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. 2023 Sep 21;18(9):e0291962. doi: 10.1371/journal.pone.0291962

The distribution of registered occupational therapists, physiotherapists, and podiatrists in Australia

Engida Yisma 1,*, Vincent L Versace 2, Martin Jones 1, Sandra Walsh 1, Sara Jones 1, Esther May 3, Lee San Puah 1, Marianne Gillam 1
Editor: Marianne Clemence4
PMCID: PMC10513188  PMID: 37733814

Abstract

Background

In Australia, the distribution of occupational therapists, physiotherapists, and podiatrists density (per 10,000 population) by measure of location/rurality, usual resident population, and area-level socioeconomic status has not been described.

Objective

To describe the national as well as states-and territories-wide distribution of registered allied health workforce—occupational therapists, physiotherapists, and podiatrists—by measures of rurality and area-level socioeconomic position in Australia.

Methods

A linked data study that brings together (1) the location of health practitioners’ principal place of practice from the Australian Health Practitioner Regulation Agency, (2) a measure of location/rurality—Modified Monash Model (MMM), and (3) an area-level measure of socioeconomic status—Index of Relative Socio-Economic Advantage and Disadvantage (IRSAD). The provider-to-population ratio (i.e., density) of three Australia’s allied health workforce (occupational therapists, physiotherapists, and podiatrists) was calculated according to the MMM classifications (i.e., Modified Monash 1–7) and IRSAD quintiles at state and national level.

Results

Nationwide, the density of occupational therapists and physiotherapists was highest in metropolitan areas (Modified Monash 1) and decreased with the increasing levels of the MMM categories. The national density of podiatrists was highest in Modified Monash 3 areas. The density of occupational therapists, physiotherapists, and podiatrists was highest in areas with IRSAD quintile 5 (i.e., the highest socioeconomic position) and decreased with the declining levels of the IRSAD quintiles nationwide. Moreover, there were notable disparities in the density of occupational therapists, physiotherapists, and podiatrists across each state and territory in Australia when stratified by the MMM classifications and IRSAD quintiles.

Conclusions

There was uneven distribution of registered occupational therapists, physiotherapists, and podiatrists when stratified by measures of location/rurality and area-level socioeconomic status across Australian jurisdictions. The density of these three groups of allied health workforce tended to be more concentrated in metropolitan and most advantaged areas while remote and most disadvantaged areas exhibited less allied health workforce distribution across each state and territory.

Introduction

The health workforce plays a pivotal and indispensable role in shaping healthcare systems worldwide. Furthermore, the healthcare workforce stands at the core of efforts to achieve the United Nations Sustainable Development Goals and promote universal health coverage [1, 2]. The 2016 Global Strategy on Human Resources for Health: Workforce 2030 projected a global shortfall of 18 million health workers by 2030 [3], encompassing both urban and rural areas. The availability and accessibility of health workers continue to exhibit considerable disparities within countries [2], owing to challenges in attracting and retaining health professionals in both urban and rural regions. For instance, compared with Australians living in metropolitan areas, residents in rural and remote areas experience poorer access to health care services, have a higher prevalence of health risk factors, and have higher rates of injury, hospitalisation, and death [4]. Similar health disparities exist between rural and metropolitan areas in other developed nations such as Canada and the United States of America (USA) [5]. Factors associated with health inequalities include socioeconomic position (income, education, and occupation), access to health care services, health workforce distribution, and occupational and physical risks [6, 7]. These factors contribute to the wide variations in health inequalities across rural and metropolitan areas.

Evidence suggests that the socioeconomic position of people in each area is an important determinant of health outcomes in that area. For instance, evidence has shown that individuals from lower socioeconomic groups experience higher rates of illness, disability, and mortality, as well as shorter lifespans compared to those individuals from higher socioeconomic groups [8]. Thus, improving access to material and social resources are important for addressing health inequalities in society. Another key aspect in health inequality is health care service delivery. Given that the health workforce is the main part of any health care system, the availability and accessibility of health workforce has a critical role in addressing the health inequalities of people in different socioeconomic groups.

The allied health workforce, together with the medical practitioners, nurses, and midwives, are the main part of Australia’s health system that is intended to provide safe and affordable health care for all residents [9]. There were about 133,400 registered allied health professionals in Australia in 2018 [10]. The availability and accessibility of adequately skilled allied health workforce such as occupational therapists, physiotherapists and podiatrists is essential to support people living with long-term physical health conditions [11]. On the other hand, a shortage of allied health workforce can affect health service delivery with implications in the form of adverse health outcome of the population, particularly in rural Australia where residents experience higher levels of long-term physical and mental health conditions [11, 12]. Equitable distribution of allied health workforce across all areas is essential to alleviate health disparities.

There are few studies that described the distribution of the allied health workforce including, physiotherapists, and occupational therapists. For instance, Rodés et al. [13], in their 2021 study that utilised data from the Brazilian National Registry of Health Care Facilities, described the trends of the physiotherapy workforce-to-population ratio in Brazil and its regions. They found that the physiotherapy workforce-to-population ratio was variable according to care levels, and public and private sectors across all regions of Brazil [13]. Moreover, several studies conducted in Canada [14–16] found that the distribution of physiotherapists and self-reported physiotherapy use varies according to health regions and population (e.g., less physiotherapists in rural and remote areas), suggesting reduced access to physiotherapy services particularly in rural and remote areas. Furthermore, a study conducted by Lin and colleagues [17] in USA based on forecast models revealed that there is a shortage of occupational therapists in several states nationwide and the shortages are anticipated to rise in all states through 2030. Ned et al. [18] in their study that utilised data obtained from ‘the Health Professions Council of South Africa’ database, described the distribution and status of occupational therapists workforce. They found that there was uneven distribution of occupational therapists in South Africa, with the high proportions of occupational therapists were in urbanized provinces.

In Australia, uneven geographic distribution of health workforce, particularly the medical workforce, has been reported using different data sources. For instance, a study conducted by Joyce and Wolfe [19] using census data from 1996 and 2001 described the geographic distribution of the medical and non-medical primary health professions, including allied health professionals. The study reported that the supply of the general medical workforce in remote areas was lower when compared with metropolitan areas. Moreover, a 2021 study by Yisma et al. [20] using linked data from three data sources described the distribution of occupational therapists, physiotherapists, and podiatrists according to the Modified Monash Model and area-level socioeconomic position in South Australia. They found that the highest occupational therapists, physiotherapists, and podiatrists density (per 10,000 population) was in metropolitan areas and the lowest density of each of these health professionals was in very remote communities. However, the health workforce density, including allied health professionals density according to the socioeconomic characteristics of an area and geographic location has not been described at national level, or for other states and territories. Areas in Australia are ranked based on a composite measure of socioeconomic position such as Index of Relative Socio-Economic Advantage and Disadvantage (IRSAD). Versace et al. [21] conducted a national analysis of Australia accounting for area-level socio-economic conditions and population distribution, stratified by the Modified Monash Model to inform health workforce planning. They found that the majority of rural residents lived in areas with the lowest IRSAD categories. Describing the allied health workforce density by such socioeconomic position measures would be important to understand and address social inequalities and disadvantage. Moreover, given that both socioeconomic disadvantage and geographical remoteness are an important predictors of health outcome, [22] understanding the allied health workforce density by measure of socioeconomic position and geographical remoteness would be critical to inform the public health policy regarding allied health workforce recruitment and retention as well as management of allied health care service provision. Unlike previous studies, the objective of the present study was to integrate geographic factors (location/rurality) and area-level socioeconomic position to provide a new insight into the interplay between health workforce availability, socioeconomic factors, and geographic disparities. The purpose of the present study was to describe the national as well as states-and territories-wide distribution of registered occupational therapists, physiotherapists, and podiatrists by measures of location/rurality and area-level socioeconomic position in Australia.

Materials and methods

Data source

We linked data from three sources: (1) the public registration data of occupational therapists, physiotherapists, and podiatrists obtained from the Australian Health Practitioner Regulation Agency (AHPRA); (2) the Modified Monash Model (MMM) 2019 data from the Australian Department of Health; and (3) the Socio-Economic Indexes for Areas (SEIFA) data and usual resident population data obtained from the Australian Bureau of Statistics (ABS) based on the 2016 census. We combined these three data sources to explore the interplay between allied health workforce availability, measure of rurality, and socioeconomic position. This approach is important to deliver policy relevant insights aimed at promoting equitable healthcare access and outcomes. The SEIFA ranks areas in Australia according to relative socioeconomic advantage and disadvantage and consists of four indexes. These are the Index of Relative Socio-Economic Disadvantage (IRSD), the Index of Relative Socio-Economic Advantage and Disadvantage (IRSAD), the Index of Education and Occupation (IEO) and the Index of Economic Resources (IER). The AHPRA data were extracted and de-identified in April 2020. The MMM categories and the SEIFA index quintiles were combined with AHPRA data based on the practitioner’s principal place of practice. The occupational therapists, physiotherapists, and podiatrists were included in this study because of limited funding to obtain the data from AHPRA and these professions are consistent with the University of South Australia’s offerings at the time. Furthermore, these group of health professionals were chosen because they play a key role in the management of long-term physical health conditions such as diabetes, cardiovascular diseases, and arthritis in Australia [11].

Study variables

The outcome measure of interest was the distribution of occupational therapists, physiotherapists, and podiatrists according to MMM and IRSAD. The MMM is a measure of location according to geographical remoteness and town/population size. The model quantifies remoteness and population size on a category scale of Modified Monash (MM) 1 to 7, which is based on the Australian Statistical Geography Standard—Remoteness Areas framework. For example, MM 1 indicates the location is a ‘metropolitan area’ and MM 7 indicates the locations that are ‘very remote communities’. The IRSAD is one of the four SEIFA indexes generated by ABS and summarises information regarding the social and economic status of people and households within an area. The IRSAD index was chosen for the purpose of this study because it is a comprehensive index that combines several variables to measure both advantage and disadvantage across Australia. Consistent with the other SEIFA indexes, IRSAD scores are based on summary measures that represent an average of people and households in an area and they are not presumed to be applicable to all individuals within that area. A low IRSAD score (quintile 1) indicates relatively most disadvantage while a high IRSAD score (quintile 5) indicates relatively most advantage within an area. We categorized the IRSAD deciles into quintiles for the purpose of this study.

Data analysis

We first calculated the proportion of occupational therapists, physiotherapists, and podiatrists by MMM categories and IRSAD quintiles for the whole of Australia as well as for each state and territory (S1 and S2 Tables). Next, we summarized the total estimated usual resident population for Statistical Areas Level 1 (SA1) and Statistical Areas Level 2 (SA2) for whole of Australia as well as for each state and territory. SA1 and SA2 are part of the main structure of the Australian Statistical Geography Standard (ASGS), which classifies Australia into a hierarchy of statistical areas. The ASGS is developed to reflect the location of people and communities. We then calculated the provider-to-population ratio (density) of occupational therapists, physiotherapists, and podiatrists (i.e., per 10,000 population) stratified by the MMM categories and IRSAD quintiles for whole of Australia as well as for each state and territory. We defined the density of these group of allied health professionals as the total number of occupational therapists, physiotherapists, and podiatrists per 10,000 population, respectively by adopting definitions used by the World Health Organization’s document [23]. To calculate the density of occupational therapists, physiotherapists, and podiatrists according to the MMM categories, we used SA1 data to align with the spatial unit used by the MMM. To calculate the density of occupational therapists, physiotherapists, and podiatrists according to IRSAD, we used SA2 data because according to ABS the SA2s are designed to represent communities that interact together socially and economically. All statistical analysis was conducted using Stata/SE version 17 (StataCorp., College Station, TX, USA).

Ethics statement

Ethics approval and the need for participant consent for this study were exempted by the University of South Australia’s Human Research Ethics Committee (Application ID: 203544).

Results

Density of occupational therapists by MMM categories and IRSAD

The density of occupational therapists within the MMM categories is presented in Fig 1. The national density of occupational therapists was highest in areas classified as MM 1 (10.9), and, except for MM 6, the density of occupational therapists decreased with the increasing levels of the MMM categories. Moreover, the density of occupational therapists varied according to each state and territory. For instance, in Victoria and New South Wales, the density of occupational therapists was highest in MM 2 areas, whereas in Queensland, South Australia, Western Australia and Australian Capital Territory, the density of occupational therapists was highest in MM 1 areas. In most states and territories, the pattern in the distribution of the occupational therapists density tended to be more concentrated in areas classified from MM 1–4, while areas classified from MM 5–7 exhibited less occupational therapists density. In the whole of Australia as well as in each state and territory that have areas classified from MM 5–7, the density of occupational therapists was high in MM 6 areas when compared to MM 5 and MM 7 areas.

Fig 1. Distribution of registered occupational therapists by MMM categories in each state and territory in Australia.

Fig 1

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Fig 1 also shows that there were disparities in the density of occupational therapists among specific regions/areas across each state and territory in Australia. For instance, for MM2 areas, South Australia had the lowest density of occupational therapists (2.6) compared to other states and territories such as Victoria (12.6) and Northern Territory (11.4).

The density of occupational therapists according to IRSAD quintiles is presented in Fig 2. In the whole of Australia, the highest density of occupational therapists was found in areas with IRSAD quintile 5 (12.9) and decreased with the declining levels of IRSAD quintiles. However, the pattern in the distribution of occupational therapists density varied by IRSAD quintiles across each state and territory. For example, while Victoria, Queensland, and Western Australia had the highest density of occupational therapists in areas with IRSAD quintile 5, New South Wales, South Australia, Tasmania, and Northern Territory had the highest density of occupational therapists in areas with IRSAD quintile 4.

Fig 2. Distribution of registered occupational therapists by IRSAD in each state and territory in Australia.

Fig 2

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Density of physiotherapists by MMM categories and IRSAD

The national density of physiotherapists was highest in MM 1 areas (16.5), and, except for MM 6, the density of physiotherapists decreased with the increasing levels of the MMM categories. In the whole of Australia as well as in each state and territory that have areas classified from MM 5–7, the density of physiotherapists was high in MM 6 areas when compared to MM 5 and MM 7 areas. Northern Territory and Tasmania had the highest density of physiotherapists in MM 2 areas, while in all other states and territories, the density of physiotherapists was highest in areas classified as MM 1 (Fig 3).

Fig 3. Distribution of registered physiotherapists by MMM categories in each state and territory in Australia.

Fig 3

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Fig 3 also shows that there were disparities in the density of physiotherapists among specific regions/areas across each state and territory in Australia. For instance, for MM2 areas, South Australia had the lowest density of physiotherapists (6.1) compared to other states such as Victoria (13.2) and Tasmania (13.3).

The physiotherapists density by IRSAD quintiles is presented in Fig 4. The highest national density of physiotherapists was found in areas with IRSAD quintile 5 (23.3) and decreased with the declining levels of IRSAD quintiles. The pattern in the distribution of physiotherapists density varied by IRSAD quintiles across each state and territory. For instance, South Australia, Tasmania, and the Northern Territory had the highest physiotherapists density in areas with IRSAD quintile 4 while the physiotherapists density in the other states was highest in areas with IRSAD quintile 5.

Fig 4. Distribution of registered physiotherapists by IRSAD in each state and territory in Australia.

Fig 4

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Density of podiatrists by MMM categories and IRSAD

The podiatrists density by MM classification is presented in Fig 5. The national density of podiatrists was highest in MM 3 (2.7) areas, while it was lowest in MM 7 areas (0.6). Consistent with the national pattern, New South Wales, Victoria, Western Australia, and Tasmania had the highest density of podiatrists in MM 3. However, Queensland, South Australia, and Australian Capital Territory had the highest density of podiatrists in MM 1 areas. Furthermore, the overall density of podiatrists tended to be more concentrated in areas classified as MM 1–4 across each state and territory while areas classified as MM 5–7 exhibited less podiatrists density.

Fig 5. Distribution of registered podiatrists by MMM categories in each state and territory in Australia.

Fig 5

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Fig 6 shows the density of podiatrists stratified by IRSAD quintiles. The highest national density of podiatrists was found in areas with IRSAD quintile 5 (3.0) and decreased with the declining levels of IRSAD quintiles. The pattern in the distribution of podiatrists density varied by IRSAD quintiles across each state and territory. For instance, New South Wales, South Australia, Tasmania, and the Northern Territory had the highest density of podiatrists in areas with IRSAD quintile 4 while the density of podiatrists in all other states was highest in areas with IRSAD quintile 5.

Fig 6. Distribution of registered podiatrists by IRSAD in each state and territory in Australia.

Fig 6

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Discussion

Main findings

The present study revealed that there was uneven distribution of occupational therapists, physiotherapists, and podiatrists according to measures of rurality classification (MMM) and area-level socioeconomic status (IRSAD) across Australian jurisdictions. The national density of occupational therapists and physiotherapists was highest in areas classified as MM 1 and decreased with the increasing levels of the MMM categories. However, the national podiatrists density was variable across the categories of the MMM. In most states and territories, the pattern in the distribution of occupational therapists, physiotherapists and podiatrists density tended to be higher in areas classified from MM 1–4, while areas classified from MM 5–7 exhibited less occupational therapists density. Moreover, notable variations in the density of occupational therapists, physiotherapists, and podiatrists were also observed when analysing specific regions (such as MM 2 regions) in different Australian states and territories. In terms of IRSAD quintiles, the national density of occupational therapists, physiotherapists, and podiatrists was highest in areas with IRSAD quintile 5 and decreased with the declining levels of IRSAD quintiles. However, the pattern in the distribution of occupational therapists, physiotherapists, and podiatrists density varied by IRSAD quintiles across each state and territory. To the best of our knowledge, this is the first comprehensive study in Australia that has described the density of occupational therapists, physiotherapists, and podiatrists stratified by measures of rurality and area-level socioeconomic position. The findings of our study will provide a comprehensive information to inform allied health workforce planning in Australia.

Our finding that there was highest national density of occupational therapists and physiotherapists in ‘metropolitan areas’ (MM 1) and most advantaged areas (i.e., IRSAD quintile 5) may reflect better employment opportunities in metropolitan Australia. Conversely, the lower densities of occupational therapists and physiotherapists in ‘very remote communities’ (MM 7) and most disadvantaged areas (IRAD quintile 1) may explain the smaller range of employment and career opportunities in remote areas across Australia. A previous study conducted in South Africa by Ned et al. [18] found that there was spatial variation in the distribution of occupational therapists across jurisdictions. They found that the majority of occupational therapists were concentrated in urbanised provinces. Consistent with our findings, several studies conducted in Canada [14–16] found that the distribution of physiotherapists varies according to health regions and population size, suggesting reduced access to physiotherapy services, particularly in rural and remote areas as well as sparsely populated areas.

Variations in the density of the three allied health workforce by a measure of rurality and jurisdiction

The highest states-wide density of occupational therapists, physiotherapists, and podiatrists varied according to MM categories across each state and territory in Australia. For instance, Victoria and New South Wales had the highest density of occupational therapists in MM 2 areas, whereas Northern Territory and Tasmania had the highest physiotherapists density in MM 2 areas. The highest density of the three allied health workforce in areas classified as MM 2 in Northern Territory and Tasmania is likely explained by absence of MM 1 areas in either jurisdiction. Moreover, in the whole of Australia as well as in each state and territory that have areas classified from MM 5–7, the density of physiotherapists was high in MM 6 areas when compared to MM 5 and MM 7 areas. Although it is unclear why MM 6 areas have higher density of these group of allied health practitioners, this finding is not surprising because the MMM scale is not meant to be in an ordinal scale and the health workforce density calculation considers total population of an area. Generally, the density of these three groups of allied health workforce tends to be more concentrated in areas classified from MM 1–4 across each state and territory while areas classified from MM 5–7 exhibited less health workforce density. As such, health workforce policies aimed to address workforce shortage need to focus on rural and remote communities. For instance, the Australian Rural Health Multidisciplinary Training (RHMT) program, which is one of several Commonwealth rural health workforce programs, aimed at recruiting and retaining health workforce has been in place for the past two decades. As it was emphasized in an independent review of the RHMT program conducted in 2020 [24], the program should continue investing in communities experiencing health workforce shortages. Consistent with the existing policy initiatives to address workforce maldistribution in high income countries [25], the RHMT program plays a key role to increase and maintain the numbers of health workforce, including occupational therapists, physiotherapists, and podiatrists, thereby attempting to correct the geographic maldistributions. Moreover, funding and regulating allied health services by state and territory governments in their jurisdictions is essential to help correct uneven distribution of allied health workforce, particularly in rural and remote areas.

Variations in the density of the three allied health workforce by area-level socioeconomic status and jurisdiction

The national density of occupational therapists, physiotherapists, and podiatrists was highest in IRSAD quintile 5 and decreased with the declining levels of the IRSAD quintiles. These figures suggest the presence of more allied health workforce in the most advantaged areas (IRSAD quintile 5) than the most disadvantaged areas (IRSAD quintile 1) in Australia. Similarly, in most states and territories, the occupational therapists, physiotherapists, and podiatrists density was highest in IRSAD quintiles 5. However, unlike the national distribution, South Australia, Tasmania, and Northern Territory had the highest density of occupational therapists, physiotherapists, and podiatrists in IRSAD quintile 4. The presence of higher density of these three allied health workforces in areas with IRSAD quintiles 4 or 5 is likely to be determined by metropolitan locations (i.e., MM 1). This is because metropolitan areas usually have higher IRSAD scores due to many households with high incomes and many people in skilled occupations. As metropolitan areas are classified as MM 1, the presence of high IRSAD scores in metropolitan areas demonstrates the inherent associations between the MMM classification and IRSAD scales. Moreover, our finding that the density of occupational therapists, physiotherapists, and podiatrists was lowest in areas of greatest socioeconomic disadvantage (i.e., IRSAD quintile 1) in Australia would appear to be intuitive because the most disadvantaged areas (quintile 1) tended to be in regional and rural areas, and it was previously reported that residents in rural and remote areas experience poorer access to health care services when compared with Australians living in metropolitan areas [4]. However, to properly analyse the overlap of remoteness and disadvantage, it is crucial to consider the specific context and relevant factors that could either intensify or alleviate the overlap between these two dimensions/measures.

Strengths and limitations

The strengths of this study include the use of public registration data of occupational therapists, physiotherapists, and podiatrists from AHPRA, linked with publicly available national data from the Australian Department of Health and the Australian Bureau of Statistics. To link the data sets in the current study, we applied the methods described by Versace et al. [21] in their 2021 analysis of access, population distribution, and socio-economic status. A 2020 scoping review by Gillam et al. [26] recommended the use of linked data sets to help inform health workforce development and service planning in Australia. Moreover, Walsh et al. [25] in their 2020 study suggested that studies that focus on addressing rural allied health, nursing and dentistry workforce maldistribution should to be done at scale or with explicit links to coherent overarching policy. In the current study, the use of linked data from diverse sources enabled us to provide new insights into the distribution of registered occupational therapists, physiotherapists, and podiatrists across Australia, categorised by the MMM classifications and IRSAD quintiles. The study’s findings, indicating a substantial distribution disparity of allied health workforce in Australia, with a concentration in metropolitan and advantaged areas and limited access in remote and disadvantaged regions, hold significant implications. From a clinical perspective, this underscores the critical need to customise healthcare delivery to address these disparities, ensuring equitable access for all patients, regardless of their location or socioeconomic status. These insights also serve as valuable resources for researchers, informing evidence-based policies and interventions aimed at enhancing healthcare access and outcomes on a national scale. Furthermore, in addition to the national analysis of the distribution of occupational therapists, physiotherapists, and podiatrists by the MMM and IRSAD, we have also provided a detailed description of the distribution of these allied health professionals by the MMM classifications and IRSAD quintiles for each state and territory.

This study has some limitations. First, although the present study found a significant disparity in the allied health workforce distribution within each state and territory in Australia when classified by MMM and IRSAD quintile, further studies should explore these variations in detail across rural and disadvantaged areas. This is essential because some rural areas and disadvantaged populations may have unique characteristics that require targeted solutions. For instance, the recruitment of physiotherapists in certain rural regions may be easier than other rural areas, depending on contextual factors. Second, as the present study included only three allied health professionals, a future study needs to include a more exhaustive list of allied health workforce, noting that the AHPRA does not capture all allied health professions such as social workers. Third, as our study only focused on describing the distribution of three allied health workforce, further work is needed to understand factors associated with allied health workforce recruitment and retention in Australia. Finally, our analysis was based only on one of four SEIFA indexes (i.e., IRSAD). As each SEIFA index measure a different aspect of the socioeconomic conditions in each area, summarizing a different set of social and economic information, it would be important to study the distribution of allied health workforce by other SEIFA indexes in the future.

Conclusions

This study found that there was uneven distribution of registered occupational therapists, physiotherapists, and podiatrists according to measures of rurality (MMM) and areal-level socioeconomic status (IRSAD) across Australian jurisdictions. The density of these three groups of allied health workforce tends to be more concentrated in metropolitan and the most advantaged areas (IRSAD quintiles 4 or 5) while remote and disadvantaged areas exhibited less allied health workforce density across each state and territory. The differing distribution of these group of allied health workforce suggests that a wide range of policy responses may be required to ensure equity of access to allied health care in all areas across states and territories. These measures are crucial in ensuring that healthcare services remain accessible and equitable for all Australians, irrespective of their geographic location or socioeconomic status.

Supporting information

S1 Table. Proportion of registered occupational therapists, physiotherapists, and podiatrists by MMM in Australia and in each state and territory, April 2020.

(PDF)

Click here for additional data file. (138.1KB, pdf)
S2 Table. Proportion of registered occupational therapists, physiotherapists, and podiatrists by SA2 IRSAD quintiles in Australia, April 2020.

(PDF)

Click here for additional data file. (157.4KB, pdf)

Acknowledgments

The authors would like to acknowledge the Commonwealth Department of Health, Rural Health Multidisciplinary Training (RHMT) Program.

Data Availability

All the three data sources used in the study are publicly available. The data can be accessible online from the AHPRA (https://www.ahpra.gov.au/), ABS (https://www.abs.gov.au/websitedbs/censushome.nsf/home/seifa) and the Commonwealth Department of Health (https://data.gov.au/data/dataset/modified-monash-model-mmm-2019).

Funding Statement

This study was funded by the Commonwealth Department of Health via the Rural Health Multidisciplinary Training (RHMT) Program. The funder played no role in the design, conduct or interpretation of the analyses.

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Decision Letter 0

Enamul Kabir

13 Dec 2022

PONE-D-22-18539Geographic distribution of registered occupational therapists, physiotherapists and podiatrists in AustraliaPLOS ONE

Dear Dr. Yisma,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Jan 27 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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We look forward to receiving your revised manuscript.

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Enamul Kabir

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: I Don't Know

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This is a relatively simple paper that describes the distribution of Australia’s allied health workforce (physio, OT, podiatry) at both a state and national scale, against 2 classifications measuring (1) rurality; (2) socio-economic status / IRSAD. There are many improvements required to its presentation.

Their title is misleading – they state “geographic distribution”, but IRSAD is technically not a geographical scale. It is a demographic classification – knowing that there are more services in a high IRSAD area does not by itself reveal geog distribution, without adding an extra geographic layer of where the high IRSAD areas are located.

I’m also not comfortable with their reference to the MM classification as a measure of “geographic access” – it is not. I am aware of reference #11 describing it in this way, but in this paper, it is actually quite confusing and misleading to use this phrase. The one ‘access’ measure this paper does utilise is the provider-to-population ratio (i.e. ‘density’), but confusingly the authors are not referring to that. The MM classification is a measure of ‘rurality’, it combines a geographic component (remoteness) with a demographic component (population size). The authors may be aware that the original measure of ‘remoteness’ (ARIA) had the word ‘accessibility’ in its name and some of the category labels used ‘accessible’; however this was highly criticised because it was NOT a measure of access, hence it was changed to the newer RA scale and variants of the word ‘access’ were wholly removed. The MM scale (which is partly defined by the RA scale) should also be applied this way.

I was somewhat disappointed by their presentation / discussion of the results. The authors almost wholly focus on the extreme categories only – those with the highest workforce density (can call this ‘access’) and those with the least. Unsurprisingly, this largely matches the extreme categories of both scales. The authors largely ignore whatever patterns are observed within the middle categories, which is arguably where much of the interest of these data is.

I think that part of the problem is that the authors have too many layers they’re trying to describe, forgetting that ‘distribution’ is the primary interest. Having 3x clinician types means that there are three patterns to describe, with little gained from if they focused on one. Jurisdictional differences may be important to some service planners, but generally add little to the paper’s value. Moreover, having 2x distribution scales doubles the observed patterns. Specific distributional differences should be the majority point of focus (e.g. what is the step down/up ratio of density (access) between categories of the MM / IRSAD classifications? Why is MM-6 generally ‘better’ than MM-5 / MM-5? (PS: this is not surprising, the MM scale is not meant to always be ordinal).

Where required, the authors don’t clarify certain patterns – chief example is the highest density in NT and Tas being in MM-2, rather than MM-1 (which is 100% explained by there being no MM-1 locations in either jurisdiction). Also, the authors at no point discuss the inherent association(s) between the MM and IRSAD scales. IRSAD differences (particularly at the higher end) will likely mostly be determined by metropolitan locations (ie. within MM-1). The last sentence prior to the Strengths directly assumes assoc between lower density and lower IRSAD relates to rural communities, but they have never actually demonstrated a linkage between MM and IRSAD.

Reflecting on my earlier point, the first sentence of the conclusion is nonsensical – ‘access’ belongs with the uneven distribution part of the sentence. The next sentence is not appropriate (‘accessible’ and ‘least accessible’ are incorrect labels). The last sentence is OK, with ‘equity of access’ being about the service levels (density). The Abstract conclusion needs to be similarly fixed up.

Another nonsensical statement is at lines 257-259 (“Conversely, the lower densities…”), which essentially is saying the ‘lower access (density)’…may explain the ‘lower access (availability)’! Following this, the heading “Variation by access and jurisdiction” needs changing.

One paragraph didn’t make sense to me – starting at line 189; it twice refers to NSW, SA, Tas, NT, ACT but I can’t determine why they are stated twice.

Reviewer #2: Major comments:

1. While this may be the first study of this kind in Australia, this type of study has been done in other countries including USA and Canada. The authors are encouraged to expand introductions and discussions comparing their findings with other studies. Are there any novel findings from this particular study?

Minor comments:

2. Abstract: The authors are requested to include the study objective after the background.

3. The background needs to describe in more detail why this study is so critical?

4. Discussion section also did not present according to the research purpose and result. The authors are encouraged to Interpret and explain study results, and critically compare to previous studies. For example, at first occupational therapist then physiotherapist and finally podiatrist.

5. Page 17, line 316-317. This sentence is not a limitation as the authors are focusing their objective based on three professions- occupational therapist, physiotherapist and podiatrist. Please drop it.

**********

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Reviewer #1: No

Reviewer #2: Yes: Mohammad Habibur Rahman Sarker

**********

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PLoS One. 2023 Sep 21;18(9):e0291962. doi: 10.1371/journal.pone.0291962.r002

Author response to Decision Letter 0

1 Feb 2023

"Geographic distribution of registered occupational therapists, physiotherapists and podiatrists in Australia" (MS: PONE-D-22-18539).

Dear Editor,

We are very grateful for the constructive comments from the editor and reviewers. We have taken due consideration of the comments provided and made the necessary revisions to the manuscript. All page and line numbers refer to the marked copy of the manuscript.

Response to Editorial comments

COMMENT: Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming.

AUTHORS’ RESPONSE: In the revision, we have re-formatted our manuscript according to the PLOS ONE’s style, including the file naming.

COMMENT: Please provide additional details regarding participant consent. In the ethics statement in the Methods and online submission information, please ensure that you have specified (1) whether consent was informed and (2) what type you obtained (for instance, written or verbal, and if verbal, how it was documented and witnessed). If your study included minors, state whether you obtained consent from parents or guardians. If the need for consent was waived by the ethics committee, please include this information.

If you are reporting a retrospective study of medical records or archived samples, please ensure that you have discussed whether all data were fully anonymized before you accessed them and/or whether the IRB or ethics committee waived the requirement for informed consent. If patients provided informed written consent to have data from their medical records used in research, please include this information

Once you have amended this/these statement(s) in the Methods section of the manuscript, please add the same text to the “Ethics Statement” field of the submission form (via “Edit Submission”).

For additional information about PLOS ONE ethical requirements for human subjects research, please refer to http://journals.plos.org/plosone/s/submission-guidelines#loc-human-subjects-research.

AUTHORS’ RESPONSE: Given that we have utilised publicly available data sources, ethics approval and the need for participant consent for this study were exempted by the University of South Australia’s Human Research Ethics Committee (Application ID: 203544). In the revision, we have stated this in the methods section of our manuscript, and we have added the same text to the “Ethics Statement” field of the submission form. Our revision can be found in the methods section track changed.

Response to Reviewer #1

COMMENT: This is a relatively simple paper that describes the distribution of Australia’s allied health workforce (physio, OT, podiatry) at both a state and national scale, against 2 classifications measuring (1) rurality; (2) socio-economic status / IRSAD. There are many improvements required to its presentation.

AUTHORS’ RESPONSE: In the revision, we have significantly improved the presentation of results and interpretation based on the reviewers’ comments. Our revision can be accessed in the track changes in the revised manuscript.

COMMENT: Their title is misleading – they state, “geographic distribution”, but IRSAD is technically not a geographical scale. It is a demographic classification – knowing that there are more services in a high IRSAD area does not by itself reveal geog distribution, without adding an extra geographic layer of where the high IRSAD areas are located.

AUTHORS’ RESPONSE: We apologise for our misleading title. We have removed the term ‘geographic’ from our title and have revised the title as “The distribution of registered occupational therapists, physiotherapists and podiatrists in Australia". We appreciate that although IRSAD measures the socioeconomic status of an area, it is a sociodemographic measure and may not be used to describe geographic classification on its own. We have revised the text of our manuscript accordingly and our revision can be found in track changes in the revised manuscript.

COMMENT: I’m also not comfortable with their reference to the MM classification as a measure of “geographic access” – it is not. I am aware of reference #11 describing it in this way, but in this paper, it is actually quite confusing and misleading to use this phrase. The one ‘access’ measure this paper does utilise is the provider-to-population ratio (i.e., ‘density’), but confusingly the authors are not referring to that. The MM classification is a measure of ‘rurality’, it combines a geographic component (remoteness) with a demographic component (population size). The authors may be aware that the original measure of ‘remoteness’ (ARIA) had the word ‘accessibility’ in its name and some of the category labels used ‘accessible’; however, this was highly criticised because it was NOT a measure of access, hence it was changed to the newer RA scale and variants of the word ‘access’ were wholly removed. The MM scale (which is partly defined by the RA scale) should also be applied this way.

AUTHORS’ RESPONSE: Thank you for the comments. We agree that the MMM classification should not be used as a measure of “geographic access”. We have removed the phrase “geographic access” and replaced it with the appropriate phrase throughout the manuscript. We have also focused on the ‘Provider-to-population ratio (i.e., ‘density’)’ as a measure of access as per your suggestion in the revised manuscript. Our revision can be found as track changes in the revised manuscript.

COMMENT: I was somewhat disappointed by their presentation / discussion of the results. The authors almost wholly focus on the extreme categories only – those with the highest workforce density (can call this ‘access’) and those with the least. Unsurprisingly, this largely matches the extreme categories of both scales. The authors largely ignore whatever patterns are observed within the middle categories, which is arguably where much of the interest of these data is.

AUTHORS’ RESPONSE: Thank you for this comment. In the revision, we have considered all categories of the MMM and IRSAD classification when presenting and discussing the results in our revised manuscript. In the whole of Australia, the highest density of the three allied health workforce was found in areas classified as MM 1 and decreased with the increasing levels of the MMM categories. Furthermore, in the whole of Australia, the highest density of the three allied health workforce was found in areas with IRSAD quintile 5 and decreased with the declining levels of IRSAD quintiles. However, the pattern in the distribution of the three allied health workforce densities varied widely by the MMM categories and IRSAD quintiles across each state and territory. Our revision can be accessed in track changes in the “Results” and “Discussion” sections.

COMMENT: I think that part of the problem is that the authors have too many layers they’re trying to describe, forgetting that ‘distribution’ is the primary interest. Having 3x clinician types means that there are three patterns to describe, with little gained from if they focused on one. Jurisdictional differences may be important to some service planners, but generally add little to the paper’s value. Moreover, having 2x distribution scales doubles the observed patterns. Specific distributional differences should be the majority point of focus (e.g. what is the step down/up ratio of density (access) between categories of the MM / IRSAD classifications? Why is MM-6 generally ‘better’ than MM-5 / MM-5? (PS: this is not surprising; the MM scale is not meant to always be ordinal).

AUTHORS’ RESPONSE: In the revision, we have focused on describing the distributional differences of the three allied health workforce densities stratified by the MMM and IRSAD in the whole of Australia as well as in each state and territory as per your comments. Our revision can be found in track changes in the text of the revised manuscript.

COMMENT: Where required, the authors don’t clarify certain patterns – chief example is the highest density in NT and Tas being in MM-2, rather than MM-1 (which is 100% explained by there being no MM-1 locations in either jurisdiction). Also, the authors at no point discuss the inherent association(s) between the MM and IRSAD scales. IRSAD differences (particularly at the higher end) will likely mostly be determined by metropolitan locations (ie. within MM-1). The last sentence prior to the Strengths directly assumes assoc between lower density and lower IRSAD relates to rural communities, but they have never actually demonstrated a linkage between MM and IRSAD.

AUTHORS’ RESPONSE: Thank you for this comment. In the revision, we have added sentences to the revised manuscript to explain the distributional patterns observed in the Northern Territory and Tasmania as per your suggestion (see page 19, lines 334-336). We have also added a couple of new sentences to the revised manuscript to explain the inherent association between the MMM and IRSAD classifications in the revised manuscript (see page 21, lines, 368-373).

COMMENT: Reflecting on my earlier point, the first sentence of the conclusion is nonsensical – ‘access’ belongs with the uneven distribution part of the sentence. The next sentence is not appropriate (‘accessible’ and ‘least accessible’ are incorrect labels). The last sentence is OK, with ‘equity of access’ being about the service levels (density). The Abstract conclusion needs to be similarly fixed up.

AUTHORS’ RESPONSE: We have revised the ‘Conclusion’ section as per your comments, and we now believe that the conclusion is appropriate. We have also revised the conclusion in the Abstract. Our revision can be found in track changes in the revised manuscript.

COMMENT: Another nonsensical statement is at lines 257-259 (“Conversely, the lower densities…”), which essentially is saying the ‘lower access (density)’…may explain the ‘lower access (availability)’! Following this, the heading “Variation by access and jurisdiction” needs changing.

AUTHORS’ RESPONSE: We have revised the stated sentence to make the message being conveyed clearer. We have also revised the heading that reads, “Variation by access and jurisdiction” as “Variation in the density of the three allied health workforce by an objective measure of rurality and jurisdiction”. Our revision can be accessed in track changes in the revised manuscript.

COMMENT: One paragraph didn’t make sense to me – starting at line 189; it twice refers to NSW, SA, Tas, NT, ACT but I can’t determine why they are stated twice.

AUTHORS’ RESPONSE: In the revision, we have grossly revised the stated paragraph to make the message conveyed clearer.

Response to Reviewer #2

Major comments

COMMENT: While this may be the first study of this kind in Australia, this type of study has been done in other countries including USA and Canada. The authors are encouraged to expand introductions and discussions comparing their findings with other studies. Are there any novel findings from this particular study?

AUTHORS’ RESPONSE: We understand that there are a few studies conducted in the USA and Canada regarding the distribution of the allied health workforce, with a focus on physiotherapists and occupational therapists. In the revision, we have added some more new references to expand the ‘Introduction’ and ‘Discussion’ sections as per your comments. Our revision can be found in track changes in the revised manuscript.

Given that our current study is the first study in Australia that described the distribution of three allied health workforce (physiotherapists, occupational therapists, and podiatrists) according to an objective measure of location/rurality and area-level socioeconomic status, there are several novel findings from this study. These include: (1) In the whole of Australia, the highest densities of the three allied health workforce were found in areas classified as MM 1 and decreased with the increasing levels of the MMM categories. (2) In the whole of Australia, the highest densities of the three allied health workforce were found in areas with IRSAD quintile 5 and decreased with the declining levels of IRSAD quintiles. (3) The patterns of the three allied health workforce densities were unevenly distributed by MM categories and IRSAD quintiles across each state and territory. (4) The densities of these three groups of allied health workforce appeared to be more concentrated in areas classified from MM 1-4 across each state and territory while areas classified from MM 5-7 exhibited less allied health workforce density.

Minor comments

COMMENT: Abstract: The authors are requested to include the study objective after the background.

AUTHORS’ RESPONSE: In the revision, we have included the study objective in the Abstract. Our revision can be accessed in track changes in the revised manuscript.

COMMENT: The background needs to describe in more detail why this study is so critical?

AUTHORS’ RESPONSE: In the revision, we have added more descriptions regarding why our current study is very important. Our revision can be found in the track changes in the revised manuscript (see page 8, lines, 128-132).

COMMENT: Discussion section also did not present according to the research purpose and result. The authors are encouraged to Interpret and explain study results, and critically compare to previous studies. For example, at first occupational therapist then physiotherapist and finally podiatrist.

AUTHORS’ RESPONSE: In the revision, we have added some new explanations and interpretations of the results of our study in the “Discussion” section. We have also re-structured the discussion to align with the study purpose and results. Moreover, we have compared our findings to previous studies conducted in Canada and South Africa. Our revision can be found in the track changes in the revised manuscript.

COMMENT: Page 17, line 316-317. This sentence is not a limitation as the authors are focusing their objective based on three professions- occupational therapist, physiotherapist and podiatrist. Please drop it.

AUTHORS’ RESPONSE: Thank you for alerting us to this. We have revised it accordingly.

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file. (36.9KB, docx)

Decision Letter 1

Moin Uddin Ahmed

28 Apr 2023

PONE-D-22-18539R1The distribution of registered occupational therapists, physiotherapists, and podiatrists in AustraliaPLOS ONE

Dear Dr. Yisma,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Jun 12 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Moin Uddin Ahmed

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #3: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #3: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: (No Response)

Reviewer #3: This is a descriptive study that presents important information about workforce distribution in Australia. The finding that the allied health workforce is lower per population in more remote regions and those with higher levels of disadvantage is not new, but the detail provided about these three disciplines offers new information. It is important for those involved in workforce planning, development and research to have this information. The paper is also clear, refers to relevant literature and describes the sources of data well. The patterns are described clearly and the implications of these are discussed in the latter sections.

The study would benefit from being more analytical. More detail about specific regions and the patterns and variations of regions would add to this paper. For example, the authors might provide examples of particular places/regions in different states to give more depth. Is it possible to consider how remoteness and disadvantage overlap (and where they do not)?

There are some minor changes for the authors to consider. First, in the results section of the abstract, it states: “However, there was no clear pattern in the distribution of occupational therapists, physiotherapists, and podiatrists density when stratified by the MMM classifications and IRSAD quintiles across each state and territory in Australia.” I could not find evidence of this in the paper; were MM and IRSAD analysed together? Or is this a general sentence, and if so, I would question whether these was not a pattern across MM regions.

Second, I would have liked a sentence in the limitations section to acknowledge variations and differences within states and within these categories. The macro view is important but rural areas and types of disadvantage differ and it is important to acknowledge this. It is easier to recruit a physio to some rural regions than others.

Third, on Line 188, it states “…because SA2 represents communities that interact together socially and economically;” is this correct? Fourth, I was unsure why MM was referred to as an “objective” measure. Finally, there are a couple of editing issues: (1) The phrase on Line 69 “lived shorter” is awkward wording. (2) The sentence on Line 144 “The AHPRA data were extracted in April 2020, which were de-identified” is also awkward wording.

Overall, while a descriptive paper, the evidence of the variation in distribution of the allied health workforce in Australia according to remoteness and levels of disadvantage is important. The detailed graphs presented in this paper would be very useful and I would likely cite this paper.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #3: No

**********

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While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2023 Sep 21;18(9):e0291962. doi: 10.1371/journal.pone.0291962.r004

Author response to Decision Letter 1

7 May 2023

"The distribution of registered occupational therapists, physiotherapists and podiatrists in Australia" (MS: PONE-D-22-18539R1).

Dear Editor,

We are very grateful for the constructive comments from reviewers. We have taken due consideration of the comments provided and made the necessary revisions to the manuscript. All page and line numbers refer to the marked copy of the manuscript.

Response to Reviewer #3

COMMENT: This is a descriptive study that presents important information about workforce distribution in Australia. The finding that the allied health workforce is lower per population in more remote regions and those with higher levels of disadvantage is not new, but the detail provided about these three disciplines offers new information. It is important for those involved in workforce planning, development and research to have this information. The paper is also clear, refers to relevant literature and describes the sources of data well. The patterns are described clearly and the implications of these are discussed in the latter sections.

AUTHORS’ RESPONSE: Thank you.

COMMENT: The study would benefit from being more analytical. More detail about specific regions and the patterns and variations of regions would add to this paper. For example, the authors might provide examples of particular places/regions in different states to give more depth. Is it possible to consider how remoteness and disadvantage overlap (and where they do not)?

AUTHORS’ RESPONSE: In the revision, we have added more details regarding the distribution of allied health workforce in specific regions/areas (such as MM 2 regions) across each state and territory in Australia. Our revision can be found in track changes in the revised manuscript (see page 11 and page 13).

Yes, it is possible to consider how remoteness and disadvantage overlap and where they do not. Remoteness and disadvantage can often overlap in areas where access to resources and services is limited due to geographical barriers or economic and social barriers. However, there may be situations where remoteness and disadvantage do not overlap. For instance, individuals living in a remote area may have access to the same resources and services as individuals living in metropolitan area due to availability of infrastructure and technology. Conversely, individuals living in a metropolitan area may experience disadvantage due to poverty, discrimination, or other social and economic factors. In the revision, we have included an explanation highlighting the significance of considering specific context and relevant factors for a thorough analysis of the overlap between remoteness and disadvantage. Our revision can be found tracked changed in the revised manuscript (see page18).

COMMENT: There are some minor changes for the authors to consider. First, in the results section of the abstract, it states: “However, there was no clear pattern in the distribution of occupational therapists, physiotherapists, and podiatrists density when stratified by the MMM classifications and IRSAD quintiles across each state and territory in Australia.” I could not find evidence of this in the paper; were MM and IRSAD analysed together? Or is this a general sentence, and if so, I would question whether these was not a pattern across MM regions.

AUTHORS’ RESPONSE: The MMM and IRSAD data were analyzed independently. In the revision, we have made improvements to the stated sentence to enhance clarity. The revised sentence can be found in the track changes in the “Abstract” section the revised manuscript.

COMMENT: Second, I would have liked a sentence in the limitations section to acknowledge variations and differences within states and within these categories. The macro view is important but rural areas and types of disadvantages differ and it is important to acknowledge this. It is easier to recruit a physio to some rural regions than others.

AUTHORS’ RESPONSE: Thank you for your feedback. In the revision, we have acknowledged that further studies should explore the significant disparities in the allied health workforce distribution in Australia when classified by MMM categories and IRSAD quintile in detail across rural and disadvantaged areas. This is essential because some rural areas and disadvantaged populations may have unique characteristics that require targeted solutions. Our revision can be found in track changes in the revised manuscript (page 19 and page 20).

COMMENT: Third, on Line 188, it states “…because SA2 represents communities that interact together socially and economically;” is this correct?

AUTHORS’ RESPONSE: Yes, it is correct. According to the Australian Bureau of Statistics (ABS), SA2s are designed to represents communities that interact together socially and economically. However, we have made some improvements to the wording in order to enhance the clarity of the message being conveyed. Our revision can be found in track changes on page 10.

COMMENT: Fourth, I was unsure why MM was referred to as an “objective” measure.

AUTHORS’ RESPONSE: The MMM is designed to provide an objective measure of geographic remoteness because it is based on specific criteria and data points that can be quantified and assessed in a consistent manner. However, like any measure, it is important to note that the MMM is not entirely free from subjectivity or limitations. In the revision, for the sake of clarity, we have removed the word "objective" throughout the revised manuscript. Our revision can be found in track changes.

COMMENT: Finally, there are a couple of editing issues: (1) The phrase on Line 69 “lived shorter” is awkward wording. (2) The sentence on Line 144 “The AHPRA data were extracted in April 2020, which were de-identified” is also awkward wording.

AUTHORS’ RESPONSE: Thank you for the comments. In the revision, we have made some edits to improve the clarity of the conveyed message. Our revision can be found in track changes in the revised manuscript.

COMMENT: Overall, while a descriptive paper, the evidence of the variation in distribution of the allied health workforce in Australia according to remoteness and levels of disadvantage is important. The detailed graphs presented in this paper would be very useful and I would likely cite this paper.

AUTHORS’ RESPONSE: Thank you.

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file. (31.2KB, docx)

Decision Letter 2

Marianne Clemence

15 Aug 2023

PONE-D-22-18539R2The distribution of registered occupational therapists, physiotherapists, and podiatrists in AustraliaPLOS ONE

Dear Dr. Yisma,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please accept my apologies for the additional perspectives obtained late in the peer review process. Nevertheless, Reviewer #5 has a few suggestions, appended below, that you may wish to consider to improve your manuscript. In particular, they request additional clarifications about the data sources, which would improve the quality of reporting. Please address this comment:""We linked data from three sources: (1) the public registration data of occupational therapists, physiotherapists, and podiatrists obtained from the Australian Health Practitioner Regulation Agency (AHPRA), the Modified Monash Model (MMM) 2019 data from the Australian Department of Health; and the Socio-Economic Indexes for Areas (SEIFA)”- Why are 3 data sources needed? Explain. Do all these agencies have committees in place to study the markers of an effective workforce, to manage demands related to access, and to create and implement public policies aimed at improving their health systems?"

Regarding the recommendation that you cite specific previously published works, as always we recommend that you please review and evaluate the requested works to determine whether they are relevant and should be cited. It is not a requirement to cite these works.

We would consider that the other suggestions, and the minor points from Reviewer #6, are not required for your manuscript to meet the PLOS ONE publication criteria and may be considered optional. However, if you do decide to make any changes, please ensure that you keep in mind that conclusions must be presented appropriately and should not be overstated, particularly with respect to clinical implications. Please submit your revised manuscript by Sep 29 2023 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

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If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

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We look forward to receiving your revised manuscript.

Kind regards,

Marianne Clemence

Staff Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #4: All comments have been addressed

Reviewer #5: All comments have been addressed

Reviewer #6: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #4: Yes

Reviewer #5: Yes

Reviewer #6: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #4: Yes

Reviewer #5: Yes

Reviewer #6: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #4: Yes

Reviewer #5: Yes

Reviewer #6: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #4: Yes

Reviewer #5: Yes

Reviewer #6: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #4: The authors have adequately responded to all comments, and I have no additional concerns.

Reviewer #5: Article: PONE-D-22-18539R2

The distribution of registered occupational therapists, physiotherapists, and podiatrists in Australia

GENERAL COMMENTS

Thank you for allowing me to review this manuscript. The manuscript adhere the PLOS ONE Data Policy. The aim of this study was to describe the national as well as states-and territories-wide distribution of registered occupational therapists, physiotherapists, and podiatrists by measures of rurality and area-level socioeconomic position in Australia. This is a descriptive exploratory quantitative study. It’s an interesting research topic with potential utilization across health disciplines and relevant to the journal. Health care workforce is a global priority to achieve universal health coverage. In my opinion, the paper would need minor changes. Revisions will be necessary. Improve the organization of your paper using the following guidelines.

Those places have all convened committees to study the markers of an effective workforce, to manage the demands related to access, and to create and implement public policies aimed at improving their health care systems.

INTRODUCTION

Abstract: The title of the study and the objective of the study is not matching (include: workforse) Please revise it.

The WHO, rehabilitation group, is being very active in the latter years with activities for strengthening rehab in health systems, with workforce as one of the pillars, with plenty of works, gatherings and citations you could/should use - the most significant. Global Forum on Human Resources for Health, an analysis of the WHO Global Health Observatory Data Repository containing information from 36 countries showed that maintaining a sufficient health care workforce is a global priority and that the effectiveness of that workforce should be determined by calculating the healthcare workforce-to-population ratio. Include these references. It is importantly to systematically search/approach/use/build over the strengths and gaps of the literature on the topic beforehand.

1.Campbell J, Dussault G, Buchan J, Pozo-Martin F, Guerra Arias M, Leone C, Siyam A, Cometto G. A universal truth: No health without a workforce. Forum Report, Third Global Forum on Human Resources for Health, Recife, Brazil. Geneva, Global Health Workforce Alliance and World Health Organization. 2013. http://www.who.int/workforcealliance/knowledge/ resources/hrhreport2013/en/. Accessed 13 Feb 2017.

2. World Health Organization. Dublin Declaration on Human Resources for Health. Fourth Global Forum on Human Resources for Health. 2017. http://www.who.int/hrh/events/Dublin_Declaration-on-HumanResou rces-for-Health.pdf?ua=1.

3. World Health Organization. Global strategy for human resources for health: workforce 2030. Draft for the 69th World Health Assembly 2016. http://www.who.int/hrh/resources/16059_Global_strategyWorkfor ce2030.pdf?ua=1.

I list at least 3 relevant articles (directly focused on the physiotherapy workforce), that were not cited:

Jesus TS, Koh G, Landry M, et al. Finding the "Right-Size" Physical Therapy Workforce: International Perspective Across 4 Countries. Physical therapy 2016;96(10):1597-609. doi: 10.2522/ptj.20160014 [published Online First: 2016/05/07]

Landry MD, Hack LM, Coulson E, et al. Workforce Projections 2010-2020: Annual Supply and Demand Forecasting Models for Physical Therapists Across the United States. Physical therapy 2016;96(1):71-80. doi: 10.2522/ptj.20150010 [published Online First: 2015/10/17]

Shah TI, Milosavljevic S, Trask C, et al. Mapping Physiotherapy Use in Canada in Relation to Physiotherapist Distribution. Physiotherapy Canada Physiotherapie Canada 2019;71(3):213-19. doi: 10.3138/ptc-2018-0023 [published Online First: 2019/11/14]

-What’s new in the scientific literature with this manuscript? Include in introduction.

-The manuscript must be include a hypothesis. Explain the hypothesis.

METHODS

-"We linked data from three sources: (1) the public registration data of occupational therapists, physiotherapists, and podiatrists obtained from the Australian Health Practitioner Regulation Agency (AHPRA), the Modified Monash Model (MMM) 2019 data from the Australian Department of Health; and the Socio-Economic Indexes for Areas (SEIFA)”- Why are 3 data sources needed? Explain. Do all these agencies have committees in place to study the markers of an effective workforce, to manage demands related to access, and to create and implement public policies aimed at improving their health systems?

DISCUSSION

-Include the strengths of the study.

-The final paragraph should leave the reader with your final message within the framework of the hypotheses posed in the Introduction.

- Include the clinical significance of this study over clinicians, patients, and researchers after the study hypothesis.

Reviewer #6: Overall, a very good study synthesizing publicly available data sets to inform workforce planning. Please see a couple of suggestions for your consideration.

You may remove "the latest available data" on Line 79 as it appears redundant.

Also, the text in lines 327-329 appears redundant as the point was made clear in the lines 287-289. However, if it was restated for emphasis, please ignore this suggestion.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #4: No

Reviewer #5: Yes: Sílvia maria Amado João

Reviewer #6: No

**********

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2023 Sep 21;18(9):e0291962. doi: 10.1371/journal.pone.0291962.r006

Author response to Decision Letter 2

5 Sep 2023

"The distribution of registered occupational therapists, physiotherapists and podiatrists in Australia" (MS: PONE-D-22-18539R2).

Dear Editor,

We are very grateful for the constructive comments from reviewers. We have taken due consideration of the comments provided and made the necessary revisions to the manuscript. All page and line numbers refer to the marked copy of the manuscript.

Response to Reviewer #5

COMMENT: INTRODUCTION: Abstract: The title of the study and the objective of the study is not matching (include workforce) Please revise it.

AUTHORS’ RESPONSE: In the revision, we have incorporated the term "workforce" into the objective stated in the Abstract. Our revision can be found in track changes in the revised manuscript (Page 2).

COMMENT: The WHO, rehabilitation group, is being very active in the latter years with activities for strengthening rehab in health systems, with workforce as one of the pillars, with plenty of works, gatherings and citations you could/should use - the most significant. Global Forum on Human Resources for Health, an analysis of the WHO Global Health Observatory Data Repository containing information from 36 countries showed that maintaining a sufficient health care workforce is a global priority and that the effectiveness of that workforce should be determined by calculating the healthcare workforce-to-population ratio. Include these references.

It is importantly to systematically search/approach/use/build over the strengths and gaps of the literature on the topic beforehand.

1. Campbell J, Dussault G, Buchan J, Pozo-Martin F, Guerra Arias M, Leone C, Siyam A, Cometto G. A universal truth: No health without a workforce. Forum Report, Third Global Forum on Human Resources for Health, Recife, Brazil. Geneva, Global Health Workforce Alliance and World Health Organization. 2013. http://www.who.int/workforcealliance/knowledge/ resources/hrhreport2013/en/. Accessed 13 Feb 2017.

2. World Health Organization. Dublin Declaration on Human Resources for Health. Fourth Global Forum on Human Resources for Health. 2017. http://www.who.int/hrh/events/Dublin_Declaration-on-HumanResou rces-for-Health.pdf?ua=1.

3. World Health Organization. Global strategy for human resources for health: workforce 2030. Draft for the 69th World Health Assembly 2016. http://www.who.int/hrh/resources/16059_Global_strategyWorkfor ce2030.pdf?ua=1.

I list at least 3 relevant articles (directly focused on the physiotherapy workforce), that were not cited:

Jesus TS, Koh G, Landry M, et al. Finding the "Right-Size" Physical Therapy Workforce: International Perspective Across 4 Countries. Physical therapy 2016;96(10):1597-609. doi: 10.2522/ptj.20160014 [published Online First: 2016/05/07]

Landry MD, Hack LM, Coulson E, et al. Workforce Projections 2010-2020: Annual Supply and Demand Forecasting Models for Physical Therapists Across the United States. Physical therapy 2016;96(1):71-80. doi: 10.2522/ptj.20150010 [published Online First: 2015/10/17]

Shah TI, Milosavljevic S, Trask C, et al. Mapping Physiotherapy Use in Canada in Relation to Physiotherapist Distribution. Physiotherapy Canada Physiotherapie Canada 2019;71(3):213-19. doi: 10.3138/ptc-2018-0023 [published Online First: 2019/11/14]

AUTHORS’ RESPONSE: Thank you for suggesting these references. In the revised manuscript, we have incorporated citations for most of the mentioned references (see Page 4).

COMMENT: What’s new in the scientific literature with this manuscript? Include in introduction.

AUTHORS’ RESPONSE: While previous studies have explored aspects of health workforce distribution, few have comprehensively analysed the allied health workforce's density on a national and state/territory level, considering both socioeconomic characteristics and geographical location. Our manuscript uniquely aimed that combining the measures of location/rurality and area-level socioeconomic position as well as the total resident population to provide a new insight into the complex interplay between health workforce availability, socioeconomic factors, and geographic disparities. This approach is important to deliver policy relevant insights aimed at promoting equitable access to allied health workforce. In the revision, we have incorporated what our manuscript adds to the scientific literature in the Introduction section. Our revision can be found in track changes in the revised manuscript (see Page 7).

COMMENT: The manuscript must be include a hypothesis. Explain the hypothesis.

AUTHORS’ RESPONSE: Given that our study is a descriptive quantitative study, our primary focus is on summarizing and presenting data based on our research objective/question rather than testing a specific hypothesis. However, we have provided/added a clear description of our research objective that can serve as a guiding framework for our study (see Introduction page 7).

COMMENT: METHODS: "We linked data from three sources: (1) the public registration data of occupational therapists, physiotherapists, and podiatrists obtained from the Australian Health Practitioner Regulation Agency (AHPRA), the Modified Monash Model (MMM) 2019 data from the Australian Department of Health; and the Socio-Economic Indexes for Areas (SEIFA)”- Why are 3 data sources needed? Explain. Do all these agencies have committees in place to study the markers of an effective workforce, to manage demands related to access, and to create and implement public policies aimed at improving their health systems?

AUTHORS’ RESPONSE: We used the three data sources (by linking each of them) to explore the interplay between allied health workforce availability, measure of location/rurality, and socioeconomic position. This approach is important to deliver policy relevant insights aimed at promoting equitable healthcare access and outcomes. The first data source, the AHPRA, plays a foundational role by providing information about registered professionals. This dataset includes details about occupational therapists, physiotherapists, and podiatrists, providing valuable insights into their numbers and locations. The second source, the MMM 2019 data, offers a geographic classification system that categorises areas based on their remoteness and population size. The third source, the SEIFA, delves into socio-economic factors at different geographic levels, offering insights into the relative socio-economic advantage or disadvantage of different areas. By incorporating SEIFA data, we gain a deeper understanding of the socio-economic context within which healthcare practitioners operate.

Regarding the presence of committees within these agencies for studying workforce markers, managing access demands, and creating/implementing public policies:

• The AHPRA is primarily responsible for the registration and regulation of health practitioners. While AHPRA itself might not have committees specifically focused on studying workforce markers or creating public policies, it collaborates with various professional boards (e.g., Physiotherapy Board, Occupational Therapy Board) to ensure practitioner standards and regulatory measures are in place.

• The Australian Department of Health, which provides the Modified Monash Model (MMM) data, may have committees or departments dedicated to healthcare workforce planning, policy development, and access management. These committees might analyze data trends to ensure that healthcare services are appropriately distributed, especially in underserved areas.

• SEIFA is a product of the ABS. The ABS might not have specific committees focused on healthcare, but the SEIFA data is widely used by various government agencies and researchers to understand socio-economic disparities and inform policy decisions, including those related to healthcare.

Therefore, while these agencies may not have dedicated committees solely for healthcare workforce markers, access demands, and policy creation, they are likely involved in these areas through collaboration, data provision, and policy implementation within their broader mandates. In the revision, we provide a clear description of why these data sources are need in our study. Our revision can be found in track changes (see Page 8.)

COMMENT: DISCUSSION: Include the strengths of the study.

AUTHORS’ RESPONSE: We have already included the strength of our study in the 'Discussion' section (see page 19).

COMMENT: The final paragraph should leave the reader with your final message within the framework of the hypotheses posed in the Introduction.

AUTHORS’ RESPONSE: In the Conclusion section, we have highlighted the notable disparity in the distribution of registered occupational therapists, physiotherapists, and podiatrists when categorised by measures of location/rurality and area-level socioeconomic status across Australian jurisdictions. These findings align with the research question/objective outlined in our Introduction, which focused on describing the density of these three groups of allied health workforce based on location/rurality and area-level socioeconomic status across Australian jurisdictions. The pronounced geographic imbalances in access to allied health workforce underscore the need for targeted policy interventions and comprehensive workforce planning. These measures are crucial in ensuring that healthcare services remain accessible and equitable for all Australians, irrespective of their geographic location or socioeconomic status. In the revision, we have added some more explanation in the last paragraph to enhance the clarity of our final message. Our revision can be found in track changes (see Page 21).

COMMENT: Include the clinical significance of this study over clinicians, patients, and researchers after the study hypothesis.

AUTHORS’ RESPONSE: In the revision, we have added some discussion regarding the significance of our findings. Our revision can be accessed track changed in the ‘Discussion’ section in the revised manuscript (see Page 19).

Response to Reviewer #6

COMMENT: You may remove "the latest available data" on Line 79 as it appears redundant.

AUTHORS’ RESPONSE: Thank you. We have revised it as per the suggestion.

COMMENT: Also, the text in lines 327-329 appears redundant as the point was made clear in the lines 287-289. However, if it was restated for emphasis, please ignore this suggestion.

AUTHORS’ RESPONSE: Thank you for pointing this. We have restated the stated text for emphasis and explanation.

Attachment

Submitted filename: Response to Reviewers.docx

Click here for additional data file. (34.4KB, docx)

Decision Letter 3

Marianne Clemence

10 Sep 2023

The distribution of registered occupational therapists, physiotherapists, and podiatrists in Australia

PONE-D-22-18539R3

Dear Dr. Yisma,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Marianne Clemence

Staff Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewer comments have been addressed adequately.

Reviewers' comments:

Acceptance letter

Marianne Clemence

13 Sep 2023

PONE-D-22-18539R3

The distribution of registered occupational therapists, physiotherapists, and podiatrists in Australia

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Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Table. Proportion of registered occupational therapists, physiotherapists, and podiatrists by MMM in Australia and in each state and territory, April 2020.

    (PDF)

    Click here for additional data file. (138.1KB, pdf)
    S2 Table. Proportion of registered occupational therapists, physiotherapists, and podiatrists by SA2 IRSAD quintiles in Australia, April 2020.

    (PDF)

    Click here for additional data file. (157.4KB, pdf)
    Attachment

    Submitted filename: Response to Reviewers.docx

    Click here for additional data file. (36.9KB, docx)
    Attachment

    Submitted filename: Response to Reviewers.docx

    Click here for additional data file. (31.2KB, docx)
    Attachment

    Submitted filename: Response to Reviewers.docx

    Click here for additional data file. (34.4KB, docx)

    Data Availability Statement

    All the three data sources used in the study are publicly available. The data can be accessible online from the AHPRA (https://www.ahpra.gov.au/), ABS (https://www.abs.gov.au/websitedbs/censushome.nsf/home/seifa) and the Commonwealth Department of Health (https://data.gov.au/data/dataset/modified-monash-model-mmm-2019).

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