Applied psychology. Health and well-being最新文献

Physical activity (PA) and sedentary behavior (SB) are associated with affective feeling states in older adults, though the strength and direction of associations vary. This study used the Ecological Momentary Assessment (EMA) to determine how habit strength affects affective responses to movement behaviors. Older adults completed a 4-day EMA protocol with 10 randomly delivered, smartphone assessments per day while simultaneously wearing two activity monitors recording PA and SB. Multilevel models assessed whether habit strength moderated positive and negative activated and deactivated affective responses following movement behaviors. Older adults with stronger PA habits had a more positive within-person association between steps in the 30 minutes before the prompt and positive deactivated affect at the prompt compared to older adults with weaker PA habits (B = 0.001, p < 0.05). Older adults with stronger SB habits had a more positive within-person association between time spent sitting in the 30 and 60 minutes before the prompt and negative activated affect at the prompt compared to older adults with weaker SB habits (30 min: B = 0.001, p < 0.05; 60 min: B = 0.001, p < 0.05). PA habits may enhance positive affective responses to PA further encouraging engagement in PA, while SB habits exacerbate negative affective responses to SB in older adults.

The aim of the study was to examine the effects of online self-management training on self-management, emotion regulation, and occupational balance in young adults with chronic diseases. Young people participated in this cluster randomized controlled trial (n = 72; mean age, 20.80 ± 2.65 years). Eight sessions of self-management training were applied in the study group (SG; n = 37), and one session was applied in the control group (CG; n = 35). To evaluate the training, all participants completed the Self Management-Self Control Scale, Cognitive Emotion Regulation (CERQ), and Occupational Balance Questionnaire at the beginning and end of the training. We performed an analysis of covariance (ANCOVA). In cases where ANCOVA assumptions could not be met, the efficacy of the intervention was determined using the mixed design/split-plot analysis of variance. Compared to the CG, SG showed a significant increase in self-management skills. For the CERQ variable, it was observed that there was no significant difference between the study and control group mean differences after the intervention. Occupational balance remained similar between the groups. The self-management training can have a positive impact on the development of their self-management, particularly in chronic conditions.

Commuting to work is often a highly habitual behavior that people perform automatically over a long period of time. Substituting an inactive with a more active commuting habit might thus support long-term behavior change. This study investigated habit substitution processes in commuting behavior and related psychological determinants. We report primary analyses of an online planning intervention study conducted in Germany with a one-arm pre-post design over 14 weeks including multiple-a-day workday assessments across a baseline week followed by five post-intervention measurement weeks. Forty-two participants (60% female, M_age = 32.3 years) reported daily automaticity, experienced reward and regret, and weekly plan enactment for new and old commuting behaviors. Multilevel models were fit. In this one-arm study, automaticity of the old commuting behavior declined linearly, whereas the increase in automaticity of the new commuting behavior was more pronounced in earlier than later study weeks. Within-person plan enactment and experienced reward were positively linked with automaticity of the new commuting behavior. Between-person plan enactment was negatively linked with automaticity of the old commuting behavior. Weekly plan enactment and outcome experiences were associated with increases of new habits and decay of old habits in this study. Results warrant replication using an experimental design.

The Benefit-Finding Intervention, a face-to-face psychoeducation program with a focus on the positive meanings of caregiving, has been found to reduce depressive symptoms and burden in dementia caregivers. The program was revamped into a computer-delivered web-based program to enable 24/7 access without location restriction. This study evaluates the efficacy of this new online program called Positive Dementia Caregiving in 30 Days (PDC30). A 2-arm (PDC30 vs. waitlist control) parallel-group randomized controlled trial will be conducted. Target sample is 200 mildly depressed dementia family caregivers with internet access and fluency in English, who will be recruited globally through a YouTube video promoted on social media and through service agencies. The primary outcome is depressive symptoms whereas secondary outcomes are anxiety symptoms, burden, and positive gains, all collected at baseline and 1, 2, and 3 months. The treatment x time (both linear and quadratic) interaction effects will be examined using mixed-effect regression. Additionally, possible therapeutic mechanisms via strengthened self-efficacy in controlling upsetting thoughts and positive reappraisal coping will be examined in a mediation path model. If positive treatment effects are found, the potential public health benefits, given the ease of access, universal availability, and flexible approach, of this online intervention are considerable.

Behavioral intentions predict behavior better if they are stable over time. A statistical argument suggests that this is due to less measurement error, but recent theoretical advances suggest self-regulatory effects: durable intentions remain temporally stable due to their persistence when faced with challenges. Here, we leverage intensive longitudinal data on adherence with non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic (N = 623; total assessments = 19,740; study duration: 6 months each). We operationalize intention durability as temporal order-dependent variability (reversed root mean square of successive differences [RMSSD] between each valid assessment). We then examine the within- and between-person moderating effects of intention durability on the intention-behavior association as well as the effects of past on current behavior. In line with the theoretical assumptions, we find that more durable intentions are not only associated with a stronger intention-behavior link on a within- and a between-person level but also a stronger effect of past on current adherence with NPIs. Our findings support the hypothesized moderating effects of intention durability and provide a more nuanced understanding of the self-regulatory processes underlying the temporal stability of intentions.

While previous studies have examined the independent effect of self-compassion or compassion for others on well-being, the present study examined how self-compassion may interact with compassion for others in predicting well-being. Two studies were conducted. In Study 1, 457 participants completed assessments at baseline and 229 participants were retained and completed the assessment at 4-month follow-up. Results showed that baseline self-compassion predicted higher levels of subsequent well-being when baseline compassion for others was moderate or high. Study 2 recruited 147 participants and they were assigned to either the self-compassion condition or the control condition. Results showed that participants who practiced self-compassion for 1 week in the self-compassion condition showed more reduction in negative affect than the control condition when baseline compassion for others was high. Findings showed that the effects of compassion for the self on one's well-being may be contingent on one's compassion for others.

Theoretically, self-control can be considered as both a facilitator of habit development and a moderator of whether behavior occurs habitually. However, debate remains on the contexts in which such relationships are likely to occur. The current study tested whether self-control, conceptualized into inhibitory and initiatory facets, would predict healthy behavior via habits or moderate the habit-behavior relationship, and whether these effects differed across complex (bootcamp attendance N = 69, physical activity in pregnant women N = 115) and simple (flossing N = 254) behaviors. Three independent samples completed measures of self-control and habit, followed by a prospective measure of behavior. Data were fitted to PLS-SEM models. Inhibitory and initiatory self-control predicted habit in all three samples, and habit in turn predicted each health behavior. Inhibitory self-control only moderated the effect of habit in the bootcamp and physical activity samples. Initiatory self-control did not moderate effects in any sample. Findings indicate that both initiatory and inhibitory self-control are associated with habit. Further, as the moderating effect of inhibitory self-control was only present in the complex behavior samples, results suggest the moderating effects of self-control on the habit-behavior relationship may be best represented by the effect of inhibiting competing cues from disrupting automatically activated behavioral sequences.

Reactivity to physical activity (PA) measurement may result from the introduction of a measurement device, researcher observation, or both. Accessing data from prior to study enrollment afforded the rare opportunity to compare behavior during versus prior to participation. This study introduced researcher observation among adults who owned their own PA monitoring device, to test whether measurement reactivity can also be observed in experienced PA trackers, by comparing their data from before versus after the introduction of observation. In addition, the salience of researcher observation was manipulated to test for potential effects. Participants were 252 adults in the U.S. They completed two electronic surveys 14 days apart, in which they recorded steps per day as collected by their PA monitors over the previous 14 days. At the end of the first survey, they were randomized to view messages, which differed in emphasis on repeating entry of step data (i.e., “low” vs. “high” salience of researcher observation). Daily step counts did not change between 14-day reporting periods, though patterns differed by gender and starting level of PA. Patterns did not differ between experimental conditions. Overall, introducing researcher observation without introducing an unfamiliar measurement device results in no meaningful reactivity with respect to PA.

Negative emotions such as loneliness, depression, and anxiety (LDA) are prevalent and pose significant challenges to emotional well-being. Traditional methods of assessing LDA, reliant on questionnaires, often face limitations because of participants' inability or potential bias. This study introduces emoLDAnet, an artificial intelligence (AI)-driven psychological framework that leverages video-recorded conversations to detect negative emotions through the analysis of facial expressions and physiological signals. We recruited 50 participants to undergo questionnaires and interviews, with their responses recorded on video. The emoLDAnet employs a combination of deep learning (e.g., VGG11) and machine learning (e.g., decision trees [DTs]) to identify emotional states. The emoLDAnet incorporates the OCC–PAD–LDA psychological transformation model, enhancing the interpretability of AI decisions by translating facial expressions into psychologically meaningful data. Results indicate that emoLDAnet achieves high detection rates for loneliness, depression, and anxiety, with F1-scores exceeding 80% and Kendall's correlation coefficients above 0.5, demonstrating strong agreement with traditional scales. The study underscores the importance of the OCC–PAD–LDA model in improving screening accuracy and the significant impact of machine learning classifiers on the framework's performance. The emoLDAnet has the potential to support large-scale emotional well-being early screening and contribute to the advancement of mental health care.