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Poor adherence to asthma controller medications results in poor treatment outcomes. To compare controller medication adherence and clinical outcomes in 612 adults with poorly controlled asthma randomized to one of two different treatment decision-making models or to usual care. In shared decision making (SDM), nonphysician clinicians and patients negotiated a treatment regimen that accommodated patient goals and preferences. In clinician decision making, treatment was prescribed without specifically eliciting patient goals/preferences. The otherwise identical intervention protocols both provided asthma education and involved two in-person and three brief phone encounters. Refill adherence was measured using continuous medication acquisition (CMA) indices-the total days' supply acquired per year divided by 365 days. Cumulative controller medication dose was measured in beclomethasone canister equivalents. In follow-up Year 1, compared with usual care, SDM resulted in: significantly better controller adherence (CMA, 0.67 vs. 0.46; P < 0.0001) and long-acting beta-agonist adherence (CMA, 0.51 vs. 0.40; P = 0.0225); higher cumulative controller medication dose (canister equivalent, 10.9 vs. 5.2; P < 0.0001); significantly better clinical outcomes (asthma-related quality of life, health care use, rescue medication use, asthma control, and lung function). In Year 2, compared with usual care, SDM resulted in significantly lower rescue medication use, the sole clinical outcome available for that year. Compared with clinician decision making, SDM resulted in: significantly better controller adherence (CMA, 0.67 vs. 0.59; P = 0.03) and long-acting beta-agonist adherence (CMA, 0.51 vs. 0.41; P = 0.0143); higher cumulative controller dose (CMA, 10.9 vs. 9.1; P = 0.005); and quantitatively, but not significantly, better outcomes on all clinical measures. Negotiating patients' treatment decisions significantly improves adherence to asthma pharmacotherapy and clinical outcomes. Clinical trials registered with www.clinicaltrials.gov (NCT00217945 and NCT00149526).

ObjectiveTo evaluate the efficacy of the Patient Reporting and Action for a Safe Environment intervention.DesignA multicentre cluster randomised controlled trial.SettingClusters were 33 hospital wards within five hospitals in the UK.ParticipantsAll patients able to give informed consent were eligible to take part. Wards were allocated to the intervention or control condition.InterventionThe ward-level intervention comprised two tools: (1) a questionnaire that asked patients about factors contributing to safety (patient measure of safety (PMOS)) and (2) a proforma for patients to report both safety concerns and positive experiences (patient incident reporting tool). Feedback was considered in multidisciplinary action planning meetings.MeasurementsPrimary outcomes were routinely collected ward-level harm-free care (HFC) scores and patient-level feedback on safety (PMOS).ResultsIntervention uptake and retention of wards was 100% and patient participation was high (86%). We found no significant effect of the intervention on any outcomes at 6 or 12 months. However, for new harms (ie, those for which the wards were directly accountable) intervention wards did show greater, though non-significant, improvement compared with control wards. Analyses also indicated that improvements were largest for wards that showed the greatest compliance with the intervention.LimitationsAdherence to the intervention, particularly the implementation of action plans, was poor. Patient safety outcomes may represent too blunt a measure.ConclusionsPatients are willing to provide feedback about the safety of their care. However, we were unable to demonstrate any overall effect of this intervention on either measure of patient safety and therefore cannot recommend this intervention for wider uptake. Findings indicate promise for increasing HFC where wards implement ≥75% of the intervention components.Trial registration numberISRCTN07689702; pre-results.

Cancer is a disease of aging and, as the world's population ages, the number of older persons with cancer is increasing and will make up a growing share of the oncology population in virtually every country. Despite this, older patients remain vastly underrepresented in research that sets the standards for cancer treatments. Consequently, most of what we know about cancer therapeutics is based on clinical trials conducted in younger, healthier patients, and effective strategies to improve clinical trial participation of older adults with cancer remain sparse. For this systematic review, the authors evaluated published studies regarding barriers to participation and interventions to improve participation of older adults in cancer trials. The quality of the available evidence was low and, despite a literature describing multifaceted barriers, only one intervention study aimed to increase enrollment of older adults in trials. The findings starkly amplify the paucity of evidence-based, effective strategies to improve participation of this underrepresented population in cancer trials. Within these limitations, the authors provide their opinion on how the current cancer research infrastructure must be modified to accommodate the needs of older patients. Several underused solutions are offered to expand clinical trials to include older adults with cancer. However, as currently constructed, these recommendations alone will not solve the evidence gap in geriatric oncology, and efforts are needed to meet older and frail adults where they are by expanding clinical trials designed specifically for this population and leveraging real-world data.

PurposeTo compare patients’ evaluation of the treatment decision-making process in localized prostate cancer between counseling that included an online decision aid (DA) and standard counseling.MethodsEighteen Dutch hospitals were randomized to DA counseling (n = 235) or the control group with standard counseling (n = 101) in a pragmatic, cluster randomized controlled trial. The DA was provided to patients at, or soon after diagnosis. Decisional conflict, involvement, knowledge, and satisfaction with information were assessed with a questionnaire after treatment decision-making. Anxiety and depression served as covariates.ResultsThe levels of decision involvement and conflict were comparable between patients in both groups. Patients with a DA felt more knowledgeable but scored equally well on a knowledge test as patients without a DA. Small significant negative effects were found on satisfaction with information and preparation for decision-making. A preference for print over online and depression and anxiety symptoms was negatively associated with satisfaction and conflict scores in the DA group.DiscussionThe DA aimed to support shared decision-making, while outcomes for a majority of DA users were comparable to patients who received standard counseling. Patients, who are less comfortable with the online DA format or experience anxiety or depression symptoms, could require more guidance toward shared decision-making. To evaluate long-term DA effects, follow-up evaluation on treatment satisfaction and decisional regret will be done.

\"Now fully-revised and updated, this second edition of ACT Made Simple includes new information and chapters on self-compassion, flexible perspective taking, working with trauma, and more. Why is it so hard to be happy? Why is life so difficult? Why do humans suffer so much? And what can we realistically do about it? No matter how rewarding your job, as a mental health professional, you may sometimes feel helpless in the face of these questions. You are also well aware of the challenges and frustrations that can present during therapy. If you're looking for ways to optimize your client sessions, consider joining the many thousands of therapists and life coaches worldwide who are learning acceptance and commitment therapy (ACT). With a focus on mindfulness, client values, and a commitment to change, ACT is proven-effective in treating depression, anxiety, stress, addictions, eating disorders, schizophrenia, borderline personality disorder (BPD), and myriad other psychological issues. It's also a revolutionary new way to view the human condition--packed full of exciting new tools, techniques, and strategies for promoting profound behavioral change. A practical primer, ideal for ACT newcomers and experienced ACT professionals alike, ACT Made Simple offers clear explanations of the six ACT processes and a set of real-world tips and solutions for rapidly and effectively implementing them in your practice. This book gives you everything you need to start using ACT with your clients for impressive results. Inside, you'll find: scripts, exercises, metaphors, and worksheets to use with your clients; a session-by-session guide to implementing ACT; transcripts from therapy sessions; guidance for creating your own therapeutic techniques and exercises; and practical tips to overcome \"therapy roadblocks.\" This book aims to take the complex theory and practice of ACT and make it accessible and enjoyable for therapists and clients\"-- Provided by publisher.

There is mixed evidence to support current ambitions for mobile health (mHealth) apps to improve chronic health and well-being. One proposed explanation for this variable effect is that users do not engage with apps as intended. The application of analytics, defined as the use of data to generate new insights, is an emerging approach to study and interpret engagement with mHealth interventions. This study aimed to consolidate how analytic indicators of engagement have previously been applied across clinical and technological contexts, to inform how they might be optimally applied in future evaluations. We conducted a scoping review to catalog the range of analytic indicators being used in evaluations of consumer mHealth apps for chronic conditions. We categorized studies according to app structure and application of engagement data and calculated descriptive data for each category. Chi-square and Fisher exact tests of independence were applied to calculate differences between coded variables. A total of 41 studies met our inclusion criteria. The average mHealth evaluation included for review was a two-group pretest-posttest randomized controlled trial of a hybrid-structured app for mental health self-management, had 103 participants, lasted 5 months, did not provide access to health care provider services, measured 3 analytic indicators of engagement, segmented users based on engagement data, applied engagement data for descriptive analyses, and did not report on attrition. Across the reviewed studies, engagement was measured using the following 7 analytic indicators: the number of measures recorded (76%, 31/41), the frequency of interactions logged (73%, 30/41), the number of features accessed (49%, 20/41), the number of log-ins or sessions logged (46%, 19/41), the number of modules or lessons started or completed (29%, 12/41), time spent engaging with the app (27%, 11/41), and the number or content of pages accessed (17%, 7/41). Engagement with unstructured apps was mostly measured by the number of features accessed (8/10, P=.04), and engagement with hybrid apps was mostly measured by the number of measures recorded (21/24, P=.03). A total of 24 studies presented, described, or summarized the data generated from applying analytic indicators to measure engagement. The remaining 17 studies used or planned to use these data to infer a relationship between engagement patterns and intended outcomes. Although researchers measured on average 3 indicators in a single study, the majority reported findings descriptively and did not further investigate how engagement with an app contributed to its impact on health and well-being. Researchers are gaining nuanced insights into engagement but are not yet characterizing effective engagement for improved outcomes. Raising the standard of mHealth app efficacy through measuring analytic indicators of engagement may enable greater confidence in the causal impact of apps on improved chronic health and well-being.