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ORIGINAL ARTICLE
Year : 2022  |  Volume : 66  |  Issue : 3  |  Page : 300-306  

Knowledge and practice pattern of integrated child development services scheme supervisors (AWS) following capacity building and remote supportive supervision


1 Junior Resident, Department of Community Medicine, Assam Medical College and Hospital, Dibrugarh, Assam, India
2 Professor, Department of Community Medicine, Assam Medical College and Hospital, Dibrugarh, Assam, India
3 Assistant Professor, Department of Community Medicine, Assam Medical College and Hospital, Dibrugarh, Assam, India

Date of Submission01-Jun-2022
Date of Decision31-Jul-2022
Date of Acceptance01-Aug-2022
Date of Web Publication22-Sep-2022

Correspondence Address:
Baidurjya Mahanta
Department of Community Medicine, Assam Medical College and Hospital, Dibrugarh - 786 002, Assam
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijph.ijph_725_22

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   Abstract 


Background: Nutritional status of under-5 children in India is not promising and lags far behind the WHO Global Nutrition Targets. Although the Integrated Child Development Services has been continuously delivered through Anganwadi centers since 1975, the burden of malnutrition still persists. Objectives: This study was conducted to estimate the knowledge and practice pattern of Anganwadi supervisors and the effect of capacity building through remote supportive supervision during the COVID-19 pandemic in Assam, India. Methods: A cross-sectional before-after study using a mixed methods approach was used to evaluate the knowledge pattern and service delivery of supervisors from each district of Assam. For qualitative assessment, telephone depth interviews were conducted. Results: Knowledge of supervisors in the beginning was 83.43% which improved by 7.97% at the end of the study. The highest burden of SAM children was in Tinsukia and Barpeta districts. On mapping, most districts with lower burden of SAM had supervisors with higher knowledge levels on Infant and Young Child Feeding practices. Qualitative assessment revealed house-to-house visit for ensuring service delivery and use of online platforms and phone calls for counseling. However, community resistance and lack of transport stood as a main challenge. Conclusion: Supportive supervision done remotely during the pandemic to enhance the performance of health workforce was found effective.

Keywords: Anganwadi, COVID, Infant and Young Child Feeding, nutrition, supportive supervision, under-5


How to cite this article:
Mahanta B, Mahanta TG, Boruah M. Knowledge and practice pattern of integrated child development services scheme supervisors (AWS) following capacity building and remote supportive supervision. Indian J Public Health 2022;66:300-6

How to cite this URL:
Mahanta B, Mahanta TG, Boruah M. Knowledge and practice pattern of integrated child development services scheme supervisors (AWS) following capacity building and remote supportive supervision. Indian J Public Health [serial online] 2022 [cited 2022 Nov 26];66:300-6. Available from: https://www.ijph.in/text.asp?2022/66/3/300/356616




   Introduction Top


Nutritional disorders are accountable for 45% of deaths globally in children under 5 years of age,[1] of which two-third are attributed to undernutrition.[2] Undernutrition cannot solely be attributed to limited income or food insecurity (World Bank 2006). With the advent of the Green Revolution toward the late 1960s, India became reasonably self-sufficient and food secure.[2] Yet, India is still burdened with 32.1% underweight, 35.5% stunted, and 19.3% wasted under-5 children as per the NFHS-5 report, 2019–2021. Improper care and faulty infant feeding practices lead to nearly two-third burden of malnutrition in the 1st year of life.[3] Ensuing 90% coverage of the Infant and Young Child Feeding (IYCF) practices, nearly 45 million deaths in under-5 children could be averted.[4]

To intercept this continuing burden of malnutrition, decades of program policies and efforts have been brought about in India. Notable among them is the Integrated Child Development Services (ICDS) that started in 1975. Progress made so far is substantial, yet India finds itself faltering far behind the WHO Global Nutrition Targets set to be achieved by 2025. To bring momentum and focus to this global effort, POSHAN (Prime Minister's Overarching Scheme for Holistic Nourishment) Abhiyaan was launched in the year 2018.[2] This program is set up on the pedestal laid down by ICDS program, and relies on ICDS to deliver services decentralized at Anganwadi center (AWC) level.[5] With approximately 1.4 million Anganwadi workers (AWWs) across nation, ICDS is the world's biggest integrated program on early childhood development.[6] AWW are frontline workers who provide necessary health and nutrition services and serve as key informants of current health issues in her community.[7] They are mentored by Anganwadi supervisors who provide constant on-job guidance, and impart nutrition and health education on several aspects of mother and child health to them. Thus, it is important for the supervisor to have sufficient scientific knowledge about feeding practices, nutrition, and growth monitoring.[8]

Even though ICDS program is ambitious in its efforts, there are certain flaws such as (a) focus on increasing coverage rather than providing quality services, (b) inadequate logistics, (c) training of workers in fragments, (d) less supervision, and (e) overburdened and overlapping roles of AWWs.[9] To strengthen nutritional service delivery, an essential aid would be supportive supervision, as evident by studies from Ghana,[10] and Nicaragua.[11] With imposition of lockdown due to the recent COVID-19 pandemic and subsequent disruption of services, efforts to tackle malnutrition are now retrogressed. Physical supervision was not feasible, and alternative methods to ensure the continuity of essential nutrition service delivery were called for to be future-proof.

Bulk of research on nutrition has been clustered around nutritional status of beneficiaries. Determining the link between remote supportive supervision and Anganwadi supervisor performance would contribute to investment planning and provide insight on ways to improve nutrition delivery service. This study aims at estimating the knowledge and practice pattern of Anganwadi Supervisor (AWS) and the effect of capacity building through remote supportive supervision in the state of Assam, India.


   Materials and Methods Top


Setting

Assam is situated in North-East India and children below 6 years constitute nearly 14.8% of its population.[12] All districts of Assam were covered in this study.

Sample size calculation

Assuming that 63% of the supervisors before sensitization have adequate IYCF knowledge,[8] to detect a 10% difference of proportion after capacity building with a design effect 2 and power of 90%, the study would require a sample size of 1183 pairs, at a two-sided P = 0.05.

Study design

This study is a cross-sectional before-after study using a mixed methods approach. A list of state-level supervision team identified as “Mentors for Nutrition” was put together for telephonic supportive supervision. Three rounds of telephonic sensitization and supportive supervision were made covering most Anganwadi supervisors from each district of Assam. In addition, an assessment of AWWs was carried out to get an insight of their knowledge and performance in service delivery following the supportive supervision of their supervisors.

The first round of phone calls was made in the month of June. Mentors reached out to all the supervisors telephonically on continuation of essential services during the pandemic, and explained about our present study. The baseline knowledge level of AWS was documented in the first round of calls. The other two rounds comprised telephonic sensitization and supportive supervision followed by assessment of knowledge retention in the month of August–September and October–November, respectively. Supervisors in turn would conduct similar sensitization for all AWWs under their respective sectors through brief in-person/telephonic interactions. All supervisors who received call and consented verbally for the study were included, whereas those who were promoted/failed to attend calls after three successive attempts were excluded [Figure 1].
Figure 1: Participant flow

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Ethical consideration

Institutional ethical clearance was taken. All necessary permission from state and district authorities were obtained. Those not giving consent were not included in the study.

Data collection tool

A pretested, semi-structured questionnaire for quantitative assessment of their knowledge was used. In-depth telephonic interview was conducted to understand progress and challenges in service delivery. The AWS also provided a compiled report of SAM children from their respective ICDS sectors.

A composite score of knowledge for each supervisor was computed based on their knowledge on breastfeeding practices, complementary feeding practices, dietary diversity, growth monitoring, identification, and referral of malnourished children. This score was compared with the burden of SAM children obtained from reports of AWS for each district and plotted on map. Mapping of SAM children was done to compare the performance of each district, and to corroborate with knowledge pattern of AWS. For the secondary analysis, performance of AWWs was gauged based on number of home visits conducted, pregnant women reached with messages of nutrition, breastfeeding, complementary feeding, growth monitoring, and supply of take-home ration.

Data analysis

Categorical data were presented as proportions, and Chi-square, regression analysis was done using Epi Info ver. 7.2.4.0. Maps were created using Quantum Geographic Information System (QGIS) v3.16.3. Categories were generated for analysis of qualitative assessment from verbatim of telephonic depth interview of AWS.


   Results Top


To achieve the desired sample size, we had to call 89.2% of total AWS in Assam. A substantial void in knowledge pattern was seen concerning knowledge on number of food groups (47.69% before supportive supervision). Nearly 95% of supervisors knew the correct frequency for weight monitoring. As shown in [Table 1], the AWS who received supportive supervision telephonically improved significantly in the third round once baseline knowledge level of AWS was adjusted. Knowledge on feeding practices, namely exclusive breastfeeding (96.59% vs. 98.48%, odds ratio [OR]: 2.29 [1.26–4.18], P = 0.006), complementary feeding (97.47% vs. 99.60%, OR: 6.41 [2.24–18.28], P < 0.001), enumeration of food groups (64.72% vs. 96.06%, OR: 13.29 [9.44–18.72], P < 0.001), minimum dietary diversity (70.8% vs. 86.0%, OR: 2.521 [2.024–3.142], P = 0.001), improved after remote supportive supervision. When the knowledge (before-after) was assessed on identification of SAM children (92.40 vs. 95.9%, OR: 1.903 [1.300–2.787], P < 0.001), a significant improvement was observed. However, knowledge on breastfeeding initiation (96.51% vs. 91.6%, OR: 0.417 [0.283–0.617], P < 0.001), and referral (98.25% vs. 95.66%, OR 0.392 [0.229–0.670], P < 0.001) of children with severe acute malnutrition (SAM) did not show any improvement post capacity building [Table 1].
Table 1: Comparative analysis of knowledge scores before and after remote supportive supervision

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The total number of SAM children identified was 2942, out of which 2327 (79.09%) were enrolled under community-based management of acute malnutrition (CMAM) at the end of the third round of analysis. The top five districts with the largest burden of SAM children were namely Tinsukia, Barpeta, Golaghat, Morigaon, and Sonitpur in descending order, with Tinsukia and Barpeta alone contributing to nearly 33% (968) of total burden.

On plotting the data of composite AWS score and SAM burden of each district in QGIS, we found that the knowledge of supervisors of the low-performing districts was lower compared to other well-performing districts. Nevertheless, few districts such as Barpeta, Golaghat, and Sonitpur had supervisors more than average knowledge score despite a higher prevalence of SAM children in their respective districts [Figure 2].
Figure 2: (a and b) Distribution of children with severe acute malnutrition and knowledge of Anganwadi supervisors. (a) (left) Burden of SAM children and (b) (right) The average knowledge scores of the supervisors from each district of Assam

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A secondary analysis on knowledge and performance of AWWs under each supervisor was also carried out. A composite score on knowledge level (similar criteria as mentioned for supervisors) and performance was calculated. Performance was assessed on the total number of home visits (minimum 30), pregnant women reached with messages of nutrition, message on breastfeeding, complementary feeding, screening of under-5 children for SAM (minimum 30), and supply of take-home ration. For the same, mediation analysis was carried out with telephonic sensitization on CMAM by their supervisors acting as a mediator. It was hypothesized that AWW knowledge will positively predict AWW performance, and sensitization on CMAM by AWS would mediate this relationship. The result shows that knowledge of AWWs positively predicts AWW performance (B: 0.124, t: 4.829 (0.174, 0.073), P < 0.001). With the inclusion of mediating variable (sensitization by AWS), the impact of AWW knowledge on performance became insignificant (B: 0.042, t: 1.113 (0.117, 0.032), P = 0.266). However, the indirect effect through mediating role of AWS sensitization (B: 0.201, t: 0.065 (0.064, 0.338), P = 0.004) had a positive impact on AWW performance, with an R2 of 0.413 [Figure 3].
Figure 3: Mediation analysis of AWS sensitization on AWW knowledge and their performance. AWW: Anganwadi worker, AWS: Anganwadi supervisor

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Telephonic depth interview was conducted to reveal the ground reality of challenges faced in service delivery during the pandemic, and how AWS/AWWs overcame it. [Table 2] illustrates the analysis brought about verbatim of supervisors. Abstraction of data from transcribed interviews revealed that the common challenges were community resistance, inaccessibility, transportation problem, and work-related issues of AWWs. Initially, people denied entry of AWWs to their houses due to fear of COVID-19 which created a huge gap in health communication. During lockdown, as public transportation was closed, many AWWs faced difficulty in transporting Take home ration (THR) to far-flung areas and containment zones. Finally, there were inherent issues of job-related satisfaction among the AWWs during the pandemic. To ensure service delivery in such adversities, community engagement, telephonic communication, and online platforms were used for health communication and nutritional counseling. Ration was made easily accessible through home delivery or distributing at community venues.
Table 2: Content analysis from verbatim of telephonic-depth interview of AWS

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   Discussion Top


Findings of the present study indicate that supportive supervision done remotely result in improvement of IYCF knowledge among AWS by 7.97%. A significant improvement on identification of SAM children was observed. Although knowledge on services under CMAM improved by the end of the study, it was not significant statistically. Once an AWW identifies a SAM child, an auxiliary nurse midwife looks for any underlying medical conditions. In the absence of any medical complication, the current protocol recommends child to be managed at the community itself under CMAM. The SAM child receives antibiotics, double THR, micronutrient supplementation, weekly home visits, fortnightly weight-for-height assessment, and follow-up by AWWs.[13] NFHS-5 2019–2021 for the state of Assam reveals an upsurge of 3.7% (21.7 vs. 17.0) wasted children, 3% underweight (32.8 vs. 29.8), and decline of 1% (35.3 vs. 36.4) stunted under-5 children compared to NFHS-4 (November 2015–March 2016).[14] To improve the nutritional service delivery, ICDS offers periodic training of AWWs and their supervisors. But even frequent training or increasing duration of training may fail to bring about change in competency as time passes.[15] Recently, POSHAN Abhiyaan has prescribed a checklist for monitoring AWC by supervisors.[16] Provision of checklist for monitoring may lead to an authoritarian approach rather than problem-solving.[17] Thus, hand-holding through mentoring, scheduled, and structured supervision with constructive feedback is required. A few notable studies done previously on the role of supportive supervision showed augmented performance of frontline health workers.[18],[19],[20],[21],[22],[23] Similarly, randomized trials have demonstrated an improvement in performance of health workers after supportive supervision.[24],[25] Supportive supervision though effective is resource intensive often requiring travel and per-diem cost of supervisors, and dedicated staff. Our study envisages enhancing skills and knowledge through supportive supervision on an ongoing basis, done remotely by leveraging technology as a promising alternative. Remote supportive supervision is a cost-effective way, to reach the unreached, utilizing quality resource persons (referred here as “Mentors for Nutrition”). Moreover, remote support is the only substitute when physical field visit was not feasible during the pandemic.

Overall, districts with increased knowledge score of AWS had a lower prevalence of SAM. A higher burden of SAM in Tinsukia and Morigaon could possibly be due to lower level of knowledge of AWS in these districts. However, AWS in districts like Barpeta, Golaghat, Sonitpur have above average IYCF knowledge. But they still report a high burden of SAM which could possibly be due to better monitoring, and reporting by AWS leading to higher count of reported SAM cases.

COVID-19 derailed the health service delivery, and to maintain the capacity of health system, frontline workers were hauled. Advisory was issued by the Ministry of Women and Child Development to utilize AWWs and supervisors in community surveillance of COVID-19.[13] Involvement of these workers in vaccination drive further increased their workload as evident from our qualitative analysis. Increased responsibilities of AWWs may reduce their service quality and performance. Hence, clearly defined roles making them accountable for nutritional service delivery should be set along with time-bound task incentive.

Even though procurement of hot cooked meal has been decentralized through AWC management committee, few supervisors expressed logistic issues. Empowering these supervisors in decision-making along with active community engagement for utilization of locally available foods could positively affect the service delivery chain loopholes. Another key challenge evident from the qualitative study was shortage of manpower and accessibility. This can be addressed by rational distribution of manpower at district level and locally tailored strategies depending on expected frequency of service delivery, topography, and accessibility. In Assam, special focus should be given to tea garden and riverine (char) areas as these areas have a high prevalence of SAM and are socially, economically marginalized. The “char/chapori” areas detached from the mainland are riverine islands which remain inaccessible unless transport facilities are made available. These areas often face the brunt of flood and land erosion forcing inhabitants to shift to temporary settlements. This accentuates the need for remote supportive supervision to alleviate the lack of manpower on coverage of health services. Further studies can focus on hybrid mode of supportive supervision for service providers and in-depth interview of beneficiaries in low-performing districts.


   Conclusion Top


Implementation of remote supportive supervision was found effective in improving knowledge of AWS. Documented role of quality supportive supervision by faculties from medical colleges in the present study can boost the motivation of workers with a zeal to improve the nutrition scenario further. Investment in remote supportive supervision could aid in augmenting nutritional service delivery in a cost-effective way. Intersectoral convergence and stakeholder engagement are necessary to address bottlenecks in nutrition service delivery.

Acknowledgment

We would like to acknowledge the support of UNICEF Assam, especially Dr. Shweta Sharma, Nutrition Specialist, UNICEF, Assam, and all the faculty “Mentors of Nutrition” from different medical colleges of the state supporting our study.

Financial support and sponsorship

This study was financially supported by UNICEF, Assam.

Conflicts of interest

There are no conflicts of interest.



 
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