethics Commission for Northwest and Central Switzerland (EKNZ: AO_2021-00002). Participants gave informed consent to participate in the study before taking part.

    Acknowledgments

    We would like to thank our field staff for their excellent work and all their efforts, as well as study participants for their willingness to help us with this project.

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    Supplementary materials

    • Supplementary Data

      This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

    Footnotes

    • DM and SMHP are joint senior authors.

    • Twitter @AguilarMLeonel

    • Contributors LJ: writing—original draft, qualitative, quantitative analysis and guarantor. LAM: quantitative analysis, writing—review and editing. MAL: investigation, project administration, qualitative analysis. AC: conceptualisation, writing—review and editing. GF: conceptualisation, writing—review and editing, supervision. KH: writing—review and editing. M-LHB: investigation, project administration, writing—review and editing. DCMcC: conceptualisation, writing—review and editing. HV: data curation, writing—review and editing. DM: conceptualisation, writing—review and editing, supervision. SMHP: conceptualisation, writing—review and editing, supervision. All authors have approved the final version of this manuscript.

    • Funding This work was supported by the Botnar Research Center for Child Health (BRCCH) through a multi-investigator grant.

    • Disclaimer The sponsor had no role in the design, interpretation or publication of this manuscript.

    • Competing interests AC is CEO of Afinidata and has thus interest in the success of this platform. She was not involved with the analysis of the data and did not influence the way results were presented. All other authors declare no conflict of interest and have no financial interests to disclose.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.