Access to and effectiveness of clinical supervision for allied health workers: A cross-sectional survey

Abstract

Introduction

Clinical supervision supports patient care and health worker wellbeing. However, access to effective clinical supervision is not equitable. We aimed to explore the access and effectiveness of clinical supervision in allied health workers.

Methods

A cross-sectional survey design using the Manchester Clinical Supervision Scale (MCSS-26), including open-ended survey responses, to collect data on effectiveness. Multivariable regression was conducted to determine how MCSS-26 scores differed across discipline, work location and setting. Open-ended responses were analysed using content analysis.

Results

1113 workers completed the survey, with 319 (28%) reporting they did not receive supervision; this group were more likely to hold management positions, work in a medical imaging discipline and practice in a regional or rural location. For those who received supervision, MCSS-26 scores significantly differed between disciplines and work settings; psychologists and those practising in private practice settings (i.e. fee-for-service) reported the highest levels of effectiveness. Suggested strategies to enhance effectiveness included the use of alternate supervision models, dedicated time for supervision, and training.

Conclusion

Targeted subgroups for improving access include senior staff, medical imaging professionals, and those working across regional and rural settings. Where supervision was least effective, strategies to address behaviours with organisational support may be required.

Keywords:

• Clinical supervision
• allied health
• continuing education
• staff development

Introduction

Clinical supervision involves an experienced health worker guiding the clinical practice and professional development of a less experienced health worker (Kilminster et al. 2007; Snowdon et al. 2016). The practice of clinical supervision positively influences quality and safety of patient care, facilitates learning and reduces health worker burnout (Snowdon et al. 2016; Snowdon et al. 2017, Martin et al. 2021). The COVID-19 pandemic has increased psychological distress and burnout within the health workforce (Dobson et al. 2021), and significantly contributed to workforce turnover and shortages (Deakin 2022). Clinical supervision provides a potential mechanism to prevent or alleviate health worker burnout and increase job satisfaction (Martin et al. 2021), by allowing opportunities to address workload, recognition, and professional relationships (Maslach and Leiter 2017). Access to effective clinical supervision must therefore be a priority, to best support and retain the existing health workforce.

Practice points

• Allied health workers in management positions, who work in medical imaging, or who practise in a regional or rural location may be less likely to receive clinical supervision.

• Psychologists and allied health workers in private practice settings (i.e. fee-for-service) may be more likely to receive effective clinical supervision.

• Strategies such as alternate supervision models, dedicated time for supervision, and education and training may enhance the effectiveness of clinical supervision of allied health workers.

• Strategies such as the establishment of relationships for supervision access, management support, and funding for alternate models of supervision may enhance allied health worker access to clinical supervision.

Proctor’s model of clinical supervision is used to inform clinical supervision practice (Ducat et al. 2016). Proctor’s model describes health worker support in three domains of professional practice: normative, restorative and formative. The normative domain refers to supporting the health worker to comply with standards of care, organisational policies and procedures; the restorative domain refers to supporting the health worker with the emotional challenges of clinical practice; and the formative domain refers to the development of professional skills (Proctor 1986). At any given time, effective clinical supervision may offer support in any or all three of Proctor’s domains (Gardner et al. 2018). Importantly, clinical supervision that provides support across Proctor’s domains is associated with reduced levels of health worker burnout, emotional exhaustion and depersonalisation (Martin et al. 2021).

Hierarchical structures for medical and nursing clinical supervision have been previously described, but the format of clinical supervision across allied health professions is less established (Kilminster et al. 2007). Allied health workers include those who specialise in the provision of therapy (e.g. physiotherapy, speech pathology), diagnostic and technical services (e.g. optometrists, audiologists), and scientific services (e.g. pharmacy, medical sciences), as well as allied health assistants (Turnbull et al. 2009). In Australia, allied health workers, excluding assistants, are tertiary educated and commonly act as primary care therapists, where a referral is not required from a medical professional to receive services (Australian Government Department of Health 2013). As such, they have the capacity to work autonomously across public and private health settings, including primary care, disability services and schools (Australian Government Department of Health 2013). There is a need to understand the access and efficacy of clinical supervision across this large workforce to proactively minimise the risk of burnout and maximise the provision of high-quality clinical care.

Allied health workers need effective clinical supervision if they are to attain the proposed benefits of participation (Martin et al. 2021). Qualitative evaluations of allied health clinical supervision suggest the content of effective clinical supervision should focus on professional development (Snowdon et al. 2019), supervisors should possess the skills required to facilitate a constructive supervisory relationship (Snowdon et al. 2019), and organisations should provide an environment and culture that is supportive of clinical supervision (Kumar et al. 2015; Ducat et al. 2016; Snowdon et al. 2019). In practice, these conditions can be difficult to achieve due to clinical demands impinging upon the time for clinical supervision (Kumar et al. 2015; Ducat et al. 2016; Martin et al. 2019), difficulty finding a supervisor with appropriate experience and skills to support professional practice (Kumar et al. 2015; Martin et al. 2019), and geographical barriers for those working in rural and remote healthcare settings (Martin et al. 2019). Collectively, these qualitative evaluations suggest there may be variable access and effectiveness of clinical supervision within allied health.

Quantitative evaluations of allied health clinical supervision using the Manchester Clinical Supervision Scale (MCSS-26) (Winstanley and White 2021), which measures the effectiveness of clinical supervision in each of Proctor’s domains, have identified that effectiveness varies between disciplines (Snowdon et al. 2016; Gardner et al. 2018). Clinical supervision has been shown to be effective in the disciplines of occupational therapy, social work and psychology, yet for physiotherapy, podiatry, dietetics and speech pathology, the effectiveness appears less certain (Snowdon et al. 2016).

While these studies provide useful insights into the effectiveness of clinical supervision, their evaluation are limited to single public health services, and specific locations (i.e. metropolitan or regional) and disciplines (i.e. therapy disciplines). Further, these evaluations are limited in their sample sizes, particularly for disciplines with a smaller sized health workforce (e.g. podiatry, dietitians, speech pathology), making it difficult to compare the effectiveness of clinical supervision between various allied health disciplines and to determine factors associated with effectiveness. In addition, access to clinical supervision requires further investigation. Allied health workers in regional or remote areas have reported limited access to skilled supervisors (Martin et al. 2019), but there has been no comparison in access made between workers practising in different geographical locations. It is also unclear whether access to clinical supervision differs between allied health disciplines, levels of seniority, and work settings.

Therefore, we aimed to: 1) describe access and effectiveness of clinical supervision in a diverse population of allied health workers in Victoria, Australia; and 2) explore the factors associated with access and effectiveness of clinical supervision.

Methods

Study design

A single cross-sectional survey collected data through a post-positivist lens (MCSS-26) and an interpretivist lens (open-ended responses).

Participants and setting

Participants were from allied health in Victoria, Australia, as defined by the Victorian Department of Health, including: Allied health assistant, art therapy, audiology, biomedical science, chiropractic, diagnostic imaging medical physics, exercise physiology, medical laboratory science, music therapy, nuclear medicine, occupational therapy, optometry, oral health, orthoptics, osteopathy, orthotics and prosthetics, pharmacy, physiotherapy, podiatry, psychology, radiation therapy, radiography, social work, sonography, speech therapy (Department of Health and Human Services 2016). Participants could be employed in public or private hospitals, community health, private practice, education (e.g. student support services in schools), mental health, aged care, disability support services, and other non-government organisations. The Victorian allied health workforce has been estimated at more than 42,500 practitioners (Department of Health and Human Services 2016). Pre-registration allied health students were not eligible to participate in the study.

The Victorian Allied Health Clinical Supervision Framework provides guidance, resources and information to enhance allied health clinical supervision (Department of Health and Human Services 2019). The framework recommends that clinical supervision be available to all allied health workers.

Data collection

The MCCS-26 survey, with additional questions regarding the prevalence of participating in clinical supervision and factors of effective clinical supervision, was piloted by seven allied health workers representing four allied health disciplines (physiotherapy, podiatry, occupational therapy, radiography). Ambiguous language was modified before survey distribution, as informed by the pilot feedback. Additional questions regarding the prevalence of participating in clinical supervision and factors of effective clinical supervision were generated by the research team, informed by the clinical supervision literature (Kumar et al. 2015; Ducat et al. 2016; Snowdon, Millard et al. 2016; Gardner et al. 2018; Martin et al. 2019; Snowdon et al. 2019).

Surveys were self-completed and distributed using Qualtrics, a secure online platform. Allied health workers were invited to participate via state government allied health workforce email distribution lists to allied health managers. Managers then forwarded the email to allied health workers under their remit. Additional methods to distribute surveys to Victorian allied health workers included invitations through professional associations (e.g. Occupational Therapy Australia) and social media.

Data were collected over a 6-week period from May to July 2021. Completed surveys were not identifiable, and all participants provided informed consent, which was implied if the participant submitted their survey. The study received ethics approval from the Monash University ethics committee (approval no. 27386).

Outcome measures

The effectiveness of clinical supervision was measured using the MCSS-26. The MCSS-26 measures the effectiveness of clinical supervision from the perspective of the health worker receiving clinical supervision, contains 26 items and takes approximately 5-10 min to complete (Winstanley and White 2021). Participants rate the level to which they agree with the 26 items on a 5-point Likert scale from strongly disagree (0) to strongly agree (4). These items are summed to provide a summary score for each of Proctor’s domains and a total score from 0 to 104, with scores ≥73 indicative of effective clinical supervision as determined based on median scores returned from several international health professional clinical supervision evaluations (Winstanley and White 2021). The items on the MCSS-26 have good internal consistency (α = 0.66 to 0.87) and test-retest reliability (intra-class correlation coefficients = 0.78 to 0.87) (Winstanley and White 2011). Only participants who received clinical supervision completed the MCSS-26.

The factors associated with access and effectiveness that were explored using quantitative methods included participants’ discipline, work location, and work setting. Qualitatively, the factors associated with access to clinical supervision and effective clinical supervision were explored by asking participants who did not receive clinical supervision ‘Describe any strategies that you think would enhance your access to quality clinical supervision?’, and by asking participants who did receive clinical supervision ‘Describe any strategies that would enhance the quality of clinical supervision from your perspective?’.

Demographic information collected included participant age, gender, grade (i.e. seniority), time in position, whether they acted as a supervisor for others, and whether they received clinical supervision. Those who indicated they did not receive clinical supervision indicated the reason(s) for not receiving clinical supervision. Work location was classified based on the Modified Monash Model classification of rurality into the following groups: metropolitan area, regional centre, rural town (Australian Government Department of Health and Aged Care, 2023). Work setting was categorised as: hospital, community health service, private practice, education, mental health service, aged care, disability sector, or other non-governmental organisation.

Data analysis

Numerical data were analysed with SPSS 26.0 (IBM-Corp 2019). Factors associated with access to clinical supervision were explored descriptively. MCSS-26 data were normally distributed and so were described using mean and 95% confidence intervals stratified by discipline, work location, and setting. The effectiveness of clinical supervision was determined by comparing mean (95% CI) to the threshold score for effective clinical supervision (≥73). Raw scores were converted to scores out of 100 to allow for comparison between Proctor’s domain scores (Winstanley and White 2021). Multivariable linear regression analysis was conducted to determine how effectiveness of clinical supervision (i.e. MCSS-26 score; dependent variable) differed across discipline, work location, and work setting (i.e. independent variables). The model was tested for the underlying assumptions of linear regression. Checks for multicollinearity were completed (Pallant 2010). Standardised residuals were examined for outliers with values of ±2.5 used to denote outliers, and sensitivity analyses were conducted with outliers removed (Pallant 2010; Field 2013). A sample size of 246 participants was required to detect an association of moderate effect (f² = .15) in the multivariable linear regression model with 95% power and α = 0.01.

Open-ended survey responses were analysed using content analysis as described by Graneheim and Lundman (2004), remaining close to the data to identify factors and strategies associated with access and effectiveness of clinical supervision. Following repeated readings for familiarisation, the data was condensed into meaning units, inductively coded by one experienced qualitative researcher, and then reviewed by the broader research team with minimal amendment. The dominant responses for each unit of analysis, as identified by frequency count, were then summarised with illustrative quotes.

The research team represented multiple allied health disciplines (physiotherapy, occupational therapy, podiatry), research perspectives (qualitative, quantitative, mixed methods), and experience in receiving and providing clinical supervision and clinical supervision training. Reflexivity was embedded into the regular research team meetings through all research design and analysis stages.

Results

1163 allied health workers consented to participate in the study, with 1133 then providing data. Of these, 319 (28%) did not receive clinical supervision (Figure 1). Of the 814 participants who did receive clinical supervision, 720 (88%) participants provided MCSS-26 data and 352 (43%) provided a response to the open-ended questions regarding the factors associated with access and effectiveness of clinical supervision. Supervision sessions were most commonly one-to-one (94%), in the workplace (69%), monthly (58%) and for a duration of 45-60 min (62%) (Supplementary Table 1).

Figure 1. Participant flow chart. CS: clinical supervision; MCSS-26: Manchester Clinical Supervision Scale.

Access to clinical supervision

The most common reasons for not receiving clinical supervision included ‘no clinical supervisor available’ (n = 85, 27%) and the belief that ‘clinical supervision is not necessary’ (n = 78, 24%). Compared to the allied health worker group who received clinical supervision, the group who did not receive clinical supervision had a higher proportion of males (21% vs. 11%), held management positions (20% vs 4%), worked in a regional (26% vs. 18%) or rural (20% vs. 11%) location, had been in their position for >5 years (57% vs. 42%), were supervisors (64% vs. 54%) and were within the allied health sciences disciplines, in particular radiography/medical imaging (12% vs. <1%) (Table 1).

Table 1. Participant characteristics.

Characteristic	Not receiving CS n = 258	Receiving CS n = 720
	n (%)	n (%)
Age, years, mean (SD)	44.7 (11.7)	40.5 (12.3)
Gender
female	205 (79)	627 (87)
male	53 (21)	79 (11)
Non-binary / gender diverse	0 (0)	5 (1)
Other	0 (0)	1 (<1)
Grade
1	10 (4)	101 (14)
2	63 (24)	256 (36)
3 or 4	104 (40)	248 (34)
management	51 (20)	29 (4)
Not applicable	30 (12)	78 (11)
Discipline
allied health assistant	17 (7)	63 (9)
art therapy^a	1 (<1)	1 (<1)
audiology^a	0 (0)	4 (1)
biomedical science	1 (<1)	0 (0)
child life therapist^a	2 (1)	2 (<1)
counselling^a	0 (0)	7 (1)
diagnostic imaging medical physics	1 (<1)	0 (0)
dietetics	10 (4)	44 (6)
exercise physiology^a	4 (2)	13 (2)
medical laboratory science	1 (<1)	0 (0)
music therapy^a	0 (0)	4 (1)
nuclear medicine	6 (2)	0 (0)
occupational therapy	52 (20)	161 (22)
orthoptics^a	1 (<1)	1 (<1)
osteopathy^a	2 (1)	1 (<1)
pastoral care^a	0 (0)	13 (2)
pharmacy^a	10 (4)	1 (<1)
physiotherapy	41 (16)	100 (14)
podiatry^a	6 (2)	13 (2)
psychiatric services officer^a	0 (0)	3 (<1)
psychology	17 (7)	145 (20)
radiation therapy	3 (1)	0 (0)
radiography / medical imaging^a	30 (12)	2 (<1)
social work	27 (10)	85 (12)
sonography	3 (1)	0 (0)
speech pathology	20 (8)	49 (7)
Location
metropolitan area	139 (54)	501 (70)
regional centre	67 (26)	132 (18)
rural town	52 (20)	79 (11)
Work setting
aged care, disability sector or other non-governmental organisation	8 (4)	24 (4)
community health service	25 (10)	39 (5)
education	6 (2)	43 (6)
hospital	176 (68)	435 (61)
mental health service	9 (3)	54 (8)
private practice	32 (12)	117 (16)
Time in position
less than one year	23 (9)	144 (20)
1–2 years	38 (15)	119 (17)
3–5 years	51 (20)	147 (20)
more than 5 years	146 (57)	302 (42)
Supervise others
Yes	166 (64)	386 (54)
no	92 (36)	326 (45)
Time receiving CS, years, mean (SD)	–	7.6 (7.6)

CS: clinical supervision. nb: missing n = 8 (1%) for receiving CS group.

^aclassified as ‘other’ allied health discipline for purpose of analysis.

Effectiveness of clinical supervision

The overall mean MCSS-26 total score was 78.7 (95%CI 77.5 to 79.8) indicating that clinical supervision was effective, with the lower band of the confidence interval exceeding the threshold of 73 units (Table 2). Participants rated the effectiveness of their supervision lowest in the normative domain (mean score out of 100 = 70.9, 95%CI 69.7 to 72.1) compared to the restorative (mean score out of 100 = 77.2, 95%CI 75.9 to 78.4) and formative domains (mean score out of 100 = 79.5, 95%CI 78.3 to 80.8) (Table 2, Supplementary Table 2).

Table 2. Mean MCSS-26 total, normative, restorative and formative scores.

Group	Total		Normative domain		Restorative domain		Formative domain
	Mean	95%CI	Mean	95%CI	Mean	95%CI	Mean	95%CI
Overall, n = 720	78.7	77.5−79.8	25.5	25.1−26.0	30.9	30.4−31.4	22.3	21.9−22.6
Discipline
Allied health assistant, n = 63	73.9	70.0−77.9	24.1	22.6−25.6	29.8	28.2−31.3	20.1	18.7−21.4
Dietetics, n = 44	71.0	66.5−75.4	22.3	20.7−23.9	28.5	26.5−30.5	20.2	18.7−21.6
Occupational therapy, n = 161	80.0	77.8−82.1	25.8	24.9−26.6	31.1	30.1−32.1	23.1	22.5−23.8
Physiotherapy, n = 100	76.6	73.5−79.7	24.5	23.4−25.7	30.2	28.8−31.5	21.9	21.0−22.9
Psychology, n = 145	84.8	82.8−86.8	28.2	27.3−29.1	32.8	31.9−33.7	23.8	23.2−24.3
Social work, n = 85	79.0	75.2−82.9	26.7	25.4−28.0	30.3	28.6−32.0	22.0	20.8−23.2
Speech pathology, n = 49	79.9	75.7−84.0	25.5	23.8−27.1	31.9	30.1−33.7	22.5	21.3−23.8
Other, n = 65	75.7	71.3−80.0	23.6	22.0−25.2	30.3	28.4−32.2	21.8	20.4−23.1
Location
Metropolitan area, n = 501	78.4	77.0−79.8	25.5	24.9−26.0	30.7	30.1−31.3	22.2	21.8−22.7
Regional centre, n = 132	81.4	78.9−83.8	26.7	25.7−27.7	31.8	30.8−32.8	22.9	22.1−23.7
Rural town, n = 79	77.9	74.9−80.8	24.8	23.7−25.9	31.1	29.7−32.5	22.0	21.0−23.0
Work Setting
aged care, disability sector or other non-governmental organisation, n = 24	82.3	77.6−86.9	26.9	24.6−29.1	32.2	30.2−34.1	23.2	21.7−24.7
Community health service, n = 39	77.2	72.0−82.4	25.0	23.1−26.9	30.9	28.6−33.1	21.4	19.6−23.2
Education, n = 43	78.7	73.9−83.4	26.5	24.7−28.3	30.0	27.8−32.4	22.2	20.8−23.5
Hospital, n = 435	75.9	74.4−77.4	24.4	23.9−25.0	29.9	29.2−30.5	21.6	21.1−22.0
Mental health service, n = 54	83.2	79.7−86.7	27.1	25.6−28.5	32.4	30.9−33.9	23.8	22.7−24.8
Private practice, n = 117	88.0	86.0−90.0	29.0	28.0−30.0	34.3	33.5−35.2	24.7	24.2−25.3

MCSS-26 total score range: 0 to 104; MCSS-26 normative domain score range: 0 to 36; MCSS-25 restorative domain score range: 0 to 40; MCSS-26 Formative domain score range: 0 to 28.

‘Other’ discipline includes: music therapy, osteopathy, orthoptics, pharmacy, podiatry, radiography/medical imaging, child life therapist, pastoral care, counselling, art therapy, psychiatric services officer, audiology and exercise physiology.

MCSS-26 scores stratified by allied health discipline, work location and setting are provided in Table 2.

Factors associated with effective clinical supervision

Quantitative findings

Multivariable regression analysis showed that there were significant differences in the effectiveness of clinical supervision between allied health disciplines, work locations and settings (Table 3). Dietitians (β = −8.40, 95%CI −13.81 to −2.98, p = .002) and allied health assistants (β = −5.83, 95%CI −10.50 to −1.16, p = .015) scored lower MCSS-26 total scores than psychologists. Participants working in a metropolitan area scored lower MCSS-26 total scores than participants working in a regional centre (β = −4.26, 95%CI −7.13 to −1.40, p = .004). Participants working in a hospital setting (β = −10.19, 95%CI −13.71 to −6.66, p<.001), community health service (β = −9.98, 95%CI −15.60 to −4.36, p<.001), and education (β = −8.38, 95%CI −13.60 to −3.16, p = .002) scored lower MCSS-26 scores than participants working in private practice. Sensitivity analysis with outliers removed confirmed significant differences in the effectiveness of clinical supervision between allied health disciplines and work settings, but not work locations (Supplementary Table 3).

Table 3. Differences in MCSS-26 total score between discipline, work location and work setting.

Variable	β	95%CI	P
Discipline
(ref: Psychology)
Allied Health Assistant	−5.83	−10.50 to −1.16	.015
Dietetics	−8.40	−13.81 to −2.98	.002
Occupational Therapy	−2.20	−5.71 to 1.32	.221
Physiotherapy	−2.59	−6.61 to 1.85	.236
Social Work	−2.38	−6.61 to 1.85	.270
Speech Pathology	−0.81	−5.86 to 4.24	.753
Other	−4.28	−9.02 to 0.46	.077
Work Location
(ref: Regional Centre)
Metropolitan Area	−4.26	−7.13 to −1.40	.004
Rural Town	−3.42	−7.54 to 0.71	.104
Work Setting
(ref: Private Practice)
Aged care, Disability Sector or Other Non-Governmental Organisation	−4.73	−11.21 to 1.75	.152
Community Health Service	−9.98	−15.60 to −4.36	<.001
Education	−8.38	−13.60 to −3.16	.002
Hospital	−10.19	−13.71 to −6.66	<.001
Mental Health Service	−4.260	−9.12 to 0.60	.086

Ref – reference group. R²= .117; n = 712.

Qualitative findings

Strategies to enhance effective clinical supervision focused on:

• Alternate supervision models such as peer or group supervision (n = 18) - “for experienced/senior staff, peer supervision rather than clinical/discipline-specific supervision likely more relevant and useful”;

• Education and training (n = 13) - “I feel like further education on how to provide feedback within a supervision setting would be beneficial to all staff no matter the grade, to further foster how we should be doing this given evidence on student-based learning principles”; and

• Dedicated time for supervision (n = 12) – “More time in work hours allocated for supervision for both supervisor and supervisee.”

Strategies to enhance access to clinical supervision focused on:

• Establishment of relationships for supervision access, especially for rural and regional staff, or staff in small professions (n = 43) - “Formal relationships between rural and regional or metropolitan health services so that rural clinicians could access supervision from a regional or metro health service without having to rely on personal networks and generosity of clinicians to enable this”;

• Management support (n = 38) - “no clinical supervision available for my role … following the recent resignation [of] the senior … senior role was filled, instead [replaced with] a new graduate”; and

• Funding for alternate models of supervision as part of work (n = 20) - “funding and/or access to metro staff with relevant expertise/experience. I am a generalist clinician, which makes it tricky to direct supervision.”

Further exemplar quotes are provided for each qualitative finding in Supplementary Table 4.

Discussion

Approximately 1 in 4 allied health workers in this study did not receive clinical supervision. Key factors associated with not accessing clinical supervision included being a manager, working in a medical imaging discipline, and practising in a rural or regional location. Overall, when received, clinical supervision was effective but the degree of effectiveness was affected by discipline, location and work setting. Psychologists rated their supervision highest, while dietitians rated their supervision lowest. Allied health workers in private practice and in regional locations rated their supervision higher than those working in hospitals and metropolitan regions.

The clinicians (n = 78) who did not believe they needed clinical supervision, were commonly senior clinicians and managers. The perception that supervision was only required for junior health workers failed to value the role of clinical supervision to manage the emotional challenges of work (Martin et al. 2021). Insufficient support has been cited as contributing to the recent acceleration of health workforce resignations (Jarden et al. 2023), as well as hospital data indicating 30% of clinical staff screen positively for symptoms of burnout (Dobson et al. 2021). This highlights the urgent need to promote the potential value of clinical supervision to senior health workers and managers. Additionally, given that clinical supervision has been reported to be less effective when provided by a manager (Gardner et al. 2022), the perception that clinical managers did not need to access clinical supervision is concerning in the context of maintaining their skills to provide effective clinical supervision to others.

The ability of psychologists to engage with effective clinical supervision may be attributed to their training in the facilitation of dialogue regarding how people think, feel, behave and react. By contrast, the effectiveness of clinical supervision was lower among allied health assistants and dietitians. Allied health assistants in Australia have limited autonomy, with their clinical scope of practice restricted to working under the delegation of others (Department of Health 2012). They are likely accustomed to a supervisory relationship that primarily involves instruction and delegation. Given that effective clinical supervision requires the supervisee to reflect upon their practice, and lead the dialogue to meet their needs (Snowdon et al. 2019), further training may be required for this workforce to engage in effective clinical supervision. It is unclear why clinical supervision in dietetics was less effective than in other disciplines; however, this aligns with previous findings (Snowdon et al. 2016).

Regional and rural health workers had significantly less access to clinical supervision, yet for those who received supervision in regional settings, the effectiveness was highly rated. It may be that the smaller scale of regional settings allowed for more meaningful relationships and supervision. Organisational policies and procedures, staffing structures and a culture of normalising clinical supervision may also have facilitated the uptake of clinical supervision in larger settings. Allied health workers working in private practice settings reported the most effective clinical supervision. Assumptions that a private (fee for service) setting does not prioritise clinical supervision were not supported by the data, which provided further evidence that private practice employers prioritise clinical supervision support (Wells et al. 2021). Further qualitative research could explore how the private setting, perhaps through perceptions of increased autonomy, provides an environment and culture that prioritises and supports clinical supervision.

Strengths of this study include the large scale, and inclusion of a broad range of allied health disciplines, working across all settings. The collection of both quantitative and qualitative data allowed for an understanding of the uptake of supervision, the quality of the supervision undertaken and reasons for deficits. Limitations include the lack of depth within the qualitative data due to the simple format through which it was collected. Interviews would provide a useful next step to better understand the areas lacking effective clinical supervision. Undertaking the research during the COVID-19 pandemic may also have impacted on both the ability to collect data, and perceptions of clinical supervision. Last, we do not know our response rate, however, our study represents the largest survey of clinical supervision among allied health workers.

Conclusions

The picture of clinical supervision practice across allied health is positive. Targeted subgroups for improving access include senior staff, medical imaging professionals, and those working across regional and rural settings. Where supervision was least effective, within the allied health assistant and dietetic workforce, strategies to address attitudes and behaviours with organisational support may be required. These strategies may be informed by the behaviours of those who reported the most effective clinical supervision, psychologists and allied health workers in private practice settings.

Authors’ contributions

DAS, MKF, FK and MG made substantial contributions to the study conception, design, acquisition of data, analysis and interpretation of data. OH and SD made substantial contributions to the study conception, design, and interpretation of data. NFT made substantial contributions to analysis of data and interpretation of data. DAS, MKF and FK drafted the manuscript. All authors revised the manuscript and agreed to be accountable for all aspects of the work.

Ethics approval and consent to participate

All methods were performed in accordance with the National Health and Medical Research Council (NHMRC) National Statement on Ethical Conduct in Human Research. The study received ethics approval from the Monash University ethics committee (approval no. 27386) and all participants provided informed consent.

Consent for publication

Not applicable.

Acknowledgements

The authors wish to acknowledge and thank the Allied Health workers from across Victoria who participated in this study.

Disclosure statement

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

Data availability statement

The datasets used and/or analysed during the current study are available from the authors on reasonable request.

Additional information

Funding

This work was supported by the Victorian Department of Health (no grant number).

Notes on contributors

David A. Snowdon

David A. Snowdon, BPhysio, PhD, is a research fellow at Monash University, Melbourne Australia. He has a research interest in enhancing clinical supervision of health professionals and assistants to positively influence patient care and outcomes.

Fiona Kent

Fiona Kent, BPhysio, MHPE, PhD, is the Director of Collaborative Care and Work Integrated Learning in the Faculty of Medicine, Nursing and Health Sciences at Monash University.

Melanie K. Farlie

Melanie K. Farlie, BPhysio, GCHPE, PhD, is a Senior Lecturer and Education Research Fellow in the Faculty of Medicine, Nursing and Health Sciences at Monash University.

Nicholas F. Taylor

Nicholas F. Taylor, B App Sci (Physio), PhD, is a Professor of Allied Health in the Allied Health Clinical Research Office at Eastern Health, and the School of Allied Health at La Trobe University.

Owen Howlett

Owen Howlett, BOT, MOT, DCSc, is a clinical occupational therapist in rural and regional Victoria, Australia

Sharon Downie

Sharon Downie, BOT, MPH, is Director, Medical Workforce, The Royal Children’s Hospital, Melbourne Australia. Her research is focused on factors which influence decisions to exercise advanced and extended scopes of practice in the health professions.

Marcus Gardner

Marcus Gardner, B App Sci (Pod), is the Manager of Allied Health Education at Bendigo Health and the Project Manager for the Victorian Allied Health Clinical Supervision Framework and Training Resources projects.