literature review of head

REVIEW article

A literature review of the potential diagnostic biomarkers of head and neck neoplasms.

• 1 Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium
• 2 Laboratorium of Experimental Medicine and Pediatrics and Member of the Infla-Med Centre of Excellence, University of Antwerp, Antwerp, Belgium
• 3 Department of Pneumology, Antwerp University Hospital, Edegem, Belgium
• 4 Department of Internal Medicine and Pediatrics, Ghent University, Ghent, Belgium
• 5 Department of Oncology, Antwerp University Hospital, Edegem, Belgium
• 6 Center for Oncological Research (CORE), University of Antwerp, Antwerp, Belgium
• 7 Department of Otorhinolaryngology-Head and Neck Surgery, Antwerp University Hospital, Edegem, Belgium
• 8 Department of Translational Neurosciences, Antwerp University, Antwerp, Belgium

Head and neck neoplasms have a poor prognosis because of their late diagnosis. Finding a biomarker to detect these tumors in an early phase could improve the prognosis and survival rate. This literature review provides an overview of biomarkers, covering the different -omics fields to diagnose head and neck neoplasms in the early phase. To date, not a single biomarker, nor a panel of biomarkers for the detection of head and neck tumors has been detected with clinical applicability. Limitations for the clinical implementation of the investigated biomarkers are mainly the heterogeneity of the study groups (e.g., small population in which the biomarker was tested, and/or only including high-risk populations) and a low sensitivity and/or specificity of the biomarkers under study. Further research on biomarkers to diagnose head and neck neoplasms in an early stage, is therefore needed.

Introduction

Head and neck cancers account for 5% of all malignant tumors and are responsible for about 600,000 new cases and 300,000 deaths in the world annually. About 50% of the patients fail to achieve cure and cancer relapse occurs despite intensive combined treatment ( 1 , 2 ). To date, there is no adequate biomarker available for the diagnosis of head and neck cancer. However, it is expected that an earlier detection could improve the patient's outcome stage ( 3 – 7 ). In this review, we provide a general overview of biomarkers that were investigated to diagnose head and neck neoplasms in an early phase. Besides, we go into detail on the restrictions of these candidate biomarkers in the clinical practice.

Head and neck neoplasms are defined as benign, premalignant and malignant tumors above the clavicles, with exception of tumors of the brain, and spinal cord and esophagus ( 2 ). This includes tumors of the paranasal sinus, the nasal cavity, the salivary glands, the thyroid, and the upper aerodigestive tract (oral cavity, pharynx, and larynx) ( 8 , 9 ). Carcinomas of the head and neck preferably metastasize lymphogenic to the regional lymph nodes and it is only in an advanced stage that they metastasize hematogenic to the lungs, liver, and bones ( 1 ). The histopathology of the cancers differs from site to site, but the most common ones are squamous cell carcinomas, accounting for more than 85% of the head and neck neoplasms ( 8 , 9 ).

There are several known risk factors for the development of head and neck carcinomas. Prolonged exposure to the sun has been shown to be partly responsible for the genesis of skin and lip cancer ( 2 ). Epstein-Barr virus infection, living in a smoky environment and eating raw salted fish are important risk factors in the development of a nasopharyngeal carcinoma ( 1 , 8 ). Infection with human papilloma virus plays a significant role in the genesis of oropharyngeal cancer ( 8 ). Carcinomas of the paranasal sinuses are more frequently seen in woodworkers; particularly tropical hardwood forms an important trigger ( 1 ). Chewing betel nut, especially in Asia, plays a major role in the etiology of cancer of the oral cavity ( 1 ). Excessive use of tobacco and alcohol induces mucosal changes of the aerodigestive tract. These alterations play an important role in the genesis of malignant tumors ( 1 , 8 ). Besides tobacco and alcohol, other factors influence mucosal changes like nutritional deficiencies (in particular vitamin A and vitamin C in the context of insufficient intake of fresh fruits and vegetables) and genetic predisposition ( 1 , 8 ). In the development of tumors of the skin, mucosa, thyroid gland, parathyroid glands and the salivary glands, former exposure to ionizing radiation might also be of influence ( 2 ).

In comparison with other malignant tumors, head, and neck neoplasms are not common in the Western world. However, a rapid increase of the incidence of oropharyngeal cancers related to HPV in developed countries, has been shown ( 8 ). Although this incidence (and therefore the mortality rate) is lower compared to other cancers, patients with head and neck cancer have a poor prognosis, mainly due to the fact that these types of cancers are usually diagnosed at an advanced stage ( 3 – 7 ). One-third of the patients gets medical care in an early stage, while two-third are only diagnosed when they already entered an advanced stage ( 1 ). According to the WHO, the most common sites of head and neck neoplasms are the oral cavity, the larynx and the pharynx ( 8 ). The highest incidence of head and neck cancer is seen in South East Asia ( 8 ). Head and neck neoplasms are more prevalent in men than women and they most likely appear in the age range of 60–80 years. The average age of diagnosis is 62 years for men and 63 years for women ( 1 ).

Literature was searched through MEDLINE (PubMed Database). The search started in October 2017 and was limited to papers published in the last decade. The last database search was performed on March 31st, 2019. A combination of the following Mesh terms was used: “biomarkers, tumor”; “head and neck neoplasms”; “early diagnosis”; “volatile organic compounds”; “microbiota”; “papillomaviridae”; “radiomics,” leading to 247 articles. Based on the title and abstract, we selected 148 articles and after reading the full texts and assessing the quality of the texts, we eventually ended up with 102 articles on this topic. The quality of the studies was assessed by three researchers (SS, HK, and MG). To broaden our search and complete our electronic query, reference lists of articles already withheld, were also verified. Six more articles were included through this snowball method. In total, 108 articles were included in this review. The selection procedure is displayed in a flow diagram ( Figure 1 ).

Figure 1 . Flow diagram of article selection.

Since head and neck cancers have a poor prognosis and are most frequently diagnosed at an advanced stage, finding a biomarker for early diagnosis of these tumors, is of tremendous importance to reduce morbidity and mortality ( 3 , 10 ). Therefore, several biomarkers have been investigated so far. We provide a general overview of known biomarkers for diagnosis of head and neck neoplasms, including a discussion of the most promising markers. Strictly speaking, cancers of the upper part of the esophagus are also part of the head and neck tumors. In this literature review, however, they were not included. In Tables 1 – 8 , all the investigated diagnostic markers with brief additional information are presented. More details about the biomarkers with their restrictions and advantages are provided in the Supplementary Tables 1 – 5 . In the following paragraphs, we will discuss and present the biomarkers based on the applied -omics approach (genomics, proteomics, metabolomics, glycomics, volatomics, microbiomics, and radiomics).

Table 1 . Summary of genomics in head and neck neoplasms.

Table 2 . Summary of proteomics in head and neck neoplasms.

Table 3 . Summary of metabolomics in head and neck neoplasms.

Table 4 . Summary of glycomics in head and neck neoplasms.

Table 5 . Summary of volatomics in head and neck neoplasms.

Table 6 . Summary of microbiomics in head and neck neoplasms.

Table 7 . Summary of radiomics in head and neck neoplasms.

Table 8 . Summary of other biomarkers for head and neck neoplasms.

In the genomic approach, various methods were used to analyze genetic aberrations such as DNA sequencing, single nucleotide polymorphism analysis and hybridization techniques. Changes in gene expression are considered as a potential biomarker. A benefit of this approach is that it might also reveal the disease's underlying cause. On the other hand, there are also some demerits. Cancer is a condition in which many genes interact. Therefore, a single biomarker is probably insufficient to diagnose head and neck cancer and a biomarker panel of genes is recommended. It might also be unclear which post-transcriptional regulatory processes are involved ( 70 ). Table 1 and Supplementary Table 1 summarize the biomarkers involving genomics.

Promoter Hypermethylation

Promoter hypermethylation refers to the epigenetic process of abnormal methylation of CpG-islands in the promoter region. The promoter regions of genes initiate gene transcription and are usually not methylated ( 12 ). These alterations are associated with gene silencing in cancer ( 14 ). Methylation is suggested to be an early event in carcinogenesis ( 3 , 14 ), which makes it an interesting candidate as a biomarker. In this manner, early diagnosis is potentially achieved and consequently leads to a better prognosis. Different papers focused on promoter hypermethylation and show that specific genes of patients with head and neck neoplasms have a higher prevalence of methylation in comparison to a healthy control group ( 3 , 6 , 11 , 12 ). Sushma et al. suggest a promoter hypermethylation panel for oral squamous cell carcinoma (OSCC) consisting of the following genes: PTEN and p16 ( 12 ), which can be detected by a tissue biopsy. Guerrero et al. also suggest a promoter hypermethylation panel for detection of OSCC with the genes HOXA9 and NID2, identified via tissue biopsy or salivary rinses ( 3 ). However, despite a high specificity of promoter hypermethylation as a biomarker, its sensitivity was low. Using a panel of genes increased the sensitivity but came at the cost of a lowered specificity. Moreover, in these studies, the included population was small and/or consisted of high-risk patients. Further research would thus be necessary to explore this potential marker.

Epstein-Barr Virus DNA Load

Nasopharyngeal carcinoma is closely associated with a latent Epstein-Barr virus (EBV) infection ( 13 , 71 ). The EBV DNA load has biomarker potential [sensitivity of 95% (95% CI, 91–98%), specificity of 98% (95% CI, 96–99%) ( 14 )]. The serum concentration correlates to the tumor burden, resulting in a low specificity in early tumor stages but pointing toward the potential of a good prognostic biomarker (high concentrations indicating a greater tumor mass and thus negative prognosis). A combination of the EBV DNA load with a marker for early detection would increase the sensitivity for an early stage detection of nasopharyngeal carcinoma. Yang et al. therefore suggested to combine EBV DNA load with a panel of hypermethylation markers for detection of nasopharyngeal carcinoma ( 13 ), since methylation is an early event in carcinogenesis ( 3 , 13 ).

Several antibodies to EBV were also investigated as a biomarker for the diagnosis of nasopharyngeal carcinoma, for example anti-EBV capsid antigen IgA (IgA-VCA) ( 71 ). This is further discussed under the paragraph “proteomics.” Epstein-Barr virus DNA load [95% (95% confidence interval, 91–98%)] and IgA-VCA [sensitivity of 81% (95% CI, 73–87%)] are two of the most sensitive biomarkers found in the peripheral blood of nasopharyngeal carcinoma patients. When combined, a sensitivity of 99% was obtained. The specificity of EBV DNA and IgA-VCA was 98% (96–99%) and 96% (91–98%), respectively. On top of this, because of their different production mechanism, the combination of both markers could minimize false positive cases ( 14 ). With its high sensitivity and specificity, this biomarker panel of EBV DNA and IgA-VCA seems very promising in the diagnosis of nasopharyngeal carcinoma. Further prospective validation studies in independent cohorts are needed for confirmation and determination of its position in the diagnostic landscape.

Human Papillomavirus DNA Load

As already mentioned, human papillomavirus (HPV) and Epstein-Barr virus (EBV) are identified viral risk factors for head and neck neoplasms ( 72 ). Since HPV-16 accounts for >90% of HPV-DNA positive head and neck squamous cell carcinomas (HNSCC), it is regarded as the predominant HPV type in these specific malignancies ( 73 ). As a result, this is currently the only HPV type that has been studied in HNSCC.

The oral HPV-16 prevalence in healthy individuals is ~1%, suggesting HPV sequences could be used as a biomarker to detect the associated neoplasms ( 73 ). An important association has been demonstrated between HPV and oropharyngeal squamous cell carcinomas (OPSCC) on the one hand and some non-oropharyngeal head and neck squamous cell carcinomas on the other hand such as cancers of the oropharynx, larynx, and hypopharynx ( 73 ). In general, the survival rate was found to be higher for tumors that were HPV-positive compared to the neoplasms that were HPV-negative ( 24 ), stressing the prognostic property. Besides this classification, tumors can also be divided in HPV-driven and non-HPV-driven cancer. HPV-driven malignancies are, amongst other things, characterized by at least one HPV genome copy per tumor cell, as opposed to non-HPV-driven malignancies which express only low copy numbers of HPV DNA ( 23 ). Holzinger et al. state that HPV-driven OPSCC are classified as a distinct tumor entity and have specific characteristics, of which a better patient survival is of the biggest clinical importance ( 23 ). In contrast, patient survival in HPV-positive but non-HPV-driven OPSCC is similar to that of patients with HPV-negative cancer ( 23 ). Kreimer et al. showed, in a small subset of tumor specimens ( n = 9), that the sensitivity of antibodies to HPV-16 oncoprotein E6 (HPV-16 E6) for detection of HPV-driven OPC in blood, was exceptionally high (estimated at 100%, 95% CI = 47.8–100%) with a specificity that was also in this range (estimated at 100%, 95% CI = 39.8–100%) ( 22 ). Holzinger et al. supported this statement and showed that HPV-16 E6 seropositivity had a very high sensitivity (96%) and specificity (98%) to diagnose HPV-driven OPSCC. In contrast, the sensitivity for diagnosis of HNSCC excluding oropharyngeal carcinoma, was much lower (50%, 95% CI = 19–81%) despite the very high specificity (100%, 95% CI = 96–100%) ( 23 ).

Regarding sampling methods, HPV DNA load, and HPV antibodies can be detected in plasma as well as in saliva ( 23 , 24 , 26 , 72 ). Wang et al. demonstrated that HPV DNA could be detected in the plasma of 86% of the patients, compared to only 40% of the saliva of these same patients, indicating that plasma would be more informative to diagnose HPV-associated tumors despite the need for invasive sampling ( 24 ). Indeed, Kreimer et al. found that in OPSCC, the sensitivity for HPV-16 DNA detection in saliva was found to be between 45 and 82% compared to a sensitivity of ≥90% when HPV-16 antibodies were detected in serum ( 73 ).

These HPV-related markers do have their limitations as well. First of all, Kreimer et al. indicate that HPV-P16 E6 seronegative individuals have a low risk of developing HPV-driven OPC but that a screening test for these antibodies in the general population, would still lead to a significant amount of false-positive results. Thus, identifying the population at risk for OPSCC would improve the positive predictive value of this biomarker ( 73 ). Another remark, which is also noticed by Wang et al. and Kreimer et al., is that the published studies consisted of small study groups and studies with greater statistical power are required to determine the possibility of using these HPV related markers in detecting not only neoplasms of the oropharynx, but also the larynx and hypopharynx ( 24 , 73 ).

In the last two decades, altered microRNA expression were studied in different solid tumors and hematological malignancies. These microRNAs are single-stranded non-coding RNAs of 17–25 nucleotides that circulate in cell-free body fluids like blood plasma, serum, saliva, and urine. They can bind to a complementary site in 3′-untranslated regions of the messenger RNA (mRNA), thereby negatively regulating the gene expression via mRNA degradation or translational inhibition. Some microRNAs are upregulated in cancers and are regarded as oncogenes. Others are downregulated and are thus presumed to be tumor suppressor genes. Tumor-derived microRNAs are also released into the blood and might thus be potential early cancer detection markers. Furthermore, these microRNA profiles can be retrieved in a minimally invasive way and they are very stable, up to 28 days, in serum and plasma when stored at −20°C or below ( 7 , 15 ). There is a plethora of papers that studied microRNAs, resulting in a large number of microRNAs that have been identified. MicroRNAs have been studied as a marker for oral cancer ( 15 , 16 ) and larynx cancer ( 7 , 17 , 74 ). Promising results have been observed for a combination of miR-657 and miR-1287 as a marker for larynx carcinoma with a sensitivity of 86% and a specificity of 100% ( 74 ). Nevertheless, the result of this study needs to be interpreted with caution, since it was not yet validated in independent cohorts. The same counts for all other microRNAs that were under investigation in the aforementioned studies.

Interferons-Related Genes

The interferons belong to the family of multifunctional cytokines. These cytokines are produced by host cells in response to microbial infections and tumor cells. When secreted, they initiate a cascade through JAK/STAT signaling (Janus Kinases/Signal Transducer and Activator of Transcription) on their turn resulting in interferon-stimulated gene upregulation. To date, more than 400 interferon-stimulated genes have been reported ( 18 , 19 ). The first one to be recognized was ISG15 and has been described in many tumor biopsies from several cancers including oral squamous cell carcinoma ( 19 ). Due to this fact, it might not be a very specific marker for head and neck neoplasms. Another candidate gene is the interferon-inducible transmembrane protein 1 gene ( 18 ). The exact mechanism resulting in overexpression of interferon-stimulated genes in tumor cells is not yet clarified. Current ongoing studies aim to identify interferon-stimulated genes in diverse tumors including oral squamous cell carcinoma ( 18 ).

A promising approach to identify biomarkers is the study of cell proteins, called proteomics ( 29 , 70 ). Protein markers like carcinoembryonic antigen (CEA), prostate specific antigen (PSA), alpha-fetoprotein (AFP), and cancer antigen 125 (CA-125) already earned their place in the diagnosis or progression of several cancer types ( 75 ). In head and neck squamous cell carcinoma, the following markers have been studied: NFκB-p50, IκB ( 4 ), and the growth factor midkine ( 31 ) by blood sampling, and total salivary protein combined with soluble CD44 levels (solCD44) in saliva ( 5 ). In oral squamous cell carcinoma, a link has been shown with the protein receptor for activated C kinase 1 (RACK1) ( 29 ). Furthermore, there is also a place for detection of cytokines in saliva, for example IL-6 in oral leukoplakia or IL-1, IL-6, IL-8, VEGF, and TNF-α in tongue squamous cell carcinoma ( 27 , 28 ). Although some proteins were put forth as a biomarker for oral squamous cell carcinoma, several problems limit their clinical utility. First, there is a substantial heterogeneity of biomarker expression. Second, some proteins are also expressed in other pathologic situations such as inflammatory conditions resulting in a low specificity. Third, different experimental protocols were used which might explain the discrepancy between the identified biomarkers ( 70 ). Because of the heterogeneity of tumor markers in different patients, a combination of proteins might again be a better approach to increase their utility. Although protein markers seem very promising, there has not yet been identified a single or a combination of biomarkers to be effective for clinical use.

Several studies have suggested that autoantibodies that target specific tumor-associated antigens, could possibly be detected years before the tumor can be discovered through incidence screening or radiography ( 76 ). During early carcinogenesis, our immune system tries to remove precancerous lesions by generating an immune response to specific tumor-associated antigens ( 76 , 77 ), which makes them suitable for early detection of cancer lesions. Besides, autoantibodies are found in serum, which is favorable for screening. These individual autoantibodies, however, lack the sensitivity and specificity required for cancer screening ( 14 , 76 ).

First of all, some specific tumor-associated antigens can arise in different types of cancer (e.g., p53) and some of them are also present in diseases other than cancer, especially autoimmune diseases (e.g., rheumatoid arthritis, diabetes mellitus type 1, systemic lupus erythematosus…). They can also be detected in non-cancer individuals, and because of the heterogenic nature of cancer, a single autoantibody can only be found in 10–30% of patients with the same type of cancer. A panel of specific tumor-associated antigens might hence be the key to raise sensitivity and specificity ( 76 ). As mentioned before, there were several antibodies to Epstein-Barr virus (EBV) investigated as a biomarker for the diagnosis of nasopharyngeal carcinoma, anti-EBV capsid antigen IgA (IgA-VCA), and anti-EA IgG individually, appeared to have the greatest potential ( 71 ). A combination of IgA-VCA and Epstein-Barr virus DNA load could minimize false positive cases [( 14 ); Table 2 ].

Metabolomics

The term metabolome refers to the identification and quantification of all the small molecule metabolites (<1 kDa) in tissue or biofluids produced during cell metabolism ( 36 ). It is directly linked to cell physiology and thus the result of both physiological and pathological metabolic processes. This explains the current use of metabolomics for discovery of novel biomarkers for cancer diagnosis ( 36 ). However, there are some drawbacks to its use. Because of the high complexity of the metabolome, interpretation of data is difficult, urging the use of deep learning and data mining techniques. There is also a big difference in concentrations ranging for nanomolar to millimolar. Diet, sex, age, drugs, environment, and lifestyle might interfere with the metabolite concentration ( 70 ). There are some papers describing metabolome-related biomarkers in oral cancer. Bernabe et al. found that the plasma and salivary cortisol levels were significantly higher in patients with oral squamous cell carcinoma in comparison with healthy controls and patients with oral leukoplakia ( 33 ). Large validation studies remain indispensable to confirm the value of metabolites in the diagnosis of head and neck neoplasms. To date, research on metabolites as a potential biomarker is still in the discovery phase.

Compared to genomics and proteomics, there is few research on glycomics. This approach focuses on the modifications of glycoconjugates related to cancer. Glycolipids and glycoproteins are glycoconjugates and are important constituents of the cell membrane. Glycosylation is important in the process of protein modification and its action relies on the function of glycosyltransferases and glycosidases in various tissues and cells. Glycoconjugates are released into the circulation because of continuously shedding and/or secretion by cancer cells or the increased cell turnover and could thus be detected in body fluids to be used as tumor markers. Especially glycoconjugates in oral cancer, which are in direct contact with saliva, seem to be promising. The major types of glycosylation are sialylation and fucosylation, which terminally modify proteins that are important in the vital biological functions. There have been reported significantly elevated levels of sialic acid, α-l-fucosidase, and total protein in oral cancer patients and there is also a link with oral cancer progression. However, there is need for further research to determine the role of these biomarkers in oral cancer development ( 37 , 38 ).

Volatomics recently emerged as new research field for early disease diagnosis. This encompasses volatile organic compounds (VOCs) in nano- to picomolar concentrations, which are the gaseous end products from endogenous metabolic changes, digestion, microbiome, inflammation, and oxidative stress. VOCs can be detected in breath, urine, feces, blood, saliva, skin, and sweat, and hence, serve as attractive biomarkers, as it is completely non-invasive, relatively cheap, and provides rapid results ( 78 ). VOCs have already shown clinical potential as biomarkers for lung ( 79 ), gastric ( 80 ), breast ( 81 ), prostate ( 82 ), and mesothelioma cancer ( 83 ), and since carcinogenesis is related to inflammation and metabolic changes, VOCs could also have added value as diagnostic biomarkers for head and neck cancer ( Table 5 ).

The study of VOCs in exhaled breath (breathomics) is potentially the most important since the sample is unlimitedly present and sampling causes no side effects for the patient. Using gas chromatography-mass spectrometry (GC-MS), García et al. found an increase of 2-butanone, ethanol, 2,3-butanediol, 9-tetradecen-1-ol, and octane, cycloheptane, and cyclononane derivates in the breath of head and neck cancer patients compared to healthy controls [( 39 ); Table 5 ]. The increase in ethanol was also found in head and neck squamous cell carcinoma (HNSCC) patients by Gruber et al., next to 2-propenenitrile and undecane ( 40 ), which discriminated patients from healthy controls and even patients with benign conditions with 77% sensitivity and 90% specificity. Hydrogen cyanide was found to be increased in the breath of HNSCC patients compared to controls using SIFT-MS and allowed discrimination with 91% sensitivity and 76% specificity ( 52 ).

The VOCs 4-chlorobenzene and methanethiol discriminated HNSCC patients from lung cancer patients with 100% accuracy ( 48 ), showing potential to use breath analysis for differential diagnosis, albeit with low study participants and a risk of overfitting the differentiating models.

Next to spectrometric analysis, VOCs can be detected by sensor technology [electronic noses (eNoses)] that recognizes the bulk of VOCs as a breath print, but without identifying individual VOCs. Using eNoses, HNSCC patients could be differentiated from controls with sensitivities and specificities ranging between 77–90% and 80–90%, respectively, underlining the difference in breath print and their use as diagnostic tool ( 40 , 41 , 43 ). Also, eNoses have shown to be promising for differential diagnosis, in which the breathprint of HNSCC patients was different from those with lung cancer, colon cancer and bladder cancer with, respectively, 85, 79, and 80% sensitivity and 84, 81, and 86% specificity ( 45 , 49 , 54 ).

Two studies discriminated patients with papillary thyroid carcinoma (PTC) from healthy controls with both 100% sensitivity and specificity ( 42 ). Although one based this discrimination on an increase of ethyl hexanol, 4-hydroxybutanoic acid, and a decrease in phenol ( 42 ), the other did not report changes in these compounds ( 46 ).

Differences in dibutylhydroxytoluene, dimethyl disulphide, decamethylcyclopentasiloxane, methyl ethyl ketone, n-heptane, p-xylene, toluene, I-heptene were found in breath between patients with oral squamous cell carcinoma and controls ( 47 ). However, based upon VOCs from saliva in these patients, an increase in 1,3-butanediol and hexadecenoic acid and a decrease in 2-pentanone and undecane allowed their discrimination from healthy controls with 96% sensitivity and 95% specificity ( 53 ). This decrease of undecane is in contrast to an increase found in breath in HNSCC ( 40 ) and patients with PTC ( 46 ). Furthermore, saliva analysis of the single VOCs 1,4-dichlorobenzene, 1,2-decanediol, 2,5-bis1,1-dimethylethylphenol, and E-3-decen-2-ol allowed to discriminate HNSCC patients from controls with a sensitivity and specificity between 80–100% and 80–100%, respectively ( 51 ), again being different to VOCs found in exhaled breath and urine ( 50 ).

Lastly, analysis of VOCs from the mucus of 6 patients with malignant glottic lesions found butyric acid, pentanoic acid, hexanoic acid, and heptanoic acid to be different compared to controls ( 44 ).

Carcinogenesis is related to an altered metabolism, upregulated aerobic glycolysis (known as the Warburg effect) and induces oxidative stress ( 84 , 85 ). This liberates highly reactive oxygen species (ROS) which induce lipid peroxidation of (poly)unsaturated omega-3 and omega-6 fatty acids (PUFA) in the cellular membranes, mainly generating alkanes and aldehydes as end products ( 86 ). Considering the high number of hydrocarbons detected in several matrices, this plays a major role in HNC and therefore, are biomarkers of interest. Aldehydes are furthermore generated in vivo in signal transduction, genetic regulation and cellular proliferation. In cancer, an increase in aldehyde dehydrogenase is seen as malignant cells proliferate. This causes aldehyde oxidation, resulting in an increased aldehyde concentration in blood and breath, which is reflected by the large number of aldehydes found in these matrices. However, longer chain aldehydes are potentially by-products of digestion and their origin needs to be explored. Also, several organic (carboxylic) acids have been found, which are the main products of proteolysis. Alcohols have 2 major pathways to be induced in vivo : by ingestion or as product from the hydrocarbon metabolism by cytochrome P450 enzymes and the alcohol dehydrogenase activity ( 86 ). Alcohols, next to carboxylic acids, are products of hydrolysis of esters. The cytochrome P450 enzymes hydroxylate lipid peroxidation biomarkers to produce alcohols, which are found by several studies. Special attention can be given to phenol: although phenol may be derived from benzene metabolism, it is most likely to be from exogenous origin, since it is a by-product of the sampling materials used.

Taken together, it seems that not one VOC is able to accurately discriminate between several types of head and neck cancer types and controls. Hence, the combination of several biomarkers into panels will therefore be key in future research as stressed by the success of eNoses that react to the bulk of VOCs in the breath and the success of biomarker panels. However, the discordance in VOCs can be explained due to a difference in technology, sampling and by the difference in concentration range. Furthermore, as with metabolites, the volatilome delivers high throughput data, complicating the interpretation of the data, and urging the use of deep learning and data mining techniques. Next to this, also diet, sex, age, drugs, environment, and lifestyle, and the microbiome can interfere with the VOC concentration and induce changes. Hence, the external influence may not be underestimated. In several trials, ethanol, and 2-propenenitrile have been identified as possible biomarkers. However, these can be linked to alcohol abuse and smoking, which are both risk factors for HNSCC, and could therefore have biased the results if not corrected for this. Furthermore, the finding that hydrogen cyanide can serve as biomarker raises concerns about the origin of this VOC and its correlation with HNSCC since hydrogen cyanide is known to be released by the microbiome and could result from exogenous exposure to exhausted fumes and cigarette smoke. Despite this, it can also be a by-product of cellular respiration. Hence, for multiple VOCs, their origin and its role as diagnostic marker remains to be determined.

Microbiomics

The human body is colonized by numerous microbes that include viruses, bacteria and microbial eukaryotes. Studying these microbial communities is referred to as “microbiomics” ( 64 ). The microbiome maintains homeostasis and has a dynamic association with the human host ( 61 , 62 ). When dysbiosis or ecological imbalance arises, processes leading to a diseased state develop ( 62 ). Some studies that have already been published, showed an association between microbiome variations and cancer. These studies have demonstrated that the mucosal layers of the mouth, throat, stomach, and intestines are colonized by commensal bacteria, which play an important part in normal human health and can therefore also play a role in the development of malignancies. For example, Helicobacter pylori infection can induce gastric cancer through gastric dysbiosis ( 63 ).

To date, few has been published about microbiomics as a (diagnostic) biomarker in head and neck cancer. Most studies focus on the oral microbiome, which can be used in the detection of oral cancer, especially oral squamous cell carcinoma (OSCC) ( 55 ). There are many bacterial species in the oral cavity involved in the genesis of oral cancer which can be explained through inflammation-induced DNA damage of epithelial cells caused by endotoxins secreted by these micro-organisms ( 55 ). The link between microorganisms and head and neck squamous cell carcinoma (HNSCC) is not yet adequately studied ( 57 ). There are some studies that have detected oral microbial alternations in consumers of alcohol, tobacco and betel nut. The association between these known oral cancer risk factors and microbial alterations should be taken into account ( 55 , 61 ). It could be possible that the microbiome helps change an environmental exposure into a carcinogenic effect ( 61 ). Lee et al. studied microbial differences between oral cancer patients, patients with epithelial precursor lesions and healthy controls ( 55 ). They found a significant abundance of 5 genera in the salivary microbiome ( Bacillus, Enterococcus, Parvimonas, Slackia , and Peptostreptococcus ) of cancer patients when compared to patients with epithelial precursor lesions. These changes in the composition of the microbiome could thus be a potential biomarker for monitoring the transformation of oral precursor lesions into oral cancer ( 55 ). The use of a microbiome panel ( Rothia, Haemophilus, Corynebacterium, Paludibacter, Porphyromonas, Oribacterium , and Capnocytophaga ) could detect oral cavity cancer and oropharyngeal cancer by oral rinse with an accuracy of 82% ( 60 ).

The association between variations in the human microbiome and throat cancer has also been studied. Wang et al. studied microbial markers in the saliva of patients with throat cancer (hypopharyngeal carcinoma and laryngeal carcinoma) and in the saliva of patients with vocal cord polyps and healthy controls ( 63 ). They revealed a significant difference in the microbiome of throat cancer patients vs. patients with vocal cord polyps and healthy controls. The following genera were found to be associated with throat cancer: Bacteroides, Pseudomonas, Ruminiclostridium , and Aggregatibacter . Additionally, they observed a significant reduction in microbial diversity in throat cancer patients ( 63 ). This reduction in diversity of the microbiome is also found in other studies concerning oral cancer ( 57 , 60 ) and head and neck squamous cell carcinoma (HNSCC) ( 62 ). Zhao et al. on the other hand, observed a greater bacterial diversity in OSCC tissue when compared to healthy tissue ( 56 ).

Table 7 shows potential microbial biomarkers for head and neck cancer. Few studies have shown that the expression of Fusobacterium is elevated in the tumor tissue of patients with OSCC ( 56 , 58 ) and HNSCC ( 62 ).

Although studies of bacteria and their role in carcinogenesis of colorectal cancer are increasing rapidly, the association between microbiome and head and neck cancer has not been substantially studied. The published studies do not specifically focus on early diagnosis of head and neck neoplasms and have only identified some potential biomarkers based on difference in expression between head and neck cancer populations and (healthy) control populations. These studies also use different sequencing technologies to measure the abundance of microbiota. There is need for further, more standardized research before microbial variations can be considered a diagnostic biomarker for head and neck neoplasms.

Radiomics comprises the high-throughput mining of advanced quantitative features to objectively and quantitatively describe tumor phenotypes. It makes use of standard of care radiologic images which are subject to advanced mathematical algorithms to detect tumor characteristics that might be missed by the radiologist's eye. This method relies on big data and supports the clinical decision to diagnose, prognose, and predict -amongst others- cancer ( 87 ). Yip and Aerts extensively reviewed the applications and limitations of this new -omics approach ( 88 ). We kindly refer to their paper for detailed information.

In head and neck cancer, radiomics has also entered the scene. Here, we focus on papers that aimed to diagnose HNC based on radiomics features. In patients with a thyroid nodule, a radiomics score (calculated from ultrasound images) was evaluated against the standard method used for the diagnosis of thyroid nodules as set by the American College of radiology, the TI-RADS score. The radiomics score was able to discriminate malignant from benign nodules with an accuracy of 93% [95% CI 88.4–97.7%]. The radiomics score performed better compared to the TI-RADS if scored by junior radiologists ( 66 ). In a similar population, a radiomics predictive model was constructed based on computer tomography (CT) images which was able to predict the immunohistochemical characteristics of suspected thyroid nodules [cytokeratin 19 (AUC 0.87, sensitivity 93%, and specificity 73%), galectin 3 (AUC 0.85, sensitivity 87%, and specificity 76%), and thyroperoxidase (AUC 0.84, sensitivity 86%, and specificity 75%)] ( 65 ). It seems clear that radiomics will become a meritorious player in the diagnostic landscape of thyroid cancer. Given the high prevalence of -largely benign- thyroid nodules, a good biomarker to discriminate benign from malignant nodules is indispensable. From the papers published to date, radiomics seems promising as a biomarker in this field.

Parmar et al. were able to identify 10 radiomic clusters in a dataset of CT images from 136 patients with HNSCC that were significantly associated with tumor stage ( 67 ). In addition, they created an HNC signature based on multivariate analysis that was highly predictive for tumor stage (AUC = 0.80). In a similar population consisting of 127 HNSCC patients, Ren et al. used magnetic resonance imaging (MRI) axial fact-suppressed T2-weighted (T2W) and contrast-enhanced T1-weighted (ceT1W) images to identify a radiomics signature for preoperative staging (I-II vs. III-IV). The radiomics signature based on ceT1W images (AUC 0.853) performed best in discriminating stage I-II from stage III-IV followed by combined T2W and ceT1W images (AUC 0.849) ( 68 ). In the training cohort, radiomics performed better than visual assessment by an experienced radiologist, however, this was no longer the case in the testing cohort. In a recent paper of Huang et al., the radiomics' potential to identify treatment-relevant subtypes of HNSCC was tested on pretreatment CT scans in a cohort of 113 patients. Moderate AUC's varying from 0.71 to 0.79 were observed in the prediction of HPV positivity, three DNA methylation subtypes and a mutation of NSD1 in these patients ( 89 ). Radiomics might thus be of additional value to define subtypes in a non-invasive manner. However, several tumors will be misclassified based on radiomics alone, making the diagnostic capacity underperforming.

Besides tumor diagnosis, radiomics is also subject of investigation in predictive ( 90 – 92 ) and prognostic models ( 67 , 93 – 96 ), to evaluate local tumor control ( 97 – 99 ), and HPV status ( 100 , 101 ).

A challenge in radiomics remains the fact that the extracted feature quality is affected by tumor segmentation methods used to define regions over which to calculate features. Consistent radiomics analysis across multiple institutions that use different segmentation algorithms are not obvious. This is particularly the case for Positron Emission Tomography (PET), where a limited resolution, a high noise component related to the limited stochastic nature of the raw data, and the wide variety of reconstruction options might confound quantitative feature metrics ( 102 ). Standardized scanner protocols and image reconstruction harmonization are thus of tremendous importance to make the transfer of radiomics features possible between institutions. Several papers already tried to identify the pitfalls of radiomics and the relevant features that delay interchangeability to make sure that radiomics becomes a full-fledged biomarker in future cancer diagnosis ( 103 ).

Mean platelet volume (MPV) was found to be significantly higher in PTC patients when compared to benign goiter patients and health controls (8.05, 7.57, and 7.36 fl, respectively; p = 000.1; see Table 8 ). Moreover, MPV significantly decreased when these patients were surgically treated [8.05 vs. 7.60 fl; p = 0.005; ( 69 )]. The quality of this study however was suboptimal. The study was retrospective and had a relatively small sample size [ n = 66; ( 69 )].

In this review, we assessed a large number of potential biomarkers for the diagnosis of head and neck neoplasms and included tables providing a detailed overview of the state-of-the-art investigated biomarkers. All proposed biomarkers have their advantages and restrictions. Many biomarkers lack the sensitivity and/or specificity that is required for utilization in the clinical practice. Therefore, individual biomarkers are frequently combined into biomarker panels to increase these diagnostic values.

Furthermore, many studies had a relatively small sample size and therefore lacked statistical power. Additionally, a great amount of these studies was retrospective. Larger, prospective studies should thus be performed in the future. Also, other elements should be kept in mind when planning future biomarker research. For example, a considerable part of the studies that were reviewed included healthy controls as control population. However, one should recognize that biomarkers in the clinical practice would be used in patients at risk for certain types of head and neck neoplasms. Future studies should thus consider including appropriate patients at risk and/or patients known with a premalignant lesion when composing their control population. Most of the described markers have been studied for one specific type of head and neck neoplasm and can therefore not be extrapolated to head and neck neoplasms in general. The diagnostic biomarkers that were reviewed, were frequently studied in patients from one specific geographical location. As a consequence, the biomarker might be influenced by race, genetics, lifestyle, and carcinogenic exposure ( 104 ). India is a high-risk region for the development of oral squamous cell carcinoma ( 12 , 18 , 19 , 38 ). Hence, a biomarker that has been evaluated in an Indian community might be applicable only to high-risk regions. The study groups should thus also investigate this marker in another population that is less at risk for the occurrence of oral squamous cell carcinoma and study its applicability worldwide. Also, other variables such as race, eating habits and environmental exposure should be taken into account. In this manner, when reviewing the literature, we noticed a large amount of variability when studying biomarkers for head and neck cancer. Standardized research would therefore be a necessity when considering future studies concerning these tumors.

The sampling method of the biomarkers and the analysis of the specimen also play a determining role in the utilization of the marker in the clinical practice. For example, saliva and exhaled breath present an attractive non-invasive alternative to tissue or serum testing. Serum is easily accessible, relatively cheap, and can be used in a minimally invasive way, but saliva and breath offer some other advantages. A non-health practitioner can easily collect these samples in a non-invasive way, they are easy to store, the sample cost is relatively low and repeated (unlimited) samples can easily be acquired because it is a comfortable sampling method for patients ( 34 , 37 ).

To our opinion, microRNA, gene hypermethylation, HPV-related markers, and a panel of proteins seem to be the biomarkers with the most promising potential of becoming a diagnostic biomarker for head and neck neoplasms based on the reported sensitivity, specificity, positive, and negative predictive values that can be obtained. In certain tumor types, such as thyroid cancer, also radiomics might become of importance in the diagnostic landscape and replace invasive needle biopsies. Hereto, radiomic signatures need to be identified that are able to discriminate benign from malignant lesions. A challenge here is to make the radiomic signatures interchangeable between institutes. Biomarkers studying the metabolome, glycome, volatilome, and microbiome still need to be thoroughly investigated before they can be considered as biomarkers.

Most of the head and neck tumors are diagnosed in an advanced stage. Hence, besides advancement in treatment of head and neck neoplasms, early detection of these tumors could play a significant role in improving the prognosis of these patients. With this in mind, a lot of research has already been done on clinically applicable single biomarkers or a panel of biomarkers, for early detection of head and neck tumors. We reviewed over 50 markers, all with their advantages and limitations. To date, a biomarker to diagnose head and neck neoplasms useful for clinical practice, has not yet been identified nor validated. Therefore, further research of biomarkers to diagnose head and neck neoplasms in an early stage is still needed.

Author Contributions

HK, SS, and MG collected, analyzed, and interpreted the data after which they drafted the article. This excludes the part concerning volatomics, which should be accredited to KL and the part concerning radiomics, which should be accredited to KJL. KJL, KL, JM, OV, BD, and PS did a critical revision of the article and gave their final approval of the version to be published. All authors contributed to the article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

The authors would like to thank the University of Antwerp, Belgium, for their guidance and support regarding this literature review.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fonc.2020.01020/full#supplementary-material

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Keywords: head and neck neoplasms, biomarker, genomics, proteomics, metabolomics, volatomics, microbiomics, radiomics

Citation: Konings H, Stappers S, Geens M, De Winter BY, Lamote K, van Meerbeeck JP, Specenier P, Vanderveken OM and Ledeganck KJ (2020) A Literature Review of the Potential Diagnostic Biomarkers of Head and Neck Neoplasms. Front. Oncol. 10:1020. doi: 10.3389/fonc.2020.01020

Received: 02 February 2020; Accepted: 22 May 2020; Published: 26 June 2020.

Reviewed by:

Copyright © 2020 Konings, Stappers, Geens, De Winter, Lamote, van Meerbeeck, Specenier, Vanderveken and Ledeganck. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Kristien J. Ledeganck, kristien.ledeganck@uantwerp.be

† These authors have contributed equally to this work

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Writing a Literature Review

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A literature review is a document or section of a document that collects key sources on a topic and discusses those sources in conversation with each other (also called synthesis ). The lit review is an important genre in many disciplines, not just literature (i.e., the study of works of literature such as novels and plays). When we say “literature review” or refer to “the literature,” we are talking about the research ( scholarship ) in a given field. You will often see the terms “the research,” “the scholarship,” and “the literature” used mostly interchangeably.

Where, when, and why would I write a lit review?

There are a number of different situations where you might write a literature review, each with slightly different expectations; different disciplines, too, have field-specific expectations for what a literature review is and does. For instance, in the humanities, authors might include more overt argumentation and interpretation of source material in their literature reviews, whereas in the sciences, authors are more likely to report study designs and results in their literature reviews; these differences reflect these disciplines’ purposes and conventions in scholarship. You should always look at examples from your own discipline and talk to professors or mentors in your field to be sure you understand your discipline’s conventions, for literature reviews as well as for any other genre.

A literature review can be a part of a research paper or scholarly article, usually falling after the introduction and before the research methods sections. In these cases, the lit review just needs to cover scholarship that is important to the issue you are writing about; sometimes it will also cover key sources that informed your research methodology.

Lit reviews can also be standalone pieces, either as assignments in a class or as publications. In a class, a lit review may be assigned to help students familiarize themselves with a topic and with scholarship in their field, get an idea of the other researchers working on the topic they’re interested in, find gaps in existing research in order to propose new projects, and/or develop a theoretical framework and methodology for later research. As a publication, a lit review usually is meant to help make other scholars’ lives easier by collecting and summarizing, synthesizing, and analyzing existing research on a topic. This can be especially helpful for students or scholars getting into a new research area, or for directing an entire community of scholars toward questions that have not yet been answered.

What are the parts of a lit review?

Most lit reviews use a basic introduction-body-conclusion structure; if your lit review is part of a larger paper, the introduction and conclusion pieces may be just a few sentences while you focus most of your attention on the body. If your lit review is a standalone piece, the introduction and conclusion take up more space and give you a place to discuss your goals, research methods, and conclusions separately from where you discuss the literature itself.

Introduction:

• An introductory paragraph that explains what your working topic and thesis is
• A forecast of key topics or texts that will appear in the review
• Potentially, a description of how you found sources and how you analyzed them for inclusion and discussion in the review (more often found in published, standalone literature reviews than in lit review sections in an article or research paper)
• Summarize and synthesize: Give an overview of the main points of each source and combine them into a coherent whole
• Analyze and interpret: Don’t just paraphrase other researchers – add your own interpretations where possible, discussing the significance of findings in relation to the literature as a whole
• Critically Evaluate: Mention the strengths and weaknesses of your sources
• Write in well-structured paragraphs: Use transition words and topic sentence to draw connections, comparisons, and contrasts.

Conclusion:

• Summarize the key findings you have taken from the literature and emphasize their significance
• Connect it back to your primary research question

How should I organize my lit review?

Lit reviews can take many different organizational patterns depending on what you are trying to accomplish with the review. Here are some examples:

• Chronological : The simplest approach is to trace the development of the topic over time, which helps familiarize the audience with the topic (for instance if you are introducing something that is not commonly known in your field). If you choose this strategy, be careful to avoid simply listing and summarizing sources in order. Try to analyze the patterns, turning points, and key debates that have shaped the direction of the field. Give your interpretation of how and why certain developments occurred (as mentioned previously, this may not be appropriate in your discipline — check with a teacher or mentor if you’re unsure).
• Thematic : If you have found some recurring central themes that you will continue working with throughout your piece, you can organize your literature review into subsections that address different aspects of the topic. For example, if you are reviewing literature about women and religion, key themes can include the role of women in churches and the religious attitude towards women.
• Qualitative versus quantitative research
• Empirical versus theoretical scholarship
• Divide the research by sociological, historical, or cultural sources
• Theoretical : In many humanities articles, the literature review is the foundation for the theoretical framework. You can use it to discuss various theories, models, and definitions of key concepts. You can argue for the relevance of a specific theoretical approach or combine various theorical concepts to create a framework for your research.

What are some strategies or tips I can use while writing my lit review?

Any lit review is only as good as the research it discusses; make sure your sources are well-chosen and your research is thorough. Don’t be afraid to do more research if you discover a new thread as you’re writing. More info on the research process is available in our "Conducting Research" resources .

As you’re doing your research, create an annotated bibliography ( see our page on the this type of document ). Much of the information used in an annotated bibliography can be used also in a literature review, so you’ll be not only partially drafting your lit review as you research, but also developing your sense of the larger conversation going on among scholars, professionals, and any other stakeholders in your topic.

Usually you will need to synthesize research rather than just summarizing it. This means drawing connections between sources to create a picture of the scholarly conversation on a topic over time. Many student writers struggle to synthesize because they feel they don’t have anything to add to the scholars they are citing; here are some strategies to help you:

• It often helps to remember that the point of these kinds of syntheses is to show your readers how you understand your research, to help them read the rest of your paper.
• Writing teachers often say synthesis is like hosting a dinner party: imagine all your sources are together in a room, discussing your topic. What are they saying to each other?
• Look at the in-text citations in each paragraph. Are you citing just one source for each paragraph? This usually indicates summary only. When you have multiple sources cited in a paragraph, you are more likely to be synthesizing them (not always, but often
• Read more about synthesis here.

The most interesting literature reviews are often written as arguments (again, as mentioned at the beginning of the page, this is discipline-specific and doesn’t work for all situations). Often, the literature review is where you can establish your research as filling a particular gap or as relevant in a particular way. You have some chance to do this in your introduction in an article, but the literature review section gives a more extended opportunity to establish the conversation in the way you would like your readers to see it. You can choose the intellectual lineage you would like to be part of and whose definitions matter most to your thinking (mostly humanities-specific, but this goes for sciences as well). In addressing these points, you argue for your place in the conversation, which tends to make the lit review more compelling than a simple reporting of other sources.

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• How to Write a Literature Review | Guide, Examples, & Templates

How to Write a Literature Review | Guide, Examples, & Templates

Published on January 2, 2023 by Shona McCombes . Revised on September 11, 2023.

What is a literature review? A literature review is a survey of scholarly sources on a specific topic. It provides an overview of current knowledge, allowing you to identify relevant theories, methods, and gaps in the existing research that you can later apply to your paper, thesis, or dissertation topic .

There are five key steps to writing a literature review:

• Search for relevant literature
• Evaluate sources
• Identify themes, debates, and gaps
• Outline the structure
• Write your literature review

A good literature review doesn’t just summarize sources—it analyzes, synthesizes , and critically evaluates to give a clear picture of the state of knowledge on the subject.

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Table of contents

What is the purpose of a literature review, examples of literature reviews, step 1 – search for relevant literature, step 2 – evaluate and select sources, step 3 – identify themes, debates, and gaps, step 4 – outline your literature review’s structure, step 5 – write your literature review, free lecture slides, other interesting articles, frequently asked questions, introduction.

• Quick Run-through
• Step 1 & 2

When you write a thesis , dissertation , or research paper , you will likely have to conduct a literature review to situate your research within existing knowledge. The literature review gives you a chance to:

• Demonstrate your familiarity with the topic and its scholarly context
• Develop a theoretical framework and methodology for your research
• Position your work in relation to other researchers and theorists
• Show how your research addresses a gap or contributes to a debate
• Evaluate the current state of research and demonstrate your knowledge of the scholarly debates around your topic.

Writing literature reviews is a particularly important skill if you want to apply for graduate school or pursue a career in research. We’ve written a step-by-step guide that you can follow below.

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Writing literature reviews can be quite challenging! A good starting point could be to look at some examples, depending on what kind of literature review you’d like to write.

• Example literature review #1: “Why Do People Migrate? A Review of the Theoretical Literature” ( Theoretical literature review about the development of economic migration theory from the 1950s to today.)
• Example literature review #2: “Literature review as a research methodology: An overview and guidelines” ( Methodological literature review about interdisciplinary knowledge acquisition and production.)
• Example literature review #3: “The Use of Technology in English Language Learning: A Literature Review” ( Thematic literature review about the effects of technology on language acquisition.)
• Example literature review #4: “Learners’ Listening Comprehension Difficulties in English Language Learning: A Literature Review” ( Chronological literature review about how the concept of listening skills has changed over time.)

You can also check out our templates with literature review examples and sample outlines at the links below.

Download Word doc Download Google doc

Before you begin searching for literature, you need a clearly defined topic .

If you are writing the literature review section of a dissertation or research paper, you will search for literature related to your research problem and questions .

Make a list of keywords

Start by creating a list of keywords related to your research question. Include each of the key concepts or variables you’re interested in, and list any synonyms and related terms. You can add to this list as you discover new keywords in the process of your literature search.

• Social media, Facebook, Instagram, Twitter, Snapchat, TikTok
• Body image, self-perception, self-esteem, mental health
• Generation Z, teenagers, adolescents, youth

Search for relevant sources

Use your keywords to begin searching for sources. Some useful databases to search for journals and articles include:

• Your university’s library catalogue
• Google Scholar
• Project Muse (humanities and social sciences)
• Medline (life sciences and biomedicine)
• EconLit (economics)
• Inspec (physics, engineering and computer science)

You can also use boolean operators to help narrow down your search.

Make sure to read the abstract to find out whether an article is relevant to your question. When you find a useful book or article, you can check the bibliography to find other relevant sources.

You likely won’t be able to read absolutely everything that has been written on your topic, so it will be necessary to evaluate which sources are most relevant to your research question.

For each publication, ask yourself:

• What question or problem is the author addressing?
• What are the key concepts and how are they defined?
• What are the key theories, models, and methods?
• Does the research use established frameworks or take an innovative approach?
• What are the results and conclusions of the study?
• How does the publication relate to other literature in the field? Does it confirm, add to, or challenge established knowledge?
• What are the strengths and weaknesses of the research?

Make sure the sources you use are credible , and make sure you read any landmark studies and major theories in your field of research.

You can use our template to summarize and evaluate sources you’re thinking about using. Click on either button below to download.

Take notes and cite your sources

As you read, you should also begin the writing process. Take notes that you can later incorporate into the text of your literature review.

It is important to keep track of your sources with citations to avoid plagiarism . It can be helpful to make an annotated bibliography , where you compile full citation information and write a paragraph of summary and analysis for each source. This helps you remember what you read and saves time later in the process.

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To begin organizing your literature review’s argument and structure, be sure you understand the connections and relationships between the sources you’ve read. Based on your reading and notes, you can look for:

• Trends and patterns (in theory, method or results): do certain approaches become more or less popular over time?
• Themes: what questions or concepts recur across the literature?
• Debates, conflicts and contradictions: where do sources disagree?
• Pivotal publications: are there any influential theories or studies that changed the direction of the field?
• Gaps: what is missing from the literature? Are there weaknesses that need to be addressed?

This step will help you work out the structure of your literature review and (if applicable) show how your own research will contribute to existing knowledge.

• Most research has focused on young women.
• There is an increasing interest in the visual aspects of social media.
• But there is still a lack of robust research on highly visual platforms like Instagram and Snapchat—this is a gap that you could address in your own research.

There are various approaches to organizing the body of a literature review. Depending on the length of your literature review, you can combine several of these strategies (for example, your overall structure might be thematic, but each theme is discussed chronologically).

Chronological

The simplest approach is to trace the development of the topic over time. However, if you choose this strategy, be careful to avoid simply listing and summarizing sources in order.

Try to analyze patterns, turning points and key debates that have shaped the direction of the field. Give your interpretation of how and why certain developments occurred.

If you have found some recurring central themes, you can organize your literature review into subsections that address different aspects of the topic.

For example, if you are reviewing literature about inequalities in migrant health outcomes, key themes might include healthcare policy, language barriers, cultural attitudes, legal status, and economic access.

Methodological

If you draw your sources from different disciplines or fields that use a variety of research methods , you might want to compare the results and conclusions that emerge from different approaches. For example:

• Look at what results have emerged in qualitative versus quantitative research
• Discuss how the topic has been approached by empirical versus theoretical scholarship
• Divide the literature into sociological, historical, and cultural sources

Theoretical

A literature review is often the foundation for a theoretical framework . You can use it to discuss various theories, models, and definitions of key concepts.

You might argue for the relevance of a specific theoretical approach, or combine various theoretical concepts to create a framework for your research.

Like any other academic text , your literature review should have an introduction , a main body, and a conclusion . What you include in each depends on the objective of your literature review.

The introduction should clearly establish the focus and purpose of the literature review.

Depending on the length of your literature review, you might want to divide the body into subsections. You can use a subheading for each theme, time period, or methodological approach.

As you write, you can follow these tips:

• Summarize and synthesize: give an overview of the main points of each source and combine them into a coherent whole
• Analyze and interpret: don’t just paraphrase other researchers — add your own interpretations where possible, discussing the significance of findings in relation to the literature as a whole
• Critically evaluate: mention the strengths and weaknesses of your sources
• Write in well-structured paragraphs: use transition words and topic sentences to draw connections, comparisons and contrasts

In the conclusion, you should summarize the key findings you have taken from the literature and emphasize their significance.

When you’ve finished writing and revising your literature review, don’t forget to proofread thoroughly before submitting. Not a language expert? Check out Scribbr’s professional proofreading services !

This article has been adapted into lecture slides that you can use to teach your students about writing a literature review.

Scribbr slides are free to use, customize, and distribute for educational purposes.

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If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

A literature review is a survey of scholarly sources (such as books, journal articles, and theses) related to a specific topic or research question .

It is often written as part of a thesis, dissertation , or research paper , in order to situate your work in relation to existing knowledge.

There are several reasons to conduct a literature review at the beginning of a research project:

• To familiarize yourself with the current state of knowledge on your topic
• To ensure that you’re not just repeating what others have already done
• To identify gaps in knowledge and unresolved problems that your research can address
• To develop your theoretical framework and methodology
• To provide an overview of the key findings and debates on the topic

Writing the literature review shows your reader how your work relates to existing research and what new insights it will contribute.

The literature review usually comes near the beginning of your thesis or dissertation . After the introduction , it grounds your research in a scholarly field and leads directly to your theoretical framework or methodology .

A literature review is a survey of credible sources on a topic, often used in dissertations , theses, and research papers . Literature reviews give an overview of knowledge on a subject, helping you identify relevant theories and methods, as well as gaps in existing research. Literature reviews are set up similarly to other  academic texts , with an introduction , a main body, and a conclusion .

An  annotated bibliography is a list of  source references that has a short description (called an annotation ) for each of the sources. It is often assigned as part of the research process for a  paper .  

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A Systematic Review of Head and Neck Cancer Health Disparities: A Call for Innovative Research

Affiliations.

• 1 Department of Otolaryngology-Head and Neck Surgery, University of Kansas Medical Center, Kansas City, Kansas, USA.
• 2 The Winters Group, Inc., Charlotte, NC, USA.
• 3 School of Medicine, University of Kansas, Kansas City, Kansas, USA.
• 4 Department of Otolaryngology-Head and Neck Surgery, St Louis University, St Louis, Missouri, USA.
• 5 Research and Learning, A.R. Dykes Library, University of Kansas Medical Center, Kansas City, Kansas, USA.
• PMID: 35133913
• DOI: 10.1177/01945998221077197

Objective: (1) Describe the existing head and neck cancer health disparities literature. (2) Contextualize these studies by using the NIMHD research framework (National Institute on Minority Health and Health Disparities). (3) Explore innovative ideas for further study and intervention.

Data sources: Ovid MEDLINE, Embase, Web of Science, and Google Scholar.

Review methods: Databases were systematically searched from inception to April 20, 2020. The PRISMA checklist was followed (Preferred Reporting Items for Systematic Reviews and Meta-analyses). Two authors reviewed all articles for inclusion. Extracted data included health disparity population and outcomes, study details, and main findings and recommendations. Articles were also classified per the NIMHD research framework.

Results: There were 148 articles included for final review. The majority (n = 104) focused on health disparities related to at least race/ethnicity. Greater than two-thirds of studies (n = 105) identified health disparities specific to health behaviors or clinical outcomes. Interaction between the individual domain of influence and the health system level of influence was most discussed (n = 99, 66.9%). Less than half of studies (n = 61) offered specific recommendations or interventions.

Conclusions: There has been extensive study of health disparities for head and neck cancer, largely focusing on individual patient factors or health care access and quality. This review identifies gaps in this research, with large numbers of retrospective database studies and little discussion of potential contributors and explanations for these disparities. We recommend shifting research on disparities upstream toward a focus on community and societal factors, rather than individual, and an evaluation of interventions to promote health equity.

Keywords: head and neck cancer; health disparities; health equity; social determinants of health.

Publication types

• Systematic Review
• Head and Neck Neoplasms* / therapy
• Health Promotion*
• Health Services Accessibility
• Retrospective Studies

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The well-being of head start teachers: a scoping literature review

Deborah wilson.

a School of Nursing, Johns Hopkins University, Baltimore, Maryland, USA

Corinne Plesko

Teresa n. brockie, nancy glass.

b Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA

Author contributions

Attention to students’ socio-emotional, behavioral, and academic outcomes raises important considerations for the psychological wellbeing of teachers, especially Head Start teachers who often work with underserved families. This scoping review summarizes current literature on Head Start teacher psychological well-being and identifies 1. how teacher well-being is conceptualized and measured, 2. Which interventions exist to promote Head Start teacher psychological well-being or help them manage stress and 3. directions for future research. The review resulted in 32 articles (29 peer-reviewed and three gray literature). Findings highlight that research is primarily descriptive using cross-sectional surveys and secondary data. Evidence suggests that although resilient and committed as educators, Head Start teachers struggle to cope with the stressors involved in supporting early childhood education. Interventions to decrease stress and promote the psychological well-being are few but teachers indicate interest in such interventions. Autonomy, feeling valued for their work, collegiality between staff, and a supportive supervisor help improve job satisfaction, retention, and psychological well-being. Future research should be guided by conceptual models that prioritize Head Start teachers’ input, use of validated measures of psychological well-being with consideration of cultural and structural factors that influence well-being.

Introduction

Quality early childhood education (ECE) promotes school readiness, contributing to improved academic and socio-emotional outcomes – particularly for children living in poverty ( Friedman-Krauss, Raver, Neuspiel, & Kinsel, 2014 ). Not only has such evidence led to an increase in preschool facilities in industrialized countries ( Kamerman & Gatenio-Gabel, 2007 ), it has also generated significant research related to teachers’ socio-emotional well-being, and how it facilitates or impedes positive learning environments for children ( Castle et al., 2016 ; Fantuzzo et al., 2012 ; Friedman-Krauss et al., 2014 ; Hamre, Pianta, Downer, & Mashburn, 2008 ; Jennings, 2015 ; McLean, Abry, Taylor, & Connor, 2018 ; Pearlin, Lieberman, Menaghan, & Mullan, 1981 ; Smith & Lawrence, 2019 ; Zinsser, Christensen, & Torres, 2016 ).

Theoretical models such as the Prosocial Classroom highlight this important correlation. They do so by connecting socially/emotionally competent teachers with greater support for children, more effective classroom management strategies and better modeling of prosocial behavior for children ( Jennings & Greenberg, 2009 ). However, there is a growing concern that connecting teacher performance to student outcomes and accountability measures may threaten a teacher’s self-worth, increase stress and burnout ( Parker, Martin, Colmar, & Liem, 2012 ), and limit a teacher’s value, by basing worth on whether they can graduate well-balanced children ( Cumming & Wong, 2019 ). This can risk teachers experiencing a sense of individual failure if their classrooms do not score high on quality ( Bullough, Hall-Kenyon, MacKay, & Marshall, 2014 ). While ECE teachers are aware of their value, they can struggle with a society that often dismisses their profession as “woman’s work” ( Gibson, 2013 ).

Since the effect of ECE teacher well-being on childhood outcomes is well established, this research team was interested in investigating how else research defines ECE teachers’ psychological well-being – particularity in studies involving Head Start teachers, who work in some of the most stressful educational contexts, often with disadvantaged children ( Harding et al., 2019 ).

Early childhood teacher well-being

While extant literature shows no consensus on how to define ECE teacher well-being ( Carine & Pablo, 2020 ; Cumming & Wong, 2019 ), it has been framed to include individual factors such as physical, financial, psychological, and emotional health. Existing research frequently measures psychological well-being in deficit terms such depression, stress, burnout, absenteeism, or staff turnover ( Carine & Pablo, 2020 ; Cumming & Wong, 2019 ). Contextual factors such as pay, workload, student behaviors and administrative support are cited as influencing a teacher’s psychological well-being, with social and political contexts also exerting their effects. A more holistic view of well-being would be to include a sense of purpose, flourishing and satisfaction with one’s quality of life ( Carine & Pablo, 2020 ; Cumming & Wong, 2019 ) which may differ by ethnicity or culture ( Adair, 2011 ). Roberts and Kim’s (2019) ecological framework presents teacher well-being not as a personal issue that they must remedy themselves, but rather shifts the focus to identifying the root causes of teacher stress to then create systems that can support and promote well-being.

Curbow’s Child Care Worker Job Stress Inventory has connected elements from job stress models (job demands and control, strain indicators) to caregiver health outcomes ( Curbow, Spratt, Ungaretti, Mcdonnell, & Breckler, 2000 ). This model also includes potential modifying factors, such as social support and self-esteem, that could promote the wellbeing and flourishing of ECE teachers ( Curbow et al., 2000 ).

Early childhood teacher stress

As Curbow’s Job Stress Inventory highlights, it is difficult to discuss ECE teacher well-being without acknowledging the elevated level of stress that these teachers struggle with, and how that stress potentially affects their well-being ( Cumming & Wong, 2019 ). Despite the high degree of job satisfaction and commitment that Head Start teachers express, especially in their ability to make a difference in their students’ lives ( Bullough & Hall-Kenyon, 2011 ; Gibson, 2013 ; United States Department of Health and Human Services. Administration for Children and Families. Office of Planning, Research and Evaluation., 2020 ), ECE teaching remains one of the most stressful occupations in the U.S., with 46% of teachers reporting increased daily stress during the school year ( Carroll, 2007 ). Burnout, anxiety, depression, sleep disorders, job dissatisfaction, poor performance, and a high turnover rate have all been attributed to teacher stress and is estimated to cost more than $7 billion a year for the economically burdened U.S. public education systems ( Carroll, 2007 ). According to a report by the Economic Policy Institute, chronic underfunding threatens ECE teachers’ well-being, and is a cause of low salaries ( Gould & Blair, 2020 ). Limited educational resources; working with children from families facing complex economic, health and social disparities; student behavioral challenges; workload; paperwork; gaps in pre-service training; and lack of appreciation are other reported factors that lead to teachers’ stress ( Lever, Mathis, & Mayworm, 2017 ). There is increasing evidence that secondary traumatic stress, or compassion fatigue, contributes to teachers’ strain as they work to support children and families that have suffered multiple adverse experiences, such as deprivation and familial loss due to violence or suicide ( Hydon, Wong, Langley, Stein, & Kataoka, 2015 ; Sharp Donahoo, Siegrist, & Garrett-Wright, 2018 ). In poverty-stricken areas, ECE teachers are likely to come from the same community as their students, and thus have dealt with similar Adverse Childhood Experiences (ACEs) as the children they teach. These ACEs can influence teachers’ levels of stress and hinder their well-being ( Hughes et al., 2017 ).

Interventions that promote teacher well-being

ECE programs need to implement early indicators of the challenges teachers face in meeting workplace demands. These indicators could trigger supportive interventions ( Li-Grining, Raver, Jones-Lewis, Madison-Boyd, & Lennon, 2014 ) that proactively focus on teacher well-being. These interventions are more likely to improve health and performance outcomes, rather than focus solely on advancing teachers’ knowledge and skills, leading to a comprehensive, holistic approach ( Roberts & Kim, 2019 ; Sears et al., 2014 ). Furthermore, evidence suggests that improving psychological well-being can lead to greater levels of job satisfaction and self-efficacy, as well as decrease stress and burnout ( Aloe, Amo, & Shanahan, 2014 ). Successful evidence-based resources designed to provide ECE teachers with tools to cope with the ongoing demands of their profession include mindfulness-based cognitive therapy ( Gold et al., 2010 ); access to mental health consultants and social workers ( Raver et al., 2008 ) and providing self-care and classroom-management skills ( Rombaoa Tanaka, Boyce, Chinn, & Murphy, 2020 ).

Review aims

With the aim of increasing the well-being of ECE teachers, this review explores which research exists that has examined a specific section of the ECE workforce: Head Start teachers.

Our goal was to investigate studies focused on 1) Head Start teachers’ psychological well-being as a primary outcome, i.e., not correlated to children’s socio-emotional competence or academic outcomes; 2) how studies defined, conceptualized, and measured well-being; and 3) which interventions have been implemented to improve or support these teachers’ psychological well-being.

The head start program

Head Start is the largest federally funded national ECE program in the U.S., and its programs and teachers must meet specific federal requirements ( Administration for Children and Families, [ACF], 2019 ). Founded in 1964, Head Start was designed to help break the cycle of poverty and provide preschool children from low-income families with a comprehensive program that meet their emotional, social, health, nutritional, and psychological needs ( ACF, 2019 ). Head Start is divided into 12 regions, 10 of which are geographically based and two defined by the populations they serve: Region XI covers programs operated by federally recognized American Indian/Alaska Native tribes, and Region XII serves migrant and seasonal workers and their families ( ACF, 2019 ).

Head Start tends to some of the most underserved, marginalized communities and vulnerable children in the U.S. ( Harding et al., 2019 ). Furthermore, ECE teachers working in Head Start programs receive relatively low compensation – more than 40% qualify for federal needs-based assistance such as Supplemental Nutritional Assistance Program (SNAP) and Medicaid ( Whitebook, McLean, & Austin, 2018 ). Studies have shown that Head Start loses as many as 25% of its teachers every year, compared to 8% among K3 educators ( Hindman & Bustamante, 2019 ).

Attempts to improve the quality of Head Start teaching has led to federal policies that mandate that teachers receive 15 hours of “research based, coordinated coaching strategy” annually, and that 50% of teachers within a setting must hold a bachelor’s degree or higher (Rep. Kildee, 2007). In addition, the No Child Left Behind Act (NCLB, 2002) reauthorized Head Start in 2007 with increased accountability measures and quality standards, as well as with randomly conducted federal review-team visits to ensure quality teaching, increased documentation to prove quality performance and the need for programs to compete for funding every five years ( NCLB,2002 ). However, these policies, meant to improve Head Start program, teacher, and classroom quality, have not been matched with increased wages or teaching resources, nor have they considered the impact that these increased demands might have on teacher well-being ( Bullough et al., 2014 ).

Scoping review

This scoping review was conducted to identify available evidence that examines Head Start teacher psychological well-being in order to provide an overview of existing research. Using Arksey and O’Malley’s (2005) methodology, we identified the following research focus and purpose:

• Which research exists that examines psychological well-being outcomes with teachers working in Head Start, a federal early child–development program, and how do these studies conceptualize and measure well-being?
• Which interventions exist to promote Head Start teacher well-being or help them manage stress, so they can meet the multiple demands of early childhood education with vulnerable families?

Methodology

After identifying the research focus, we used Arksey and O’Malley’s methodological framework for scoping reviews to guide this review. This includes 1) identifying relevant studies, which may include gray literature, blogs, and conference papers; 2) study selection; 3) charting and mapping the data; and 4) collating, summarizing, and reporting the results ( Arksey & O’Malley, 2005 ). Scoping reviews examine the extent and nature of research activity in a particular field; clarify key definitions or concepts in the literature; survey how research is conducted on a certain topic; identify key characteristics in connection with a topic; and locate knowledge gaps ( Munn et al., 2018 ). While systematic reviews seek to produce a synthesis or critical appraisal to a specific question, scoping reviews aim to provide an overview of evidence. Therefore, scoping reviews typically do not perform an assessment of risk of bias, or methodological limitations ( Munn et al., 2018 ).

Arksey and O’Malley’s framework also includes an optional step, where stakeholders outside the study review team are invited to provide their insights. After completing the review, the results were forwarded to an expert in occupation health psychology, work-life integration, and workplace violence, and to another expert who specializes in early childcare and education, family characteristics and neighborhood disadvantage that impact children’s lives. This review incorporates their insights.

Step one: identifying relevant studies

To identify relevant studies, we utilized the following inclusion/exclusion criteria:

Inclusion criteria

Research studies in the United States (U.S.) that include Head Start or early Head Start teachers in the sample; peer reviewed, published in English after 2008 to capture effects from federal policy changes, with a focus on the psychological well-being of Head Start teachers.

Exclusion criteria

International studies of ECE teachers; US-based studies that did not include Head Start; studies focused only on physical well-being (diet, exercise, food insecurity); studies where the measure of Head Start teacher well-being was correlated solely with changes in children’s socio-emotional regulation or school readiness, rather than changes in the teachers own psychological health.

Step two: study selection

We enlisted the assistance of a subject specialist librarian to ensure as comprehensive a search as possible. Scopus, PubMed, ERIC, and Psyche Info databases were searched from inception to the final search, in September 2022. We used Medical Subject Headings (MeSH) and non-MeSH search terms. The subject librarian explored MeSH terms and sub-headings, and we settled on three main subject headings: (1) School Teachers, (2) Stress and (3) Adaptation, psychological. (See Appendix A for all search terms and the lemmas * used). This search yielded 53 articles, so we expanded subject headings to include the non-MeSH terms “psychological well-being,” “Well-being,” “Head Start Program,” “Early Childhood Educators,” “Mindfulness,” “Resilience,” “Stress Psychological,” “Mental Health,” “Burnout,” “Post-Traumatic Stress” and “Coping.” The combined searches in all databases yielded 1,107 articles. These were uploaded into Covidence to assist in duplicate removal, screening, and full-text review. We removed 347 duplicates and the first and second author screened 761 title and abstracts. This led to the review of 193 full-text articles for inclusion. The research team then hand searched the reference lists of selected relevant studies, which added six additional articles to the review. Twenty-nine peer-reviewed articles met the eligibility criteria for inclusion.

Two additional searches on search engines specific to identifying gray literature: greylit.org and mednar.com were conducted. Due to the limited articles found within these search engines, we used only the term “Head Start,” in hopes of yielding the maximum number of potentially relevant publications. We limited gray literature searches to publications from the last five years. This search resulted in 24 and 65 articles for review from greylit.org and mednar.com , respectively. However, none of these publications were found to be relevant for this scoping review.

Lastly, we searched Google Scholar for gray literature that had not been included in the other search engines. Due to the large volume of blogs and papers that this search generated, we restricted the search to “Head Start Teacher well-being 2020” and “Head Start teacher stress 2020.” This reduced our results to 14 and 19 websites, respectively (n = 33 total gray literature). The process of inclusion for this literature review is documented in the flow diagram in Figure 1 .

Flow diagram of included literature.

The authors reviewed the full texts of 111 peer-reviewed articles and 33 briefs or government websites, writing summaries of each article, noting sample, research question, methods and measures used, findings and conclusions. Then, as a team discussed each summary and talked over any discrepancies with the last author.

Two issues arose in the review process: 1) whether to include studies that measured changes in teacher well-being but also correlated it to changes in children’s socio-emotional outcomes/school readiness (an exclusion criteria); and 2) inclusion of studies with samples that included Head Start teachers and ECE teachers employed outside a Head Start program. If included, what proportion of the total sample must be Head Start teachers, to meet inclusion criteria? After discussion among the authors, we decided to include these studies. To expand the criteria and contribute to a more complete scoping review, we contacted two authors of studies we considered to clarify inclusion of Head Start teachers in their sample ( Nagasawa & Tarrant, 2020 ; Roberts, Gallagher, Daro, Iruka, & Sarver, 2019 ).

Thirty-two articles met inclusion criteria for the review: 29 peer-reviewed research studies and three from gray literature. They consisted of two studies from one randomized controlled trial (RCT), two mixed-methods studies, one multi-methods study, four longitudinal studies, 19 cross-sectional studies, one case study, one qualitative study, one government website, one thinktank, and one blog. (See Table 1 for summary of included research studies, demographics, and outcome measures and Table 2 for summary of included of gray literature.)

Summary of research articles identified in scoping review.

Summary of Grey literature.

Step three: charting and mapping the data

To answer the first question, we mapped the data according to individual characteristics and contextual factors that the studies used to measure well-being. We also looked at the measurement tools utilized by each study. To answer the second question, we documented interventions implemented to promote Head Start teacher psychological well-being.

Well-being defined and measured

Six studies defined well-being of Head Start teachers: a multidimensional construct that focuses on holistic flourishing ( Roberts et al., 2019 ); high levels of satisfaction; low levels of stress ( Hur, Hur, Jeon, Buettner, & Buettner, 2016 ); the presence or absence of health ( Whitaker, Becker, Herman, & Gooze, 2013 ); goals and aspirations; commitment to teaching; sources of satisfaction and concern and worry ( Bullough, Hall-Kenyon, & MacKay, 2012 ); judging life positively and feeling good ( Kwon et al., 2021 ), a high level of energy and strong identification with ones work ( Lipscomb, Chandler, Abshire, Jaramillo, & Kothari, 2021 ) and job satisfaction and depression ( Harding et al., 2019 ). One study noted that while Head Start teachers are driven by caring for the well-being of the children, little attention has been placed on the well-being (satisfaction, commitment, aspirations) of the teachers themselves ( Bullough et al., 2012 ).

Measurement of well-being as an outcome varied across studies (see Table 1 for exact measurement tools used in each study), with the most common outcomes measured being stress ( Clayback & Williford, 2021 ; Farewell, Quinlan, Melnick, Powers, & Puma, 2021 ; Grant, Jeon, & Buettner, 2019 ; Kwon et al., 2021 ; Lang, Jeon, Sproat, Brothers, & Buettner, 2020 ; Li Grining et al., 2010 ; McGinty, Justice, & Rimm-Kaufman, 2008 ; Roberts et al., 2019 ; Whitaker et al., 2013 , 2014 ; Zhai et al., 2011 ), depression ( Berlin, Shdaimah, Goodman, & Slopen, 2020 ; Harding et al., 2019 ; Hindman & Bustamante, 2019 ; Kwon et al., 2021 , 2020 ; Li-Grining et al., 2014 ; Ling, 2018 ; Roberts et al., 2019 ; Whitaker et al., 2013 , 2014 ), job satisfaction ( Bullough et al., 2012 ; Farewell et al., 2021 ; Harding et al., 2019 ; Hindman & Bustamante, 2019 ; Jeon & Wells, 2018 ; Wagner & French, 2010 ; Wells, 2015 ), and attitudes toward teaching (which includes measures of both job satisfaction and stress) ( Hur et al., 2016 ; Jeon, Buettner, & Hur, 2016 ; McGinty et al., 2008 ).

After establishing how studies defined and measured Head Start teachers’ psychological well-being, we mapped the outcomes of each study, noting how they facilitated well-being or changed negative outcomes. Below are our findings.

Job satisfaction and teacher motivation

Job satisfaction was one of the most common components within the well-being definitions and was used as an outcome measure in seven studies, with three others utilizing the measure Attitudes Toward Teaching as a Career, which includes questions about job satisfaction. Across all studies, teachers describe or score high on feeling committed to their students and making a difference in their lives. Studies describe teachers as having a deep service ethic ( Bullough et al., 2012 ; Kwon et al., 2020 ). This intrinsic motivation (e.g., internal motivation and satisfaction) correlated less with intention to leave and more with intention to stay or move within the Head Start organization ( Grant et al., 2019 ). Experienced teachers were more satisfied and committed to their jobs ( Jeon et al., 2016 ). A sense of collegiality was positively correlated with workplace satisfaction and decreased emotional exhaustion ( Hur et al., 2016 ; Schaack, Le, & Stedron, 2020 ). Feeling respected and having influence also helped improve workplace well-being ( McGinty et al., 2008 ; Rodriguez & McKee, 2022 ) and decrease teacher turnover ( Schaack et al., 2020 ). In three studies, the constant monitoring of teacher performance and the amount of administrative paperwork took teachers away from the children, which decreased job satisfaction and motivation ( Bullough et al., 2014 ; Rodriguez & McKee, 2022 ; Wells, 2017 ). The lack of motivation was predictive of turnover in two studies ( Jeon et al., 2016 ; Wagner & French, 2010 ). Those with greater extrinsic motives for teaching (e.g., job security) were more likely to express intention to leave ( Clayback & Williford, 2021 ; Grant et al., 2019 ). Five articles found working conditions that placed value and rewarded teachers’ work ethic improved job satisfaction and were significantly related with a teacher’s intention to remain in the position ( Bullough et al., 2012 ; Grant et al., 2019 ; McGinty et al., 2008 ; Roberts & Kim, 2019 ; Wagner & French, 2010 ) with another study finding that involving teachers in decision-making and organizational direction could build loyalty to the organization ( Rodriguez & McKee, 2022 ) Relationship with the Head Start program director was also an indicator of workplace satisfaction and improving workplace satisfaction decreased turnover ( Jeon & Wells, 2018 ).

Influence of social support within the workplace

Our findings revealed that adequate social support had positive effects on several psychological well-being measures. In seven studies, social support within the workplace was associated with teacher retention, decreased depression, and increased satisfaction ( Grant et al., 2019 ; Hur et al., 2016 ; Jeon & Wells, 2018 ; McGinty et al., 2008 ; Schaack et al., 2020 ; Wagner & French, 2010 ; Wells, 2015 ). Social activities among staff, collegiality, proximity to other teachers, team building, and coworker relationships were associated with a more stable workforce, decreased depression, or decreased stress ( Grant et al., 2019 ; Hindman & Bustamante, 2019 ; Hur et al., 2016 ; Jeon & Wells, 2018 ; McGinty et al., 2008 ) with well-being (flourishing) being dependent on the quality of interactions with these colleagues ( Roberts et al., 2019 ). One study noted that offering professional development could increase collegial relationships ( Harding et al., 2019 ). Another study fund that negative relationships with coworkers was more strongly correlated to burnout than structural demands (e.g. classroom ratio) ( Schaack et al., 2020 ). High turnover rates within Head Start resulted in an unstable workforce, which prevented the development of relationships with other teachers, risking further turnover ( Hur et al., 2016 ).

Positive relationships with supervisors and program directors were identified as a source of support, workplace satisfaction and promoted commitment to the job ( Berlin et al., 2020 ). On the other hand, a negative relationship was associated with intention to leave ( Grant et al., 2019 ; Harding et al., 2019 ; Hur et al., 2016 ; Jeon & Wells, 2018 ; McGinty et al., 2008 ; Wagner & French, 2010 ; Wells, 2015 ).

One study of community-oriented schools (which recognize teachers for their engaged decision-making and collegiality, rather than student performance) found that Head Start programs showed large differences across local chapters if their teachers perceived collegial support and influence ( McGinty et al., 2008 ). The authors concluded that individual schools must augment state-level programmatic support by fostering a sense of community that considers specific local factors within their own programs ( McGinty et al., 2008 ).

With so few articles conceptualizing or measuring well-being in positive terms, the research team then extracted data on outcomes that measured psychological well-being in deficit terms.

Ten articles discussed teacher stress, with mixed results ( Berlin et al., 2020 ; Bullough et al., 2012 ; Hindman & Bustamante, 2019 ; Jeon et al., 2016 ; Li-Grining et al., 2014 ; McGinty et al., 2008 ; Roberts et al., 2019 ; United States Department of Health and Human Services, 2019 ; Wells, 2015 ; Zhai et al., 2011 ). Two studies recognized that Head Start teachers struggle with personal stress (low income, single parent, large family, poverty), which influences workplace stress (high job demands, low resources) ( Bullough et al., 2012 ; Li-Grining et al., 2014 ). Scoring high on both these stressors was not always associated with poor classroom quality (measured as emotional climate and behavior management), pointing to evidence of Head Start teacher resourcefulness ( Li Grining et al., 2010 ). Two studies found that teachers scoring high on personal stressors tended to keep these stressors separate from workplace stress, and that personal stressors were not predictive of turnover – suggestive again of the resilience and coping power of Head Start teachers ( Grant et al., 2019 ). Teachers who scored low on stress scored low on classroom quality, indicating that low stress might relate to a lack of awareness of any professional weaknesses ( Jeon et al., 2016 ). Conversely, high levels of stress were associated with high classroom quality, suggesting that high stress could be an indicator of the degree in which a teacher is committed to and cares about their job ( Hur et al., 2016 ; Jeon et al., 2016 ). However, another study found that high levels of teacher stress is associated with increased levels of burnout, absenteeism, and turnover ( Zhai et al., 2011 ).

Five articles discussed teacher–parent relationships as a source of stress ( Berlin et al., 2020 ; Elicker, Wen, Kwon, & Sprague, 2013 ; Li Grining et al., 2010 ; Roberts et al., 2019 ; Wells, 2017 ). Teacher–parent relationships are important to teachers. But despite initiatives to involve parents in program activities, teachers find it difficult to engage them ( Elicker et al., 2013 ) which could lead to limited appreciation of the teachers by the parents ( Berlin et al., 2020 ; Li Grining et al., 2010 ). Furthermore, teachers identified discordant relationships with parents as a workplace stressor ( Berlin et al., 2020 ; Roberts et al., 2019 ) made worse if a teacher already had negative views of their workplace ( Elicker et al., 2013 ). Two studies found Head Start teachers reporting higher levels of stress compared to ECE in public and private settings ( Clayback & Williford, 2021 ; Farewell et al., 2021 ).

Four articles revealed that workplace autonomy was associated with decreasing job-related stress ( Hindman & Bustamante, 2019 ; Roberts et al., 2019 ; Zhai et al., 2011 ), and higher levels of collegiality ( McGinty et al., 2008 ) which in turn lead to greater feelings of personal fulfillment with the work ( Schaack et al., 2020 ). Teachers who employed help-seeking behaviors and reflective practices showed improved competence, which decreased work-related stress ( Jeon et al., 2016 ).

Depressive symptoms

Depression rates in Head Start teachers are significantly higher when compared to the national average of 4.7% ( Centers for Disease Control and Prevention, 2020 ). A national survey of ECE staff found the prevalence of depression to be at 9.4%, using the Center for Epidemiological Studies Depression (CES-D) score ( Hamre & Pianta, 2004 ). In comparison, five articles found that depression rates in Head Start teachers ranged between 25% and 31% ( Hindman & Bustamante, 2019 ; Kwon et al., 2021 ; Ling, 2018 ; Whitaker et al., 2013 ). While two studies acknowledged that depression is more prevalent in women nationally ( Hindman & Bustamante, 2019 ; Ling, 2018 ) we found no studies that explored how gender might correlate with the high levels of depression in Head Start teachers. One study noted that female Hispanic/Latinx Head Start teachers reported a larger increase in depression as the year progressed, compared to other Head Start teachers ( Hindman & Bustamante, 2019 ). This mirrors national data, which shows that Latinx women struggle with greater depression risks than females of other ethnic backgrounds ( Hindman & Bustamante, 2019 ).

Techniques demonstrating a decrease in Head Start teacher depression were workplace support and curriculum guidance ( Harding et al., 2019 ). And while not successful at reducing depression, professional development (one of the requirements of Head Start policies) and improving job control did increase workplace satisfaction ( Kwon et al., 2021 ; Li Grining et al., 2010 ; Lipscomb et al., 2021 ; Schaack et al., 2020 ; Wagner & French, 2010 ). Lack of job control and autonomy in the workplace were associated with depression ( Roberts et al., 2019 ). Contrary to expectations, depression increased with the availability of health insurance benefits, the supposition being that these benefits enabled teachers to seek help for symptoms, which sometimes resulted in a diagnosis of depression ( Harding et al., 2019 ).

Influence of policy on psychological well-being

The Improving Head Start for School Readiness Act of 2007 required 50% of center-based teachers obtain a bachelor’s degree by 2013. Results were mixed as to whether higher education improved classroom quality and staff retention. Two studies found that teachers with a lower level of education were more likely to quit rather than pursue a higher degree ( Wells, 2015 ; Zhai et al., 2011 ) and having an associate degree was significantly linked with intention to stay in the job, compared to Head Start teachers who did not possess at least an associate’s degree ( Jeon & Wells, 2018 ). Another study found that while an advanced degree was predictive of teachers having difficulty trusting communication and collaboration with families, once these teachers did establish a relationship there was a significant association, with an increase in positive parenting behaviors ( Elicker et al., 2013 ). Kwon et al. (2020) found that teachers with higher levels of education had greater resources and provided higher quality care but reported poorer professional well-being. Overall these results support federal guidelines that mandate higher education. Experience, regardless of education, was predictive of retention ( Bullough et al., 2012 ) and improved job satisfaction ( Jeon, 2016 ). Higher education was not predictive of a sense of community ( McGinty et al., 2008 ) and teachers were more likely to leave due to lack of support from administration and coworkers. This indicates that fostering a sense of community and support may be more important for teacher retention than a higher level of education ( Hindman & Bustamante, 2019 ; Wells, 2015 ).

The No Child Left Behind Act (NCLB), increased accountability measures and standards and implemented randomly conducted federal review team visits, increased the documentation required to prove successful performance and the need for programs to compete for funding every five years, with the goal of improving Head Start programming teacher, and classroom quality. When asked about their experiences of these policies, teachers describe them as burdensome, because the amplified paperwork and federal oversight diminished their self-efficacy and control. ( Bullough et al., 2014 ; Rodriguez & McKee, 2022 ; Wells, 2017 ). Three studies found that the increased expectations on Head Start teachers, without a matching increase in wages or compensation, was associated with increased stress and intention to leave ( Clayback & Williford, 2021 ; Harding et al., 2019 ; Schaack et al., 2020 ). This, however, was contradicted in other studies, where teachers cited that they would leave due to personal stressors, lack of support or children’s behavioral problems, rather than issues with pay ( Bullough et al., 2012 ; Kwon et al., 2020 ; Wagner & French, 2010 ).

Six articles discussed the outcomes of implementing new policy without considering their effects on teacher well-being ( Bullough et al., 2012 ; Clayback & Williford, 2021 ; Gould & Blair, 2020 ; Harding et al., 2019 ; Roberts & Kim, 2019 ; Wells, 2017 ) with the following harmful consequences identified: higher turnover, with subsequent increased workplace instability; increased accountability expectations, leading to the diminishment of the value of teacher judgment ( Bullough et al., 2014 ); the vulnerability of teachers who are too afraid to refuse the extra work ( Bullough et al., 2014 ); conforming to regulations that take teachers away from their students’ needs ( Wells, 2017 ); prevents teacher self-regulation; increased stress when emphasis is on performance standards without support ( Clayback & Williford, 2021 ); and the push for higher-quality teaching has not been matched with an increase in pay ( Gould & Blair, 2020 ; Harding et al., 2019 ). In contrast, Harding et al. (2019) and Jeon et al. (2016) found that, contrary to their predictions, increased federal requirements for professional development was positively associated with increased job satisfaction and teachers feeling more valued.

Study demographics

Finally, we make note of the study demographics in Table 1 . This is especially crucial, because these demographics made the research team aware of two important gaps in the existing research. Six studies reported samples of predominately African American teachers and teachers’ assistants ( Berlin et al., 2020 ; Clayback & Williford, 2021 ; Lang et al., 2020 ; Li-Grining et al., 2014 ; Wells, 2017 ; Zhai et al., 2011 ); all the other studies reported samples from predominately white populations (53–97%). Two studies captured the experience of Latinx teachers ( Farewell et al., 2021 ; Hindman & Bustamante, 2019 ) and another included 16% immigrant teachers ( Zhai et al., 2011 ). Importantly, however, only one study included American Indian/Alaska Native Head Start teachers, even though Region XI covers programs operated by federally recognized American Indian/Alaska Native tribes ( Kwon et al., 2020 ). All studies reported that their samples of teachers and teachers’ assistants were predominantly female (all greater than 98%). This lack of representation was not addressed in any study, nor the fact that potentially gendered social norms may be a contributing factor to the low pay, low status, and decreased psychological well-being of Head Start teachers.

Interventions that support head start teacher psychological well-being

Interventions implemented to support Head Start teacher well-being are few, yet the teachers do express interest in stress-reduction interventions particularly if it satisfies educational or accreditation requirements ( Berlin et al., 2020 ; Ling, 2018 ). When provided mental health support, those teachers who experienced the highest levels of stress took advantage of the interventions offered ( Li Grining et al., 2010 ). Interventions focusing on teacher stress-reduction did positively change the way teachers thought about job demands ( Zhai et al., 2011 ). Stress-reduction tips and relaxation techniques are provided for teachers on the Administration for Children and Families (ACF) website ( United States Department of Health and Human Services, 2019 ) which offers helpful information, but also requires that teachers take personal responsibility for their well-being and stress management. Younger, less experienced teachers are more likely to quit ( Bullough et al., 2012 ; Roberts et al., 2019 ), but allocating mental health support for newly trained teachers delivers the support needed to increase retention ( Roberts & Kim, 2019 ).

One study identified ACEs as a source of poor mental health and trauma-related stress for Head Start teachers ( Whitaker et al., 2014 ). The study measured ACE score and dispositional mindfulness (awareness developed because of paying attention to sensations). It found that, across a wider range of exposures to ACEs, greater dispositional mindfulness was associated with better quality of life, better health behavior and fewer health conditions. The study recommended interventions to increase dispositional mindfulness in Head Start teachers who score high on ACEs, as it may result in an improvement in their health and well-being ( Whitaker et al., 2014 ). A more recent study found that Head Start teachers report lower levels of mindfulness when compared with normative data, but their resilience was comparable with the national standard ( Farewell et al., 2021 ). Implementing an eight-week mindfulness compassion-based program had a large and positive effect on mental well-being with an overall reduction in participants reported levels of burnout ( Hatton-Bowers et al., 2022 ). An on-line three-hour stress education and reduction intervention effectively increased teachers knowledge about stress, stress reduction, and resilience techniques. However, teachers also reported an increased level of personal perceived stress indicating that education about stress helps participants to identify how they are stressed ( Lang et al., 2020 ).

One study noted that treatment techniques (e.g., cognitive-behavioral therapy) used to support teacher depression have not been culturally adapted for Latinx cultures and are thus likely to be less effective ( Hindman & Bustamante, 2019 ) while another noted that black participants reported less benefit from a stress-reduction intervention ( Lang et al., 2020 ). The authors suggest tailoring the intervention to include structural racism as a stressor thus making it more relevant to the population served ( Lang et al., 2020 ).

Discussion and implications

Step four: collate, summarize, report.

The purpose of this scoping review was to summarize current literature on Head Start teacher psychological well-being and identify 1. How teacher well-being is conceptualized and measured and, 2. Interventions that exist to promote Head Start teachers’ psychological well-being and manage stress

Research that investigates the well-being of ECE teachers has increased over the last 10 years, as evidenced by the growing number of publications in databases. However, overall research is still sparse, and even more limited for Head Start teachers. In this review, we found that emphasis is placed on how stress or depression affects Head Start staff turnover and the academic and socio-emotional outcomes of the children they teach, rather than valuing the teachers as individuals who need psychological support ( Kwon et al., 2021 ; Li Grining et al., 2010 ; Roberts & Kim, 2019 ).

Implications for research

Definitions and measures of well-being are different across studies, making it challenging to compare teacher outcomes. Investigating Head Start teacher well-being from a holistic perspective, using a strengths-based focus as suggested in the conceptual models “Early Childhood Teacher Well-being” by Roberts and Kim (2019) the “Whole Teacher Well-being” by Kwon et al. (2021) , would emphasize teacher well-being as an important goal, rather than as a component needed to improve outcomes for children. We did not find any peer-reviewed studies that used a conceptual model; going forward, this would more clearly frame research intentions and the rationale for the variables chosen to measure teacher well-being.

Using validated measurement tools, such as “Satisfaction with Life,” would gauge a more holistic, strengths-based perspective of teacher well-being, rather than using scales that serve as proxies for this concept. We should also consider physiological measures in future research (e.g., cortisol levels), as all the studies identified for this review relied on self-report or observational data, which risks social desirability bias and subjectivity.

One study investigated the trauma and ACEs these teachers may have experienced, and how it might affect their health and well-being ( Whitaker et al., 2014 ). This will be an important area to pursue more extensively, as Head Start teachers tend to live in the communities where they teach – communities that often struggle with poverty, crime, and violence ( Zhai et al., 2011 ). Furthermore, secondary traumatic stress (compassion fatigue) has become increasingly identified as an issue that Head Start teachers must face as they struggle to help traumatized children within their classrooms ( Hydon et al., 2015 ; Lipscomb et al., 2021 ).

Attention to the issue of the gender of Head Start teachers – especially given the effect that the COVID-19 pandemic has had on amplifying preexisting inequalities, such as underpayment, increased unpaid care work and gender-based violence – would be crucial for further research. Concepts and constructs such as ACEs, compassion fatigue, gendered social norms, discrimination, and innovative teaching practices post-pandemic will be important to incorporate into existing conceptual frameworks.

Experimental and quasi-experimental studies would also help strengthen the data surrounding changes in well-being over time, due to the implementation of control groups. There is enough evidence to suggest that Head Start teachers are interested in stress reduction techniques ( Li Grining et al., 2010 ; Ling, 2018 ; Zhai et al., 2011 ) but careful attention to the time burden of an intervention and the use of incentives such as educational credits is warranted ( Lang et al., 2020 ). To date there is a lack of interventions that work to support and improve the psychological well-being of these teachers. Care must be taken when educating about stress or introducing stress reduction interventions as teachers become more aware of their stress and how it impacts them ( Lang et al., 2020 ). Encouragement within the work-place environment to continue to implement stress-reduction techniques may help decrease perceived stress over time ( Lang et al., 2020 ). Thus, the need for longitudinal follow-up is highlighted as this will help identify how perceived stress and well-being changes over time ( Lang et al., 2020 ).

Three studies used secondary data analysis on the national representative data set, the Family Child, and Experiences (FACEs) study. This robust longitudinal study uses outcome measures to assess Head Start children’s results and program quality. It is, however, limited in its data on teacher well-being, as it specifically looks at teacher depression and job satisfaction. Moving forward, the addition of questions or measures that more accurately capture the well-being of the Head Start teacher workforce may provide us with greater data and information on how to increase said well-being and potentially enhance staff retention.

Since 2016, the FACEs study has been adapted to capture data on Region XI – the Head Start area servicing children in American Indian and Alaska Native communities. Studies on teacher well-being using data from this set were not found for this review. And to our knowledge, the FACEs study has not been adapted for Region XII (immigrants and seasonal workers). Research within these regions of Head Start teachers would also be important.

Specific cultural factors are likely to influence Head Start teachers’ stressors and strengths, and we need to identify and incorporate these factors into any future support interventions.

Only six studies ( Berlin et al., 2020 ; Bullough et al., 2012 , 2014 ; Rodriguez & McKee, 2022 ; Wagner & French, 2010 ; Wells, 2017 ) included qualitative interviews. Concepts such as autonomy and job-control are key to improving teachers’ job satisfaction and their sense of value. More qualitative studies that include the voices of teachers could help identify ways in which they desire more workplace autonomy (e.g., control of their schedule), or highlight other needs that could be implemented in the workplace to promote well-being. This is even more critical as the COVID-19 pandemic continues, and beyond.

Implications for policy and practice

Despite evidence of the resourcefulness and resilience of Head Start teachers ( Elicker et al., 2013 ; Farewell et al., 2021 ; Wells, 2015 ), we need to make a greater effort to secure the implementation of workplace and political supports, to ensure the psychological well-being of Head Start teachers. Evidence shows that many of these teachers are motivated by a deep service ethic, and that those with intrinsic motives are more likely to stay on at Head Start – and report better coping skills and health ( Grant et al., 2019 ; Kwon et al., 2020 ). This suggests that interventions, policies, or practices that recognize and reward these traits could strengthen the well-being of these teachers. We need implementation studies that take the existing evidence of positive support mechanisms for Head Start teachers (social support, stress-reduction techniques, focusing on strengths such as intrinsic motive, resilience, autonomy, and control in the workplace) and develop interventions aimed at bolstering their well-being.

The research team was surprised to find positive evidence of the effect of Head Start policies, namely increasing educational status and implementing professional development. However, stronger evidence exists for the need to focus on improving teacher well-being, rather than trying to “fix” the teacher through mandated requirements that warrant a heavier workload.

Several articles demonstrated the positive effect of creating a sense of community between teacher coworkers ( Elicker et al., 2013 ; Hur et al., 2016 ; Kwon et al., 2020 ; McGinty et al., 2008 ; Wagner & French, 2010 ). One of the strongest positive effects of professional development was the chance to interact with coworkers, suggesting that focusing on cohorts might improve teacher well-being ( Hindman & Bustamante, 2019 ). Thus, it’s worth considering ways to create more open collaborative models of professionalism ( Bullough et al., 2014 ; Rodriguez & McKee, 2022 ). This is essential to consider when thinking of the organizational climate and structure of Head Start schools. Relationships with supervisors and administrators have an important, positive effect on teacher well-being ( Berlin et al., 2020 ; Bullough et al., 2014 ; McGinty et al., 2008 ; Rodriguez & McKee, 2022 ; Wagner & French, 2010 ; Wells, 2015 , 2017 ). Ensuring that these supervisors have the support and training they need to be effective leaders could potentially decrease turnover rates, improve individual well-being, strengthen the school community and more.

While formal data is not yet available, the psychological well-being of Head Start teachers is likely to be an even more important issue as the COVID-19 pandemic continues to place stress on the teachers, as well as the parents, students, and communities they serve. Thus, it is critical that the teachers themselves are not placed with the burden of dealing with their psychological well-being on their own. Rather, it’s crucial to advocate for the implementation of workplace, structural, and national policies that allow teachers to receive the help they need to rebound from this pandemic. With said help, teachers can flourish as they continue teaching and supporting their students and families.

Limitations of this review

Studies that investigate Head Start teacher well-being, causes of stress, or implement interventions to promote teacher well-being are few. The purpose of this study was to map currently available evidence. While a scoping rather than a systematic review could be a limitation, we felt it was more important to map what is available. That way, we could identify clearer avenues for further research, rather than focus on the quality of the articles, as done in a systematic review.

Another limitation: we only investigated ECE in the U.S. – specifically, Head Start programs. Expanding this review to include all early childhood educators in the U.S. or internationally may reveal more trends, methods, or interventions, which we could then adapt to the Head Start context, that promote the well-being of teachers.

Limitations of the literature reviewed

We identified only one RCT, and three longitudinal studies. All other studies assessed teacher well-being at one time point; thus, changes have not been assessed over time. Studies that developed a questionnaire (n = 13) had small sample sizes, which limits how we drew conclusions. The surveys and questionnaires were largely self-reported, which may prompt teachers to deliver socially acceptable answers. National survey data sets were large, and multiple studies used the same data set (FACEs). Given that this was the most frequently used data set, it was striking that immigrant and Native American teachers were not represented; this suggests a need to target these Head Start regions (XI and XII), to identify their needs, strengths and supports.

It was difficult to compare across studies, due to the numerous measurement tools each study utilized. As a result, conclusions made from this review need to be interpreted carefully. Furthermore, to develop a more robust scientific understanding of Head Start teacher well-being, we recommend expanding the level of evidence by implementing more randomized control trials and quasi-experimental studies with adequate sample sizes.

With increasing interest in the effects of Head Start teachers on children’s socio-emotional, behavioral, and academic outcomes, it is critical to pay attention to the health and well-being of the Head Start teachers themselves. And with COVID-19 exacting a heavy toll on teachers, families, and communities – school closures, switching to remote learning, deaths of loved ones – this has become even more urgent. There is enough evidence to suggest that teachers would utilize, with positive results, interventions that support their well-being. Yet a gap exists in research that describes successful interventions with this population. More attention needs to account for these teachers’ experiences, with a focus on their definition of well-being, the types of support they want, and their specific community and cultural contexts.

For all Head Start teachers – and, in fact, all ECE teachers – there is a need for a greater push to provide them with the necessary ongoing support to protect their well-being. Despite the resilience and commitment demonstrated by these teachers, it is imperative not to ignore their psychological health and well-being.

This scoping review has identified individual and contextual factors that affect Head Start teacher well-being. It has also identified the need for legislators to carefully consider the effect that educational policies may have on the teachers themselves, not just on the children’s academic and socio-emotional outcomes. Education systems – and policies that address the specific needs of Head Start teachers – are necessary to provide the support, funding and infrastructure required to manage stress and enhance well-being. These positive steps are essential to foster a healthy workforce, children, families, and communities.

Acknowledgments

The authors would like to thank Donna Hesson, Welch medical library informationist for assistance in identifying search string strategies and Dr. Ginger Hanson and Dr. Lieny Jeon for their feedback and insights.

This work was supported by the National Institute of Nursing Research of the National Institutes of Health under Award Number 1F31NR019742-01 FAIN: F31NR019742. “The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.”; Johns Hopkins University School of Nursing Discovery and Innovation Fund. Under grant number 80055563; and Johns Hopkins School of Public Health Center for Qualitative Studies (no grant number); Foundation for the National Institutes of Health.

Search Strings

“School Teacher*” OR “schoolteacher*” OR educator*

Concept #2A

“Psychological Stress*” OR “Life Stress*” OR “Posttraumatic Stress Disorder*” OR “Post Traumatic Stress Disorder*” OR PTSD OR depression OR mental health

Concept #2B

“Well-being” OR wellbeing OR “quality of life” OR wellness OR positive effect*

Concept #2C

“Psychological adaptation” OR “Psychological Resilience*” OR “Coping Behavior*” OR “Coping Skill*” OR “Adaptive Behavior*” OR resilience

“Head Start” OR “early childhood education”

Disclosure statement

No potential conflict of interest was reported by the author(s).

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Humanoid robot heads for human-robot interaction: A review

• Published: 25 December 2023

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• Yi Li 1 , 2 ,
• LiXiang Zhu 1 , 2 ,
• ZiQian Zhang 1 , 2 ,
• MingFei Guo 1 , 2 ,
• ZhiXin Li 1 , 2 ,
• YanBiao Li 1 , 2 &
• Minoru Hashimoto 3  

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The humanoid robot head plays an important role in the emotional expression of human-robot interaction (HRI). They are emerging in industrial manufacturing, business reception, entertainment, teaching assistance, and tour guides. In recent years, significant progress has been made in the field of humanoid robots. Nevertheless, there is still a lack of humanoid robots that can interact with humans naturally and comfortably. This review comprises a comprehensive survey of state-of-the-art technologies for humanoid robot heads over the last three decades, which covers the aspects of mechanical structures, actuators and sensors, anthropomorphic behavior control, emotional expression, and human-robot interaction. Finally, the current challenges and possible future directions are discussed.

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Key Laboratory of Special Purpose Equipment and Advanced Processing Technology of Ministry of Education, Zhejiang University of Technology, Hangzhou, 310023, China

Yi Li, LiXiang Zhu, ZiQian Zhang, MingFei Guo, ZhiXin Li & YanBiao Li

Zhejiang Provincial Key Laboratory of Special Purpose Equipment and Advanced Processing Technology, Zhejiang University of Technology, Hangzhou, 310023, China

Faculty of Textile Science and Technology, Shinshu University, Ueda, 386-8567, Japan

Minoru Hashimoto

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Correspondence to Yi Li , YanBiao Li or Minoru Hashimoto .

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This work was supported by Zhejiang Provincial Natural Science Foundation of China (Grant Nos. LY22E050019 and LGG21E050015), Ningbo Public Welfare Research Program Foundation of China (Grant No. 2023S066), the National Natural Science Foundation of China (Grant No. U21A20122), and the JSPS Grant-in-Aid for Scientific Research (C) (Grant No. JP22K04010) .

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Li, Y., Zhu, L., Zhang, Z. et al. Humanoid robot heads for human-robot interaction: A review. Sci. China Technol. Sci. (2023). https://doi.org/10.1007/s11431-023-2493-y

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Received : 02 June 2023

Accepted : 28 August 2023

Published : 25 December 2023

DOI : https://doi.org/10.1007/s11431-023-2493-y

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