Outcome predictors in autism spectrum disorders preschoolers undergoing treatment as usual: insights from an observational study using artificial neural networks

Figures & data

Table 1 Variables on study

Age	PSI Total
Sex	PSI Child Domain
Griffiths locomotor	PSI Parent Domain
Griffiths personal	Vineland Communication
Griffiths speech	Vineland Daily Living
Griffiths eye	Vineland Socialization
Griffiths performance	Vineland Motor
Griffiths general	Vineland Composite
CBCL-int	Hours of Treatment
CBCL-ext	Parents Involvement
CBCL-tot	Treatment Centre Localization
MacArthur Comprehension	Response (ADOS-CSS)
MacArthur Expressive	No Response (ADOS-CSS)
MacArthur Gestures

Notes: Griffiths locomotor is locomotor development; Griffiths personal is personal–social development; Griffiths speech is hearing and speech; Griffiths eye is hand and eye coordination; Griffiths general is general quotient.

Abbreviations: CBCL, Child Behavior Checklist; int, internalizing; ext, externalizing; tot, total; PSI, Parenting Stress Index; ADOS-CSS, Autism Diagnostic Observation Schedule-calibrated severity score.

Table 2 Learning machines in the WEKA software package

Learning machine	Nick name	References
Logistic	Logistic	Hosmer, Lemeshow S^Citation28
J48	LogitBoost	Ross^Citation29
Multilayer perceptron	MLP	Collobert, Bengio^Citation30
Naïve Bayes	NaivBayes	George, Langley^Citation31
Random forest	RandomForest	Livingston^Citation32
Rotation forest	RotationForest	Rodriguez et al^Citation33
Sequential minimal optimization	SMO	Keerthi, Gilbert^Citation34

Table 3 Variables selected by the TWIST system

CBCL-int

CBCL-ext

CBCL-tot

PSI Child Domain

PSI Parent Domain

Vineland Communication

Vineland Motor

Vineland Composite

Parents Involvement

Abbreviations: TWIST, Training With Input Selection and Testing; CBCL, Child Behavior Checklist; int, internalizing; ext, externalizing; tot, total; PSI, Parenting Stress Index.

Table 4 Comparison at T0 among Response vs No Response groups

Demographic and clinical characteristics	Response (T0)		No response (T0)		Independent t-test			Effect size
	Mean	SD	Mean	SD	t	df	P-value	Cohen’s d
Age
Years	2.90	0.84	3.17	0.66	0.29	54	NS	0.07
ADOS
Calibrated severity score	7.54	2.10	7.23	1.44	0.58	54	NS	0.15
Griffiths
GQ	59.08	11.05	59.33	13.41	0.07	54	NS	0.01
Locomotor development	83.09	16.5	117.28	20.2	2.27	54	NS	0.61
Personal–social development	49.65	19.13	56.19	15.19	1.33	54	NS	0.36
Hearing and speech	33.91	18.63	36.57	13.31	0.57	54	NS	0.15
Hand and eye coordination	60.62	13.62	62.14	17.35	0.36	54	NS	0.09
Performance test	73.42	17.03	74.42	20.85	0.19	54	NS	0.05
Vineland-II
Composite	68.58	13.23	62.05	9.35	1.98	54	NS	0.53
Communication	63.22	13.41	52.90	15.99	2.59	54	NS	0.70
Daily Living	72	14.65	66.95	11.78	1.33	54	NS	0.36
Socialization	63.37	13.27	64.14	8.08	0.24	54	NS	0.06
Motor	82.37	16.97	76.57	10.02	1.42	54	NS	0.38
MacArthur
Production	52.45	75.56	58.71	92.39	0.27	54	NS	0.07
Comprehension	130.6	97.99	137.14	101.55	0.23	54	NS	0.06
Gestures	27.8	12.06	28.7	16.11	0.25	54	NS	0.06
CBCL
Internalizing problems	68.34	12.19	56.80	8.61	3.79	54	P<0.001	1.03
Externalizing problems	61.6	13.50	51.95	9.46	2.87	54	NS	0.78
Total problems	67.4	15.03	55.80	15.13	3.12	54	NS	0.84
PSI
Total	304.71	67.76	244.23	38.35	3.73	54	P<0.001	1.01
Child Domain	146.82	30.23	119.80	20.01	3.63	54	P<0.001	0.98
Parent Domain	157.6	41.70	125.66	21.93	3.24	54	NS	0.88

Abbreviations: SD, standard deviation; ADOS, Autism Diagnostic Observation Schedule; GQ, General Quotient; CBCL, Child Behavior Checklist; PSI, Parenting Stress Index; NS, nothing significant.

Table 5 Predictive results without variable selection

Machine learning systems	Response	No response	Global accuracy	Errors
FF_Bp	74.17%	81.82%	77.99%	12
FF_Sn	68.33%	86.36%	77.35%	13
NaivBayes	70.00%	72.73%	71.36%	16
RotationForest	88.33%	51.82%	70.08%	14
SMO	76.67%	61.82%	69.24%	16
RandomForest	85.83%	38.64%	62.23%	18
J48	75.83%	47.73%	61.78%	19
MLP	72.50%	46.82%	59.66%	20
Logistic regression	70.00%	47.27%	58.64%	21

Note: The results are the average of two testing experiments with training–testing A–B and B–A sequences.

Abbreviations: FF_Bp, feed forward Back Propagation; FF_Sn, feed forward Sine Net; MLP, multilayer perceptron; SMO, sequential minimal optimization.

Table 6 Predictive results with variable selection

Machine learning systems	Response	No response	Global accuracy	Errors
FF_Sn	93.18%	85.29%	89.24%	8
FF_Bp	86.36%	85.29%	85.83%	11
IBk	88.57%	80.95%	84.76%	8
NaivBayes (WEKA)	68.57%	76.19%	72.38%	16
SMO	77.14%	66.67%	71.90%	15
NaivBayes	57.87%	85.29%	71.58%	18
MLP	80.00%	57.14%	68.57%	16
Logistic regression	77.14%	52.38%	64.76%	18

Note: The results are the average of two testing experiments with training–testing A–B and B–A sequences.

Abbreviations: FF_Sn, feed forward Sine Net; FF_Bp, feed forward_Back Propagation; IBk, instance-based learning algorithm; MLP, multilayer perceptron; SMO, sequential minimal optimization.

Figure 1 Semantic connectivity map obtained with Auto-Cm System.

Notes: The figures on the arches of the graph refer to the strength of the association between two adjacent nodes. The range of this value is from 0 to 1. Red arrow points to the no response group; green arrow points to the response group.
Abbreviations: ADOS-CSS, Autism Diagnostic Observation Schedule-Calibrated Severity Score; CBCL, Child Behavior Checklist; int, internalizing; ext, externalizing; tot, total; Griffiths (locomotor, Locomotor development; personal, Personal–social development; speech, Hearing and speech; eye, Hand and eye coordination; general, General quotient); PSI, Parenting Stress Index; Vineland (Com, Communication; Daily Living, Daily Living Skills; Soc, Socialization).

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