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The sequence effect improved on open and closed-loop STN DBS | PD | One of the debilitating features of the sequence effect in PD is that it does not improve on levodopa or during repetitive transmagnetic stimulation (rTMS) [ | PMC10357155 | |
Neural basis of the sequence effect and potential mechanism for the therapeutic effect of DBS | Several studies suggest that the sequence effect may arise from pathological neural activity in cortical, subcortical and cerebellar circuitry that contribute to central drive, motor sequencing, sensorimotor integration, timing cues, and updating of the motor set [ | PMC10357155 | ||
Limitations | PD, bradykinesia | DISEASE, PATHOPHYSIOLOGY | The experiments were all performed off medication and thus we cannot assert whether or not medication improved the sequence effect of this particular task, calculated by this metric. The study was focused on a novel metric of the sequence effect, its validation as a measure of bradykinesia and overall PD disease severity, and the effect of DBS. The correlations with bradykinesia and MDS-UPDRS III were performed before activation of DBS. To answer whether the sequence effect became worse over time and to examine the effect of DBS on the sequence effect, testing began after withdrawal of DBS for at least 60 min. After turning off STN DBS we have demonstrated that the resting state local field potential spectrum, and specifically beta band power, was stable and unchanged among recordings performed immediately (14 s) and every 15 min up to 60 min later, suggesting that this is enough time to wash out the effect of DBS on underlying pathophysiology [An additional limitation is the presence of study dropout for the longitudinal OFF therapy protocol. Dropout was due to a combination of IPG replacement to a non-research device following battery depletion, moving out of state, or progression of disease that made OFF therapy testing intolerable. Due to their ability to account for missing data due to the participant dropout, linear mixed effect models were used in the analysis. Additionally, study exits prior to 3 years do not bias the results because participants are typically exiting the study once their bradykinesia has worsened so much that they are unable to perform the WFE task. These participants remaining in the study would have pushed the results even further in favor of the observed conclusion that sequence effect, which is related to bradykinesia, worsens over time.One potential limitation for the titration experiment is there may be a ‘cumulative” effect of increasing doses of DBS on behavior as seen for attenuation of the beta band [Finally, as the neural closed loop sequence effect data is preliminary data taken from a single subject, it is difficult to conclude whether the noted behavioral improvement will be seen in a larger group of people with PD. For transparency, we included all data regardless of whether parameters such as stimulation delay are critical to the clinical significance. | PMC10357155 |
Conclusions | PD, lower extremity bradykinesia | In this study we demonstrated that a quantitative metric of the sequence effect in upper limb movement strongly correlated with overall motor disability and upper and lower extremity bradykinesia in PD and worsened over time in a longitudinal cohort. In a careful examination of randomized presentations of different intensities of STN DBS, we showed for the first time that continuous open-loop DBS improved the sequence effect of limb bradykinesia in a dose-dependent manner. Finally, we presented evidence that closed-loop, or adaptive, DBS also improved the sequence effect and was slightly more efficacious than open-loop DBS in one participant. This suggests that STN DBS is a promising therapy to improve the sequence effect in bradykinesia for people with PD. | PMC10357155 | |
FUNDING | Parkinson’s, NINDS | FOX, BRAIN | This study was funded by the NIH Brain Initiative Grant 1UH3NS107709, NINDS Grant 5 R21 NS096398-02, PF-FBS-2024 from the Parkinson’s Foundation, Michael J. Fox Foundation (9605), Robert and Ruth Halperin Foundation, John A. Blume Foundation, and Helen M. Cahill Award. Medtronic PLC provided devices but no financial support. | PMC10357155 |
CONFLICT OF INTEREST | H.M.B.-S. serves on a clinical advisory board for Medtronic PLC.All other authors have no conflict of interest to report. | PMC10357155 | ||
DATA AVAILABILITY | Data supporting the findings of this study will be made available on request when possible from the corresponding author. | PMC10357155 | ||
ACKNOWLEDGMENTS | We would like to thank Chioma Anidi and Muhammad Furqan Afzal for their contributions to experimental design and data collection for the study. We would also like to thank the rest of the members of the Human Motor Control and Neuromodulation laboratory, Dr. Jaimie Henderson, and, most importantly, the participants who dedicated their time to this study. | PMC10357155 | ||
REFERENCES | PMC10357155 | |||
1. Introduction | obesity, NCD, cancer, diabetes, cardiovascular disease, FOP, WL | OBESITY, CANCER, DISEASES, SHOP | One common strategy for governments to tackle the non-communicable disease (NCD) epidemic is front-of-package (FOP) nutrition labeling. The Kingdom of Saudi Arabia (KSA) is considering implementing a new FOP label that is based on either France’s Nutri-Score (NS), which labels all foods (A = healthiest to E = least healthy) based on overall nutritional quality, or the Chilean warning label (WL) approach, which identifies foods to avoid based on select nutritional characteristics. Using a fully functional online grocery store, this study aimed to test these two promising FOP strategies by randomizing 656 KSA adults into one of the three versions of the store to complete a hypothetical grocery shop: no-label (control), NS, and WL. The NS was modified with a sugar percentage tag given that reducing sugar consumption is one of KSA’s public health goals. We found that both modified NS labels and Chilean warning labels positively influenced food and beverage choices among KSA participants, but there were differential effects across the two labels. Relative to the control, NS improved the overall diet quality of the shopping baskets, measured by the weighted (by the number of servings) average NS point (ranging from 0, least healthy, to 55, healthiest), by 2.5 points [95% CI: 1.7, 3.4; The health and economic burden of non-communicable diseases (NCDs) globally is large and growing [FOP labels can generally be classified as reductive or interpretive. Reductive labels present a subset of relevant information without interpretation, such as calories per serving and calories per day for a healthy diet. Interpretive labels use nutritional information to convey a message to consumers as to the underlying healthiness of the product in the dimensions considered. Interpretive FOP labels can focus solely on identifying foods that are healthier (i.e., positive labels), such as in Singapore’s healthier choice symbol (HCS) labels [Despite the limitations, both graded and warning FOP labels have been shown to be effective relative to a no-label control condition [As with many countries, Saudi Arabia (KSA) has observed a dramatic rise in NCDs. Comparing data between 2008 and 2017, the prevalence of diabetes, cardiovascular disease, and cancer increased to 51%, 47%, and 96%, respectively [We chose a holistic measure of nutritional quality, the weighted average Nutri-Score point, as the primary outcome. Although not free from concerns [We expect that both labels would positively influence food-purchasing patterns relative to a no-label control arm. We hypothesized that the modified Nutri-Score label (NS) would perform best when it comes to overall diet quality, given that is its primary focus. Warning labels (WL) are expected to be more effective at reducing the nutrients (and calories) that are the target of the labels, including sugar intake. This results because the stop sign warning is a stronger signal than simply noting the sugar percentage per serving, as it appears on the NS label. We tested these hypotheses with KSA shoppers using a randomized controlled trial design and a fully functional web grocery store where shoppers completed a one-time hypothetical grocery shop. We investigated the effectiveness of the labels not only on foods and beverages but also on beverages alone, given that sugar-sweetened beverages are a primary contributor to obesity and NCDs [ | PMC10343722 |
2. Materials and Methods | PMC10343722 | |||
2.1. Online Grocery Store | The study took advantage of an experimental online grocery store developed for research purposes (For this study, products were primarily selected from an online store of a large Saudi supermarket, called Danube ( | PMC10343722 | ||
2.2. Experimental Design | WL | The study was a three-arm randomized controlled trial (RCT) design with three versions of the grocery store (the no-label control, the NS, and the WL arms; see In | PMC10343722 | |
2.3. Participants and Procedures | obesity, WL, diabetes | OBESITY, HYPERTENSION, SHOP, DIABETES | Participants were recruited from July to August 2021 from the Kantar online web panel of Saudi Arabian citizens and residents. Prospective participants were asked to complete an online screener to determine their eligibility. They were eligible if they were aged 18 years or older, were KSA residents, able to read and write in Arabic, and were the primary grocery shopper for their household. Those interested and eligible were asked to complete an online consent form. Participants were made aware that there were multiple versions of the online grocery store but were not told of the nature of the study; those who consented were exposed only to the version of the store into which they were randomized.Once they consented, participants were directed to a baseline survey collecting their demographic characteristics, including age, sex, education level, housing type, monthly household income, and the underlying diet-related health conditions of their household members (e.g., overweight, obesity, diabetes, and hypertension). Upon completion of the baseline survey, participants were randomly assigned to one of the three study arms with equal probability and landed in a randomly chosen food subcategory to start shopping. Participants were then asked to complete a single hypothetical shopping trip as though all meals and snacks for their household members for the next 7 days would be made from foods and beverages purchased from this shopping trip. In efforts to encourage shoppers to take the task seriously, they were also required to spend a minimum of 150 Saudi riyals (SAR, equivalent to 40 US dollars) per household member and to shop in at least four food categories. This minimum amount was determined based on the average per capita monthly spending on foods and beverages (excluding consumption away from home) reported in the 2018 KSA Household Expenditure Survey, with inflation and taxes accounted for. Those who were assigned to the NS arm were shown a brief introductory video about the modified NS label. They were able to watch this video again at any time during their shopping trip. We did not show a similar video to participants assigned to the WL arm because we believed that messages on WL (‘high in [nutritional component X]’) are relatively straightforward. Panelists who completed the study received compensation in points according to Kantar’s in-house incentive protocols.The use of a web panel enabled us to collect data relatively quickly, at low cost, and from a geographically diverse population of shoppers in KSA. Once participants completed their shopping and clicked on “check-out,” they were asked to take a brief post-study survey that included questions that tested how well they understood the labels and video (if applicable), as well as an open-ended feedback question.A power calculation revealed that 602 participants were required to detect a standardized effect size of 0.3 in outcomes between arms, assuming a two-tailed | PMC10343722 |
2.4. Statistical Analyses | PMC10343722 | |||
2.4.1. Outcome Variables | SECONDARY | The primary outcome was a holistic measure of diet quality: the average NS points of the shopping basket, weighted by the number of servings. Because the NS points range from −15 to 40, to ease the interpretation of the results, we reversed and shifted the NS point such that it lies in between 0 and 55, with 0 being the least healthy score and 55 the healthiest. For instance, if a participant’s grocery basket contains beverage A (1 serving, NS point 13) and food B (3 servings, NS point 30), then we compute the weighted average of NS points by using the following formula: The secondary outcome measures of diet quality focused on (1) total and (2) weighted (by the number of servings) average calories, sugar, sodium, and saturated fat per serving of the grocery baskets. The per-serving measures were calculated in the same way as for the primary outcome variable. The reason we are interested in both total and per-serving changes is to examine whether the labels induce people to purchase fewer nutrients or energy per serving but more total nutrients or energy, which has been shown to occur for some labels [ | PMC10343722 | |
2.4.2. Estimation | WL | REGRESSION, REGRESSIONS | To test the hypotheses, we employed ordinary least squares (OLS) regressions with robust standard errors. The regression specification is as follows:To gain further insight into what is driving differential effectiveness, we quantified the following across the arms: (1) the proportion of products in a grocery basket that are subject to the warning labels (and labeled in the WL arm); (2) the weighted average NS points of the products that are subject to the warning labels; and (3) the weighted average NS points of the products that are | PMC10343722 |
3. Results | PMC10343722 | |||
3.3. The Effects of FOP Labels on Diet Quality for Beverages Only | WL | We present the results on the primary outcome along with the per-serving outcomes in The proportion of warning-labeled beverages in the baskets is 9.2% in the NS arm and 8.7% in the WL arm. Relative to the control arm (9.7%), the difference is only significant for the WL arm ( | PMC10343722 | |
4. Discussion | FOP, WL | SHOP | Consistent with prior evidence, we found that both the modified Nutri-Score (NS) and the Chilean warning labels (WL) promoted healthier food and beverage choices relative to the no-label control arm. However, the effectiveness of the two labels varied depending on which outcome we focused on. Consistent with our hypothesis, the NS improved the overall diet quality of shopping baskets as measured by the weighted (by the number of servings) average NS point, whereas the WL did not. However, again, as hypothesized, the WL is generally more effective at reducing targeted nutritional attributes. Compared with the no-label control, these labels were more effective at decreasing per-serving energy (kcal) and saturated fat (g) intake. However, contrary to expectations, the reduction in sugar intake per serving was greater with the NS. This finding may be due to our modification of the NS to explicitly show the sugar percentage per serving, thus minimizing the difference between the two labels for this nutrient.Although cross-study comparisons may be confounded by differences in participant and store characteristics, the effect size of the two labels in our study appears reasonable. A study testing the standard NS label with 290 products with 691 French subjects showed the NS score of a grocery basket (normalized by 100 kcal) in the NS arm was better by 2.65 points relative to the no-label arm [We further show that both labels improved overall diet quality and reduced per-serving intakes of sugar and calories from beverages purchased. We also found no evidence that either label induced shoppers to purchase more The heterogeneous effect of the two labels on different outcomes is an important finding. The choice of one label over another should depend on the public health goal. Our results suggest that, if the goal is to improve overall diet quality while targeting one factor to emphasize (sugar in our case), then a modified NS label as applied here should be considered. If the goal is to reduce intake of a small number of negative factors, then warning labels targeting these factors may be the optimal approach, in which case focusing on those nutrients as the primary outcomes would be appropriate. However, if there are too many nutrients targeted, efforts to avoid one nutrient could inadvertently increase the consumption of another. Our study also showed that not only did the modified NS label improve overall diet quality, but that, compared to shoppers in the WL arm, shoppers in the NS arm purchased healthier non-WL products (i.e., products that did not have a warning label in the WL arm had higher average NS points in a grocery cart) and bought a smaller percentage of WL products (products that had a warning label in the WL arm). This is consistent with the NS label providing additional information that is not available to those in the warning label arm.None of the labels statistically reduced sodium (mg) per serving, which contrasts with our hypothesis about the effectiveness of the high-in-sodium warning label. Although few papers reported nutrient-specific effects of the Chilean warning-type labels, one study with Mexican adults found that the labels led to a reduction in sodium purchases per 100 g/mL relative to the GDA label (56). As noted above, the sodium warning label might not have the intended effect if it is displayed with other warning labels. Prior studies showed that multiple claims increase information costs [Our findings come with the following limitations: First, our two cart criteria (i.e., a minimum expenditure and a minimum number of food categories in which to shop) probably reduced biases associated with hypothetical shopping, but the data for this study still represent hypothetical purchases, which may not represent actual purchases. Second, even if it provides an accurate reflection of purchases from a single shopping trip online, this study does not address the long-term effects of the FOP labels or the effects of the labels on offline grocery shopping patterns. Third, we modified the NS label, assuming that this change would increase its effectiveness for the targeted nutrient. Our results suggest this may be the case, but we did not conduct a formal test of this hypothesis because funding and other constraints did not allow for a four-arm trial. Fourth, although our primary outcome has been shown to be a valid measure of overall diet quality [As managing risks for NCDs requires long-term behavior change, future studies should extend these results to test the labels over repeated shopping trips with actual purchases, both in online and in-store settings, and extend the analysis to measure clinical outcomes such as body mass index and blood pressure. In the real world, food purchase channels for home consumption are a mix of online and offline grocery shopping trips, where the effects of FOP labels may differ. Our results are applicable to similar online grocery shops where individuals make grocery purchases for future consumption, but the extent to which the labels improve diet quality may differ for other online shopping for more immediate consumption and when the range of products is more limited (e.g., online convenience store vs. grocery store). The results may also differ for in-store purchases, where visceral factors (sounds, smells, placement, and lighting) may attenuate the effects of the label. Future efforts should also formally test different variants of these labels to identify which is most beneficial for a given target population. For instance, given that Arabic is read from right to left, KSA shoppers may respond to the NS labels differently than those in other countries, as they read the sugar percentage before the grade for overall diet quality.In conclusion, this study showed that both the modified NS labels and Chilean warning labels positively influenced food and beverage choices among KSA participants, but that there were differential effects across the two labels. The modified NS label with the sugar per serving tagline increased overall diet quality and decreased sugar per serving to a greater extent than the warning labels. By contrast, the warning labels were more effective at reducing calories and saturated fat per serving. Policymakers should consider these findings, along with their stated objectives, when determining which strategy may be best for their target population. | PMC10343722 |
Supplementary Materials | The following supporting information can be downloaded at: Click here for additional data file. | PMC10343722 | ||
Author Contributions | Conceptualization, S.S., A.M.A., R.F.A., R.A.A., A.A. (Amaal Alruwaily), A.A. (Abdullah Algwizani), M.S., C.H.H. and E.A.F.; methodology, S.S. and E.A.F.; validation, S.S., A.M.A., R.F.A., R.A.A., C.H.H. and E.A.F.; formal analysis, S.S.; investigation, S.S. and E.A.F.; writing—original draft preparation, S.S.; writing—review and editing, S.S., R.A.A., C.H.H. and E.A.F.; visualization, S.S.; funding acquisition, E.A.F. All authors have read and agreed to the published version of the manuscript. | PMC10343722 | ||
Institutional Review Board Statement | The study protocols and procedures are in accordance with the Declaration of Helsinki. Ethical clearance was provided by the National University of Singapore Institutional Review Board (IRB), reference code: NUS-IRB-2020-794 and the KSA Public Health Authority IRB, reference code: SCDC-IRB-A034-2021. | PMC10343722 | ||
Informed Consent Statement | Consent from the participants was asked at the beginning of the Participant Information Sheet and Consent Form stage. Although we did not collect any identifiable information from participants, we informed them that deidentified data would be used in this research. We asked the participants to agree or disagree with the processing of their data. If they agreed, they would continue with the next step, which was the baseline survey. When they disagreed, they could not participate in the study. | PMC10343722 | ||
Data Availability Statement | The datasets used and/or analyzed during the current study are not publicly available due to a lack of consent from all participants for making the data publicly available, but they are available from the corresponding author upon reasonable request. | PMC10343722 | ||
Conflicts of Interest | The authors declare no conflict of interest. | PMC10343722 | ||
References | WL | English-language versions of modified Nutri-Score labels (A screenshot of the experimental online grocery store for KSA (control arm).Example products from three versions of the online grocery store showing how the labels were presented across the three study arms; (Participant flow diagram.Summary statistics of the participants by arms and total (n = 656).Note: NS = Nutri-Score; SAR = Saudi riyals; SD = standard deviation.Descriptive statistics of outcomes by arm (Effects of the NS and WL on weighted average NS point and per-serving energy and nutrients.Notes: robust standard errors are in parentheses. * Effects of the NS and WL on total energy and nutrients of the shopping basket.Notes: robust standard errors are in parentheses. * Effects of the NS and WL on weighted average NS point and per-serving energy and nutrients (beverages only).Notes: robust standard errors are in parentheses. * Effects of the NS and WL on total energy and nutrients of the shopping basket (beverages only).Notes: robust standard errors are in parentheses. | PMC10343722 | |
Background | The transition to motherhood is characterized by physical, psychological, social, and relational changes. Quality of life (QoL) changes substantially during this transition. Higher QoL is associated with social support, essential for coping with the challenges and changes of becoming a mother. An early universal home visiting program (New Families) is developed to strengthen and support families. The study aims to evaluate the impact of New Families on first-time mothers’ QoL and to investigate the association between their QoL, social support, and selected possible predictive factors. | PMC10704737 | ||
Methods | A prospective non-randomized controlled study with parallel group design. Child Health Services in five city districts of Oslo were matched in intervention and control groups. First-time mothers were allocated based on the residential area and assessed at pregnancy week 28 ( | PMC10704737 | ||
Results | Our data did not reveal a significant association between New Families intervention and the QoL levels of first-time mothers at three months postpartum. Thus, we analyzed the whole sample together. Emotional support was significantly associated with higher QoL levels in the physical health (B = 0.19, 95%CI [0.04 to 0.34]) and social relationships (B = 0.40, 95%CI [0.20 to 0.60]) domains. Appraisal support was significantly associated with higher QoL levels in the psychological (B = 0.34, 95%CI [0.18 to 0.50]) and environment (B = 0.33, 95%CI [0.19 to 0.48]) domains. QoL levels in pregnancy were significantly associated with QoL levels postpartum, showing small to medium effect size (ES = 0.30 to 0.55), depending on the domain. | PMC10704737 | ||
Conclusions | Further research, including qualitative interviews, could provide more insights into the impact of New Families on QoL. A positive association between QoL levels in pregnancy and postpartum suggests that postnatal interventions targeting improved QoL could potentially improve postpartum QoL. Emotional and appraisal support seems beneficial for first-time mothers’ QoL and could be provided and facilitated by public health nurses. | PMC10704737 | ||
Trial registration | clinicaltrial.gov | PMC10704737 | ||
Supplementary Information | The online version contains supplementary material available at 10.1186/s12889-023-17285-0. | PMC10704737 | ||
Keywords | PMC10704737 | |||
Background | DISEASES, TRANSITION | Transition to motherhood is characterized by physical, psychological, and social changes [In postpartum women, various aspects of support, such as adequate antenatal care consultations [Home visits, as formal professional support, are recommended in the WHOs strategy on maternal care [The Norwegian Child Health Services (CHS) are provided through the Primary Health Care Services, aiming to prevent diseases, maintain good health status for all children, and improve parents’ autonomy and independence. The CHS is the only health promotive and preventive service to children 0–5 years old at the municipal level. The CHS is free, used by 98% of the eligible population [An early universal home visiting program, New Families (NF), has been developed by a department in the City of Oslo in close collaboration with researchers, PHNs, and users of the CHS. Further information on this development is described elsewhere [The transition to motherhood is argued to be a vulnerable period, affecting aspects of QoL, and emphasizing the need for informal and formal support. The potential for PHNs to provide more formal support through NF, compared to the traditional CHS, may affect women’s QoL during the transition to motherhood. Therefore, the aims of this study were to 1) evaluate the impact of NF on first-time mothers’ QoL by exploring differences between the first-time mothers receiving NF and the first-time mothers receiving follow-up as usual, and if no impact of NF on QoL 2) investigate the association between QoL, social support and selected possible predictive factors in the sample of first-time mothers. | PMC10704737 | |
Methods | PMC10704737 | |||
Study design | This is a prospective non-randomized controlled study with parallel group design, using data from the New Families research project, which evaluates the New Families home visiting program registered at clinicaltrials.gov (NCT04162626). The Regional Committees for medical and health research ethics in Norway (reference no: 2018/1378) and the Norwegian Centre for Research Data (project no: 735207) has approved the New Families research project. This study reports on the additional outcome QoL, which were collected in the study described above. | PMC10704737 | ||
Participants and setting | Depression | RECRUITMENT, DISEASES | A department in the City of Oslo selected and matched five city districts of Oslo as either intervention or control districts. The aim of matching the groups was to achieve equality between the intervention and control districts by using data and statistics on population level regarding sociocultural factors, population composition, birth statistics, immigrant proportion, and work participation. Randomization of districts or respondents was impossible, as NF was already implemented in the CHS in several districts. Hence, this limited the number of city districts available for inclusion, and the number of variables we were able to match for had to be adjusted for accordingly. The residential district determined the respondents’ group allocation. First-time mothers and their families in the control districts received service as usual, and the intervention districts received NF in addition to service as usual.Midwives or clinic secretaries at the CHS clinics in the five city districts recruited pregnant women attending pregnancy check-ups by screening them according to eligibility criteria and inviting them to participate. Inclusion criteria were pregnant women expecting their first child and living in one of the five city districts. The exclusion criteria were multiparous women. Women with specific conditions or diseases were not actively excluded, and no exclusion criteria were applied later based on birth outcomes. The recruiters at the CHS clinics were instructed to provide the pregnant women with initial information on the study, including a short information letter available in ten languages (Norwegian, English, Arabic, Lithuanian, Pashto, Polish, Somali, Tamil, Turkish, and Urdu). Contact information for these pregnant women was provided by the CHS clinics to researchers in the NF research project who contacted the pregnant women for inclusion in the study. The current study only includes pregnant women/first-time mothers. However, in the NF research project the women’s partners were recruited to the study by the researchers when contacting the pregnant women interested in participating.The recruitment was conducted from October 2018 to December 2019. Of the 427 pregnant women invited to participate, we included 228 pregnant women, divided by 124 pregnant women in the intervention districts and 86 pregnant women in the control districts. Due to General Data Protection Regulation laws, we were not allowed to collect any information on non-respondents.Power calculation for the NF research project were estimated based on the outcome measure of Edinburgh Postnatal Depression Scale [ | PMC10704737 |
Data collection | All pregnant women interested in participating received informed consent, by mail, for written completion. Self-reported measures were sent to first-time mothers by mail from October 2018 to June 2020. Data were collected at three time points: around pregnancy week 28 (T1), six weeks postpartum (T2), and three months postpartum (T3). The consent form and all measures were available in ten languages. | PMC10704737 | ||
Control | The pregnant women/first-time mothers in the control districts received the traditional child health program provided by the CHS. Up to three months postpartum, the CHS provides one home visit 7–10 days postpartum, one group consultation, and two clinical consultations [Timeline of the New Families home visiting program in the context of the traditional child health program | PMC10704737 | ||
Intervention | The pregnant women/first-time mothers in the intervention districts received NF in addition to the traditional child health program offered by the CHS, as described under NF is based on a salutogenic perspective, focusing on resource mobilization, using methods of motivational interviewing and empathic communication. NF is regulated by a manual [ | PMC10704737 | ||
Measures | PMC10704737 | |||
Demographics and selected possible predictive factors | COMPLICATIONS | Standard demographic data were measured at T1 and included family income, educational level, age, nationality, and marital status. Single items at T1 assessed the presence of complications during pregnancy, previous and present mental health conditions, hours of sleep, and the perception of enough/not enough sleep (also assessed at T2). | PMC10704737 | |
Quality of life | QoL is measured at T1 and T3 by the World Health Organization Quality of Life Questionnaire brief version (WHOQOL-BREF) [ | PMC10704737 | ||
Social support | Social support is measured at T2 by | PMC10704737 | ||
Statistical methods | REGRESSION, SENSITIVITY, REGRESSIONS | Descriptive statistics were used to describe the sample characteristics. Continuous variables were described by means and standard deviations (SD) and categorical data as counts and percentages. Crude comparisons between pairs of variables were performed using t-test for continuous variables and chi-square for categorical variables.As the dependent variable (QoL) was assessed at two time points, all models were constructed with QoL variable assessed at T3 and adjusted for QoL variable measured at T1 to account for the design and possible statistical dependencies as the same individuals were assessed two times. All models are conducted with listwise exclusion, and the number of participants used in each model is marked in Tables A linear regression model was fitted with QoL as the dependent and intervention vs. control groups (labeled: Intervention) as the independent variable. We constructed one regression model for each of the four QoL domains at T3. All the models were adjusted for baseline differences between the intervention and control groups. Further, we constructed an interaction term to test whether the effect of the intervention on our outcome depended on the QoL level at T1, e.g., that the intervention had a larger effect on those who had lower QoL in pregnancy. This variable is labeled Intervention*QoL domain and included as an independent variable.As no differences in the outcome were found between the intervention and control groups, a two-step linear regression with a backward selection method was used to investigate the association between QoL domains, social support, and the selected possible predictive factors in the whole sample of first-time mothers. We tested four regression models, one for each of the four QoL domains assessed at T3. In the first step of each model, we entered the four subscales of the PICSS functional scale (informational, instrumental, emotional, appraisal) and PICSS structural scale (formal and informal supporters) assessed at T2, and the QoL domain assessed at T1. In the second step, we retained the variables that were statistically significant from step one and included the selected possible predictive factors (family income, pregnancy week at T1, age of the mother, and perception of sleep at T1 and T2). The criterion for removing variables from the model in the linear regression with backward selection method was set to The results of all linear regressions are presented as unstandardized regression coefficient (B), with 95% confidence interval for B (95% CI), and Sensitivity analyses were conducted to explore if answering the survey after the outbreak of COVID-19, which was on March 12Internal consistency reliability was examined by calculating Cronbach’s alpha for all WHOQOL-BREF domain scales and subscales of the PICSS functional scale.All statistical analyses were conducted in SPSS, version 28, in the secure platform of Services for Sensitive Data [ | PMC10704737 | |
Results | Of the 427 first-time mothers invited to participate in the study, 228 (53.4%) were included at T1. The number of participating first-time mothers, response rates at each time point, and the dropouts by intervention and control group are presented in the flow chart in Fig. Flow chart of first-time mothers at T1, T2, and T3, with reasons for dropoutsFirst-time mothers completed the measures in three languages. Norwegian was used by 95.6% (In the intervention group, non-respondents ( | PMC10704737 | ||
Sensitivity analyses | We replicated the analyses in Tables Regarding the analyses of the association between QoL and social support, the sensitivity analyses revealed only small changes compared to the main analyses (Supplementary Table S | PMC10704737 | ||
Discussion | This study aimed to evaluate NF’s impact on first-time mothers’ QoL and to investigate the association between their QoL, social support, and selected possible predictive factors. Our data did not reveal that NF impacted first-time mothers’ QoL at three months postpartum. Social support through a supporting presence at six weeks postpartum was associated with higher QoL at three months postpartum. In addition, the study showed that the QoL during the third trimester of pregnancy was related to the QoL at three months postpartum.Our study’s null finding regarding NF’s impact on QoL may imply that the traditional program provided by the CHS is sufficient in maintaining first-time mothers’ QoL levels during the given period. Thus, until further outcomes of NF are evaluated, politicians and clinical practitioners may continue with NF. Further research, such as qualitative interviews, may provide more insight into the first-time mother’s experiences with NF regarding QoL and related factors.The abovementioned finding could be due to several reasons. Emotional and appraisal support were statistically significantly associated with higher QoL in the first-time mothers. This relationship has previously been sparsely explored due to predominant attention on general social support measurements [Appraisal support was associated with the QoL domains environment and psychological. These domains encompass factors such as safety, home environment, self-esteem, feelings, and access to information and health care [Our findings suggest that informational and instrumental support may not play a crucial role in influencing the QoL of first-time mothers. Further, the findings may imply that emotional or appraisal support is more beneficial to improve QoL in first-time mothers. However, the results should be interpreted by Norway’s cultural and societal context to understand the clinical implications of this finding. Appropriate advice on infant care and behaviors with hands-on assistance may be readily available to our sample of first-time mothers from professionals and close ones. This may imply that the informational and instrumental support is sufficient enough. Further research utilizing different designs and measures is needed to better understand the role of informational and instrumental, as well as emotional and appraisal, support on the QoL of first-time mothers in Norway.Our findings revealed that the QoL level in pregnancy was related to the level at three months postpartum. This association was found in all QoL domains, with its highest effect in the psychological and social relationship domains. In line with the intention of NF, this finding supports that to improve first-time mothers’ QoL levels, interventions should be started already during pregnancy. Extensive knowledge exists of factors associated with poor and good QoL that emerge during pregnancy [The perception of enough sleep at six weeks postpartum was associated with higher levels of QoL in all domains at three months postpartum, showing the highest impact in the physical health domain. A similar relationship was found in our sample during pregnancy [ | PMC10704737 | ||
Strengths and limitations | RECRUITMENT | The strength of our study is the generation of new knowledge on Norwegian first-time mothers’ QoL and the program offered by the CHS related to QoL. In a Norwegian context, this population and the CHS are rarely subjects to research. Additionally, our study provides knowledge on the association between specific constructs of social support and QoL.This study was not powered to reveal possible differences between the intervention and control group, thus we consider our findings to be exploratory. Our study has a recruitment rate slightly above 50% in both the intervention and control groups and a response rate of around 70–75% from T1 to T3. We acknowledge that the recruitment rate was low, however, it is not uncommon in studies of new parent populations. This limits the generalizability of our study. However, our results are valid for a sub-population of Norwegian women between 29–35 years, who are partnered or married, and have higher family income and educational levels.Limitations and challenges of our study regarding the timeframe, fidelity and implementation, time points, response shift, the use of a generic QoL measure, complexity of the intervention, and biased sample, are already discussed above.The measure of PICSS has not previously been validated in a Norwegian sample of postpartum women. For the New Families research project, the measure was translated and re-translated by professional translators, and we have provided Cronbach’s alpha for each dimension. Future studies should aim to provide further psychometric testing of the instrument in a Norwegian sample, including assurance of cultural adaptation. | PMC10704737 | |
Conclusions | ’ | Our results did not reveal that NF has a statistically significant impact on the QoL of first-time mothers at three months postpartum. Our results suggest that NF does not harm the QoL of first-time mothers, and the intervention may be continued if found effective on other outcomes. Further research, including qualitative interviews, is needed to provide insights into the impact of NF. The association between the QoL level during pregnancy and postpartum suggests that postnatal interventions targeting improved QoL could potentially improve postpartum levels. Social support as emotional and appraisal support seems beneficial for first-time mothers’ QoL, indicating that PHNs may contribute by assessing and providing support and facilitating informal support to first-time mothers. | PMC10704737 | |
Acknowledgements | RECRUITMENT | We express our gratitude to all participating first-time mothers and the recruitment work by the Child Health Services in our included districts. | PMC10704737 | |
Authors’ contributions | Malene Brekke: Conceptualization, Methodology, Formal analysis, Investigation, Data Curation, Writing—Original Draft & Editing. Milada Cvancarova Småstuen: Conceptualization, Methodology, Formal analysis (expert statistician), Writing—Review & Editing. Kari Glavin: Conceptualization, Methodology, Investigation, Data Curation, Writing—Review & Editing, Supervision, Project administration (New Families research project). Amin Amro: Conceptualization, Methodology, Writing—Review & Editing, Supervision. Beate Solberg, Anne-Martha Utne Øygarden & Kristin Marie Sæther: Investigation, Data Curation, Writing—Review & Editing. Trude Haugland: Conceptualization, Methodology, Writing—Review & Editing, Supervision. | PMC10704737 | ||
Funding | The New Families research project, in which the data material for this study is retrieved from, was funded by the Research Council of Norway (project code 282167). The funding had no role or influence in the design of the study, collection, analysis, and interpretation of data and in writing this manuscript. | PMC10704737 | ||
Availability of data and materials | All relevant data are presented in this paper. Further records from this study are available from the corresponding author upon reasonable request. | PMC10704737 | ||
Declarations | PMC10704737 | |||
Ethics approval and consent to participate | The New Families research project is approved by the Regional Committees for medical and health research ethics in Norway (reference no: 2018/1378) and the Norwegian Centre for Research Data (project no: 735207) and registered at clinicaltrial.gov (identifier: | PMC10704737 | ||
Consent for publication | Not applicable. | PMC10704737 | ||
Competing interests | The authors declare no competing interests. | PMC10704737 | ||
References | PMC10704737 | |||
1. Introduction | obesity, mood disturbances, anger, confusion, Obesity, weight loss regimen, fatigue, mood disturbance, pain, Intentional reductions, depression, Depression, weight loss | OBESITY, SECONDARY, OBESITY | The purpose of this secondary analysis is to compare the effects of two popular weight loss regimens, time-restricted eating (TRE) and daily calorie restriction (CR), on mood and quality-of-life measures in adults with obesity. Ninety participants were randomized to one of three interventions for 12 months: 8 h TRE (eating only between 12:00 and 8:00 p.m., with no calorie counting); CR (25% energy restriction daily); or no-intervention control group. Questionnaires were administered to measure mood (Beck Depression Inventory-II (BDI-II), and Profile of Mood States (POMS)) and quality of life (Rand 36-Item Short Form) at baseline and month 12. Body weight decreased in the TRE group (−4.87%, 95%CI: −7.61, −2.13) and CR group (−5.30%, 95%CI: −9.06, −1.54) versus controls, with no difference between TRE and CR. The BDI-II depression score did not change in the TRE or CR group, versus controls, by month 12. Likewise, there were no changes in any of the POMS subscales (tension, depression, anger, fatigue, anger, confusion, or vigor) or the total mood disturbance score in the TRE or CR group versus controls. As for quality of life, there were no significant changes in the SF-36 constructs of mental health, bodily pain, and general physical health in the TRE or CR group versus controls. However, there was a trend towards increased vitality in the TRE group (7.77 [95% CI: 0.15, 15.39] Depression and mood disturbances are commonly associated with obesity [Obesity is also associated with lower quality of life [Intentional reductions in body weight have been shown to improve both mood and quality of life [In recent years, time-restricted eating (TRE) has gained popularity as a weight loss regimen. TRE involves shortening the eating window to 4–10 h per day and fasting with energy-free beverages for the remaining hours [We recently conducted a 12-month randomized controlled trial comparing the effects of 8 h TRE and CR on body weight in adults with obesity [ | PMC10609268 |
2. Methods | PMC10609268 | |||
2.1. Participant Selection and Randomization | SECONDARY | This study is a secondary analysis of a previously published 12-month randomized controlled trial [Inclusion criteria: male or female; age between 18 and 65 years; and BMI between 30 and 50 kg/m | PMC10609268 | |
2.2. Time-Restricted Eating Protocol | weight loss | During the 6-month weight loss phase, TRE subjects were asked to eat only between the hours of 12:00 and 8:00 p.m. and to fast from 8:00 to 12:00 p.m. the following day. Subjects did not have to monitor food or energy intake during the 8 h eating window. During the 16 h fasting window, subjects were allowed to drink water and calorie-free beverages like coffee and tea without additives, and diet sodas (limit 2 per day). During the 6-month weight maintenance period, subjects were asked to maintain their weight by expanding their eating window to 10:00 a.m. to 8:00 p.m. (10 h eating window) and fast from 8:00 p.m. to 10:00 a.m. (14 h fasting window). TRE subjects received diet counseling (over Zoom) weekly during the first 3 months and then biweekly from months 4 to 12. During the counseling sessions, subjects learned how to make healthy food choices [ | PMC10609268 | |
2.3. Calorie Restriction Protocol | weight loss | During the 6-month weight loss phase, CR subjects were asked to reduce their energy intake by 25% each day. Total energy expenditure was calculated using the Mifflin equation [ | PMC10609268 | |
2.4. Control Group Protocol | Control subjects were asked to maintain their weight by not changing their eating and activity habits during the 12-month trial. Controls did not receive diet counseling but were contacted by the study coordinators at the same frequency as the TRE and CR groups to provide body weight measurements. | PMC10609268 | ||
2.5. Assessment of Body Weight and Body Composition | CREST | All variables were measured at baseline and month 12. Body weight was assessed without shoes, in light clothing, using a digital scale at the research center. Body composition (fat mass, lean mass, and visceral fat ass) was measured using dual X-ray absorptiometry (iDXA, GE). Waist circumference was measured using a measuring tape midway between the lowest rib and the iliac crest by trained study personnel. | PMC10609268 | |
2.6. Diet Adherence and Physical Activity | Adherence to the TRE diet was measured using a paper or digital adherence log, which recorded the time each participant started and stopped eating each day. The day was labeled as adherent if the log showed that the subject ate within the correct eating window that day. If they did not, the day was labeled as nonadherent. Compliance with the TRE diet was expressed as percentage of adherent days from baseline to month 12. Adherence to CR was expressed as the percentage of participants who were compliant with their calorie targets (within ±200 kcal). Energy intake and dietary composition were assessed through a 7-day food log using the Automated Self-Administered 24-hour (ASA-24) diet assessment tool [ | PMC10609268 | ||
2.7. Assessment of Mood | Depression | Mood was quantified with the Beck Depression Inventory II (BDI-II) [ | PMC10609268 | |
2.8. Assessment of Quality of Life | Quality of life was measured using the Rand 36-Item Short Form (SF-36) [ | PMC10609268 | ||
2.9. Statistical Analyses | Data are shown as mean (95% CI) unless otherwise noted. We conducted an intention-to-treat analysis, which included data from all 90 participants who were randomly assigned. Results are reported for the intention-to-treat analysis unless indicated otherwise. A linear mixed model was used to assess time, group, and time × group effects for each outcome. In each model, time and group effects (and their interaction) were estimated without imposing a linear time trend. For each outcome variable, linear modeling assumptions were assessed with residual diagnostics. To account for the potential for nonuniform variances (heteroskedasticity) between treatment groups due to random chance, all CIs and | PMC10609268 | ||
3. Results | PMC10609268 | |||
3.1. Baseline Characteristics | As reported previously [ | PMC10609268 | ||
3.2. Body Weight and Body Composition | Changes in body weight and body composition are reported in | PMC10609268 | ||
3.3. Diet Adherence and Physical Activity | TRE subjects adhered to their eating window on 87% of days on average over the 12-month trial. In the CR group, 61% of subjects adhered to their prescribed calorie targets over 12 months. Energy intake decreased by −425 kcal/d (SD 531 kcal/d) in the TRE group and −405 kcal/d (SD 712 kcal/d) in the CR group, with no difference between groups, over 12 months. As reported previously [ | PMC10609268 | ||
3.4. Mood | Changes in mood are presented in | PMC10609268 | ||
3.5. Quality of Life | Changes in quality of life are presented in | PMC10609268 | ||
3.6. Relationships between Changes in Body Weight, Physical Activity, Mood, and Quality of Life | There were no associations between changes in body weight, physical activity, mood, or quality of life in any group by the end of the study. | PMC10609268 | ||
4. Discussion | obesity, Obesity, mood disorders, weight reduction, depression, weight loss | OBESITY, OBESITY | To our knowledge, this is the first study to compare the effects of TRE (without calorie counting) versus daily CR on mood and quality of life in adults with obesity. Our results indicate that 12 months of TRE and CR have no effect on mood or quality of life in this population group, relative to no-intervention controls.Obesity is associated with a higher risk of mood disorders and depression [While several studies have examined the impact of CR on mood, only two studies [In view of these previous findings, it would appear as though at least 6% weight loss is needed to see changes in mood. Since our TRE and CR participants only achieved approximately 5% weight loss, it is possible that the degree of weight reduction was not large enough to see changes in mood scores.While the exact mechanism linking depression and obesity remains unclear, it is likely that the hypothalamic–pituitary–adrenal (HPA) axis, also known as the reward center of the brain, plays a major role [Individuals with obesity have also been shown to have lower quality of life [Findings from the present trial suggest that TRE and CR do not significantly impact quality of life in adults with obesity. Our data differ from previous reports, which generally show that TRE and CR have mild positive effects on quality of life. For instance, Carson et al. [Our study has several limitations. First, our sample size was small ( | PMC10609268 |
Author Contributions | S.L. designed the research, conducted the clinical trial, and wrote the manuscript; S.C., M.E., V.P., K.C., M.M. and M.-C.R. assisted with the conduction of the clinical trial; S.J.A. performed the statistical analyses; K.A.V. designed the research and wrote the manuscript. All authors have read and agreed to the published version of the manuscript. | PMC10609268 | ||
Institutional Review Board Statement | The protocol was approved by the Office for the Protection of Research Participants at the University of Illinois at Chicago (IRB #2020-1512). | PMC10609268 | ||
Informed Consent Statement | Informed consent was obtained from all participants (IRB #2020-1512). | PMC10609268 | ||
Data Availability Statement | Data are unavailable due to privacy or ethical restrictions. | PMC10609268 | ||
Conflicts of Interest | The authors declare no conflict of interest. | PMC10609268 | ||
Trial Registration | Clinicaltrials.gov, NCT04692532. | PMC10609268 | ||
References | Depression | Change in mood scores by month 12. Data are included for 90 participants; means were estimated using an intention-to-treat analysis using a linear mixed model. Error bars indicate 95% confidence intervals for each parameter from baseline by diet group. (Change in quality of life constructs by month 12. Data are included for 90 participants; means were estimated using an intention-to-treat analysis using a linear mixed model. Error bars indicate 95% confidence intervals for each parameter from baseline by diet group. (Baseline characteristics of the study participants.Data are expressed as mean ± SD unless otherwise indicated. BMI: body mass index; BDI-II: Beck Depression Inventory II; CR: calorie restriction; POMS: Profile of Mood States; SF-36: Rand 36-Item Short Form; TRE: time-restricted eating.Change in body weight, body composition, mood, and quality of life parameters by month 12.Data were included for 90 participants; means were estimated using an intention-to-treat analysis using a linear mixed model. Error bars indicate 95% confidence intervals for each parameter from baseline by diet group. Abbreviations: BDI-II: Beck Depression Inventory II; CON: control; CR: calorie restriction; POMS: Profile of Mood States; SF-36: Rand 36-Item Short Form; TRE: time-restricted eating. | PMC10609268 | |
Background | HIV and sexual reproductive | Antiretroviral therapy (ART) through universal test and treat (UTT) and HIV pre-exposure prophylaxis (PrEP) substantially reduces HIV-related mortality and incidence. Effective ART based prevention has not translated into population-level impact in southern Africa due to sub-optimal coverage among youth. We aim to investigate the effectiveness, implementation and cost effectiveness of peer-led social mobilisation into decentralised integrated HIV and sexual reproductive health (SRH) services amongst adolescents and young adults in KwaZulu-Natal (KZN). | PMC10428543 | |
Methods | HIV infection | HIV INFECTION | We are conducting a type 1a hybrid effectiveness/implementation study, with a cluster randomized stepped-wedge trial (SWT) to assess effectiveness and a realist process evaluation to assess implementation outcomes. The SWT will be conducted in 40 clusters in rural KZN over 45 months. Clusters will be randomly allocated to receive the intervention in period 1 (early) or period 2 (delayed). 1) Intervention arm: Resident peer navigators in each cluster will approach young men and women aged 15–30 years living in their cluster to conduct health, social and educational needs assessment and tailor psychosocial support and health promotion, peer mentorship, and facilitate referrals into nurse led mobile clinics that visit each cluster regularly to deliver integrated SRH and differentiated HIV prevention (HIV testing, UTT for those positive, and PrEP for those eligible and negative). Standard of Care is UTT and PrEP delivered to 15–30 year olds from control clusters through primary health clinics. There are 3 co-primary outcomes measured amongst cross sectional surveys of 15–30 year olds: 1) effectiveness of the intervention in reducing the prevalence of sexually transmissible HIV; 2) uptake of universal risk informed HIV prevention intervention; 3) cost of transmissible HIV infection averted. We will use a realist process evaluation to interrogate the extent to which the intervention components support demand, uptake, and retention in risk-differentiated biomedical HIV prevention. | PMC10428543 |
Discussion | HIV and sexual and reproductive health | The findings of this trial will be used by policy makers to optimize delivery of universal differentiated HIV prevention, including HIV pre-exposure prophylaxis through peer-led mobilisation into community-based integrated adolescent and youth friendly HIV and sexual and reproductive health care. | PMC10428543 | |
Supplementary Information | The online version contains supplementary material available at 10.1186/s12889-023-16262-x. | PMC10428543 | ||
Keywords | PMC10428543 | |||
Background | HIV viral suppression | CNS INFECTIONS, CURB | Despite global concerted efforts to curb the HIV epidemic, South Africa (SA) remains at the epicentre with approximately 8.2 million people in the country living with HIV. Despite effective biomedical tools, including freely available HIV testing, universal test and treat (UTT) and HIV pre-exposure prophylaxis (PrEP) there were an estimated 230,000 new infections in South Africa in 2020, the highest number in the world, with youth aged 15–24 accounting for 32% of these [Although HIV prevalence amongst youth in SA has been declining over recent years, HIV incidence among adolescent girls and young women (AGYW), particularly amongst women aged 20–24, in rural KwaZulu-Natal (KZN) remains high [HIV prevention has advanced in recent years because of new developments in biomedical HIV prevention tools including: HIV point of care tests (POCT) and self-tests [There has been a consistently high burden of poor sexual health among young people in rural KZN [There is growing evidence on the effectiveness of community-based HIV care. A meta-analysis found that community healthcare worker HIV care delivery significantly improved HIV viral suppression, which also reduces sexual transmission [Community-based approaches, when integrated with wider psychosocial care, foster social networks and norms that endorse HIV care and can accelerate progress towards attaining UN sustainable development goal targets [Evidence for peer-led HIV prevention amongst key populations, such as sex workers, men who have sex with men and people who inject drugs, is well established. A 2020 systematic review of the effectiveness of peer-led out-reach amongst key populations found a 36% reduction in HIV incidence [To fill this evidence gap we conducted community-based participatory research to develop and pilot the We hypothesise that social mobilization will attract and engage young people into decentralised SRH services where HIV prevention is tailored to need. Decentralised differentiated biosocial HIV prevention will increase uptake of risk-informed biomedical HIV care and prevention and reduce the overall prevalence of sexually transmissible HIV amongst young people aged 15–30. We are testing our hypotheses in a cluster-randomised stepped wedge trial. | PMC10428543 |
Objectives | PMC10428543 | |||
Main trial objective | The overarching goal of the trial is to identify scalable and sustainable ways to stem the HIV epidemic and its negative impact on young people aged 15–30 in rural KZN, South Africa through effective implementation of biosocial HIV prevention (trial registration NCT 05405582). The trial is focused on adolescents and young people, because our studies have shown a high unmet sexual health need in this age group and low engagement with existing HIV prevention and care services [ | PMC10428543 | ||
Specific trial objectives | biosocial HIV | This hybrid implementation-effectiveness trial has two main objectives: (1) to measure the effectiveness of social mobilisation combined with decentralised SRH services and tailored HIV prevention in (a) creating demand for differentiated HIV prevention and care, and (b) reducing the prevalence of transmissible HIV; (2) to understand real-world implementation of social mobilisation and decentralised SRH to deliver tailored, differentiated biosocial HIV prevention, by evaluating its acceptability, feasibility, reach, scalability and cost-effectiveness. | PMC10428543 | |
Methods | PMC10428543 | |||
Trial design | Differentiated biosocial HIV | This hybrid design trial will include a cluster randomized stepped-wedge design to assess effectiveness and a realist process evaluation to assess implementation outcomes, conducted over 45 months from 2022 to 2024 (Fig. Hybrid design 1 effectiveness implementation trial designWe will use a realist process evaluation to interrogate the extent to which the intervention components deliver according to the theory of change (Fig. Theory of change (ToC) for Differentiated biosocial HIV prevention—Social mobilization, SRH and tailored HIV | PMC10428543 | |
Study setting | This trial is embedded in the Africa Health Research Institute’s (AHRI) multidisciplinary adolescent and youth programme in AHRI’s demographic surveillance area in uMkhanyakude district in rural KZN, SA [The trial will be conducted in 40 areas (clusters) of AHRI’s surveillance area that have been purposively selected to include areas where peer navigators are working and reflect a range of rural, peri-urban and urban settings. The clusters have distinctive boundaries based on roads and rivers to minimise the risk of contamination/spill-over. | PMC10428543 | ||
Study population |
The population eligible to receive the intervention:All young people aged 15–30 years residing in 40 clusters, of whom an estimated 20% are at risk of HIV acquisition (based on our pilot work using a screening tool based on the South African national guidelines) and would benefit from PrEP, are eligible to receive the intervention.The eligible population for the evaluation:The primary outcome of the prevalence of transmissible HIV will be collected through three population-based surveys among a random sample of 16–30-year-olds who are resident in the 40 clusters: at baseline, at the end of period 1 and at the end of period 2. | PMC10428543 | ||
Study interventions | Clusters have been randomly allocated to receive the early or delayed rollout of the Thetha Nami intervention. All individuals allocated to the delayed intervention will receive standard of care in the first period of the trial. | PMC10428543 |
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