Table 2.
Summary of review: important predictors and whether variable importance (VI) is reported
| ID | Important predictors | VI-yes | Participants/class/predictors |
|---|---|---|---|
| 26 | Cognitive-behavioral features | Participants: 35 labeled 80 unlabeled | |
| 27 | Patient health questionnaire-9 items | Participants: university students | |
| 28 | Demographic, health-behavioral factors | Participants: pregnancy risk assessment monitoring system enrollee | |
| 29 | Comorbid psychopathology, symptom-related disability, treatment credibility, access to therapists, time spent using certain internetintervention (deprexis) modules | 1 | |
| 30 | Pain-fatigue (symptom intensity scale), comorbidity | 1 | Participants: rheumatoid arthritis patients |
| 31 | 30 Microbial markers (gut microbiota) | 1 | Predictors: 16s-ribosomal rna gene sequences |
| 32 | Psychological elasticity, depression during the third trimester, income level | 1 | Participants: women with delivery |
| 33 | Blood-derived methylome and transcriptome features | ||
| 34 | Upper body movements-postures | 1 | Participants: university students |
| 35 | 19 Features of brain connectivity | Participants: parkinson’s disease patients | |
| 36 | Demographic, health-behavioral factors | Participants: 510/110 elders for internal/external validation | |
| 37 | SNS-derived behavioral patterns | ||
| 38 | Brain connectivity within posterior cingulate cortex, within insula, between posterior cingulate cortex and insula/hippocampus-amygdala, between insula and precuneus, between superior parietal lobule and medial prefrontal cortex | 1 | Participants: 156 advanced parkinson’s disease patients and 45 normal controls (predictors: 42 brain connectivity networks) |
| 39 | Fewer contacts, fewer calls, more messages | ||
| 40 | Higuchi’s fractal dimension, sample entropy | ||
| 41 | Fluoxetine more important than cognitive-behavioural therapy, two combined more important than one | ||
| 42 | Patient-reported immune-mediated inflammatory disease measures | ||
| 43 | SNPs rs12248560, rs878567, rs17710780 | 1 | Participants: 150 depression patients on 6-month regular therapy from the psycolaus cohort (predictors: 44 snps in existing literature) |
| 44 | Psychosometric properties in general health questionnaire | ||
| 45 | Six cognitive-behavioral tasks | Class: anxiety, depression or mixed vs. Healthy | |
| 46 | Motor activity recorded in a wearable device | ||
| 47 | Prefrontal cortical activation during working memory task anticipation | Class: unipolar vs. Bipolar depression | |
| 48 | Cingulate isthmus asymmetry, pallidal asymmetry, ratio of the paracentral to precentral cortical thickness, ratio of lateral occipital to pericalcarine cortical thickness | 1 | Class: depression relapse after electroconvulsive therapy |
| 49 | 4–6 Computerized-adaptive-diagnostic-test measures | ||
| 50 | Sex, age, medical insurance, marital status, education level, household income, pathological stage, psychosocial measures (social skills rating system, pittsburgh sleep quality index, european organization for research and treatment of cancer quality of life questionnaire [QLQ-C30]) | Participants: non-hodgkin’s lymphoma patients with chemotherapy | |
| 51 | Left precuneus, left precentral gyrus, left inferior frontal cortex (pars triangularis), left cerebellum | ||
| 52 | 120 Behavioral patterns based on smartphone censors including app adherence | ||
| 53 | Whole body kinematic cues | ||
| 54 | Age, race | Participants: women with delivery | |
| 55 | Physical activity and light exposure measured by a wearable device, sleep efficiency measured in a survey | ||
| 56 | Demographic, health-behavioral factors | ||
| 57 | Self-assessed cardiac-related fear, sex, number of words to answer the first homework assignment | 1 | Class: adherence to internet-delivered psychotherapy for myocardial infarction patients’ anxiety and depression |
The following predictors would be important variables for the early diagnosis of depression: comorbid psychopathology, symptom-related disability, treatment credibility, access to therapists, time spent using certain internet-intervention modules; pain-fatigue (symptom intensity scale), comorbidity; 30 microbial markers (gut microbiota); psychological elasticity, income level; upper body movements-postures; brain connectivity within posterior cingulate cortex, within insula, between posterior cingulate cortex and insula/hippocampus-amygdala, between insula and precuneus, between superior parietal lobule and medial prefrontal cortex; single-nucleotide polymorphisms (rs12248560, rs878567, rs17710780); cingulate isthmus asymmetry, pallidal asymmetry, ratio of the paracentral to precentral cortical thickness, ratio of lateral occipital to pericalcarine cortical thickness; self-assessed cardiac-related fear, sex, number of words to answer the first homework assignment for internet-delivered psychotherapy. ANN, artificial neural network; AR, augoregressive; AUC, area under the receiver operating characteristic curve; DT, decision tree; EEG, electroencephalogram; EN, elastic net; GB, gradient boosting; LR, logistic regression; NB, naïve bayes; RF, random forest; RMSE, root mean squared error; SNS, social network service; SNP, single nucleotide polymorphism; SVM, support vector machine