Introduction
Depressive disorders (D.D.) in aging are not a usual way of life, but the prevalence rate has continually increased. This mental health problem can be solved by accessing services, medicine, and psychosocial therapy. Persons with D.D. who underwent treatment would have a better quality of life. The proportion of clients with high quality of life (QOL) increased from 28.5% to 42.5% after undergoing the treatment for one year [
1]. Moreover, patient QOL scores rose in the 2nd month after antidepressant treatment and were stable in the 6th, 12th, and 24th, respectively [
2]. However, previous studies reported that the rate of access to care in this age group was under compared to other age groups [
3‐
5]. In addition, the rate of continuing to receive mental service use is essential to improve health outcomes but still is little understood.
For adults and older persons in six low- and middle-income countries, 69.5% of patients, have not received depression treatment in one year [
6]. Across European regions in eight countries, 79% of late-life depression have received neither diagnosis nor treatment. Besides, a study in Korea found that the older persons were the lowest at receiving mental health services compared to other ages [
7]. The evidence related to mental health service use in people with depression is most likely to explore access to health care services or adherence to antidepressants; on the contrary, continuing service use has received less attention. A study revealed that the dropout rate from mental health treatment was associated with higher age, mainly older persons. More than 50% of patients first diagnosed with depression drop out of service at the first time of appointment. Also, 25 and 15% did not return to receive mental health services at the second and third appointments [
8].
Similarly, of 42% of Chinese patients with depressive disorders (mean age = 57.3, ≥ 55 years), 59% dropped out of depression treatment at the first month’s appointment, 71% dropped out by the second month, 77% at three months, 81% dropped out at six months, and 82% dropped out at 12 months [
9]. We found no study about continuing or dropout rate of mental health service use in older persons with depressive disorders in Thailand. Continuing service use implies that the client continues to take antidepressants as treatment. The evidence has strongly supported that using antidepressant treatment as a protocol recommended would be remit effectively from depressive symptoms and improve QOL [
10,
11].
Thailand’s Health policy has a strategic plan to increase the number of older people’s access to mental health services and recommends providing integrated physical and mental health services in general hospitals. A clinical practice guideline in public hospitals was provided, and trained physicians and psychiatric nurses to use the guideline 2015. The appointment for treatment of depression is at least six months after starting antidepressant drugs [
12,
13]. As a result, depressive disorders’ access to services rose from 30 to 70% from 2015 to 2020 [
14]. However, mental health service use in general hospitals has never been explored. A previous study revealed that older people have many barriers to health service utilization, both mental health service system and personal factors.
The evidence was inconclusive regarding distinguishing factors affecting mental health service usage among older persons with D.D. Various factors such as individual characteristics, social determinants, and clinical characteristics impact this service use outcome. For instance, females use mental health services more than males [
15]. Having no spouse or significant others was likely to have lower treatment depression than those with marital status [
16,
17]. Besides, comorbid conditions were negatively associated with treatment adherence [
8,
16] and mental health service use with emotional problems [
18]. Insufficient income [
19], attitude toward depression, and embarrassment [
20] were obstacles to receiving depression and negatively impacted service utilization.
In contrast, patients with a positive attitude toward depression and trust in nurses had more frequent health services [
21]. Besides, social support plays an essential role in health care service utilization [
22]. Moreover, the severity of depression was reported in both negative and positive associations with healthcare service utilization. For example, Grover, Dua, Chakrabarti, and Avasthi found that older persons with mild depression tended to drop out of the treatment at the early to intermediate stage of the treatment, and those with moderate depression were more likely to leave the medicine in the middle stage of treatment [
23].
Meanwhile, Stein et al. found that older persons with more depressive symptoms (GDS ≥ 6) had 0.144 less medication treatment time (− 0.885, 0.378) compared to those with less severity of depression (GDS4–5) [
24]. Hansen and Kristoffersen also found that severe depression of participants (30–87 years) was strongly associated with mental service use. Participants with severe depression utilized more mental services than those with moderate disease (OR 7.53, CI 2.75, 20.65) [
25].
The mental health service delivery system is associated with mental health service use. It includes organizational and provider-related factors such as hospital level, nurse competency, nurse-patient ratio, and appointment reminders. These factors are the structure and organized delivery system for patients. However, far too little attention has been paid to mental health service organizations associated with mental health service use. Most studies have only been carried out in a small number of areas. For instance, Kales et al. indicated that primary hospitals predicted antidepressant treatment adherence of older persons with depressive disorders [
16]. However, some studies have found relevance that can imply influencing factors at the hospital level and mental health services use. For instance, Germack, Bizhanova, and Roberts conducted a study with substantial hospital-level variation in remission rates among severe mental illness patients [
26]. Another study based on patient perception also mentioned hospital levels and differences in the quality of services [
27]. Similarly, providers’ performance is also helpful for improving care quality, and it was associated with mortality in a university hospital [
28].
The conceptual framework in this study is derived from the Behavioral model of health service uses (B.M.), improving in the fifth phase [
29]. The B.M. is a multilevel model that incorporates individual and contextual determinants of health services use. This model emphasizes that understanding health service use is best accomplished by focusing on contextual and individual determinants or characteristics. Unique characteristics consist of predisposing factors, enabling factors, and need. Personal characteristics can represent predisposing factors, including age, sex, and marital status. Enabling factors include sufficient income, social support, attitude toward depression, and its treatment. In addition, the need factor represents actual needs for health care services use. This study uses the diagnosis of depressive disorders as a classification according to ICD 10 and comorbidity in terms of index resource utilization [
30].
Organization at the contextual level includes the amount and distribution of health services facilities and personnel and how they are structured to offer services [
29]. In this study, organizational mental health service delivery comprises supplies of services in the hospital and the availability of service delivery that offers continuing services to older persons with D.D., including hospital-level, nurse competency, nurse-patient ratio, and appointment reminders.
Continuing mental health service use in this study means that older persons continuously attend mental health clinics by appointment and never miss a clinical appointment for depression treatment for more than 90 days. This meaning is consistent with the algorithm of D.D. management for Thai general practitioners that monitoring relapse should not leave attendance for more than three months [
12]. Previous studies have little examined variance among the organizational and Individual determinants associated with continuing mental health service use. Therefore, this study aimed to (1) explore the rate of continuing mental health service use, (2) identify groups of organizations that took part in continuing mental health service use based on service delivery and human resources, and (3) explain organizational and personal determinants affecting continuing mental health service use within six months after diagnosed D.D. in general hospital among older persons.
Results
Of the total 424 participants, of which 32.3% (
n = 137) were from the two university hospitals, 34.7% (
n = 147) were from five advanced and standard hospitals, and 33% (
n = 140) were from five community hospitals across four regions in Thailand. The demographic and clinical characteristics of the participants are shown in Tables
1 and
2.
Table 2
Clinical characteristics of the participants categorized by hospital level (n = 424)
Comorbidity |
No comorbidity | 56 | 40.9 | 63 | 42.9 | 59 | 42.1 | 178 | 42.0 |
≥ 1disease | 81 | 59.1 | 84 | 57.1 | 81 | 57.9 | 246 | 58.0 |
No. of disease |
1 disease | 32 | 23.4 | 44 | 29.9 | 37 | 26.4 | 113 | 26.7 |
2 diseases | 27 | 19.7 | 26 | 17.7 | 29 | 20.7 | 82 | 19.3 |
3 diseases | 17 | 12.4 | 11 | 7.5 | 10 | 7.1 | 38 | 9.0 |
≥ 4 diseases | 5 | 3.6 | 3 | 2.0 | 5 | 3.5 | 13 | 3.3 |
Top 10 Comorbidity |
No disease | 56 | 40.9 | 63 | 42.9 | 59 | 42.1 | 178 | 42.0 |
Hypertension | 64 | 46.7 | 63 | 42.9 | 57 | 40.7 | 184 | 43.4 |
Diabetes | 24 | 17.5 | 20 | 13.6 | 27 | 19.3 | 71 | 16.7 |
Ulcer disease | 2 | 1.5 | 11 | 7.5 | 13 | 9.3 | 26 | 6.1 |
Cerebrovascular disease | 8 | 5.8 | 10 | 6.8 | 7 | 5.0 | 25 | 5.9 |
Moderate/ severe renal disease | 7 | 5.1 | 6 | 4.1 | 12 | 8.6 | 25 | 5.9 |
Chronic pulmonary disease | 9 | 6.6 | 5 | 3.4 | 7 | 5.0 | 21 | 5.0 |
Any tumor | 17 | 12.4 | 2 | 1.4 | 1 | 0.7 | 20 | 4.7 |
Mild liver disease | 5 | 3.6 | 4 | 2.7 | 2 | 1.4 | 11 | 2.6 |
Congestive heart failure | 0 | 0.0 | 7 | 4.8 | 3 | 2.1 | 10 | 2.4 |
Take warfarin /coumadin | 5 | 3.6 | 2 | 1.4 | 3 | 2.1 | 10 | 2.4 |
Severity of depressive symptoms |
Mild depression (F32.0, F33.0) | 5 | 3.6 | 8 | 5.4 | 76 | 54.3 | 89 | 21.0 |
Moderate depression (F32.1, F34.1) | 40 | 29.2 | 31 | 21.1 | 29 | 20.7 | 100 | 23.6 |
Severity depression (F32.2, F32.3) | 48 | 35.0 | 93 | 63.3 | 6 | 4.3 | 147 | 34.7 |
NOS/F32.9, F38, F39 | 44 | 32.1 | 15 | 10.2 | 29 | 20.7 | 88 | 20.8 |
Continuation of mental health service use
According to Table
3, more than half of the participants were in continuous mental health service. University hospitals’ mental health service use had the most continuous mental health service (39.3%). Of the participants who did not have ongoing mental health services, 37.9% were participants whose mental health services use was in advanced and standard hospitals, the same amount as in community hospitals.
Table 3
The hospital-level and participant characteristics categorized by mental heal service use
Hospital level |
University hospital | 47 | 24.2 | 90 | 39.3 | 137 | 32.3 |
Advanced and standard hospital | 74 | 37.9 | 73 | 31.9 | 147 | 34.7 |
Community hospital | 74 | 37.9 | 66 | 28.8 | 140 | 33.0 |
Sex |
Male | 60 | 30.8 | 73 | 31.9 | 133 | 31.4 |
Female | 135 | 69.2 | 156 | 68.1 | 291 | 68.6 |
Age groups |
60–69 years | 115 | 59.0 | 137 | 59.8 | 252 | 59.4 |
70–79 years | 59 | 30.3 | 70 | 30.6 | 129 | 30.4 |
≥ 80 years | 21 | 10.8 | 22 | 9.6 | 43 | 10.1 |
Marital status |
Other | 89 | 45.6 | 111 | 48.5 | 200 | 47.2 |
Married | 106 | 54.4 | 118 | 51.5 | 224 | 52.8 |
Perceived income |
Insufficient | 106 | 54.4 | 102 | 44.5 | 208 | 49.1 |
Sufficiency | 89 | 45.6 | 127 | 55.5 | 216 | 50.9 |
Severity of depression |
Mild depression | 46 | 23.6 | 43 | 18.8 | 89 | 21.0 |
Moderate depression | 39 | 20.0 | 61 | 26.6 | 100 | 23.6 |
Severe depression | 68 | 34.9 | 79 | 34.5 | 147 | 34.7 |
F32.9/NOS | 42 | 21.5 | 46 | 20.1 | 88 | 20.7 |
Regarding the number of appointment attendance times within six months, Table
4 shows that only a few participants had completed attendance eight times (0.7%), and most participants only attended two times (26.4%). In addition, 13.9% of participants did not even show up for their first appointment.
Table 4
Number of times to attend by appointment within six months categorized by hospital level
0 | 14 | 10.2 | 26 | 17.7 | 19 | 13.6 | 59 | 13.9 |
1 time | 16 | 11.7 | 31 | 21.1 | 31 | 22.1 | 78 | 18.4 |
2 times | 37 | 27.0 | 36 | 24.5 | 39 | 27.9 | 112 | 26.4 |
3 times | 35 | 25.5 | 22 | 15.0 | 30 | 21.4 | 87 | 20.5 |
4 times | 21 | 15.3 | 17 | 11.6 | 16 | 11.4 | 54 | 12.7 |
5 times | 7 | 5.1 | 7 | 4.8 | 4 | 2.9 | 18 | 4.2 |
6 times | 3 | 2.2 | 5 | 3.4 | 0 | 0.0 | 8 | 1.9 |
7 times | 3 | 2.2 | 2 | 1.4 | 0 | 0.0 | 5 | 1.2 |
8 times | 1 | 0.7 | 1 | 0.7 | 1 | 0.7 | 3 | 0.7 |
Groups of mental health service delivery system
The latent class analysis analyzed each group of organizations based on the mental health service delivery system (hospital level, nurse competency, nurse-patient ratio, and appointment reminder). Table
5 shows the model fit statistics of latent class analysis for deciding the number of classes. Comparing the results obtained from the latent class analysis for the model with 2, 3, and 4 latent variables, we find that when using information criteria (AIC and BIC), the best model is the one with 3 or 4 latent classes (AIC = 2446.32, BIC = 2964.69 and AIC = 2312.34, BIC = 3004.84, respectively), as the minimal value of those criteria indicate the best fit of the model [
42]. The lower BIC and AIC values indicate a better model fit. However, the two-class solution with the highest BIC was slightly larger than the lowest BIC in the three-class solution. It was chosen as the optimal solution as it yielded classifications that were distinct and interpretable and had adequate class sizes. The two latent classes were the best in the current study for a clear interpretation of the mental health service delivery system.
Table 5
Model- fit statistics of latent class analysis models for number of classes
2 | 2917.67 | 3261.90 | 820.08 | 1239.85 |
3 | 2446.32 | 2964.69 | 262.74 | 296.12 |
4 | 2312.34 | 3004.84 | 42.75 | 29.83 |
Characteristics of groups of the mental health service delivery system
According to latent class analysis, Table
6 shows that the organization of the mental health service delivery system was divided into two classes. Class one was a high potency mental health services system resource. It included two university-level hospitals, with 77.4% of the participant in Siriraj and Ramathibodi Hospitals, and one standard and advanced hospital (26.6%), Chaophraya Yommarat Hospital. The nurses with the highest qualification in mental health clinics were 100% R.N.s combined with R.N.s + MHN/MNS. This class had a high workload, between 23.92 and 37.3, with a nurse-patient ratio of 37.5 for 40.1%, a nurse-patient ratio of 23.92 for 37.3%, and a nurse-patient ratio of 16.38 for 22.6%. In addition, the high resource system had the most successful appointment reminder system for older persons who would visit mental health services. It had due date reminders of 77.4%, with only 22.6% without reminders. The characteristics of organization group two were low potency of mental health service resources. It was 43.3% standard and advanced hospitals and 56.7% of community hospitals. However, the low resource group had higher qualifications than the high resource group. Of nurses, 61.1% consisted of RN + (RN+ PMHN), RN+ (RN + MNS/APN). Moreover, 38.9% of registered nurses had been trained to provide psychiatry nursing care.
Table 6
Organizational characteristics categorized by the group of organizations (n = 424)
Hospital level |
University hospital | 137 | 77.4 | | |
Advanced and standard hospital | 40 | 22.6 | 107 | 43.3 |
Community hospital | | | 140 | 56.7 |
Hospital name |
Chaoprayamaraj hospital | 40 | 22.6 | | |
Khonkean hospital | | | 30 | 12.2 |
Kuangnai hospital | | | 44 | 17.8 |
Lamphun hospital | | | 25 | 10.1 |
Mousamsip hospital | | | 16 | 6.5 |
Pathaluang hospital | | | 24 | 9.7 |
Rama hospital | 71 | 40.1 | | |
Sappasitiprasong hospital | | | 28 | 11.3 |
Siriraj hospital | 66 | 37.3 | | |
Srimuangmai hospital | | | 14 | 5.7 |
Tragarn hospital | | | 22 | 8.9 |
Warinchamrap hospital | | | 44 | 17.8 |
Nurse-patient ratio |
9.78 | | | 25 | 10.1 |
10.75 | | | 44 | 17.8 |
11.00 | | | 30 | 12.1 |
11.40 | | | 28 | 11.3 |
14.75 | | | 44 | 17.8 |
16.38 | 40 | 22.6 | | |
17.33 | | | 24 | 9.7 |
20.00 | | | 16 | 6.5 |
21.33 | | | 22 | 8.9 |
23.92 | 66 | 37.3 | | |
36.25 | | | 14 | 5.7 |
37.50 | 71 | 40.1 | | |
Nurse competency |
RN + PMHN | | | 96 | 38.9 |
RN + PMHN+MNS | 177 | 100.0 | | |
RN + PMHN+MNS/APN | | | 151 | 61.1 |
Appointment reminders |
No | 40 | 22.6 | 247 | 100.0 |
Yes | 137 | 77.4 | | |
The low resource class had a high workload or lower nurse-patient ratio than the high resource class. Thereby nurse-patient ratio 10.75 was 17.8%, ratio14.75 was 17.8%, ratio11.0 was 12.1% and ratio14.75 was 17.8%. In addition, the low-resource mental health service group does not have any reminder system to alert patients to mental health care services.
Table
7 shows that the older persons with depressive disorders in the high resource organization were statistically significant more continuous mental health service use (
n = 112, 63.3%) than low resource organization (
n = 117, 47.4%) with a
p-value of 0.001.
Table 7
Continuous mental health service use of participants within six months categorized by group of organization (n = 424)
Mental health service use | | | | | 0.001 |
Not-continuing | 65 | 36.7 | 130 | 52.6 | |
Continuing | 112 | 63.3 | 117 | 47.4 | |
Organizational and individual determinants affecting continuing mental health service use
According to Table
8, logistic models run sequentially to assess mental health service use prediction over six months. Within six months, individual characteristics were significantly associated with mental health service use by the organizational group. When an organized group was added to the univariate model, the organized group was significantly related to mental health services. The high resource organization had 1.9 times increase in odds of mental health service use (unadjusted Log OR 0.637,
p-value = 0.007; 95% CI: 0.171, 1.103) compared with the low resource organization. In the multivariable model, the high resource organization remained significantly associated with mental health service use after adjustment for other individual characteristics (adjusted Log OR 0.511,
p-value = 0.046; 95% CI: 0.009, 1.014) versus the low resource organization.
Table 8
Factors associated with mental health service use within six months in older persons with depressive disorders (n = 412)
Organization group |
Low resource | Reference | | | | Reference | | | |
High resource | 0.637 | 0.238 | (0.171, 1.103) | 0.007 | 0.511 | 0.256 | (0.009, 1.014) | 0.046 |
Age (years) | −0.12 | 0.013 | (−0.038, 0.013) | 0.333 | | | | |
Sex |
Female | Reference | | | | | | | |
Male | 0.098 | 0.149 | (−0.194, 0.391) | 0.510 | | | | |
Marital status |
Other | Reference | | | | | | | |
Married | −0.056 | 0.188 | (−0.425, 0.313) | 0.765 | | | | |
Perceived income |
Insufficient | Reference | | | | Reference | | | |
Sufficient | 0.337 | 0.143 | (0.057, 0.617) | 0.018 | 0.310 | 0.161 | (−0.005, 0.626) | 0.054 |
ATDS | 0.021 | 0.007 | (0.007, 0.035) | 0.003 | 0.021 | 0.007 | (0.007, 0.035) | 0.003 |
MSPSS | 0.008 | 0.006 | (−0.004, 0.020) | 0.184 | | | | |
CCI | 0.025 | 0.036 | (−0.045, 0.096) | 0.482 | | | | |
Severity of depression |
Mild | Reference | | | | | | | |
Moderate | 0.299 | 0.326 | (−0.340, 0.938) | 0.359 | | | | |
Severe | 0.108 | 0.270 | (− 0.421, 0.638) | 0.688 | | | | |
F32.9/NOS | −0.299 | 0.283 | (−0.854, 0.256) | 0.291 | | | | |
Regarding individual characteristics, perceived sufficiency income was only associated with mental health service use in the univariate model (unadjusted Log OR 0.337; 95% CI: 0.057, 0.617) versus insufficient income. ATDS was significantly associated with mental health service use within six months. In the univariate (unadjusted Log OR 0.021; 95%CI: 0.007, 0.035) and multivariable model, after adjustment for other individual characteristics and organizational groups, ATDS remained significantly associated with mental health service use within six months (adjusted Log OR 0.021, p-value = 0.003; 95%CI: 0.007, 0.035).
Discussion
The present study is the first study to clarify the predictive power of the mental health service delivery system and individual determinants on continuing mental health services use among older persons with D.D. Regarding mental health service use of the older persons with D.D. in the last six months after diagnosis of D.D., the dropout rate at the first appointment was 13.9%. Dropout was less than in a previous study of older Indian persons with D.D. when 41.4% (58/140 persons) never returned after first attending psychiatry outpatient facilities of a tertiary hospital [
23]. The current study had a range of dropouts depending on the type of hospital facility., The dropout rate ranged from 10.2 to 17.7%, with the lowest rate in university hospitals and the highest rate in advanced and standard hospitals comparable to tertiary hospitals in India. The advanced and standard hospitals are the referral hospitals from the community hospital. The possible reason for appointment non-attendance may be transportation and time constraints.
In contrast, the causes for early dropout of Indian older persons were “no relief” of symptoms, closely followed by complete relief of symptoms [
23]. In addition, the rate of not attending mental health clinics at least 90 days consecutively out of six months after diagnosis in this study was 46%. The highest rate was in the advance and stardard hospital and community hospital (37.9%). The dropout rate among Indian older persons was 23.6% after three months and 8.6% between three and six months. These findings show different appointment attending behaviors in older persons of two cultures, with Indian older persons likely to drop out in earlier scheduled appointments and Thai older persons to drop out later. The reasons for non-attendance in the current study were attitudes toward depression and its treatment, insufficient income, and factors related to organizational resources for delivery services.
The characteristic of organizations affected continuing mental health service use. Older persons were more likely to continue appointment attendance at the high resource organizations (63.3%) than the low resource organizations (47.4%). It is possible that high-resource organizations (with highly qualified nurses, multidisciplinary professionals, more choices of antidepressant drugs, and psychosocial therapies) can provide services that better meet the need of mental health service users. Previous studies have reported that mental health service users prioritize access, information, peer support, service avoidance, and day centers as continuing care elements [
43]. Furthermore, service users avoided service use because they did not realize they needed support or feared the loss of choice and control. Some avoidance service users had developed their strategies for living and no longer wanted or needed services [
43].
After adjusting for all other determinants, the determinants affecting continuing mental health service use among older persons with D.D. were high resource organizations and ATDS. The two determinants are modifiable factors associated with depression treatment adherence among older persons [
44]. The finding reinforces a prior study [
45] that the availability of specialized mental health services such as combined therapy and psycho-pharmacotherapy assists in retaining depression treatment among ethnic and racial minorities in the United States. Also, it is consistent with findings of a previous study that medical facilities were associated with a four-month adherence among older persons with D.D [
16]. Furthermore, older persons who received a prescription in primary care were significantly more likely to be non-attendance than those who received service in psychiatric hospitals [
16]. According to ATDS, in this study, the ATDS in the older persons tended to be high, including acceptance of treatment, perceived stigma and shame, negative to antidepressants, self-stigma, and preferred psychotherapy. In this study, the ATDS in older Thai persons was consistent with prior research revealing that older Americans had positive help-seeking attitudes or positive beliefs about the efficacy of treatment for mental health problems [
46]. The older persons with a better attitude toward depression and its cure had a significantly higher mental health service use than those with less ATDS. The result supports Kohls et al. [
47] finding that people in countries with depression awareness campaigns on personal stigma, perceived stigma, openness to help, and perceived value of help reported more willingness to seek professional help than respondents unaware of it. This study demonstrated that the mechanism of organization groups was a variable influence on the individual characteristics. This principle underpins the Behavioral Model of health service uses (B.M.), improving in the fifth phase [
29] that applies organization groups as the contextual characteristics. This study emphasized only organization groups and ATDS promoting mental health services use. Therefore, as discussed above, this study demonstrated the mechanism and evidence of the Behavior model of health services for investigating factors predicting mental health service use among older persons with depressive disorders. This finding contributes to discussing modifying resources of organization and ATDS among policymakers to improve appointment attendance among older persons with D.D.
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