Nonpsychiatric Medications Research Articles

Antipsychotic medications and severe sepsis in schizophrenia: A nested case–control study

Background: Sepsis constitutes a condition that involves life-threatening organ dysfunction induced by severe infection. This nested case–control study investigated risk factors for severe sepsis and whether antipsychotic use is associated with severe sepsis risk in patients with schizophrenia, a topic that has not been comprehensively explored in previous studies. Methods: We selected 39,432 patients with schizophrenia aged between 15 and 65 years from Taiwan’s Psychiatric Inpatient Medical Claims database for the period 2000–2012. The case group comprised patients with severe sepsis after their first psychiatric admission ( n = 1382). The case and control groups were randomly matched (1:4) by age, sex and first psychiatric admission (year) and finally comprised 1382 and 5528 individuals, respectively. We employed multivariable conditional logistic regression to identify (1) risk factors (physical illnesses and nonpsychiatric medications) and (2) antipsychotic–severe sepsis associations. Results: Higher numbers of psychiatric admissions and physical illnesses such as delirium, cerebrovascular disease and cancer were significantly associated with a higher risk of severe sepsis. Furthermore, severe sepsis was associated with the use of antithrombotic agents, systemic corticosteroids and agents targeting the renin–angiotensin system. Clozapine (adjusted risk ratio = 1.65) and quetiapine (adjusted risk ratio = 1.59) use were associated with an increased risk of severe sepsis. The use of more than one antipsychotic drug could further increase this risk. Conclusion: Several physical illnesses and nonpsychiatric medications increase the risk of severe sepsis in patients with schizophrenia. Specifically, clozapine or quetiapine use significantly increased the risk of severe sepsis in these patients.

Documentation of results and medication prescribing after combinatorial psychiatric pharmacogenetic testing: A case for discrete results

PurposeCombinatorial pharmacogenetic (PGx) panels intended to aid psychiatric prescribing are available to clinicians. Here, we evaluated the documentation of PGx panel results and subsequent prescribing patterns within a tertiary health care system. MethodsWe performed a query of psychiatry service note text in our electronic health record using 71 predefined PGx terms. Patients who underwent combinatorial PGx testing were identified, and documentation of test results was analyzed. Prescription data following testing were examined for the frequency of prescriptions influenced by genes on the panel along with the medical specialties involved. ResultsA total of 341 patients received combinatorial PGx testing, and documentation of results was found to be absent or incomplete for 198 patients (58%). The predominant method of documentation was through portable document formats uploaded to the electronic health record’s “Media” section. Among patients with at least 1 year of follow-up, a large majority (194/228, 85%) received orders for medications affected by the tested genes, including 132 of 228 (58%) patients receiving at least 1 non-psychiatric medication influenced by the test results. ConclusionResults from combinatorial PGx testing were poorly documented. Medications affected by these results were often prescribed after testing, highlighting the need for discrete results and clinical decision support.

Risk Stratification of QTc Prolongation in Critically Ill Patients Receiving Antipsychotics for the Management of Delirium Symptoms.

Patients experiencing significant agitation or perceptual disturbances related to delirium in an intensive care setting may benefit from short-term treatment with an antipsychotic medication. Some antipsychotic medications may prolong the QTc interval, which increases the risk of potentially fatal ventricular arrhythmias. In this targeted review, we describe the evidence regarding the relationships between antipsychotic medications and QTc prolongation and practical methods for monitoring the QTc interval and mitigating arrhythmia risk. Searches of PubMed and Cochrane Library were performed to identify studies, published before February 2023, investigating the relationships between antipsychotic medications and QTc prolongation or arrhythmias. Most antipsychotic medications commonly used for the management of delirium symptoms (eg, intravenous haloperidol, olanzapine, quetiapine) cause a moderate degree of QTc prolongation. Among other antipsychotics, those most likely to cause QTc prolongation are iloperidone and ziprasidone, while aripiprazole and lurasidone appear to have minimal risk for QTc prolongation. Genetic vulnerabilities, female sex, older age, pre-existing cardiovascular disease, electrolyte abnormalities, and non-psychiatric medications also increase the risk of QTc prolongation. For individuals at risk of QTc prolongation, it is essential to measure the QTc interval accurately and consistently and consider medication adjustments if needed. Antipsychotic medications are one of many risk factors for QTc prolongation. When managing agitation related to delirium, it is imperative to assess an individual patient's risk for QTc prolongation and to choose a medication and monitoring strategy commensurate to the risks. In intensive care settings, we recommend regular ECG monitoring, using a linear regression formula to correct for heart rate. If substantial QTc prolongation (eg, QTc > 500 msec) is present, a change in pharmacologic treatment can be considered, though a particular medication may still be warranted if the risks of discontinuation (eg, extreme agitation, removal of invasive monitoring devices) outweigh the risks of arrhythmias. This review aims to summarize the current literature on relationships between antipsychotic medications and QTc prolongation and to make practical clinical recommendations towards the approach of antipsychotic medication use for the management of delirium-related agitation and perceptual disturbances in intensive care settings.

Use of Non-Psychiatric Medications With Potential Depressive Symptom Side Effects and Level of Depressive Symptoms in Major Depressive Disorder

Objective: To determine whether use of medications with potential depressive symptom side effects is associated with a higher level of depressive symptoms in adults with antidepressant-treated major depressive disorder (MDD).Methods: The study was based on the 2013-2014, 2015-2016, and 2017-2018 National Health and Nutrition Examination Survey (NHANES)-a nationally representative cross-sectional survey of the US general population. In 885 adult participants from these NHANES cycles who reported receiving antidepressants for treatment of International Classification of Diseases, Tenth Revision, Clinical Modification MDD, the association between the number of medications with potential depressive symptom side effects and the level of depressive symptoms was assessed.Results: A majority (66.7%, n = 618) of the participants with antidepressant-treated MDD used at least 1 non-psychiatric medication with potential depressive symptom side effects, and 37.3% (n = 370) used more than 1 such medication. The number of medications with depressive symptom side effects was significantly associated with lower odds of no to minimal depressive symptoms, defined as a Patient Health Questionnaire-9 (PHQ-9) score < 5 (adjusted odds ratio [AOR] = 0.75, 95% confidence interval [CI] = 0.64-0.87, P < .001), and higher odds of moderate to severe symptoms, defined as a PHQ-9 score ≥ 10 (AOR = 1.14, 95% CI = 1.004-1.29, P = .044). No such associations were found for medications without potential depressive symptom side effects.Conclusions: Individuals treated for MDD frequently use non-psychiatric medications for comorbid medical conditions that are associated with an increased risk of depressive symptoms. In evaluating the response to antidepressant medication treatment, side effects of concomitantly used medications should be considered.

Clozapine use at a specialised psychiatric hospital in Johannesburg.

Clozapine is the gold standard medication for treatment-resistant psychosis, with robust evidence supporting its efficacy in multiple symptom domains. However, clozapine's side effect profile contributes to its underutilisation and discontinuation. This study aimed to explore the magnitude of clozapine use and describe factors that impact on its effective use among in-patients. Tara Hospital, a specialised psychiatric hospital in Johannesburg. This was a retrospective, cross-sectional file review of clozapine-treated patients admitted over the 2-year study period. Data variables included: demographics, clinical information, discharge prescription, clozapine-related side effects and details of clozapine discontinuation, where applicable. A cohort of 33.2% of patients from Tara's biological wards received a trial of clozapine. Participants experienced anti-cholinergic clozapine-related side effects that included weight gain (79.5%), tachycardia (35.2%) and constipation (35.2%). Clozapine was discontinued in 13.7% of participants, and no life-threatening side effects or deaths occurred. Significantly more use of flupenthixol decanoate (64.3% vs. 30.7%; p = 0.0322) and anticholinergics (35.7% vs. 11.4%; p = 0.0474) occurred in the clozapine-discontinued group. Polypharmacy rates were high for psychiatric and non-psychiatric medications. One-third of patients received clozapine trials, most of whom continued at discharge. Although side effects occurred frequently, life-threatening side effects did not. Clozapine monitoring protocols, side effect rating scales, pre-emptive management of side effects, lifestyle interventions and clinician education may improve outcomes of clozapine use. The use of plasma clozapine levels may be beneficial. This study expands our limited knowledge regarding current clozapine prescribing trends in South Africa.

A Polysomnographic and Cluster Analysis of Periodic Limb Movements in Sleep of Restless Legs Syndrome Patients with Psychiatric Conditions

Only survey studies have linked specific individual psychiatric disorders such as anxiety, depression and schizophrenia to Restless Legs Syndrome (RLS), Periodic Limb Movements in Sleep (PLMS) or both. We therefore aim to polysomnographically characterize sleep in a sample of physician-based, newly diagnosed cases of RLS with various ICD-10 psychiatric diagnoses. Retrospective analysis of data from a convenience sample of psychiatric patients (n = 43) per standard clinical sleep disorder cut-offs was conducted. Next, a cluster analysis was performed on the sleep data, taking into account the psychiatric diagnosis, comorbid non-psychiatric somatic problems and medication. We found that 37.2% of our sample showed clinically significant PLMS ≥ 15 and 76.5% exhibited an apnea hypopnea index (AHI) ≥ 5. Sleep structure was unaltered apart from the PLMS-related parameters. Two clusters were statistically identified: Cluster 1 primarily representing recurrent major depressive issues and Cluster 2 representing present but not predominant mood symptomatology as well as mixed disorders with personality problems. The known confounders were controlled. A PLMS index ≥ 15 was differentially distributed among the two clusters with Cluster 1: 10 out of 17 with PLMS index ≥ 15; Cluster 2: 1 out of 16 with PLMS index ≥15; whilst AHI was not different. Patients in Cluster 1 have a higher rate of periodic leg movements than patients in Cluster 2. This suggests that the high association with PLMS is primarily driven by affective disorders. Our findings warrant questioning of RLS symptomatology in patients with psychiatric conditions.

Genome-wide association study accounting for anticholinergic burden to examine cognitive dysfunction in psychotic disorders.

Identifying genetic contributors to cognitive impairments in psychosis-spectrum disorders can advance understanding of disease pathophysiology. Although CNS medications are known to affect cognitive performance, they are often not accounted for in genetic association studies. In this study, we performed a genome-wide association study (GWAS) of global cognitive performance, measured as composite z-scores from the Brief Assessment of Cognition in Schizophrenia (BACS), in persons with psychotic disorders and controls (N = 817; 682 cases and 135 controls) from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) study. Analyses accounting for anticholinergic exposures from both psychiatric and non-psychiatric medications revealed five significantly associated variants located at the chromosome 3p21.1 locus, with the top SNP rs1076425 in the inter-alpha-trypsin inhibitor heavy chain 1 (ITIH1) gene (P = 3.25×E-9). The inclusion of anticholinergic burden improved association models (P < 0.001) and the number of significant SNPs identified. The effect sizes and direction of effect of the top variants remained consistent when investigating findings within individuals receiving specific antipsychotic drugs and after accounting for antipsychotic dose. These associations were replicated in a separate study sample of untreated first-episode psychosis. The chromosome 3p21.1 locus was previously reported to have association with the risk for psychotic disorders and cognitive performance in healthy individuals. Our findings suggest that this region may be a psychosis risk locus that is associated with cognitive mechanisms. Our data highlight the general point that the inclusion of medication exposure information may improve the detection of gene-cognition associations in psychiatric genetic research.

CYP2D6 Reduced Function Variants and Genotype/Phenotype Translations of CYP2D6 Intermediate Metabolizers: Implications for Personalized Drug Dosing in Psychiatry.

Genetic differences in cytochrome P450 (CYP)-mediated metabolism have been known for several decades. The clinically most important polymorphic CYP enzyme is CYP2D6, which plays a key role in the metabolism of many antidepressants and antipsychotics, along with a range of non-psychiatric medications. Dose individualization based on CYP2D6 genotype to improve the effect and safety of drug treatment has been an ambition for a long time. Clinical use of CYP2D6 genotyping is steadily increasing; however, for pre-emptive genotyping to be successful in predicting individual dose requirements, high precision of genotype-to-phenotype translations are required. Recently, guidelines for assigning CYP2D6 enzyme activity scores of CYP2D6 variant alleles, and subsequent diplotype-to-phenotype translations, were published by the Clinical Pharmacogenetics Implementation Consortium (CPIC) and the Dutch Pharmacogenetics Working Group. Consensus on assigning activity scores of CYP2D6 variant alleles and translating diplotype scores into CYP2D6 poor, intermediate, normal, or ultrarapid metabolizer groups were obtained by consulting 37 international experts. While assigning enzyme activities of non-functional (score 0) and fully functional (score 1) alleles are straightforward, reduced function variant alleles are more complex. In this article, we present data showing that the assigned activity scores of reduced function variant alleles in current guidelines are not of sufficient precision; especially not for CYP2D6*41, where the guideline activity score is 0.5 compared to 0.05–0.15 in pharmacogenetic studies. Due to these discrepancies, CYP2D6 genotypes with similar guidelinediplotype scores exhibit substantial differences in CYP2D6 metabolizer phenotypes. Thus, it is important that the guidelines are updated to be valid in predicting individual dose requirements of psychiatric drugs and others metabolized by CYP2D6.

Perspectives on illness-related stigma and electronically sharing psychiatric health information by people with multiple sclerosis

BackgroundElectronic medical records (EMRs) facilitate more integrated and comprehensive care. Despite this, EMRs are used less frequently in psychiatry compared to other medical disciplines, in part due to concerns regarding stigma surrounding mental health. This paper explores the willingness to share medical information among patients with multiple sclerosis (MS), who experience higher rates of psychiatric comorbidities compared to the general population, and the role that stigma plays in patient preferences. MethodsMS patients were surveyed about their co-occurring psychiatric and non-psychiatric diagnoses, willingness to share their health information electronically among their treating doctors, and levels of self and societal stigma associated with their diagnoses. ResultsParticipants were slightly more willing to share their non-psychiatric medical information vs. psychiatric information. Despite the presence of stigma decreasing patient willingness to share medical records, those with psychiatric co-occurring disorders, compared to those without, endorsed significantly greater willingness to electronically share their health records. The majority of diagnoses for which participants experienced the greatest difference in self vs. societal stigmas were psychiatric ones, including substance use, eating and mood disorders. Societal stigma strongly correlated with decreased non-psychiatric medication sharing, while self stigma was strongly correlated with decreased psychiatric medications sharing. LimitationsStandardized scales were not used to assess patient stigma and there is a potential lack of generalizability of results beyond patients with MS. ConclusionsThese insights into patient preferences toward sharing their medical information should inform decisions to implement EMRs, particularly for patient populations experiencing higher than average levels of psychiatric comorbidities.

Why Are Patients With COVID-19 at Risk for Drug-Drug Interactions?

The goal of this column is to provide information to health care professionals about drug-drug interactions (DDIs) and why DDIs are important to consider in those at serious risk of illness with Coronavirus Disease 2019 (COVID-19). Important considerations discussed in this column include the frequency and complexity of multiple medication use, particularly important for the older patient who often has multiple comorbid illnesses. The column covers the following issues: (1) Why patients at high risk for serious illness from COVID-19 are also at high risk for DDIs. (2) Application of results of pharmacoepidemiological studies to the population at risk for serious COVID-19 illness. (3) Mechanisms underlying DDIs, frequency and potential complexity of DDIs, and how DDIs can present clinically. (4) Methods for preventing or mitigating DDIs. (5) An introduction to the University of Liverpool drug interaction checker as a tool to reduce the risk of adverse DDIs while treating patients for COVID-19. Commentary is also provided on issues related to specific psychiatric and nonpsychiatric medications a patient may be taking. A subsequent column will focus on DDIs between psychiatric medications and emerging COVID-19 treatments, as a detailed discussion of that topic is beyond the scope of this column.

Guide to Considering Nonpsychiatric Medical Intervention Over Objection for the Patient Without Decisional Capacity

A considerable percentage of medical inpatients are communicative but lack decisional capacity.1,2 These patients also often lack surrogates, particularly when they are homeless, elderly, mentally ill, or substance users.3,4 Caring for such patients often raises ethical dilemmas, particularly when the patient refuses a proposed medical intervention. Legal and ethical guidelines regarding patients without capacity focus on treating for psychiatric illnesses,5 do-not-resuscitate orders,6 and withdrawal of life-sustaining therapies.

Integrative Review of Mobile Phone Contacts and Medication Adherence in Severe Mental Illness.

Poor medication adherence is a significant problem in individuals with severe mental illness (SMI). About 50% of people with SMI become nonadherent to treatment in the first month following discharge from the hospital. This study examined literature in the past decade (2006-2016) on the use of mobile phone contacts in individuals with SMI to improve medication adherence post hospital discharge. This integrative review used the search terms texting, text messaging, SMS, cell/mobile phone, medication adherence, medication compliance, and mental illness. Databases (CINAHL, PubMed, PsycINFO, and Scopus) and manual searching of reference lists were done. The main inclusion criteria were the use of mobile phone contacts on medication adherence in individuals with SMI. Adults 18 years and older, studies conducted from 2006 to 2016, and studies conducted in English were also criteria for inclusion. Only five studies met criteria for inclusion. Outcomes from the review showed that mobile phone contacts have been used to improve medication adherence in individuals with SMI and able to provide the four types of social support (instrumental, informational, emotional, and, appraisal). When phone contacts especially text messaging was used as an adjunct to other interventions, it yielded better medication adherence than when used alone. However, results on medication adherence rates were mixed in participants on both psychiatric and nonpsychiatric medications. Although mobile phone contacts are a promising tool to enhance medication adherence after hospital discharge, its effectiveness to increase medication adherence in this population remains inconclusive.

Self-reported medication use validated through record linkage to national prescribing data

ObjectivesResearchers need to be confident about the reliability of epidemiologic studies that quantify medication use through self-report. Some evidence suggests that psychiatric medications are systemically under-reported. Modern record linkage enables validation of self-report with national prescribing data as gold standard. Here, we investigated the validity of medication self-report for multiple medication types. Study Design and SettingParticipants in the Generation Scotland population-based cohort (N = 10,244) recruited 2009–2011 self-reported regular usage of several commonly prescribed medication classes. This was matched against Scottish NHS prescriptions data using 3- and 6-month fixed time windows. Potential predictors of discordant self-report, including general intelligence and psychological distress, were studied via multivariable logistic regression. ResultsAntidepressants self-report showed very good agreement (κ = 0.85, [95% confidence interval (CI) 0.84–0.87]), comparable to antihypertensives (κ = 0.90 [CI 0.89–0.91]). Self-report of mood stabilizers showed moderate-poor agreement (κ = 0.42 [CI 0.33–0.50]). Relevant past medical history was the strongest predictor of self-report sensitivity, whereas general intelligence was not predictive. ConclusionIn this large population-based study, we found self-report validity varied among medication classes, with no simple relationship between psychiatric medication and under-reporting. History of indicated illness predicted more accurate self-report, for both psychiatric and nonpsychiatric medications. Although other patient-level factors influenced self-report for some medications, none predicted greater accuracy across all medications studied.

Possible predictors of age at illness onset and illness duration in a cohort study comparing younger adults and older major affective patients

BackgroundMajor affective conditions are associated with significant disability and psychosocial impairment. Whether specific socio-demographic and clinical characteristics may distinguish subgroups of patients in terms of prognosis and illness trajectories is a matter of debate. MethodsThe sample of this naturalistic cohort study included 675 currently euthymic patients with major affective disorders of which 428 (63.4%) were diagnosed with unipolar and 247 (36.6%) with bipolar disorders. ResultsYounger adults with a longer duration of untreated illness and residual inter-episodic symptoms were more likely to be single or divorced, students, with an earlier age of first treatment/hospitalization, longer duration of substance abuse and duration of illness than older patients who were, conversely, more likely to be widowed and retired. Multivariate analyses showed a significant positive contribution to age at illness onset by marital status, nonpsychiatric medications, substance abuse, psychiatric diagnosis (bipolar vs. unipolar), age at first treatment/hospitalization, duration of illness, and current age. According to a further analysis, we also found a significant positive contribution to duration of illness by marital status, educational level, positive history of psychiatric conditions in family, substance abuse, psychiatric diagnosis (bipolar vs. unipolar), age at illness onset, age at first treatment, and certain cardiovascular disorders. ConclusionsThere are substantial socio-demographic and clinical differences that may help to distinguish specific subgroups of patients; however, additional studies are requested to replicate these results and further investigate the main factors underlying our findings.

Managing Psychotropic Medications in Complex, Real-World Patients Using Comprehensive Therapeutic Drug Monitoring.

There are multiple treatment options for depression, anxiety, psychosis, and other psychiatric disorders, and psychiatry patients are often comorbid with complex, polypharmacy treatment regimens. Unlike cardiovascular disease and diabetes, there are no readily available biomarkers to gauge treatment success with psychotropic medications, often resulting in subjective determination of medication therapy effectiveness. The physiochemical properties of psychiatric medications in general lend themselves to quantitative measurement in blood, offering an avenue to optimize treatment for each patient. Herein, we describe a novel application that employs comprehensive therapeutic drug monitoring of both psychiatric and nonpsychiatric medications to holistically personalize therapy for complex psychiatry patients.

A Reexamination of Nonpsychiatric Medication Adherence in Individuals With Bipolar Disorder and Medical Comorbidities.

Individuals with bipolar disorder (BD) have high rates of nonadherence, medical illness, and premature mortality. This analysis reexamined correlates of poor adherence to nonpsychiatric medication in 73 patients with BD and medical comorbidities. The majority was female (74%) and African American (77%) with mean age of 48.08 (SD, 8.04) years, mean BD duration of 28.67 (SD, 10.24) years, mean years of education of 12.01 (SD, 1.87), and mean proportion of days with missed doses in past week of 43.25 (SD, 31.14). Sex, age, education, race, and living alone did not correlate with adherence. More BD medications and more severe psychiatric symptoms correlated with worse adherence. Specifically, poor adherence correlated with the retardation and vegetative factors of Montgomery-Åsberg Depression Rating Scale and affect factor of the Brief Psychiatric Rating Scale. Among poorly adherent patients with BD and medical comorbidities, the number of BD medications, tension/anxiety, and somatic symptoms of depression related to worse nonpsychiatric medication adherence.

Antipsychotic Use and Physical Morbidity in Parkinson Disease

To determine if antipsychotic (AP) use in Parkinson disease (PD) patients is associated with increased physical morbidity. Veterans Health Administration data (1999-2010) was used to examine physical morbidity risk associated with AP use in idiopathic PD patients with stable recent physical health. We compared 180-day morbidity rates in patients initiating an AP with matched non-AP users who survived for 180 days (matched on age, sex, race, index year, presence and duration of dementia, PD duration, delirium, hospitalization, Charlson Comorbidity Index, and new non-psychiatric medications; covarying for psychosis). Outcomes were 180-day emergency department (ED), and inpatient and outpatient visits. There were 6,679 matched PD pairs. Any AP use was associated with an increased risk of ED visit (HR: 1.64, 95% CI: 1.51, 1.77), inpatient care (HR: 1.58, 95% CI: 1.46, 1.71), and outpatient visits (IRR: 1.08, 95% CI: 1.05, 1.12). The risk was significantly higher for atypical AP use compared with nonuse for all three morbidity outcomes, and was similar for atypical and typical AP use. Any AP use, and atypical AP use, are associated with significantly increased physical morbidity risk in PD patients, as evidenced by increased ED, inpatient, and outpatient visits. These findings, which require replication, extend the risk associated with use of APs in this population from mortality to a broader range of adverse outcomes, and further highlight the need to use APs cautiously in PD patients.

Effect of a Telephone Intervention on Measures of Psychiatric and Nonpsychiatric Medication Adherence in Outpatients With Schizophrenia Spectrum Disorders.

Telephone intervention may address the need for problem-solving interventions to improve medication adherence in patients with schizophrenia spectrum disorders (SSDs). The current randomized controlled trial examined the effect of weekly telephone intervention problem solving (TIPS) on quantitative measures of psychiatric and nonpsychiatric medication adherence over 6 months in 105 stable outpatients with SSDs. Independent samples t test revealed no significant differences in psychiatric or nonpsychiatric pill count adherence between groups at 6 months; however, 54.7% of experimental participants versus 32.7% of controls had serum antipsychotic levels within therapeutic range at 6 months (χ2 = 5.2, df = 1, p = 0.023). The current study extends the literature on adherence in patients with SSDs by describing a clinical sample of stable outpatients over 6 months and examining adherence to psychiatric and nonpsychiatric medications. [Journal of Psychosocial Nursing and Mental Health Services, 55(1), 29-36.].

Commentary on Management of Older Inpatients who Refuse Non-Psychiatric Medication

Commentary on Management of Older Inpatients who Refuse Non-Psychiatric Medication

Effect of a Telephone Intervention upon Medication Adherence and Related Outcomes in Outpatients with Schizophrenia Spectrum Disorders (SSDs)

Background: Telephone intervention is an innovative option to provide needed problem solving interventions to improve medication adherence in Schizophrenia Spectrum Disorders (SSDs). Methods: This randomized controlled trial examined the effect of weekly Telephone Intervention-Problem Solving (TIPS) upon quantitative and qualitative measures of psychiatric and nonpsychiatric medication adherence in 119 stable outpatients with SSDs for nine months. Findings: Independent samples T-test revealed no significant differences in psychiatric or nonpsychiatric pill count adherence between groups; however 29% of experimental versus 19.6% of controls had serum antipsychotic levels within therapeutic range (NS). Conclusion: This study extends the literature on adherence in SSDs by describing a clinical sample of stable outpatients for nine months. Our next project will examine the effectiveness of TIPS boosters upon outcomes.