Predictors Of Dropout Research Articles

Sex Differences in Predictors of Completion of a 6-Month Adapted Cardiac Rehabilitation Program for People With Type 2 Diabetes and No Known Cardiac Disease

BackgroundOur aim in this study was to determine sex differences and predictors of noncompletion of a comprehensive adapted cardiac rehabilitation program (CRP) for people with type 2 diabetes (no known cardiac disease). MethodsReasons for noncompletion of a 6-month adapted diabetes exercise-based CRP were ascertained by interview between 2006 and 2017. Regression analyses were conducted to determine demographic, cardiopulmonary, medical and psychosocial predictors of noncompletion in all participants and in females and males separately. ResultsAmong all participants (460 females and 375 males), predictors of dropout included higher depression score, being unemployed, higher glycated hemoglobin (A1C), younger age and fewer comorbidities. There was no difference in completion rate between females and males in bivariate (28% vs 28.3%, p=0.9) or multivariate (odds ratio=1.089, 95% confidence interval 0.79 to 1.5, p=0.6) analyses, but predictors of dropout varied. In females, these predictors included being married/partnered, living with obesity and having a higher depression score, A1C and triglycerides level, independent of age. For males, only higher depression score and younger age predicted dropout. There was no difference in medical dropouts between females and males (37.2% vs 34% of all dropouts, p=0.6) or in reasons for dropout (p>0.05 for all) or attendance to prescheduled sessions in completers (69.2±16.8% vs 70.4±18.8%, p=0.5) or dropouts (24.7±15.7% vs 25.2±16.1%, p=0.8), respectively. ConclusionsThere was no sex difference in noncompletion, attendance or reasons for dropout from a diabetes CRP. However, being married/partnered, living with obesity and having higher A1C and triglycerides were unique predictors of dropout for females and younger age for males. Being unemployed, glycemic control and depressive symptoms are targets for promoting completion in all participants that can be addressed by multidisciplinary CRP teams.

Age and Social Background as Predictors of Dropout in Second Chance Education in Germany

Second chance education (SCE) has been established to offer adults the opportunity to catch up on higher qualifications, for instance the eligibility to study. SCE often suffers from high dropout rates, but little is known about the reasons. This article investigates whether dropout rates depend on family background and age, and if so, why. Data from 3278 students at an institution of SCE in Germany who entered this institution between 2000 and 2016 are analysed using logistic path modelling. The results show that the higher dropout probability of socially disadvantaged students can be traced back completely to poorer academic performance in SCE, partly associated with an unfavourable previous school career. Older students are – irrespective of their family background and despite a better academic performance – more likely to drop out than younger students. If SCE aims to reduce these dropout risks, strategies should vary for different groups of students.

Factors associated with dropout in the longitudinal Vogel study of cognitive decline.

Dementia, including Alzheimer's disease, is a growing problem worldwide. Prevention or early detection of the disease or a prodromal cognitive decline is necessary. By means of our long-term follow-up 'Vogel study', we aim to predict the pathological cognitive decline of a German cohort (mean age was 73.9 ± 1.55 years at first visit) with three measurement time points within 6years per participant. Especially in samples of the elderly and subjects with chronic or co-morbid diseases, dropouts are one of the biggest problems of long-term studies. In contrast to the large number of research articles conducted on the course of dementia, little research has been done on the completion of treatment. To ensure unbiased and reliable predictors of cognitive decline from study completers, our objective was to determine predictors of dropout. We conducted multivariate analyses of covariance and multinomial logistic regression analyses to compare and predict the subject's dropout behaviour at the second visit 3years after baseline (full participation, partial participation and no participation/dropout) with neuropsychiatric, cognitive, blood and lifestyle variables. Lower performance in declarative memory, attention and visual-spatial processing predicted dropout rather than full participation. Lower performance in visual-spatial processing predicted partial participation as opposed to full participation. Furthermore, lower performance in mini-mental status examination predicted whether subjects dropped out or participated partially instead of full participation. Baseline cognitive parameters are associated with dropouts at follow-up with a loss of impaired participants. We expect a bias into a healthier sample over time.

Predictors of Attrition and Response in Cognitive Processing Therapy for Interpersonal Trauma Survivors with PTSD.

With the establishment of empirically validated treatments for posttraumatic stress disorder (PTSD), concerns remain regarding the effectiveness of such treatments in real-world clinical settings. Specifically, premature termination and treatment response limit the effectiveness of these interventions. The current study investigated factors potentially related to premature termination and treatment response in Cognitive Processing Therapy with Account (CPT-A). Participants in this study included 42 women (Mage = 30.70 SDage = 9.40) with PTSD from exposure to interpersonal trauma. Demographic characteristics, pre-treatment symptoms of PTSD and depression, and transdiagnostic factors were examined as predictors of attrition and treatment response. Hierarchical regression and logistic regression models were analyzed to test the variance explained and predictive value of these factors. The present study revealed that age was a significant factor related to dropout from CPT-A whereas baseline PTSD symptom severity was significantly related to treatment response. Results of this study suggest the importance of the interrelationships among pre-treatment predictors as well as the consideration of attrition and treatment response as distinct metrics of treatment outcome. Further, these results inform the application of CPT-A for PTSD in survivors of interpersonal trauma, as consideration of the identified predictors of dropout and non-response at intake may contribute to treatment retention and response.

Dropout from psychological interventions for refugees and asylum seekers: A meta-analysis.

Refugees and asylum seekers often suffer from migration stressors and related psychopathology. However, providing this population with psychological treatment has a number of barriers (e.g., culture and language differences), which are widely thought to hinder the success and continuation of treatment. The current systematic review and meta-analysis aims to provide first comprehensive evidence on the prevalence and predictors of dropout in treatment provided for refugees and asylum seekers. We synthesized the existing evidence on dropout from psychological and psychosocial interventions provided to adult refugees and asylum seekers resettled in high-income countries. Specifically, we meta-analyzed the prevalence of dropout from treatment and explored the factors that predict dropout. Our database search in Pubmed, PsycINFO, Web of Science, and PTSDpubs identified 28 eligible randomized controlled trials (RCTs; 2,691 participants; 39 active treatment conditions), published up to January 31, 2021. Results showed a weighted average dropout rate of 19.14%, 95% confidence interval [14.66, 24.60] across studies and treatment conditions. Subgroup analyses and meta-regressions revealed no statistically significant predictors for dropout. However, several refugee-specific variables (e.g., longer mean duration in country of resettlement, lower rate of insecure asylum status) may merit closer attention in future research. These findings suggest that, in contrast to widespread assumption, the estimated average dropout rate is comparable to those reported in nonrefugee populations. However, more research is needed to establish the underlying mechanisms of dropout, which may differ across populations. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Drop out from mental health treatment in the Saudi national mental health survey

Objectives To evaluate the patterns and potential risk factors associated with mental health treatment dropout in the Saudi National Mental Health Survey (SNMHS). Methods The SNMHS is a face-to-face community-based epidemiological survey in a nationally representative household sample of respondents aged 15–65 in the Kingdom of Saudi Arabia (KSA) (n = 4,004). The sample was limited to those who had received any type of mental health treatment during the past year (n = 168). The distribution of service use and the number of visits were examined. Predictors of treatment dropout were analyzed using logistic regression models. Results Treatment drop out rate was very high overall (42.1%), with dropout occurring early (after 2 visits) in the majority of cases. Participants who were previously married or were diagnosed with a 12-month substance use disorder were significantly more likely than other participants to drop out. Those receiving care from more than three types of providers were significantly less likely than others to terminate treatment prematurely. Conclusions The rate of premature termination of treatment was high and positively associated with previously married status and substance use and inversely related to the number of different providers and number of visits.

Association between Big Five Personality Traits and Participation in Cardiac Rehabilitation in Japanese Patients with Cardiovascular Disease: A Retrospective Cohort Study.

Cardiac rehabilitation (CR) remains underutilised, despite its established clinical benefit. A personality traits assessment may help promote CR implementation, as they are determinants of health-related behaviour. This study aimed to examine the association between the Big Five personality traits and outpatient CR participation in patients with cardiovascular disease (CVD) after discharge. This retrospective cohort study included 163 patients aged <80 years, who underwent inpatient CR when hospitalised for CVD. The Big Five personality traits (conscientiousness, neuroticism, openness, extraversion, and agreeableness) of each patient were evaluated at discharge, using the Japanese version of the Ten-Item Personality Inventory. We examined the relationship of each personality trait with non-participation in outpatient CR and dropout within three months, using logistic regression analysis. Out of 61 patients who initiated the outpatient CR, 29 patients dropped out, leaving us with 32 subjects. The logistic regression analysis results showed that high conscientiousness was associated with non-participation in CR. The primary reason for this was a lack of motivation. Conversely, low conscientiousness and high openness were predictors of dropout. This study suggests that the assessment of the Big Five personality traits, especially conscientiousness and openness, can help improve health communication with patients to promote outpatient CR participation after discharge.

Association between Big Five personality traits and participation in cardiac rehabilitation in Japanese patients with cardiovascular disease: a longitudinal study

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): JSPS KAKENHI Background Cardiac rehabilitation (CR) remains underutilised, despite its established clinical benefit. Assessments of personality traits may serve for patient-medical staff communication to promote CR implementation as they are determinants of health-related behavior. However, few studies have explored the potential effects of the Big Five personality traits on CR participation. Purpose This study aimed to examine the association between the Big Five personality traits and CR participation in patients with cardiovascular disease. Methods This longitudinal analysis included patients aged &amp;lt;80 years hospitalised for cardiovascular disease. We excluded patients aged ≥ 80 years because of the increased prevalence of the need of assistance for outdoor walking, resulting in non-participation in CR. The Big Five personality traits (conscientiousness, neuroticism, openness, extraversion, agreeableness) of each patient were evaluated using the Japanese version of Ten-Item Personality Inventory at discharge (references: 1, 2). Each patient was also asked to answer a self-administered questionnaire related to outpatient CR. The questionnaire included the will to participate in outpatient CR after discharge (yes or no) and the reasons for non-participation in CR. We examined the frequency of CR attendance for each patient for three months after discharge from medical records. According to the participation frequency, patients were stratified into non-participation, participation, and dropout groups. The participation group was defined as at least one CR session a month within three months after discharge. Patients who did not continue CR for three months were considered dropouts. We examined the relationship of each personality trait with non-participation in CR and dropout within three months using logistic regression analysis. Results A total of 139 patients hospitalised for cardiovascular disease were analysed (the mean age: 67.2 ± 9.8 years, men: 71.9%). Of 49 patients who initiated the outpatient CR after discharge, 26 patients continued CR for three months, and 23 patients dropped out. The results of the logistic regression analysis are shown in Figure 1. After adjusted for age, gender, and heart failure, high conscientiousness was associated with non-participation in CR (odds ratio [OR] 1.35, per 1 point; 95% confidence interval (CI) 1.00-1.87). The primary reason for non-participation among patients with high conscientiousness was a lack of motivation. Conversely, low conscientiousness (OR 0.56; 95% CI 0.35-0.90) and high openness (OR 2.19; 95% CI 1.27-3.78) were predictors of dropout within three months after discharge. Conclusion The results of this study imply that the Big Five assessment serves for the health communication to improve CR participation. In particular, high conscientious was associated with non-participation in CR due to a lack of motivation, and patients with low conscientiousness and high openness tended to dropout.

Turn on, Tune in, and Drop out: Predictors of Attrition in a Prospective Observational Cohort Study on Psychedelic Use.

BackgroundThe resurgence of research and public interest in the positive psychological effects of psychedelics, together with advancements in digital data collection techniques, have brought forth a new type of research design, which involves prospectively gathering large-scale naturalistic data from psychedelic users; that is, before and after the use of a psychedelic compound. A methodological limitation of such studies is their high attrition rate, particularly owing to participants who stop responding after initial study enrollment. Importantly, study dropout can introduce systematic biases that may affect the interpretability of results.ObjectiveBased on a previously collected sample (baseline n=654), here we investigated potential determinants of study attrition in web-based prospective studies on psychedelic use.MethodsLogistic regression models were used to examine demographic, psychological trait and state, and psychedelic-specific predictors of dropout. Predictors were assessed 1 week before, 1 day after, and 2 weeks after psychedelic use, with attrition being defined as noncompletion of the key endpoint 4 weeks post experience.ResultsPredictors of attrition were found among demographic variables including age (β=0.024; P=.007) and educational levels, as well as personality traits, specifically conscientiousness (β=–0.079; P=.02) and extraversion (β=0.082; P=.01). Contrary to prior hypotheses, neither baseline attitudes toward psychedelics nor the intensity of acute challenging experiences were predictive of dropout.ConclusionsThe baseline predictors of attrition identified here are consistent with those reported in longitudinal studies in other scientific disciplines, suggesting their transdisciplinary relevance. Moreover, the lack of an association between attrition and psychedelic advocacy or negative drug experiences in our sample contextualizes concerns about problematic biases in these and related data.

Traumatic Stress as a Treatment Priority: Its Prevalence and Impact on Children’s Mental Health Services

This study examined the prevalence of traumatic stress in children’s community mental health settings and assessed the impact of traumatic stress on therapy. Data were collected as part of a randomized effectiveness trial examining a modular treatment. Participants included 140 youth (5–15 years). Multilevel regression analyses examined predictors of treatment dropout, client crises, practice delivery, and therapist deviations from treatment plans. Findings indicate that, despite a high prevalence of trauma and the impact of traumatic stress on treatment dropout, trauma is not often perceived by clients as a treatment priority and trauma characteristics do not predict therapist practice delivery.

Predictors of Discontinuation From Individual Treatment in Men Perpetrators of Intimate Partner Violence

Practitioners working with male perpetrators of intimate partner violence (IPV) observe high rates of treatment dropout in their clientele, which can undermine their ability to reduce the occurrence of IPV. Studies have also mostly documented predictors of dropout from group-format IPV treatment programs, but not from individual-format treatment modalities. This study aimed to identify the predictors and key moments of dropout in 206 French-Canadian men seeking individual treatment for IPV. Results of Cox regression survival analyses indicate that age, education, employment, court-ordered treatment, adult attachment, and the number of perpetrated acts of psychological violence were significant predictors of dropout. Findings highlight the need to assess and target those predictors early in treatment to help men remain in therapy and prevent further use of IPV.

The Role of Lifestyle and Cardiovascular Risk Factors in Dropout From an Australian Cardiac Rehabilitation Program. A Longitudinal Cohort Study

Cardiac rehabilitation (CR) programs reduce the risk of further cardiac events and improve the ability of people living with cardiovascular disease to manage their symptoms. However, many people who experience a cardiac event do not attend or fail to complete their CR program. Little is known about the characteristics of people who drop out compared to those who complete CR. To identify subgroups of patients attending a cardiac rehabilitation program who are more likely to dropout prior to final assessment by (1) calculating the dropout rate from the program, (2) quantifying the association between dropout and socio-demographic, lifestyle, and cardiovascular risk factors, and (3) identifying independent predictors of dropout. The study population is from a large metropolitan teaching hospital in Sydney, Australia, and consists of all participants consecutively enrolled in an outpatient CR program between 2006 and 2017. Items assessed included diagnoses and co-morbidities, quality of life (SF-36), psychological health (DASS-21), lifestyle factors and physical assessment. Dropout was defined as failure to complete the outpatient CR program and post CR assessment. Of the 3,350 patients enrolled in the CR program, 784 (23.4%; 95%CI: 22.0-24.9%) dropped out prior to completion. The independent predictors of dropout were smoking (OR 2.4; 95%CI: 1.9-3.0), being separated or divorced (OR 2.0; 95%CI: 1.5-2.6), younger age (<55 years) (OR 1.9; 95%CI: 1.6-2.4), obesity (OR 1.6; 95%CI: 1.3-2.0), diabetes (OR 1.6; 95%CI: 1.3-2.0), sedentary lifestyle (OR 1.3; 95%CI: 1.1-1.6) and depressive symptoms (OR 1.3; 95%CI: 1.1-1.6). To improve the CR program completion rate, clinicians need to consider the impact of socio-demographic, lifestyle, and cardiovascular risk factors on their patients' ability to complete CR. Tailored strategies which target the independent predictors of dropout are required to promote adherence to CR programs and thereby potentially reduce long-term cardiovascular risk.

Tracking the dropout patients of neoadjuvant chemotherapy with locally advanced oral cavity cancer

BackgroundPatients with locally advanced oral cavity cancer sometimes stopped treatment after neoadjuvant chemotherapy. There are no guidelines of the management for these patients. Before designing clinical trials, we conducted this study to investigate their characteristics, reasons of dropout, and the follow-up information.MethodsMedical records were consecutively reviewed of patients with locally advanced oral cavity cancer who underwent neoadjuvant chemotherapy from Jan 2017 to Dec 2019.Variables were compared between patients stopped treating after chemotherapy and completed treatments by student t-test and Chi-square test. Logistic regression model was used to calculate the odd rations of potential predictors of dropout. The dropout patients were followed up for reasons and results of their decision.ResultsA total of 171 patients were included with 23 not undergoing surgery after chemotherapy. The odd ratios of age over 65 and single marital status were 3.11 (95%CI: 1.1, 8.7) and 4.935 (95%CI: 1.5, 16.1), respectively, for the dropout. The median survival of patients without surgery was 7.4 months. Believing that chemotherapy would be effective and being afraid of the consequence of surgery were the main reasons of refusing surgery.ConclusionsThe prognosis was poor of these dropout patients. Symptom relief and fear of surgery were the reasons of dropout. Age and marital status affected their decision. Clinical trials are needed to be designed for these patients.

MO1053FACTORS INFLUENCING DROPOUT FROM PHYSICAL FUNCTION ASSESSMENT PROGRAMS AMONG PATIENTS RECEIVING MAINTENANCE HEMODIALYSIS

Abstract Background and Aims Continuing participation in physical function assessment programs is a critical component of treatment for patients undergoing hemodialysis (HD). Maintaining physical function through participation in a physical function assessment program is important to prevent adverse events in the clinical field of nephrology. Several clinical practice guidelines recommend regular assessment of physical activity and physical function as part of routine care for patients receiving hemodialysis (HD). However, the factors related to patients’ continuation of a physical function assessment program while undergoing HD remain unknown. We aimed to investigate the predictors associated with dropout from a physical function assessment program among patients receiving outpatient HD. Method In 2016, Seirei Sakura Citizen Hospital initiated a physical function assessment program for patients receiving outpatient HD. This retrospective cohort study included 230 patients receiving HD who participated in the first physical function assessment program in 2016. Following the initial visit, all patients were invited to complete a physical function assessment once a year. We assessed self-efficacy (SE), short physical performance battery (SPPB), exercise habits, and hand grip and provided patients with appropriate feedback. These measures were performed before the hemodialysis session. Laboratory Data and dialysis status were also collected. Participants were tracked for three years after their first physical function assessment to determine their attendance rate. Patients were provided with four opportunities for participation, including the initial assessment. The program's participation rate was defined as the number of program sessions in which the patient actually participated and the percentage (%) of the four physical functioning assessment visits attended. Patients were then divided into a continuation group (&amp;gt; 50% participation, including the initial assessment) and a dropout group (≤ 50% participation, including the initial assessment). Multivariate logistic regression analyses were used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) for the continuation group to determine the predictors of dropout from the physical function assessment program. Ethical approval was provided by Seirei Sakura Citizen Hospital,and written informed consent. Results A total of 230 patients receiving outpatient HD were invited to participate in the study. Among these, 78 patients refused to participate, 45 participants died or changed clinic within three years of obtaining baseline measurements, and six patients had missing data. Therefore, the final analysis included 101 patients undergoing HD. The continuation and dropout groups included 43 and 58 patients, respectively. SE (continuation: 13.0 ± 4.3 points; dropout: 9.8 ± 4.8 points) and age (continuation: 65.7 ± 10.4 years; dropout: 61.2 ± 12.2 years) were significantly higher in the continuation group than in the dropout group (p = 0.001, p = 0.047, respectively). Multivariate logistic regression analyses indicated that only SE (OR: 1.192, 95% CI: 1.088–1.319) remained a significant predictor after adjustment (p &amp;lt; 0.05). Conclusion Our data demonstrate that exercise-related SE and age significantly influenced dropout from the physical function assessment program; in particular, SE was a strong predictor of dropout, possibly because the patients with high SE may have had positive feelings about exercise based on previous experience. The older patients may have had a smaller social circle and more time to spare and been more aware of their health and desires. There is a need to evaluate SE to prevent dropout from physical functioning assessment programs. Interventions designed to enhance exercise-related SE may improve program retention among patients with HD.

Matching research and practice: Prediction of individual patient progress and dropout risk for basic routine outcome monitoring

Objective Despite evidence showing that systematic outcome monitoring can prevent treatment failure, the practical conditions that allow for implementation are seldom met in naturalistic psychological services. In the context of limited time and resources, session-by-session evaluation is rare in most clinical settings. This study aimed to validate innovative prediction methods for individual treatment progress and dropout risk based on basic outcome monitoring. Methods Routine data of a naturalistic psychotherapy outpatient sample were analyzed (N = 3902). Patients were treated with cognitive behavioral therapy with up to 95 sessions (M = 39.19, SD = 16.99) and assessment intervals of 5–15 sessions. Treatment progress and dropout risk were predicted in two independent analyses using the nearest neighbor method and least absolute shrinkage and selection operator regression, respectively. Results The correlation between observed and predicted patient progress was r = .46. Intrinsic treatment motivation, previous inpatient treatment, university-entrance qualification, baseline impairment, diagnosed personality disorder, and diagnosed eating disorder were identified as significant predictors of dropout, explaining 11% of variance. Conclusions Innovative outcome prediction in naturalistic psychotherapy is not limited to elaborated progress monitoring. This study demonstrates a reasonable approach for tracking patient progress as long as session-by-session assessment is not a valid standard.

Internet-based cognitive and behavioural therapies for post-traumatic stress disorder (PTSD) in adults.

Internet-based cognitive and behavioural therapies for post-traumatic stress disorder (PTSD) in adults.

Therapist Interventions and Skills as Predictors of Dropout in Outpatient Psychotherapy

The current study employed machine learning to investigate whether the inclusion of observer-rated therapist interventions and skills in early sessions of psychotherapy improved dropout prediction beyond intake assessments. Patients were treated by postgraduate clinicians at a university outpatient clinic. Psychometric instruments were assessed at intake and therapeutic interventions and skills in the third session were routinely rated by independent observers. After variable preselection, an elastic net algorithm was used to build two dropout prediction models, one including and one excluding observer-rated session variables. The best model included observer-rated variables and was significantly superior to the model including intake variables only. Alongside intake variables, two observer-rated variables significantly predicted dropout: therapist use of feedback and summaries and treatment difficulty. Although not retained in the final prediction model, the observer-rated use of cognitive techniques was also significantly correlated with dropout. Observer ratings of therapist interventions and skills in early sessions of psychotherapy improve predictors of dropout from psychotherapy beyond intake variables alone. Future research could work toward personalizing dropout predictions to the specific dyad, thereby improving their validity and aiding therapists to recognize and react to increased dropout risk.

737 Prediction of drop out in an adjunctive light treatment trial in patients with non-seasonal depression and evening chronotype

Abstract Introduction Drop out during treatment hampers therapeutic effect of interventions. The current study examines the possible predictors of drop out during the five-week light treatment in patients with unipolar non-seasonal depression and evening-chronotype. Methods Baseline characteristics including demographics, sleep diary parameters, light treatment prescribed, and early clinical outcomes changes were compared between the Drop out and Non drop out group. Logistic regression analysis was used to examine predictors for drop out. All data were analyzed in a modified intention to treat analysis with last observation carried forward approach. Results A total of 91 subjects (Female 79%, 46.3 ± 11.8 years old) were included in the analysis. There was no significant difference in the baseline demographic and clinical characteristics between the Drop out and Non drop out group. There was also no significant difference in the improvement of clinical parameters over the first week among the two groups. However, treatment non-adherence (in terms of compliance of less than 80% of prescribed duration) over the first treatment week predicts a five-fold increase in risk of drop out during light therapy. (OR: 5.85, CI: 1.414–24.205, p=0.015) after controlling for potential confounders including age, gender, treatment group, patient expectation, and treatment-emergent adverse events. Conclusion This study found that baseline clinical characteristics including depression severity and improvement of depressive symptoms in the initial week did not differ between the Drop out and Non drop out group. The drop out was also not affected by the type of light (dim red versus bright red light), indirectly supporting dim red light as a valid placebo in bright light therapy trial. Treatment adherence is the early phase of light treatment is an important predictor of drop out. Support (if any):

366 Predictors of Dropout in University Students Participating in an 8-week E-mail Based Cognitive Behavioral Therapy for Insomnia

Abstract Introduction As dropout from treatment potentially diminishes its therapeutic effect and poses clinical concern, it is important to find out which characteristics of participants are suitable for online-based treatment. Therefore, we aimed to identify factors that predicted a dropout in the e-mail based cognitive behavioral therapy (REFRESH) developed by Stanford University for the purpose of psychological intervention for insomnia. Methods Participants who participated in the REFRESH program consisted of 158 university and graduate students aged 18 to 30 in Hong Kong and Korea who scored higher than 10 on the Insomnia Severity Index (ISI), and the intervention was delivered in 8 weekly sessions sent via weekly e-mails. Among them, 110 were women (70%) and the average age was 22 (±2.71) years old. All participants were asked to answer the following self-reporting questionnaires before and after the intervention: Insomnia Severity Index; ISI, Depression Anxiety Stress Scale 21; DASS-21, Sleep Hygiene Practice Scale; SHPS, Dysfunctional Beliefs and Attitude about Sleep 16; DBAS-16. Descriptive statistics and ROC decision tree analysis were conducted to address our aim. Results Of the 158 participants, 68 completed the program, and 90 participants (57%) dropped out. The best predictor of dropout was DASS score with an optimal cup-point of &amp;lt;34. Of the 107 participants who reported DASS &amp;lt;30, 70(65.4%) dropped out. In contrast, of the 50 participants who reported DASS ≥34, 12(38%) dropped out. The second-level predictor was expectations for sleep score with a cut-point of &amp;lt;18. Among participants with DASS &amp;lt;34 and expectations for sleep score &amp;lt;18, 57(73.1%) dropped out. Of the 29 participants who reported DASS &amp;lt;34 and expectations for sleep score ≥18, 13(44.8%) dropped out. Conclusion Mild levels of depression, anxiety and stress and expectations for sleep appear to be predictive of dropout in an e-mail based intervention. People with mild symptoms may experience less distress and impairment, which may result in lower motivation to receive treatment. This may lead to inability to complete treatment and higher rates of dropout. Support (if any):

The Role of Personality Functioning on Early Drop out in Outpatient Substance Misuse Treatment

Background Treatment initiation is a major factor contributing to positive outcomes, but the supporting literature remains limited. It is difficult to draw conclusions regarding predictors of dropout, and there is a need to target clients’ major early attrition vulnerabilities. Despite empirically validated models for assessing personality, little is known about its role in the treatment process. Studies that have been conducted in this area have focused mainly on stable personality traits and provide conflicting evidence. Aims: The aim of this study is to examine to what extent service users’ personality functioning are potential determinants of early drop out. Methodology: A cross-sectional multi-site design examined the therapy process in a naturalistic setting in 5 outpatient preparation treatment centers with 210 service users. The current study adopts a contemporary dimensional-based framework, similar to the Alternative Model of Personality Disorder of the DSM-V and examines the role of characteristic adaptations (SIPP-118) on early drop out (CEST-Intake). Findings: From the broad spectrum of personality traits, only Depression remained significant predictor of drop out. Higher dysfunctional levels in Social Concordance [OR] = 1.85, Wald =19.87, p =.002, 95% CI [1.1, 1.9] as well as the facets Aggression Regulation, Respect and Purposefulness were also predictors of early drop out, while Treatment Readiness and Desire for Help accounted for a significant amount of variance. Conclusions: These findings extend our knowledge of the predictive role of characteristic adaptations in treatment and suggest it may be important to assess these individual differences early on and to design personalized-informed interventions.