Treatments

Import data

load("~/madness/nmhss_2019_puf_R.RData")

load("~/madness/N-MHSS-2010-DS0001-data-r.rda")

rename data sets

treatments_2019 <- PUF
treatments_2010 <- da34945.0001

library(skimr)

## Warning: package 'skimr' was built under R version 4.0.3

skim(da34945.0001)

Data summary

Name	da34945.0001
Number of rows	10374
Number of columns	237
_______________________
Column type frequency:
factor	119
numeric	118
________________________
Group variables	None

Variable type: factor

skim_variable	n_missing	complete_rate	ordered	n_unique	top_counts
STFIPS	0	1.00	FALSE	52	(06: 927, (36: 685, (42: 541, (17: 512
MODE	0	1.00	FALSE	4	(4): 5538, (3): 2535, (1): 1726, (2): 575
MHINTAKE	623	0.94	FALSE	2	(1): 8208, (0): 1543
MHDIAGEVAL	622	0.94	FALSE	2	(1): 8253, (0): 1499
MHREFERRAL	626	0.94	FALSE	2	(1): 6630, (0): 3118
SASERV	625	0.94	FALSE	2	(1): 4897, (0): 4852
MENTALHTHSERV	0	1.00	FALSE	1	(1): 10374
ADMINSERV	653	0.94	FALSE	2	(1): 5802, (0): 3919
SETTINGIP	0	1.00	FALSE	2	(0): 8399, (1): 1975
SETTINGRC	0	1.00	FALSE	2	(0): 8100, (1): 2274
SETTINGOP	0	1.00	FALSE	2	(1): 7931, (0): 2443
FACILITYTYPE	0	1.00	FALSE	6	(5): 6468, (2): 1238, (4): 878, (3): 781
FOCUS	630	0.94	FALSE	2	(1): 7287, (3): 2457
OWNERSHIP	0	1.00	FALSE	8	(2): 6968, (1): 996, (7): 953, (3): 727
RELIGIOUS	682	0.93	FALSE	2	(0): 8876, (1): 816
TREATACTVTYTHRPY	1297	0.87	FALSE	2	(1): 4676, (0): 4401
TREATBEHAVMOD	1294	0.88	FALSE	2	(1): 5950, (0): 3130
TREATCOGTHRPY	1291	0.88	FALSE	2	(1): 8061, (0): 1022
TREATFAMTHRPY	1293	0.88	FALSE	2	(1): 6129, (0): 2952
TREATELECTRO	1342	0.87	FALSE	2	(0): 8459, (1): 573
TREATGRPTHRPY	1292	0.88	FALSE	2	(1): 7742, (0): 1340
TREATPSYCHOTHRPY	1286	0.88	FALSE	2	(1): 7844, (0): 1244
TREATDUALMHSA	1331	0.87	FALSE	2	(1): 4967, (0): 4076
TREATPSYCHOMED	1289	0.88	FALSE	2	(1): 7601, (0): 1484
TREATTELEMEDINCE	1372	0.87	FALSE	2	(0): 7593, (1): 1409
TREATOTH	1240	0.88	FALSE	2	(0): 8371, (1): 763
ASSERTCOMM	1333	0.87	FALSE	2	(0): 7420, (1): 1621
MHCASEMGMT	1298	0.87	FALSE	2	(1): 6741, (0): 2335
MHCHRONIC	1351	0.87	FALSE	2	(0): 7174, (1): 1849
MHCONSUMER	1327	0.87	FALSE	2	(0): 7352, (1): 1695
MHEDUCATION	1317	0.87	FALSE	2	(0): 4991, (1): 4066
FAMPSYCHED	1316	0.87	FALSE	2	(1): 5490, (0): 3568
MHHOUSING	1333	0.87	FALSE	2	(0): 6870, (1): 2171
ILLNESSMGMT	1341	0.87	FALSE	2	(0): 6006, (1): 3027
MHLEGAL	1358	0.87	FALSE	2	(0): 8250, (1): 766
MHEMGCY	1328	0.87	FALSE	2	(0): 5654, (1): 3392
MHPSYCHREHAB	1334	0.87	FALSE	2	(0): 4693, (1): 4347
SMOKINGCESSATION	1326	0.87	FALSE	2	(0): 6858, (1): 2190
MHSUICIDE	1325	0.87	FALSE	2	(1): 5230, (0): 3819
SUPPEMPLOY	1333	0.87	FALSE	2	(0): 7157, (1): 1884
SUPPHOUSING	1339	0.87	FALSE	2	(0): 7336, (1): 1699
FOSTERCARE	1354	0.87	FALSE	2	(0): 8370, (1): 650
MHVOCREHAB	1351	0.87	FALSE	2	(0): 7564, (1): 1459
MHOTH	1241	0.88	FALSE	2	(0): 8605, (1): 528
CHILDADOL	1242	0.88	FALSE	2	(1): 5781, (0): 3351
ADULTS	1250	0.88	FALSE	2	(1): 7810, (0): 1314
SENIORS	1247	0.88	FALSE	2	(1): 6870, (0): 2257
SED	1266	0.88	FALSE	2	(0): 5164, (1): 3944
TRANSITIONAGE	1280	0.88	FALSE	2	(0): 6347, (1): 2747
SPMI	1277	0.88	FALSE	2	(1): 5738, (0): 3359
ALZHDEMENTIA	1298	0.87	FALSE	2	(0): 7911, (1): 1165
MHANDSA	1276	0.88	FALSE	2	(1): 5333, (0): 3765
MHANDOTHER	1288	0.88	FALSE	2	(0): 4787, (1): 4299
POSTTRAUM	1275	0.88	FALSE	2	(1): 4569, (0): 4530
VETERNS	1317	0.87	FALSE	2	(0): 6971, (1): 2086
TRAUMATICBRAIN	1322	0.87	FALSE	2	(0): 7995, (1): 1057
GLBT	1304	0.87	FALSE	2	(0): 6665, (1): 2405
FORENSIC	1288	0.88	FALSE	2	(0): 6100, (1): 2986
PROGOTH	1237	0.88	FALSE	2	(0): 8569, (1): 568
HEARIMPAIR	1322	0.87	FALSE	2	(1): 5510, (0): 3542
LANGENGLISH	1247	0.88	FALSE	2	(1): 9084, (0): 43
LANGSPANISH	1250	0.88	FALSE	2	(0): 5705, (1): 3419
LANGOTH	1249	0.88	FALSE	2	(0): 8367, (1): 758
CRISISTEAM	1278	0.88	FALSE	4	(4): 3803, (3): 2185, (1): 2157, (2): 951
COMPRESULTRPTG	1277	0.88	FALSE	2	(0): 5331, (1): 3766
COMPCPOE	1301	0.87	FALSE	2	(0): 6407, (1): 2666
COMPCLINDATA	1298	0.87	FALSE	2	(0): 6283, (1): 2793
COMPREFERRALS	1284	0.88	FALSE	2	(0): 7059, (1): 2031
COMPTREATPLAN	1267	0.88	FALSE	2	(1): 6166, (0): 2941
COMPSATISFYSURVEY	1292	0.88	FALSE	2	(0): 6462, (1): 2620
COMPMEDCHECK	1332	0.87	FALSE	2	(0): 5358, (1): 3684
COMPBILLING	1304	0.87	FALSE	2	(1): 7478, (0): 1592
COMPPATIENTSCHED	1286	0.88	FALSE	2	(1): 5767, (0): 3321
COMPPROCESSNOTE	1286	0.88	FALSE	2	(1): 5852, (0): 3236
COMPOTH	1241	0.88	FALSE	2	(0): 8745, (1): 388
EDUCREQUIRE	1257	0.88	FALSE	2	(1): 8147, (0): 970
CASEREVIEW	1258	0.88	FALSE	2	(1): 8342, (0): 774
COMMITTEE	1273	0.88	FALSE	2	(1): 6399, (0): 2702
OUTCOME	1279	0.88	FALSE	2	(1): 4882, (0): 4213
UTILIZATION	1275	0.88	FALSE	2	(1): 8298, (0): 801
SATISFYSURVEY	1266	0.88	FALSE	2	(1): 8583, (0): 525
NOCHARGE	1298	0.87	FALSE	2	(1): 5537, (0): 3539
FEESCALE	1361	0.87	FALSE	2	(1): 5527, (0): 3486
FUNDMEDICAID	1263	0.88	FALSE	2	(1): 8062, (0): 1049
FUNDMEDICARE	1279	0.88	FALSE	2	(1): 6324, (0): 2771
FUNDSMHA	1354	0.87	FALSE	2	(1): 6466, (0): 2554
FUNDSTATEWELFARE	1341	0.87	FALSE	2	(0): 4941, (1): 4092
FUNDSTATEJUV	1319	0.87	FALSE	2	(0): 6123, (1): 2932
FUNDSTATEEDUC	1345	0.87	FALSE	2	(0): 7107, (1): 1922
FUNDLOCALGOV	1341	0.87	FALSE	2	(0): 4540, (1): 4493
FUNDVA	1335	0.87	FALSE	2	(0): 6862, (1): 2177
FUNDCSBG	1403	0.86	FALSE	2	(0): 6757, (1): 2214
FUNDCMHG	1392	0.87	FALSE	2	(0): 5607, (1): 3375
FUNDCLIENTFEES	1282	0.88	FALSE	2	(1): 7689, (0): 1403
FUNDPRVTINS	1291	0.88	FALSE	2	(1): 7166, (0): 1917
FUNDOTHPUB	1261	0.88	FALSE	2	(0): 8586, (1): 527
FUNDOTHPRVT	1268	0.88	FALSE	2	(0): 8419, (1): 687
MAJORSINGLEFUND	1445	0.86	FALSE	2	(1): 5913, (0): 3016
MAJORFUNDTYPE	4522	0.56	FALSE	14	(01: 3320, (03: 958, (02: 402, (12: 269
SMOKINGPOLICY	1256	0.88	FALSE	5	(2): 4537, (1): 3806, (3): 714, (5): 55
USEDSECLUSION	1289	0.88	FALSE	2	(0): 6476, (1): 2609
ADOPTSECLUSION	1643	0.84	FALSE	2	(0): 4796, (1): 3935
LICENSESMHA	1341	0.87	FALSE	2	(1): 6727, (0): 2306
LICENSESA	1362	0.87	FALSE	2	(0): 6241, (1): 2771
LICENSEDPH	1399	0.87	FALSE	2	(0): 5318, (1): 3657
LICENSEHOSPLIC	1429	0.86	FALSE	2	(0): 7540, (1): 1405
LICENSEJC	1376	0.87	FALSE	2	(0): 5725, (1): 3273
LICENSECARF	1393	0.87	FALSE	2	(0): 7180, (1): 1801
LICENSECOA	1500	0.86	FALSE	2	(0): 7933, (1): 941
LICENSEDFCS	1436	0.86	FALSE	2	(0): 7428, (1): 1510
LICENSEDHHS	1546	0.85	FALSE	2	(0): 7534, (1): 1294
LICENSEMEDICARE	1502	0.86	FALSE	2	(0): 4467, (1): 4405
LICENSEMEDICAID	1466	0.86	FALSE	2	(1): 5743, (0): 3165
LICENSEOTHORG	1319	0.87	FALSE	2	(0): 8407, (1): 648
FACONLY	0	1.00	FALSE	3	(1): 7473, (3): 2209, (2): 692
IPSERV	0	1.00	FALSE	2	(0): 8386, (1): 1988
RCSERV	0	1.00	FALSE	2	(0): 8048, (1): 2326
OPSERV	0	1.00	FALSE	2	(1): 7871, (0): 2503
SRVCHAR	0	1.00	FALSE	2	(1): 9139, (0): 1235

Variable type: numeric

skim_variable	n_missing	complete_rate	mean	sd	p0	p25	p50	p75	p100	hist
CASEID	0	1.00	5187.50	2994.86	1	2594.25	5187.5	7780.75	10374	▇▇▇▇▇
TOTALFAC	9682	0.07	3.93	2.97	2	2.00	3.0	5.00	27	▇▁▁▁▁
IPTOTAL	8386	0.19	50.05	90.53	1	12.00	23.0	52.00	1506	▇▁▁▁▁
IPSEXTOTM	8386	0.19	29.65	66.30	0	6.00	12.0	27.00	1157	▇▁▁▁▁
IPSEXPERM	8386	0.19	52.62	17.46	0	42.00	51.0	61.00	100	▁▃▇▃▁
IPSEXTOTF	8386	0.19	20.40	31.06	0	6.00	11.0	22.00	371	▇▁▁▁▁
IPSEXPERF	8386	0.19	47.38	17.46	0	39.00	49.0	58.00	100	▁▃▇▂▁
IPAGETOT017	8386	0.19	10.37	35.95	0	0.00	0.0	10.00	923	▇▁▁▁▁
IPAGEPER017	8386	0.19	20.23	33.74	0	0.00	0.0	28.00	100	▇▂▁▁▂
IPAGETOT1864	8386	0.19	33.99	77.34	0	4.00	14.0	30.00	1409	▇▁▁▁▁
IPAGEPER1864	8386	0.19	61.69	36.82	0	33.75	75.0	93.00	100	▅▁▂▃▇
IPAGETOT65	8386	0.19	5.69	13.29	0	0.00	2.0	7.00	238	▇▁▁▁▁
IPAGEPER65	8386	0.19	18.08	28.21	0	0.00	7.0	20.00	100	▇▁▁▁▁
IPETHTOTHISP	8386	0.19	3.56	15.93	0	0.00	0.0	1.00	338	▇▁▁▁▁
IPETHPERHISP	8386	0.19	5.33	13.01	0	0.00	0.0	5.00	100	▇▁▁▁▁
IPETHTOTNONHISP	8386	0.19	25.82	71.12	0	0.00	6.0	21.00	1168	▇▁▁▁▁
IPETHPERNONHISP	8386	0.19	48.70	46.12	0	0.00	65.0	97.00	100	▇▁▁▁▇
IPETHTOTUNK	8386	0.19	20.68	52.55	0	0.00	2.0	23.00	923	▇▁▁▁▁
IPETHPERUNK	8386	0.19	45.97	49.13	0	0.00	4.0	100.00	100	▇▁▁▁▇
IPRACETOTINDIAN	8386	0.19	0.21	1.62	0	0.00	0.0	0.00	40	▇▁▁▁▁
IPRACEPERINDIAN	8386	0.19	0.42	2.68	0	0.00	0.0	0.00	50	▇▁▁▁▁
IPRACETOTASIAN	8386	0.19	0.48	2.69	0	0.00	0.0	0.00	56	▇▁▁▁▁
IPRACEPERASIAN	8386	0.19	0.69	2.70	0	0.00	0.0	0.00	50	▇▁▁▁▁
IPRACETOTBLK	8386	0.19	7.94	28.70	0	0.00	0.0	3.00	457	▇▁▁▁▁
IPRACEPERBLK	8386	0.19	10.35	17.84	0	0.00	0.0	15.00	100	▇▁▁▁▁
IPRACETOTHAWPAC	8386	0.19	0.09	1.51	0	0.00	0.0	0.00	53	▇▁▁▁▁
IPRACEPERHAWPAC	8386	0.19	0.14	2.72	0	0.00	0.0	0.00	85	▇▁▁▁▁
IPRACETOTWHIT	8386	0.19	17.85	50.04	0	0.00	2.0	15.00	775	▇▁▁▁▁
IPRACEPERWHIT	8386	0.19	37.33	39.93	0	0.00	20.5	78.00	100	▇▁▂▂▃
IPRACETOTMR	8386	0.19	1.06	18.45	0	0.00	0.0	0.00	757	▇▁▁▁▁
IPRACEPERMR	8386	0.19	1.42	8.26	0	0.00	0.0	0.00	100	▇▁▁▁▁
IPRACETOTUNK	8386	0.19	22.41	49.67	0	0.00	6.5	25.00	923	▇▁▁▁▁
IPRACEPERUNK	8386	0.19	49.66	48.47	0	0.00	27.0	100.00	100	▇▁▁▁▇
IPLEGALTOTVOL	8386	0.19	20.69	32.01	0	5.00	12.0	25.00	522	▇▁▁▁▁
IPLEGALPERVOL	8386	0.19	59.63	36.84	0	26.75	67.0	100.00	100	▅▂▃▂▇
IPLEGALTOTNONFOREN	8386	0.19	19.00	49.95	0	0.00	4.0	16.00	923	▇▁▁▁▁
IPLEGALPERNONFOREN	8386	0.19	31.67	32.98	0	0.00	20.0	55.00	100	▇▂▂▂▂
IPLEGALTOTFOREN	8386	0.19	10.36	57.91	0	0.00	0.0	0.00	1506	▇▁▁▁▁
IPLEGALPERFOREN	8386	0.19	8.70	24.68	0	0.00	0.0	0.00	100	▇▁▁▁▁
IPBEDS	8386	0.19	57.13	89.25	1	18.00	31.0	60.00	1506	▇▁▁▁▁
RCTOTAL	8048	0.22	26.12	34.13	1	8.00	15.0	30.00	427	▇▁▁▁▁
RCSEXTOTM	8048	0.22	17.90	27.88	0	4.00	9.0	22.00	422	▇▁▁▁▁
RCSEXPERM	8048	0.22	64.41	28.30	0	50.00	62.0	97.00	100	▂▂▇▆▇
RCSEXTOTF	8048	0.22	8.23	12.62	0	0.00	4.0	10.00	159	▇▁▁▁▁
RCSEXPERF	8048	0.22	35.59	28.30	0	3.00	38.0	50.00	100	▇▇▇▂▂
RCAGETOT017	8048	0.22	13.71	25.79	0	0.00	0.0	17.00	360	▇▁▁▁▁
RCAGEPER017	8048	0.22	41.63	46.95	0	0.00	0.0	100.00	100	▇▁▁▁▆
RCAGETOT1864	8048	0.22	10.96	25.07	0	0.00	5.0	13.00	402	▇▁▁▁▁
RCAGEPER1864	8048	0.22	52.52	44.61	0	0.00	67.0	100.00	100	▇▁▁▁▇
RCAGETOT65	8048	0.22	1.46	6.69	0	0.00	0.0	0.00	186	▇▁▁▁▁
RCAGEPER65	8048	0.22	5.85	15.99	0	0.00	0.0	0.00	100	▇▁▁▁▁
RCETHTOTHISP	8048	0.22	1.88	5.14	0	0.00	0.0	1.00	60	▇▁▁▁▁
RCETHPERHISP	8048	0.22	6.99	13.70	0	0.00	0.0	9.00	100	▇▁▁▁▁
RCETHTOTNONHISP	8048	0.22	15.69	27.99	0	0.00	7.5	17.00	406	▇▁▁▁▁
RCETHPERNONHISP	8048	0.22	63.08	42.72	0	0.00	87.0	100.00	100	▅▁▁▂▇
RCETHTOTUNK	8048	0.22	8.55	21.53	0	0.00	0.0	7.00	320	▇▁▁▁▁
RCETHPERUNK	8048	0.22	29.93	44.64	0	0.00	0.0	100.00	100	▇▁▁▁▃
RCRACETOTINDIAN	8048	0.22	0.36	1.85	0	0.00	0.0	0.00	29	▇▁▁▁▁
RCRACEPERINDIAN	8048	0.22	1.52	7.19	0	0.00	0.0	0.00	100	▇▁▁▁▁
RCRACETOTASIAN	8048	0.22	0.17	0.74	0	0.00	0.0	0.00	13	▇▁▁▁▁
RCRACEPERASIAN	8048	0.22	0.79	3.45	0	0.00	0.0	0.00	50	▇▁▁▁▁
RCRACETOTBLK	8048	0.22	4.80	11.43	0	0.00	1.0	4.00	198	▇▁▁▁▁
RCRACEPERBLK	8048	0.22	17.50	23.72	0	0.00	5.0	30.00	100	▇▂▁▁▁
RCRACETOTHAWPAC	8048	0.22	0.09	0.93	0	0.00	0.0	0.00	24	▇▁▁▁▁
RCRACEPERHAWPAC	8048	0.22	0.57	5.80	0	0.00	0.0	0.00	100	▇▁▁▁▁
RCRACETOTWHIT	8048	0.22	9.93	18.98	0	0.00	5.0	11.00	359	▇▁▁▁▁
RCRACEPERWHIT	8048	0.22	44.38	37.11	0	0.00	49.5	78.00	100	▇▂▃▅▅
RCRACETOTMR	8048	0.22	0.79	3.10	0	0.00	0.0	0.00	80	▇▁▁▁▁
RCRACEPERMR	8048	0.22	2.88	8.17	0	0.00	0.0	0.00	100	▇▁▁▁▁
RCRACETOTUNK	8048	0.22	9.98	23.71	0	0.00	0.0	9.00	400	▇▁▁▁▁
RCRACEPERUNK	8048	0.22	32.37	44.56	0	0.00	0.0	100.00	100	▇▁▁▁▃
RCLEGALTOTVOL	8048	0.22	15.57	26.78	0	1.00	8.0	17.00	427	▇▁▁▁▁
RCLEGALPERVOL	8048	0.22	66.39	42.78	0	11.00	100.0	100.00	100	▃▁▁▁▇
RCLEGALTOTNONFOREN	8048	0.22	6.75	18.37	0	0.00	0.0	5.00	288	▇▁▁▁▁
RCLEGALPERNONFOREN	8048	0.22	20.25	33.08	0	0.00	0.0	37.00	100	▇▁▁▁▁
RCLEGALTOTFOREN	8048	0.22	3.80	15.67	0	0.00	0.0	0.00	336	▇▁▁▁▁
RCLEGALPERFOREN	8048	0.22	13.36	29.38	0	0.00	0.0	0.00	100	▇▁▁▁▁
RCBEDS	8048	0.22	29.26	40.20	1	8.00	16.0	34.00	713	▇▁▁▁▁
OPTOTAL	2503	0.76	384.50	584.28	1	60.00	200.0	465.00	14332	▇▁▁▁▁
OPSEXTOTM	2503	0.76	188.66	356.57	0	30.00	97.0	220.00	13375	▇▁▁▁▁
OPSEXPERM	2503	0.76	49.31	14.60	0	42.00	49.0	55.00	100	▁▂▇▁▁
OPSEXTOTF	2503	0.76	195.83	293.48	0	29.00	99.0	239.00	4791	▇▁▁▁▁
OPSEXPERF	2503	0.76	50.69	14.60	0	45.00	51.0	58.00	100	▁▂▇▂▁
OPAGETOT017	2503	0.76	105.56	240.11	0	0.00	35.0	115.00	5127	▇▁▁▁▁
OPAGEPER017	2503	0.76	30.93	32.27	0	0.00	24.0	41.00	100	▇▅▂▁▂
OPAGETOT1864	2503	0.76	248.71	414.88	0	24.00	112.0	295.00	8018	▇▁▁▁▁
OPAGEPER1864	2503	0.76	61.57	30.97	0	48.00	68.0	86.00	100	▅▁▅▇▇
OPAGETOT65	2503	0.76	30.23	112.20	0	0.00	8.0	26.50	6314	▇▁▁▁▁
OPAGEPER65	2503	0.76	7.50	12.97	0	0.00	4.0	10.00	100	▇▁▁▁▁
OPETHTOTHISP	2503	0.76	32.98	122.14	0	0.00	2.0	18.00	3320	▇▁▁▁▁
OPETHPERHISP	2503	0.76	8.96	17.43	0	0.00	1.0	10.00	100	▇▁▁▁▁
OPETHTOTNONHISP	2503	0.76	200.33	389.41	0	0.00	44.0	231.00	8594	▇▁▁▁▁
OPETHPERNONHISP	2503	0.76	54.95	43.21	0	0.00	75.0	96.00	100	▆▁▁▂▇
OPETHTOTUNK	2503	0.76	151.19	447.03	0	0.00	3.0	100.00	14332	▇▁▁▁▁
OPETHPERUNK	2503	0.76	36.09	46.26	0	0.00	1.0	100.00	100	▇▁▁▁▅
OPRACETOTINDIAN	2503	0.76	2.29	9.79	0	0.00	0.0	1.00	334	▇▁▁▁▁
OPRACEPERINDIAN	2503	0.76	0.93	4.72	0	0.00	0.0	0.00	100	▇▁▁▁▁
OPRACETOTASIAN	2503	0.76	3.53	26.89	0	0.00	0.0	1.00	1148	▇▁▁▁▁
OPRACEPERASIAN	2503	0.76	0.81	4.34	0	0.00	0.0	0.00	100	▇▁▁▁▁
OPRACETOTBLK	2503	0.76	44.09	138.19	0	0.00	1.0	24.00	2365	▇▁▁▁▁
OPRACEPERBLK	2503	0.76	11.79	20.07	0	0.00	1.0	15.00	100	▇▁▁▁▁
OPRACETOTHAWPAC	2503	0.76	1.37	16.29	0	0.00	0.0	0.00	567	▇▁▁▁▁
OPRACEPERHAWPAC	2503	0.76	0.39	3.77	0	0.00	0.0	0.00	99	▇▁▁▁▁
OPRACETOTWHIT	2503	0.76	149.76	343.79	0	0.00	16.0	160.00	12017	▇▁▁▁▁
OPRACEPERWHIT	2503	0.76	40.28	38.80	0	0.00	40.0	80.00	100	▇▁▂▂▅
OPRACETOTMR	2503	0.76	7.32	39.34	0	0.00	0.0	1.00	1470	▇▁▁▁▁
OPRACEPERMR	2503	0.76	2.13	7.48	0	0.00	0.0	1.00	100	▇▁▁▁▁
OPRACETOTUNK	2503	0.76	176.14	424.82	0	0.00	18.0	162.50	7482	▇▁▁▁▁
OPRACEPERUNK	2503	0.76	43.67	47.03	0	0.00	12.0	100.00	100	▇▁▁▁▆
OPLEGALTOTVOL	2503	0.76	313.24	536.21	0	25.00	133.0	378.00	14332	▇▁▁▁▁
OPLEGALPERVOL	2503	0.76	82.01	34.49	0	87.00	100.0	100.00	100	▂▁▁▁▇
OPLEGALTOTNONFOREN	2503	0.76	13.87	114.73	0	0.00	0.0	0.00	7141	▇▁▁▁▁
OPLEGALPERNONFOREN	2503	0.76	3.75	12.49	0	0.00	0.0	0.00	100	▇▁▁▁▁
OPLEGALTOTFOREN	2503	0.76	57.39	243.48	0	0.00	0.0	6.00	7482	▇▁▁▁▁
OPLEGALPERFOREN	2503	0.76	14.24	32.28	0	0.00	0.0	3.00	100	▇▁▁▁▁
PERCENTCP	3197	0.69	27.40	25.81	0	5.00	20.0	40.00	100	▇▃▂▁▁
MHADMISSIONS	6	1.00	801.14	1835.69	0	91.00	480.0	786.00	60000	▇▁▁▁▁
PERCENTVA	3478	0.66	5.60	15.87	0	0.00	1.0	5.00	100	▇▁▁▁▁

Clean 2019

library(dplyr)

## Warning: package 'dplyr' was built under R version 4.0.3

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(tidyr)

## Warning: package 'tidyr' was built under R version 4.0.3

treat_cleaned_2019 <- treatments_2019 %>%
  #select treatment variables
  select(starts_with("TREAT")) %>%
  pivot_longer(cols = everything(), names_to = "treatment", values_to = "count") %>%
  #compute percentage of facilities that offer the treatment
  group_by(treatment) %>%
  summarise(percent2019 = mean(count)) %>%
  mutate(treatment = case_when(
    treatment == "TREATPSYCHOTHRPY" ~ "psychotherapy",
    treatment == "TREATFAMTHRPY" ~ "family therapy",
    treatment == "TREATGRPTHRPY" ~ "group therapy",
    treatment == "TREATCOGTHRPY" ~ "cognitive behavioral therapy",
    treatment == "TREATDIALTHRPY" ~ "dialectical behavior therapy",
    treatment == "TREATBEHAVMOD" ~ "behavior modification",
    treatment == "TREATDUALMHSA" ~ "integrated dual disorders treatment",
    treatment == "TREATTRAUMATHRPY" ~ "trauma therapy",
    treatment == "TREATACTVTYTHRPY" ~ "activity therapy",
    treatment == "TREATELECTRO" ~ "electroconvulsive therapy",
    treatment == "TREATTELEMEDINCE" ~ "telemedicine therapy",
    treatment == "TREATPSYCHOMED" ~ "psychotropic medication",
    treatment == "TREATOTH" ~ "mentalhealth treatment approach",
    treatment == "TREATMT" ~ "substanceuse treatment",
    TRUE ~ as.character(treatment)))

treat_cleaned_2019

## # A tibble: 14 x 2
##    treatment                           percent2019
##  * <chr>                                     <dbl>
##  1 activity therapy                         0.446 
##  2 behavior modification                    0.660 
##  3 cognitive behavioral therapy             0.902 
##  4 dialectical behavior therapy             0.563 
##  5 integrated dual disorders treatment      0.566 
##  6 electroconvulsive therapy                0.0410
##  7 family therapy                           0.725 
##  8 group therapy                            0.856 
##  9 substanceuse treatment                   0.563 
## 10 mentalhealth treatment approach          0.0585
## 11 psychotropic medication                  0.818 
## 12 psychotherapy                            0.916 
## 13 telemedicine therapy                     0.380 
## 14 trauma therapy                           0.773

Clean 2010 data

library(readr)

## Warning: package 'readr' was built under R version 4.0.3

treat_cleaned_2010 <- treatments_2010 %>%
  select(starts_with("TREAT")) %>%
  pivot_longer(cols = everything(), names_to = "treatment", values_to = "count") %>%
  mutate(count = parse_number(as.character(count))) %>%
  group_by(treatment) %>%
  summarise(percent2010 = mean(count, na.rm = TRUE)) %>%
  mutate(treatment = case_when(
    treatment == "TREATPSYCHOTHRPY" ~ "psychotherapy",
    treatment == "TREATFAMTHRPY" ~ "family therapy",
    treatment == "TREATGRPTHRPY" ~ "group therapy",
    treatment == "TREATCOGTHRPY" ~ "cognitive behavioral therapy",
    treatment == "TREATDIALTHRPY" ~ "dialectical behavior therapy",
    treatment == "TREATBEHAVMOD" ~ "behavior modification",
    treatment == "TREATDUALMHSA" ~ "integrated dual disorders treatment",
    treatment == "TREATTRAUMATHRPY" ~ "trauma therapy",
    treatment == "TREATACTVTYTHRPY" ~ "activity therapy",
    treatment == "TREATELECTRO" ~ "electroconvulsive therapy",
    treatment == "TREATTELEMEDINCE" ~ "telemedicine therapy",
    treatment == "TREATPSYCHOMED" ~ "psychotropic medication",
    treatment == "TREATOTH" ~ "mentalhealth treatment approach",
    treatment == "TREATMT" ~ "substanceuse treatment",
    TRUE ~ as.character(treatment)))

treat_cleaned_2010

## # A tibble: 11 x 2
##    treatment                           percent2010
##  * <chr>                                     <dbl>
##  1 activity therapy                         0.515 
##  2 behavior modification                    0.655 
##  3 cognitive behavioral therapy             0.887 
##  4 integrated dual disorders treatment      0.549 
##  5 electroconvulsive therapy                0.0634
##  6 family therapy                           0.675 
##  7 group therapy                            0.852 
##  8 mentalhealth treatment approach          0.0835
##  9 psychotropic medication                  0.837 
## 10 psychotherapy                            0.863 
## 11 telemedicine therapy                     0.157

Join data

treat <- full_join(treat_cleaned_2010, treat_cleaned_2019) %>%
  mutate(percent2010 = ifelse(is.na(percent2010),0,percent2010),
         treatment = forcats::fct_reorder(treatment,percent2019)) %>%
  pivot_longer(cols = -treatment, names_to = "year", values_to = "percent")

## Joining, by = "treatment"

treat

## # A tibble: 28 x 3
##    treatment                           year        percent
##    <fct>                               <chr>         <dbl>
##  1 activity therapy                    percent2010  0.515 
##  2 activity therapy                    percent2019  0.446 
##  3 behavior modification               percent2010  0.655 
##  4 behavior modification               percent2019  0.660 
##  5 cognitive behavioral therapy        percent2010  0.887 
##  6 cognitive behavioral therapy        percent2019  0.902 
##  7 integrated dual disorders treatment percent2010  0.549 
##  8 integrated dual disorders treatment percent2019  0.566 
##  9 electroconvulsive therapy           percent2010  0.0634
## 10 electroconvulsive therapy           percent2019  0.0410
## # ... with 18 more rows

Visualize data

library(ggplot2)

## Warning: package 'ggplot2' was built under R version 4.0.4

library(scales)

## Warning: package 'scales' was built under R version 4.0.4

## 
## Attaching package: 'scales'

## The following object is masked from 'package:readr':
## 
##     col_factor

ggplot(treat, 
       aes(x = percent, 
           y = treatment,
           fill = year)) +
  geom_bar(stat = "identity", position = "dodge")+  
labs(title = "Popular Mental Illness treatments in the US",
     y = NULL,
     x = "Percent of Facilities",
     caption = "Data Source: SAMHSA, National Mental Health Services Survey")

Methods and practices for treating the mentally ill have changed drastically over time. Current methods most commonly consist of therapy and a wide variety of medicines including antidepressants that increase dopamine levels in people, and more. In the data used in class we found that the most common treatments are varieties of therapy. For example, family therapy, group therapy, cognitive behavior therapy, and psychotherapy just to name a few. This reflects back in history on Phillipe Pinel and his theories and practices. Pinel believed that the mentally ill should not be chained up. He believed methods like rotational therapy, malarial infection therapy, insulin coma therapy and electroconvulsive therapy were inhumane and unnecessary because. He had a strong believe that kindness and discipline go hand in hand and this is still seen today in modern medicine. Pinel was not satisfied with the state of madhouses and how their patients were being treated. Everyone was treated like animals and given the same treatments, even though everyone is different and has their own personal illness. Pinel believed that moral treatment was going to be incredibly beneficial for patients, along with cohorts so people are not all receiving the same treatment that are likely not making a difference. This is similar to practices today, therapists meet with a certain amount of patients who struggle with a variety of mental illnesses, and together focus on ways to improve.

One popular method in today’s current treatment is cognitive behavioral therapy, which is a hybrid of cognitive and behavioral therapy. This reflects back on the theory developed by Aaron Beck and Albert Ellis, who had the idea of one of the most successful innovations during its time, cognitive behavioral therapy. Beck found that, “depressed patients tended to be overwhelmed by spontaneous negative thoughts, and that challenging the veracity of these thoughts more often than not led to recovery”(Eghigian, 2021). This is still seen today, a great practice to help with depression is mindfulness and turning negative thoughts into positive ones, although that is difficult for metnally ill people. Beck believed it is not necessary to travel into one’s past, and that a patient is ill as they are now, not in the past. He believed peoples current problems do not have to do with past trauma, everything is in the now, and any struggles mentally are completely conscious. This is interesting to compare to therapy nowadays, often mental illness is characterized by past trauma, and therapists work with their patients to get down to the bottom of where their mental illness first sprung from, so there is some contrast regarding Becks’ beliefs in comparison to today.

In the passage “Osheroff v. Chestnut Lodge”, Rafael Osheroff, a physician himself, was admitted to the psychiatric treatment center Chestnut Lodge, where a variety of treatments were done to him. Osheroff later filed a lawsuit against the facility for refusing to provide him with the proper treatment he knew he should have received. The treatments he received were similar to treatments still used today, like drugs and psychotherapy. This passage addresses efficacy and how Osheroff was not treated with efficacy by the Chestnut Lodge. Nowadays efficacy is very important in mental illness facilities and things like diagnosing patients incorrectly and prescribing them with improper medication is not tolerated and/or is hard to pass by.

Current day facilities that house the mentally ill are often seen as very beneficial for the patients, they receive proper hands on care and learn coping mechanisms tailored to their illness. The passage “Insulin and I” by an anonymous author shared about her asylum experiences, and described it as being fun and beneficial. She said she played games and hung out with friends after receiving her treatments. The treatment given to her was insulin therapy, where patients would receive an overdose of insulin till their body went into a coma, and the idea was when they wake up from their coma their mental illness would be cured. The anonymous author did not share much about her experience with these treatments, besides that it was beneficial to her. It is important to recognise that this passage could have been written by anyone. Insulin treatment is something that has been long discontinued in today’s modern medicine, this is a drastic difference when comparing past treatments to todays. There are no unethical treatments that are commonly used today, and different kinds of therapy are now the most popular forms of treatment.

Throughout the year treatment methods have grown and developed into smart and beneficial practices. We have come a long way from unethical treatments like insulin therapy, and have learned from people like Phillipe Pinel and Aaron Beck to have evolved where we are today.

Work Cited:

Eghigian, Greg, editor. From Madness to Mental Health : Psychiatric Disorder and Its Treatment in Western Civilization. Rutgers University Press, 2010. Accessed 14 April. 2021.