This statistic displays the distribution of caregivers in the U.S. as of 2019, by the age and status of the person they provided care for. It was found that 52 percent of caregivers provided care for a sick/ill and/or elderly adult.

Number of individuals who received a tax credit for natural caregivers and average amount paid, by age, gender and administrative region, for the 2014 to 2019 tax years, as of September 30, 2023.

The Older Persons and Informal Caregivers Survey - Minimum DataSet (TOPICS-MDS) is a public data repository which contains information on the physical and mental health and well-being of older persons and informal caregivers and their care use across the Netherlands. The database was developed at the start of The National Care for the Elderly Programme (‘Nationaal Programma Ouderenzorg’ - NPO) on behalf of the Organisation of Health Research and Development (ZonMw - The Netherlands), in part to ensure uniform collection of outcome measures, thus promoting comparability between studies.

Since September 2014, TOPICS-MDS data are also collected within the ZonMw funded ‘Memorabel’ programme, that is specifically aimed at improving the quality of life for people with dementia and the care and support provided to them. In Memorabel round 1 through 4, 11 different research projects have collected TOPICS-MDS data, which has resulted in a pooled database with cross-sectional and (partly) longitudinal data of 1,400 older persons with early onset or advanced dementia and about 950 informal caregivers. Out of these numbers, a number of 919 concerns care receiver - caregiver dyads of whom information on both the care receiver and caregiver is available.

More background information on both NPO and Memorabel 1-4 can be found in the overall information on TOPICS-MDS under the tab ‘Data files’ in DANS EASY (doi.org/10.17026/dans-xvh-dbbf).

The 'TOPICS-MDS Memorabel 1-4 caregiver’ dataset, as part of the Memorabel 1-4 database, contains no care receiver (older person) data, only informal caregiver data. The dataset includes data on age and gender of the caregiver and their relationship with the care receiver, as well as data on emotional health and well-being, quality of life, time spent on informal caregiving and caregiver burden.

Although the TOPICS-MDS survey instrument for the caregiver was updated in 2019, the same initial version of the instrument was used in both NPO and Memorabel 1-4 projects. The TOPICS-MDS caregiver data from NPO and Memorabel 1-4 can therefore be easily merged.

ABSTRACT. Due to the disruption of normal flow of treatment during the restrictions related to the coronavirus disease 2019 (COVID-19) pandemic, the health status of persons with dementia (PwD) and their caregivers’ burden might worsen. Objective: The article aims to find out the health status of PwD and caregivers’ burden during the peak of second wave of COVID-19 and make a comparison with the preceding trough phase. Methods: The study was conducted with 53 PwD and their caregivers in two phases. On their visit to the hospital during the unlock phase (phase 1), data were collected for CDR from PwD, and NPI-Q and ZBI from their caregivers. During the peak of second wave (phase 2), data were collected for NPI-Q, ZBI, and DASS-21 through telephonic communication, and statistical analyses were performed on the collected data. Results: Significantly higher caregiver burden (p=0.001) and neuropsychiatric symptoms (NPSs) [both in severity (p=0.019) and distress (p=0.013)] were observed among the respondents during the peak of second wave of the pandemic as compared to the preceding trough phase. Positive correlations were observed between the caregiver burden and depression, anxiety, and stress of the caregivers (p

Number of individuals who received a tax credit for natural caregivers and average amount paid, by age, gender and administrative region, for the 2014 to 2019 tax years, as of September 30, 2023.

IH466 - Average weekly hours of care provided by caregivers aged 18 years and older. Published by Central Statistics Office. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Average weekly hours of care provided by caregivers aged 18 years and older...

IntroductionLifestyle risk behaviors for cardiovascular disease (CVD) often co-occur. However, little is known about their co-occurrence patterns among family caregivers, a high-risk population for CVD. This study aimed to identify distinct latent classes of lifestyle risk behaviors for CVD among caregivers and to examine socio-demographic, health-related, and caregiving characteristics associated with membership in the latent classes.MethodsWe conducted a cross-sectional secondary data analysis of the 2019 Health Information National Trends Survey 5 Cycle 3, involving 643 unpaid family caregivers in the United States. The lifestyle risk behaviors for CVD included current cigarette use, current alcohol consumption, low physical activity, prolonged sedentary time, low fruit intake, and low vegetable intake, as defined by established guidelines. We performed latent class analysis to identify unobserved subgroups based on these multiple lifestyle risk behaviors. Subsequently, we conducted multinomial logistic regression to investigate socio-demographic, health-related, and caregiving characteristics associated with latent class membership.ResultsThe majority of participants were females (55.3%) and non-Hispanic white (57.1%), with a mean age of 55 ± 16 years. Three distinct classes were identified: Class 1 (Physically active caregivers, 17.1%), Class 2 (Physically inactive, healthy eaters, 18.8%), and Class 3 (Physically inactive, unhealthy eaters, 64.1%). In unadjusted models, older caregivers (≥65 years) were more likely to belong to Class 2, relative to Class 1, compared to those aged 18–49 years. Caregivers with perceived financial difficulties, psychological distress, low self-efficacy in health management, and poor sleep quality were more likely to belong to Class 3, rather than Class 1, compared to their counterparts. Additionally, dementia care and caregiving ≥ 20 h/week were significantly associated with Class 3 membership. In the adjusted model, psychological distress remained significant. Caregivers reporting psychological distress were more likely to belong to Class 3 rather than Class 1, compared to those without psychological distress.ConclusionOur findings reveal the presence of subgroups of caregivers with unique patterns of lifestyle risk behaviors, with most not meeting the recommended levels of health behaviors. Future studies should consider these co-occurring patterns along with the key factors associated with higher-risk lifestyle behavior patterns when developing interventions to promote caregivers’ cardiovascular health.

We present the analysis dataset, script, as well as the data collection forms from an evaluation of an 11-week, remote early learning program (RELP) delivered via WhatsApp calls and messages to families in areas of Lebanon with little or no access to ECE. The program was created in response to COVID-19 with a focus on Syrian refugee and vulnerable Lebanese families and tested in hard-to-access areas in order to capture impacts on those most likely to need remote ECE post-pandemic. It is shorter than typical school programming because in under-resourced, conflict-affected, and displaced settings it is not always possible to find the political will and resources, or to maintain families, for longer programming (see Bonilla et al., 2019). Thus, in seeking to provide ECE in such settings, it is critical that we understand the impact of programs that are shorter, cheaper, and potentially more scalable than full-year, in-person options. In this evaluation, we examine the impacts of both i) RELP alone and ii) RELP provided alongside a remote parenting support program (RPSP). Impacts presented are in comparison to a wait list control group who received RELP immediately following endline data collection. Analyses examine experimental impacts on child development, parenting, and caregiver well-being. The files provided include: 1) The analysis dataset titled "RELP_clean_deidentified". This dataset includes all outcome variables as well as covariates. Use "Models_dofile" to replicate the analyses. 2) The STATA .do file used to run the analyses, titled "Models_dofile" 3) The CAPI xls forms that were used to collect baseline and endline data for both the IDELA measure of child development as well as the caregiver surveys (baseline and endline) 4) The STATA .do file used to clean the data, run psychometrics and obtain outcome scores, and run the multiple imputation. This file is called "RELP_raw_to_analytic" and it is meant to provide transparency around data transformations that took place starting with the raw data and ending with the analysis dataset "RELP_clean_deidentified". 5) A pdf copy of the published pre-registration document. The study and analysis plan were pre-registered in REES (ID:13920).

Abstract

This study is a stratified cluster-randomised trial (CRT) designed to test Sugira Muryango’s effects on promoting early childhood development (ECD) and preventing violence among families receiving the VUP social protection. The data collection for the study took place between January 2018 and September 2019. The trial was conducted within the Nyanza, Ngoma, and Rubavu districts with existing VUP programmes, selected to minimize the overlap with ECD interventions by government or nongovernmental organizations. All families in this study were eligible for one of two versions of the VUP programme: classic public works (cPW), which provides cash for (typically hard) manual labour; or the newer expanded public works (ePW), which provides cash for (typically lighter) labour and also provides access to livestock. Sugira Muryango, a 12-module coaching-based parenting intervention for vulnerable families (Ubudehe 1, the most extreme level of poverty) with children aged 6-36 months in Rwanda. Sugira Muryango is designed to: 1) Increase positive parent-child interactions with both male and female caregivers; 2) Reduce intimate partner violence and harsh discipline in the home; 3) Strengthen families through conflict resolution and shared decision making; 4) Improve caregiver mental health through emotion regulation and problem solving/executive function skill building; and, 5) Improve child health via care-seeking, hygiene and improved dietary diversity.

Geographic coverage

Selected families in the districts of Rubavu, Nyanza and Ngoma.

Analysis unit

Data is collected at 3 levels of observation: the child, the caregiver, and the household. Each level of analysis has its own data file. Household_id and timepoint can be used to merge files.

Kind of data

Clinical data [cli]

Sampling procedure

Study sample size includes the following: 1.049 families in total participated in the program. This resulted in 1,498 caregivers and 1,084 children enrolled in the study.

Families’ participation in the VUP and selection into cPW and ePW is determined by governmental policies and was not under the control of the research team. Lists of families participating in the VUP program were obtained from government staff in each district.

Nonoverlapping, geographically defined clusters were created comprising at least 30 families participating in the cPW program or ten families participating in the ePW program, with some clusters containing both ≥30 cPW and ≥10 ePW households. Clusters were formed from one or more contiguous villages such that one CBV could provide services to all participating families in the cluster. Villages within the same cluster were selected to be as close to each other and as far apart from other clusters as possible. Due to the relative scarcity of the ePW families, 100% of clusters containing at least 10 ePW families were sampled for participation in the study. Clusters which contained cPW families (including combined clusters containing ePW families) were randomly sampled for inclusion into our study until we reached our target sample size of ≥1,040 households. Randomization was performed by Laterite and occurred at the cluster level within strata defined by public works type (ePW only, combined ePW/cPW, and cPW only) and geographic sector. Within strata, clusters were assigned random numbers and placed on a ranked list. The first half of clusters on the randomly ranked list were assigned to treatment. In case of an uneven number of clusters per strata, a lottery was used to round the number assigned to treatment up or down. After assignment of the cluster, households were contacted by the data collection contractor and invited to participate in the study. Clusters were retained if at least five families in the cPW strata or at least one family in the ePW strata enrolled and had at least one child aged 6–36 months. We retained 48 ePW-only clusters, 38 ePW/cPW clusters, and 112 cPW-only clusters.

Neither the families nor the enumerators who conducted the assessments knew about a family’s assignment to treatment versus control before they had completed the baseline assessment. All caregivers gave written informed consent for themselves and their eligible children ages 6–36 months.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Excel spreadsheets with detailed information about the surveys is provided (for each timepoint) as supplemental materials.

The interviews with caregivers used structured questionnaires based on validated and piloted measures. Caregivers reported on themselves and the primary caregiver (the person who self-identified as knowing the child best, usually the biological mother) also reported on the child. The primary caregiver also reported on the household.

Questionnaire measures:

Caregivers report on the Child: Questions for the caregiver regarding Child feeding practices, Child health Care seeking for child illness Child discipline [from MICS] Child development - Ages and Stages Questionnaire (ASQ)-3

Caregiver Report on Self: Completed by each primary caregiver in the study household. [If the primary caregiver had an intimate partner, the Caregiver Report on Self was completed by the intimate partner as well. Intimate partner surveys were not considered mandatory for household completion, but every attempt was made to complete this survey with both partners when applicable.] Family unity Shared decision making Early childhood development knowledge [Knowledge and Attitudes: KAP] Caregiver mental health [depression, anxiety [HSCL] and PTSD [PCL-C] Caregiver alcohol use [AUDIT] Daily hardships Intimate partner violence [from DHS]

Caregiver Report on Household: Completed by the primary caregiver in each study household or by his or her intimate partner and includes modules regarding the: Family composition Household assets Social protection Social protection program participation - VUP Access to financial institutions,health care Food security and meal frequencies Water and sanitation

Observational child measures: Home Observation for Measurement of the Environment (HOME); Observation of Mother Child Interaction (OMCI.) Malawi Development Assessment Tool (MDAT): This observation-based assessment was completed by each eligible child in the study household. Child anthropometric measurements: Measurements of weight, height or length depending on age, and mid-upper arm circumference (MUAC) were taken for each eligible child in the study household.

Response rate

Household Attrition

Between each wave of data collection, some households moved, declined to participate, or were otherwise not able to be surveyed. During field preparation, 1,062 households were drawn but only 1,054 were eligible to be surveyed at baseline. Five households moved or could not be found so the original baseline household sample was composed of 1,049 households.

At midline, 5 households moved or did not consent to participate, which represents a 0.5% attrition rate with respect to baseline data collection. At endline 8 households moved, could not be located, or did not consent to participate at endline. This represents an attrition rate of 1.2% with respect to baseline data collection and an attrition rate of 0.76% with respect to midline data collection.

Caregiver Attrition A simple attrition calculation was performed by looking at counts of the “relationship to child” category after filtering out “new caregivers” that were enrolled after the intervention began.

A total of 1498 caregivers were surveyed at baseline (63.68% Mothers, 29.57% Fathers, 6.74% other, e.g., aunt, grandparent, etc.). At midline 1462 caregivers were surveyed, which represents an attrition rate of 2.4% considering only caregivers enrolled at baseline. At endline, 1353 caregivers enrolled at baseline answered the survey. This represents an attrition rate of 9.61% with respect to baseline and 7.38% with respect to midline.

***Note: If a simple count of observation per timepoints is requested in the caregiver dataset, the number of caregivers increases from baseline to endline data collection given the inclusion of new caregivers. There are also some changes in the caregiver type (e.g. some additional caregivers became new endline primary caregivers), so attrition estimates should be interpreted with caution because they depend on several "methodological decisions".

Child Attrition 1084 children were assessed at baseline, 1078 at midline, and 1062 at endline. This yields an attrition rate of 0.55% at midline. At endline the attrition rate is 2.02% with respect to baseline and 1.48% with respect to midline.

IH468 - Average weekly hours of care provided by caregivers aged 18 years and older. Published by Central Statistics Office. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Average weekly hours of care provided by caregivers aged 18 years and older...

Background: Sepsis arises when the body’s response to an infection injures its own tissues and organs. Among children hospitalized with suspected sepsis in low-income country settings, mortality rates following discharge are high, similar to mortality rates in hospital. The Smart Discharges Program uses a mobile health (mHealth) platform to identify children at high risk of post-discharge mortality to receive enhanced post-discharge care. This study sought to explore the perceptions and experiences of the caregivers and nurses of children enrolled into the Smart Discharges Program and the program’s effect on post-discharge care. Methods: We conducted an exploratory qualitative study, which included in-person focus group discussions (FGDs) with 30 caregivers of pediatric patients enrolled in the Smart Discharges Program and individual, semi-structured interviews with eight Smart Discharges Program nurses. The study was carried out at four hospitals in Uganda in 2019. Findings: Following thematic analysis, three key themes pertaining to the Smart Discharges program were identified: (1) Facilitators and barriers to follow-up care after discharge; (2) Changed caregiver behavior following discharge; and (3) Increased involvement of male caregivers. Facilitators included telephone/text message reminders, positive nurse-patient relationship, and the complementary aspects of the program. Barriers included resource constraints and negative experiences during post-discharge care seeking. With regards to behavior, when provided with relevant and well-timed information, caregivers reported increased knowledge about post-discharge care and improvements in their ability to care for their child. Enrolment in the Smart Discharges Program also increased male caregiver involvement, increased provision of resources and improved communication within the family and with the healthcare system. The Smart Discharges approach is an impactful strategy to improve pediatric post-discharge care, and similar approaches should be considered to improve the hospital to home transition in similar low-income country settings. Data Collection Methods: Facilitators of the same sex as the participants moderated the FGDs in the local language. Individual interviews with nurses were conducted by a social scientist in English. A focus group discussion guide and a semi-structured interview guide were used to provide structure and consistency to the discussion/interviews while allowing for novel concepts to be shared. Topics in the interview and FGD guides were developed by senior investigators who have expertise in the field of pediatric sepsis. The FDG guides focused on experiences at the admitting facility, experiences after discharge, processes involving referral for post-discharge clinical care, and barriers to post-discharge care. Interview guides focused on the experience of providing caregiver education and counselling, and reporting of which programmatic components worked well and did not work well. Nurse interviewees were also asked about their observations of the benefits and challenges of the program to the caregivers. Due to budget and logistical constraints, the FGD and interview guides were not pre-tested prior to use and no repeat interviews were done. FGDs and interviews were audio recorded and transcribed directly in English by a professional translator and then reviewed for accuracy and consistency. Using a thematic analysis approach, initial open coding of transcripts was done by two investigators. During analysis, data was organized using NVivo version 12.0 (QSR, Massachusetts, United States). After development of the coding framework and initial coding, themes were proposed, and discussed between three investigators who jointly agreed on the study themes and then confirmed full team agreement on the final themes. Ethics Declaration: Ethical approval was obtained from the the Makerere University School of Public Health, Research and Ethics Committee (SPH-REC # 691) and the Uganda National Council for Science and Technology (UNCST SS #5047). NOTE for restricted files: If you are not yet a CoLab member, please complete our membership application survey to gain access to restricted files within 2 business days. Some files may remain restricted to CoLab members. These files are deemed more sensitive by the file owner and are meant to be shared on a case-by-case basis. Please contact the CoLab coordinator at sepsiscolab@bcchr.ca or visit our website.

Graph and download economic data for All Employees, Nursing and Residential Care Facilities (CEU6562300001) from Jan 1990 to Jun 2025 about nursing homes, nursing, health, establishment survey, residential, education, services, employment, and USA.

The dataset contains all data extractions (CMO configurations) and following data analysis used for the research described by Thijssen and collegues.The paper describes and explains the outcomes of community dementia friendly initiatives (DFIs) for people with dementia and their caregivers to inform the development and tailoring of DFIs. DFIs are activities that aim to promote dignity, empowerment, engagement and autonomy to enable the wellbeing of people with dementia and the needs of their caregivers throughout the dementia trajectory. A rapid realist review review was conducted between April 2018 and November 2019. The description of the methodology reports the data extraction and data synthesis. The first file of each category presents an overview of the data extraction (all CMO configurations) The next files of each category are numbered referring to the steps of the data synthesis. Rapid realist review

These data were generated as part of an ESRC-funded research project examining the impact of the COVID-19 crisis on U.K. family home environments, including children’s health, psychological wellbeing, eating, physical activity and sedentary behaviours. The data include caregiver reported information provided as part of the telephone-administered Home Environment Interview (HEI) and child-reported questionnaire data. The HEI and child questionnaires were completed in three phases: T1 (November 2019 - March 2020), T2 (August 2020-March 2021) and T3 (April 2021-October 2021).

IH467 - Average weekly hours of care provided by caregivers aged 18 years and older. Published by Central Statistics Office. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Average weekly hours of care provided by caregivers aged 18 years and older...

The global Dementia Care APP market is expected to grow at a Compound Annual Growth Rate (CAGR) of 4.8% for the forecast period 2023-2030. The Driving Factor of the Dementia Care APP Market

Rising number of geriatric populations

The rising number of geriatric populations worldwide is a demographic trend characterized by an increasing proportion of elderly individuals within the global population. Advances in healthcare, nutrition, and medical technology have led to significant increases in life expectancy. People are living longer due to better disease management, improved access to healthcare, and healthier lifestyles. In many Western countries, the post-World War II baby boomer generation is now reaching old age. This generation represents a significant portion of the population, and as they age, they contribute to the growing elderly population. The rising number of geriatric populations has a significant influence on the demand for dementia care products and services as diseases like Alzheimer's is more common among older adults.

According to the World Health Organization

by 2030, 1 in 6 people in the world will be aged 60 years or over. At this time the share of the population aged 60 years and over will increase from 1 billion in 2020 to 1.4 billion. By 2050, the world’s population of people aged 60 years and older will double (2.1 billion). The number of persons aged 80 years or older is expected to triple between 2020 and 2050 to reach 426 million.

Between 2015 and 2050, the proportion of the world's population over 60 years will nearly double from 12% to 22%.

The increasing prevalence of dementia such as Alzheimer's disease and other forms

The increasing prevalence of dementia, including Alzheimer's disease and other forms of dementia, can be attributed to a combination of demographic, lifestyle, and medical factors. Alzheimer's disease is the most common cause of dementia, accounting for a significant portion of dementia cases. As the population ages, the number of individuals developing Alzheimer's disease also increases. In addition, chronic health conditions such as diabetes, hypertension, and cardiovascular disease have been associated with an increased risk of dementia. The prevalence of these conditions has risen in many parts of the world, contributing to a higher dementia risk.

Based on the data of 2019 Global Burden of Disease (GBD) database, globally, the incidence of Alzheimer's disease and other dementias increased by 147.95% from 1990 to 2019, with 2.92 million cases in 1990 and 7.24 million cases in 2019.

(Source:Frontiers Media)

According to the Statista report, in 2020, it was estimated that around 6.1 million people aged 65 years and older suffered from Alzheimer's disease, with this figure expected to grow to 8.5 million by the year 2030.

Market Dynamics of Dementia Care APP

Limited awareness

Many potential users, especially older adults and their caregivers, may not be aware of the existence or benefits of dementia care apps. In addition, elderly people are resistant for adopting new technology as some dementia care apps may be too complex for elderly individuals or their caregivers to use effectively.

In April 2012 the Pew Research Centre found for the first time that more than half of older adults (defined as those ages 65 or older) were internet users. However, many seniors continue to lag behind younger Americans when it comes to tech adoption. In addition, large number of seniors remain largely unattached from online and mobile life; for instance, 41% do not use the internet at all, 53% do not have broadband access at home, and 23% do not use cell phones.

Integration with of Dementia Care APP with Wearable Devices

There is a growing demand for dementia care apps due to the increasing prevalence of dementia and the desire to improve the quality of life for both patients and caregivers. Dementia care apps were becoming more tailored to individual patient needs. With technology development, integration of these apps with wearable devices and sensors was on the rise. These devices can monitor vital signs, track movements, and provide data for better caregiving and safety.

For instance; the Theora Connect is a smartwatch designed to be used by older adults — especially those with mild cognitive impairment or dementia. Theora Connect™ ...

Snapshot img

Behavioral Health Software Market Size 2025-2029

The behavioral health software market size is forecast to increase by USD 3.42 billion at a CAGR of 16.4% between 2024 and 2029.

The market is experiencing significant growth, driven by the increasing adoption of Electronic Health Records (EHRs) in mental and behavioral health care. EHRs offer numerous benefits, including streamlined patient data management, improved care coordination, and enhanced clinical workflows. This trend is expected to continue as healthcare providers recognize the importance of digital solutions in delivering efficient and effective care. The shift towards telehealth and remote care has gained momentum due to the COVID-19 pandemic, enabling providers to reach patients in need from the comfort of their homes.
This trend is likely to persist post-pandemic, as patients appreciate the convenience and accessibility of virtual care. Another key trend shaping the market is the emergence of virtual behavioral and mental health services. However, the market also faces challenges, including concerns about the security of patient data and the threat of cyberattacks. With the growing digitization of healthcare, protecting sensitive patient information has become a top priority. Providers must invest in robust cybersecurity measures to safeguard their systems and maintain patient trust. Additionally, ensuring compliance with various data privacy regulations, such as HIPAA, adds to the complexity of managing behavioral health software systems.

What will be the Size of the Behavioral Health Software Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The market is experiencing significant growth, driven by the adoption of technology to enhance patient engagement and improve provider efficiency. System usability and user satisfaction are key factors influencing this trend, as providers seek to streamline operations and increase practice revenue. Data-driven insights derived from analytics enable better communication between caregivers, improved patient outcomes, and reduced hospitalizations. Insurance verification and payment processing are also important features, ensuring smooth workflows and resource allocation. Provider collaboration, outcome measurement, and staff management are essential for effective treatment plan management and performance metrics.

Scheduling optimization and data visualization tools further enhance staff satisfaction and enable more effective caregiver communication. Overall, the market is focused on delivering solutions that optimize clinical workflows, facilitate progress tracking, and provide valuable data insights to improve patient care. Companies seeking to capitalize on market opportunities must address these challenges effectively, while also staying abreast of emerging trends and technologies to remain competitive. The increasing adoption of electronic health records (EHRs) in healthcare services is driving the demand for advanced eHealth software and services, including those focused on mental health.

How is this Behavioral Health Software Industry segmented?

The behavioral health software industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Component

  Software
  Support services


End-user

  Providers
  Payers
  Patients


Deployment

  Cloud-based
  On-premises


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    Spain
    UK


  APAC

    China
    India
    Japan


  Rest of World (ROW)

By Component Insights

The software segment is estimated to witness significant growth during the forecast period. The market is experiencing significant growth due to the increasing prevalence of mental health issues, such as depression, stress, anxiety, substance abuse, and addiction. Customizable software solutions enable personalized treatment plans based on clinical evidence and patient records, including Electronic Medical Records (EMRs). Telehealth capabilities and the widespread adoption of smartphones are further fueling the market's expansion. Integration of Artificial Intelligence (AI) and machine learning into behavioral health platforms facilitates real-time monitoring, predictive analytics, and personalized care pathways. Cloud-based solutions are increasingly popular due to their scalability, cost-effectiveness, and remote accessibility, particularly among small and mid-sized practices.

Customizable workflows, compliance monitoring, integration services, and regulatory compliance are essential features that enhance the functionality of these softwar

This data asset contains the data from the baseline, midline, and endline data collection for an impact evaluation of the Makhalidwe Athu project (MA), an 18-month intervention aimed at improving the reading skills of 1,200 students in 2nd and 3rd grades in the Chipata and Lundazi districts of Zambia’s Eastern province. Baseline data were collected between November 2015 and January 2016, and endline data collection occurred in January 2017. To collect data, NORC fielded a parent/caregiver survey, a student survey, and an Early Grade Reading Assessment (EGRA) at baseline and endline. In addition, in June 2016 a midline survey on a subsample of treatment caregivers was fielded to document program uptake. To construct the sample frame, Advanced Teams of enumerators were sent to the field to survey all students in 1st and 2nd grades in 80 sampled schools and ask if anyone in their home had a cell phone, which was a requirement to participate in the study. The caregiver survey was developed by NORC and INESOR, and was intended to determine the respondent’s eligibility to participate in the study and to assess the home literacy environment and household assets. The student questionnaire assessed student reading practices at home and in school. The EGRA includes five tasks that measure the following capacities: Orientation to Print, Letter Sound Identification, Non-Word Reading, Oral Reading Passage, Reading Comprehension, and Listening Comprehension. In total 1,942 caregivers, corresponding to 2,019 children, were surveyed at baseline and endline: 965 in the treatment group and 977 in the control group.

Informal care time in mean hours per caregiver per week.

Snapshot img

Dementia And Movement Disorder Treatment Market Size 2025-2029

The dementia and movement disorder treatment market size is forecast to increase by USD 14.43 billion at a CAGR of 9% between 2024 and 2029.

The market is experiencing significant growth, driven primarily by the increasing geriatric population, who are more susceptible to these neurological conditions. As the global population ages, the prevalence of neurological disorders such as dementia and movement disorders is rising, creating a substantial demand for effective treatments. A second key driver is the emergence of biomarkers, which are revolutionizing the diagnosis and treatment of these conditions. However, the high cost of neurological disorders treatment poses a significant challenge for both patients and healthcare systems. Despite this, opportunities exist for companies to innovate and develop more affordable and effective treatments, particularly through the use of advanced technologies and personalized medicine approaches.
Navigating this complex market requires a deep understanding of the latest research and development trends, as well as a strategic approach to addressing the challenges of cost and accessibility. Companies seeking to capitalize on these opportunities must stay abreast of the latest scientific advancements and regulatory developments, while also building strong partnerships with key stakeholders in the healthcare ecosystem. Gene therapy and drug therapy are emerging as promising treatments for various neurological conditions, including spinal muscular atrophy and multiple sclerosis.

What will be the Size of the Dementia And Movement Disorder Treatment Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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Diagnostic imaging plays a crucial role in early diagnosis and disease management, enabling healthcare providers to develop personalized treatment plans for patients. The market encompasses a range of interventions aimed at managing cognitive decline and motor impairments. Cognitive assessment plays a crucial role in diagnosing and monitoring disease progression, while end-of-life care focuses on improving the quality of life for patients and their families. Treatment guidelines prioritize a multidisciplinary approach, incorporating lifestyle modifications, ethical considerations, and psychosocial support. Communication aids and behavioral interventions are essential for maintaining patient engagement and enhancing caregiver communication. Speech difficulties, a prevalent issue in conditions such as Huntington's disease and Parkinson's disease, are being addressed through speech therapy and cognitive rehabilitation. Cerebrospinal fluid analysis and genetic testing offer insights into disease mechanisms, informing personalized treatment plans. Brain imaging techniques, such as PET scans and MRI scans, facilitate early diagnosis and functional capacity assessment.
Cholinesterase inhibitors and NMDA receptor antagonists represent pharmacological interventions, while brain imaging, adaptive equipment, environmental modifications, and remote monitoring enable non-pharmacological approaches. Prevention strategies, including caregiver burden reduction and economic impact mitigation, are vital for addressing the social and economic consequences of these disorders. Ethical considerations and social impact are increasingly important in the context of dementia and movement disorder treatment, as the global population ages and the burden on healthcare systems grows. The market is characterized by ongoing research and innovation, with a focus on improving patient outcomes and enhancing caregiver support.

How is this Dementia And Movement Disorder Treatment Industry segmented?

The dementia and movement disorder treatment industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Application

  Movement disorders
  Progressive dementia
  Progressive dementia with neurological abnormality (PDNA)


Drug Class

  MAO inhibitors
  Acetylcholinesterase inhibitors
  Glutamate inhibitors
  Others


Distribution Channel

  Hospital pharmacies
  Retail pharmacies
  Online pharmacies


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    Spain
    UK


  APAC

    China
    India
    Japan


  Rest of World (ROW)

By Application Insights

The movement disorders segment is estimated to witness significant growth during the forecast period. Movement disorders, including conditions such as balance problems, Parkinson's disease, Huntington's disease, spinal muscular atrophy, multiple sclerosis, c