20
views
0
recommends
+1 Recommend
2 collections
    0
    shares

      To submit your manuscript, please click here

      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      An Artificial Intelligence–Based, Personalized Smartphone App to Improve Childhood Immunization Coverage and Timelines Among Children in Pakistan: Protocol for a Randomized Controlled Trial

      research-article
      , MBBS, MPH 1 , , , PhD 2 , 3 , , MBBS 1 , , BSc, MA, MSc 1 , , BE, MS 4 , , BE 4 , , BCom 1 , , BE, MCS, MS, MEngg 4 , , MSc 5 , , MCS 1 , , BCS 1 , , BPharm, MPhil 6 , , MSc 1 , , PhD 7 , , MSc, PhD 7
      (Reviewer), (Reviewer)
      JMIR Research Protocols
      JMIR Publications
      artificial intelligence, AI, routine childhood immunization, EPI, LMICs, mHealth, Pakistan, personalized messages, routine immunization, smartphone apps, vaccine-preventable illnesses

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          The immunization uptake rates in Pakistan are much lower than desired. Major reasons include lack of awareness, parental forgetfulness regarding schedules, and misinformation regarding vaccines. In light of the COVID-19 pandemic and distancing measures, routine childhood immunization (RCI) coverage has been adversely affected, as caregivers avoid tertiary care hospitals or primary health centers. Innovative and cost-effective measures must be taken to understand and deal with the issue of low immunization rates. However, only a few smartphone-based interventions have been carried out in low- and middle-income countries (LMICs) to improve RCI.

          Objective

          The primary objectives of this study are to evaluate whether a personalized mobile app can improve children’s on-time visits at 10 and 14 weeks of age for RCI as compared with standard care and to determine whether an artificial intelligence model can be incorporated into the app. Secondary objectives are to determine the perceptions and attitudes of caregivers regarding childhood vaccinations and to understand the factors that might influence the effect of a mobile phone–based app on vaccination improvement.

          Methods

          A mixed methods randomized controlled trial was designed with intervention and control arms. The study will be conducted at the Aga Khan University Hospital vaccination center. Caregivers of newborns or infants visiting the center for their children’s 6-week vaccination will be recruited. The intervention arm will have access to a smartphone app with text, voice, video, and pictorial messages regarding RCI. This app will be developed based on the findings of the pretrial qualitative component of the study, in addition to no-show study findings, which will explore caregivers’ perceptions about RCI and a mobile phone–based app in improving RCI coverage.

          Results

          Pretrial qualitative in-depth interviews were conducted in February 2020. Enrollment of study participants for the randomized controlled trial is in process. Study exit interviews will be conducted at the 14-week immunization visits, provided the caregivers visit the immunization facility at that time, or over the phone when the children are 18 weeks of age.

          Conclusions

          This study will generate useful insights into the feasibility, acceptability, and usability of an Android-based smartphone app for improving RCI in Pakistan and in LMICs.

          Trial Registration

          ClinicalTrials.gov NCT04449107; https://clinicaltrials.gov/ct2/show/NCT04449107

          International Registered Report Identifier (IRRID)

          DERR1-10.2196/22996

          Related collections

          Most cited references27

          • Record: found
          • Abstract: found
          • Article: not found

          Patient reminder and recall interventions to improve immunization rates

          Immunization rates for children and adults are rising, but coverage levels have not reached optimal goals. As a result, vaccine-preventable diseases still occur. In an era of increasing complexity of immunization schedules, rising expectations about the performance of primary care, and large demands on primary care providers, it is important to understand and promote interventions that work in primary care settings to increase immunization coverage. One common theme across immunization programs in many nations involves the challenge of implementing a population-based approach and identifying all eligible recipients, for example the children who should receive the measles vaccine. However, this issue is gradually being addressed through the availability of immunization registries and electronic health records. A second common theme is identifying the best strategies to promote high vaccination rates. Three types of strategies have been studied: (1) patient-oriented interventions, such as patient reminder or recall, (2) provider interventions, and (3) system interventions, such as school laws. One of the most prominent intervention strategies, and perhaps best studied, involves patient reminder or recall systems. This is an update of a previously published review.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            SMS text message reminders to improve infant vaccination coverage in Guatemala: A pilot randomized controlled trial

            Highlights • A novel SMS vaccine reminder platform was created in a LMIC. • SMS vaccine reminders were proven feasible to implement in a LMIC. • SMS vaccine reminders were acceptable to use in a LMIC with high user satisfaction. • SMS vaccine reminders have the potential for widespread scalability at low cost.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Text4Health: impact of text message reminder-recalls for pediatric and adolescent immunizations.

              We conducted 2 studies to determine the impact of text message immunization reminder-recalls in an urban, low-income population. In 1 study, text message immunization reminders were sent to a random sample of parents (n = 195) whose children aged 11 to 18 years needed either or both meningococcal (MCV4) and tetanus-diphtheria-acellular pertussis (Tdap) immunizations. We compared receipt of MCV4 or Tdap at 4, 12, and 24 weeks with age- and gender-matched controls. In the other study, we compared attendance at a postshortage Haemophilus influenzae B (Hib) immunization recall session between parents who received text message and paper-mailed reminders (n = 87) and those who only received paper-mailed reminders (n = 87). Significantly more adolescents with intervention parents received either or both MCV4 and Tdap at weeks 4 (15.4% vs 4.2%; P < .001), 12 (26.7% vs 13.9%; P < .005), and 24 (36.4% vs 18.1%; P < .001). Significantly more parents who received both Hib reminders attended a recall session compared with parents who only received a mailed reminder (21.8% vs 9.2%; P < .05). After controlling for age, gender, race/ethnicity, insurance status, and language, text messaging was still significantly associated with both studies' outcomes. Text messaging for reminder-recalls improved immunization coverage in a low-income, urban population.
                Bookmark

                Author and article information

                Contributors
                Journal
                JMIR Res Protoc
                JMIR Res Protoc
                ResProt
                JMIR Research Protocols
                JMIR Publications (Toronto, Canada )
                1929-0748
                December 2020
                4 December 2020
                : 9
                : 12
                : e22996
                Affiliations
                [1 ] Department of Pediatrics and Child Health Aga Khan University Karachi Pakistan
                [2 ] Department of Electrical Engineering NED University of Engineering and Technology Karachi Pakistan
                [3 ] Neurocomputation Lab National Centre of Artificial Intelligence Karachi Pakistan
                [4 ] Department of Civil Engineering NED University of Engineering and Technology Karachi Pakistan
                [5 ] Faculty of Electrical and Computer Engineering NED University of Engineering and Technology Karachi Pakistan
                [6 ] Pharmacy Services Aga Khan University Karachi Pakistan
                [7 ] Surrey Business School University of Surrey Guildford Surrey United Kingdom
                Author notes
                Corresponding Author: Abdul Momin Kazi momin.kazi@ 123456aku.edu
                Author information
                https://orcid.org/0000-0001-8253-1777
                https://orcid.org/0000-0002-1522-0677
                https://orcid.org/0000-0002-3049-9979
                https://orcid.org/0000-0002-4200-3918
                https://orcid.org/0000-0002-0735-5387
                https://orcid.org/0000-0001-8675-9963
                https://orcid.org/0000-0002-0473-2992
                https://orcid.org/0000-0001-8151-6428
                https://orcid.org/0000-0003-3270-1314
                https://orcid.org/0000-0001-6244-9063
                https://orcid.org/0000-0002-7862-8530
                https://orcid.org/0000-0003-1827-386X
                https://orcid.org/0000-0001-9453-0237
                https://orcid.org/0000-0001-7141-0312
                https://orcid.org/0000-0002-8615-2253
                Article
                v9i12e22996
                10.2196/22996
                7748948
                33274726
                e08b9ef8-3460-48cb-ae68-14ac25703b86
                ©Abdul Momin Kazi, Saad Ahmed Qazi, Sadori Khawaja, Nazia Ahsan, Rao Moueed Ahmed, Fareeha Sameen, Muhammad Ayub Khan Mughal, Muhammad Saqib, Sikander Ali, Hussain Kaleemuddin, Yasir Rauf, Mehreen Raza, Saima Jamal, Munir Abbasi, Lampros K Stergioulas. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 04.12.2020.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on http://www.researchprotocols.org, as well as this copyright and license information must be included.

                History
                : 29 July 2020
                : 27 August 2020
                : 7 September 2020
                : 10 November 2020
                Categories
                Protocol
                Protocol

                artificial intelligence,ai,routine childhood immunization,epi,lmics,mhealth,pakistan,personalized messages,routine immunization,smartphone apps,vaccine-preventable illnesses

                Comments

                Comment on this article