The relationship between Motivation for Occupation and Pattern of Occupation scores of the MOHOST and types of discharge placement from a mental health rehabilitation unit

Abstract

Introduction

Model of Human and Occupational Screening Tool (MOHOST) is a scale used to assess occupational functioning in mental health inpatients which can inform suitable post-discharge placements. However, there is little research on the relationship between scores on Motivation for Occupation (MO) and Pattern of Occupation (PO) subscales of the MOHOST and types of discharge placement.

Method

The records of all patients discharged over a 2-year period from a male psychiatric rehabilitation unit were examined. All patients had undergone MOHOST assessments; however, these scores were not a factor in their discharge placement selection. Analyses were done on types of discharge placements (transfer to another psychiatric unit or community discharge) versus predischarge scores in MO and PO of MOHOST.

Results

N = 20 and average length of stay was 23 months. There was positive correlation between MO and PO scores and discharge placements (rs = 0.66, p = 0.002; rs = 0.67 and p = 0.001, respectively). Using ordinal logistic regression, for each unit increase of negative score in PO, there was 0.68 increase in the log odds of more restrictive discharge placements, p = 0.008.

Conclusion

The study suggests that MOHOST is a useful tool in determining suitable placements for patients being discharged or transferred from psychiatric rehabilitation units.

Keywords

MOHOST mental health discharge accommodation psychiatry

Introduction

Model of Human Occupation Screening Tool (MOHOST) was initially developed with international collaboration amongst academicians and occupational therapists in the United Kingdom and United States of America (Forsyth et al., 2011). It was further developed with international consultations involving other countries (Forsyth et al., 2011). It is based on a conceptual Model of Human Occupation (MOHO). MOHO focuses on how personal and environmental factors influence a person’s occupational participation (Kielhofner, 2002).

There are two types of MOHOST in use: The full MOHOST and MOHOST Single Observation Form (MOHOST-SOF). MOHOST-SOF is designed to capture information for MOHOST rating from a single observation of a person rather than after multiple observations expected for the full MOHOST.

The MOHOST is an observer rating tool with six main subscales. Each subscale is subdivided into four items (see Table 1).

Table 1.

MOHOST subscales.

Subscales	Items
Motivation for Occupation (MO) also called Volition	1. Appraisal of activity 2. Expectations for success 3. Interest 4. Choices
Pattern of Occupation (PO) also called Habituation	1. Routine 2. Adaptability 3. Roles 4. Responsibility
Communication/Interaction Skills	1. Nonverbal skills 2. Conversation 3. Vocal expression 4. Relationships
Process Skills	1. Knowledge 2. Timing 3. Organisation 4. Problem-solving
Motor Skills	1. Posture and mobility 2. Coordination 3. Strength and effort 4. Energy
Environment	1. Physical space 2. Physical resources 3. Social groups 4. Occupational demands

Each item is scored on a 4-point ordinal rating scale (Hawes and Houlder, 2010; Wright and Linacre, 1989; Kielhofner et al., 2009; Forsyth et al., 2011; Marie, 2015) in increasingly negative order: Facilitates (F), Allows (A), Inhibits (I) and Restricts (R).

The validity and reliability of MOHOST in different health settings and countries are well established (Fan, 2008; Forsyth et al., 2011; Pan et al., 2011); however, the validity of the environmental subscale of the full MOHOST and intra-rater reliability of the MOHOST-SOF may be questionable (Kramer et al., 2009; Maciver et al., 2016).

Literature Review

The studies that have examined factors affecting the length of stay (LOS) in psychiatric units, rather than types of discharge destinations, have broadly found that demographic variables, patients’ illness history, co-morbidities, mode of funding and mode of delivery of care play important roles in determining LOS (Douzenis et al., 2012; Kono et al., 2015; Lave and Frank, 1988; Spaulding et al., 1999).

The studies that examined relationship between performance in occupational function assessments and types of discharge destinations have mainly examined patients in acute psychiatric units using Allen Cognitive Test rather than using MOHOST as the occupational function assessment tool. The Allen Cognitive Level Screen-5 (ACLS-5) is a visuomotor screening task used to assess functional cognition (Allen, 1985). The ACLS-5 requires examinees to reproduce three lacing stitches of increasing complexity which then yields Allen Cognitive Levels (Allen, 1985). Henry et al. (1998) found that patients of an acute psychiatric unit with higher Allen Cognitive Level (ACL) scores on admission were significantly more likely to be discharged to independent accommodation than were patients with lower ACL scores. While Velligan et al. (1998) found that for patients with schizophrenia discharged from a state psychiatric facility, ACL did not predict independence in performance of activities of daily living 1–3.5 years after discharge. Furthermore, Schubmehl et al.’s (2018) prospective study of 193 patients showed that Allen Cognitive Tests carried out within 3 days of admission of acutely psychotic patients was not predictive of post-hospitalisation discharge destination. The difference in result between Henry et al. (1998) finding a significant relationship on the one hand, and Velligan et al. (1998) and Schubmehl et al. (2018) not finding any significant relationship on the other hand, might be due to Velligan et al.’s (1998) study involving patients with various diagnoses whilst the other two studies involved only patients with psychosis or schizophrenia. Schizophrenia is known to affect executive functions and executive factors are known to predict performance on Allen Cognitive Tests (Schubmehl et al., 2018; Velligan et al., 1998).

Other variables that have been found to affect types of discharge destination for acute psychiatric inpatients apart from performance on occupational function assessments included performance on an aspect of executive function – card sorting test (Spaulding et al., 1999) and age. Older age was found to be associated with discharge to residential settings (Kono et al., 2015). Other variables were living situations prior to hospitalisation (Henry et al., 1998; Schubmehl et al., 2018) and whether admission was voluntary or involuntary (Schubmehl et al., 2018). Demographic factors found to affect LOS such as sex, employment status, educational level and marital status were not found to be predictive of discharge destinations (Schubmehl et al., 2018).

Unlike the findings for acute psychiatric units, the studies of relationship between performance on occupational function assessments and discharge destinations from medical units showed a consistent relationship that positive performance on occupational function assessment tools was associated with discharge to independent living (Kim and Pyun, 2019; Pitman, 2010; Thorpe et al., 2018).

No study appears to have specifically examined whether performance on occupational function assessments predicts types of discharge destinations for patients in psychiatric rehabilitation hospitals. A study by Killaspy and Zis (2013) of inpatient and community rehabilitation patients showed that poor adherence to medication was associated with a move to a more restrictive environment or readmission. A survey of all patients referred to a rehabilitation unit over 3 years by McCrum and MacFlynn (1990) found that the rate of schizophrenia diagnosis did not differ between patients that did or did not resettle successfully in the community rather being of older age at discharge and fewer prior hospitalisation were associated with successful resettlement. Neither of the two studies ((Killaspy and Zis (2013) and McCrum and MacFlynn (1990)) examined for occupational functioning as a predictive factor for types of discharge destination from rehabilitation units.

However, at least two studies have shown that occupational functioning of patients in psychiatric rehabilitation or medium stay wards do improve. Ayres et al. (2019) retrospectively studied 72 inpatients with schizophrenia spectrum disorders of a medium stay psychiatric unit between 2010 and 2016. They found that scores on the Assessment of Motor and Process Skills (AMPS) tool improved significantly from admission to discharge overall, albeit greater than 60% of participants did not experience meaningful changes in activities of daily living (ADL). The predictors for improvement of the Motor Skills of AMPS were both low admission AMPS score and duration of illness of more than 5 years whilst only low admission AMPS score predicted improvement in the Process Skills of AMPS. No other clinical or demographical variables that were included in their model had a significant effect on change in either motor or process score of AMPS. The study did not examine for how AMPS score influenced types of discharge destination. A prospective study of 35 patients admitted to a forensically informed predischarge unit in England between April 2012 and 2016 showed a significant improvement in MOHOST scores from admission to discharge for patients that were discharged to the community (P = 0.038) compared to MOHOST scores of those were returned to more secure units (Sales et al., 2018). However, the study did not set out as its objective to examine whether MOHOST scores correlate with or predict discharge destinations.

There has been a consistent link between the level of occupational functioning and the level of independence of psychiatric patients resident in the community. Dickerson et al. (1999) examined 72 outpatients with schizophrenia by assigning them to three groups based on their degree of residential independence: those in highly supervised residential facilities, independent living and intermediate supported housing situations. Using Social Functioning Scale, they found that independent living status was related to competence in ADL, frequency of family contact and participation in social activities. Mulholland et al. (1999) also explored factors associated with degree of support required by 90 patients with severe mental illness living in community supported accommodation. Using modified version of the Functional Analysis of Care Environments, they found that three variables: poor communication skills, socially unacceptable behaviour or attitude and relationship problems differentiated the level of support provided. Demographic and clinical variables (diagnosis, age of onset and admissions) did not affect the level of support provided. Neither of these two studies used the MOHOST as their occupational function assessment tool.

Despite evidence that occupational functioning could affect discharge destinations for acute psychiatric inpatients, that it does improve with admission to psychiatric rehabilitation units and occupational function is a significant factor in determining the residential status of psychiatric patients in the community, there have been no studies examining relationship between occupational functioning and discharge destinations from psychiatric rehabilitation units. Moreover, for the few studies that are available for psychiatric inpatients in general, none has used MOHOST as the occupational function assessment tool to predict the relationship between occupational function and discharge destinations, in spite of MOHOST probably being the most widely used occupational function assessment tool in psychiatric units (Bugajska and Brooks, 2020).

This study aimed to determine whether there is a relationship between the scores on the subscales of Motivation for Occupation (MO) and Pattern of Occupation (PO) of the MOHOST and types of discharge or transfer destination from a psychiatric rehabilitation unit. The MO and PO subscales of MOHOST were chosen for this study because these subscales have been found to correlate with ADL (Kielhofner et al., 2010) and higher level of occupational functioning (Forsyth et al., 2011). The MO, PO and the Process Skills subscales of MOHOST also represent known barriers to occupational participation for people with mental illnesses (Grimm et al., 2009; Maciver et al., 2016).

In this study, any type of discharge destination, whether transfer to other psychiatric units or discharge to the community, are all referred to as discharge placements.

Method

The UK Health Research Authority categorised this study as being exempt from needing Research Ethics Committee approval and additional patient consents. The Research and Development Department of the Cygnet Healthcare granted permission for retrospective review of patients’ records for the purpose of this study in August 2017 and December 2020

This is a retrospective study that examined the records of all patients discharged from Cygnet Victoria House in 2014 and 2015. Cygnet Victoria House is part of Cygnet Healthcare. Cygnet Healthcare is an independent provider of mental health services which operates over 150 centres with more than 2500 beds across the UK.

Parts of the information were retrieved in 2017 and additional information was retrieved from records in 2020. The information retrieved for each patient were age at discharge, diagnosis, mental health act status, ethnicity, date of admission, date of last MOHOST before discharge, last MOHOST MO and PO Scores, date of discharge and type of discharge placement.

Cygnet Victoria House was a 25-bed, high dependence psychiatric rehabilitation unit for adult men, during the study period. The unit admitted men who had severe enduring mental illness or might have been detained under the Mental Health Act (MHA); were stepping down from medium or low secure forensic mental health units, psychiatric intensive care units (PICU) or acute inpatient psychiatric units; were from multiple placement breakdowns, failed treatment programmes, or required specialist treatment programmes for behaviours relating to offending, self-harm, substance and alcohol misuse, trauma and anger management. The primary aim of admission was to eventually discharge these patients to either fully independent or varying levels of supported accommodation in the community.

A typical case was a patient being treated for treatment resistant schizophrenia with negative symptoms. He had a long history of mental illness with several admissions and previous community placements had failed. This patient had a co-morbidity of substance misuse. His behaviour was challenging with risk of violence and aggression, and he was almost always detained under the Mental Health Act.

During admission, each patient was managed with individualised care plans that were jointly formulated by the patient, patient’s family, patient’s community team and the hospital multi-disciplinary team (MDT). The MDT consisted of a consultant psychiatrist that used semi-structured interviews to diagnose patients based on ICD-10 (World Health Organization, 1993), a clinical psychologist, psychiatric nurses and an occupational therapist assisted by two activity coordinators. The occupational therapist at the unit worked as part of the MDT to provide assessments and intensive rehabilitation to support patients with their occupational functioning in activities of daily living. This was delivered though the provision of meaningful occupation in individual and group settings, across the domains of self-care, leisure and productivity. The occupational therapist routinely carried out MOHOST on all the patients every 3 months as part of patients’ Care Programme Approach meetings. However, the MOHOST scores were not considered in determining the timing and types of discharge placements.

The types of discharge placements were determined by the hospital MDT in conjunction with the community mental health team, patient and patient’s family considering the following factors: patient’s level of improvement in mental state, risk assessments and occupational functioning. A typical patient that was discharged to independent or supported accommodation was a patient that his mental state had become stable and had developed reasonable insight into the nature of his mental health and treatment needs, as demonstrated by improvement in outcome scores such as Health of the Nation Outcome Scales (HONOS) (Royal College of Psychiatrists, 2021). Such a patient was able to self-medicate, demonstrate moderate skills in ADL and go out of the ward unescorted. Such that his risk to self, property and others could be managed in the community with varying levels of care package and support. Some patients would be transferred to other psychiatric rehabilitation units to be closer to their family, or as an initial stepdown before being discharged to the community. Some patients would be moved up to a more secure setting such as PICU or forensic units usually on account of unmanageable levels of risk to others or property.

Analysis

The ordinal scoring of each of the four items under MO and PO was numbered 1–4: Facilitates = 1, Allows = 2, Inhibits = 3 and Restrict = 4. Thus, a patient could score a total of 4–16 for each of MO and PO. The total score for MO or PO was used as independent ordinal variable.

The types of discharge placements were converted into an ordinal variable ranging from 1 to 5. Each ascending number represents a more restrictive (negative) discharge placement. Thus, 1 is the most positive placement and 5 the most negative placement as in the following: independent accommodation = 1, supported accommodation = 2, rehabilitation unit = 3, psychiatric intensive care unit (PICU) = 4 and low secure forensic unit = 5. No patient was transferred to medium or high secure unit.

All analyses were carried out using Stata/IC 13.1 for Mac (64-bit Intel).

Non-parametric statistical tests were used throughout the study as the dependent variable (types of discharge placements) and two main independent variables of interest (MO and PO scores) were ordinal and all the variables were found not to be normally distributed on histograms.

Correlations were calculated between MO and PO scores and types of discharge placement. Other possible confounding independent variables such as age at discharge, diagnosis and length of time between last MOHOST and discharge were also considered for correlation. Scatter plot of the various variables versus discharge placement showed that PO score versus discharge placement was monotonic (the two variables tend to move in the same direction, but not necessarily at a constant rate) whilst MO score was not fully monotonic with floor effect. The MO score versus discharge placements data was then transformed to 1/MO score versus log10 of discharge placements to get a monotonic scatter plot. The scatter plots for age at discharge, length of admission and length of time between last MOHOST and discharge were grossly non-monotonic with apparently no evidence of correlation with types of discharge placement.

An ordinal logistic regression with proportional odds was run to determine whether types of diagnosis, age at discharge, length of admission, time between last MOHOST and discharge and PO score were predictors of types of discharge placement. MO score was omitted from the regression analysis because of its strong correlation with PO score (r_s = 0.88 and P = 0.000), thereby avoiding undermining effect of multicollinearity on the regression analysis (Daoud, 2017).

Two by three contingency tables were used to examine whether there was a significant difference in types of discharge placements based on MO and PO score. The total score for MO and PO was sorted into independent categorical variable ≤8 or >8 (halfway of possible maximum of 16). The type of discharge placements was sorted into three different categorical variables of discharge placements (positive = independent and supported accommodation, neutral = rehabilitation unit and negative = PICU and low secure units).

Results

Twenty-five patients were discharged during the study period. All 25 patients were white and detained under the Mental Health Act. Five patients were excluded from the study because their records were missing information and treated as missing completely at random (Papageorgiou et al., 2018). This left 20 patients’ records (80%) for analysis.

The average age for the included 20 patients was 34.0 years (age range 22.3–53.7 years). The average length of admission was 715.7 days (23.6 months). The average length of time between the last MOHOST and discharge was 49 days (range: 0–139). Five patients were discharged to independent accommodation, six patients were discharged to supported accommodation, five patients were transferred to other rehabilitation units, two patients were transferred to PICU and two patients were transferred to low secure units. Seventeen patients (85%) had a primary diagnosis of psychotic disorders, and the remaining three patients (15%), each had affective, anxiety and personality disorders, respectively.

The calculated Spearman correlation coefficient and p-value were identical for non-transformed and transformed data for MO score (see Table 2). Overall, there was positive correlation between MO and PO scores and discharge placements (r_s = 0.66, P = 0.002; r_s = 0.67 and P = 0.001, respectively). The ordinal regression analysis showed that the model as a whole was statistically significant, signifying that it contained at least a predictor for types of discharge placements (likelihood ratio chi square = 21.87 with P = 0.0027) (see Table 3). Of all the variables tested, it was only PO Score that was a significant predictor for types of discharge placements, that is, with other variables in the model held constant, for each unit of negative score on PO score, there was 0.68 increase in the log odds of more negative discharged placements, P = 0.008.

Table 2.

Results of correlation analysis.

Variable	Spearman’s rho	P	N
PO score versus discharge placement	0.67	0.001	20
MO score versus discharge placement	0.66	0.002	20
1/MO score versus log10_discharge placement	0.66	0.002	20

Table 3.

Result of ordinal regression analysis.

Ordered logistic regression (n = 20) LR Chi2 = 21.87Prob >Chi2 = 0.0027^a
Discharge placements	Coefficient	Standard error	z	P-values	95% confidence interval
Age at discharge	0.037389	0.0743766	0.50	0.615	−0.1083864 to 0.1831644
Length of admission	−0.001484	0.0010078	−1.47	0.141	−0.0034592 to 0.0004912
Time between last MOHOST and discharge	−0.0245264	0.0144802	−1.69	0.090	−0.0529071 to 0.0038544
PO score	0.6849872	0.2568944	2.67	0.008^a	0.1814835–1.188491
Diagnosis type
2	0.7281609	2.566575	0.28	0.777	−4.302233 to 5.758555
3	−17.39018	3311.909	−0.01	0.996	6508.612–6473.832
4	22.58256	54,257.33	0.00	1.000	−106319.8 to 106365

^a P value <0.05.

The proportional odd assumption necessary for the regression model was shown to be true when subjected to OMODEL test (the approximate likelihood ratio test of proportionality of odds across response categories: chi2 = 21.95 with P = 0.109).

Table 4 showed the result of analysing two by three contingency tables with two-tailed Fisher’s exact test. There was significant higher likelihood of negative discharge placements for scores above 8 (>50% of possible maximum score of 16) on MO and PO subscales of the MOHOST (P = 0.02 and P = 0.04).

Table 4.

Two by three contingency table.

	Level of discharge placements			Total
	Negative	Neutral	Positive	Total
Fisher’s exact test, P = 0.04
PO ≤ 8	0	0	6	6
PO > 8	4	5	5	14
Total	4	5	11	20
Fisher’s exact test, P = 0.02
MO ≤ 8	0	0	7	7
MO > 8	4	5	4	13
Total	4	5	11	20

Discussion

To the best of our knowledge, this is the first study to examine whether MOHOST subscales correlate with or predict types of discharge placement from any type of psychiatric units. This study found that there was a positive correlation between negative scores on MO and PO subscales of MOHOST and restrictive (negative) discharge placements. It also found that for each unit increase of negative score in PO subscale of MOHOST, there was 0.68 increase in the log odds of more restrictive discharge placement. Contingency table analyses showed that those patients with higher negative scores (>50% of maximum score) on MO and PO subscales of MOHOST are significantly more likely to be discharged to more restrictive units.

Eighty-five percent of patients in this study were diagnosed with a psychotic disorder. This is in keeping with the expected United Kingdom national average of 80% of patients in psychiatric rehabilitation units having main diagnoses of psychotic disorders (Joint Commissioning Panel for Mental Health, 2016)

The finding that those with higher negative scores on MO and PO subscales of MOHOST in this study are significantly more likely to be discharged to more restrictive units is similar to the finding of Sales et al. (2018). They found that the mean of the MOHOST from admission to discharge significantly increased for 22 patients that were discharged to the community compared to seven patients that were recalled to more secure units. The forensic informed discharge unit in the (Sales et al., 2018) study was operating more like a long stay ward (no seclusion room and patients having unescorted leave) with an average LOS of 269 days (8.8 months), thus making it appropriate to compare their results to ours.

The discordant results from previous studies of how performance on Allen Cognitive Tests predicted types of discharge placement form acute psychiatric units made it difficult to make a generalised comparison between the studies (Henry et al., 1998; Schubmehl et al., 2018; Velligan et al., 1998) and ours. The results of Henry et al. (1998) study were similar to ours. Performance on predischarge Allen Cognitive Tests by patients in an acute psychiatric unit predicted types of discharge placements just like PO scores predicted type of discharge placements in our study. However, our finding is contrary to the other two studies. Velligan et al. (1998) found in a sample of 110 patients with schizophrenia who underwent Allen Cognitive Tests at discharge, that the ACLs did not predict independence in performance of activities of daily living 1–3.5 years after discharge. Schubmehl et al. (2018) measured ACLs within 3 days of admission of 193 acutely psychotic patients and they found ACLs not to be a predictor of discharge placements. The findings that ACLs might not be predictive of discharge destinations in these two studies (Schubmehl et al., 2018; Velligan et al., 1998) might be because they were carried out on acutely ill patients with psychosis or schizophrenia, when maximum disruption to cognition was taking place. It is known that it takes a substantial length of time, irrespective of medication therapy, before cognitive disruption settles in patients with schizophrenia (Tripathi et al., 2018).

Our study was carried out in non-acutely ill, majority psychotic patients with settled levels of cognitive and functional abilities. This makes the result of our MO and PO scores arguably a truer picture of the patients’ long-term occupational functioning, relevant for long term discharge destinations. It is also known that scores on MO and PO subscales of MOHOST do not discriminate between psychotic and organic or cognitive patients (Kielhofner et al., 2010) unlike ACLs that are predicted by higher cognitive processes (Schubmehl et al., 2018; Velligan et al., 1998). It is possible that our study that used MO and PO subscales of MOHOST and the studies that used ACLs measured subtly different factors of occupational functioning. Thus, a future correlation study between MOHOST and ACLs would be useful.

Limitations

This is a small-sized retrospective study with 20 participants. Due to the small sample size, the outcome of this study must be interpreted with caution. There could have been a type II error such that more significant findings might have been found if the study size was larger. Nevertheless, our significant findings would likely have still held true if it were a larger study. A further limitation is that the findings of this study might be applicable to only long stay mental health units, on account of long average LOS of 23.6 months. However, this LOS of 23.6 months is in keeping with up to 3 years of LOS expected for high dependency mental health units in the UK (Joint Commissioning Panel for Mental Health, 2016). Lastly, all included patients were white and male. However, previous psychometric studies of MOHOST that included both males and females and different ethnicities did not report differential results based on ethnicity and gender (Forsyth et al., 2011; Kielhofner et al., 2009, 2010)

Conclusion

This study suggests that for patients in psychiatric rehabilitation units, the score on the MO and PO subscales of MOHOST correlates with type of discharge placement. The more negative the score on the MO and PO subscales, the higher the likelihood of being discharged to a more restrictive placement. Furthermore, performance on the PO subscale of MOHOST predicts how restrictive the discharge placement would be.

Thus, types of discharge placement from a psychiatric rehabilitation unit were influenced by the level of occupational functioning of patients. This study also gives empirical evidence for the clinical use of performance on the MO and PO subscales of MOHOST for determining suitable discharge placements for patients from psychiatric rehabilitation units. Just as performance on non-MOHOST occupational functioning tools can be used to predict the type of suitable discharge placements for patients from medical units, performance on the PO subscales of MOHOST can be used to predict the type of suitable discharge placements for patients from psychiatric rehabilitation units.

Prospective larger studies of correlation of MOHOST scores and discharge placements that include participants of mixed gender, ethnicity and nationalities are recommended. It would also be useful to have studies that compare scores on MOHOST with ACLs by patients in various mental health settings.

Key findings

MO and PO subscales of MOHOST are appropriate clinical determinants of suitable discharge placements from psychiatric rehabilitation units.

Poor performance on PO subscale of MOHOST predicts more restrictive discharge placements.

What the study has added

This study shows that it is suitable to use MOHOST scores as one of the tools in deciding suitable discharge placements for patients in psychiatric rehabilitation units.

Footnotes

Acknowledgements

We thank Adam Peyton for assisting in data extraction.

Research ethics

Ethics approval was not required for this study.

Declaration of conflicting interests

The authors declare no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Contributorship

Victoria Wisniewski conceived the study, extracted the data and carried out the initial literature review and was involved in gaining approval from the Research and Development Department of Cygnet Healthcare. Gbolagade S Akintomide was involved in literature search, protocol development, data analysis and wrote the final manuscript. The two authors reviewed and edited the manuscript and approved the final version of the manuscript.

Patient and public involvement data

During the development, progress and reporting of the submitted research, Patient and Public Involvement in the research was not included at any stage of the research.

ORCID iD

Gbolagade S Akintomide

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