Skip to main content

Table 5 Factors related to general practitioner vigilance to suicidalitya

From: Patterns and predictors of help-seeking contacts with health services and general practitioner detection of suicidality prior to suicide: a cohort analysis of suicides occurring over a two-year period

 

Univariate analysisb

M1: adjusted for consultations, age & gender

M2: M1 + diagnosis

M3: M2 + socio-demographic

M4: M3 + locale

GPconsultations: numberc

1.18 (1.10, 1.27)***

1.24 (1.12, 1.36)***

1.20 (1.08, 1.33)***

1.20 (1.08, 1.33)**

1.18 (1.07, 1.31)**

Age: 35–54 (ref = < 35)

3.31 (1.61, 6.79)***

2.09 (0.94, 4.62)

1.25 (0.51, 3.03)

1.20 (0.48, 2.99)

1.20 (0.47, 3.11)

 55+

2.11 (0.86, 5.20)

0.67 (0.21, 2.18)

0.50 (0.14, 1.79)

0.49 (0.13, 1.88)

0.52 (0.13, 2.15)

Gender: female (ref = male)

0.50 (0.18, 1.38)

0.18 (0.04, 0.72)*

0.19 (0.05, 0.79)*

0.21 (0.05, 0.89)*

0.18 (0.04, 0.81)*

MH problems: (ref = none)

     

 Common MH problems

5.24 (2.36, 11.62)***

 

2.75 (1.06, 7.14)*

2.86 (1.09, 7.53)*

3.47 (1.25, 9.66)*

 Serious mental illness

11.08 (3.39, 36.20)***

7.76 (2.03, 29.67)**

8.61 (2.13, 34.85)**

8.08 (1.94, 33.71)**

 Drugs/alcohol problems

10.15 (3.45, 29.88)***

4.34 (1.18, 16.0)*

4.74 (1.23, 18.17)*

4.28 (1.13, 16.25)*

Lives alone: yes (ref = no)

1.35 (0.67, 2.68)

  

0.85 (0.34, 2.12)

0.74 (0.28, 1.95)

In paid work: no (ref = yes)

0.87 (0.45, 1.65)

  

0.79 (0.34, 1.87)

0.90 (0.37, 2.22)

Locale: large towns (ref = urban)

1.99 (0.94, 4.22)

   

2.35 (0.93, 5.60)

Small townsd

na

na

Rural areas

1.65 (0.74, 3.65)

1.65 (0.60, 4.56)

  1. *** = p < 0.001; ** = S < 0.005; * = 0.05
  2. a Analysis includes only those who have no history of prior attempts
  3. b Data represents Odds Ratios (ORs) indicating the likelihood of the patient having discussed suicide with their GP
  4. c Number of consultations entered into the model as continuous-ORs represent the increase in likelihood of engagement per additional consultation
  5. d The category ‘small towns’ predicts the outcome perfectly-they are therefore dropped from the analysis