Community Ment Health J DOI 10.1007/s10597-014-9702-2
ORIGINAL PAPER
Predictors of Consumer Satisfaction in Community Mental Health Center Services Minji Sohn • Hope Barrett • Jeffery Talbert
Received: 12 September 2012 / Accepted: 20 January 2014 Ó Springer Science+Business Media New York 2014
Abstract Kentucky Department for Behavioral Health Developmental and Intellectual Disabilities conducted a survey to evaluate consumers’ satisfaction with services delivered at the Community Mental Health Centers (CMHCs) in Kentucky. The survey was administered at outpatient clinics operated by fourteen CMHCs in 2010. The purpose of this study was to identify factors that predict whether clients will respond that they were ‘‘generally satisfied’’ with services received from CMHCs. A logistic regression model was developed using respondents’ characteristics and their responses to survey questions. Survey questions were grouped into seven core domains: general satisfaction, access, quality, participation in treatment planning, outcomes, functioning, and social connectedness. In result, responses to domains of access, quality and participation in treatment planning significantly affected clients’ perception of general satisfaction. Respondents who positively assessed those domains of services were more likely to answer that they were generally satisfied with services. Based on the analysis in this report, improvement in certain domains of services, especially access, quality and participation in treatment planning could increase the level of positive responses in general satisfaction.
M. Sohn (&) J. Talbert College of Pharmacy, University of Kentucky, 789 South Limestone Street, Lexington, KY 40536-0596, USA e-mail: [email protected] H. Barrett Kentucky Department for Behavioral Health Developmental Intellectual Disabilities, Kentucky Cabinet for Health and Family Services, 100 Fair Oaks Lane 4E-A, Frankfort, KY 40601, USA
Keywords Community Mental Health Centers (CMHCs) Satisfaction Access Quality Participation in treatment planning
Introduction In 2010, the Kentucky Cabinet for Health and Family Services, Department for Behavioral Health Developmental and Intellectual Disabilities (BHDID) conducted a survey to evaluate consumers’ satisfaction with services delivered at the Community Mental Health Centers (CMHCs) in Kentucky. The survey was developed by the Mental Health Statistics Improvement Program (MHSIP) Advisory Committee of the Center for Mental Health Services (CMHS) and was designed to assess the clients’ perspectives on public mental health services they have received (Leginski et al. 1989; Carlson et al. 2010; Minsky and Lloyd 1996; Jerrell 2006; Ganju 1999; Ganju et al. 1996). The purpose of this study was to scrutinize factors that affect clients’ perception of ‘‘general satisfaction’’. Do people positively respond as ‘‘generally satisfied’’ when the treatment outcomes are improved, or when they meet doctors quickly and conveniently without waiting in a long line? This study attempts to answer the question by analyzing the relative association of general satisfaction with responses to other survey questions. More specifically, the survey asked about several aspects of services received, such as general satisfaction, access, quality, participation in treatment planning, outcomes, functioning and social connectedness. Also, patients’ characteristics such as gender, race and birth date were obtained in the survey. Because the analysis was performed only using survey responses, findings in this report may not reflect all of the factors
123
Community Ment Health J Table 1 Primary concerns related to domain
Table 2 Adult survey respondents’ characteristics
Domain
Primary concerns related to domain
Age of adult respondents
Race of adult respondents
General satisfaction
Services were, overall, satisfactory and preferable to other choices (e.g., I like the services that I receive here. I would recommend this agency to a friend or family member)
Gender of adult respondents
18–30
24 %
Male
40 %
American Indian/Alaska Native
Access
Quality/ appropriateness
Participation in treatment Planning
31–40
25 %
Female
60 %
Native Hawaiian
0.1 %
Staff availability, the range of service options and how quickly and conveniently services were received (e.g., Staff returned my call in 24 h. Services were available at times that were good for me)
41–50
25 %
Total
6,346
Asian
0.3 %
51–60
19 %
White (Caucasian)
90 %
61–70
6%
Black (African– American)
7%
Cultural and linguistic access and whether services promoted recovery and continuity of care (e.g., Staff was sensitive to my cultural background. I was given information about my rights. Staff told me what side effects to what out for) Clients’ participation in planning services (e.g., I, not staff, decided treatment goals)
71–80
1%
Other
1%
C81
0.2 %
Total
6,222
Total
5,251
Outcomes
Services provided patients with positive changes in areas for which treatment was sought and minimal negative outcomes (e.g., I deal more effectively with daily problems. I am better able to control my life)
Social connectedness
Services contributed to improving natural supports, which come from family or friends (e.g., I have people with whom I can do enjoyable things. I am happy with the friendships I have.)
Functioning
There was a positive effect on independent community living and decreasing distress caused by symptoms (e.g., I am better able to do things that I want to do. I am better able to handle things when they go wrong)
influencing general satisfaction. Also, the survey was administered only to participants visiting a CMHC. Therefore, clients who are no longer receiving services are not included in the report, implying that the analysis might draw different conclusion otherwise.
Methods The survey was administered at outpatient clinics operated by fourteen CMHCs in Kentucky. During a 2 weeks period each spring, the CMHC staff made the survey available to clients who arrived for outpatient appointments. Completing the survey was voluntary and had no implications for appointments or services provided. The surveys had seven core domains and each set of related questions asked about a specific aspect of services provided. (Table 1) For each question, possible responses were arrayed on a five point scale that ranges from
123
2%
‘‘strongly agree’’ to ‘‘strongly disagree’’. For example, for a question, ‘‘I felt free to complain’’, respondents were able to choose one answer out of six choices: strongly agree, agree, neutral, disagree, strongly disagree and don’t know/ not applicable. The responses of ‘‘agree’’ and ‘‘strongly agree’’ were considered as positive responses. In the analysis, responses of ‘‘don’t know/not applicable’’ were treated as missing values and not included in calculating percent responses of each question. Also, surveys with more than 1/3 of the items in the scale missing were excluded from the result of that scale. A logistic regression model was developed to predict general satisfaction. Patient demographics (age, sex, race) and region of residence (urban, rural), and the responses to other domains of the survey were included as explanatory variables.
Results During the fiscal year 2010 (July 1, 2009–June 30, 2010), 117,526 adult patients visited Kentucky CMHCs and 7,029 of them participated in the survey, resulting in a 5.98 % penetration rate. Table 2 shows the demographic characteristics of survey respondents. Approximately 74 % of respondents were age 18–50, with the mean of 41.2. For race, a high proportion of respondents were white (90 %). This could be explained by a high rate of white residents in Kentucky. In fact, this observation is consistent with the 2010 US Census Bureau data showing that Kentucky consists of over 87 % of white residents (US Census Bureau 2010). Approximately 92 % of participants responded positively on the domain of general satisfaction. (Figure 1) It was the second highest following to the domain of quality where 94 % responded positively. The domains of access,
% Positive Response
Community Ment Health J 100 90 80 70 60 50 40 30 20 10 0
92%
89%
94% 82%
74%
73%
73%
Fig. 1 Percent positive response by domain
Table 3 Logistic regression predicting general satisfaction General satisfaction
Odds ratio
P value
11.65*
\0.001
\Domain[ Access Outcomes
1.75
0.120
Functioning
1.27
0.521
Participation in treatment planning Quality Social connectedness
2.69*
0.001
14.41* 1.75
\0.001 0.050
\Region of residence[
participation in treatment planning, outcomes, social connectedness, and functioning showed the relatively lower level of positively response compared to general satisfaction. Especially, outcomes and functioning were the lowest (73 %). Next, we used a multivariable logistic regression to predict general satisfaction using respondents’ characteristics and survey responses to other domains.(Table 3) In result, females were more likely to respond positively on general satisfaction (odds ratio: 1.55). Compared to white, American Indian were less likely to answer positively on general satisfaction (odds ratio: 0.2). Age and regional characteristics (rural/urban) were not significantly related with general satisfaction. Among domains, the access and the quality showed considerably high odds ratios, indicating their large impact on general satisfaction (odd ratio: 11.65 for access, 14.41 for quality). In other words, if one is satisfied with the service with respect to the access, then the likelihood for the person to perceive general satisfaction positively increases significantly. In addition to the access and quality, participation in treatment planning was shown to affect one’s perception of general satisfaction (odds ratio: 2.69).
Discussion
Urban (reference) Rural
0.88
0.851
Black
1.41
0.470
American Indian
0.21*
\Race[ White (reference) 0.003 à
Asian
Dropped
Hawaiian/Pacific Islander
Droppedà
Other races
0.68
0.646
1.55*
0.041
0.83
0.497
Age 41–50
1.09
0.761
Age 51–60
1.26
0.532
Age 61–70
0.85
0.781
Age 71–80
0.18
0.112
\Sex[ Male (reference) Female \Age[ Age 18–30 Age 31–40 (reference)
Age [81
Droppedà
* Odds ratio is significant at 95 % confidence level à
These variables are dropped from logistic regression model because maximum likelihood estimation is impossible. That is, whenever X = 1, Y = 1. This is probably because of small number of observation of the explanatory variable (Wooldridge 2005)
The purpose of this study was to identify factors predicting general satisfaction in community mental health center services. Our analysis showed that the domains of access, quality and participation in treatment planning were significantly associated with general satisfaction. Previous studies that examined predictors of patient satisfaction reported similar findings. Jackson et al. (2001) examined predictors of patient satisfaction in adults from a general medicine walk-in clinic and found that patient-doctor communication was one of the important predictors of patient satisfaction. Sorlie et al. (2000) also observed a significant association between the patient-doctor communication and patient satisfaction in their study. This is consistent with our findings in which the domains of quality and participation in treatment planning were significant predictors of general satisfaction. More specifically, the domain of quality included questions about whether the patient was educated with their treatment and whether the staff respected the patient’s wishes about who is and who is not to be given information about their treatment. The domain of participation in treatment planning asked whether the patient played a central role in deciding treatment goals. We believe that these findings are clinically meaningful as the current health care provision is
123
Community Ment Health J
moving towards the patient-centered care in which the patient actively involves in their treatment process. Understanding predictors of general satisfaction is important because patient satisfaction has a substantial impact on treatment compliance (Kane et al. 1997; Mitchell and Selmes 2007a). Having good compliance is essential for patients with chronic conditions, as it leads to better health outcomes. However, it has been shown that those with mental illness have particularly high drop-out rates during the course of treatments, reflecting poor engagement with their treatments (Mitchell and Selmes 2007b). This is further linked to increased risk of relapse and hospital readmissions (Novick et al. 2010). Therefore, much attention is needed for improving patient satisfaction in mental health care. We believe that the findings of this study provide useful insights about what factors affect general satisfaction in mental health care services. Some limitations should be noted when the findings of this study are implemented. First, the samples selected in this paper may not be a good representative of a general population. For example, our study sample consisted of a high proportion of white respondents. Although it was the nature of the state where the survey was conducted, it is certainly not the case in other states such as California or New York. Therefore, one should be cautious when applying the findings of this paper to a population with different demographic characteristics. Second, our sampling method could threat the validity of conclusions. We used a convenient sampling method in which the subjects were selected based on their convenient accessibility rather than probability. Considering that our samples were selected when they visited a CMHC, those who were dissatisfied and refused to visit a CMHC would have been excluded. This could have a substantial impact on the implication of our findings if the way of perceiving general satisfaction is inherently different between CMHC visitors and those who refuse to receive services from a CMHC.
Conclusion The purpose of this report was to identify the factors that predict ‘‘general satisfaction’’ with mental health services in Kentucky CMHCs. Our analysis showed that responses to general satisfaction were more associated with the domains of access, quality, and participation in treatment planning. We suggest that paying more attention to those
123
domains of service could positively influence mental health care clients’ perception of general satisfaction.
References Carlson, J. A., Sarkin, A. J., Levack, A. E., Sklar, M., Tally, S. R., Gilmer, T. P., et al. (2010) Evaluating a measure of social health derived from two mental health recovery measure: The California Qualtiy of Life (CA-QOL) and Mental Health Statistics Improvement Program consumer survey (MHSIP). Community Mental Health Journal, 47(4), 454–462. Ganju, V. (1999). The MHSIP consumer survey. Arlington, VA: National Association of State Mental Health Program Directors Research Institute. Ganju, V., Beall, M. A., Callahan, N., Dailey, W., Dumont, J., Homik, J. A., et al. (1996). The MHSIP consumer-oriented mental health report card. Washington, DC: Center for Mental Health Services (SAMHSA, DHHS). Jackson, J. L., Chamberlin, J., & Kroenke, K. (2001). Predictors of patient satisfaction. Social Science Medicine, 52(4), 609–620. Jerrell, J. M. (2006). Psychometrics of the MHSIP adult consumer survey. Journal of Behavioral Health Services and Research, 33(4), 483–488. Kane, R. L., MacIejewski, M., & Finch, M. (1997). The relationship of patient satisfaction with care and clinical outcomes. Medical Care, 35(7), 714–730. Leginski, W. A., Croze, C., Driggers, J., Dumpman, S., Geertsen, D., Kamis-Gould, E., et al. (1989). Data standards for mental health decision support systems. Series FN No. 10. DHHS Pub. No. (ADM) 89-1589. Washington, DC: National Institute of Mental Health. Minsky, S., & Lloyd, P. (1996). The use of unique client identifiers in state mental health service systems. Administration and Policy in Mental Health Services Research, 23(3), 231–252. Mitchell, A. J., & Selmes, T. (2007a). Why don’t patients attend their appointments? Maintaining engagement with psychiatric services. Advances in Psychiatric Treatment, 13, 423–434. Mitchell, A. J., & Selmes, T. (2007b). A comparative survey of missed initial and follow-up appointments to psychiatric specialties in the United Kingdom. Psychiatric Services, 58(6), 868–871. Novick, D., Haro, J. M., Suarez, D., Perez, V., Dittmann, R. W., & Haddad, P. M. (2010). Predictors and clinical consequences of non-adherence with antipsychotic medication in the outpatient treatment of schizophrenia. Psychiatry Research, 176(2), 109–113. Sorlie, T., Sexton, H. C., Busund, R., & Sorlie, D. (2000) Predictors of satisfaction with surgical treatment. International Journal for Quality in Health Care, 12(1), 31–40. US Census Bureau. (2010). American factfinder: Profile of general population and housing characteristics. Retrieved 7 January 2014 from http://factfinder2.census.gov/faces/tableservices/jsf/ pages/productview.xhtml?pid=DEC_10_DP_DPDP1. Wooldridge, J. (2005). Introductory econometrics: A modern approach, South-Western. Third edition.
ORIGINAL PAPER
Predictors of Consumer Satisfaction in Community Mental Health Center Services Minji Sohn • Hope Barrett • Jeffery Talbert
Received: 12 September 2012 / Accepted: 20 January 2014 Ó Springer Science+Business Media New York 2014
Abstract Kentucky Department for Behavioral Health Developmental and Intellectual Disabilities conducted a survey to evaluate consumers’ satisfaction with services delivered at the Community Mental Health Centers (CMHCs) in Kentucky. The survey was administered at outpatient clinics operated by fourteen CMHCs in 2010. The purpose of this study was to identify factors that predict whether clients will respond that they were ‘‘generally satisfied’’ with services received from CMHCs. A logistic regression model was developed using respondents’ characteristics and their responses to survey questions. Survey questions were grouped into seven core domains: general satisfaction, access, quality, participation in treatment planning, outcomes, functioning, and social connectedness. In result, responses to domains of access, quality and participation in treatment planning significantly affected clients’ perception of general satisfaction. Respondents who positively assessed those domains of services were more likely to answer that they were generally satisfied with services. Based on the analysis in this report, improvement in certain domains of services, especially access, quality and participation in treatment planning could increase the level of positive responses in general satisfaction.
M. Sohn (&) J. Talbert College of Pharmacy, University of Kentucky, 789 South Limestone Street, Lexington, KY 40536-0596, USA e-mail: [email protected] H. Barrett Kentucky Department for Behavioral Health Developmental Intellectual Disabilities, Kentucky Cabinet for Health and Family Services, 100 Fair Oaks Lane 4E-A, Frankfort, KY 40601, USA
Keywords Community Mental Health Centers (CMHCs) Satisfaction Access Quality Participation in treatment planning
Introduction In 2010, the Kentucky Cabinet for Health and Family Services, Department for Behavioral Health Developmental and Intellectual Disabilities (BHDID) conducted a survey to evaluate consumers’ satisfaction with services delivered at the Community Mental Health Centers (CMHCs) in Kentucky. The survey was developed by the Mental Health Statistics Improvement Program (MHSIP) Advisory Committee of the Center for Mental Health Services (CMHS) and was designed to assess the clients’ perspectives on public mental health services they have received (Leginski et al. 1989; Carlson et al. 2010; Minsky and Lloyd 1996; Jerrell 2006; Ganju 1999; Ganju et al. 1996). The purpose of this study was to scrutinize factors that affect clients’ perception of ‘‘general satisfaction’’. Do people positively respond as ‘‘generally satisfied’’ when the treatment outcomes are improved, or when they meet doctors quickly and conveniently without waiting in a long line? This study attempts to answer the question by analyzing the relative association of general satisfaction with responses to other survey questions. More specifically, the survey asked about several aspects of services received, such as general satisfaction, access, quality, participation in treatment planning, outcomes, functioning and social connectedness. Also, patients’ characteristics such as gender, race and birth date were obtained in the survey. Because the analysis was performed only using survey responses, findings in this report may not reflect all of the factors
123
Community Ment Health J Table 1 Primary concerns related to domain
Table 2 Adult survey respondents’ characteristics
Domain
Primary concerns related to domain
Age of adult respondents
Race of adult respondents
General satisfaction
Services were, overall, satisfactory and preferable to other choices (e.g., I like the services that I receive here. I would recommend this agency to a friend or family member)
Gender of adult respondents
18–30
24 %
Male
40 %
American Indian/Alaska Native
Access
Quality/ appropriateness
Participation in treatment Planning
31–40
25 %
Female
60 %
Native Hawaiian
0.1 %
Staff availability, the range of service options and how quickly and conveniently services were received (e.g., Staff returned my call in 24 h. Services were available at times that were good for me)
41–50
25 %
Total
6,346
Asian
0.3 %
51–60
19 %
White (Caucasian)
90 %
61–70
6%
Black (African– American)
7%
Cultural and linguistic access and whether services promoted recovery and continuity of care (e.g., Staff was sensitive to my cultural background. I was given information about my rights. Staff told me what side effects to what out for) Clients’ participation in planning services (e.g., I, not staff, decided treatment goals)
71–80
1%
Other
1%
C81
0.2 %
Total
6,222
Total
5,251
Outcomes
Services provided patients with positive changes in areas for which treatment was sought and minimal negative outcomes (e.g., I deal more effectively with daily problems. I am better able to control my life)
Social connectedness
Services contributed to improving natural supports, which come from family or friends (e.g., I have people with whom I can do enjoyable things. I am happy with the friendships I have.)
Functioning
There was a positive effect on independent community living and decreasing distress caused by symptoms (e.g., I am better able to do things that I want to do. I am better able to handle things when they go wrong)
influencing general satisfaction. Also, the survey was administered only to participants visiting a CMHC. Therefore, clients who are no longer receiving services are not included in the report, implying that the analysis might draw different conclusion otherwise.
Methods The survey was administered at outpatient clinics operated by fourteen CMHCs in Kentucky. During a 2 weeks period each spring, the CMHC staff made the survey available to clients who arrived for outpatient appointments. Completing the survey was voluntary and had no implications for appointments or services provided. The surveys had seven core domains and each set of related questions asked about a specific aspect of services provided. (Table 1) For each question, possible responses were arrayed on a five point scale that ranges from
123
2%
‘‘strongly agree’’ to ‘‘strongly disagree’’. For example, for a question, ‘‘I felt free to complain’’, respondents were able to choose one answer out of six choices: strongly agree, agree, neutral, disagree, strongly disagree and don’t know/ not applicable. The responses of ‘‘agree’’ and ‘‘strongly agree’’ were considered as positive responses. In the analysis, responses of ‘‘don’t know/not applicable’’ were treated as missing values and not included in calculating percent responses of each question. Also, surveys with more than 1/3 of the items in the scale missing were excluded from the result of that scale. A logistic regression model was developed to predict general satisfaction. Patient demographics (age, sex, race) and region of residence (urban, rural), and the responses to other domains of the survey were included as explanatory variables.
Results During the fiscal year 2010 (July 1, 2009–June 30, 2010), 117,526 adult patients visited Kentucky CMHCs and 7,029 of them participated in the survey, resulting in a 5.98 % penetration rate. Table 2 shows the demographic characteristics of survey respondents. Approximately 74 % of respondents were age 18–50, with the mean of 41.2. For race, a high proportion of respondents were white (90 %). This could be explained by a high rate of white residents in Kentucky. In fact, this observation is consistent with the 2010 US Census Bureau data showing that Kentucky consists of over 87 % of white residents (US Census Bureau 2010). Approximately 92 % of participants responded positively on the domain of general satisfaction. (Figure 1) It was the second highest following to the domain of quality where 94 % responded positively. The domains of access,
% Positive Response
Community Ment Health J 100 90 80 70 60 50 40 30 20 10 0
92%
89%
94% 82%
74%
73%
73%
Fig. 1 Percent positive response by domain
Table 3 Logistic regression predicting general satisfaction General satisfaction
Odds ratio
P value
11.65*
\0.001
\Domain[ Access Outcomes
1.75
0.120
Functioning
1.27
0.521
Participation in treatment planning Quality Social connectedness
2.69*
0.001
14.41* 1.75
\0.001 0.050
\Region of residence[
participation in treatment planning, outcomes, social connectedness, and functioning showed the relatively lower level of positively response compared to general satisfaction. Especially, outcomes and functioning were the lowest (73 %). Next, we used a multivariable logistic regression to predict general satisfaction using respondents’ characteristics and survey responses to other domains.(Table 3) In result, females were more likely to respond positively on general satisfaction (odds ratio: 1.55). Compared to white, American Indian were less likely to answer positively on general satisfaction (odds ratio: 0.2). Age and regional characteristics (rural/urban) were not significantly related with general satisfaction. Among domains, the access and the quality showed considerably high odds ratios, indicating their large impact on general satisfaction (odd ratio: 11.65 for access, 14.41 for quality). In other words, if one is satisfied with the service with respect to the access, then the likelihood for the person to perceive general satisfaction positively increases significantly. In addition to the access and quality, participation in treatment planning was shown to affect one’s perception of general satisfaction (odds ratio: 2.69).
Discussion
Urban (reference) Rural
0.88
0.851
Black
1.41
0.470
American Indian
0.21*
\Race[ White (reference) 0.003 à
Asian
Dropped
Hawaiian/Pacific Islander
Droppedà
Other races
0.68
0.646
1.55*
0.041
0.83
0.497
Age 41–50
1.09
0.761
Age 51–60
1.26
0.532
Age 61–70
0.85
0.781
Age 71–80
0.18
0.112
\Sex[ Male (reference) Female \Age[ Age 18–30 Age 31–40 (reference)
Age [81
Droppedà
* Odds ratio is significant at 95 % confidence level à
These variables are dropped from logistic regression model because maximum likelihood estimation is impossible. That is, whenever X = 1, Y = 1. This is probably because of small number of observation of the explanatory variable (Wooldridge 2005)
The purpose of this study was to identify factors predicting general satisfaction in community mental health center services. Our analysis showed that the domains of access, quality and participation in treatment planning were significantly associated with general satisfaction. Previous studies that examined predictors of patient satisfaction reported similar findings. Jackson et al. (2001) examined predictors of patient satisfaction in adults from a general medicine walk-in clinic and found that patient-doctor communication was one of the important predictors of patient satisfaction. Sorlie et al. (2000) also observed a significant association between the patient-doctor communication and patient satisfaction in their study. This is consistent with our findings in which the domains of quality and participation in treatment planning were significant predictors of general satisfaction. More specifically, the domain of quality included questions about whether the patient was educated with their treatment and whether the staff respected the patient’s wishes about who is and who is not to be given information about their treatment. The domain of participation in treatment planning asked whether the patient played a central role in deciding treatment goals. We believe that these findings are clinically meaningful as the current health care provision is
123
Community Ment Health J
moving towards the patient-centered care in which the patient actively involves in their treatment process. Understanding predictors of general satisfaction is important because patient satisfaction has a substantial impact on treatment compliance (Kane et al. 1997; Mitchell and Selmes 2007a). Having good compliance is essential for patients with chronic conditions, as it leads to better health outcomes. However, it has been shown that those with mental illness have particularly high drop-out rates during the course of treatments, reflecting poor engagement with their treatments (Mitchell and Selmes 2007b). This is further linked to increased risk of relapse and hospital readmissions (Novick et al. 2010). Therefore, much attention is needed for improving patient satisfaction in mental health care. We believe that the findings of this study provide useful insights about what factors affect general satisfaction in mental health care services. Some limitations should be noted when the findings of this study are implemented. First, the samples selected in this paper may not be a good representative of a general population. For example, our study sample consisted of a high proportion of white respondents. Although it was the nature of the state where the survey was conducted, it is certainly not the case in other states such as California or New York. Therefore, one should be cautious when applying the findings of this paper to a population with different demographic characteristics. Second, our sampling method could threat the validity of conclusions. We used a convenient sampling method in which the subjects were selected based on their convenient accessibility rather than probability. Considering that our samples were selected when they visited a CMHC, those who were dissatisfied and refused to visit a CMHC would have been excluded. This could have a substantial impact on the implication of our findings if the way of perceiving general satisfaction is inherently different between CMHC visitors and those who refuse to receive services from a CMHC.
Conclusion The purpose of this report was to identify the factors that predict ‘‘general satisfaction’’ with mental health services in Kentucky CMHCs. Our analysis showed that responses to general satisfaction were more associated with the domains of access, quality, and participation in treatment planning. We suggest that paying more attention to those
123
domains of service could positively influence mental health care clients’ perception of general satisfaction.
References Carlson, J. A., Sarkin, A. J., Levack, A. E., Sklar, M., Tally, S. R., Gilmer, T. P., et al. (2010) Evaluating a measure of social health derived from two mental health recovery measure: The California Qualtiy of Life (CA-QOL) and Mental Health Statistics Improvement Program consumer survey (MHSIP). Community Mental Health Journal, 47(4), 454–462. Ganju, V. (1999). The MHSIP consumer survey. Arlington, VA: National Association of State Mental Health Program Directors Research Institute. Ganju, V., Beall, M. A., Callahan, N., Dailey, W., Dumont, J., Homik, J. A., et al. (1996). The MHSIP consumer-oriented mental health report card. Washington, DC: Center for Mental Health Services (SAMHSA, DHHS). Jackson, J. L., Chamberlin, J., & Kroenke, K. (2001). Predictors of patient satisfaction. Social Science Medicine, 52(4), 609–620. Jerrell, J. M. (2006). Psychometrics of the MHSIP adult consumer survey. Journal of Behavioral Health Services and Research, 33(4), 483–488. Kane, R. L., MacIejewski, M., & Finch, M. (1997). The relationship of patient satisfaction with care and clinical outcomes. Medical Care, 35(7), 714–730. Leginski, W. A., Croze, C., Driggers, J., Dumpman, S., Geertsen, D., Kamis-Gould, E., et al. (1989). Data standards for mental health decision support systems. Series FN No. 10. DHHS Pub. No. (ADM) 89-1589. Washington, DC: National Institute of Mental Health. Minsky, S., & Lloyd, P. (1996). The use of unique client identifiers in state mental health service systems. Administration and Policy in Mental Health Services Research, 23(3), 231–252. Mitchell, A. J., & Selmes, T. (2007a). Why don’t patients attend their appointments? Maintaining engagement with psychiatric services. Advances in Psychiatric Treatment, 13, 423–434. Mitchell, A. J., & Selmes, T. (2007b). A comparative survey of missed initial and follow-up appointments to psychiatric specialties in the United Kingdom. Psychiatric Services, 58(6), 868–871. Novick, D., Haro, J. M., Suarez, D., Perez, V., Dittmann, R. W., & Haddad, P. M. (2010). Predictors and clinical consequences of non-adherence with antipsychotic medication in the outpatient treatment of schizophrenia. Psychiatry Research, 176(2), 109–113. Sorlie, T., Sexton, H. C., Busund, R., & Sorlie, D. (2000) Predictors of satisfaction with surgical treatment. International Journal for Quality in Health Care, 12(1), 31–40. US Census Bureau. (2010). American factfinder: Profile of general population and housing characteristics. Retrieved 7 January 2014 from http://factfinder2.census.gov/faces/tableservices/jsf/ pages/productview.xhtml?pid=DEC_10_DP_DPDP1. Wooldridge, J. (2005). Introductory econometrics: A modern approach, South-Western. Third edition.
