OBJECTIVE: This systematic review examined the components of pharmacists-delivered COPD self-management interventions according to an established taxonomy of behaviour change techniques (BCTs).
METHODS: A systematic search was conducted on PubMed, ScienceDirect, OVID, and Google Scholar from January 2011 to December 2021 for studies of pharmacist-delivered self-management interventions in COPD patients.
RESULTS: A total of seventeen studies of intervention were eligible for inclusion in the narrative review. Interventions were educational and were delivered individually and face-to-face for the first session. Across studies, pharmacists spent an average of 35 min on the first meeting and had an average of 6 follow-up sessions. Recurrent BCTs in pharmacist interventions were "Information on the health consequence", "Feedback on behaviour", "Instruction on how to perform a behaviour", "Demonstration of the behaviour" and "Behavioural practice/rehearsal".
CONCLUSIONS: Pharmacists have provided interventions towards improving health behaviours, especially on adherence and usage of inhaler devices for patients with COPD. Future self-management interventions should be designed using the identified BCTs for the improvement of COPD self-management and disease outcomes.
AIM: This review had three aims: first, to identify the outcome measures (OMs) reported in trials of dental behavior support; second, to categorize the component DBS techniques reported within interventions according to emerging agreed terminology; and, third, to map outcome measures to intervention type.
METHODS: A scoping review of trials evaluating DBS techniques was undertaken from 2012 to 2022. The review was prospectively registered. Studies were identified through Medline, Embase, and PsycINFO. Study abstracts were screened by two reviewers. Data were extracted by single selector. Outcome measures were sorted according to measurement domains (physiological, behavioral, psychological, and treatment). Responses were assimilated and summed to produce a refined list of distinguishable outcome measures. Intervention types were categorized according to accepted descriptors. Frequencies were presented; associations between outcome domain and DBS type were also reported (Chi-square test of independence).
RESULTS: A total of 344 trials were included in the review from an initial 14,793 titles / title and abstracts screened. Most involved children (n = 215), most were from India (n = 104), involving basic dental care (n = 117). The median number of outcome measures per trial was four (range = 1-12); 1,317 individual outcomes were reported, categorized as: psychological (n = 501, 38.0%); physiological (n = 491, 37.3%), behavioral (n = 123, 9.3%) or, treatment-related (n = 202, 15.3%). DBS interventions were split between 239 (45.7%) pharmacological and 283 (54.1%) non-pharmacological; 96.6% of interventions mapped to accepted descriptors. A significant relationship was noted between the type of intervention and the outcome domain reported.
CONCLUSION: The findings demonstrate massive variation in outcome measures of DBS interventions that likely lead to unnecessary heterogeneity, selective reporting, and questionable relevance in the literature. A large range of DBS interventions were mapped according to BeSiDe list. There is a need for consensus on a core outcome set across the spectrum of DBS techniques.
MATERIALS AND METHODS: A total of 60 inpatient substance abusers post detoxification in Fountain House, Lahore, Pakistan, participated in this study. Fountain House was selected as the Minnesota model is primarily used there. Therefore, a new treatment approach was introduced to investigate its effectiveness for individuals with substance abuse. A randomized 12-week trial was conducted as a substance use disorders (SUDs) treatment program. Persons with SUD (i.e., identified patients) enrolled in a residential treatment program were randomized into the integrated model of the Community Reinforcement Approach (CRA) and traditional Minnesota model treatment (n = 30), and traditional Minnesota model treatment only (TMM; n = 30). All the participants in the experimental group attended the group therapy sessions and other activities in the facility in addition to the treatment conditions. The participants attended the individual therapeutic sessions, which were conducted according to the CRA guidelines used in the experimental group. In this study, each individual in the CRA treatment group received 12 one-to-one sessions ranging from 45 min to 1 h. The WHOQOL-BREF scale and Happiness Scale (1) were used for data collection.
RESULT: The results showed a significant increase in the quality of life of participants in the treatment group with CRA compared with the control group with TMM. The findings also indicated that the individuals in the treatment group with CRA had improved levels of happiness compared with individuals with TMM.
DISCUSSION: The CRA is an effective and adaptable treatment approach that works well in combination with other treatment approaches. The proven efficacy, compatibility, and cost-effectiveness distinguish it from other treatment methods.
IMPLICATIONS: The CRA should be adapted, assessed, and evaluated further, especially in Pakistan, where there is a pressing need to adopt an effective treatment strategy for addiction problems.
METHODS: This study examined self-monitoring data from 61 Chinese adults who participated in a 5-week online group intervention for weight loss. Participants reported their baseline Body Mass Index (BMI), weight loss motivation, and engaged in both daily quantitative self-monitoring (e.g., caloric intake, mood, sedentary behavior, etc.) and qualitative self-monitoring (e.g., daily log that summarizes the progress of weight loss). The timeliness of participants' daily self-monitoring data filling was assessed using a scoring rule. One-way repeated measurement ANOVA was employed to analyze the dynamics of each self-monitoring indicator. Correlation and regression analyses were used to reveal the relationship between baseline data, self-monitoring indicators, and weight change. Content analysis was utilized to analyze participants' qualitative self-monitoring data. Participants were categorized into three groups based on their weight loss outcomes, and a chi-square test was used to compare the frequency distribution between these groups.
RESULTS: After the intervention, participants achieved an average weight loss of 2.52 kg (SD = 1.36) and 3.99% (SD = 1.96%) of their initial weight. Daily caloric intake, weight loss satisfaction, frequency of daily log, and the speed of weight loss showed a downward trend, but daily sedentary time gradually increased. Moreover, regression analysis showed that baseline BMI, weight loss motivation, and timeliness of daily filling predicted final weight loss. Qualitative self-monitoring data analysis revealed four categories and nineteen subcategories. A significant difference in the frequency of qualitative data was observed, with the excellent group reporting a greater number of daily logs than expected in all categories and most subcategories, and the moderate and poor groups reporting less than expected in all categories and most subcategories.
CONCLUSION: The self-monitoring data in short-term online group intervention exhibited fluctuations. Participants with higher baseline BMI, higher levels of weight loss motivation, and timely self-monitoring achieved more weight loss. Participants who achieved greater weight loss reported a higher quantity of qualitative self-monitoring data. Practitioners should focus on enhancing dieters' weight loss motivation and promote adherence to self-monitoring practices.
METHODS: A search for economic evaluation studies was conducted from inception to 30 September 2022, on PubMed, Embase, Cost-Effectiveness Analysis (CEA) Registry by Tufts Medical Centre, EconLit and the NHS Economic Evaluation Database (NHS EED). Eligible studies were included if they were (1) conducted among adults ages 18 years old and older who were smokers attempting to quit for the first time; (2) compared varenicline to behaviour support with bupropion or NRT, behaviour support alone and unaided cessation; and (3) performed a CEA or cost-utility analysis. The INBs were calculated and pooled across studies stratified by country income level and study perspective using the random-effects model. Statistical heterogeneity between studies was assessed using the I2 statistic and Cochrane Q statistic.
RESULTS: Of the 1433 identified studies, 18 studies were included in our review. Our findings from healthcare system/payer perspective suggested that the use of varenicline is statistically significantly cost-effective compared with bupropion (pooled INB, $830.75 [95% confidence interval, $208.23, $1453.28]), NRTs ($636.16 [$192.48, $1079.84]) and unaided cessation ($4212.35 [$1755.79, $6668.92]) in high-income countries. Similarly, varenicline is also found to be cost-effective compared to bupropion ($2706.27 [$1284.44, $4128.11]), NRTs ($3310.01 [$1781.53, $4838.50]) and behavioural support alone ($5438.22 [$4105.99, $6770.46]) in low- and middle-income countries.
CONCLUSION: Varenicline is cost-effective as a smoking cessation aid when compared with behavioural support with bupropion or nicotine replacement therapies and behavioural support alone in both high-income countries and low- and middle-income countries, from the healthcare system/payer perspective in adult smokers who attempt to quit for the first time.
METHODS AND FINDINGS: We recruited 280 adults from 27 post-outbreak villages in the state of Terengganu, east coast of Malaysia. Measures of health promotion and educational intervention activities and types of communication during outbreak, level of dengue knowledge, level and strength of self-efficacy and dengue preventive behaviour were obtained via face-to-face interviews and questionnaires. A structural equation model was tested and fitted the data well (χ(2) = 71.659, df = 40, p = 0.002, RMSEA = 0.053, CFI = 0.973, TLI = 0.963). Mass media, local contact and direct information-giving sessions significantly predicted level of knowledge of dengue. Level and strength of self-efficacy fully mediated the relationship between knowledge of dengue and dengue preventive behaviours. Strength of self-efficacy acted as partial mediator in the relationship between knowledge of dengue and dengue preventive behaviours.
CONCLUSIONS: To control and prevent dengue outbreaks by behavioural measures, health promotion and educational interventions during outbreaks should now focus on those approaches that are most likely to increase the level and strength of self-efficacy.
METHOD: Six medicated children (five boys, one girl; aged 6-12 years) with ADHD participated in a 4-week sleep intervention program. The main behavioral strategies used were Faded Bedtime With Response Cost (FBRC) and positive reinforcement. Within a case-series design, objective measure (Sleep Disturbance Scale for Children [SDSC]) and subjective measure (sleep diaries) were used to record changes in children's sleep.
RESULTS: For all six children, significant decrease was found in the severity of children's sleep problems (based on SDSC data). Bedtime resistance and mean sleep onset latency were reduced following the 4-week intervention program according to sleep diaries data. Gains were generally maintained at the follow-up. Parents perceived the intervention as being helpful.
CONCLUSION: Based on the initial data, this intervention shows promise as an effective and feasible treatment.
METHODS: This was a randomized controlled parallel-group trial in which 372 antenatal care attendees were randomly assigned to either an intervention or control group after collecting baseline data using a structured questionnaire. The intervention group received a 4-h health education on malaria, guided by a module developed based on the IMB theory, while the control group received health education on breastfeeding for a similar duration and by the same facilitator. Follow-up data were subsequently collected at 2 months and at 4 months post-intervention using the same questionnaire. The generalized linear mixed models analysis was used to determine the between-group and within-group effects of the intervention. The intention-to-treat analysis was used after missing data had been replaced. This was followed by a sensitivity analysis, where the analyses were repeated without replacing the missing values.
RESULTS: The intervention was significant in achieving a 12.75% (p