Motivational interviewing (MI) may be an effective intervention to improve medication adherence in patients with schizophrenia. However, for this patient group, mixed results have been found in randomized controlled trials. Furthermore, the process of becoming (more) motivated for long-term medication adherence in patients with schizophrenia is largely unexplored
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Risk assessment instruments are widely used to predict risk of adverse outcomes, such as violence or victimization, and to allocate resources for managing these risks among individuals involved in criminal justice and forensic mental health services. For risk assessment instruments to reach their full potential, they must be implemented with fidelity. A lack of information on administration fidelity hinders transparency about the implementation quality, as well as the interpretation of negative or inconclusive findings from predictive validity studies. The present study focuses on adherence, a dimension of fidelity. Adherence denotes the extent to which the risk assessment is completed according to the instrument’s guidelines. We developed an adherence measure, tailored to the ShortTerm Assessment of Risk and Treatability: Adolescent Version (START:AV), an evidence-based risk assessment instrument for adolescents. With the START:AV Adherence Rating Scale, we explored the degree to which 11 key features of the instrument were adhered to in 306 START:AVs forms, completed by 17 different evaluators in a Dutch residential youth care facility over a two-year period. Good to excellent interrater reliability was found for all adherence items. We identified differences in adherence scores on the various START:AV features, as well as significant improvement in adherence for those who attended a START:AV refresher workshop. Outcomes of risk assessment instruments potentially impact decision-making, for example, whether a youth’s secure placement should be extended. Therefore, we recommend fidelity monitoring to ensure the risk assessment practice was delivered as intended.
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Objectives Adherence to injury prevention programmes in football remains low, which is thought to drastically reduce the effects of injury prevention programmes. Reasons why (medical) staff and players implement injury prevention programmes, have been investigated, but player’s characteristics and perceptions about these programmes might influence their adherence. Therefore, this study investigated the relationships between player’s characteristics and adherence and between player’s perceptions and adherence following an implemented injury prevention programme. Methods Data from 98 of 221 football players from the intervention group of a cluster randomised controlled trial concerning hamstring injury prevention were analysed. Results Adherence was better among older and more experienced football players, and players considered the programme more useful, less intense, more functional and less time-consuming. Previous hamstring injuries, educational level, the programme’s difficulty and intention to continue the exercises were not significantly associated with adherence. Conclusion These player’s characteristics and perceptions should be considered when implementing injury prevention programmes.
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Purpose: To describe nurses' support interventions for medication adherence, and patients' experiences and desired improvements with this care. Patients and methods: A two-phase study was performed, including an analysis of questionnaire data and conducted interviews with members of the care panel of the Netherlands Patients Federation. The questionnaire assessed 14 types of interventions, satisfaction (score 0-10) with received interventions, needs, experiences, and desired improvements in nurses' support. Interviews further explored experiences and improvements. Data were analyzed using descriptive statistics and a thematic analysis approach. Results: Fifty-nine participants completed the questionnaire, and 14 of the 59 participants were interviewed. The satisfaction score for interventions was 7.9 (IQR 7-9). The most common interventions were: "noticing when I don't take medication as prescribed" (n = 35), "helping me to find solutions to overcome problems with using medications" (n = 32), "helping me with taking medication" (n = 32), and "explaining the importance of taking medication at the right moment" (n = 32). Fifteen participants missed ≥1 of the 14 interventions. Most mentioned the following: "regularly asking about potential problems with medication use" (33%), "regularly discussing whether using medication is going well" (29%), and "explaining the importance of taking medication at the right moment" (27%). Twenty-two participants experienced the following as positive: improved self-management of adequate medication taking, a professional patient-nurse relationship to discuss adherence problems, and nurses' proactive attitude to arrange practical support for medication use. Thirteen patients experienced the following as negative: insufficient timing of home visits, rushed appearance of nurses, and insufficient expertise about side effects and taking medication. Suggested improvements included performing home visits on time, more time for providing support in medication use, and more expertise about side effects and administering medication. Conclusion: Overall, participants were satisfied, and few participants wanted more interventions. Nurses' support improved participants' self-management of medication taking and enabled patients to discuss their adherence problems. Adequately timed home visits, more time for support, and accurate medication-related knowledge are desired.
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BACKGROUND: Blended face-to-face and web-based treatment is a promising way to deliver smoking cessation treatment. Since adherence has been shown to be an indicator of treatment acceptability and a determinant for effectiveness, we explored and compared adherence and predictors of adherence to blended and face-to-face alone smoking cessation treatments with similar content and intensity. OBJECTIVE: The objectives of this study were (1) to compare adherence to a blended smoking cessation treatment with adherence to a face-to-face treatment; (2) to compare adherence within the blended treatment to its face-to-face mode and web mode; and (3) to determine baseline predictors of adherence to both treatments as well as (4) the predictors to both modes of the blended treatment. METHODS: We calculated the total duration of treatment exposure for patients (N=292) of a Dutch outpatient smoking cessation clinic who were randomly assigned either to the blended smoking cessation treatment (n=130) or to a face-to-face treatment with identical components (n=162). For both treatments (blended and face-to-face) and for the two modes of delivery within the blended treatment (face-to-face vs web mode), adherence levels (ie, treatment time) were compared and the predictors of adherence were identified within 33 demographic, smoking-related, and health-related patient characteristics. RESULTS: We found no significant difference in adherence between the blended and the face-to-face treatments. Participants in the blended treatment group spent an average of 246 minutes in treatment (median 106.7% of intended treatment time, IQR 150%-355%) and participants in the face-to-face group spent 238 minutes (median 103.3% of intended treatment time, IQR 150%-330%). Within the blended group, adherence to the face-to-face mode was twice as high as that to the web mode. Participants in the blended group spent an average of 198 minutes (SD 120) in face-to-face mode (152% of the intended treatment time) and 75 minutes (SD 53) in web mode (75% of the intended treatment time). Higher age was the only characteristic consistently found to uniquely predict higher adherence in both the blended and face-to-face groups. For the face-to-face group, more social support for smoking cessation was also predictive of higher adherence. The variability in adherence explained by these predictors was rather low (blended R2=0.049; face-to-face R2=0.076). Within the blended group, living without children predicted higher adherence to the face-to-face mode (R2=0.034), independent of age. Higher adherence to the web mode of the blended treatment was predicted by a combination of an extrinsic motivation to quit, a less negative attitude toward quitting, and less health complaints (R2=0.164). CONCLUSIONS: This study represents one of the first attempts to thoroughly compare adherence and predictors of adherence of a blended smoking cessation treatment to an equivalent face-to-face treatment. Interestingly, although the overall adherence to both treatments appeared to be high, adherence within the blended treatment was much higher for the face-to-face mode than for the web mode. This supports the idea that in blended treatment, one mode of delivery can compensate for the weaknesses of the other. Higher age was found to be a common predictor of adherence to the treatments. The low variance in adherence predicted by the characteristics examined in this study suggests that other variables such as provider-related health system factors and time-varying patient characteristics should be explored in future research. TRIAL REGISTRATION: Netherlands Trial Register NTR5113; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=5113.
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Objectives: To develop an instrument to measure adherence to frequency, intensity, and quality of performance of home-based exercise (HBE) programs recommended by a physical therapist and to evaluate its construct validity and reliability in patients with low back pain. Methods: The Exercise Adherence Scale (EXAS) was developed following a literature search, an expert panel review, and a pilot test. The construct validity of the EXAS was determined based on data from 27 participants through an investigation of the convergent validity between adherence, lack of time to exercise, and lack of motivation to exercise. Associations between adherence, pain, and disability were determined to test divergent validity. The reliability of the EXAS quality of performance score was assessed using video recordings from 50 participants performing four exercises. Results: Correlations between the EXAS and lack of time to exercise, lack of motivation to exercise, pain, and disability were rho = 0.47, rho = 0.48, rho = 0.005, and rho = 0.24, respectively. The intrarater reliability of the quality of performance score was Kappa quadratic weights (Kqw) = 0.87 (95%-CI 0.83–0.92). The interrater reliability was Kqw = 0.36 (95%-CI 0.27–0.45). Conclusions: The EXAS demonstrates acceptable construct validity for the measurement of adherence to HBE programs. Additionally, the EXAS shows excellent intrarater reliability and poor interrater reliability for the quality of performance score and is the first instrument to measure adherence to frequency, intensity, and quality of performance of HBE programs. The EXAS allows researchers and clinicians to better investigate the effects of adherence to HBE programs on the outcomes of interventions and treatments.
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Aims: Medication non-adherence post-discharge is common among patients, especially those suffering from chronic medical conditions, and contributes to hospital admissions and mortality. This study aimed to evaluate the effect of the Cardiac Care Bridge (CCB) intervention on medication adherence post-discharge. Methods: We performed a secondary analysis of the CCB randomized single-blind trial, a study in patients ≥70 years, at high risk of functional loss and admitted to cardiology departments in six hospitals. In this multi-component intervention study, community nurses performed medication reconciliation and observed medication-related problems (MRPs) during post-discharge home visits, and pharmacists provided recommendations to resolve MRPs. Adherence to high-risk medications was measured using the proportion of days covered (PDC), using pharmacy refill data. Furthermore, MRPs were assessed in the intervention group. Results: For 198 (64.7%) of 306 CCB patients, data were available on adherence (mean age: 82 years; 58.9% of patients used a multidose drug dispensing [MDD] system). The mean PDC before admission was 92.3% in the intervention group (n = 99) and 88.5% in the control group (n = 99), decreasing to 85.2% and 84.1% post-discharge, respectively (unadjusted difference: -2.6% (95% CI -9.8 to 4.6, P = .473); adjusted difference -3.3 (95% CI -10.3 to 3.7, P = .353)). Post-hoc analysis indicated that a modest beneficial intervention effect may be restricted to MDD non-users (Pinteraction = .085). In total, 77.0% of the patients had at least one MRP post-discharge. Conclusions: Our findings indicate that a multi-component intervention, including several components targeting medication adherence in older cardiac patients discharged from hospital back home, did not benefit their medication adherence levels. A modest positive effect on adherence may potentially exist in those patients not using an MDD system. This finding needs replication.
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Background: Computer-based cognitive rehabilitation is used to improve cognitive functioning after stroke. However, knowledge on adherence rates of stroke patients is limited. Objective: To describe stroke patients’ adherence with a brain training program using two frequencies of health professionals’ supervision. Methods: This study is part of a randomized controlled trial comparing the effect of the brain training program (600 min playtime with weekly supervision) with a passive intervention in patients with self-perceived cognitive impairments after stroke. Patients randomized to the control condition were offered the brain training after the trial and received supervision twice (vs weekly in intervention group). Adherence was determined using data from the study website. Logistic regression analyses were used to examine the impact of supervision on adherence. Results: 53 patients allocated to the intervention group (group S8; 64% male, mean age 59) and 52 patients who were offered the intervention after the trial (group S2; 59% male, mean age 59) started the brain training. The median playtime was 562 min (range 63–1264) in group S8 vs. 193 min (range 27–2162) in group S2 (p < 0.001, Mann Whitney U). Conclusions: The overall adherence of stroke patients with a brain training was low and there are some implications that systematic, regular interaction with a supervisor can increase training adherence of stroke patients with a restitution-focused intervention performed at home. “This is an Accepted Manuscript of an article published by Taylor & Francis in "Topics in Stroke Rehabilitation" on 04/17/18, available online: https://doi.org/10.1080/10749357.2018.1459362. LinkedIn: https://www.linkedin.com/in/joritmeesters/ https://www.linkedin.com/in/moniqueberger/ https://www.linkedin.com/in/arend-de-kloet-4329102/
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AimsMedication non-adherence post-discharge is common among patients, especially those suffering from chronic medical conditions, and contributes to hospital admissions and mortality. This study aimed to evaluate the effect of the Cardiac Care Bridge (CCB) intervention on medication adherence post-discharge.MethodsWe performed a secondary analysis of the CCB randomized single-blind trial, a study in patients ≥70 years, at high risk of functional loss and admitted to cardiology departments in six hospitals. In this multi-component intervention study, community nurses performed medication reconciliation and observed medication-related problems (MRPs) during post-discharge home visits, and pharmacists provided recommendations to resolve MRPs. Adherence to high-risk medications was measured using the proportion of days covered (PDC), using pharmacy refill data. Furthermore, MRPs were assessed in the intervention group.ResultsFor 198 (64.7%) of 306 CCB patients, data were available on adherence (mean age: 82 years; 58.9% of patients used a multidose drug dispensing [MDD] system). The mean PDC before admission was 92.3% in the intervention group (n = 99) and 88.5% in the control group (n = 99), decreasing to 85.2% and 84.1% post-discharge, respectively (unadjusted difference: −2.6% (95% CI −9.8 to 4.6, P = .473); adjusted difference −3.3 (95% CI −10.3 to 3.7, P = .353)). Post-hoc analysis indicated that a modest beneficial intervention effect may be restricted to MDD non-users (P interaction = .085). In total, 77.0% of the patients had at least one MRP post-discharge.ConclusionsOur findings indicate that a multi-component intervention, including several components targeting medication adherence in older cardiac patients discharged from hospital back home, did not benefit their medication adherence levels. A modest positive effect on adherence may potentially exist in those patients not using an MDD system. This finding needs replication.
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Purpose In this systematic literature review, the effects of the application of a checklist during in hospital resuscitation of trauma patients on adherence to the ATLS guidelines, trauma team performance, and patient-related outcomes were integrated. Methods A systematic review was performed following the Preferred Reporting Items for Systematic Reviews and Metaanalyses checklist. The search was performed in Pubmed, Embase, CINAHL, and Cochrane inception till January 2019. Randomized controlled- or controlled before-and-after study design were included. All other forms of observational study designs, reviews, case series or case reports, animal studies, and simulation studies were excluded. The Effective Public Health Practice Project Quality Assessment Tool was applied to assess the methodological quality of the included studies. Results Three of the 625 identified articles were included, which all used a before-and-after study design. Two studies showed that Advanced Trauma Life Support (ATLS)-related tasks are significantly more frequently performed when a checklist was applied during resuscitation. [14 of 30 tasks (p < 0.05), respectively, 18 of 19 tasks (p < 0.05)]. One study showed that time to task completion (− 9 s, 95% CI = − 13.8 to − 4.8 s) and workflow improved, which was analyzed as model fitness (0.90 vs 0.96; p < 0.001); conformance frequency (26.1% vs 77.6%; p < 0.001); and frequency of unique workflow traces (31.7% vs 19.1%; p = 0.005). One study showed that the incidence of pneumonia was higher in the group where a checklist was applied [adjusted odds ratio (aOR) 1.69, 95% Confidence Interval (CI 1.03–2.80)]. No difference was found for nine other assessed complications or missed injuries. Reduced mortality rates were found in the most severely injured patient group (Injury Severity score > 25, aOR 0.51, 95% CI 0.30–0.89). Conclusions The application of a checklist may improve ATLS adherence and workflow during trauma resuscitation. Current literature is insufficient to truly define the effect of the application of a checklist during trauma resuscitation on patientrelated outcomes, although one study showed promising results as an improved chance of survival for the most severely injured patients was found.
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