Conscientious objection – a cross-sectional, vignette-based, mixed methods exploration of Australian pharmacists’ perspectives

Figures & data

Table 1. Demographic of participating registered pharmacists (n = 223).

Characteristics		n	%
Sex	Male	66	30
	Female	155	69
	I prefer not to answer	2	1
Age Range	≤ 24	27	12
	25–34	118	53
	35–44	42	19
	45–54	17	8
	55–64	16	7
	65 +	3	1
Primary Roles* (participants indicated multiple roles hence n≠223)	Community Pharmacists	161	N/A
	Hospital Pharmacists	59	N/A
	Industry	15	N/A
	Academia	20	N/A
	Professional organisations representatives /Government	16	N/A
	Other	13	N/A
Degree Type	B. Pharm/Hons	192	86
	M. Pharm	21	10
	PhD	10	4
Years’ experience	1–5 years	104	43
	6–10 years	51	23
	11–20 years	33	15
	21 + years	35	16
State of Practice	ACT	15	7
	NSW	89	40
	NT	8	3
	QLD	29	13
	SA	12	5
	TAS	13	6
	VIC	31	14
	WA	26	12
Extent religion shapes your decision making in practice.	Not at all	134	60
	Somewhat	71	32
	Very much so	18	8

Table 2. Response rates to remaining questionnaire questions related to personal perspectives (non-vignette questions).

Questions	Response Options	No. of responses (n = 223) except *	%
Q8. What does conscientious objection mean to you?	I know what it is about	133	60
	I have a vague idea what it is about	72	32
	I don’t know anything about it	18	8
Q9. Pharmacists should have the right to conscientious objection?	Agree	106	48
	Neither agree nor disagree	27	12
	Disagree	90	40
Q10. Is it ethically justifiable to C/O if it means your patient cannot get treatment?	Yes	20	9
	No	142	64
	Only If (+ comments)	61	27
Q15. If a pharmacist has the right to conscientious objection, in your opinion should they ensure continuity of care?	Yes	217	97
	No (+ comments)	6	3
*Q16. Which of the following best describes how you would practice ‘continuity of care'? – (More than 1 option)"	Referring the patient to try another pharmacy	113	51
	Referring the patient back to their doctor	92	41
	Providing the patient with information/resources of alternative pharmacies they can successfully access treatment"	207	93
*Q17. Which of the following do you feel influences your views on conscientious objection? (More than 1 option)	Do No Harm	149	67
	Patient Autonomy	159	71
	Faith	46	21
	Professional & Legal frameworks	165	74
Q18. How open are you to changing your views on conscientious objection?	Not going to change	109	49
	May or may not change	47	21
	Open to change	67	30

Table 3. Chi Square analysis of demographics vs responses for each Vignette Case, using results from tables 4–7.

Characteristics	Chi Square
	Case1 – Medical Abortifacient	Case2 – Emergency Contraceptive Pill	Case3 – IVF Surrogate to same-sex couple	Case4 - VAD
‘Age’	13.36	12.46	5.71	17.35
‘Sex’	0.5	6.4*	1.66	0.52
‘Religion’	53.12^#	20.99	20.99^#	55.23^#
‘Degree’	2.34	3	3	1.84

*p < 0.05, ^#p < 0.001.

Table 4. Response groups vs characteristics for Case 1.

Characteristic	Case 1: Medical Abortifacient			p-value^1
	Do Not Supply, N = 32	Conditional Supply, N = 27	Supply, N = 164
Age, n (%)				0.2
<24	1 (3.1%)	1 (3.7%)	25 (15%)
25–34	21 (66%)	17 (63%)	80 (49%)
35–44	8 (25%)	3 (11%)	31 (19%)
45–54	0 (0%)	3 (11%)	14 (8.5%)
55–64	2 (6.2%)	3 (11%)	11 (6.7%)
65–74	0 (0%)	0 (0%)	3 (1.8%)
Sex, n (%)				0.8
Female	21 (66%)	20 (74%)	113 (70%)
Male	11 (34%)	7 (26%)	49 (30%)
Unknown	0	0	2
Degree, n (%)				0.6
B.Pharm/Hons	26 (81%)	23 (85%)	143 (87%)
M.Pharm	5 (16%)	2 (7.4%)	14 (8.5%)
PhD	1 (3.1%)	2 (7.4%)	7 (4.3%)
Religion, n (%)				<0.001
Not At All	5 (16%)	13 (48%)	116 (71%)
Somewhat	16 (50%)	13 (48%)	42 (26%)
Very Much So	11 (34%)	1 (3.7%)	6 (3.7%)
Working Years, Median (IQR)	6 (3, 12)	8 (4, 16)	6 (2, 13)	0.3

¹ Statistical tests performed: Fisher's test; Kruskal-Wallis test.

Table 5. Response groups vs characteristics for Case 2.

Characteristic	Case 2: Emergency Contraceptive Pill (15 yo)			p-value^1
	Do Not Supply, N = 17	Conditional Supply, N = 50	Supply, N = 156
Age, n (%)				0.3
<24	4 (24%)	5 (10%)	18 (12%)
25–34	10 (59%)	34 (68%)	74 (47%)
35–44	2 (12%)	7 (14%)	33 (21%)
45–54	0 (0%)	3 (6.0%)	14 (9.0%)
55–64	1 (5.9%)	1 (2.0%)	14 (9.0%)
65–74	0 (0%)	0 (0%)	3 (1.9%)
Sex, n (%)				0.050
Female	14 (82%)	28 (56%)	112 (73%)
Male	3 (18%)	22 (44%)	42 (27%)
Unknown	0	0	2
Degree, n (%)				0.7
B.Pharm/Hons	17 (100%)	42 (84%)	133 (85%)
M.Pharm	0 (0%)	5 (10%)	16 (10%)
PhD	0 (0%)	3 (6.0%)	7 (4.5%)
Religion, n (%)				0.13
Not At All	8 (47%)	27 (54%)	99 (63%)
Somewhat	5 (29%)	20 (40%)	46 (29%)
Very Much So	4 (24%)	3 (6.0%)	11 (7.1%)
Working Years, Median (IQR)	3 (1, 7)	4 (2, 9)	7 (3, 16)	0.032

¹ Statistical tests performed: Fisher's test; Kruskal-Wallis test.

Table 6. Response groups vs characteristics for Case 3.

Characteristic	Case 3: IVF Surrogate to Same-sex Couple			p-value^1
	Do Not Supply, N = 7	Conditional Supply, N = 9	Supply, N = 207
Age, n (%)				>0.9
<24	0 (0%)	1 (11%)	26 (13%)
25–34	6 (86%)	4 (44%)	108 (52%)
35–44	1 (14%)	3 (33%)	38 (18%)
45–54	0 (0%)	1 (11%)	16 (7.7%)
55–64	0 (0%)	0 (0%)	16 (7.7%)
65–74	0 (0%)	0 (0%)	3 (1.4%)
Sex, n (%)				0.5
Female	5 (71%)	8 (89%)	141 (69%)
Male	2 (29%)	1 (11%)	64 (31%)
Unknown	0	0	2
Degree, n (%)				0.7
B.Pharm/Hons	7 (100%)	8 (89%)	177 (86%)
M.Pharm	0 (0%)	0 (0%)	21 (10%)
PhD	0 (0%)	1 (11%)	9 (4.3%)
Religion, n (%)				<0.001
Not At All	0 (0%)	3 (33%)	131 (63%)
Somewhat	4 (57%)	4 (44%)	63 (30%)
Very Much So	3 (43%)	2 (22%)	13 (6.3%)
Working Years, Median (IQR)	6 (4, 10)	9 (3, 17)	6 (2, 13)	0.7

¹ Statistical tests performed: Fisher's test; Kruskal-Wallis test.

Table 7. Response groups vs characteristics for Case 4.

Characteristic	Case 4: Euthanasia			p-value^1
	Do Not Supply, N = 27	Conditional Supply, N = 35	Supply, N = 161
Age, n (%)				0.053
<24	1 (3.7%)	3 (8.6%)	23 (14%)
25–34	22 (81%)	24 (69%)	72 (45%)
35–44	3 (11%)	4 (11%)	35 (22%)
45–54	0 (0%)	2 (5.7%)	15 (9.3%)
55–64	1 (3.7%)	1 (2.9%)	14 (8.7%)
65–74	0 (0%)	1 (2.9%)	2 (1.2%)
Sex, n (%)				0.6
Female	19 (70%)	22 (63%)	113 (71%)
Male	8 (30%)	13 (37%)	46 (29%)
Unknown	0	0	2
Degree, n (%)				0.3
B.Pharm/Hons	21 (78%)	33 (94%)	138 (86%)
M.Pharm	5 (19%)	1 (2.9%)	15 (9.3%)
PhD	1 (3.7%)	1 (2.9%)	8 (5.0%)
Religion, n (%)				<0.001
Not At All	1 (3.7%)	18 (51%)	115 (71%)
Somewhat	17 (63%)	14 (40%)	40 (25%)
Very Much So	9 (33%)	3 (8.6%)	6 (3.7%)
Working Years, Median (IQR)	4 (2, 9)	4 (3, 10)	7 (2, 16)	0.2

¹ Statistical tests performed: Fisher's test; Kruskal-Wallis test.

Figure 1. Responses to vignette cases (n-223).

Figure 2. Driver Diagram.

Figure 3. Example quotes for driver 1.

Figure 4. Example quotes for driver 2.

Figure 5. Example quotes for driver 3.