Introduction
Women community health workers (CHWs) are instrumental in improving maternal and neonatal health indicators in conservative regions like Pakistan and South Asia where the mobility of women is restricted due to cultural and religious interpretations and women are dependent on health services at the doorstep (Gilmore and McAuliffe, Reference Gilmore and Mcauliffe2013). The additional and essential role that CHWs are expected to perform during the coronavirus pandemic is creating awareness and ensuring prevention for infection control in underprivileged and semi-literate communities (Bhaumik et al., Reference Bhaumik, Moola, Tyagi, Nambiar and Kakoti2020). Recent scholarship highlights that there is greater vulnerability to mothers and newborns during pandemics in South Asia and other developing countries and also greater risk of still-births (McClure et al., Reference Mcclure, Kinney, Leisher, Nam, Quigley, Storey, Christou and Blencowe2020).
Doorstep services in the community during pandemics are not just essential for reproductive health services but also for the protection of mother, newborn and entire families through guidance about both infection control and coronavirus symptom management (Webber and Chirangi, Reference Webber and Chirangi2020). In Pakistan, women CHWs play a critical role in facilitating access to primary healthcare for women, and in addition, they are the only healthcare support for majority of impoverished women in the country (Shaikh and Hatcher, Reference Shaikh and Hatcher2005). The Pakistan Ministry of National Health Services Regulation and Coordination launched the National Programme for Family Planning and Primary Health Care, commonly referred to as the Lady Health Workers (LHWs) Program, in 1994. This program has successfully deployed more than 110 000 CHWs across disadvantaged communities of the country (Farooq and Arif, Reference Farooq and Arif2014).
After recruitment, CHWs receive 15 months of training and are designated to visit 1,500 women in the community to provide antenatal, natal and postnatal services (Hafeez et al., Reference Hafeez, Mohamud, Shiekh, Shah and Jooma2011). They are also responsible for referral to nearby health facilities and provision of health education, including infection control and prevention (Douthwaite and Ward, Reference Douthwaite and Ward2005). However, CHWs in Pakistan are known to face considerable challenges while delivering services, mainly that of low pay and community resistance in accepting services from non-traditional agents (Haq et al., Reference Haq, Iqbal and Rahman2008; Closser and Jooma, Reference Closser and Jooma2013). Another issue is the low-quality training they receive at induction and the drop in their knowledge and skill set due to non-existence of a regular training system (Oxford Policy Management, 2009; Jalal, Reference Jalal2011).
Despite the challenges they face, evidence shows that CHWs have been effective in some indicators for maternal and neonatal health, such as increasing tetanus coverage, immunization, attended deliveries and exclusive breastfeeding (Jalal, Reference Jalal2011). With regard to areas related to infection control, CHWs have also been evidenced to improve women’s awareness and practices in sterilizing drinking water and improving hygiene (Rabbani et al., Reference Rabbani, Perveen, Aftab, Zahidie, Sangrasi and Qazi2016a). In the age of coronavirus, the impact of CHWs services assumes greater significance with regard to educating mothers in the community about coronavirus prevention and management.
After the 18th constitutional amendment in 2011, the subject of health was devolved to provinces. In 2013, the provincial government of Punjab integrated the LHWs program with three other programs: (i) The MNCH (Maternal Neonate Child Health); (ii) Nutrition enhancement; and (iii) The Basic EmONC (Emergency Obstetric Care) program. This new integrated system is called the Integrated Reproductive Maternal Neonatal Child Health (IRMNCH & NP) Programme (Nishtar, Reference Nishtar2011). In Punjab, 78% of rural and 30% of the urban population is covered by CHWs across the 36 districts of the province (Oxford Policy Management, 2009). Post the spread of the coronavirus pandemic in the country, there have been guidelines issued by The Primary and Secondary Healthcare Department (Punjab Government, 2020). However, the major limitation is that no formal training has been carried out, and only guidelines for prevention, sanitation and symptom management have been distributed through booklets to CHWs. There has been no investigation about the efficacy and limitations of these guidelines, additional needs for preparedness and response, or the quality of primary healthcare services for maternal and newborn health during the pandemic.
Study aims
The perceived satisfaction of CHWs in delivering maternal and neonatal health services is an important indicator of mother and newborn wellbeing (Wilford et al., Reference Wilford, Phakathi, Haskins, Jama, Mntambo and Horwood2018). In the absence of sufficient research during the coronavirus pandemic (Singhal, Reference Singhal2020), it is important for independent researchers to help in filling the gaps about how maternal and neonatal health services are influenced by coronavirus preparedness and responsiveness in CHWs. At first step, we aimed to identify the lower odds for CHWs’ perceived satisfaction for maternal and neonatal health services, with respect to four areas: (1) socio-demographic characteristics; (2) coronavirus preparedness; (3) coronavirus responsiveness; and (4) employee satisfaction.
Local literature highlights that CHWs face considerable occupational challenges (Hafeez et al., Reference Hafeez, Mohamud, Shiekh, Shah and Jooma2011) and that their service response and employee satisfaction may influence maternal and neonatal health services. Thus, at second step we aimed to investigate the interplay among study variables by performing structural equational modeling (SEM). In this way, the objective of our fifth and last research question was to examine (5) how coronavirus responsiveness and employee satisfaction, as mediating variables, influence the relationship between coronavirus preparedness (independent variable) and maternal and neonatal health services (dependent variable). We believe our study is important not just for healthcare practitioners with weak bargaining power and inadequate governance voice in South Asia and other developing countries (Iacobucci, Reference Iacobucci2020) but also for the poor women dependent on primary healthcare services in low-income communities (Hick and Biddinger, Reference Hick and Biddinger2020). Overall, the findings of our study will be useful for the planning of primary health services delivered by women CHWs across South Asia and other developing regions.
Methods
This study adopts a cross-sectional quantitative design. Ethics approval was taken from the Institutional Review Board, Forman Christian College University. A cover letter was provided to CHWs describing the study and informed consent was taken (Panter and Sterba, Reference Panter and Sterba2011). No names were taken from the respondents, and there was no risk to their safety. Respondents were assured that they could withdraw from the study at any point during the telephonic interview. No incentives were offered for participation in this study.
Sample
The selection criterion for this study was all currently working, government employed, CHWs called LHWs providing outreach services at the doorstep of the community. A total of 44 700 LHWs are deployed in the rural and urban slums of Punjab (Kayani et al., Reference Kayani, Khalid and Kanwal2016). The target sample for this study based on Taros sampling formulae and population of LHWs in Punjab was estimated at 327 (Tepping, Reference Tepping1968).
Measures
The survey included questions from three standardized tools and consisted of 58 items. There were 6 questions addressing socio-demographic characteristics of respondents (Appendix A).
Coronavirus preparedness and responsiveness
Coronavirus preparedness and responsiveness was measured using 27 questions from the Zika Outbreak Emergency Preparedness and Response Survey (Rajiah et al., Reference Rajiah, Maharajan, Yin, Yee, Lin and Kean2019). This survey includes items from a checklist developed by The Center for Disease Control and Prevention and World Health Organization, which assesses how prepared healthcare professionals are for a pandemic outbreak. Minor modifications for relevancy to coronavirus were made. A five-point Likert scale was used ranging from ‘strongly disagree’ to ‘strongly agree’. A sample item for measuring coronavirus preparedness was ‘I know all the information about coronavirus preparedness related to my community needs’, and a sample item for coronavirus responsiveness was ‘I can manage the common symptoms and reactions of coronavirus’.
Employee satisfaction
Employee satisfaction was measured using 13 questions from the Community Health Worker Employer Survey (Chaidez et al., Reference Chaidez, Palmer-Wackerly and Trout2018). A five-point Likert scale was used ranging from ‘strongly disagree’ to ‘strongly agree’. This measure took into consideration employee support from coworkers and supervisors, and satisfaction with regard to workload, pay and contractual benefits. Items included statements like ‘My supervisor/team leader treats me with respect’ and ‘My workload is reasonable’.
CHW satisfaction with maternal and neonatal health services delivered
CHW satisfaction with maternal and neonatal health services delivered was measured using the Self-reported Performance of maternal and child health Workers-Nepal scale (Chhetry et al., Reference Chhetry, Clapham and Basnett2005). The measure included 12 items related to satisfaction with antenatal care, postnatal care, emergency care, birthing care and newborn care. A five-point Likert scale was used ranging from ‘strongly disagree’ to ‘strongly agree’. The measure included items like ‘I am satisfied with delivery of services for prior referrals for birth care’ and ‘I am satisfied with delivery of services for birth complications managed and/or referred’.
Data collection
We requested a list of mobile contact numbers of CHWs from the IRMNCH & NP, Punjab, and were able to gain access to a list of 1,000 numbers. The authors of the study recruited and trained 12 women research assistants for the data collection, during a two-week period through zoom video sessions. The research assistants were University students of Psychology experienced in data collection. The data were collected during the months of May 2020 to June 2020, using telephonic survey method, to observe physical distancing and safety during the coronavirus pandemic. Initially, we text-messaged the entire contact list informing CHWs of the research objectives, and seeking their permission for participation in the study (Delice and Practice, Reference Delice2010). We followed up with one text message when we did not receive a reply. A total of 373 CHWs replied and gave consent to be interviewed, and we were finally able to collect complete data from 350 women, making the final response rate for this study 35%. The responding CHWs belonged to 35 of the 36 districts of the province, divided into North and South Punjab (Appendix B).
Data analysis
We used SPSS 21.0 for analysis of descriptive statistics and bivariate regression. The independent variables for the study include ‘coronavirus preparedness’, ‘coronavirus responsiveness’ and ‘employee satisfaction’, and the dependent variable for the study was ‘satisfaction with maternal and neonatal health services’. Reliability statistics for the scales in the study show good reliability above values of 0.71 (Terwee et al., Reference Terwee, Bot, De Boer, Van Der Windt, Knol, Dekker, Bouter and De Vet2007). The overall internal consistency ranged from 0.764 to 0.878 (Table 1). At first step, descriptive statistics were derived. Then, study variables were compounded to assess association between variables, and linear regression was calculated in order to ascertain the direction of relationship.
Table 1. Reliability statistics for study domains
Next, we calculated bivariate odds regression, by recoding study variables into binary categories. We created dummy variables with ‘0’ representing low odds of satisfaction and ‘1’ representing higher odds of satisfaction. Significance of the main effects was estimated by computing the confidence levels. P-values of less than 0.05 were considered significant for this study. For adjusted odds ratios (AOR), age and serving years, as continuous variables, were held constant. In the third phase of our analysis, the complex relationships among variables, as well as their determinants, were calculated along with the parameter estimates of the structural model using a path diagram. The authors used AMOS software (version 17.0) for SEM analysis (Byrne, Reference Byrne2001) and entered coronavirus preparedness as the independent variable and satisfaction for maternal and neonatal health services as the dependent variable. Coronavirus responsiveness and employee satisfaction were entered as mediating variables. We opted for maximum likelihood estimation method and performed the bootstrapping on 2000 samples with 90 percent confidence intervals.
Results
Descriptive statistics
From a sample of 350 women, majority at 71.1% belonged to North Punjab and were between the ages of 40–59 years. Most CHWs have a secondary (74.0%) or intermediate level degrees (17.4%), and majority had been serving between 1–9 years. Most CHWs are married at 84.3% and have less than 3 children, at 64.6% (Table 2).
Table 2. Socio-demographic characteristics of sample, n = 350
Correlation and linear results
Table 3 presents the mean and standard deviations of study variables and the Pearson correlation results. All study variables have significant Pearson’s correlation associations, above cutoff values of 0.300 (Schober et al., Reference Schober, Boer and Schwarte2018), ranging from 0.304 to 0.768. Linear regression results showed that maternal and neonatal health satisfaction is positively associated with independent variables of (i) coronavirus preparedness (R 2 = 0. 128); (ii) coronavirus responsiveness (R 2 = 0.122); and (iii) employee satisfaction (R 2 = 0. 115).
Table 3. Pearson’s correlation results for study domain variables
** P value < 0.005.
Socio-demographic regression results
In Table 4, we present the results for higher odds of CHWs’ satisfaction for maternal health services and neonatal health services with respect to socio-demographic characteristics. We found no significant associations.
Table 4. Bivariate regression results for lower odds of CHWs’ satisfaction for maternal health services and neonatal care services, with respect to socio-demographic characteristics
*For adjusted odds ratio calculation, age and service years, as continuous variables, have been kept constant.
Coronavirus preparedness regression results
With regard to results for adjusted odds ratio results for coronavirus preparedness (Table 5), we find that CHWs have lower odds of satisfaction with maternal and neonatal health services when they (i) do not have all the information about coronavirus preparedness related to community needs (AOR: 8.20; 95% CI 3.09–13.74); (ii) do not know how to advise about distancing to minimize risks of community exposure (AOR: 5.33; 95% CI 1.16–9.56); (iii) do not have access to journal articles related to coronavirus preparedness (AOR: 5.31; 95% CI 2.84–9.90); (iv) do not know about decontamination procedures (AOR: 5.20; 95% CI 1.10–9.51); (v) are not familiar with the local emergency response for coronavirus (AOR: 3.70; 95% CI 1.82–7.53); (vi) are not prepared for the management of coronavirus (AOR: 3.68; 95% CI 1.97–6.87); (vii) do not have sufficient support from local officials in an emergency (AOR: 3.38; 95% CI 1.54–7.40); (viii) are not considered key leaders in the community in coronavirus outbreak (AOR: 2.98; 95% CI 1.65–5.39); (ix) do not have awareness of the programs about CP and management offered by the government (AOR: 2.69; 95% CI 1.47–4.93); (x) do not know who to contact from chain of command in disaster situations (AOR: 2.19; 95% CI 1.13–4.21); and (xi) have not participated in emergency planning for coronavirus situations (AOR: 1.78; 95% CI 1.03–3.10).
Table 5. Bivariate regression results for lower odds of CHWs’ satisfaction for maternal health services and neonatal care services, with respect to coronavirus preparedness (CP)
*For adjusted odds ratio calculation, age and service years, as continuous variables, have been kept constant.
Coronavirus responsiveness regression results
Adjusted odds ratio results for coronavirus responsiveness (Table 6) show that CHWs have lower odds of satisfaction with maternal and neonatal health services when they (i) are not familiar with the scope of their role in coronavirus (AOR: 5.60; 95% CI 2.14–9.65); (ii) are not confident in their abilities in coronavirus as a member of a healthcare team (AOR: 5.16; 95% CI 2.51–7.62); (iii) are not confident in their abilities as a direct care provider or first responder in coronavirus (AOR: 2.85; 95% CI 1.49–5.45); (iv) cannot manage the common symptoms and reactions of coronavirus (AOR: 2.51; 95% CI 1.45–4.34); (v) are not confident implementing plans for social distancing, infection control, hygiene literacy, & similar functions (AOR: 2.45; 95% CI 1.10–5.47); (vi) cannot identify possible indicators of mass exposure evidenced by a clustering of patients with similar symptoms (AOR: 2.79; 95% CI 1.39–5.57); (vii) as healthcare practitioners, do not feel confident as a manager or coordinator of a community exposed to coronavirus (AOR: 3.14; 95% CI 1.44–6.83); (viii) are not provided opportunities to participate in peer evaluation of skills and governance planning on coronavirus (AOR: 3.50; 95% CI 1.49–8.23); and (ix) are not accepted as a legitimate authority for coronavirus awareness/prevention in the community (AOR: 3.43; 95% CI 1.91–6.15).
Table 6. Bivariate regression results for lower odds of CHWs’ satisfaction for maternal health services and neonatal care services, with respect to coronavirus responsiveness
*For adjusted odds ratio calculation, age and service years, as continuous variables, have been kept constant.
Employee satisfaction regression results
Adjusted odds ratio results for employee satisfaction (Table 7) show that CHWs have lower odds of satisfaction with maternal and neonatal health services when (i) working relationship with coworkers is not good (AOR: 11.59; 95% CI 3.55–18.78); (ii) supervisors do not treat them with respect (AOR: 7.94; 95% CI 2.30–14.38); (iii) they do not believe their profession is a good place to work (AOR: 5.97; 95% CI 2.17–8.39); (iv) communication between senior leadership and employees is not good (AOR: 5.00; 95% CI 2.39–8.48); (v) supervisors do not work well with employees of different backgrounds (AOR: 4.42; 95% CI 1.42–8.72); (vi) they are not provided opportunities to demonstrate their leadership by supervisor (AOR: 3.63; 95% CI 1.82–7.21); (vii) supervisors do not support employee development (AOR: 3.49; 95% CI 1.66–7.33); (viii) supervisor do not support balance in work and family issues (AOR: 2.96; 95% CI 1.69–5.19); (ix) job security and contract is not satisfactory (AOR: 2.49; 95% CI 1.46–4.26); and (x) they cannot learn from coworkers as they do their work (AOR: 1.99; 95% CI 1.01–3.94).
Table 7. Bivariate regression results for lower odds of CHWs’ satisfaction for maternal health services and neonatal care services, with respect to employee satisfaction
*For adjusted odds ratio calculation, age and service years, as continuous variables, have been kept constant.
Structural equation model
Our SEM results for model fit, presented in Table 8, show that all fit indices are within the acceptable limit: [GFI = .998; AGFI = .977; CFI = .999; TLI = .993; RMSEA = .042].
Table 8. Model fit indices for SEM
Results presented in Table 9 show that coronavirus preparedness has a direct effect on maternal and neonatal health service satisfaction (β = .242, P < .001) and an indirect effect on maternal health satisfaction (β = .242, P < .001) via the mediation of employee satisfaction. Coronavirus responsiveness does not have any direct effect on maternal and neonatal health service satisfaction, whereas coronavirus responsiveness has an indirect effect on maternal and neonatal health service satisfaction (β = .113, P < .001) via the mediation of employee satisfaction. Coronavirus preparedness has a direct effect (β = .173, P < .001) and also an indirect effect (β = .405, P < .001) on employee satisfaction via the mediation of coronavirus responsiveness. SEM results are summarized in Figure 1.
Table 9. Direct and indirect effects of independent and mediating variables on maternal and neonatal health service satisfaction (M&NHSS)
***P values are significant at < .001.
Figure 1. The structural path model for study variables.
Discussion
Our study variables show linear association, providing evidence that when coronavirus preparedness, coronavirus responsiveness and employee satisfaction are high, CHWs perceive their delivery of maternal and neonatal services to be better. Bivariate regression results addressing our four research questions imply considerable policy improvement is needed for CHWs with regard to preparedness and response for infection control and general employee support. Our first research question examined a relationship between socio-demographic variables and lower odds of satisfaction with maternal and neonatal services. The results of the data analysis revealed no significant associations.
The second research question tested the relationship between coronavirus preparedness and lower odds of satisfaction with maternal and neonatal services. We found that CHWs have lower odds of satisfaction when they lack information and education and training programs by the government. Specifically, CHWs have lower satisfaction when they are not trained about how to guide mothers about physical distancing, decontamination and disinfection procedures. There is also lower satisfaction when there is inadequate support from local officials and lack of information about local emergency response and who to contact during emergencies. Other research confirms that maternal health indicators show improvement when the state invests in the training and skill development of primary healthcare workers (Scott et al., Reference Scott, Beckham, Gross, Pariyo, Rao, Cometto and Perry2018). Coordination and collaboration with cross-sector partners in the community is vital for emergency response and effective service delivery (Ransom et al., Reference Ransom, Goodman and Moulton2008). Additionally, information sharing about local health teams and effective communication between health teams is needed for optimal delivery of services by CHWs. We also found that lower probability of satisfaction is associated with CHWs’ lack of acceptance as key leaders by the community. Local research suggests that CHWs face considerable resistance in certain communities due to patriarchal and traditional forces which prefer local healers (Jafree et al., Reference Jafree, Zakar and Anwar2020).
The third research question examined the relationship between coronavirus responsiveness and lower odds of satisfaction with maternal and neonatal services. Findings revealed that CHWs have lower odds of satisfaction when they are not confident about their exact role and abilities to identify patients and manage coronavirus in the community. Other research confirms that CHWs need formal training about their roles and responsibilities for coronavirus management (Ajisegiri et al., Reference Ajisegiri, Odusanya and Joshi2020). We also found that lower probabilities for satisfaction were linked with specific problems related to management of symptoms, implementing social distancing, infection spread and hygiene literacy. Unless CHWs have training for coronavirus symptom management and infection control, there is greater risk of disease spread in disadvantaged communities (Perry et al., Reference Perry, Zulliger and Rogers2014). We also found that the odds of satisfaction were low when CHWs are not provided opportunities to participate in peer evaluation of skills and governance planning for coronavirus. Other scholarship highlights that when CHWs participate in peer evaluation and governance, there is improved service quality for maternal and child health in the primary health sector (Kaplan et al., Reference Kaplan, Dominis, Palen and Quain2013).
The fourth research question examined the relationship between employee satisfaction and lower odds of satisfaction with maternal and neonatal services. Results reveal that CHWs have lower odds of satisfaction when they do not have a good working relationship with their coworkers and are unable to learn from each other. Prior research has reported that coworkers can assist in supporting CHWs in dealing suitably with local issues and improving services (Sharma et al., Reference Sharma, Webster and Bhattacharyya2014). Satisfaction is also low when supervisors are disrespectful, communication is inadequate, skill development and leadership is not supported, and work-family balance is not reinforced. Other scholarship confirms that supervisor support is essential for CHW service quality, employee outcomes and stability in family and work equation (Jaskiewicz and Tulenko, Reference Jaskiewicz and Tulenko2012). Lastly, we found that the odds of satisfaction are low when there is job insecurity and the employment contract is inadequate. Local research shows that there is need for CHWs contracts to be improved with regard to matching income with inflation and improving their career path and professional advancement (Haq et al., Reference Haq, Iqbal and Rahman2008).
With regard to our fifth research question, examining if coronavirus responsiveness and employee satisfaction as mediating variables influence the relationship between coronavirus preparedness and maternal and neonatal health service, we are able to conclude two important things. First, coronavirus preparedness has a significant effect on maternal and neonatal health services, and this relationship is mediated significantly by employee satisfaction. Coronavirus preparedness also has a direct effect and indirect effect on employee satisfaction via the mediation of coronavirus responsiveness. We may derive that even when CHWs are prepared for infection control and management, their response may not be optimal, unless they have organizational, supervisor and coworker support (Jaskiewicz and Tulenko, Reference Jaskiewicz and Tulenko2012; Rabbani et al., Reference Rabbani, Shipton, Aftab, Sangrasi, Perveen and Zahidie2016b; Cometto et al., Reference Cometto, Ford, Pfaffman-Zambruni, Akl, Lehmann, Mcpake, Ballard, Kok, Najafizada and Olaniran2018). Second, we found that coronavirus responsiveness has an indirect effect on maternal and neonatal health services via the mediation of employee satisfaction. The results confirm that employee satisfaction is a key factor in securing delivery services during emergency and crisis situations in the community, including pandemics (Zhang et al., Reference Zhang, Yang, Wang, Gillespie, Clarke and Yan2016).
Limitations of study
The limitations of this research include the cross-sectional design and the inability to sample more provinces. However, Punjab comprises 60% of the Pakistani population and has greater CHW deployment compared to other provinces in the country, thus lending strength to our study in terms of representation (Oxford Policy Management, 2009). There is also the limitation of this being a perception-based study and the biases inherent in healthcare provider response, with respect to delivery of services and employer support. For future studies, we recommend interviews with CHW supervisors and women availing services from CHWs. However, overall the findings of this research have value in providing recommendations and impetus for improving: (i) primary-level maternal and neonatal healthcare services for women of Pakistan; (ii) service quality, training and employee support of CHWs; and (iii) coronavirus preparedness and response protocols for CHWs.
Though this research is relevant for the coronavirus pandemic, it also holds value as a contribution for research-based recommendations for future pandemics and infection management in community settings. In addition, the findings have relevancy for other developing countries planning a CHW program to support disadvantaged women with primary health services. Stemming from the findings of this study, a randomized controlled trial for digital healthcare services for women in communities is being conducted by the first author of this study. Future researchers might want to plan mixed methods research and case studies to better recommend policy improvement for the primary health sector in developing regions.
Concluding recommendations
CHWs can play a critical role in controlling infection and also protecting mothers and newborn during pandemics. Pakistan is lucky to have an existing CHW program across the country, which is managed by The Ministry of National Health Services Regulation and Coordination and the provincial health bodies responsible for community health services. The findings of our study enable us to inform about the needs of CHWs in delivering optimal services for maternal and neonatal health during pandemics. Our recommendations are beneficial for South Asia and other developing regions planning community health services for maternal and neonatal health for disadvantaged women during pandemics. We conclude with four key areas for support to improve maternal and neonatal health services by CHWs during times of pandemics, described below and summarized in Table 10:
(1) Education and Training – it is critically needed to improve skill sets for management of coronavirus in the community, identification of mass exposure and development of confidence levels in CHWs as pandemic coordinators. There is also need to provide access to understandable academic material and recent scholarship related to pandemic management and infection material in CHWs who are mostly secondary school graduates and are not highly educated;
(2) Operational Support – it is needed to provide clear guidelines for roles and responsibilities during pandemics and for the introduction of routine practice for pandemic management. We also recommend the formation of and regular participation in committees for emergency response and infection control and regular meetings with local officials and CHW teams for improved coordination and pandemic response;
(3) Public Acceptance – it is essential that there is community acceptance of CHWs as legitimate authorities and key leaders for infection control for the effectiveness of service delivery. This is possible through social media and community awareness drives by established community notables like religious leaders, elected political leaders and older and trusted male populations within the local districts; and
(4) Employee Support and Benefits – we recommend consistent accountability measures of supervisors to prevent disrespect, bullying and discrimination. There is also need for increased communication and team-building initiatives with coworkers in the primary healthcare sector, such as the medical officer in charge, lady health visitor, vaccinators, community midwives, traditional birth attendants, medical technicians and dispensers, district health officer and lady health supervisor. Opportunities for employee development and leadership are also needed, along with support for work-family balance in order to make service delivery more optimal. Finally, there is need for reforms with regard to job stability and career progression.
Table 10. Summary recommendations to help improve maternal and neonatal health services of CHWs during pandemics
Supplementary material
To view supplementary material for this article, please visit https://doi.org/10.1017/S1463423622000081
Acknowledgements
We thank all the busy community healthcare worker respondents for their willingness to participate in this study and giving their generous time. Our deepest gratitude to our hardworking and committed research assistants who assisted us in data collection: Fatima Zeeshan, Maham Salah ud Din, Uzma Parveen, Ayesha Afzal, Bushra Zafar, Hamna Aftab, Shireen Imran, Iffah Khan, Faroza Islam and Rabia Chaudary. We would also like to acknowledge Amna Maryum and Zara Ali Shah for their support in coding and data preparation for transfer from Excel to SPSS.
Authors’ contributions
S.R.J. has drafted the project, collected the data, analyzed it and prepared the manuscript. A.U.M. and A.K. assisted in data collection. Q.K.M. assisted in data analysis. All authors approved the final manuscript.
Financial support
This research received no specific grant from any funding agency, commercial or not-for-profit sectors.
Conflict of interest
None.
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