The evaluation of effect Gammarana intervention to reducing stunting during the Covid-19 pandemic: Protocol evaluation of stunting intervention in Enrekang District

  • Sirajuddin Sirajuddin
    Student of Doctoral Public Health Hasanuddin University, Makassar; Nutrition and Dietetic Department Health Polytechnic of Makassar, Indonesia.
    https://orcid.org/0000-0001-9477-5824
  • Saifuddin Sirajuddin
    Department of Nutrition, Faculty of Public Health, Hasanuddin University, Makassar, Indonesia.
  • Razak Thaha
    Department of Nutrition, Faculty of Public Health, Makassar, Indonesia.
  • Amran Razak
    Department of Health Administration Policy ) Faculty Public Health, Hasanuddin University,Indonesia, Indonesia.
  • Ansariadi Ansariadi
    Department of Nutrition, Faculty of Public Health, Makassar, Indonesia.
  • Ridwan M Taha
    Department of Nutrition, Faculty of Public Health, Makassar, Indonesia.
  • Purnawan Junadi
    Department of Public Health, Faculty of Public Health, Indonesia University, Jakarta , Indonesia.
  • Pungkas Bahjuri Ali
    National Development Planning Agency of Indonesia. Jakarta , Indonesia.

ABSTRACT

Background: Evaluation of large-scale stunting interventions in Indonesia has never been carried out, because it found limited sensitive and specific interventions that were carried out massively at the village level. The provincial government of South Sulawesi Indonesia in 2020 has implemented a stunting intervention model called Gammarana. The purpose of this evaluation is to analyze the impact of Gammarana on changes in stunting at the project site. Location project as many as 30 villages with a population estimated 60,000.

Design and methods
: Evaluation in this study using a retrospective method and internal and external audit to document potential, then validated after the field visit Gammarana first phase in 2020. Basic Logic Model evaluation model with 22 indicators (input, process, secondary output and primary output). Proving the effect of Gammarana on changes in stunting by comparing the phenomena in the comparison village.

Results: 
The comparison villages were set as equal and comparable in 13 indicators that could disturb the study conclusions. The result of the initial condition is that the conditions of the two villages of Gammarana and Villages Comparison are seen as the same in various characteristics, so that whatever the results of this evaluation study are believed to be the impact of Gammarana Project.

Conclusions: 
this protocol eligible to evaluation of Gammarana Project Intervention in Enrekang District, South Sulawesi Indonesia.

REFERENCES

Ministry of Health. Basic Health Research Report of Indonesia Year 2018. Jakarta, Ministry of Health; 2018.

Keats EC, Haider BA, Tam E, Bhutta ZA. Multiple-micronutrient supplementation for women during pregnancy. Cochrane Database Syst Rev 2019;3:CD004905. DOI: https://doi.org/10.1002/14651858.CD004905.pub6

Nazmi A, Tseng M, Robinson D, et al. A Nutrition education intervention using NOVA is more effective than myplate alone: A proof-of-concept randomized controlled trial. Nutrients 2019;11:2965. DOI: https://doi.org/10.3390/nu11122965

Beal T, Tumilowicz A, Sutrisna A, et al. A review of child stunting determinants in Indonesia. Matern Child Nutr 2018;14:e12617. DOI: https://doi.org/10.1111/mcn.12617

Al Jawaldeh A, Doggui R, Borghi E, et al. Tackling childhood stunting in the eastern Mediterranean region in the context of COVID-19. Children (Basel) 2020;7:239. DOI: https://doi.org/10.3390/children7110239

Thornton RLJ, Glover CM, Cené CW, et al. Evaluating strategies for reducing health disparities by addressing the social determinants of health. Physiol Behav 2017;176:139-48.

Correia MITD. Nutrition in times of Covid-19, how to trust the deluge of scientific information. Curr Opin Clin Nutr Metab Care 2020;23:288-93. DOI: https://doi.org/10.1097/MCO.0000000000000666

Wilson R, Godfrey CM, Sears K, et al. Exploring conceptual and theoretical frameworks for nurse practitioner education: a scoping review protocol. JBI Database Syst Rev Implement Rep 2015;13:146-55. DOI: https://doi.org/10.11124/jbisrir-2015-2150

Malone HE. Fundamentals of estimating sample size. Nurse Res 2016;23:21-5. DOI: https://doi.org/10.7748/nr.23.5.21.s5

Mooney SJ. Big data in public health: Terminology, machine learning, and privacy. Annu Rev Public Health 2018;39:95-112. DOI: https://doi.org/10.1146/annurev-publhealth-040617-014208

Sherman M, Covert H, Brown L, et al. Enterprise evaluation: A new opportunity for public health policy. J Public Health Manag Pract 2019;25:479-89. DOI: https://doi.org/10.1097/PHH.0000000000000862

Hyejin K, Sefcik JS, Bradway C. Characteristics of qualitative descriptive studies: a systematic review. Res Nurs Health 2017;40:23-42. DOI: https://doi.org/10.1002/nur.21768

Abu-Arafeh A, Jordan H, Drummond G. Reporting of method comparison studies: A review of advice, an assessment of current practice, and specific suggestions for future reports. Br J Anaesth 2016;117:569-75. DOI: https://doi.org/10.1093/bja/aew320

Heo M, Kim N, Faith MS. Statistical power as a function of Cronbach alpha of instrument questionnaire items Data analysis, statistics and modelling. BMC Med Res Methodol 2015;15:1-9. DOI: https://doi.org/10.1186/s12874-015-0070-6

Hossain M, Choudhury N, Abdullah KAB, et al. Evidence-based approaches to childhood stunting in low and middle income countries: A systematic review. Arch Dis Child 2017;102:903-9. DOI: https://doi.org/10.1136/archdischild-2016-311050