Who uses Better Access treatment services? A re-analysis of data from the usual care arms of two randomised controlled trials

Abstract

Objective:

To describe characteristics, service use and clinical changes among people who received treatment through Australia’s Better Access programme.

Methods:

We re-analysed data from the usual care arms of two randomised controlled trials of tailored care approaches for depression and anxiety in primary care (Target-D, 2016–2019; Link-me, 2017–2019). Participants completed measures of depression and anxiety symptoms, quality of life and days out of role due to psychological distress over 12 months. They reported the use of mental health services from different providers/settings; from this, we classified a subset as likely Better Access treatment users.

Results:

Of 394 Target-D and 547 Link-me participants, one-third were classified as having used Better Access treatment sessions over 12 months. They used five to seven Better Access sessions on average; half to two-thirds paid out-of-pocket costs (median $78–$89 per session). The number of Better Access sessions and other mental health services they used increased with severity of mental health problems. At baseline, Better Access treatment users reported more severe symptoms and more days out of role than those who used other or no mental health services, and poorer quality of life than those who used no services. Approximately half (43–55%) of Better Access treatment users showed improvements in mental health over 12 months. Among those with severe problems, improvements in depression and anxiety symptoms were associated with using 5+ Better Access sessions.

Conclusions:

Better Access treatment is used by people with different levels of mental health need. Many experience improvements in their mental health and functioning.

Keywords

Better Access psychological therapy mental health services primary care allied health professionals depression anxiety

Introduction

In Australia each year, one in every five adults experiences a mental disorder (Australian Bureau of Statistics, 2023; Slade et al., 2009). Modelling suggests that the burden and costs of mental illness could be reduced if more people who need care received evidence-based treatment (Andrews et al., 2004; Productivity Commission, 2020).

The Better Access to Psychiatrists, Psychologists and General Practitioners through the Medicare Benefits Schedule initiative (Better Access) was introduced in late 2006. Better Access offers people with mental illness up to 10 individual sessions of evidence-based psychological treatment per year, provided by allied health professionals working in private practice (clinical psychologists, psychologists, social workers, occupational therapists) upon referral (usually from a general practitioner [GP]). The programme is administered through Medicare, Australia’s universal health insurance scheme. Medicare provides rebates to help consumers cover session costs; when a provider charges more than the rebate, the consumer pays the difference out-of-pocket (Australian Government Department of Health and Aged Care, 2023).

Better Access has become the main pathway for Australians to receive psychological treatment. In 2021–22, 1 in every 20 Australians received sessions of psychological treatment funded through Better Access, delivered primarily (>90%) by psychologists (Australian Institute of Health and Welfare, 2023; Pirkis et al., 2022). Approximately 75% of adults who saw a psychologist in 2020–21 received Better Access treatment (Australian Bureau of Statistics, 2023; Australian Institute of Health and Welfare, 2023). Expenditure on psychology services through Better Access far exceeds the combined total from other major funding sources ($720 million vs $125 million in 2019) (Australian Institute of Health and Welfare, 2022; Australian Prudential Regulation Authority, 2022).

Despite the programme’s reach, few studies have examined Better Access treatment users’ characteristics and clinical trajectories. We conducted an evaluation of Better Access in 2009–11 which included a study of 411 new Better Access treatment users recruited by a national sample of clinical psychologists and psychologists (Pirkis et al., 2011). At the start of treatment, most users reported moderate or severe levels of symptoms and psychological distress. By the end of the study, most had shifted to normal or low/mild levels. Those with poorer mental health at the start improved the most. The number of sessions used did not predict outcome. Similar results were reported among samples recruited from single practices (Kohn et al., 2012; Mackey and Henderson, 2016).

In 2021–22, we conducted a new evaluation of Better Access comprising 10 studies (Pirkis et al., 2022). This study and eight others are reported on in this issue of the Australian and New Zealand Journal of Psychiatry (Arya et al., 2026; Chilver et al., 2026; Currier et al., 2026; Newton et al., 2026; Pirkis et al., 2026a, 2026b; Tapp et al., 2026a, 2026b). This study is one of four that examined clinical changes among people who received Better Access care. It assessed clinical change using validated measures collected prospectively at set points over a period of time. Arya et al. (2026) used a similar approach. Two studies by Pirkis et al. (2026a, 2026b) considered clinical change between the start and end of treatment, the former using prospectively collected measures, and latter using retrospective reports.

This study involved a re-analysis of data from two randomised controlled trials (RCTs) of tailored care approaches for depression and anxiety in primary care (Fletcher et al., 2021a; Fletcher et al., 2021b) in which participants completed measures of their clinical status over 12 months. They also provided detailed information about their use of mental health services delivered by a range of providers in different settings, enabling us to classify a subset as likely Better Access treatment users. Although the assessment timepoints were not designed to correspond with the start and end of a Better Access treatment episode, we reasoned that these trials could contribute evidence about: (1) the sociodemographic and clinical characteristics of Better Access treatment users, (2) their patterns of service use, (3) whether their clinical status improved over 12 months and, if so, (4) factors associated with improvement.

Methods

Design

This observational prospective study drew on data from the usual care arms of two RCTs of prognosis-matched treatment recommendations for depression or anxiety in primary care: Target-D (Fletcher et al., 2021a), conducted from 2016 to 2019 and Link-me (Fletcher et al., 2021b), conducted from 2017 to 2019. The usual care groups did not receive any special interventions as part of the trials, so we assumed that their service use would reflect real-world patterns.

The University of Melbourne Human Research Ethics Committee approved the parent trials (Target-D: 1749832, Link-me: 1543648) and the analyses undertaken in the current study (Target-D: 2021-11714-21906-5, Link-me: 2021-11155-21707-4). All participants provided informed consent in the parent trials.

Participants and procedures

Target-D and Link-me shared similar designs and methods, detailed elsewhere (Fletcher et al., 2021a, 2021b) and summarised in Supplemental Material Table S1. Briefly, adults with current symptoms of depression (both trials) or anxiety (Link-me only) were recruited by research or practice staff in participating GPs’ waiting rooms, irrespective of their reason for visiting the GP. Those who met inclusion criteria completed a brief clinical prediction tool that used information about their mental health and social circumstances to predict the severity of their depressive or anxiety symptoms in 3 months’ time if their management plan was unchanged (Chondros et al., 2018; Fletcher et al., 2021a, 2021b). From this, participants were stratified into three prognostic groups: minimal/mild, moderate, or severe symptoms. Participants completed online questionnaires at baseline (T0), 3 months post-baseline in Target-D or 6 months post-baseline in Link-me (T1), and 12 months post-baseline (T2).

Measures

Use of services

Information on services used for mental health was gathered at T1 and T2 via purpose-designed resource use questionnaires (RUQs) (Chatterton et al., 2016, 2018; Herrman et al., 2016). The RUQs covered the time since the previous assessment timepoint, except that T2 in Target-D covered the previous 6 months. This meant that we could collate service use information covering the full 12 months of follow-up for Link-me participants and covering 9 of the 12 months for Target-D participants. Using this information, participants were classified into one of three hierarchically-ordered service use groups: (1) Better Access treatment (any visit to a psychologist, social worker or occupational therapist in a private practice-type setting) regardless of other services used; (2) Other provider-delivered services for mental health (any visit to a psychologist, social worker or occupational therapist in a setting other than private practice; any visit to a GP, other mental health specialist or other health professional in any setting; any emergency department visit or overnight hospital admission; or use of a mental health-related medication); (3) No mental health services (none of the services included in groups (1) or (2)).

Participants estimated the number of visits and out-of-pocket costs for each service they used. In Link-me, these estimates were provided in single units. In Target-D, participants selected from pre-grouped categories, so we used the category mid-points and estimated the lower- and upper-most values from the Link-me dataset and other reports (Australian Institute of Health and Welfare, 2018; Duckett et al., 2022). Out-of-pocket costs were converted to 2021–22 dollars (Australian Bureau of Statistics, 2022).

Clinical measures

We used information from clinical measures collected at T0 and T2. Severity of depression and anxiety symptoms were measured by the Patient Health Questionnaire (PHQ-9) (Kroenke et al., 2001) and Generalised Anxiety Disorder Scale (GAD-7) (Spitzer et al., 2006), respectively. Health-related quality of life was measured by the Assessment of Quality of Life instrument (AQoL-8D) (Richardson et al., 2014) in Target-D and the EuroQol 5-dimension quality of life questionnaire (EQ-5D-5L) (Herdman et al., 2011) in Link-me. Days out-of-role due to psychological distress in the past 4 weeks was measured by the extended Kessler Psychological Distress Scale (K10+) (Australian Government Department of Health, 2021; Kessler et al., 2002) (Link-me only). See Supplemental Material Table S2 for further detail.

Other sociodemographic, clinical and treatment characteristics (T0)

Sociodemographic characteristics included: age (years), gender, education level, employment status, whether living alone, managing on available income, health care card holder and benefit or disability support recipient (Target-D only). Clinical characteristics included: prognostic group, self-rated health, self-reported history of depression, long-term illness or health problems which limit daily activities or work, and reason for visiting the GP (Link-me only). Current treatment indicators included: saw a doctor or other health professional (for mental health in the last month [Target-D]/about psychological distress in the last 4 weeks [K10 + item, Link-me]) and currently taking (an antidepressant [Target-D]/medication for mental health [Link-me]).

Statistical analyses

Analyses were conducted in Stata version 17 (StataCorp, 2021). Data for the Target-D and Link-me cohorts were analysed separately, as differences between the studies might have influenced results. Potential differences in baseline characteristics between included participants and those lost-to-follow-up were compared using chi-square (or Fisher’s exact) tests and t-tests, as were potential differences between the three service use groups.

We summarised the service use patterns of Better Access treatment users between T0 and T2 with simple descriptive statistics. We calculated change in their scores for depression symptoms, anxiety symptoms and quality of life between T0 and T2. We then classified the magnitude of change as either showing a significant improvement, no significant change or significant deterioration, using an effect size of 0.3 of a standard deviation (a small-to-medium effect, as per Cohen’s (1988) classification]. The choice of 0.3 as the effect size was informed by studies of the Minimum Clinically Important Difference (MCID) on the PHQ-9 and GAD-7 in similar populations (Kounali et al., 2020; Kroenke et al., 2019) and other guidance (Angst et al., 2017). For days out of role, we applied a change threshold based on the average number of days out of role for Australians without a mental disorder (Slade et al., 2009). See Supplemental Material Table S3 for further detail.

Among Better Access treatment users, we used bivariate logistic regression models to estimate the strength of associations between baseline characteristics and significant improvement (versus no significant change or significant deterioration) on each clinical measure. In separate analyses, we estimated the strength of association between number of Better Access treatment sessions and significant improvement on each clinical measure. Because the amount of treatment needed to achieve improvement may be different at different levels of severity (de Beurs et al., 2020; Pybis et al., 2017), we included prognostic group and tested for interaction effects. To ensure reasonable cell sizes for these analyses, we collapsed some categories of prognostic group (minimal/mild and moderate vs severe) and number of sessions (1–4 vs 5+ sessions). In supplementary analyses, all regression analyses were repeated to predict significant deterioration (versus no significant change or significant improvement).

Results

Participants included in the analysis

Figure 1 shows the flow of participants from the usual care arms of the parent trials into the current study. Ultimately, 394 usual care group participants from Target-D and 547 from Link-me were included. There was no statistical evidence that included participants differed from those lost-to-follow-up on the baseline clinical measures or prognostic group category. Included participants were somewhat more likely to have had recent treatment contact for mental health and, in the Link-me cohort, to be aged 36+ years and to have a university degree (data not shown). According to our classification, one-third of participants in each cohort had used Better Access treatment during follow-up (Figure 1).

Figure 1.

Summary of participants included in the analysis of usual care group data from Target-D and Link-me.

Characteristics of Better Access treatment users

Table 1 shows the characteristics of Better Access treatment users at baseline. The average depression and anxiety symptom scores of Better Access treatment users were in the moderate severity range (refer to Supplemental Material Table S2 for severity ranges). The standard deviation of the mean indicates that around two-thirds fell in the mild to moderately severe range. Better Access treatment users (Link-me only) experienced more days out of role per month (median 7.5 days) relative to people with depression and anxiety disorders in the general population (medians 6 and 4 days, respectively, see Supplemental Material Table S2), with 75% falling in the range 2–16 days. One quarter to one half (23–51%) rated their health as fair/poor or had a health issue that limited their daily activities. Relatively more of the Link-me cohort had a severe prognosis than the Target-D cohort (51% vs 19%).

Table 1.

Baseline characteristics of Target-D and Link-me participants included in 12-month follow-up analyses, by service use group.

	Target-D (n = 394)				Link-me (n = 547)
	Better Access treatment users	Other mental health services	No mental health services		Better Access treatment users	Other mental health services	No mental health services
	n = 132	n = 194	n = 68	p-value	n = 182	n = 226	n = 139	p-value
Depressive symptom severity (PHQ-9 total), mean (SD)^a	10.8 (5.7)	8.7 (4.9)	6.7 (4.1)	<0.001	12.5 (6.6)	10.1 (6.1)	7.6 (4.6)	<0.001
Anxiety symptom severity (GAD-7 total), mean (SD)^a	9.8 (5.2)	8.0 (4.4)	6.9 (4.5)	<0.001	9.9 (5.3)	7.8 (5.5)	6.5 (4.7)	<0.001
Quality of life (AQoL-8D/EQ-5D-5L) utility weight, mean (SD)^a	0.53 (0.18)	0.58 (0.18)	0.64 (0.20)	<0.001	0.56 (0.28)	0.59 (0.26)	0.75 (0.18)	<0.001
Total days out of role (K10+), median (IQR)^a,b	n/a				7.5 (2.0–16.0)	3.0 (0.0–13.0)	0.0 (0.0–3.5)	<0.001
Prognostic group
Minimal/mild	83 (63%)	143 (74%)	64 (94%)		29 (16%)	55 (24%)	84 (60%)
Moderate	24 (18%)	n.a.	n.a.		60 (33%)	95 (42%)	36 (26%)
Severe	25 (19%)	n.a.	n.a.	<0.001	93 (51%)	76 (34%)	19 (14%)	<0.001
Age group
18–35 years	76 (58%)	89 (46%)	29 (43%)		77 (42%)	58 (26%)	53 (38%)
36–55 years	41 (31%)	75 (39%)	27 (40%)		61 (34%)	88 (39%)	49 (35%)
56 years and over	15 (11%)	30 (15%)	12 (18%)	0.206	44 (24%)	80 (35%)	37 (27%)	0.006
Gender
Male	39 (30%)	45 (23%)	17 (25%)		44 (24%)	61 (27%)	49 (35%)
Female	90 (68%)	148 (76%)	51 (75%)	0.375	137 (75%)	164 (73%)	90 (65%)	0.087
First Nations status
First Nations	4 (2%)	8 (2%)	5 (2%)		4 (2%)	n.a.	n.a.
Not First Nations	160 (98%)	321 (98%)	220 (98%)	1.000	178 (98%)	n.a.	n.a.	0.667
Main language spoken at home
English	n.a.	n.a.	n.a.		n.a.	n.a.	n.a.
Other	n.a.	n.a.	n.a.	0.005	n.a.	n.a.	n.a.	0.020
Highest level of education
Year 12 or equivalent or less	32 (24%)	56 (29%)	17 (25%)		52 (29%)	62 (27%)	44 (32%)
Certificate/diploma	35 (27%)	52 (27%)	16 (24%)		63 (35%)	83 (37%)	42 (30%)
Bachelor’s degree or higher	65 (49%)	86 (44%)	35 (51%)	0.800	67 (37%)	81 (36%)	53 (38%)	0.785
Employment status
Employed	95 (75%)	134 (72%)	47 (73%)		111 (61%)	146 (65%)	107 (77%)
Unemployed	31 (25%)	53 (28%)	17 (27%)	0.764	71 (39%)	80 (35%)	32 (23%)	0.008
Manage on available income
Easily/not too bad/difficult some of the time	115 (87%)	170 (88%)	61 (90%)		145 (80%)	194 (86%)	127 (91%)
Difficult all the time/impossible	17 (13%)	24 (12%)	7 (10%)	0.864	37 (20%)	32 (14%)	12 (9%)	0.013
Receiving benefit or disability support
Yes	16 (13%)	30 (16%)	8 (13%)		n/a
No	109 (87%)	157 (84%)	55 (87%)	0.665
Health care card holder
Yes	32 (26%)	56 (30%)	8 (13%)		73 (40%)	86 (38%)	46 (33%)
No	92 (74%)	130 (70%)	56 (88%)	0.021	109 (60%)	140 (62%)	93 (67%)	0.425
Live alone
Yes	14 (11%)	31 (16%)	4 (6%)		37 (20%)	44 (19%)	24 (17%)
No	118 (89%)	163 (84%)	64 (94%)	0.070	145 (80%)	182 (81%)	115 (83%)	0.781
Self-rated health
Excellent/very good/good	101 (77%)	147 (76%)	56 (82%)		113 (62%)	157 (69%)	116 (83%)
Fair/poor	31 (23%)	47 (24%)	12 (18%)	0.526	69 (38%)	69 (31%)	23 (17%)	<0.001
Self-reported history of depression
Yes	107 (81%)	121 (62%)	30 (44%)		146 (80%)	170 (75%)	54 (39%)
No	25 (19%)	73 (38%)	38 (56%)	<0.001	36 (20%)	56 (25%)	85 (61%)	<0.001
Long-term illness or health problems which limit daily activities/work
Yes	45 (34%)	64 (33%)	11 (16%)		92 (51%)	107 (47%)	40 (29%)
No	87 (66%)	130 (67%)	57 (84%)	0.019	90 (49%)	119 (53%)	99 (71%)	<0.001
Saw doctor/other health professional for mental health in last month (Target-D)/for psychological distress in last 4 weeks (Link-me)
Yes	101 (77%)	76 (39%)	16 (24%)		118 (66%)	88 (40%)	20 (15%)
No	31 (23%)	118 (61%)	52 (76%)	<0.001	62 (34%)	133 (60%)	115 (85%)	<0.001
Currently taking an antidepressant (Target-D)/mental health (Link-me) medication
Yes	45 (34%)	n.a.	n.a.		108 (59%)	158 (70%)	15 (11%)
No	87 (66%)	n.a.	n.a.	<0.001	74 (41%)	68 (30%)	124 (89%)	<0.001
Reason for visiting GP
Mental health (+/− physical health)	n/a				105 (58%)	109 (48%)	15 (11%)
Not mental health					77 (42%)	117 (52%)	124 (89%)	<0.001

Data are n (%) unless otherwise stated. AQoL-8D = Assessment of Quality of Life-8 Dimensions. EQ-5D-5L = EuroQol 5-dimension quality of life questionnaire. GAD-7 = Generalised Anxiety Disorder scale, 7-item version. K10+ = Extended Kessler Psychological Distress Scale. PHQ-9 = Patient Health Questionnaire, 9-item version. n/a, not assessed in this cohort. n.a., not available (one or more cells with n ⩽ 3). SD, standard deviation.

Denominators may vary due to missing data or the omission of categories due to small cell sizes.

Among the subset of participants who reported any psychological distress at baseline.

Better Access treatment users had worse symptoms and more days out of role on average than those who used other, or no, mental health services (Table 1). Relatively more Better Access treatment users reported a history of depression and recent mental health-related service contact, compared to the other two groups. Their general health and quality of life tended to resemble those who used other mental health services and were poorer than those who used no mental health services. Likewise, the percentage who used mental health–related medications was comparable to users of other mental health services.

On baseline sociodemographic factors, the proportion of Better Access treatment service users who mainly speak a language other than English at home was comparable to people who used other mental health services but lower than those who did not use services. In the Link-me cohort, more Better Access treatment users reported difficulty managing on their income compared to those who used other or no mental health services, and a higher percentage were not employed compared to those who used no services. Relatively more were aged 18–35 years, and fewer were aged 56 years or over compared to those who used other services. In the Target-D cohort, Better Access treatment users were more likely to hold a health care card compared to those who used other or no mental health services.

Patterns of service use among Better Access treatment users

Among participants in the Link-me cohort, the average number of Better Access sessions used over the 12-month follow-up was 6.9 (Table 2). In the Target-D cohort the average was 5.0 sessions, likely reflecting the shorter period covered by the RUQs. In both cohorts, the number of sessions used by those in the severe prognosis group was 1.5–2 times higher than in the minimal/mild prognostic group.

Table 2.

Mental health-related service use among Better Access treatment users over 12 month follow-up, by prognostic group.

	Target-D				Link-me
	Minimal/ mild	Moderate	Severe	Total	Minimal/ mild	Moderate	Severe	Total
	n = 83	n = 24	n = 25	n = 132	n = 29	n = 60	n = 93	n = 182
Better Access treatment sessions: ^a
Delivered by a psychologist	83 (100%)	24 (100%)	25 (100%)	132 (100%)	29 (100%)	60 (100%)	92 (99%)	181 (99%)
Delivered by a social worker or OT	-	-	-	-	n.a.	n.a.	n.a.	6 (3%)
Number of sessions (grouped):
1–2	27 (33%)	6 (25%)	3 (12%)	36 (27%)	13 (45%)	14 (23%)	25 (27%)	52 (29%)
3–4	25 (30%)	5 (21%)	7 (28%)	37 (28%)	8 (28%)	17 (28%)	11 (12%)	36 (20%)
5–6	15 (18%)	7 (29%)	5 (20%)	27 (20%)	8 (28%)ⁱ	29 (48%)ⁱ	15 (16%)	29 (16%)
7+	16 (19%)	6 (25%)	10 (40%)	32 (24%)			42 (45%)	65 (36%)
Number of sessions, mean (SD)	4.4 (3.4)	5.7 (4.3)	6.5 (4.3)	5.0 (3.8)	4.2 (3.6)	5.6 (5.1)	8.7 (14.3)	6.9 (10.8)
Any out of pockets costs^b	54 (68%)	15 (68%)	14 (61%)	83 (67%)	9 (31%)	36 (60%)	43 (46%)	88 (48%)
Out-of-pocket cost per session, median (IQR)^c	$73 (61–95)	$84 (63–131)	$84 (56–95)	$78 (61–95)	$78 (34–140)	$84 (45–145)	$99 (58–190)	$89 (50–153)
Total out-of-pocket costs, median (IQR)^c	$326 (183–549)	$458 (142–917)	$408 (192–649)	$331 (183–649)	$279 (156–838)	$335 (179–575)	$682 (168–2011)	$419 (173–1067)
Other providers (excludes Better Access sessions)
Any visits	80 (96%)	24 (100%)	25 (100%)	129 (98%)	28 (97%)	58 (97%)	92 (99%)	178 (98%)
Type of provider:
Primary care^d	76 (92%)	23 (96%)	23 (92%)	122 (92%)	26 (90%)	53 (88%)	85 (91%)	164 (90%)
Mental health specialist/service^e	13 (16%)	7 (29%)	9 (36%)	29 (22%)	9 (31%)	28 (48%)	57 (61%)	94 (52%)
Other health professional/service^f	22 (27%)	5 (21%)	5 (20%)	32 (24%)	7 (24%)	20 (33%)	44 (47%)	71 (39%)
Number of visits, median (IQR)^g	5.0 (3.0–8.5)	5.0 (4.5–8.8)	7.0 (3.0–9.5)	5.0 (3.0–8.5)	3.0 (2.0–7.5)	5.0 (2.0–12.0)	11.0 (5.0–21.0)	8.0 (3.0–16.0)
Any medication taken for mental health^h	38 (46%)	15 (63%)	19 (76%)	72 (55%)	13 (45%)	43 (72%)	73 (78%)	129 (71%)
All mental health care
Total visits/contacts, median (IQR)	8.5 (6.5–13.5)	10.0 (8.5–16.0)	12.0 (8.0–19.0)	10.0 (8.0–14.8)	7.0 (5.0–12.0)	10.0 (5.0–21.0)	16.0 (11.0–32.0)	12.0 (7.0–23.0)

Data are n (%) unless otherwise stated. Percentages are within prognostic group. -, zero. IQR, interquartile range. n.a., not available (one or more cells with n ⩽ 3). OT, occupational therapist. SD, standard deviation.

In Target-D, information about visits to an occupational therapist was not separately collected.

In Target-D, eight people had missing data for out-of-pocket costs.

Denominator is people who paid any out-of-pocket costs. Out-of-pockets costs are in 2020/21 dollars.

Visits to a GP (both trials) or a mental health nurse in a doctor’s room/clinic or private practice location (Link-me only).

Visits to a mental health or substance use specialist or service, or mental health/substance use related overnight stay in hospital or residential care unit.

Visits to a health professional/service not included in d or e above.

Denominator is people who had any visits with other providers.

Includes antidepressants, anxiolytics, hypnotics and sedatives, antipsychotics, psychostimulants and nootropics and antiepileptics.

Categories 5-6 and 7+ merged due to small cell sizes.

Many paid out-of-pocket for their Better Access sessions (67% in Target-D, 48% in Link-me), paying a median per session of $78 and $89 and a total of $331 and $419, respectively (the difference in total again reflecting the shorter period covered by the Target-D RUQs).

Virtually all Better Access treatment users had contact with providers for their mental health in addition to their Better Access treatment provider. The use of other providers and the number of services used generally increased with severity. More than half reported using medications for mental health (Target-D 55%, Link-me 71%), again increasing with severity.

Significant improvement among Better Access treatment users

Table 3 shows that, in both cohorts, approximately half of Better Access treatment users were classified as showing significant improvement (43–55%, depending on the measure). More than two-thirds showed significant improvement on any of the measures of depression, anxiety, or quality of life (Target-D 68%, Link-me 70%). In Link-me, this increased to 80% when days out of role was included. The percentages classified as showing significant improvement were highest in the moderate and severe prognostic groups in Target-D (depression symptoms and quality of life) and in the severe prognostic group in Link-me (all measures), although there was less variation across prognostic groups in Target-D than in Link-me.

Table 3.

Classification of change in symptoms, quality of life and functioning among Better Access treatment users over 12-month follow-up, by prognostic group.

	Target-D				Link-me
	Minimal/mild	Moderate	Severe	Total	Minimal/mild	Moderate	Severe	Total
Depression symptom severity (PHQ-9)	n = 82	n = 24	n = 25	n = 131	n = 29	n = 60	n = 93	n = 182
Baseline score, mean (SD)	7.3 (3.2)	14.2 (2.7)	19.2 (3.4)	10.9 (5.8)	5.7 (2.4)	8.2 (4.0)	17.5 (4.7)	12.6 (6.6)
Significant improvement, % (95% CI)	43% (33, 53)	50% (31, 69)	52% (34, 70)	46% (38, 54)	31% (17, 49)	38% (27, 51)	58% (48, 68)	47% (40, 54)
No significant change, % (95% CI)	27% (18, 37)	21% (9, 40)	24% (12, 43)	25% (19, 33)	31% (17, 49)	30% (20, 43)	22% (14, 31)	26% (20, 33)
Significant deterioration, % (95% CI)	30% (22, 41)	29% (15, 49)	24% (12, 43)	29% (22, 37)	38% (22, 56)	32% (21, 44)	20% (13, 30)	27% (21, 34)
Anxiety symptom severity (GAD-7)	n = 76	n = 22	n = 21	n = 119	n = 29	n = 60	n = 93	n = 182
Baseline score, mean (SD)	7.8 (4.1)	12.5 (4.7)	14.0 (4.9)	9.7 (5.1)	6.3 (2.7)	6.5 (4.4)	13.1 (4.3)	9.9 (5.3)
Significant improvement, % (95% CI)	55% (44, 66)	55% (35, 73)	57% (37, 76)	55% (46, 64)	38% (23, 56)	40% (29, 53)	57% (47, 67)	48% (41, 56)
No significant change, % (95%CI)	25% (17, 36)	18% (7, 39)	19% (8, 40)	23% (16, 31)	45% (28, 62)	28% (19, 41)	23% (15, 32)	28% (22, 35)
Significant deterioration, % (95% CI)	20% (12, 30)	27% (13, 48)	24% (11, 45)	22% (15, 30)	17% (8, 35)	32% (21, 44)	20% (13, 30)	24% (18, 30)
Quality of life (AQoL-8D/EQ-5D-5L)	n = 75	n = 22	n = 21	n = 118	n = 29	n = 60	n = 92	n = 181
Baseline score, mean (SD)	0.62 (0.16)	0.41 (0.09)	0.32 (0.09)	0.53 (0.19)	0.73 (0.16)	0.70 (0.20)	0.41 (0.28)	0.56 (0.28)
Significant improvement, % (95% CI)	40% (30, 51)	55% (35, 73)	48% (28, 68)	44% (35, 53)	31% (17, 49)	30% (20, 43)	54% (44, 64)	43% (36, 50)
No significant change, % (95% CI)	25% (17, 36)	14% (5, 33)	29% (14, 50)	24% (17, 32)	34% (20, 53)	43% (32, 56)	15% (9, 24)	28% (22, 35)
Significant deterioration, % (95% CI)	35% (25, 46)	32% (16, 53)	24% (11, 45)	32% (24, 41)	34% (20, 53)	27% (17, 39)	30% (22, 40)	30% (24, 37)
Days out of role due to psychological distress (K10+) ^a	n/a	n/a	n/a	n/a	n = 29	n = 58	n = 93	n = 180
Baseline (days), mean (SD)					4.7 (5.7)	5.6 (6.1)	14.0 (8.7)	9.8 (8.7)
Significant improvement, % (95% CI)					30% (17, 48)	43% (31, 56)	55% (45, 65)	47% (40, 54)
No significant change, % (95% CI)					40% (25, 58)	28% (18, 40)	18% (13, 29)	25% (20, 32)
Significant deterioration, % (95% CI)					30% (17, 48)	29% (18, 36)	26% (18, 36)	28% (22, 35)
Any of: PHQ-9, GAD-7 or AQoL/EQ-5D-5L	n = 75	n = 22	n = 21	n = 118	n = 29	n = 60	n = 92	n = 181
Significant improvement, % (95% CI)	68% (57, 77)	68% (47, 84)	67% (45, 83)	68% (59, 76)	52% (34, 69)	63% (51, 74)	80% (71, 87)	70% (63, 76)
Any of: PHQ-9, GAD-7, AQoL/EQ-5D-5L or days out of role ^a	n/a	n/a	n/a	n/a	n = 29	n = 58	n = 92	n = 179
Significant improvement, % (95% CI)					66% (47, 80)	78% (65, 86)	86% (77, 92)	80% (73, 85)

95% CI, 95% confidence interval. AQoL-8D, Assessment of Quality of Life-8 Dimensions. EQ-5D-5L, EuroQol 5-dimensions. K10+ = extended Kessler Psychological Distress scale. IQR, interquartile range. n/a., not assessed in this cohort. GAD-7, Generalised Anxiety Disorder scale, 7-item version. PHQ-9, Patient Health Questionnaire, 9-item version. SD, standard deviation. Percentages may not sum to 100 due to rounding.

Among the subset of participants who reported any psychological distress at baseline.

Factors associated with significant improvement

Factors associated with significant improvement on each of the clinical measures are shown in Table 4. In the Link-me cohort, participants with poorer mental health on a given clinical measure at baseline had higher odds of showing significant improvement on that same measure. In the Target-D cohort, this association was present for anxiety symptoms. In the Link-me cohort, additional indicators of poor mental health (e.g. being in the severe prognostic group; recent contact for mental health; history of depression) were associated with significant improvement on one of more of the clinical measures. In the Target-D cohort, poor/fair self-rated health was associated with lower odds of significant improvement in anxiety symptoms.

Table 4.

Baseline characteristics associated with significant improvement on clinical measures over 12-month follow-up.

	Significant improvement in depression symptom severity (PHQ-9)	Significant improvement in anxiety symptom severity (GAD-7)	Significant improvement in quality of life (AQol-8D/EQ-5D-5L)	Significant improvement in total days out of role (K10+)
Target-D
Baseline score on clinical measure^a,b	-	1.18 (1.08, 1.28)***	-	n/a
Self-rated health: Fair/Poor (ref. Excellent/very good/good)	-	0.35 (0.14, 0.84)*	-	n/a
Link-me
Baseline score on clinical measure^a,b	1.11 (1.05, 1.16)***	1.16 (1.09, 1.24)***	0.07 (0.02, 0.25)***	1.12 (1.08, 1.17)***
Prognostic group: Severe (ref. Minimal/mild)	3.08 (1.27, 7.48)*	-	2.65 (1.09, 6.42)*	2.70 (1.11, 6.55)*
Age group: 56 years or over (ref. 18–35 years)	-	0.39 (0.18, 0.85)*	-	-
Gender: Female (ref. Male)	-	-	-	0.47 (0.23, 0.94)*
Highest level of education: Certificate/diploma (ref. Year 12/equivalent or less)	-	-	-	0.46 (0.22, 0.98)*
Health care card: Yes (ref. No)		0.51 (0.28, 0.93)*	-	-
Self-reported history of depression: Yes (ref. No)	-	-	-	3.35 (1.47, 7.63)**
Reason for visit to GP: Mental health (ref. Not mental health)	2.62 (1.42, 4.81)**	-	-	2.28 (1.25, 4.21)**
Saw a doctor/health professional for mental health in last month: Yes (ref. No)	1.94 (1.03, 3.65)*	1.88 (1.00, 3.51)*	-	2.08 (1.11, 3.92)*

p < 0.05. **p < 0.01. ***p < 0.001. -, not shown. AQoL-8D = Assessment of Quality of Life-8 Dimensions. EQ-5D-5L, EuroQol 5-dimension quality of life questionnaire. GAD-7 = Generalised Anxiety Disorder scale, 7-item version. K10+ = Extended Kessler Psychological Distress Scale. n/a = not assessed in this cohort. PHQ-9 = Patient Health Questionnaire, 9-item version. ref. = reference category.

Data are odds ratios (ORs) and 95% confidence intervals from bivariate logistic regression analyses. Baseline characteristics shown in Table 1 were considered one at a time. First Nations status and language spoken at home were excluded, due to small counts. Sample sizes varied slightly due to missing data (Target-D n = 116–131; Link-me n = 180–182). Results are shown only for associations at the p < 0.05 level.

For each clinical measure, we examined the baseline score on the same measure. For example, whether baseline depression symptom severity score was a predictor of significant improvement in depression symptom severity.

For the PHQ-9, GAD-7 and Days out of role, higher scores indicate poorer mental health so an odds ratio above 1 indicates that poorer mental health at baseline is associated with higher odds of improvement. For the AQol-8D (Target-D)/EQ-5D-5L (Link-me), lower scores indicate poorer quality of life, so an odds ratio below 1 indicates that poorer quality of life at baseline is associated with higher odds of improvement.

In the Link-me cohort, being 56 years or over (vs 18–35 years) and holding a health care card (vs no health care card) were associated with lower odds of significant improvement in anxiety symptoms. Being female (vs male) and having a certificate or diploma (vs a high school education) were associated with lower odds of significant improvement in days out of role.

Number of Better Access sessions and significant improvement

There was evidence of an interaction between number of Better Access sessions and prognostic severity in predicting significant improvement on some, but not all, clinical measures. In the Target-D cohort, participants in the severe prognostic group who used five or more sessions had higher odds of significant improvement in depression symptom severity than those in the severe group who used 1–4 sessions (OR = 10.2, 95% CI [1.28, 81.28], p = 0.029). In the Link-me cohort, participants in the severe prognostic group had higher odds of significant improvement in anxiety symptom severity (OR = 4.79, 95% CI [1.38, 16.57], p = 0.013).

Supplementary analyses of significant deterioration

Between 22% and 39% of participants experienced significant deterioration, depending on measure and cohort (Table 3). Generally, associations with significant deterioration were the opposite of those for significant improvement (Supplemental Material Table S4). Similarly, those in the severe group who used five or more sessions had lower odds of significant deterioration in depression symptoms (Link-me, OR = 0.22, 95% CI [0.06, 0.86], p = 0.030) and in anxiety symptoms (Target-D, OR = 0.07, 95% CI [0.004, 0.97], p = 0.048; Link-me, OR = 0.24, 95% CI [0.06, 0.97], p = 0.045) compared to those in the severe group who used 1–4 sessions.

Discussion

Our first goal was to better understand the clinical and sociodemographic characteristics of people who used Better Access treatment. We found that Better Access is delivering care to people whose mental health was similar to or worse than people who used other types of provider-delivered mental health services, and worse than people who used no such services. These findings align with previous Better Access studies using different samples (Byles et al., 2011; Dolja-Gore et al., 2018; Harris et al., 2011).

Several socioeconomic characteristics (difficulty managing on income, not employed, health care card holder) differentiated Better Access treatment users from those who used other and/or or no services. These associations were cohort-specific. Given that Target-D recruited participants from sites in one city, and Link-me from sites in multiple regions, this might indicate that region characteristics (e.g. availability of alternative mental health services) played a part in determining service use patterns. People who speak a language other than English at home were less likely to use Better Access or other mental health services, consistent with other Australian data (Australian Bureau of Statistics, 2016). In Link-me, people aged 56 years or over were less likely to use Better Access treatment compared to other services, which could indicate a need for improved GP recognition of mental health problems and/or appropriate referral to Better Access services for relatively older adults (Bodner et al., 2018). Several of these associations have been found in other Better Access studies based on national samples (Arya et al., 2026; Dolja-Gore et al., 2018; Harris et al., 2011).

A second goal was to understand service use patterns among Better Access treatment users. Reassuringly, we found that individuals with greater prognostic severity used more Better Access sessions, were more likely to consult other specialists, and used a higher volume of services overall. However, the high out-of-pocket costs incurred by many participants (regardless of severity) are of concern given evidence that these costs may discourage or delay some consumers from seeking or completing treatment (Duckett et al., 2022; Tapp et al., 2026a).

A third goal was to explore whether Better Access treatment users experienced improvement in their mental health over 12 months. Although the design of our study meant we did not know Better Access treatment users’ clinical status at the start or end of treatment, approximately half (43–55%) of users showed significant improvement on individual measures of mental health and functioning. The other studies in our evaluation that focused on clinical change also found that people who received Better Access care tended to improve, with rates varying by sample and study design (Arya et al., 2026; Pirkis et al., 2026a, 2026b). The current study also showed that 68–80% reported significant improvement on any of the included measures; it may be that people seek help for different types of problems and might experience improvements in specific domains.

A fourth goal was to better understand factors associated with significant improvement. Indicators of poorer mental health at baseline were the most consistent predictors of improvement. Again, this finding was consistent across other studies in our evaluation (Arya et al., 2026; Pirkis et al., 2026a, 2026b). This might reflect that more unwell people had greater scope for improvement (regression towards the mean). It could also be that they were more likely to be referred by their GPs to, or to independently access, services that helped.

Our interaction analyses showed that, among those with a severe prognosis, receiving five or more sessions of Better Access treatment was associated with significant improvement in depression and anxiety symptoms. Another study in our evaluation based on retrospective consumer reports showed that levels of improvement tended to increase with number of sessions (Pirkis et al., 2026b). In the current study, the cutoff of five sessions was selected for feasibility of analysis, so we cannot say that this represents an optimal number of sessions. The precise number needed for a given individual is likely to depend on their diagnosis, comorbidities and other factors (Crome and Baillie, 2016).

In this study, 22–32% of Better Access treatment users experienced significant deterioration. Other studies in our evaluation also reported deterioration among a significant minority of Better Access treatment users (Arya et al., 2026; Pirkis et al., 2026a). A large study of psychotherapy completers in England found that negative effects of psychotherapy were related to lack of timely referral, insufficient treatment sessions and lack of progress monitoring with their therapist (McQuaid et al., 2021). These measures were not available in our datasets. Further research is needed to understand why some Better Access treatment users experience worsening mental health (Allison et al., 2023).

Strengths and limitations

This study had limitations. The RUQs did not ascertain whether services were paid for by Medicare, so it is possible that some people were misclassified as Better Access users. However, as most services delivered by psychologists in private practice in Australia are reimbursed under Better Access, we are confident that most participants in this group received Better Access sessions. The RUQs relied on self-report which may be subject to recall bias; however, previous analyses of the Link-me dataset have shown reasonable concordance between RUQ responses and administrative data (Chatterton et al., 2022). The trial data were collected in defined geographic areas and prior to COVID-19, so findings may not represent the national picture nor patterns of service following the expanded availability of telehealth from 2020 onwards. People with higher levels of depression or anxiety and people with recent mental health contact were more likely to participate in Link-me (Gunn et al., 2020) and the latter group were more likely to complete follow-up assessments (both cohorts). This could mean that participants in our study had greater mental health need than their peers attending primary care. Better Access was not subject to RCTs prior to national roll-out, so it is necessary to use other study designs to evaluate effectiveness. Ideally, RCTs and adaptive designs would be conducted prior to the implementation of major mental health programmes.

Conclusions

This study indicates that people who make use of Better Access treatment have levels of mental health need that are, on average, similar to users of other provider-delivered mental health services, and that the number of services they use for mental health varies in line with how unwell they are. Many Better Access treatment users experienced improvements in their mental health and functioning over 12 months. Those with severe problems were more likely to obtain some benefits if they received more sessions of treatment. Conversely, a non-trivial proportion experienced significant deterioration; this merits further investigation.

Supplemental Material

sj-docx-1-anp-10.1177_00048674251406028 – Supplemental material for Who uses Better Access treatment services? A re-analysis of data from the usual care arms of two randomised controlled trials

Supplemental material, sj-docx-1-anp-10.1177_00048674251406028 for Who uses Better Access treatment services? A re-analysis of data from the usual care arms of two randomised controlled trials by Meredith Harris, Caley Tapp, Long Khanh-Dao Le, Jan Faller, Bridget Bassilios, Philip Burgess, Mary Lou Chatterton, Patty Chondros, Katrina Scurrah, Matthew J. Spittal, Cathrine Mihalopoulos, Jane Gunn and Jane Pirkis in Australian & New Zealand Journal of Psychiatry

Footnotes

Acknowledgements

This study was funded by the Australian Government Department of Health, Disability and Ageing, as part of the broader evaluation of Better Access. We would like to thank the two groups that were constituted to advise on the evaluation, the Clinical Advisory Group and the Stakeholder Engagement Group. We would like to acknowledge the participants who took part in the Target-D and Link-me trials.

Declaration of conflicting interests

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

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The Better Access evaluation was funded by the Australian Government Department of Health, Disability and Ageing. Target-D was funded by the National Health and Medical Research Council. Link-me was funded by the Department of Health.

ORCID iDs

Meredith Harris

Caley Tapp

Long Khanh-Dao Le

Jan Faller

Bridget Bassilios

Philip Burgess

Mary Lou Chatterton

Patty Chondros

Katrina Scurrah

Matthew J. Spittal

Cathrine Mihalopoulos

Jane Gunn

Jane Pirkis

Data availability statement

The specific analytic datasets derived for the current study are not available.

Supplemental material

Supplemental material for this article is available online.

References

Allison

Looi

Kisely

, et al. (2023) Could negative outcomes of psychotherapies be contributing to the lack of an overall population effect from the Australian Better Access initiative? Australasian Psychiatry: Bulletin of Royal Australian and New Zealand College of Psychiatrists 31: 339–342.

Andrews

Issakidis

Sanderson

, et al. (2004) Utilising survey data to inform public policy: Comparison of the cost-effectiveness of treatment of ten mental disorders. The British Journal of Psychiatry: the Journal of Mental Science 184: 526–533.

Angst

Aeschlimann

Angst

(2017) The minimal clinically important difference raised the significance of outcome effects above the statistical level, with methodological implications for future studies. Journal of Clinical Epidemiology 82: 128–136.

Arya

Tapp

Currier

, et al. (2026) Examining Better Access use by Australian adults using data from two longitudinal studies (Ten to Men and the Australian Longitudinal Study on Women’s Health). Australian & New Zealand Journal of Psychiatry 60: 74–94.

Australian Bureau of Statistics (2016) Cultural and Linguistic Characteristics of People Using Mental Health Services and Prescription Medications. Available at: https://www.abs.gov.au/statistics/health/mental-health/cultural-and-linguistic-characteristics-people-using-mental-health-services-and-prescription-medications/latest-release#mbs-subsidised-mental-health-related-services (accessed 21 February 2024).

Australian Bureau of Statistics (2022) Australian Bureau of Statistics. Consumer Price Index, Australia. TABLE 7. CPI: Group, Sub-group and Expenditure Class, Weighted Average of Eight Capital Cities. 2022. Available at: https://www.abs.gov.au/statistics/economy/price-indexes-and-inflation/consumer-price-index-australia/jun-2022/640105.xlsx (accessed 11 August 2022).

Australian Bureau of Statistics (2023) National Study of Mental Health and Wellbeing. Summary Statistics on Key Mental Health Issues Including National and State and Territory Estimates of Prevalence of Mental Disorders. Reference Period 2020-2022. Available at: https://www.abs.gov.au/statistics/health/mental-health/national-study-mental-health-and-wellbeing/latest-release (accessed 9 November 2023).

Australian Government Department of Health (2021) Primary mental health care minimum data set: Scoring the Kessler-10 Plus. Canberra, ACT Australia: Australian Government.

Australian Government Department of Health and Aged Care (2023) Better Access Initiative. Available at: https://www.health.gov.au/initiatives-and-programs/better-access-initiative#about-the-better-access-initiative (accessed 3 April 2023).

10.

Australian Institute of Health and Welfare (2018) Patients’ Out-of-pocket Spending on Medicare Services 2016–17. Available at: https://www.aihw.gov.au/reports/health-welfare-expenditure/patient-out-pocket-spending-medicare-2016-17/contents/summary (accessed 11 August 2022).

11.

Australian Institute of Health and Welfare (2022) Mental Health Services in Australia [Expenditure on Mental Health-related Services]. Available at: https://www.aihw.gov.au/reports/mental-health-services/mental-health-services-in-australia/report-contents/expenditure-on-mental-health-related-services/data-source-and-key-concepts (accessed 8 September 2022).

12.

Australian Institute of Health and Welfare (2023) Mental Health Online Report: Medicare-subsidised Mental Health-specific Services. Available at: https://www.aihw.gov.au/mental-health/topic-areas/medicare-subsidised-services (accessed 27 June 2023).

13.

Australian Prudential Regulation Authority (2022) Operations of Private Health Insurers Annual Report. Available at: https://www.apra.gov.au/operations-of-private-health-insurers-annual-report (accessed 8 May 2022).

14.

Bodner

Palgi

Wyman

(2018) Ageism in mental health assessment and treatment of older adults. In: Ayalon

Tesch-Römer

(eds). Contemporary Perspectives on Ageism. Cham: Springer, pp. 241–262.

15.

Byles

Dolja -Gore

Loxton

, et al. (2011) Women’s uptake of Medicare Benefits Schedule mental health items for general practitioners, psychologists and other allied mental health professionals. Medical Journal of Australia 194: 175–179.

16.

Chatterton

Chambers

Occhipinti

, et al. (2016) Economic evaluation of a psychological intervention for high distress cancer patients and carers: Costs and quality-adjusted life years. Psycho-oncology 25: 857–864.

17.

Chatterton

Harris

Burgess

, et al. (2022) Economic evaluation of a Decision Support Tool to guide intensity of mental health care in general practice: The Link-me pragmatic randomised controlled trial. BMC Primary Care 23: 236.

18.

Chatterton

Mihalopoulos

O’Neil

, et al. (2018) Economic evaluation of a dietary intervention for adults with major depression (the “SMILES” trial). BMC Public Health 18: 599.

19.

Chilver

Harris

Pirkis

, et al. (2026) Accessibility and responsiveness of Better Access treatment services: Insights from the use of linked administrative data in the evaluation of Better Access. Australian & New Zealand Journal of Psychiatry 60: 25–34.

20.

Chondros

Davidson

Wolfe

, et al. (2018) Development of a prognostic model for predicting depression severity in adult primary patients with depressive symptoms using the diamond longitudinal study. Journal of Affective Disorders 227: 854–860.

21.

Cohen

(1988) Statistical Power Analysis for the Behavioral Sciences. Hillsdale, NJ: Lawrence Erlbaum.

22.

Crome

Baillie

(2016) Better Access and equitable access to clinical psychology services: What do we need to know? Medical Journal of Australia 204: 341–343.

23.

Currier

Williamson

Newton

, et al. (2026) A virtual consultative forum on future reforms to Better Access. Australian & New Zealand Journal of Psychiatry 60: 115–127.

24.

de Beurs

Bruinsma

Warmerdam

(2020) The relationship between clinical complexity, treatment dose and outcome in everyday clinical practice. The European Journal of Psychiatry 34: 90–98.

25.

Dolja-Gore

Loxton

D’Este

, et al. (2018) Differences in use of government subsidised mental health services by men and women with psychological distress: A study of 229,628 Australians aged 45 years and over. Community Mental Health Journal 54: 1008–1018.

26.

Duckett

Stobart

Lin

(2022) Not So Universal: How to Reduce Out-of-pocket Healthcare Payments. Available at: https://grattan.edu.au/wp-content/uploads/2022/03/Not-so-universal-how-to-reduce-out-of-pocket-healthcare-payments-Grattan-Report.pdf (accessed 8 May 2022).

27.

Fletcher

Chondros

Densley

, et al. (2021a) Matching depression management to severity prognosis in primary care: Results of the Target-D randomised controlled trial. The British Journal of General Practice: the Journal of the Royal College of General Practitioners 71: e85–e94.

28.

Fletcher

Spittal

Chondros

, et al. (2021b) Clinical efficacy of a Decision Support Tool (Link-me) to guide intensity of mental health care in primary practice: A pragmatic stratified randomised controlled trial. The Lancet Psychiatry 8: 202–214.

29.

Gunn

Fletcher

Harris

, et al. (2020) Primary Health Network Mental Health Reform Lead Site Project. Link-me: Final Report. Available at: https://www.health.gov.au/sites/default/files/documents/2021/11/foi-request-2758-release-documents-inquiry-into-mental-health-and-suicide-prevention-primary-health-network-mental-health-reform-lead-site-project-link-me-final-report.pdf (accessed 19 February 2024).

30.

Harris

Burgess

Pirkis

, et al. (2011) Policy initiative to improve access to psychological services for people with affective and anxiety disorders: Population-level analysis. The British Journal of Psychiatry: the Journal of Mental Science 198: 99–108.

31.

Herdman

Gudex

Lloyd

, et al. (2011) Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Quality of Life Research: an International Journal of Quality of Life Aspects of Treatment, Care and Rehabilitation 20: 1727–1736.

32.

Herrman

Humphreys

Halperin

, et al. (2016) A controlled trial of implementing a complex mental health intervention for carers of vulnerable young people living in out-of-home care: the ripple project. BMC Psychiatry 16: 436.

33.

Kessler

Andrews

Colpe

, et al. (2002) Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychological Medicine 32: 959–976.

34.

Kohn

Hitch

Stagnitti

(2012) Better access to mental health program: Influence of mental health occupational therapy. Australian Occupational Therapy Journal 59: 437–444.

35.

Kounali

Button

Lewis

, et al. (2020) How much change is enough? Evidence from a longitudinal study on depression in UK primary care. Psychological Medicine 52: 1875–1882.

36.

Kroenke

Baye

Lourens

(2019) Comparative responsiveness and minimally important difference of common anxiety measures. Medical Care 57: 890–897.

37.

Kroenke

Spitzer

Williams

(2001) The PHQ-9: Validity of a brief depression severity measure. Journal of General Internal Medicine 16: 606–613.

38.

Mackey

Henderson

(2016) Outcome evaluation in a private practice setting. In: Menzies

Kyrios

Kazantzis

(eds) Innovations and Future Directions in the Behavioural and Cognitive Therapies. Samford Valley, QLD, Australia: Australian Academic Press.

39.

McQuaid

Sanatinia

Farquharson

, et al. (2021) Patient experience of lasting negative effects of psychological interventions for anxiety and depression in secondary mental health care services: A national cross-sectional study. BMC Psychiatry 21: 578.

40.

Newton

Williamson

Pirkis

, et al. (2026) Perspectives on Better Access: In-depth interviews with users and non-users of the initiative. Australian & New Zealand Journal of Psychiatry 60: 95–102.

41.

Pirkis

Buchannan

Burgess

, et al. (2026a) Examining the effectiveness of the Better Access initiative using data from real-world practice settings. Australian & New Zealand Journal of Psychiatry 60: 35–48.

42.

Pirkis

Currier

Harris

, et al. (2022) Evaluation of the Better Access Initiative – Final Report. Available at: https://www.health.gov.au/resources/collections/evaluation-of-the-better-access-initiative-final-report (accessed 5 September 2023).

43.

Pirkis

Ftanou

Williamson

, et al. (2011) Australia’s Better Access initiative: An evaluation. Australian & New Zealand Journal of Psychiatry 45: 726–739.

44.

Pirkis

Harris

Arya

, et al. (2026b) Consumers’ experiences with and outcomes from Better Access: Results from a national survey. Australian & New Zealand Journal of Psychiatry 60: 49–60.

45.

Productivity Commission (2020) Mental Health, Report No. 95. Available at: https://www.pc.gov.au/inquiries/completed/mental-health/report/mental-health.pdf (accessed 2 May 2023).

46.

Pybis

Saxon

Hill

, et al. (2017) The comparative effectiveness and efficiency of cognitive behaviour therapy and generic counselling in the treatment of depression: Evidence from the 2nd UK National Audit of psychological therapies. BMC Psychiatry 17: 215.

47.

Richardson

Iezzi

Khan

, et al. (2014) Validity and reliability of the Assessment of Quality of Life (AQoL)-8D multi-attribute utility instrument. The Patient 7: 85–96.

48.

Slade

Johnston

OakleyBrowne

, et al. (2009) 2007 National Survey of Mental Health and Wellbeing: Methods and key findings. The Australian and New Zealand Journal of Psychiatry 43: 594–605.

49.

Spitzer

Kroenke

Williams

, et al. (2006) A brief measure for assessing generalized anxiety disorder: The GAD-7. Archives of Internal Medicine 166: 1092–1097.

50.

StataCorp (2021) Stata Statistical Software: Release 17. College Station, TX: Statacorp LLC.

51.

Tapp

Harris

Currier

, et al. (2026a) Australia’s Better Access initiative: A survey of provider and referrer views. Australian & New Zealand Journal of Psychiatry 60: 103–114.

52.

Tapp

Scheurer

Burgess

, et al. (2026b) Uptake, utilisation, and costs of treatment through Better Access from 2018 to 2022: An analysis of Medicare Benefits Schedule data. Australian & New Zealand Journal of Psychiatry 60: 11–24.

Supplementary Material

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