Capacity of nurses and midwives for early identification of developmental delays among children in a Ghanaian rural district

Abstract

: Early identification of developmental delays provides an opportunity for early intervention that improves the child’s growth and development. Primary healthcare providers have a basic responsibility for the early identification of developmental delays for intervention or referral to the appropriate specialist. However, the capacity of primary healthcare providers to identify children with developmental delays in the Wa West District of Ghana is unknown. A cross-sectional study was conducted involving 113 primary healthcare providers working in various healthcare facilities in the Wa West district. The participants were obtained through a simple random sampling technique. Quantitative data were collected using a structured questionnaire and analyzed using descriptive statistical analysis. The results indicated that 87 (77.0%) participants found their training adequate for early identification of developmental delays. However, less than 10% of the participants reported having excellent knowledge on the use of tools for early identification. While an average of 77.1% of the participants showed knowledge in the areas of a child’s medical history-taking, the diet of the child 65 (57.5%) was cited as least important. Also, an average of 67.6% of participants responded accurately to questions seeking their knowledge on screening. However, few 30 (26.5%) participants knew that not all screening results are always accurate. Higher education and work experience appear influential on participants’ knowledge on various areas of early identification of developmental delays. In conclusion, gaps in participants’ knowledge on areas of early identification of developmental delays could lead to late identification, hence limiting the child’s development and outcome of intervention services.

Keywords:

• Primary healthcare
• capacity
• developmental delays
• early identification
• Ghana

PUBLIC INTEREST STATEMENT

Children with disabilities are among the world's most-deprived people with many unmet healthcare needs especially in rural or poorer nations. Early identification and intervention of disabling health conditions improves health outcomes, growth, and development. A quantitative study was conducted among primary care providers in a rural district of Ghana to assess their capacity for childhood impairments’ identification. An average of 77.1% of the participants showed knowledge in areas of child’s medical history-taking, an average of 67.6% responded accurately on screening and less than 10% reported having excellent knowledge on the use of tools for early identification of impairments.

1. Introduction

Early childhood development includes the physical, socio-emotional, cognitive, and motor development of children between ages 0 and 8 years (World Vision International, 2016). Early childhood development is a prioritized area for international organizations such as the World Health Organization (WHO), World Vision International (WVI), and governments because the experiences of children at this stage have a significant impact on their growth across various domains (Purvis et al., 2014; World Health Organization, 2016; World Vision International, 2016). Meeting the healthcare needs of children and newborns is key towards meeting Universal Health Coverage (UHC), the Sustainable Development Goal 3 (SDG3) (WHO and UNICEF, 2019) as well as the demands of the United Nations Convention on the Rights of the Child (UNCRC, 1989) and the United Nations Convention on the Rights of Persons with Disabilities (UNCRPD, 2006).

However, impairments impede early childhood development and contribute largely to childhood disabilities, a major chronic condition that inhibits health, proper growth, and development (Halfon et al., 2012; Miller et al., 2016). The International Classification of Impairments, Disabilities, and Handicaps (ICIDH) of the World Health Organization (WHO) referred to impairments, in the context of health experience, as any loss or abnormality in the psychological, physiological, or anatomical structure or function (World Health Organization, 1980). “Impairment” is a purposefully used as an inclusive term covering a wide range of disorders and losses in body structures (ibid). Impairments are the leading cause of developmental delays and childhood disabilities especially in poor settings where about 80% of children with disabilities live (Houtrow et al., 2014; UNICEF, 2013).

The enactment of global policies such as the SGDs, UHC, and the UNCRPD (2006) which mandates State Parties (in Article 25b) to carry out appropriate early identification and intervention services aimed at minimizing and/or preventing further disabilities in children has impacted the Ghanaian healthcare system through policy and practical initiatives. Articles 34 and 35 of the Persons with Disabilities law (2006) of Ghana tasked primary healthcare (PHC) providers with periodic screening of children for early detection and management of developmental delays for subsequent placement into schools. A roadmap was further developed by the Ghana government which emphasized on the strengthening of health systems to improve service availability and easy access to all people in bid to attain global policies such the UHC (Ministry of Health, 2020). The current roadmap and earlier policies such as the Community-Based Health Planning Services (CHPS) policy (2016) lead to the expansion of the PHC coverage through the CHPS system which is aimed at providing essential services to Ghanaians at the community level and reducing access barriers due to distance for improving child and maternal health (Ministry of Health MoH, 2016). The government further introduced a national health insurance policy aimed at minimizing health expenditure, especially for the poor and vulnerable. It is also required that the CHPS and local stakeholders to collaboratively mobilize and sensitize communities on available services, including the community-based child screening exercises (“weighing”), neonatal care, nutrition education, and child growth monitoring and promotion (Ministry of Health, 2020).

Data on the prevalence and incidence of developmental delays in Ghana appear scanty due to numerous early identification challenges including limited human and material resources and limited studies on this phenomenon for that matter (Ruparelia et al., 2016; Colgan et al., 2012). However, Bello et al. (2013) found the prevalence of children with developmental delays as 44.6% of children under 5 years screened in rural clinics in Ghana. Among these, 12.4% had developmental delays in social interaction, 5.8% had delays in communication domain, 9.7% in fine motor domain, 6.7% in gross motor domain, and 10.0% in problem-solving skills. Sherriff et al. in a recent study revealed that healthcare providers are more capable of identifying developmental delays that present physical features. For instance, children with cerebral palsy, Down syndrome, and Autism Spectrum Disorder (ASD) were identified by many healthcare providers compared to learning and attention deficit disorder (Sheriff et al., 2022).

Early identification of developmental delays which involves measures taken to diagnose or detect children at risk or exhibit primary symptoms for a health condition is critical in preventing childhood disabilities and promoting early childhood development (Fischer et al., 2014). Early identification is necessary for early intervention. It provides room for evidence-based preventive and therapeutic measures that mitigate the impact of developmental delays on the child (Novak et al., 2017; WHO, 2012). Without early intervention, children with developmental delays are exposed to multiple health risks, co-morbidities, and deteriorating conditions which lead to permanent disabilities (Lin et al., 2014). This limits full realization of the child’s potentials and consequently affecting the child’s future endeavors such as work and family life (Wickenden et al., 2013).

The responsibility for monitoring the health and development of children rests largely on the PHC providers since they are the first point of contact with the health system (Purvis et al., 2014). Thus, competent and knowledgeable PHC providers are required for screening and accurate medical history-taking to identify developmental delays, deviations in children’s developmental milestones, or their risk factors (McCullough & Martino, 2012). This could be achieved through adequate training and regular practice (Calma et al., 2019; Radecki et al., 2011; Ridde & Yaméogo, 2018). However, Kankam et al. (2017) and Ruparelia et al. (2016) reported nearly no or weak early identification efforts in African countries including Ghana. Challenges including limited availability of well-trained/skilled PHC providers (Bhana et al., 2010; Caitlyn and Alisha, 2017; Sarpomaa et al., 2017), inadequate supply of tools and equipment (Kankam et al., 2017; Ruparelia et al., 2016) among others limit the early identification efforts. In the Wa West district of Ghana, the capacity and knowledge of the PHC providers for early identification of developmental delays is unknown, even though fundamental for the effectiveness of early intervention programs/initiatives or related policies. Hence, this study was conducted to assess the knowledge of nurses and midwives on early identification of developmental delays in Wa West district.

1.1 Training of healthcare professionals in Ghana

The duration of school training of health professionals in Ghana ranges from two (2) academic years for certificate programs to six (6) years for physician assistants. The professionals with the least years of training such as enrolled or certified nurses (2 years) are primarily responsible for the healthcare delivery at the primary level and sometimes led by Registered General Nurses and Midwives (3 years). This period of training is generally inadequate to equip them with the needed skills and competence for service delivery, causing a general frustration among these PHC providers (Bhana et al., 2010; WHO, 2008). For example, Essel et al. (2020) reported the unavailability of appropriate Information Communication Technology (ICT) resources for the training of nurses and midwives as well as limited knowledge of the teachers in the use of these technologies. The limited practical components in the training of nurses and midwives, and the limited preparedness of the tutors to teach such courses like Informatics is also a concern. A community-based study on the clinical education of nurses in Ghana revealed the need for change through providing adequate tools and equipment for practice, effective teaching, and evaluation among others (Asirifi et al., 2017). These lapses are sometimes catered for through workshops and in-service training programs.

2. Methods and materials

2.1 Study setting

The study was conducted in the Wa West district of the Upper West Region, Ghana. The district is a typical rural district with a population of 81,348, of which children between 0 and 14 years were 45.5% according to the 2010 population and housing census (Ghana Statistical Service; GSS, 2014). The district is geographically the largest in the region with a land area of 1492 km² and represents 11.6% of the region’s populations. The GSS rated it as the poorest district in Ghana with a poverty incidence of 92.4% and deprived of socio-economic resources and amenities such as health infrastructure and personnel, education, and basic life necessities. In 2010, 33.5% of its population were in school, out of which 77.5% were at the basic level while 0.4% were at the tertiary level (GSS, 2014). The disability population was 3% of the total population. The visually impaired constituted 33.6%, the people with physical disability constituted (25.1%), the hearing impaired were 15.9%, those who had speech difficulties were 10.6%, whiles the remaining were classified as “others”. Currently, the district has 38 health facilities, consisting of 1 polyclinic, 6 clinics, 1 maternity home, and 30 Community-Based Health Planning Services (CHPS) compounds. The district’s human resource strength in healthcare delivery is presented in Table 1.

Table 1. Human resource of Wa West district in healthcare delivery

Profession	Number of staff
Nurses	161
Midwives	32
Physician assistants	3
Medical officers	2
Medical officer—consultant	0
Medical officer—specialist	0
Medical laboratory technicians	7
Midwife officer	1
Nursing officers	2
Disease control	2
Health information	2
Health promotion	1
Technical officer—nutrition	2

Source: District Health Directorate (2020), unpublished

2.2 Study design and approach

The study adopted a descriptive cross-sectional design due to its appropriateness in assessing health professionals’ knowledge and attitude on a phenomenon without a detailed assessment of the association between different variables (Kesmodel, 2018). It can establish a piece of preliminary evidence for a causal relationship or basis for an intervention study (Alexander Lorraine et al., 2015). Data were collected at 1-point using a researcher-administered questionnaire. A quantitative approach was adopted for an objective and reliable investigation and to allow for predictions and generalization of the study findings to areas with similar characteristics.

2.3 Study population and sample

The population of the study consisted of all formally trained healthcare providers within the Wa West district. These include nurses, midwives, medical officers, physician assistants, laboratory technicians, and public health workers, among others. The groups of interest that constituted the sample were the nurses and midwives. This is because they are the first point of contact with healthcare system and responsible for the primary healthcare delivery at the CHPS compounds and clinics. As a result, they have the responsibility to identify, diagnose, and treat or otherwise refer cases.

2.4 Sample size determination

A sample size of 130 participants (consisting of 108 nurses and 22 midwives) was estimated using the Yamane’s (1967) sample size determination formula, n=$\frac{N}{1+N{\left(\alpha \right)}^2}$, where n = the sample size

N = the population size (Nurses and Midwives) = 193 and α = the level of precision (at 0.05).

The respective sample sizes for the nurses and midwives were determined proportional to their populations.

2.5 Sampling method and procedure

A simple random sampling was used to select both the health facilities and the participants. This probability sampling method gave equal chances to all health facilities and the nurses and midwives to be selected for the study. From the 38 health facilities, the maternity home and the polyclinic were selected because they were one each. The list of the clinics and CHPS compounds obtained at the district health directorate were folded into a box, and 27 of them were randomly drawn to get the required sample size. Therefore, health facilities recruited were 1 polyclinic, 1 maternity home, 4 clinics, and 23 CHPS compounds. At each health facility, permission to recruit the participants was sought from the facility head, aided by an approval letter from the district health directorate. The nurses and midwives were separately sampled in order to have both represented. Their list was usually obtained from the facility head and randomly sampled in half by drawing the names from a box. Where they were uneven, any other one potential participant who consented to the study was recruited.

2.6 Data collection methods and procedure

A semi-structured questionnaire was used to collect the data for the study. The use of questionnaire allowed for the collection of objective data which the results could be generalized to other districts. It also sought specific responses on the areas of enquiry. Some items in the questionnaire were Likert Scale type questions, while others had YES or NO, TRUE or FALSE, and I DON’T KNOW or NOT SURE options. Approximately, the questionnaire was designed to take each participants 25–30 minutes to complete and structured into sections to collect demographic information, knowledge on screening, medical history-taking, and tools and equipment or guidelines for identifying developmental delays. Those who consented to participate were given a printed questionnaire to complete at their convenient schedule for recollection.

2.7 Data analysis procedure

The data collected were cross-checked to remove errors and for completeness, accuracy, and consistency of the responses before entry. The data was coded and entered into MS-Excel. Descriptive statistical analysis was performed on the data aided by the Statistical Package for Social Sciences (SPSS) software version 14.0. Results were presented in frequency tables. Percentages and measures of central tendencies were also computed. Also, inferential statistics—chi-square were performed to establish an association between variables of interest.

2.8 Ethical considerations

Ethical approval with Ref: CHRPE/AP/086/20 was obtained from the Committee on Human Research and Publication Ethics (CHRPE), Kwame Nkrumah University of Science and Technology (KNUST), Kumasi, to conduct the study. A written approval was also granted by the Upper West Regional Health Directorate of the Ghana Health Service which was subsequently endorsed by the Wa West District Health Directorate (Ref. No. GHS/UWR/TP-51).

The data for this study were used solely for this academic purpose for which they were collected. Anonymity of the participants was ensured by not collecting personal identifiers such as names, contact numbers, or addresses and other identifiers that can be attributed to a particular person. Participants’ consent was sought after explaining to them the purpose and procedures for the study, the benefits, potential risk, and voluntary participation. Participants could opt out anytime they felt uncomfortable.

3. Results

The results were presented using descriptive statistics such as frequencies and percentages and summarized in tables. Association between variables was also determined. A knowledge score of 50% or more was classified as “Adequate” and below 50% as “Inadequate”. The knowledge score was determined as

$\frac{100}{\mathrm{N}\mathrm{u}\mathrm{m}\mathrm{b}\mathrm{e}\mathrm{r}\mathrm{o}\mathrm{f}\mathrm{q}\mathrm{u}\mathrm{e}\mathrm{s}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}\mathrm{s}}\times \mathrm{N}\mathrm{u}\mathrm{m}\mathrm{b}\mathrm{e}\mathrm{r}\mathrm{o}\mathrm{f}\mathrm{r}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t}\mathrm{r}\mathrm{e}\mathrm{s}\mathrm{p}\mathrm{o}\mathrm{n}\mathrm{s}\mathrm{e}\mathrm{s}$

3.1 Demographic characteristics of participants

From Table 2, the mean (±SD) age of the participants was 29.32 ± 4.573, with 63 (55.8%) between the ages of 20 and 29 years. Females 63 (55.8%) were the majority as well as Christians 71 (62.8%). Only 4 (3.5%) were first-degree holders, while about two-thirds 67 (59.3%) were certificate holders and trained for 2 years or less. The majority 103 (91.2%) of the participants worked at the community level (Clinics/CHPS compounds) whiles 10 (8.8%) work at the polyclinic. The Mean ± SD for the participants’ work experience was 1.72 ± 0.647 years as a little 57 (50.4%) had worked between 2 and 5 years and only 12 (10.6%) had worked for over 5 years. Nurses constituted 91 (80.5%) of the study participants. Most of the participants 88 (77.9%) were natives of the study area.

Table 2. Showing demographic characteristics of participants

Variable	Mean ± SD	Frequency (113)	Percentage (100%)
Gender Male Female		50 63	44.2 55.8
Ages	29.32 ± 4.573
Religion Muslim Christian Traditionalist		36 71 6	31.9 62.8 5.3
Highest qualification Certificate HND/Diploma Degree		67 42 4	59.3 37.2 3.5
Duration of training ≤2 years Between 2 to 4 years ≥4 years	2.48 ± 0.628	67 38 8	59.3 33.6 7.1
Work experience <2 years 2–5 years 5+ years	1.72 ± 0.647	44 57 12	38.9 50.4 10.6
Facility of work District’s polyclinic Comm’ty facility/CHPS		10 103	8.8 91.2
Profession Nurses Midwife		91 22	80.5 19.5
Residential Natives Non-natives		88 25	77.9 22.1

Source: Author’s Survey, 2020

3.2 Self-reported level of knowledge for early identification of developmental delays in children

In Table 3, participants assessed their level of knowledge and capacity for early identification of developmental delays among children. The results showed that 84 (74.3%) and 88 (77.9%) of them, respectively, reported being familiar with developmental delays and had knowledge on their causes/risk factors. However, a total of 30 (23.0%) either disagreed or had doubts if they were adequately trained to identify developmental delays in children. Similarly, 43 (38.1%) were either not sure or disagreed to have knowledge of the tools or guidelines for early identification of developmental delays, even though most 70 (61.9%) claimed to have knowledge.

Table 3. Showing self-reported level of knowledge/capacity for early identification of developmental delays in children

Area of knowledge/capacity	Response n = 113
	Agree Freq(%)	Not sure Freq(%)	Disagree Freq(%)
I am familiar with impairments that can lead to disabilities in children	84(74.3)	19(16.8)	10(8.8)
I have adequate knowledge about the causes, risk factors and intervention measures for childhood disabilities	88(77.9)	16(14.2)	9(8.0)
My training prepared me adequately to identify developmental delays in children	87(77.0)	12(10.6)	14(12.4)
I know most of the tools and guidelines for assessing children for developmental delays	70(61.9)	25(22.1)	18(15.9)

Source: Author’s Survey, 2020

3.2.1 Self-reported level of knowledge and capacity for early identification of developmental delays in children by work experience, qualification, and profession

A cross-tabulation of the participants’ self-reported knowledge and capacity for early identification of developmental delays showed that participants with over 5 years’ work experience were more confident of their knowledge and capacity as indicated by at least 11 (97.1%) of them. Surprisingly, those who had worked between 2 and 5 years were less confident than those who had worked below 2 years. Similarly, degree holders were the most confident among other participants as 3 out of 4 (75.0%) reported knowledge on all the areas assessed. However, a slightly higher proportion of the certificate holders 52 (77.6%) claimed to be knowledgeable on developmental delays and their causes/risk factors, compared to 29 (69.0%) of the Higher National Diploma (HND) holders. Yet, more certificate holders 19 (28.4%) believed they were not adequately trained compared to HND holders 6 (14.3%). Thus, higher level of education and work experience influence participants’ perception of knowledge and confidence.

Also, a higher proportion of nurses 72 (79.1%) than midwives 15 (68.2%) found their training adequate. However, a higher proportion of midwives 17 (77.3%) than nurses 67 (73.6%) claim familiarity with developmental delays including their causes and risk factors as indicated by 19 (84.6%) midwives and 69 (75.8%) nurses [see Table 4].

Table 4. Showing participants’ knowledge for early identification of impairments by work experience, qualification, and profession

Self-reported level of confidence for early identification and referral of impairments in children	Response n = 113
	Work experience			Qualification			Profession
	<2 yrs	2–5 yrs	5+ yrs	Certificate HND degree			Nurse midwife
	N(%)	N(%)	N(%)	N(%)	N(%)	N(%)	N(%)	N(%)
I am familiar with impairments that lead to disabilities in children.	34(77.3)	39(68.4)	11(97.1)	52(77.6)	29(69.0)	3(75.0)	67(73.6)	17(77.3)
I have adequate knowledge on causes, risk factors for childhood impairments.	35(79.5)	42(73.3)	11(97.1)	52(77.6)	33(78.6)	3(75.0)	69(75.8)	19(84.6)
I am trained adequately for the early identification of impairment in children.	37(84.1)	38(66.7)	12(100.0)	48(71.6)	36(85.7)	3(75.0)	72(79.1)	15(68.2)
I am familiar with most tools and guidelines for assessing children for impairments.	29(65.9)	30(52.6)	11(97.1)	41(61.2)	26(61.9)	3(75.0)	58(63.7)	12(54.5)

3.3 Perception of responsibility for early identification of developmental delays

Knowing and acknowledging that one has a responsibility for early identification could potentially influence the quest for the needed knowledge/capacity. In Table 5, majority 89 (78.8%) of the participants accepted the responsibility for early identification of developmental delays. However, only 45 (39.8%) ever participated in any screening programs.

Table 5. Showing participants who accepted responsibility and participated in screening for early identification of impairments

Perception of responsibility	Response (n = 113)
	All categories	Profession		Qualification			Facility type
		Nurses midwives		Certificate HND degree			CHPS Dist. Hosp.
		N(%)	N(%)	N(%)	N(%)	N(%)	N(%)	N(%)
It is my duty for early identification of impairments in children	89(78.8%)	72(79.1)	17(77.3)	55(82.1)	32(76.2)	2(50.0)	81(78.6)	8(80. 0)
Ever participated in newborn screening?	45(39.8%)	33(36.3)	12(54.5)	22(32.8)	21(50.0)	2(50.0)	39(37.9)	6(60.0)

Source: Author’s Survey, 2020

The responsibility for early identification of developmental delays was accepted by a higher proportion of certificate holders 55 (82.1%) than HND 32 (76.2%) and degree holders 2(50.0%). Similarly, nurses 72 (79.1%) were slightly more likely than midwives 17 (77.3%) to accept this responsibility though more midwives 12 (54.5%) participated in newborn screening for developmental delays. Surprisingly, 22 (22.4%) of participants at the CHPS compounds rejected this responsibility even though they are the first personnel in the healthcare delivery.

3.4 Knowledge on screening for developmental delays identification in children

An average of 67.6% of participants responded accurately on screening and was considered encouraging. For instance, 94 (83.2%) indicated screening as being effective in identifying most developmental delays and 99 (87.6%) also knew that developmental screening could help assess the child’s developmental milestones. However, few 30 (26.5%) participants knew that not all screening results are always accurate.

Education seems to be influential on participants’ knowledge. For instance, all degree holders 4 (100.0%) were more knowledgeable than certificate 55 (82.1%) and HND 35 (83.3%) holders in most areas including screening being able to detect most developmental delays/abnormalities. Between certificate and HND holders, there appears to be a slight difference in their knowledge. Similarly, participants with over 5 years of work experience showed more knowledge than the others on four out of the five areas of assessment [see Table 6]. Profession seems less influential on the participants’ knowledge of screening though nurses appear slightly more knowledgeable than midwives. For instance, 79 (86.8%) nurses and 15 (68.2%) midwives knew screening being effective in identifying health conditions in children.

Table 6. Showing participants who responded correctly on screening

Knowledge of screening	All categories N(%)	Response (n = 113)
		Profession		Qualification			Work experience
		Nurses midwife		Cert HND degree			<2 yrs	2–5 yrs	5+ yrs
		N(%)	N(%)	N(%)	N(%)	N(%)	N(%)	N(%)	N(%)
Screening is the best way to identify a health condition in children at early stage	94(83.2)	79(86.8)	15(68.2)	55(82.1)	35(83.3)	4(100)	39(88.6)	46(80.7)	9(75. 0)
Screening tests cannot reveal risk factors for disabling conditions	62(54.9)	53(58.2)	9(40.9)	41(61.2)	19(45.2)	2(50.0)	23(52.3)	31(54.4)	8(66.7)
Screenings can provide track records of the child’s medical history for future diagnosis	97(85.8)	78(85.7)	19(86.4)	54(80.6)	39(92.9)	4(100)	38(86.4)	48(84.2)	11(91.7)
Screening results are always accurate	30(26.5)	24(26.4)	6(27.3)	20(29.9)	8(19.0)	2(50.0)	11(25.0)	14(24.6)	5(41.7)
Developmental screening helps assess the child’s developmental milestones	99(87.6)	82(90.1)	17(77.3)	60(89.6)	35(83.3)	4(100)	38(86.4)	49(86.0)	12(100)

Source: Author’s Survey, 2020

3.5 Knowledge of relevant areas for medical history-taking

The medical history of patients is important in diagnosing a health condition. In Table 7, an average of 77.1% of the participants showed knowledge of some relevant areas of a child’s medical history-taking. However, the child’s family medical history 106 (93.8%), mother’s lifestyle during pregnancy 102 (90.3%), and whether the child had previously been sick 100 (88.5%) were considered most important. The diet of the child 65 (57.5%) was cited as the least important.

Table 7. Showing relevant areas of a child’s medical history-taking for impairments identification

Relevant areas of history taking	Response n = 113
	Right N(%)	Wrong N(%)	Not sure N(%)
Medical history of family	106(93.8)	2(1.8)	5(4.4)
Kind of food child often ate	65(57.5)	21(18.6)	27(23.9)
If the child has previously been sick	100(88.5)	1(0.9)	12(10.6)
Occupation of mother	76(67.3)	23(20.4)	14(12.4)
Mother’s medical history and lifestyle during pregnancy	102(90.3)	1(0.9)	10(8.8)
Duration of labor	90(79.6)	11(9.7)	12(10.6)
If a child cried immediately after birth	77(68.1)	23(20.4)	13(11.5)
Functional abilities of the child such as eating, playing, hearing, etc.	81(71.7)	10(8.8)	22(19.5)

Source: Author’s Survey, 2020

3.5.1 Knowledge of relevant areas of medical history-taking by profession, qualification, and facility type

A cross tabulation revealed that all degree holders 4 (100.0%) responded correctly to five out of the eight areas of assessment. An average of 34 (81.0%) of HND holders and 50 (74.6%) responded correctly to the areas of assessment on history-taking, suggesting the influence of higher education. Also, nearly an equal average of midwives 17 (77.8%) and nurses 70 (76.9%) correctly responded on the medical history-taking of children. However, a higher proportion of midwives correctly identified six out of the eight areas of assessment than nurses [see Table 8].

Table 8. Showing participants who responded correctly on medical history taking by profession, qualification, and the facility of work

The relevance of history taking	Response (n = 113)
	Profession		Qualification			Facility type
	Nurses midwives		Certificate HND degree			Polycl CHPS
	N(%)	N(%)	N(%)	N(%)	N(%)	N(%)	N(%)
Medical history of family	85(93.4)	21(95.5)	61(91.0)	41(97.6)	4(100.0)	10(100.0)	96(93.2)
Kind of food child often ate	51(56.0)	14(63.6)	38(56.7)	25(59.5)	2(50.0)	7(70.0)	55(56.3)
If the child has previously been sick	78(85.7)	22(100.)	58(86.6)	38(90.5)	4(100.0)	8(80.0)	92(89.3)
Occupation of mother	60(65.9)	16(72.1)	44(65.7)	30(71.4)	2(50.0)	6(60.0)	70(68.0)
Mother’s medical history and lifestyle during pregnancy	83(91.2)	19(86.4)	59(88.1)	39(92.9)	4(100.0)	9(90.0)	93(90.3)
Duration of labor	72(79.1)	18(81.8)	51(76.1)	36(85.7)	3(75.0)	8(80.0)	82(79.6)
If child cried immediately after birth	62(68.1)	15(68.2)	42(62.7)	31(73.8)	4(100.0)	8(80.0)	69(67.0)
Functional abilities of the child such as eating, playing, hearing, etc.	67(73.6)	14(63.6)	47(70.1)	30(71.4)	4(100.0)	7(70.0)	74(71.8)

Source: Author’s Survey, 2020

Similarly, little difference in knowledge was found based on the facility of work, even though much was expected from participants at the CHPS compounds because they are the first point of contact. For example, 10 (100.0%) and 96 (93.2%) of participants at the polyclinic and CHPS centers, respectively, indicated the child’s family medical records as important in history taking. Similarly, 92 (89.3%) of participants at the CHPS compounds and 8 (80.0%) at the polyclinic indicated the child’s previous health status in the current diagnosis as relevant as shown in Table 7.

3.5.2 Association between demographic characteristics and knowledge on medical history taking

In Table 9, a majority of the participants showed adequate knowledge of children’s medical history-taking with the pass mark placed at 50% (Mean ± SD = 77.10 ± 21.32). In terms of gender, all the males 50 (100.0%) were knowledgeable as against 57 (90.5%) of females. Age does not seem to have much influence probably because of the sample size of the age groups. Midwives 21 (95.5%) were slightly more knowledgeable than nurses 86 (94.5%), and all participants who work over 5 years 12 (100.0%) had adequate knowledge of medical history-taking of children. Only gender (p = 0.007) showed a statistical significance at 95% CI.

Table 9. Showing association between demographic characteristics and knowledge on medical history taking

Demographic characteristics	Knowledge of medical history taking
	n	Inadequate n(%)	Adequate n(%)	p-value
Gender				0.007
Male	50	0(0.0)	50(100.0)
Female	63	6(9.5)	57(90.5)
Age				0.946
10–19	1	0(0.0)	1(100.0)
20–29	63	4(6.3)	59(93.7)
30–39	45	2(4.4)	43(95.6)
40–49	3	0(0.0)	3(100.0)
50–59	1	0(0.0)	1(100.0)
Qualification				0.390
Certificate	67	5(7.5)	62(92.5)
Diploma/HND	42	1(2.4)	41(97.6)
Degree	4	0(0.0)	4(100.0)
Profession				1.00
Nurse	91	5(5.5)	86(94.5)
Midwife	22	1(4.5)	21(95.5)
Work experience				0.435
<2 years	44	2(4.5)	42(95.5)
2–5 years	57	4(7.0)	53(93.0)
5+ years	12	0(0.0)	12(100.0)
Facility type				1.00
District polyclinic	10	0(0.0)	10(100.0)
Comm’ty facility/CHPS	103	6(5.8)	97(94.2)
Religion				0.451
Muslim	36	1(2.8)	35(97.2)
Christian	71	5(7.0)	66(93.0)
Traditionalist	6	0(0.0)	6(100.0)
Tribe				1.00
Natives	88	5(5.7)	83(94.3)
Non-natives	25	1(4.0)	24(96.0)
Mean ± SD: 77.10 ± 21.32

Source: Author’s Survey, 2020

3.6 Knowledge on tools/procedures for identification of developmental delays

In Table 10, participants self-reported a general low level of knowledge on tools/procedures for examining children for developmental delays. For instance, many participants reported having no knowledge at all on Peabody Picture Vocabulary Test-III (PPVT-III) 62 (54.9%), Mullen Scale of Early Learning (MSEL) 57 (50.4%), Child Behavior Checklist (GBCL) 56 (49.6%), and Denver Developmental Screening Test (DDST) 55 (48.7%) (Rydz et al., 2005). Participants reported to have knowledge on Apgar score 21 (18.6%), monitoring children for vital signs of deviation 19 (16.8%), and physical assessment of children 18 (15.9%). With all the other tools/procedures, less than 10% of participants reported having excellent knowledge.

Table 10. Showing level of knowledge on tools for early identification of impairments

Tools/protocols	Response
	NIL N(%)	L N(%)	M N(%)	G N(%)	E N(%)
Screening of newborns and children for various forms of impairments/defects	32(28.3)	26(23.0)	35(31.0)	14(12.4)	6(5.3)
The International Classification of Functioning, Disability, and Health- Child and Youth version assessment tool (ICF-CY)	42(37.2)	36(31.9)	22(19.5)	8(7.1)	5(4.4)
Child Development Inventory -CDI	47(41.6)	22(19.5)	26(23.0)	11(11.0)	7(6.2)
The Ages and Stages Questionnaire (ASQ)	49(43.4)	20(17.7)	24(21.2)	13(11.5)	7(6.2)
Differential Abilities Scale (DAS)	47(41.6)	26(23.0)	23(20.4)	12(10.6)	5(4.4)
Mullen Scale of Early Learning (MSEL)	57(50.4)	18(15.9)	24(21.2)	7(6.2)	7(6.2)
Screening Tool for Autism in Two-Year Olds (STAT)	52(46.0)	23(20.4)	27(23.9)	7(6.2)	4(3.5)
Child Behavior Checklist (GBCL)	56(49.6)	18(15.9)	23(20.4)	9(8.0)	7(6.2)
Denver Developmental Screening Test (DDST)	55(48.7)	24(21.2)	24(21.2)	6(5.3)	4(3.5)
Children’s Communication Checklist-2 (CCC-2)	45(39.8)	23(20.4)	28(24.8)	9(8.0)	8(7.1)
Peabody Picture Vocabulary Test-III (PPVT-III)	62(54.9)	19(16.8)	18(15.9)	10(8.8)	4(3.5)
Physical examination of newborns and children for impairments and signs of prematurity	21(18.6)	20(17.7)	42(37.2)	12(10.6)	18(15.9)
Monitoring of vital signs for deviations	20(17.7)	18(15.9)	33(29.2)	23(20.4)	19(16.8)
The use of the Apgar score assessment tool for newborns	18(15.9)	24(21.2)	33(29.2)	17(15.0)	21(18.6)
The use of the Brazelton Assessment tool for newborns	53(46.9)	18(15.9)	26(23.0)	9(8.0)	7(6.2)
Anthropometric measurements of newborns	34(30.1)	22(19.5)	34(30.1)	15(13.3)	8(7.1)

Source: NIL, L—Low, M—Moderate, G—Good, E—Excellent. Source: Author’s Survey, 2020

4. Discussion

This study’s participants were relatively youthful with female dominance in the nursing and midwifery profession as also observed in Ethiopia (Dilie and Mengistu, 2015) and Nigeria (Igwe et al., 2011). The low educational status of our study participants is attributable to perhaps the rural nature and the low educational enrolment in the district (GSS, 2014). This contradicted an earlier study by Abebe and Daniel 2015 who found a comparatively higher educational status among nurses and midwives in a metropolitan setting of Ethiopia. This highlighted a gap in quality healthcare between the rural and urban settings.

The low training duration of the participants (Mean ± SD = 2.48 ± 0.628) reflected the 2-year training period for the majority, the certificate holders. Therefore, participants reporting the lack of adequate training on early detection of developmental delays was not surprising, though unexpected. It was expected that this category of health professionals, especially midwives, should have adequate training on early identification of developmental delays because they work closely with newborns, and as first-hand healthcare providers in the study area. Calma et al. (2019), Ridde and Yaméogo (2018), and Radecki et al. (2011) reported that adequate training and practice are necessary to help healthcare providers become familiar and knowledgeable for early identification of developmental delays or their risk factors for timely intervention. However, the problem of inadequate training of PHC workers is common in many African countries, including Ghana (Bhana et al., 2010), and hence increasing frustrations among PHC workers (Ojakaa et al., 2014). This could limit the confidence of the PHC practitioners and their ability to properly diagnose the health conditions of children who cannot properly explain their health needs.

This inadequate training could translate into knowledge deficiencies that will not only widen the gap in PHC delivery but also, many children with developmental delays in the Wa West district are at risk of late identification or not being identified. This will deny such children early intervention, depriving them of reaching their full developmental potentials such as in educational outcomes. If this situation continues in the district without conscientious efforts to address it, the realization of the provisions in the Persons with Disability Act (2006) of Ghana (Article 34 and 35), Sustainable Development Goal 3, and other global initiatives for children such as “Child Health Now” (World Vision, 2016) will continue to be a mirage as far as the Wa West District of Ghana is concerned. Particularly, in this case, some primary healthcare providers rejected responsibility for early identification of developmental delays, possibly because of the numerous challenges associated with the task expected of them (Kok et al., 2015). For instance, the inadequacy of screening tools and equipment, limited training of the health personnel, and low financial commitment by governments towards early identification programs could be devastating for the wellbeing of children with developmental delays in the district (Kankam et al., 2017; Ruparelia et al., 2016; Zwaigenbaum, and Bryson and Garon, 2013). This could compel parents to resort to alternative such as the services of spiritual/traditional healers or may give up on their wards’ health situation, leading to death or a long-lasting disabling condition.

Many participants in this study expressed good knowledge of screening tests and/or screening protocols. However, many misconstrued screening test results as always accurate, hence contradicting Sheldrick et al. (2015), Borson et al. (2013), and Valcour et al. (2011) who reported inaccuracies in screening test results and/or their interpretations. Even though screening is harmless by itself, the tendency for misinterpretation of the screening results and the subsequent utilization of such information to make healthcare decisions could be detrimental to the child involved. For instance, a false-negative could exclude the child from early intervention programs while a false positive could also cause unnecessary frustrations, anxiety, and needless medical intervention which could be harmful to the child. In less-resourced settings or health facilities in terms of unavailability of knowledgeable/experienced personnel and updated tools, this menace of screening test inaccuracies becomes common as is the case in rural district such as the Wa West district of Ghana. This is similar to the views of Sarpomaa et al. (2017) and Sheldrick et al. (2015) that inaccurate screening test results are likely to be found in less resourced settings.

The use of tools for assessing function, developmental delays, and disability yields more accurate and reliable results (Erlandson et al., 2014). But the findings showed a larger gap in knowledge on the use of tools and procedures for the identification of developmental delays among the nurses and midwives in the Wa West district. This is possibly due to the scarcity of tools as reported in this study because the availability of screening tools increases the workers’ knowledge on their use (Radecki et al., 2011). Therefore, the health decisions on children in the Wa West district by the PHC workers may largely be based on “guess-work” without any clear evidence. This risks subjecting children to inappropriate medical interventions or denying them the needed healthcare attention. However, as formally trained personnel, much was expected in terms of knowledge on the use of basic screening/assessment tools or procedures.

A comprehensive medical history-taking of the child’s health records including the family is key in identifying developmental delays or their risk factors (McCullough & Martino, 2012). Generally, participants showed capability of taking a good medical history. However, the child’s diet/nutrition was underrated though malnutrition is a fundamental cause of childhood impairments (UNESCO, 2019). Surprisingly, some participants downplayed other relevant aspects of history-taking such as duration of labor and the cry of the baby immediately after birth. This contradicted modern science and as indicated by Miller et al. (2016) that a deviation from the ideal in these areas has a high tendency to cause developmental delays such as cerebral palsy. In rural districts, for instance, mothers may equally overlook and not report these relevant aspects during their wards’ health diagnosis, leading to unidentified cause of children’s ill-health for targeted intervention. This is because the PHC workers may not be in the capacity to give them the needed education on monitoring and identifying risk factors that need attention.

This study supports Ridde and Yaméogo’s (2018) and Calma et al. (2019) assertion that higher levels of education enhance one’s knowledge in the field of practice and vice versa. Similarly, as more years of work exposure positively influence participants’ knowledge, also reported by Igwe et al. (2011).

5. Conclusion

Poor healthcare services in rural districts like the Wa West district do not only bother on insufficient technical resources or infrastructure but the quality of human resources. The numerous challenges of early identification of developmental delays which can be attributed to the knowledge gap of the PHC workers put many children at risk of late identification or not being identified for early intervention. Adequate training is necessary to enhance PHC workers’ capacity and knowledge on relevant areas for early identification such as screening, medical history-taking, and the use of tools/procedures.

Alongside the provision of adequate tools and equipment, the governments through the health ministry should invest in the training of PHC providers to build their capacity for early identification of developmental delays through in-service programs. This may also require recruiting and training health personnel dedicated to community-based new-born screening for the identification of developmental delays. This will facilitate evidence-based intervention to prevent or mitigate the impact of developmental delays on children such as developing into a long-term disability.

Authors’ contribution

HV and WKM designed the study and wrote proposal for ethical clearance. HV, WKM, and EA wrote the study background, the methodological approach, and designed the tool for data collection. Data collection and entry was done by JJM and HV. Data were analyzed by EA-B supported by WKM. EA wrote the manuscript with support from JJM and revised by EA-B and WKM. All authors read the final manuscript.

Acknowledgments

We are most grateful to the Business Council for Africa (BCA) UK, especially Mr Clive Carpenter and Mr David Lamp for their support. We are also grateful to Janet Mary Kirk, UK, and the Wa West district health director for his immense contribution.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

Data are not available for online access; however, readers may contact Hasehni Vampere via [email protected] for the dataset.

Additional information

Funding

Funding support was received from the Business Council for Africa (BCA) UK

Notes on contributors

Hasehni Vampere

Hasehni Vampere is a MPhil graduate from the department of health promotion and disability studies, School of public health, Kwame Nkrumah University of Science and Technology, Kumasi-Ghana

Wisdom Kwadwo Mprah

Wisdom Kwadwo Mprah is a senior lecturer and head of department; department of health promotion and disability studies, School of public health, Kwame Nkrumah University of Science and Technology, Kumasi-Ghana

Enoch Acheampong

Enoch Acheampong a lecturer at the department of health promotion and disability studies, School of public health, Kwame Nkrumah University of Science and Technology, Kumasi-Ghana

Emmanuel Appiah-Brempong

Emmanuel Appiah-Brempong is a senior lecturer at the department of health promotion and disability studies, School of public health, Kwame Nkrumah University of Science and Technology, Kumasi-Ghana

Joseph Jenkins Mensah

Joseph Jenkins Mensah is a MPhil graduate from the department of health promotion and disability studies, School of public health, Kwame Nkrumah University of Science and Technology, Kumasi-Ghana