A total of 15 GP practices (participation rate 22.1%) agreed to have the study carried out in their waiting rooms, of which eight group practices (several practicing physicians; min 2, max 8) and seven individual practices (one single GP). Patients’ participation rate was 80.5% (N=314). Our sample reflects the quota of patients consulting in individual (44%) and group practices (56%) in Switzerland (22). Figure 1 illustrates the study inclusion/exclusion process.
Table 1: Prevalence of NPHR use (N=307), participants’ views on NPHRs (N=307) and GPs’ involvement in NPHRs use (N=195)
Prevalence of NPHR use and participants’ views on NPHRs (N=307)
|
Number of participants (%) [95%CI]
|
Do you use NPHRs? (N=306)
|
|
Yes
|
197 (64.4) [59.0-69.7]
|
No
|
109 (35.6) [30.3-41.0]
|
For what reason(s) do you use NPHRs? (N=195)1
|
|
For preventive purposes, to stay healthy or to avoid getting ill
|
108 (55.3) [48.4-62.4]
|
Because I can treat myself without the help of a therapist
|
80 (41.0) [34.1-47.9]
|
As an alternative to conventional medicine2
|
793 (40.5) [33.6-47.4]
|
To limit the number of pharmacological treatments
|
53 (27.2) [20.9-33.4]
|
To avoid side effects associated with pharmacological treatments
|
43 (22.1) [16.2-27.9]
|
Because I do not trust pharmacological treatments
|
26 (13.3) [8.6-18.1]
|
Because I do not trust conventional medicine
|
15 (7.7) [4.0-11.4]
|
Because an effective pharmacological treatment does not exist
|
6 (3.1) [0.7-5.5]
|
To avoid or delay a medical consultation
|
75 (38.5) [31.6-45.3]
|
As a complement to pharmacological treatment
|
45 (23.1) [17.2-29.0]
|
When medical care seems too expensive for my health problem
|
18 (9.2) [5.2-13.3]
|
Other reasons4
|
7 (3,6) [1.0-6.2]
|
For what reason(s) do you not use NPHRs? (N=109)5
|
|
I do not know of any NPHRs.
|
53 (48.6) [39.2-58.0]
|
I would rather see my GP than take NPHRs.
|
42 (38.5) [29.4-47.7]
|
I have easy access to medical care and do not need to take NPHRs.
|
39 (35.8) [26.8-44.8]
|
I prefer to use pharmacological treatments than NPHRs.
|
17 (15.6) [8.8-22.4]
|
In my opinion NPHRs are ineffective.
|
8 (7.3) [2.4-12.2]
|
Other reasons6
|
19 (17.4) [10.3-24.6]
|
Do you think a GP’s role is to inform you about NPHRs? (N=195)7
|
Number of participants (%) [95%CI]
|
Yes
|
136 (69.7) [63.3-76.1]
|
Spontaneously on the initiative of my GP
|
71 (36.4) [29.7-43.2]
|
Only upon specific request from me
|
63 (32.3) [25.7-38.9]
|
No
|
59 (30.3) [23.8-36.7]
|
Have you talked to your GP about your use of NPHRs? (N=194)7
|
|
Yes8
|
65 (33.5) [26.9-40.2]
|
I brought it up spontaneously
|
52 (26.8) [20.6-33.0]
|
My doctor brought it up spontaneously
|
16 (8.2) [4.4-12.1]
|
Other reasons10
|
2 (1.0) [0.0-2.5]
|
No9
|
129 (66.5) [59.9-73.1]
|
I did not feel the need to talk to my GP about it
|
66 (34.2) [27.4-40.7]
|
My GP did not ask me about it
|
47 (24.2) [18.2-30.3]
|
I consider it a personal matter
|
23 (11.6) [7.3-16.4]
|
I forgot to tell my GP about it
|
10 (5.2) [2.0-8.3]
|
I consider that this practice is not part of medical care
|
8 (4.1) [1.3-6.9]
|
I fear my GP’s judgement of this practice
|
1 (0.5) [0.0-1.5]
|
Because I am afraid of being misunderstood by my doctor GP.
|
0 (0%) [0.0-0.0]
|
My GP raised the subject, but I did not want to talk to him about it.
|
0 (0%) [0.0-0.0]
|
Other reasons10
|
7 (3.6) [1.0-6.2]
|
1 Number of patients differs from 197 due to several possible responses.
2 Total differs from 100% due to several possible responses.
3 Number of patients differs from 79 due to several possible responses.
4 Other reasons (several possible answers): Because my GP didn’t prescribe pharmacological treatment (N=3; 1.5%; 95%CI 0.0-3.2); Because I live or work in an area where it is difficult to consult a GP (N=2; 1.0%; 95%CI 0.0-2.4); In combination with pharmacological treatment, as the maximum dose was reached (N=2; 1.0%; 95%CI 0.0-2.4)
5 Number of patients differs from 109 due to several possible responses.
6 Other reasons (several possible answers): My GP advised me not to use NPHRs (N=1; 0.9%; 95%CI 0.0-2.7); I think NPHRs are too expensive (N=1; 0.9%; 95%CI 0.0-2.7); Other10 (N=17; 15.6%; 95%CI 8.8-22.4).
7 Number of participants does not add up to 197 because of missing data.
8 Number of participants differs from 65 due to several possible responses.
9 Number of participants differs from 129 due to several possible responses.
10 Not listed in detail due to the low representativeness.
Table 2 presents participants’ main sociodemographic characteristics. Their median age was 52 years and the majority of participants were women (60.5%), Swiss (71.1%) and living in an urban zone (70.7%). According to the latest data published by the Federal Statistical Office (FSO), our sample represented Geneva’s multiculturalism with its foreign resident population (Geneva 2020: 39.8%) (23).
Table 2: Participants’ sociodemographic characteristics (N=307)
Characteristics (N=307)
|
Number of participants (%) [95%CI]
|
Mean (SD)
|
Gender (N=304)
|
|
|
Female
|
184 (60.5) [55.0-66.0]
|
|
Male
|
120 (39.5) [34.0-45.0]
|
|
Age group (N=305)
|
|
52.1 (18.8)
|
< 40 years
|
86 (28.2) [23.2-33.3]
|
|
40 - 59 years
|
110 (36.1) [30.7-41.5]
|
|
≥ 60 years
|
109 (35.7) [30.4-41.1]
|
|
Place of residence (N=307)
|
|
|
Urban zone
|
217 (70.7) [65.6-75.8]
|
|
Semi-rural zone
|
65 (21.2) [16.6-25.7]
|
|
Rural zone
|
25 (8.1) [5.1-11.2]
|
|
Nationality (N=305)*
|
|
|
Swiss
|
217 (71.1) [66.1-76.2]
|
|
French
|
40 (13.1) [9.3-16.9]
|
|
Italian
|
19 (6.2) [3.5-8.9]
|
|
Spanish
|
13 (4.3) [2.0-6.5]
|
|
Portuguese
|
11 (3.6) [1.5-5.7]
|
|
Other (< 2% per different nationality)
|
52 (17.0) [12.8-21.3]
|
|
Marital status (N=301)
|
|
|
Married or living as a couple
|
160 (53.2) [47.5-58.8]
|
|
Single
|
76 (25.2) [20.3-30.2]
|
|
Divorced or separated
|
50 (16.6) [12.4-20.8]
|
|
Widowed
|
15 (5.0) [2.5-7.4]
|
|
Family situation (N=196)
|
|
|
With child/-ren
|
90 (45.9) [38.9-52.9]
|
|
Without child/-ren
|
106 (54.1) [47.1-61.1]
|
|
Work status (N=305)
|
|
|
Occupational activity
|
156 (51.2) [45.5-56.8]
|
|
Retired
|
79 (25.9) [21.0-30.8]
|
|
Student or apprenticeship/vocational training
|
26 (8.5) [5.4-11.7]
|
|
Recipient of unemployment (ALV1) or invalidity (DI1) benefits2
|
22 (7.2) [4.3-10.1]
|
|
Housewife/husband
|
8 (2.6) [0.8-4.4]
|
|
Other3 (mainly without employment)
|
14 (4.6) [2.2-6.9]
|
|
Completed training/education (N=305)
|
|
|
University, FIT4, UAS4
|
120 (39.3) [33.9-44.8]
|
|
Apprenticeship/vocational training
|
75 (24.6) [19.8-29.4]
|
|
Baccalaureate or diploma from intermediate school
|
63 (20.7) [16.1-25.2]
|
|
Compulsory schooling
|
42 (13.8) [9.9-17.6]
|
|
No training/education5
|
5 (1.6) [0.2-3.1]
|
|
Self-estimated general health status (N=304)
|
|
|
Excellent or very good
|
106 (34.9) [29.5-40.2]
|
|
Good
|
150 (49.3) [43.7-55.0]
|
|
Moderate or poor
|
48 (15.8) [11.7-19.9]
|
|
Number of daily medications (N=295)
|
|
2.0 (2.6)
|
0
|
103 (34.9) [29.5-40.4]
|
|
1
|
58 (19.7) [15.1-24.2]
|
|
2
|
46 (15.6) [11.5-19.7]
|
|
≥ 3
|
88 (29.8) [24.6-35.1]
|
|
Number of consultations6 to GP in the past 12 months (N=306)
|
|
|
1
|
54 (17.6) [13.4-21.9]
|
|
2-5
|
167 (54.6) [49.0-60.2]
|
|
6-9
|
45 (14.7) [10.7-18.7]
|
|
≥ 10
|
40 (13.1) [9.3-16.9]
|
|
Model of health insurance (compulsory health insurance) (N=302)
|
|
|
Basic insurance with standard or optional deductible
|
191 (63.3) [57.8-68.7]
|
|
General practitioner model
|
70 (23.2) [18.4-27.9]
|
|
HMO (Health Maintenance Organisation) model
|
11 (3.6) [1.5-5.8]
|
|
Telemedical model (Telmed or Callmed)
|
7 (2.3) [0.6-4.0]
|
|
No-claims bonus
|
3 (1.0) [0.0-2.1]
|
|
Other (mainly not knowing what kind of model)
|
20 (6.6) [3.8-9.4]
|
|
Annual deductible in Swiss Francs (N=299)
|
|
|
300
|
141 (47.2) [41.5-52.8]
|
|
500
|
62 (20.7) [16.1-25.3]
|
|
1’000
|
11 (3.7) [1.6-5.8]
|
|
1’500
|
13 (4.4) [2.0-6.7]
|
|
2’000
|
4 (1.3) [0.0-2.6]
|
|
2’500
|
26 (8.7) [5.5-11.9]
|
|
Other7 (mainly not knowing the amount of annual deductible)
|
42 (14.0) [10.1-18.0]
|
|
* Number of patients differs from 305 due to several possible responses (e.g. double citizen).
1 ALV = Unemployment Insurance; DI = Disability Insurance
2 Unemployment benefits (N=4; 1.3%; 95%CI 0.0-2.6); invalidity benefits (N=18; 5.9%; 95%CI 3.3-8.6)
3 No unemployment benefits, no invalidity benefits
4 FIT = Federal Institute of Technology, UAS = University of Applied Sciences
5 Compulsory schooling not finished.
6 Only a personal meeting with the GP was defined as a consultation.
7 Not knowing the amount of annual deductible (N=36; 12.0%; 95%CI 8.4-15.7); Preferring not to answer (N=5; 1.7%; 95%CI 0.2-3.1); Insurance for WHO employees (N=1; 0.3%; 95%CI 0.0-1.0)
Prevalence of NPHR use and reasons for using (or not using) NPHRs
Nearly two thirds (64.4%) of all participants reported using NPHRs (Table 1). They were mainly used for preventive purposes (55.3%), self-care (41.0%), as an alternative to conventional medicine (40.5%) (either to limit the number of medications taken (27.2%) or to avoid side effects associated with medications (21.1%)), and to avoid or delay a medical consultation (38.5%). By contrast, the main reasons for not using them were ignorance of NPHRs (48.6%), preference to consult their GP (38.5%) and easy access to medical care (35.8%).
Patients’ expectations
About two-thirds of the users considered that it was the GP’s role to inform them about NPHRs, either spontaneously (36.4%) or upon specific request from patients (32.3%), whereas one third thought that it was not his/her role (30.3%). Accordingly, two-thirds of the users did not talk to their GP about their use of NPHRs (66.5%) (Table 1).
Univariable and multivariable analysis
Table 3 presents participants’ sociodemographic characteristics associated with NPHR use. There seemed to be an association between NPHR use and female gender, but this association did not reach statistical significance in the multivariable analysis (adjusted OR 1.7; 95%CI 1.0-2.9, p 0.06). Table 4 shows participants’ sociodemographic characteristics associated with their expectations. Patients living in an urban zone and those with tertiary education background considered twice as strongly that it was their GP’s role to inform them about NPHRs (p 0.05). There were no other significant associations with patients’ sociodemographic characteristics.
Table 3: Associations between NPHR use and participants’ sociodemographic characteristics
Characteristics
|
Unadjusted OR (95%CI)
|
p-value*
|
Multivariate analysis
|
Adjusted OR (95%CI)
|
p-value§
|
Gender
|
|
0.04
|
|
0.06
|
Female
|
1.6 (1.0-2.6)
|
|
1.7 (1.0-2.9)
|
|
Male
|
1
|
|
1
|
|
Age group
|
|
0.28
|
|
0.92
|
< 40
|
1.5 (0.9-2.4)
|
|
1.3 (0.8-2.3)
|
|
40 - 59
|
1.1 (0.7-1.8)
|
|
1.0 (0.6-1.7)
|
|
≥ 60
|
1
|
|
|
|
Place of residence
|
|
0.77
|
|
0.73
|
Urban zone
|
1.1 (0.7-1.6)
|
|
1.1 (0.7-1.7)
|
|
Semi-rural or rural zone
|
1
|
|
1
|
|
Nationality
|
|
0.06
|
|
0.22
|
Swiss
|
1
|
|
1
|
|
Other
|
1.6 (1.0-2.5)
|
|
1.5 (0.8-2.7)
|
|
Completed training
|
|
0.44
|
|
0.31
|
University, FIT1, UAS1
|
1.2 (0.7-2.0)
|
|
1.3 (0.8-2.0)
|
|
Other
|
1
|
|
1
|
|
Self-estimated health status
|
|
0.11
|
|
0.10
|
Excellent or very good
|
1
|
|
1
|
|
Good
|
0.7 (0.4-1.1)
|
|
0.7 (0.5-1.1)
|
|
Moderate or poor
|
1.1 (0.6-2.1)
|
|
1.3 (0.7-2.5)
|
|
* Univariate logistic regression, adjusted for clustering within practices.
§ Multivariate logistic regression, adjusted for all variables listed in the table and for clustering within practice.
1 FIT = Federal Institute of Technology, UAS = University of Applied Sciences
Table 4: Associations between the view of GP’s role in informing about NPHRs and participants’ sociodemographic characteristics
Characteristics
|
Unadjusted OR (95%CI)
|
p-value*
|
Multivariate analysis
|
Adjusted OR (95%CI)
|
p-value§
|
Gender
|
|
0.04
|
|
0.07
|
Female
|
1
|
|
1
|
|
Male
|
1.6 (1.0-2.6)
|
|
1.6 (1.0-2.5)
|
|
Age group
|
|
0.51
|
|
0.81
|
< 40
|
1
|
|
1
|
|
40 - 59
|
1.3 (0.7-2.1)
|
|
1.1 (0.6-2.1)
|
|
≥ 60
|
1.2 (0.8-1.8)
|
|
0.9 (0.5-1.6)
|
|
Place of residence
|
|
0.04
|
|
0.05
|
Urban zone
|
2.0 (1.0-3.8)
|
|
2.1 (1.0-4.4)
|
|
Semi-rural or rural zone
|
1
|
|
1
|
|
Nationality
|
|
0.28
|
|
0.12
|
Swiss
|
1.4 (0.7-2.7)
|
|
1.9 (0.9-4.3)
|
|
Other
|
1
|
|
1
|
|
Completed training
|
|
0.07
|
|
0.05
|
University, FIT1, UAS1
|
1.7 (1.0-3.1)
|
|
1.9 (1.0-3.6)
|
|
Other
|
1
|
|
1
|
|
Self-estimated general health status
|
|
0.82
|
|
0.86
|
Excellent or very good
|
1
|
|
1
|
|
Good
|
1.2 (0.6-2.2)
|
|
1.2 (0.6-2.4)
|
|
Moderate or poor
|
1.3 (0.5-3.2)
|
|
1.3 (0.5-3.7)
|
|
* Univariate logistic regression, adjusted for clustering within practices.
§ Multivariate logistic regression, adjusted for all variables listed in the table and for clustering within practices.
1 FIT = Federal Institute of Technology, UAS = University of Applied Sciences