Comparison of nursing diagnostic accuracy when aided by Knowledge-Based Clinical Decision Support Systems with Clinical Diagnostic Validity and Bayesian Decision Models for psychiatric care plan formulation among nursing students: a quasi-experimental study

Table 1 Demographic characteristics and pretest data of the three groups

Demographics and pretest data	Total (N = 607)		Control^a (N = 206)		CDV^b (N = 203)		BADE^c (N = 198)		P value (χ² or F)
Demographics and pretest data	n	%	N	%	n	%	n	%
Age (years), mean (SD)	21.47 (1.66)		21.30 (1.44)		21.59 (1.49)		21.53 (2.00)		.18 (1.74)^j
Sex									.08 (5.05)
Male	47	7.74	9	4.37	20	9.85	18	9.09
Female	560	92.26	197	95.63	183	90.15	180	90.91
Education program									.18 (6.23)
5-year junior college program	282	46.46	100	48.54	88	43.35	94	47.47
4-year technical program	192	31.63	56	27.18	77	37.93	59	29.80
2-year technical program	133	21.91	50	24.27	38	18.72	45	22.73
Weekly computer uses									.08 (11.40)
≤ 3 times	262	43.16	76	36.89	87	42.86	99	50.00
4 times	188	31.97	79	38.35	61	30.05	48	24.24
5 times	64	10.54	23	11.17	21	10.34	20	10.10
≥ 6 times	93	15.32	28	13.56	34	16.75	31	15.66
Experience stress when using a computer?									.07 (5.21)
Yes	142	23.39	37	17.96	52	25.62	53	26.77
No	465	76.61	169	82.04	151	74.38	145	73.23
Compliance with NANDA-I suggestions^d	438	72.16	144	69.90	152	74.88	142	71.72	.53 (1.29)
False positives^e	128	21.09	44	21.36	47	23.15	37	18.69	.55 (1.22)
False negatives^f	305	50.25	104	50.49	95	46.80	106	53.54	.40 (1.83)
True positives^g	174	28.67	58	28.16	61	30.05	55	27.78	.86 (0.29)
Positive predictive value^h	0.58		0.57		0.56		0.60		.88 (0.13)^j
Sensitivity scoreⁱ	0.36		0.36		0.39		0.34		.65 (0.43)^j

^aControl: control group using the psychiatric care planning system
^bCDV, group using the knowledge-based clinical decision support system (KBCDSS) with the clinical diagnostic validity inference engine
^cBADE, group using the KBCDSS with the Bayesian decision model inference engine
^dCompliance with NANDA-I suggestions, the frequency with which defining characteristics or risk factors were identified by the participants in accordance with NANDA-I suggestions
^eFalse positives, higher frequency of participants identifying defining characteristics than that of the researcher
^fFalse negatives, lower frequency of participants identifying defining characteristics than that of the researcher
^gTrue positives, equal frequency of participants and the researcher of identifying defining characteristics
^hPositive predictive value = true positives/(true positives + false positives)
ⁱSensitivity = true positives/(true positives + false negatives)
^jOne-way analysis of variance, P value followed by the F value in parentheses

ISSN: 1472-6955