Awareness Of Saving One Million Lives Program For Results Among Women Of Reproductive Age And The Application Of Diffusion Of Innovations Theory In Accelerating Adoption Of The Programme In Bayelsa State, Nigeria

Authors

  • Abisoye Sunday Oyeyemi Department of Community Medicine, Faculty of Clinical Sciences, College of Health Sciences,Niger Delta University, WilberforceIsland, Bayelsa State, Nigeria https://orcid.org/0000-0001-8455-7591
  • Stella Ufuoma Rotifa Department of Community Medicine, Faculty of Clinical Sciences, College of Health Sciences,Niger Delta University, WilberforceIsland, Bayelsa State, Nigeria
  • Obioma Obiora Obikeze Department of Community Medicine, Federal Medical Centre, Yenagoa, Bayelsa State, Nigeria
  • Ulunma Ikwuoma Mariere Department of Community Medicine, Federal Medical Centre, Yenagoa, Bayelsa State, Nigeria
  • Numonyo Duabo Dambo Department of Obstetrics and Gynaecology, Diete-Koki Memorial Hospital, Yenagoa, Bayelsa State, Nigeria
  • Adedotun Daniel Adesina The Medical Centre, The Nigerian Law School, Yenagoa Campus, Bayelsa state, Nigeria
  • Ebikapaye Okoyen Bayelsa State Ministry of Health, Yenagoa, Bayelsa State, Nigeria

Keywords:

awareness, adoption, diffusion, innovation, SOML PforR

Abstract

Background: Saving One Million Lives Program for Results (SOML PforR) is a relatively new intervention designed to improve maternal, newborn, and child health (MNCH) in Nigeria. This study aimed to determine awareness of SOML PforR and discuss the application of Diffusion of Innovations (DOI) theory to accelerate adoption of the programme.

Methods: A cross-sectional descriptive study was conducted in all the 105 wards in the eight local government areas (LGAs) of Bayelsa State, Nigeria. A structured interviewer-administered questionnaire was used to collect data from a random sample of 1250 women of reproductive age residing in communities where facilities offering SOML PforR services were located. Descriptive statistics were used to summarise the quantitative variables. The association between categorical variables was determined using Chi‑square test. Binary logistic regression was done to determine predictors of awareness of SOML in the state.

Results: Data were analysed for 1223 women. The mean age (standard deviation) of the women was 28.5 (6.8) years. Most (81.8%) participants were married/cohabiting and 77.1% had at least secondary education. Only 7% of the women had heard about SOML PforR with radio as the predominant source of information (61.2%). Education was the only predictor of awareness among the women (Adjusted OR=2.26, 95%CI 1.03-4.95).

Conclusion: Awareness of SOML PforR was poor despite several months of implementation. Engaging early adopters and use of appropriate communication channels can accelerate adoption of the programme.

Author Biographies

Abisoye Sunday Oyeyemi, Department of Community Medicine, Faculty of Clinical Sciences, College of Health Sciences,Niger Delta University, WilberforceIsland, Bayelsa State, Nigeria

Oasis Public Health Consulting Research Group, Yenagoa, Bayelsa State, Nigeria

Stella Ufuoma Rotifa, Department of Community Medicine, Faculty of Clinical Sciences, College of Health Sciences,Niger Delta University, WilberforceIsland, Bayelsa State, Nigeria

Oasis Public Health Consulting Research Group, Yenagoa, Bayelsa State, Nigeria

Obioma Obiora Obikeze, Department of Community Medicine, Federal Medical Centre, Yenagoa, Bayelsa State, Nigeria

Oasis Public Health Consulting Research Group, Yenagoa, Bayelsa State, Nigeria

Ulunma Ikwuoma Mariere, Department of Community Medicine, Federal Medical Centre, Yenagoa, Bayelsa State, Nigeria

Oasis Public Health Consulting Research Group, Yenagoa, Bayelsa State, Nigeria

Numonyo Duabo Dambo, Department of Obstetrics and Gynaecology, Diete-Koki Memorial Hospital, Yenagoa, Bayelsa State, Nigeria

Oasis Public Health Consulting Research Group, Yenagoa, Bayelsa State, Nigeria

Adedotun Daniel Adesina, The Medical Centre, The Nigerian Law School, Yenagoa Campus, Bayelsa state, Nigeria

Oasis Public Health Consulting Research Group, Yenagoa, Bayelsa State, Nigeria

Ebikapaye Okoyen, Bayelsa State Ministry of Health, Yenagoa, Bayelsa State, Nigeria

Oasis Public Health Consulting Research Group, Yenagoa, Bayelsa State, Nigeria

References

Central Intelligence Agency. The World Factbook. Country comparison: maternal mortality rate [Internet]. [cited 2020 Aug 29]. Available from: https://www.cia.gov/library/publications/resources/the-world-factbook/fields/353rank.html

Central Intelligence Agency. The World Factbook. Country comparison: infant mortality rate [Internet]. [cited 2020 Aug 29]. Available from: https://www.cia.gov/library/publications/resources/the-world-factbook/fields/354rank.html

National Population Commission (NPC) [Nigeria], ORC Macro. Nigeria Demographic and Health Survey 2003. Calverton, Maryland; 2004.

National Population Commission(NPC)[Nigeria] and ORC Macro. Nigeria Demographic and health Survey 2008. 2010;1–630.

National Population Commission (NPC) [Nigeria] and ICF International. Nigeria Demographic and Health Survey 2013. Abuja, Nigeria, and Rockville, Maryland, USA: NPC and ICF International. 2014;1–566.

National Population Commission (NPC) [Nigeria] and ICF. Nigeria Demographic and Health Survey 2018. Abuja, Nigeria, and Rockville, Maryland, USA: NPC and ICF.; 2019.

World Health Organization. Technical updates of the guidelines on the Integrated Management of Childhood Illness (IMCI ): Evidence and recommendations for further adaptations [Internet]. 2005. Available from: https://apps.who.int/iris/bitstream/handle/10665/43303/9241593482.pdf?sequence=1

EpiAfric. An Evaluation of the Maternal and Child Health Project of the Subsidy Reinvestment and Empowerment Programme (SURE-P MCH) [Internet]. 2015 [cited 2020 Aug

. Available from: http://epiafric.com/wp-content/uploads/2019/05/An-Evaluation-of-the-Maternal-and-Child-Health-Project-of-the-Subsidy-Reinvestment-and-Empowerment-Programme-SURE-P-MCH.pdf

National Primary Health Care Development Agency. Nigeria Midwives Service Scheme [Internet]. [cited 2020 Aug 29]. Available from: https://www.who.int/workforcealliance/forum/2011/hrhawardscs26/en/

Federal Ministry of Health. Program Implementation Manual (PIM): Saving One Million Lives Program for Results. Abuja, Nigeria; 2016.

The World Bank. Nigeria - Program to Support Saving One Million Lives [Internet]. [cited 2020 Sep 22]. Available from: cts-operations/project-detail/P146583?lang=en

World Health Organization Europe. Ottawa Charter for Health Promotion [Internet]. 1986 [cited 2020 Sep 2]. Available from: https://www.euro.who.int/__data/assets/pdf_file/0004/129532/Ottawa_Charter.pdf?ua=1

Koh H, Seng CK, Id HL. Community participation in health services development, implementation, and evaluation: A systematic review of empowerment, health, community, and process outcomes. PLoS One. 2019;14(5):1–25.

Yaya S, Bishwajit G, Uthman OA, Amouzou A. Why some women fail to give birth at health facilities : A comparative study between Ethiopia and Nigeria. PLoS One. 2018;13(5):1–11.

Inuwa J. Barriers to facility-based delivery in Niger State, North Central Nigeria. Int J Percept Public Heal. 2018;2(2):108–14.

Dearing J, Cox J. Diffusion Of Innovations Theory, Principles, And Practice. Health Aff. 2018;37(2):183–90.

LaMorte WW. Behavioral Change Models [Internet]. [cited 2020 Sep 19]. Available from: https://sphweb.bumc.bu.edu/otlt/MPH-Modules/SB/BehavioralChangeTheories/BehavioralChangeTheories4.html#headingtaglink_1

Health Communication Capacity Collaborative. Diffusion of Innovations: an HC3 Research Primer [Internet]. [cited 2020 Sep 19]. Available from: http://www.healthcommcapacity.org/wp-content/uploads/2014/03/diffusion_of_innovations_kim.pdf

Lien AS-Y, Jiang Y-D. Integration of diffusion of innovation theory into diabetes care. J Diabetes Investig. 2017;8(3):2016–7.

Zhang X, Yu P, Yan J, Spil ITAM. Using diffusion of innovation theory to understand the factors impacting patient acceptance and use of consumer e-health innovations : a case study in a primary care clinic. BMC Health Serv Res. 2015;15(71):1–15.

Dearing JW, Smith DK, Larson RS, Estabrooks CA. Designing for Diffusion of a Biomedical Intervention. AMEPRE [Internet]. 2013;44(1):S70–6. Available from: http://dx.doi.org/10.1016/j.amepre.2012.09.038

National Bureau of Statistics. Annual Abstract of Statistics 2016 [Internet]. 2017 [cited 2020 Oct 1]. Available from: https://www.nigerianstat.gov.ng/pdfuploads/ANNUAL ABSTRACT STATISTICS VOLUME-1.pdf

National Bureau of Statistics. 2017 Demographic statistics bulletin. 2018.

Araoye MO. Research methodology with statistics for health and social sciences. Ilorin: Nathadex Publishers; 2004.

National Bureau of Statistics. National Nutrition and Health Survey (NNHS) 2015. Abuja,

Downloads

Published

2022-06-30

How to Cite

Oyeyemi, A. S., Rotifa, S. U., Obikeze, O. O., Mariere, U. I., Dambo, N. D., Adesina, A. D., & Okoyen, E. (2022). Awareness Of Saving One Million Lives Program For Results Among Women Of Reproductive Age And The Application Of Diffusion Of Innovations Theory In Accelerating Adoption Of The Programme In Bayelsa State, Nigeria . The Nigerian Health Journal, 22(2). Retrieved from https://tnhjph.com/index.php/tnhj/article/view/553

Similar Articles

1 2 3 4 5 6 7 > >> 

You may also start an advanced similarity search for this article.