Home About us Editorial board Ahead of print Current issue Search Archives Submit article Instructions Subscribe Contacts Login 
  • Users Online: 456
  • Home
  • Print this page
  • Email this page
Cover page of the Journal of Health Sciences


 
 Table of Contents  
ORIGINAL ARTICLE
Year : 2020  |  Volume : 13  |  Issue : 2  |  Page : 98-104

Audio-visual training intervention improves knowledge, skill, confidence, and performance of barefoot nurses for screening noncommunicable disease


Department of Health and Family, Senior Medical Officer, District Hospital, Vijaypura, Bengaluru, Karnataka, India

Date of Submission26-Feb-2020
Date of Acceptance22-Apr-2020
Date of Web Publication23-Jun-2020

Correspondence Address:
Dr. Biswamitra Sahu
Indian Institute of Public Health, Public Health Foundation of India, Magadi Road, First Cross, State Institute of Health and Family Welfare Premises, Bengaluru, Karnataka
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/kleuhsj.kleuhsj_47_20

Rights and Permissions
  Abstract 


CONTEXT: In India, the primary health system is inadequate to screen noncommunicable diseases (NCDs) at a population level due to sub-centers being short-staffed and underequipped. Training barefoot nurses (BFNs) to screen NCD is an important strategy of task shifting. Again, there is paucity of studies exploring the effectiveness of training program using technology for training BFNs in the screening of NCDs.
AIMS: The aim of the study was to assess the effectiveness of audio-visual-based training to improve knowledge, skill, confidence, and performance (number screened and completeness of data entry) of BFNs to strengthen NCD screening.
SETTINGS AND DESIGN: This study was conducted at Doddaballapura taluk of Bengaluru rural district, India. A mixed-method research design was employed to assess the effectiveness of an audio-visual module for training BFNs.
SUBJECTS AND METHODS: Descriptive analysis was conducted to test the effectiveness of intervention in pre- and post-intervention period. A focus group discussion was conducted to explore the facilitators and barriers to the intervention.
STATISTICAL ANALYSIS USED: Statistical analysis was performed using mean knowledge score (MKS) and two-tailed t-test. Descriptive analysis was done using simple percentages.
RESULTS: The MKS of BFN improved across all the six components by 15% after the introduction of the video intervention. This improvement in MKS was statistically significant. The qualitative analysis testifies the improvement in skillsets, namely, finger pricking, swab placement, blood specimen collection, and waste disposal. In addition, the BFNs experience heightened confidence in conducting these procedures. The performance of BFNs has improved the number of screening and data entry into mobile apps.
CONCLUSIONS: The findings from this study suggest that audio-visual-based training of BFNs improves their knowledge, skill, confidence, and performance during the screening of NCDs. This evidence has relevance for the Indian public health system, which is struggling due to short-staffing, and is a value addition for training BFNs.

Keywords: Audio-visual videos, barefoot nurse, community health worker, performance, training


How to cite this article:
Timmapur SM, Sahu B, Sathyanarayana T, Pai AG. Audio-visual training intervention improves knowledge, skill, confidence, and performance of barefoot nurses for screening noncommunicable disease. Indian J Health Sci Biomed Res 2020;13:98-104

How to cite this URL:
Timmapur SM, Sahu B, Sathyanarayana T, Pai AG. Audio-visual training intervention improves knowledge, skill, confidence, and performance of barefoot nurses for screening noncommunicable disease. Indian J Health Sci Biomed Res [serial online] 2020 [cited 2020 Aug 11];13:98-104. Available from: http://www.ijournalhs.org/text.asp?2020/13/2/98/287421




  Introduction Top


Noncommunicable diseases (NCDs) account for 63% of all deaths in India[1] in 2018. The importance of screening NCDs and seeking treatment at the primary level is greatly stressed in order to avert deaths due to NCDs.[2] However, the primary health system is inadequate to meet the population-level screening need of NCD due to short-staffing[3] and underequipped subcenters, which does not attract many for opportunistic screening of NCDs in rural[4] and urban India.[5] In addition, the entry and update of data is completely missing at several urban health facilities. Importantly, the access to these public health facilities also involves cost and inconvenience experienced by health seekers.[5],[6] As part of the Karnataka NCD control program, the auxiliary nurse midwife is assigned the task of screening NCD at the health facility. However, this provision is not helpful in addressing the cost and convenience barriers faced by people to seek health care at the public health facility.

Community health workers (CHWs) are recognized by the World Health Organization as potential candidates for task shifting,[7] who can play a key role in delivering health services in resource-deficit areas experiencing access troubles. The spotlight is on CHWs who are championed as the solution to many health challenges that are being faced in low- and middle-income countries (LMIC). There is enough evidence that reiterates the potential of technology, mobile-based services (mHealth), for improving the delivery of health services by CHWs in LMICs.[8] Evidence also suggests that mobile technology has been found to be beneficial as a job aide, clinical decision support tools, and for data submission and instant feedback on performance.[9]

Study context

The health innovation unit (HIU) of the Public Health Foundation of India has developed the barefoot nurse (BFN) model and is responsible for recruiting the BFNs. The model is embedded in a sustainability framework where the BFNs do not get paid by the HIU. They are trained by the HIU, and HIU facilitates the distribution of one kit per BFN. The kit consists of all the screening instruments. The kit is donated by a local philanthropic organization where the BFN project is being implemented. The BFN earns livelihood by screening willing people in the community who are charged a nominal fee for the services provided by BFN and also for purchasing the consumables (glucose strips, urine protein strips, lancets etc.). Some BFNs are working full time and others are part-time workers.

CHWs, hereafter called as BFNs, are currently working in Doddaballapura block of Bengaluru rural district in India. They have been screening NCDs at the doorstep and charging a nominal amount to create livelihood option and to run the entire project on a self-sustainable manner.

Training barefoot nurses

The traditional face-to-face training poses some challenges for BFNs in getting trained because of accessibility issues such as cost, travel, and convenience. In such context, e-learning modules are ideal for catering to the training needs of BFNs. In addition, there is evidence that a blended module, a mix of face-to-face training and e-learning module, could ensure effective training with significant saving in cost, travel, classroom time, and trainers.[10]

The current article seeks to assess the effectiveness of audio-visual-based training to improve the knowledge, skills, confidence, and performance (number screened, completeness of data entry) of CHW, named BFN here, to strengthen NCD screening in Doddaballapura taluk of Bengaluru rural district.


  Subjects and Methods Top


Study site

The data collection was conducted in Doddaballapura taluk of Bengaluru rural district where the ongoing BFN intervention is operating since April 2019. The BFN project trains local community women by screening willing community members for five disease conditions. This study was conducted over a period of 3 months (July–September 2019). This study was conducted among 19 barefoot community health nurses.

Selection criteria for recruiting barefoot nurse

The BFNs are selected with certain set criteria, such as,

  • Ideally a woman aged between 25 and 45 years
  • Willing to work
  • Hailing from an area neighboring the intervention
  • Should have completed 10–12 years of education
  • Possess minimal digital literacy in order to be able to do data entry into a mobile app
  • Speaks the local language.


Design

A mixed-methods research design was employed in order to assess the effectiveness of an audio-visual module for training CHW. Descriptive analysis was conducted to test the effectiveness of intervention in pre- and post-intervention period. A focus group discussion was conducted to explore the facilitators and barriers to the implementation of the intervention.

Face-to-face training

The training of the BFN was first conducted through face-to-face sessions imparted over a period of 3 months (April–June) in Doddaballapura where medical professionals trained the BFNs regarding the protocol of screening five disease conditions. The 3-day training consisted of six sessions. These sessions consist of theory as well as practical demonstration of all the procedures. After appointment, there are refresher training sessions conducted every 3 months to maintaining the rigor of the skillset and improve efficiency at work. Second, short audio-video clips of 2–5 min were developed in the local language (Kannada) explaining the screening procedures. The content of these audio-video training clips includes device usage methods, device-setting techniques, data entry tips, and waste management tips.

Baseline assessment

Baseline data were collected using a preintervention questionnaire on the knowledge and skill information of the BFNs before the introduction of the video intervention. The standard preintervention questionnaire containing 36 questions including multiple-choice and dichotomous questions (true/false) was used to assess their knowledge of using devices for NCD screening, device-setting techniques, waste management, data entry, etc. The 36-item questionnaire included eight sections namely (1) BP measurement and knowledge about digital BP machine, (2) using the hemoglobinometer, (3) using the glucometer, (4) waste management, (5) measuring weight, (6) measuring height, (7) refractive error testing, and (8) urine analysis for protein. A total of six sessions were conducted. The repeat sessions were conducted every 3 months. The participants were given 1-h time to answer the preintervention questionnaire and an additional 15 min time to fill the general demographic information.

Intervention

Intervention development

The intervention, ten short videos, was developed by the first author, a trained medical doctor with 15 years of experience in practicing public health.

[Table 1] describes the duration of each video.
Table 1: Details and duration of video intervention

Click here to view


The script for the videos was developed by the researcher based on the technical guidelines of the Government of India, Ministry of Health and Family Welfare, and National Program for Prevention and Control of Cancer, Diabetes, Cardiovascular Disease and Stroke guidelines. The researcher with the help of two research staff then shot the ten videos on the following topics: training video for screening of hemoglobin, blood pressure (BP), blood sugar, height, weight, refractive error, urine protein analysis, preparation of spirit swab, waste disposal, and data entry. The editing of the videos was done by the first author. He scripted and did the voice-over in Kannada, the local language of Karnataka.

Intervention administration

The training videos were displayed to all the participants using an LCD projector over 4 × 6 screen. The training videos were then uploaded to the mobile phones of the BFNs. The videos were also uploaded on YouTube and shared on the BFNs' mobile phone (https://www.youtube.com/playlist?l ist=PLLTbJUiOHijz3PrQdEeO hEyBdr21Tz35K.) The participants were taught how to view the videos through YouTube link and asked all the participants to view the videos as per their need and requirement to improve their knowledge and skills. We have given them 1-week time for watching video clips.

Operationalization

The knowledge and skill level of the BFN was operationalized based on 36 questions, comprising of the following Eight set of questions: BP apparatus (six questions), hemoglobinometer (five questions), glucometer (four questions), waste management/disposal (five questions), weight measurement (four questions), height measurement (three questions), refraction test (five questions), and urine protein analysis (four questions). The same six set of questions were administered prior to the intervention and postintervention. The quality of the intervention or the ten videos was assessed using a 5-point Likert scale. The usefulness of the intervention was assessed using a 5-point Likert scale. The subsequent confidence boost of the BFNs due to the intervention was further assessed using a 5-point Likert scale answering 24 questions. BFN is a pilot project testing the feasibility of a preventive health delivery model. The modality of training is at two levels: face to face and video based. Hence, in the absence of a reference point to test the efficiency of the video-based training, the investigator has developed the questionnaire. The validity of the tool has not been done. The impact of the intervention was assessed through the number of screening that the BFNs did in the 1st and 2nd weeks postintervention. After 7 days (1 week), posttest was done.

The BFNs also participated in a focus group discussion spanning 40–45 min in order to understand the major enablers and barriers to the implementation of the audio-video training intervention.

Ethical consideration

The participants of this study consented to participate after having received orientation to the background of this study. They expressed their consent through voluntary written consent. Ethical approval was obtained from the institutional ethics committee of the Indian Institute of Public Health, Bangalore. All the identifying information was removed during analysis in order to maintain the anonymity of the participant.

Analysis

Descriptive analysis of the data was carried out using Statistical Package for the Social Sciences (IBM SPSS Statistica, Stanford, USA) version 23 for Windows. The analysis was conducted at three levels. First, the performance of BFNs as a function of the intervention was assessed. Second, the usefulness of the intervention for BFNs was assessed. Third, the perception of BFNs regarding the intervention was explored.


  Results Top


The participants of this study are aged between 19 and 36 years, with a median age of 29 years. The BFNs are primarily female (89.5%) followed by male (10.5%) participants. Majority of the BFNs had completed SSLC (36.8%), followed by 9 years of education (31.6%), PUC (10.5%), diploma (10.5%), and only one participant had Diploma in Medical Laboratory Technology (DMLT) and (GNM) General Nursing and Midwifery nursing background [Table 2].
Table 2: Socio-demographic profile of the participants of the study

Click here to view


There has been a substantial increase in the knowledge of BFNs postintervention where they have shown improvement spanning across all the six components of NCD screening. The details of the percentage increase in knowledge, operationalized based on 36 questions that were asked before and after intervention, are summarized in [Table 3].
Table 3: Percentage distribution of correct responses to the 36 knowledge based questions before and post intervention

Click here to view


The mean knowledge score (MKS) of BFNs in the preintervention phase was 28 (77.77%). However, the mean overall knowledge score increased to 33.63 (93.41%) during the postintervention assessment. In [Table 4], a two-tailed t-test suggests that improvement of MKSs postintervention is statistically significant (P = 0.000). This finding was corroborated by the response of BFN participants below who elaborated how the intervention helped them refine their knowledge and skillset. One participant clearly mentions that she was not able to follow the steps of conducting screening before she received the intervention, implying the usefulness of the audio-visual training.
Table 4: Improvement in BFN's knowledge, screening and completeness of mobile data entry post intervention using audio-visual training

Click here to view


“Before video training, I could not follow the steps of doing a test properly.”

Another participant is specifically indicating the improvement in knowledge around the finger that is to be pricked as follows:

“Now I learnt something new. e.g., before I used to prick any finger to get the blood sample. But after video training I came to know that we have to prick ring finger to take the blood sample.”

A BFN soon adds how her skill of placing swab has been incorporated in her practice as follows:

“Before I used to keep the cotton swab on the table/floor after cleaning the finger. But after video training I came to know that cotton swab should be kept in the palm.”

Another BFN outlines the details of blood sample collection:

“Before I used to take the first drop of blood for testing. Now I came to know that first drop of blood should be wiped away and second drop should be taken for testing.”

Waste disposal is another important topic that has improved as expressed by a BFN below:

“Before training I didn't know how to dispose the lancets and test strips properly. After video training I came to know the correct way of disposing.”

The potential of these videos as a refresher training is elaborated by another BFN:

“We have been given training for one day 3 months back. After that we did not have any training for refreshing our knowledge. These video training clips served as a readymade source of knowledge for us so that as when we have any doubts, we can easily refer to these video clips.”

A BFN lucidly explains how the learning of the skillset has improved due to the video training:

“The video is the most important and the most effective because we watched the video clip [of] what we did the first [time] and then saw our weak points and strong points then we repeated it again so we could see which part we improved…. we can see directly” “when we saw the video, we knew how we were doing and if we were missing something and the next time we try to correct [ourselves]………. Like I used to dispose the Glucostrips with my hand, and in that process sometimes my fingers used to contaminate with the person's blood sample.”

In addition, the confidence of the BFNs in performing all NCD screening has increased postintervention, with the response of BFNs primarily being that of “confident” and “very confident” on a 5-point Likert scale. The results indicate that there has been a substantial improvement in the knowledge of BFN postintervention. One BFN elaborates in her own words about the confidence which these video training has instilled in her to do screening as follows:

“After this session, I have more confidence because I came to know various new things which I did not know before this video training.”

The maximum knowledge score preintervention is 33 and postintervention is 36. There has not been any dropouts between the pre- and post-intervention period. As far as performance is concerned, the mean overall performance score in the postintervention phase increased to 69.42 from 53.37 in the preintervention phase. The increase in screening postintervention compared to the preintervention phase was found to be statistically significant (P = 0.019). The total beneficiaries screened increased from 1014 to 1319 in the postintervention phase.

Finally, the mean performance score of data entries made by all BFNs at preintervention decreased to 37.79 in the postintervention compared to an earlier assessment of 47.84 in the preintervention period. However, this decline in data entry was not statistically significant (P = 0.261). This finding is not congruent with the findings so far because there has been improvement in all other parameters, such as, knowledge, skill, confidence, and performance.


  Discussion Top


The health system in LMICs is struggling with deficit of health professional,[11] resulting in a huge workload for those working in such settings. Hence, screening and management of NCDs in Indian primary care is neglected due to shortage of human resource in the health sector. However, there is enough evidence to suggest that CHWs can play a key role in adverting NCDs.[12],[13] A multifaceted intervention using CHWs, a combination of training and supervision, addressing multiple determinants of performance, is recommended as it is more likely to yield better results.[14] There is a felt need for conducting good-quality mixed-method studies covering the effectiveness of training programs tailored for BFNs.[15] However, there is scarcity of studies that focus on harnessing technology for training CHWs.[16] Furthermore, the increased use of mobile phones in LMICs has opened new avenues for the use of technology by BFNs. Nevertheless, the use of technology for training CHWs is poorly understood.[17] Specifically, the evidence base of studies that explores the use of technology for training CHWs in NCDs is very low.[17]

Our study is an attempt to fill this gap and has generated evidence that demonstrate the effectiveness of audio-visual-based training intervention in improving the knowledge, skill, confidence, and performance of BFNs in screening NCDs. These BFNs had received face-to-face training; however, the video training has refined their skill sets, namely, preparation to screen NCDs, screening of NCDs, and disposal of waste. The most important advantage of such intervention is that these audio-video training content can be viewed several times, allowing these BFNs to refine their skillsets till complete understanding and rectification of mistake takes place.

Similar findings have been noted elsewhere, for instance, a peer training of CHW using videos among African-American women was found to be effective for heart health education.[18] An interactive distance learning program using video to train CHW in New Mexico resulted in significant improvement in knowledge, confidence, and attitude of CHW in providing care to patients with diabetes.[19] Use of video conferencing for case-based learning for mentoring CHWs is vouched to have scalability potential for other locations.[20] The training of CHWs using live and video conferencing was found to be effective in knowledge acquisition for child hearing health in Brazil.[21] Access to a preventive cancer detection program was improved by training lay CHWs using training videos.[22] However, the CHWs have relatively less formal education and training.[7] The training of CHWs needs standardization.[16] Using technology to train CHWs is an immense opportunity to bridge the health-care needs in LMICs.


  Conclusion and Recommendation Top


This mixed-method research conducted in the rural taluk of Doddaballapura, Bengaluru district, suggests that training of BFNs using audio-visual modality improves their knowledge, skill, confidence, and performance during the screening of NCDs. The qualitative data testify improvement in skillsets and heightened confidence in conducting these procedures. This study underlines the importance of training CHWs using audio-visual format. This study should be replicated in multiple study sites in order to address the problem of short-staffing by ensuring better trained CHWs for improving access for NCD screening in India.

Limitation

This study was conducted among BFNs in one location; hence, it is difficult to generalize the findings. Similar study exploring the effectiveness of audio-visual mode of training CHW in multiple locations and encompassing a bigger sample can help improve the generalizability of the intervention.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
World Health Organization. Country. NCD Country Profile. World Health Organization; 2018. p. 1. Available from: https://www.who.int/nmh/countries/2018/ind_en.pdf?ua=1. [Last accessed on 2019 Oct 16].  Back to cited text no. 1
    
2.
Seshadri SR, Hebbare V. Non-Communicable Diseases Screening and Treatment for Non-Communicable Diseases: The Case for Andhra Pradesh. Bangalore; 2018. Available from: https://www.copenhagenconsensus.com/publ ication/andhra-pradesh-priorities-non-communicable-diseases-seshadri. [Last accessed on 2019 Oct 14].  Back to cited text no. 2
    
3.
Ainapure K, Sumit K, Pattanshetty SM. A study on implementation of national programme for prevention and control of cancer, diabetes, cardiovascular diseases and stroke in Udupi district, Karnataka. Int J Community Med Public Health 2018;5:2384-7.  Back to cited text no. 3
    
4.
Das J, Mohpal A. Socioeconomic status and quality of care in rural India: New evidence from provider and household surveys. Health Aff 2016;35:1764-73. Available from: https://www.healthaffairs.org/doi/ful l/10.1377/hlthaff.2016.0558. [Last accessed on 2019 Oct 15].  Back to cited text no. 4
    
5.
Jayanna K, Bradley J, Mony P, Cunningham T, Washington M, Bhat S, et al. Effectiveness of onsite nurse mentoring in improving quality of institutional Births in the primary health centres of high priority districts of Karnataka, South India: A cluster randomized trial. PLoS One 2016;11:e0161957.  Back to cited text no. 5
    
6.
Basu P, Mahajan M, Patira N, Prasad S, Mogri S, Muwonge R, et al. A pilot study to evaluate home-based screening for the common non-communicable diseases by a dedicated cadre of community health workers in a rural setting in India. BMC Public Health 2019;19:1-12.  Back to cited text no. 6
    
7.
Sam S, Edirippullihe S, Steyn K, Gaziano T, Puoane T, Levitt N. Evaluating the use of mobile phone technology to enhance cardiovascular disease screening by community health workers. Int J Med Inf 2014;83:648-54.  Back to cited text no. 7
    
8.
Agarwal S, Perry HB, Long L, Labrique AB. Evidence on feasibility and effective use of mHealth strategies by frontline health workers in developing countries: Systematic review. Trop Med Int Health 2015;20:1003-14.  Back to cited text no. 8
    
9.
Karin K, Tibenderana JK, Chb MB, Akpogheneta OJ. Mobile health (mHealth) approaches and lessons for increased performance and retention of community health workers in low- and middle-income countries: A review. J Med Internet Res 2013;15:1-13.  Back to cited text no. 9
    
10.
Mastellos N, Tran T, Dharmayat K, Cecil E, Lee H, Wong CC, et al. Training community healthcare workers on the use of information and communication technologies: A randomised controlled trial of traditional versus blended learning in Malawi, Africa. BMC Med Educ 2018;18:1-13.  Back to cited text no. 10
    
11.
Campbell J, Dussault G, Buchan J, Pozo-Martin F, Arias MG, Leone C, et al. A Universal Truth: No Health Without a Workforce. Recife, Brazil and Geneva; 2013. Available from: https://www.who.int/workforcealliance/knowledge/resources/GHWA_AUnive rsalTruthReport.pdf. [Last accessed on 2019 Dec 20].  Back to cited text no. 11
    
12.
Kamath D, Xavier D, Gupta R, Devereaux P, Sigamani A, Hussain T, et al. Rationale and design of a randomized controlled trial evaluating Community Health Worker (CHW) based interventions for the secondary prevention of acute coronary syndromes in India (SPREAD). Am Heart J 2014;168:690-7.  Back to cited text no. 12
    
13.
Muhihi AJ, Urassa DP, Mpembeni RNM, Leyna GH, Sunguya BF, Kakoko D, et al. Effect of training community health workers and their interventions on cardiovascular disease risk factors among adults in Morogoro, Tanzania: Study protocol for a cluster randomized controlled trial. Trials 2018;19:1-12.  Back to cited text no. 13
    
14.
Rowe AK, De Savigny D, Lanata CF, Victora CG. How can we achieve and maintain high-quality performance of health workers in low-resource settings? Lancet 2005;366:1026-35.  Back to cited text no. 14
    
15.
Willock R, Mayberry R, Yan F, Daniels P. Peer training of community health workers to improve heart health among African American Women. Health Promot Pr 2016;16:63-71.  Back to cited text no. 15
    
16.
Abdel-All M, Putica B, Praveen D, Abimbola S. Effectiveness of community health worker training programmes for cardiovascular disease management in countries: A systematic review. BMJ Open 2017;7:1-11.  Back to cited text no. 16
    
17.
Donovan JO, Bersin A, Donovan CO. The effectiveness of mobile health (mHealth) technologies to train healthcare professionals in developing countries: A review of the literature. BMJ Innov 2015;1:33-6. Available from: https://innovations.bmj.com/cont ent/1 / 1/33. [Last accessed on 2020 Jan 11].  Back to cited text no. 17
    
18.
Winters N, Langer L, Nduku P, Robson J, Donovan JO, Maulik P, et al. Using mobile technologies to support the training of community health workers in low-income and middle- income countries: Mapping the evidence. BMJ Glob Health 2019;4:1-10. Available from: https://gh.bmj.com/content/4 /4/e001421. [Last accessed on 2020 Jan 10].  Back to cited text no. 18
    
19.
Colleran K, Harding E, Kipp BJ. Building capacity to reduce disparities in diabetes: Training community health workers using an integrated distance learning model. Diabetes Educ 2012;38:386-96.  Back to cited text no. 19
    
20.
Komaromy M, Ceballos V, Zurawski A, Bodenheimer T, Thom DH, Arora S. Extension for community healthcare outcomes (ECHO): A new model for community health worker training and support. J Public Health Policy 2018;39:203-16. Available from: https://link.springer.com/art icle/10.1057%2Fs41271-017-0114-8. [Last accessed on 2020 Jan 25].  Back to cited text no. 20
    
21.
Castro TT, Zucki F. Training of community health agents in health hearing children: Current perspectives Capacitação do Agente Comunitário de Saúde. Codas 2015;27:616-22. Available from: http://www.scielo.br/scielo.p hp?script=sci_arttext&p id=S2317-17822015000600616&lng=pt&tlng=pt. [Last accessed on 2020 Feb 01].  Back to cited text no. 21
    
22.
Santos SL, Tagai EK, Wang MQ, Scheirer MA, Slade JL, Holt CL. Feasibility of a web-based training system for peer community health advisors in cancer early detection among African Americans. Am J Public Health 2014;104:2282-9.  Back to cited text no. 22
    



 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]



 

Top
 
 
  Search
 
Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

 
  In this article
   Abstract
  Introduction
  Subjects and Methods
  Results
  Discussion
   Conclusion and R...
   References
   Article Tables

 Article Access Statistics
    Viewed219    
    Printed9    
    Emailed0    
    PDF Downloaded31    
    Comments [Add]    

Recommend this journal


[TAG2]
[TAG3]
[TAG4]